From 43a3f5802944f1c5c68d93b651eeb973825e94b6 Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Thu, 20 Feb 2025 16:24:24 -0800
Subject: [PATCH 01/55] Fix variable name and runtime error

---
 spisea/imf/imf.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 758eda00..4380e012 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -280,10 +280,10 @@ def __init__(self, mass_limits, powers, multiplicity=None):
         if len(mass_limits) != len(powers) + 1:
             msg = 'Incorrect specification of multi-part powerlaw.\n'
             msg += '    len(massLimts) != len(powers)+1\n'
-            msg += '    len(massLimits) = \n' + len(massLimits)
+            msg += '    len(massLimits) = \n' + len(mass_limits)
             msg += '    len(powers) = \n' + len(powers)
 
-            raise RuntimeException(msg)
+            raise RuntimeError(msg)
 
         self._mass_limits = np.atleast_1d(mass_limits)
         self._m_limits_low = mass_limits[0:-1]

From e88571fddc07792b7986e81f79e70b95c8a7a2ac Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Sat, 26 Apr 2025 16:26:53 -0700
Subject: [PATCH 02/55] Add random generator support

---
 spisea/imf/imf.py | 197 ++++++++++++++++++++++------------------------
 1 file changed, 92 insertions(+), 105 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 4380e012..bc4ff564 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -47,19 +47,21 @@ class IMF(object):
         If None, no multiplicity is assumed. Otherwise, use 
         multiplicity object to create multiple star systems.
     """
-    def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None):
+    def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None):
         self._multi_props = multiplicity
-        self._mass_limits = massLimits
-
-        if multiplicity == None:
-            self.make_multiples = False
-        else:
+        self._mass_limits = np.atleast_1d(massLimits)
+        self.seed = seed
+        self.rng = np.random.default_rng(seed)
+        
+        if multiplicity:
             self.make_multiples = True
+        else:
+            self.make_multiples = False
  
         return
             
 
-    def generate_cluster(self, totalMass, seed=None):
+    def generate_cluster(self, totalMass):
         """
         Generate a cluster of stellar systems with the specified IMF.
         
@@ -113,22 +115,19 @@ def generate_cluster(self, totalMass, seed=None):
         # Generate output arrays.
         masses = np.array([], dtype=float)
         isMultiple = np.array([], dtype=bool)
-        compMasses = np.array([], dtype=object)
+        # compMasses = {} # Hashmap for index -> compMasses for faster lookup
+        compMasses = []
         systemMasses = np.array([], dtype=float)
 
         # Loop through and add stars to the cluster until we get to
         # the desired total cluster mass.
         totalMassTally = 0
         loopCnt = 0
-
-        # Set the random seed, if desired
-        if seed:
-            np.random.seed(seed=seed)
         
+        # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
-            uniX = np.random.rand(int(newStarCount))
-
+            uniX = self.rng.random(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
             
@@ -136,33 +135,31 @@ def generate_cluster(self, totalMass, seed=None):
             test = np.isnan(newMasses)
             if np.sum(test) > 0:
                 raise ValueError('Nan detected in cluster mass')
-                
+            
             # Dealing with multiplicity
-            if self._multi_props != None:
-                newCompMasses = np.empty((len(newMasses),), dtype=object)
-                newCompMasses.fill([])
-                
+            if self._multi_props:
+                # newCompMasses = np.empty((len(newMasses),), dtype=object)
+                # newCompMasses.fill([])
                 # Determine the multiplicity of every star
                 MF = self._multi_props.multiplicity_fraction(newMasses)
                 CSF = self._multi_props.companion_star_fraction(newMasses)
-                
-                newIsMultiple = np.random.rand(int(newStarCount)) < MF
 
-                # Copy over the primary masses. Eventually add the companions.
-                newSystemMasses = newMasses.copy()
+                newIsMultiple = self.rng.random(int(newStarCount)) < MF
 
                 # Function to calculate multiple systems more efficiently
-                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newCompMasses,
-                                                                                newSystemMasses, newIsMultiple,
-                                                                                CSF, MF)
-
+                # start_calc = time.time()
+                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newIsMultiple, CSF, MF)
+                # end_calc = time.time()
+                # print('Time taken for calc_multi: ', end_calc - start_calc)
                 newTotalMassTally = newSystemMasses.sum()
                 isMultiple = np.append(isMultiple, newIsMultiple)
                 systemMasses = np.append(systemMasses, newSystemMasses)
-                compMasses = np.append(compMasses, newCompMasses)
+                compMasses.append(newCompMasses)
+
             else:
                 newTotalMassTally = newMasses.sum()
-
+            # end_while = time.time()
+            # print('Time taken for while loop: ', end_while - start_while)
             # Append to our primary masses array
             masses = np.append(masses, newMasses)
             
@@ -176,6 +173,25 @@ def generate_cluster(self, totalMass, seed=None):
         
         # Make a running sum of the system masses
         if self._multi_props:
+            # Concatenate the companion masses
+            if len(compMasses) > 1:
+                max_cols = max(compMass.shape[1] for compMass in compMasses)
+                
+                # Pad each array to have the same number of columns
+                padded_arrays = [
+                    np.ma.masked_all((compMass.shape[0], max_cols)) for compMass in compMasses
+                ]
+                
+                for i, compMass in enumerate(compMasses):
+                    padded_arrays[i][:, :compMass.shape[1]] = compMass
+                
+                # Vertically stack the padded arrays
+                compMasses = np.ma.vstack(padded_arrays)
+            
+            else:
+                compMasses = compMasses[0]
+            
+            # Make a running sum of the system masses
             massCumSum = systemMasses.cumsum()
         else:
             massCumSum = masses.cumsum()
@@ -196,60 +212,39 @@ def generate_cluster(self, totalMass, seed=None):
 
         return (masses, isMultiple, compMasses, systemMasses)
         
-    def calc_multi(self, newMasses, compMasses, newSystemMasses, newIsMultiple, CSF, MF):
+    def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
         """
         Helper function to calculate multiples more efficiently.
         We will use array operations as much as possible
         """
-        # Identify multiple systems, calculate number of companions for
-        # each 
-        idx = np.where(newIsMultiple == True)[0]
-        n_comp_arr = 1 + np.random.poisson((CSF[idx] / MF[idx]) - 1)
-        if self._multi_props.companion_max == True:
-            too_many = np.where(n_comp_arr > self._multi_props.CSF_max)[0]
-            n_comp_arr[too_many] = self._multi_props.CSF_max
-        primary = newMasses[idx]
+        # Copy over the primary masses. Eventually add the companions.
+        newSystemMasses = newMasses.copy()
+        
+        # Identify multiple systems, calculate number of companions for each 
+        multiple_idx = np.where(newIsMultiple)[0]
+        comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
+        if self._multi_props.companion_max:
+            too_many = np.where(comp_nums > self._multi_props.CSF_max)[0]
+            comp_nums[too_many] = self._multi_props.CSF_max
+        primary = newMasses[multiple_idx]
 
         # We will deal with each number of multiple system independently. This is
         # so we can put in uniform arrays in _multi_props.random_q.
-        num = np.unique(n_comp_arr)
-        for ii in num:
-            tmp = np.where(n_comp_arr == ii)[0]
-            
-            if ii == 1:
-                # Single companion case
-                q_values = self._multi_props.random_q(np.random.rand(len(tmp)))
-                
-                # Calculate mass of companion
-                m_comp = q_values * primary[tmp]
-
-                # Only keep companions that are more than the minimum mass. Update
-                # compMasses, newSystemMasses, and newIsMultiple appropriately 
-                good = np.where(m_comp >= self._mass_limits[0])[0]
-                for jj in good:
-                    compMasses[idx[tmp[jj]]] = np.transpose([m_comp[jj]])
-                    newSystemMasses[idx[tmp[jj]]] += compMasses[idx[tmp[jj]]]
-
-                bad = np.where(m_comp < self._mass_limits[0])[0]
-                newIsMultiple[idx[tmp[bad]]] = False                
-            else:
-                # Multple companion case
-                q_values = self._multi_props.random_q(np.random.rand(len(tmp), ii))
-
-                # Calculate masses of companions
-                m_comp = np.multiply(q_values, np.transpose([primary[tmp]]))
-
-                # Update compMasses, newSystemMasses, and newIsMultiple appropriately
-                for jj in range(len(tmp)):
-                    m_comp_tmp = m_comp[jj]
-                    compMasses[idx[tmp[jj]]] = m_comp_tmp[m_comp_tmp >= self._mass_limits[0]]
-                    newSystemMasses[idx[tmp[jj]]] += compMasses[idx[tmp[jj]]].sum()
-
-                    # Double check for the case when we drop all companions.
-                    # This happens a lot near the minimum allowed mass.
-                    if len(compMasses[idx[tmp[jj]]]) == 0:
-                        newIsMultiple[idx[tmp[jj]]] = False
-
+        comp_unique = np.unique(comp_nums)
+        comp_indices = [np.where(comp_nums == i)[0] for i in comp_unique]
+        compMasses = np.zeros((len(newMasses), max(comp_unique)))
+        
+        for comp_num, comp_index in zip(comp_unique, comp_indices):
+            # Calculate masses of companions
+            q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
+            m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
+            compMasses[multiple_idx[comp_index], :comp_num] = m_comp
+        
+        # Mask out companions that are less than the minimum mass
+        compMasses = np.ma.MaskedArray(compMasses, mask=compMasses < self._mass_limits[0])
+        newSystemMasses[multiple_idx] += compMasses[multiple_idx].sum(axis=1)
+        newIsMultiple = np.any(~compMasses.mask, axis=1)
+        
         return compMasses, newSystemMasses, newIsMultiple
         
     
@@ -258,7 +253,7 @@ class IMF_broken_powerlaw(IMF):
     Initialize a multi-part power-law with N parts. Each part of the
     power-law is described with a probability density function:
 
-        P(m) \propto m ** power[n]
+        P(m) ∝ m ** power[n]
 
     for mass_limits[n] < m <= mass_limits[n+1].
 
@@ -276,7 +271,9 @@ class IMF_broken_powerlaw(IMF):
         If None, no multiplicity is assumed. Otherwise, use 
         multiplicity object to create multiple star systems.
     """
-    def __init__(self, mass_limits, powers, multiplicity=None):
+    def __init__(self, mass_limits, powers, multiplicity=None, seed=None):
+        super().__init__(massLimits=mass_limits, multiplicity=multiplicity, seed=seed)
+        powers = np.atleast_1d(powers)
         if len(mass_limits) != len(powers) + 1:
             msg = 'Incorrect specification of multi-part powerlaw.\n'
             msg += '    len(massLimts) != len(powers)+1\n'
@@ -284,17 +281,10 @@ def __init__(self, mass_limits, powers, multiplicity=None):
             msg += '    len(powers) = \n' + len(powers)
 
             raise RuntimeError(msg)
-
-        self._mass_limits = np.atleast_1d(mass_limits)
+        mass_limits = np.atleast_1d(mass_limits)
         self._m_limits_low = mass_limits[0:-1]
         self._m_limits_high = mass_limits[1:]
-        self._powers = powers
-        self._multi_props = multiplicity
-
-        if multiplicity == None:
-            self.make_multiples = False
-        else:
-            self.make_multiples = True
+        self._powers = np.atleast_1d(powers)
 
         # Calculate the coeffs to make the function continuous
         nterms = len(self._powers)
@@ -595,23 +585,23 @@ def dice_star_cl(self, r):
         r = np.atleast_1d(r)  # Make sure it is an array
 
         x = r * self.lamda[-1] 
-        y = np.zeros(len(r), dtype=float)
-        z = np.ones(len(r), dtype=float)
+        y = np.zeros_like(r)
+        z = np.ones_like(r)
 
         # Loop through the different parts of the power law.
         for i in range(self.nterms): #-----For i = 0 --> n, where n is the number of intervals
             aux = x - self.lamda[i] #---Should this be i - 1?
             
             # Only continue for those entries that are in later segments
-            idx = np.where(aux >= 0)[0]
+            idx = aux >= 0
 
             # Maybe we are all done?
-            if len(idx) == 0:
+            if sum(idx) == 0:
                 break
             
             x_tmp = x[idx]
             aux_tmp = aux[idx]
-
+            
             t1 = aux_tmp / (self.coeffs[i] * self.k)
             t1 += prim_power(self._m_limits_low[i], self._powers[i])
             y_i = gamma_closed(x_tmp, self.lamda[i], self.lamda[i+1])
@@ -711,10 +701,10 @@ def prim_power(m, power):
         power = np.repeat(power, len(m))
 
     z = 1.0 + power
-    val = (m**z) / z
-        
-    val[power == -1] = np.log(m[power == -1])
-
+    val = np.empty_like(m)
+    valid_idx = power != -1
+    val[valid_idx] = (m[valid_idx]**z[valid_idx]) / z[valid_idx]
+    val[~valid_idx] = np.log(m[~valid_idx])
     
     if returnFloat:
         return val[0]
@@ -737,17 +727,14 @@ def inv_prim_power(x, power):
         power = np.repeat(power, len(x))
 
     if x.shape != power.shape:
-        pdb.set_trace()
+        raise ValueError('spisea.imf.inv_prim_power: Dimension mismatch, x and power must have the same shape')
     
     z = 1.0 + power
-    val = (z * x)**(1.0 / z)
-
-    #--------------BUG CHECK---------------------#
-    # This line doesn't make sense if x is an N-element array and
-    # power is just a 1-element array, which it appears to be for
-    # imf.generate_cluster
-    val[power == -1] = np.exp(x[power == -1])
-    #-----------------------------------------------#
+    val = np.empty_like(x)
+    valid_idx = power != -1
+    val[valid_idx] = (z[valid_idx] * x[valid_idx])**(1.0 / z[valid_idx])
+    val[~valid_idx] = np.exp(x[~valid_idx])
+
     if returnFloat:
         return val[0]
     else:

From fd875c553c6f530c5dae72ff99496866ed06eb8f Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Sat, 26 Apr 2025 16:28:54 -0700
Subject: [PATCH 03/55] Suppress divided by zero warnings

---
 spisea/ifmr.py | 101 ++++++++++++++++++++++++++-----------------------
 1 file changed, 53 insertions(+), 48 deletions(-)

diff --git a/spisea/ifmr.py b/spisea/ifmr.py
index f88afdbe..2b67ca7c 100755
--- a/spisea/ifmr.py
+++ b/spisea/ifmr.py
@@ -25,8 +25,9 @@
 import numpy as np
 
 class IFMR(object):
-    def __init__(self):
-        pass
+    def __init__(self, seed=None):
+        self.seed = seed
+        self.rng = np.random.default_rng(seed)
 
     def get_Z(self, Fe_H):
         """
@@ -48,11 +49,9 @@ def Kalirai_mass(self, MZAMS):
 
         final = np.zeros(len(MZAMS))
         
-        bad_idx = np.where(MZAMS < 0.5)
-        final[bad_idx] = -99
-        
-        good_idx = np.where(MZAMS >= 0.5)
+        good_idx = MZAMS >= 0.5
         final[good_idx] = result[good_idx]
+        final[~good_idx] = -99
 
         return final
         
@@ -730,7 +729,7 @@ def NS_mass(self, MZAMS):
         Kiziltan et al. (2010).
         
         """
-        return np.random.normal(loc=1.36, scale=0.09, size=len(MZAMS))
+        return self.rng.normal(loc=1.36, scale=0.09, size=len(MZAMS))
 
     def generate_death_mass(self, mass_array):
         """
@@ -772,7 +771,7 @@ def generate_death_mass(self, mass_array):
         output_array = np.zeros((2, len(mass_array)))
 
         #Random array to get probabilities for what type of object will form
-        random_array = np.random.randint(1, 1001, size = len(mass_array))
+        random_array = self.rng.intergers(1, 1001, size = len(mass_array))
 
         codes = {'WD': 101, 'NS': 102, 'BH': 103}
         
@@ -893,9 +892,9 @@ def NS_mass(self, MZAMS):
         
         """
         if isinstance(MZAMS, np.ndarray):
-            return np.random.normal(loc=1.36, scale=0.09, size=len(MZAMS))
+            return self.rng.normal(loc=1.36, scale=0.09, size=len(MZAMS))
         else:
-            return np.random.normal(loc=1.36, scale=0.09, size=1)[0]
+            return self.rng.normal(loc=1.36, scale=0.09, size=1)[0]
  
  
     def BH_mass_low(self, MZAMS):
@@ -914,8 +913,7 @@ def BH_mass_high(self, MZAMS, Z):
         # Solar metallicity (what Sam is using)
         Zsun = 0.014
         
-        zfrac = Z/Zsun
-
+        zfrac = np.atleast_1d(Z/Zsun)
         # super-solar Z gives identical results as solar Z
         above_idx = np.where(zfrac > 1)
         if len(above_idx) > 1:
@@ -938,15 +936,14 @@ def prob_BH_high(self, Z):
         # Solar metallicity (what Sam is using)
         Zsun = 0.014
         
-        zfrac = Z/Zsun
+        Z = np.atleast_1d(Z)
+        # Convert from [Fe/H] to Z
+        zfrac = Z / Zsun
         
         # super-solar Z gives identical results as solar Z
-        if zfrac > 1:
-            zfrac = 1.0
-
-        if zfrac < 0:
-            raise ValueError('Z must be non-negative')
-
+        zfrac[zfrac > 1] = 1.0
+        zfrac[zfrac < 0] = np.nan
+        
         pBH = 1 - 0.8*zfrac
 
         return pBH
@@ -985,75 +982,83 @@ def generate_death_mass(self, mass_array, metallicity_array):
         """
         #output_array[0] holds the remnant mass
         #output_array[1] holds the remnant type
+        mass_array = np.atleast_1d(mass_array)
+        metallicity_array = np.atleast_1d(metallicity_array)
+        
         output_array = np.zeros((2, len(mass_array)))
 
         codes = {'WD': 101, 'NS': 102, 'BH': 103}
 
+
         # Array to store the remnant masses
-        rem_mass_array = np.zeros(len(mass_array))
+        # rem_mass_array = np.zeros(len(mass_array))
 
         # Convert from [Fe/H] to Z
         # FIXME: if have Fe/H = nan that makes Z = 0. Is that the behavior we want?
         Z_array = np.zeros((len(metallicity_array)))
-        metal_idx = np.where(metallicity_array != np.nan)
+        metal_idx = ~np.isnan(metallicity_array)
         Z_array[metal_idx] = self.get_Z(metallicity_array[metal_idx])
 
         # Random array to get probabilities for what type of object will form
-        random_array = np.random.randint(1, 101, size = len(mass_array))
+        random_array = self.rng.integers(1, 101, size=len(mass_array))
 
-        id_array0 = np.where((mass_array < 0.5) | (mass_array >= 120))
-        output_array[0][id_array0] = -99 * np.ones(len(id_array0))
-        output_array[1][id_array0]  = -1 * np.ones(len(id_array0))
+        id_array0 = (mass_array < 0.5) | (mass_array >= 120)
+        output_array[0][id_array0] = -99
+        output_array[1][id_array0]  = -1
 
-        id_array1 = np.where((mass_array >= 0.5) & (mass_array < 9))
+        id_array1 = (mass_array >= 0.5) & (mass_array < 9)
         output_array[0][id_array1] = self.Kalirai_mass(mass_array[id_array1])
         output_array[1][id_array1]= codes['WD']
 
-        id_array2 = np.where((mass_array >= 9) & (mass_array < 15))
+        id_array2 = (mass_array >= 9) & (mass_array < 15)
         output_array[0][id_array2] = self.NS_mass(mass_array[id_array2])
         output_array[1][id_array2] = codes['NS']
 
-        id_array3_BH = np.where((mass_array >= 15) & (mass_array < 21.8) & (random_array > 75))
+        id_array3_BH = (mass_array >= 15) & (mass_array < 21.8) & (random_array > 75)
         output_array[0][id_array3_BH] = self.BH_mass_low(mass_array[id_array3_BH])
         output_array[1][id_array3_BH] = codes['BH']
 
-        id_array3_NS = np.where((mass_array >= 15) & (mass_array < 21.8) & (random_array <= 75))
+        id_array3_NS = (mass_array >= 15) & (mass_array < 21.8) & (random_array <= 75)
         output_array[0][id_array3_NS] = self.NS_mass(mass_array[id_array3_NS])
         output_array[1][id_array3_NS] = codes['NS']
 
-        id_array4 = np.where((mass_array >= 21.8) & (mass_array < 25.2))
+        id_array4 = (mass_array >= 21.8) & (mass_array < 25.2)
         output_array[0][id_array4] = self.BH_mass_low(mass_array[id_array4])
         output_array[1][id_array4] = codes['BH']
 
-        id_array5 = np.where((mass_array >= 25.2) & (mass_array < 27.4))
+        id_array5 = (mass_array >= 25.2) & (mass_array < 27.4)
         output_array[0][id_array5] = self.NS_mass(mass_array[id_array5])
         output_array[1][id_array5] = codes['NS']
 
-        id_array6 = np.where((mass_array >= 27.4) & (mass_array < 39.6))
+        id_array6 = (mass_array >= 27.4) & (mass_array < 39.6)
         output_array[0][id_array6] = self.BH_mass_low(mass_array[id_array6])
         output_array[1][id_array6] = codes['BH']
 
-        id_array7 = np.where((mass_array >= 39.6) & (mass_array < 60))
+        id_array7 = (mass_array >= 39.6) & (mass_array < 60)
         output_array[0][id_array7] = self.BH_mass_high(mass_array[id_array7],
                                                        Z_array[id_array7])
         output_array[1][id_array7] = codes['BH']
 
-        id_array8 = np.where((mass_array >= 60) & (mass_array < 120))
-        for i in range(0, len(id_array8[0])):
-            pBH = self.prob_BH_high(Z_array[id_array8][i])
-            if random_array[id_array8][i] > 100*pBH:
-                output_array[0][id_array8[0][i]] = self.BH_mass_high(mass_array[id_array8][i],
-                                                                    Z_array[id_array8][i])
-                output_array[1][id_array8[0][i]] = codes['BH']
-                
-            else:
-                output_array[0][id_array8[0][i]] = self.NS_mass(mass_array[id_array8][i])
-                output_array[1][id_array8[0][i]] = codes['NS']
+        BH_or_NS = np.where((mass_array >= 60) & (mass_array < 120))[0]
+        pBH = self.prob_BH_high(Z_array[BH_or_NS])
+        is_BH = random_array[BH_or_NS] > 100 * pBH
+        
+        id_array8 = BH_or_NS[is_BH]
+        id_array9 = BH_or_NS[~is_BH]
+        
+        # Assign BH masses and types for BH-forming indices
+        output_array[0][id_array8] = self.BH_mass_high(mass_array[id_array8], Z_array[id_array8])
+        output_array[1][id_array8] = codes['BH']
+        
+        # Assign NS masses and types for NS-forming indices
+        output_array[0][id_array9] = self.NS_mass(mass_array[id_array9])
+        output_array[1][id_array9] = codes['NS']
+
         #this is where sam's janky fix for unphysical BH massses goes
         #any BH with mass less then 3 M_sun is reassigned as a NS
         #and given a mass from the NS mass dist instead
-        id_array9 = np.where((output_array[1] == codes['BH']) & (output_array[0] < 3.0))
-        output_array[0][id_array9] = self.NS_mass(mass_array[id_array9])
-        output_array[1][id_array9] = codes['NS']
+        id_array10 = (output_array[1] == codes['BH']) & (output_array[0] < 3.0)
+        output_array[0][id_array10] = self.NS_mass(mass_array[id_array10])
+        output_array[1][id_array10] = codes['NS']
 
-        return(output_array)
+        return output_array

From bb49170a4366edc775e9c2d900196e4d0a6b47d6 Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Sat, 26 Apr 2025 16:29:46 -0700
Subject: [PATCH 04/55] Add verbose control

---
 spisea/atmospheres.py | 24 +++++++++++++-----------
 1 file changed, 13 insertions(+), 11 deletions(-)

diff --git a/spisea/atmospheres.py b/spisea/atmospheres.py
index 8df2fbe1..35caeffd 100755
--- a/spisea/atmospheres.py
+++ b/spisea/atmospheres.py
@@ -12,7 +12,7 @@
 
 log = logging.getLogger('atmospheres')
 
-def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4):
+def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4, verbose=False):
     """
     Given atmosphere model, get temperature and gravity bounds
     """
@@ -77,14 +77,15 @@ def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4
     if gravity < np.max([np.min(logg_arr_1), np.min(logg_arr_2)]):
         gravity_new = np.max([np.min(logg_arr_1), np.min(logg_arr_2)])
     
-    # Print out changes, if any
-    if temperature_new != temperature:
-        teff_msg = 'Changing to T={0:6.0f} for T={1:6.0f} logg={2:4.2f}'
-        print( teff_msg.format(temperature_new, temperature, gravity))
-    
-    if gravity_new != gravity:
-        logg_msg = 'Changing to logg={0:4.2f} for T={1:6.0f} logg={2:4.2f}'
-        print( logg_msg.format(gravity_new, temperature, gravity))
+    if verbose:
+        # Print out changes, if any
+        if temperature_new != temperature:
+            teff_msg = 'Changing to T={0:6.0f} for T={1:6.0f} logg={2:4.2f}'
+            print( teff_msg.format(temperature_new, temperature, gravity))
+        
+        if gravity_new != gravity:
+            logg_msg = 'Changing to logg={0:4.2f} for T={1:6.0f} logg={2:4.2f}'
+            print( logg_msg.format(gravity_new, temperature, gravity))
     
     return (temperature_new, gravity_new)
 
@@ -274,7 +275,7 @@ def get_phoenix_atmosphere(metallicity=0, temperature=5000, gravity=4,
 
     return sp
 
-def get_cmfgenRot_atmosphere(metallicity=0, temperature=24000, gravity=4.3, rebin=True):
+def get_cmfgenRot_atmosphere(metallicity=0, temperature=24000, gravity=4.3, rebin=True, verbose=False):
     """
     metallicity = [M/H] (def = 0)
     temperature = Kelvin (def = 24000)
@@ -285,7 +286,8 @@ def get_cmfgenRot_atmosphere(metallicity=0, temperature=24000, gravity=4.3, rebi
     # Take care of atmospheres outside the catalog boundaries
     logg_msg = 'Changing to logg={0:3.1f} for T={1:6.0f} logg={2:4.2f}'
     if gravity > 4.3:
-        print( logg_msg.format(4.3, temperature, gravity))
+        if verbose:
+            print( logg_msg.format(4.3, temperature, gravity))
         gravity = 4.3
         
     if rebin:

From ce64564d3c60d7e883669dc753b25f160e7cb745 Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Sat, 26 Apr 2025 16:30:36 -0700
Subject: [PATCH 05/55] Major Update: Accelerate generating resolved cluster by
 vectorization

---
 spisea/synthetic.py | 547 +++++++++++++++++++++++++++-----------------
 1 file changed, 334 insertions(+), 213 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index d60119bc..50593f12 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -37,7 +37,7 @@
 def Vega():
     # Use Vega as our zeropoint... assume V=0.03 mag and all colors = 0.0
     # These parameters are defined in Girardi+02
-    vega = atm.get_kurucz_atmosphere(temperature=9550, 
+    vega = atm.get_kurucz_atmosphere(temperature=9550,
                                      gravity=3.95,
                                      metallicity=-0.5)
 
@@ -47,22 +47,39 @@ def Vega():
 
     # This is (R/d)**2 as reported by Girardi et al. 2002, page 198, col 1.
     # and is used to convert to flux observed at Earth.
-    vega *= 6.247e-17 
-    
+    vega *= 6.247e-17
+
     return vega
 
 vega = Vega()
 
+class Interpolator(object):
+    def __init__(self, xp, yp):
+        """Wrapper for np.interp to allow for pickling in multiprocessing.
+
+        Parameters
+        ----------
+        xp: array-like
+            x data points for interpolation
+        yp: array-like
+            y data points for interpolation
+        """
+        self.xp = xp
+        self.yp = yp
+
+    def __call__(self, x):
+        return np.interp(x, self.xp, self.yp, left=np.nan, right=np.nan)
+
 class Cluster(object):
     """
     Base class to create a cluster with user-specified isochrone,
-    imf, ifmr, and total mass. 
+    imf, ifmr, and total mass.
 
     Parameters
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -90,17 +107,18 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=False,
         self.ifmr = ifmr
         self.cluster_mass = cluster_mass
         self.seed = seed
-        
+        self.rng = np.random.default_rng(self.seed)
+
         return
-    
+
 class ResolvedCluster(Cluster):
     """
     Cluster sub-class that produces a *resolved* stellar cluster.
-    A table is output with the synthetic photometry and intrinsic 
-    properties of the individual stars (or stellar systems, if 
+    A table is output with the synthetic photometry and intrinsic
+    properties of the individual stars (or stellar systems, if
     mutliplicity is used in the IMF object).
 
-    If multiplicity is used, than a second table is produced that 
+    If multiplicity is used, than a second table is produced that
     contains the properties of the companion stars independent of their
     primary stars.
 
@@ -108,7 +126,7 @@ class ResolvedCluster(Cluster):
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -136,12 +154,13 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         if seed is not None and verbose:
             print('WARNING: random seed set to %i' % seed)
 
-        t1 = time.time()
-        ##### 
+        #####
         # Sample the IMF to build up our cluster mass.
         #####
-        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass,
-                                                                    seed=seed)
+        # start0 = time.time()
+        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass)
+        # end0 = time.time()
+        # print('IMF sampling took {0:f} s.'.format(end0 - start0))
 
         # Figure out the filters we will make.
         self.filt_names = self.set_filter_names()
@@ -153,31 +172,49 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         interp_keys = ['Teff', 'L', 'logg', 'isWR', 'mass_current', 'phase'] + self.filt_names
         self.iso_interps = {}
         for ikey in interp_keys:
-            self.iso_interps[ikey] = interpolate.interp1d(self.iso.points['mass'], self.iso.points[ikey],
-                                                          kind='linear', bounds_error=False, fill_value=np.nan)
-        
-        ##### 
+            # self.iso_interps[ikey] = interpolate.interp1d(self.iso.points['mass'], self.iso.points[ikey],
+            #                                               kind='linear', bounds_error=False, fill_value=np.nan)
+            self.iso_interps[ikey] = Interpolator(self.iso.points['mass'], self.iso.points[ikey])
+
+        #####
         # Make a table to contain all the information about each stellar system.
         #####
+        # start1 = time.time()
         star_systems = self._make_star_systems_table(mass, isMulti, sysMass)
-        
+        # end1 = time.time()
+        # print('Star systems table took {0:f} s.'.format(end1 - start1))
+
         # Trim out bad systems; specifically, stars with masses outside those provided
         # by the model isochrone (except for compact objects).
+        # start2 = time.time()
         star_systems, compMass = self._remove_bad_systems(star_systems, compMass)
+        # end2 = time.time()
+        # print('Bad system removal took {0:f} s.'.format(end2-start2))
 
-        ##### 
+        #####
         # Make a table to contain all the information about companions.
         #####
         if self.imf.make_multiples:
-            companions = self._make_companions_table(star_systems, compMass)
-            
+            # start3 = time.time()
+            star_systems, companions = self._make_companions_table_new(star_systems, compMass)
+            # end3 = time.time()
+            # print('Companion table new took {0:f} s.'.format(end3 - start3))
+            self.companions = companions
+
+            # compMass = [
+            #     [value for value, mask in zip(row, row_mask) if not mask]
+            #     for row, row_mask in zip(compMass.data, compMass.mask)
+            # ]
+            # start3 = time.time()
+            # star_systems, companions = self._make_companions_table(star_systems, compMass)
+            # end3 = time.time()
+            # print('Companion table took {0:f} s.'.format(end3-start3))
+            # self.companions = companions
+
         #####
         # Save our arrays to the object
         #####
         self.star_systems = star_systems
-        
-        if self.imf.make_multiples:
-            self.companions = companions
 
         return
 
@@ -186,13 +223,13 @@ def set_filter_names(self):
         Set filter column names
         """
         filt_names = []
-        
+
         for col_name in self.iso.points.colnames:
             if 'm_' in col_name:
                 filt_names.append(col_name)
 
         return filt_names
-        
+
     def _make_star_systems_table(self, mass, isMulti, sysMass):
         """
         Make a star_systems table and get synthetic photometry for each primary star.
@@ -201,28 +238,20 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
                              names=['mass', 'isMultiple', 'systemMass'])
         N_systems = len(star_systems)
 
-        # Add columns for the Teff, L, logg, isWR, mass_current, phase for the primary stars.
-        star_systems.add_column( Column(np.zeros(N_systems, dtype=float), name='Teff') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='L') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='logg') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='isWR') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='mass_current') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='phase') )
-        star_systems.add_column( Column(np.empty(N_systems, dtype=float), name='metallicity') )
+        # Use our pre-built interpolators to fetch values from the isochrone for each star.
+        for key in ['Teff', 'L', 'logg', 'mass_current']:
+            star_systems.add_column(Column(self.iso_interps[key](star_systems['mass']), name=key))
+
+        # Treat out-of-range mass as isWR=True
+        star_systems.add_column(Column(~(self.iso_interps['isWR'](star_systems['mass']) < 0.5), name='isWR'))
+        star_systems.add_column(Column(np.round(self.iso_interps['phase'](star_systems['mass'])), name='phase'))
+
+        star_systems['metallicity'] = np.ones(N_systems) * self.iso.metallicity
 
         # Add the filter columns to the table. They are empty so far.
         # Keep track of the filter names in : filt_names
         for filt in self.filt_names:
-            star_systems.add_column( Column(np.empty(N_systems, dtype=float), name=filt) )
-
-        # Use our pre-built interpolators to fetch values from the isochrone for each star.
-        star_systems['Teff'] = self.iso_interps['Teff'](star_systems['mass'])
-        star_systems['L']    = self.iso_interps['L'](star_systems['mass'])
-        star_systems['logg'] = self.iso_interps['logg'](star_systems['mass'])
-        star_systems['isWR'] = np.round(self.iso_interps['isWR'](star_systems['mass']))
-        star_systems['mass_current'] = self.iso_interps['mass_current'](star_systems['mass'])
-        star_systems['phase'] = np.round(self.iso_interps['phase'](star_systems['mass']))
-        star_systems['metallicity'] = np.ones(N_systems)*self.iso.metallicity
+            star_systems.add_column(Column(self.iso_interps[filt](star_systems['mass']), name=filt))
 
         # For a very small fraction of stars, the star phase falls on integers in-between
         # the ones we have definition for, as a result of the interpolation. For these
@@ -232,29 +261,22 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
         # effect is so small
         # Convert nan_to_num to avoid errors on greater than, less than comparisons
         star_systems_phase_non_nan = np.nan_to_num(star_systems['phase'], nan=-99)
-        bad = np.where( (star_systems_phase_non_nan > 5) & (star_systems_phase_non_nan < 101) & (star_systems_phase_non_nan != 9) & (star_systems_phase_non_nan != -99))
-        # Print warning, if desired
-        verbose=False
-        if verbose:
-            for ii in range(len(bad[0])):
-                print('WARNING: changing phase {0} to 5'.format(star_systems['phase'][bad[0][ii]]))
+        bad = (star_systems_phase_non_nan > 5) & (star_systems_phase_non_nan < 101) & (star_systems_phase_non_nan != 9) & (star_systems_phase_non_nan != -99)
         star_systems['phase'][bad] = 5
-        
-        for filt in self.filt_names:
-            star_systems[filt] = self.iso_interps[filt](star_systems['mass'])
+
 
         #####
         # Make Remnants
         #     Note: Some models already have WDs in them. If they do, then they shouldn't
         #     be handled by this code here (because their Teff > 0).
-        # 
+        #
         # Remnants have flux = 0 in all bands if they are generated here.
-        ##### 
+        #####
         if self.ifmr != None:
             # Identify compact objects as those with Teff = 0 or with phase > 100.
             highest_mass_iso = self.iso.points['mass'].max()
             idx_rem = np.where((np.isnan(star_systems['Teff'])) & (star_systems['mass'] > highest_mass_iso))[0]
-            
+
             # Calculate remnant mass and ID for compact objects; update remnant_id and
             # remnant_mass arrays accordingly
             if 'metallicity_array' in inspect.getfullargspec(self.ifmr.generate_death_mass).args:
@@ -265,7 +287,7 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
 
             # Drop remnants where it is not relevant (e.g. not a compact object or
             # outside mass range IFMR is defined for)
-            good = np.where(r_id_tmp > 0)
+            good = r_id_tmp > 0
             idx_rem_good = idx_rem[good]
 
             star_systems['mass_current'][idx_rem_good] = r_mass_tmp[good]
@@ -276,13 +298,111 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
                 star_systems[filt][idx_rem_good] = np.full(len(idx_rem_good), np.nan)
 
         return star_systems
-        
+
+
+    def _make_companions_table_new(self, star_systems, compMass):
+        """Make companions table for resolved clusters with multiplicity.
+
+        Parameters
+        ----------
+        star_systems : astropy.table.Table
+            Table containing the properties of the primary stars.
+        compMass : numpy.ma.MaskedArray
+            Masked array containing the masses of the companions.
+
+        Returns
+        -------
+        companions : astropy.table.Table
+        """
+        N_systems = len(star_systems)
+        N_companions = np.sum(~compMass.mask, axis=1)
+        N_comp_tot = np.sum(N_companions)
+        star_systems.add_column(Column(N_companions, name='N_companions'))
+        system_index = np.repeat(np.arange(N_systems), N_companions)
+        companions = Table([system_index], names=['system_idx'])
+        companions.add_column(np.zeros(N_comp_tot, dtype=float), name='mass')
+
+        if isinstance(self.imf._multi_props, multiplicity.MultiplicityResolvedDK):
+            companions.add_column(Column(self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx']]), name='log_a'))
+            companions.add_column(Column(self.imf._multi_props.random_e(self.rng.random(N_comp_tot)), name='e'))
+            companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot)
+            )
+
+        companions['mass'] = compMass.compressed()
+        for key in ['Teff', 'L', 'logg', 'mass_current']:
+            companions[key] = self.iso_interps[key](companions['mass'])
+
+        for key in ['isWR', 'phase']:
+            companions[key] = np.round(self.iso_interps[key](companions['mass']))
+
+        companions['metallicity'] = np.ones(N_comp_tot) * self.iso.metallicity
+
+        # For a very small fraction of stars, the star phase falls on integers in-between
+        # the ones we have definition for, as a result of the interpolation. For these
+        # stars, round phase down to nearest defined phase (e.g., if phase is 71,
+        # then round it down to 5, rather than up to 101).
+        # Convert nan_to_num to avoid errors on greater than, less than comparisons
+        companions_phase_non_nan = np.nan_to_num(companions['phase'], nan=-99)
+        companions['phase'][
+            (companions_phase_non_nan > 5) &
+            (companions_phase_non_nan < 101) &
+            (companions_phase_non_nan != 9) &
+            (companions_phase_non_nan != -99)
+        ] = 5
+
+        # Update primary fluxes to include the flux of companions.
+        for filt in self.filt_names:
+            companions[filt] = self.iso_interps[filt](companions['mass'])
+            primary_flux = 10**(-star_systems[filt] / 2.5)
+            # Sum the flux of all companions in each system
+            companions_flux = np.bincount(companions['system_idx'], weights=10**(-companions[filt] / 2.5), minlength=N_systems)
+            combined_flux = np.nansum(np.vstack((primary_flux, companions_flux)), axis=0)
+            combined_flux[combined_flux == 0] = np.nan
+            star_systems[filt] = -2.5 * np.log10(combined_flux)
+
+        #####
+        # Make Remnants with flux = 0 in all bands.
+        #####
+        if self.ifmr:
+            # Identify compact objects as those with Teff = 0 or with masses above the max iso mass
+            highest_mass_iso = self.iso.points['mass'].max()
+            remnant_idx = np.where(np.isnan(companions['Teff']) & (companions['mass'] > highest_mass_iso))[0]
+            self.remnant_idx_new = remnant_idx
+            # Calculate remnant mass and ID for compact objects; update remnant_id and remnant_mass arrays accordingly
+            if 'metallicity_array' in inspect.getfullargspec(self.ifmr.generate_death_mass).args:
+                remnant_mass, remnant_code = self.ifmr.generate_death_mass(mass_array=companions['mass'][remnant_idx], metallicity_array=companions['metallicity'][remnant_idx])
+            else:
+                remnant_mass, remnant_code = self.ifmr.generate_death_mass(mass_array=companions['mass'][remnant_idx])
+
+            # Drop remnants where it is not relevant (e.g. not a compact object or outside mass range IFMR is defined for)
+            remnant_valid = remnant_code > 0
+            remnant_valid_idx = remnant_idx[remnant_valid]
+            self.remnant_mass_new = remnant_mass
+            self.remnant_valid_idx_new = remnant_valid_idx
+            companions['mass_current'][remnant_valid_idx] = remnant_mass[remnant_valid]
+            companions['phase'][remnant_valid_idx] = remnant_code[remnant_valid]
+            # Give remnants a magnitude of nan, so they can be filtered out later when calculating flux.
+            for filt in self.filt_names:
+                companions[filt][remnant_valid_idx] = np.full(len(remnant_idx[remnant_valid]), np.nan)
+
+        companions_teff_non_nan = np.nan_to_num(companions['Teff'], nan=-99)
+        if self.verbose and sum(companions_teff_non_nan > 0) != N_comp_tot:
+            print(f'Found {N_comp_tot - sum(companions_teff_non_nan > 0):d} companions out of stellar mass range')
+
+        assert companions['mass'][companions_teff_non_nan > 0].min() > 0, "Companion mass is not positive"
+
+        return star_systems, companions
+
+
     def _make_companions_table(self, star_systems, compMass):
 
         N_systems = len(star_systems)
-        
+
         #####
-        #    MULTIPLICITY                 
+        #    MULTIPLICITY
         # Make a second table containing all the companion-star masses.
         # This table will be much longer... here are the arrays:
         #    sysIndex - the index of the system this star belongs too
@@ -306,25 +426,29 @@ def _make_companions_table(self, star_systems, compMass):
         companions.add_column( Column(np.empty(N_comp_tot, dtype=float), name='metallicity') )
         for filt in self.filt_names:
             companions.add_column( Column(np.empty(N_comp_tot, dtype=float), name=filt) )
-            
+
         if isinstance(self.imf._multi_props, multiplicity.MultiplicityResolvedDK):
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='log_a') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='e') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='i', description = 'degrees') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='Omega') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='omega') )
-            
+
             for ii in range(len(companions)):
                 companions['log_a'][ii] = self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx'][ii]])
-            
-            companions['e'] = self.imf._multi_props.random_e(np.random.rand(N_comp_tot))
-            companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(np.random.rand(N_comp_tot),np.random.rand(N_comp_tot),np.random.rand(N_comp_tot))
+
+            companions['e'] = self.imf._multi_props.random_e(self.rng.random(N_comp_tot))
+            companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot)
+            )
 
 
         # Make an array that maps system index (ii), companion index (cc) to
         # the place in the 1D companions array.
         N_comp_max = N_companions.max()
-        
+
         comp_index = np.zeros((N_systems, N_comp_max), dtype=int)
         kk = 0
         for ii in range(N_systems):
@@ -340,9 +464,10 @@ def _make_companions_table(self, star_systems, compMass):
             idx = np.where(N_companions >= cc)[0]
 
             # Get the location in the companions array for each system and
-            # the cc'th companion. 
+            # the cc'th companion.
             cdx = comp_index[idx, cc-1]
-            
+
+            # companions['mass'][cdx] = compMass[idx, cc-1]
             companions['mass'][cdx] = [compMass[ii][cc-1] for ii in idx]
             comp_mass = companions['mass'][cdx]
 
@@ -391,13 +516,13 @@ def _make_companions_table(self, star_systems, compMass):
                     # as np.nan. Otherwise, add fluxes together
                     good = np.where( (f1 != 0) | (f2 != 0) )
                     bad = np.where( (f1 == 0) & (f2 == 0) )
-                    
+
                     star_systems[filt][idx[good]] = -2.5 * np.log10(f1[good] + f2[good])
                     star_systems[filt][idx[bad]] = np.nan
 
         #####
         # Make Remnants with flux = 0 in all bands.
-        ##### 
+        #####
         if self.ifmr != None:
             # Identify compact objects as those with Teff = 0 or with masses above the max iso mass
             highest_mass_iso = self.iso.points['mass'].max()
@@ -411,7 +536,7 @@ def _make_companions_table(self, star_systems, compMass):
                                                                      metallicity_array=companions['metallicity'][cdx_rem])
             else:
                 r_mass_tmp, r_id_tmp = self.ifmr.generate_death_mass(mass_array=companions['mass'][cdx_rem])
-            
+
 
             # Drop remnants where it is not relevant (e.g. not a compact object or
             # outside mass range IFMR is defined for)
@@ -420,7 +545,7 @@ def _make_companions_table(self, star_systems, compMass):
 
             companions['mass_current'][cdx_rem_good] = r_mass_tmp[good]
             companions['phase'][cdx_rem_good] = r_id_tmp[good]
-                
+
             # Give remnants a magnitude of nan, so they can be filtered out later when calculating flux.
             for filt in self.filt_names:
                 companions[filt][cdx_rem_good] = np.full(len(cdx_rem_good), np.nan)
@@ -434,18 +559,18 @@ def _make_companions_table(self, star_systems, compMass):
             print( 'Found {0:d} companions out of stellar mass range'.format(N_comp_tot - len(idx)))
 
         # Double check that everything behaved properly.
-        assert companions['mass'][idx].min() > 0
+        # assert companions['mass'][idx].min() > 0, "Companion mass must be positive"
+
+        return star_systems, companions
 
-        return companions
 
-    
     def _remove_bad_systems(self, star_systems, compMass):
         """
         Helper function to remove stars with masses outside the isochrone
-        mass range from the cluster. These stars are identified by having 
+        mass range from the cluster. These stars are identified by having
         a Teff = 0, as set up by _make_star_systems_table_interp.
-        If self.ifmr == None, then both high and low-mass bad systems are 
-        removed. If self.ifmr != None, then we will save the high mass systems 
+        If self.ifmr == None, then both high and low-mass bad systems are
+        removed. If self.ifmr != None, then we will save the high mass systems
         since they will be plugged into an ifmr later.
         """
         N_systems = len(star_systems)
@@ -456,12 +581,12 @@ def _remove_bad_systems(self, star_systems, compMass):
         star_systems_phase_non_nan = np.nan_to_num(star_systems['phase'], nan=-99)
         if self.ifmr == None:
             # Keep only those stars with Teff assigned.
-            idx = np.where(star_systems_teff_non_nan > 0)[0]
+            idx = star_systems_teff_non_nan > 0
         else:
-            # Keep stars (with Teff) and any other compact objects (with phase info). 
-            idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) )[0]
+            # Keep stars (with Teff) and any other compact objects (with phase info).
+            idx = (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0)
 
-        if len(idx) != N_systems and self.verbose:
+        if self.verbose and sum(idx) != N_systems:
             print( 'Found {0:d} stars out of mass range'.format(N_systems - len(idx)))
 
         star_systems = star_systems[idx]
@@ -469,8 +594,8 @@ def _remove_bad_systems(self, star_systems, compMass):
 
         if self.imf.make_multiples:
             # Clean up companion stuff (which we haven't handled yet)
-            compMass = [compMass[ii] for ii in idx]
-        
+            compMass = compMass[idx]
+
         return star_systems, compMass
 
 
@@ -483,7 +608,7 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -493,7 +618,7 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
     delta_AKs: float
         Amount of differential extinction to apply to synthetic photometry,
         in terms of magnitudes of extinction in the Ks filter. Specifically,
-        delta_AKs defines the standard deviation of a Gaussian distribution 
+        delta_AKs defines the standard deviation of a Gaussian distribution
         from which the delta_AKs values will be drawn from for each individual
         system.
 
@@ -516,14 +641,10 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         ResolvedCluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                                      seed=seed)
 
-        # Set random seed, if desired
-        if seed is not None:
-            np.random.seed(seed=seed)
-
         # Extract the extinction law from the isochrone object
         redlaw_str = iso.points.meta['REDLAW']
         red_law = reddening.get_red_law(redlaw_str)
-            
+
         # For a given delta_AKs (Gaussian sigma of reddening distribution at Ks),
         # figure out the equivalent delta_filt values for all other filters.
         #t1 = time.time()
@@ -535,7 +656,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         for filt in self.filt_names:
             obs_str = get_obs_str(filt)
             filt_info = get_filter_info(obs_str)
-            
+
             mag_lo = mag_in_filter(red_vega_lo, filt_info)
             mag_hi = mag_in_filter(red_vega_hi, filt_info)
             delta_red_filt[filt] = mag_hi - mag_lo
@@ -543,7 +664,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         # Perturb all of star systems' photometry by a random amount corresponding to
         # differential de-reddening. The distribution is normal with a width of
         # Aks +/- deltaAKs in each filter
-        rand_red = np.random.randn(len(self.star_systems))
+        rand_red = self.rng.standard_normal(len(self.star_systems))
 
         for filt in self.filt_names:
             self.star_systems[filt] += rand_red * delta_red_filt[filt]
@@ -563,18 +684,18 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         #t2 = time.time()
         #print 'Diff redden: {0}'.format(t2 - t1)
         return
-    
+
 class UnresolvedCluster(Cluster):
     """
     Cluster sub-class that produces an *unresolved* stellar cluster.
-    Output is a combined spectrum that is the sum of the individual 
+    Output is a combined spectrum that is the sum of the individual
     spectra of the cluster stars.
 
     Parameters
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -592,10 +713,10 @@ def __init__(self, iso, imf, cluster_mass,
                  wave_range=[3000, 52000], verbose=False):
         # Doesn't do much.
         Cluster.__init__(self, iso, imf, cluster_mass, verbose=verbose)
-        
+
         # Sample a power-law IMF randomly
         self.mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass)
-        
+
         temp = np.zeros(len(self.mass), dtype=float)
         self.mass_all = np.zeros(len(self.mass), dtype=float)
         self.spec_list = [None] * len(self.mass)
@@ -629,7 +750,7 @@ def __init__(self, iso, imf, cluster_mass,
             tmpspectrim = spectrum.trimSpectrum(tmpspecresamp,wave_range[0],wave_range[1])
             self.spec_list_trim[ii] = tmpspectrim
             spec_list_trim_np[:,ii] = np.asarray(tmpspectrim._fluxtable)
-            
+
 
         t2 = time.time()
         print( 'Mass matching took {0:f} s.'.format(t2-t1))
@@ -651,7 +772,7 @@ def __init__(self, iso, imf, cluster_mass,
 
         self.spec_trim = np.sum(spec_list_trim_np,1)
         self.wave_trim = self.spec_list_trim[0].wave
-        
+
         t4 = time.time()
         print( 'Spec trimming took {0:f}s'.format(t4-t3))
 
@@ -659,10 +780,10 @@ def __init__(self, iso, imf, cluster_mass,
         print( 'Total cluster mass is {0:f} M_sun'.format(self.mass_tot))
 
         return
-        
+
 class Isochrone(object):
     """
-    Base Isochrone class. 
+    Base Isochrone class.
 
     Parameters
     ----------
@@ -680,20 +801,20 @@ class Isochrone(object):
         Default is 0.
 
     evo_model: model evolution class, optional
-        Set the stellar evolution model class. 
+        Set the stellar evolution model class.
         Default is evolution.MISTv1().
 
     atm_func: model atmosphere function, optional
-        Set the stellar atmosphere models for the stars. 
+        Set the stellar atmosphere models for the stars.
         Default is get_merged_atmosphere.
 
     wd_atm_func: white dwarf model atmosphere function, optional
-        Set the stellar atmosphere models for the white dwafs. 
-        Default is get_wd_atmosphere   
+        Set the stellar atmosphere models for the white dwafs.
+        Default is get_wd_atmosphere
 
     mass_sampling : int, optional
         Sample the raw isochrone every `mass_sampling` steps. The default
-        is mass_sampling = 0, which is the native isochrone mass sampling 
+        is mass_sampling = 0, which is the native isochrone mass sampling
         of the evolution model.
 
     wave_range : list, optional
@@ -722,7 +843,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
 
 
         t1 = time.time()
-        
+
         c = constants
 
         # Assert that the wavelength ranges are within the limits of the
@@ -733,7 +854,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
         except:
             print('Desired wavelength range invalid. Limit to 1000 - 10000 A')
             return
-        
+
         # Get solar metallicity models for a population at a specific age.
         # Takes about 0.1 seconds.
         evol = evo_model.isochrone(age=10**logAge,
@@ -749,7 +870,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
             evol = evol[idx]
         if max_mass != None:
             idx = np.where(evol['mass'] <= max_mass)
-            evol = evol[idx] 
+            evol = evol[idx]
 
         # Trim down the table by selecting every Nth point where
         # N = mass sampling factor.
@@ -799,10 +920,10 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
             star *= (R / distance)**2  # in erg s^-1 cm^-2 A^-1
 
             # Redden the spectrum. This doesn't take much time at all.
-            red = red_law.reddening(AKs).resample(star.wave) 
+            red = red_law.reddening(AKs).resample(star.wave)
             star *= red
-            
-            # Save the final spectrum to our spec_list for later use.            
+
+            # Save the final spectrum to our spec_list for later use.
             self.spec_list.append(star)
 
         # Append all the meta data to the summary table.
@@ -830,7 +951,7 @@ def plot_HR_diagram(self, savefile=None):
         Parameters
         -----------
         savefile: path or None, optional
-             Path to file plot too, if desired. 
+             Path to file plot too, if desired.
              Default is None
         """
         plt.clf()
@@ -839,7 +960,7 @@ def plot_HR_diagram(self, savefile=None):
         plt.gca().invert_xaxis()
         plt.xlabel(r'T$_{\mathrm{eff}}$ (K)')
         plt.ylabel('Luminosity (erg / s)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
@@ -847,7 +968,7 @@ def plot_HR_diagram(self, savefile=None):
 
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
     def plot_mass_luminosity(self, savefile=None):
@@ -857,28 +978,28 @@ def plot_mass_luminosity(self, savefile=None):
         Parameters
         -----------
         savefile: path or None, optional
-             Path to file plot too, if desired. 
+             Path to file plot too, if desired.
              Default is None
         """
         plt.clf()
         plt.loglog(self.points['mass'], self.points['L'], 'k.')
         plt.xlabel(r'Mass (M$_\odot$)')
         plt.ylabel('Luminosity (erg / s)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
                                   self.points.meta['AKS']))
-        
+
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
 class IsochronePhot(Isochrone):
     """
-    Make an isochrone with synthetic photometry in various filters. 
-    Load from file if possible. 
+    Make an isochrone with synthetic photometry in various filters.
+    Load from file if possible.
 
     Parameters
     ----------
@@ -896,16 +1017,16 @@ class IsochronePhot(Isochrone):
         Default is 0.
 
     evo_model: model evolution class, optional
-        Set the stellar evolution model class. 
+        Set the stellar evolution model class.
         Default is evolution.MISTv1().
 
     atm_func: model atmosphere function, optional
-        Set the stellar atmosphere models for the stars. 
+        Set the stellar atmosphere models for the stars.
         Default is atmospheres.get_merged_atmosphere.
 
     wd_atm_func: white dwarf model atmosphere function, optional
-        Set the stellar atmosphere models for the white dwafs. 
-        Default is atmospheres.get_wd_atmosphere   
+        Set the stellar atmosphere models for the white dwafs.
+        Default is atmospheres.get_wd_atmosphere
 
     red_law : reddening law object, optional
         Define the reddening law for the synthetic photometry.
@@ -913,14 +1034,14 @@ class IsochronePhot(Isochrone):
 
     iso_dir : path, optional
          Path to isochrone directory. Code will check isochrone
-         directory to see if isochrone file already exists; if it 
-         does, it will just read the isochrone. If the isochrone 
+         directory to see if isochrone file already exists; if it
+         does, it will just read the isochrone. If the isochrone
          file doesn't exist, then save isochrone to the isochrone
          directory.
 
     mass_sampling : int, optional
         Sample the raw isochrone every `mass_sampling` steps. The default
-        is mass_sampling = 0, which is the native isochrone mass sampling 
+        is mass_sampling = 0, which is the native isochrone mass sampling
         of the evolution model.
 
     wave_range : list, optional
@@ -941,14 +1062,14 @@ class IsochronePhot(Isochrone):
         which is often sufficient synthetic photometry in most cases.
 
     recomp : boolean, optional
-        If true, recalculate the isochrone photometry even if 
+        If true, recalculate the isochrone photometry even if
         the savefile exists. You should recompute anytime you change
         the filter set (see filters below).
 
     filters : array of strings, optional
         Define what filters the synthetic photometry
-        will be calculated for, via the filter string 
-        identifier. 
+        will be calculated for, via the filter string
+        identifier.
     """
     def __init__(self, logAge, AKs, distance,
                  metallicity=0.0,
@@ -983,11 +1104,11 @@ def __init__(self, logAge, AKs, distance,
             else:
                 metal_pre = 'p'
             metal_flag = int(abs(metallicity)*10)
-            
+
             save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_{4}{5:2s}.fits'
             self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
             self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
-            
+
         # Expected filters
         self.filters = filters
 
@@ -1004,7 +1125,7 @@ def __init__(self, logAge, AKs, distance,
                                red_law=red_law, mass_sampling=mass_sampling,
                                min_mass=min_mass, max_mass=max_mass, rebin=rebin)
             self.verbose = True
-            
+
             # Make photometry
             self.make_photometry(rebin=rebin, vega=vega)
         else:
@@ -1018,11 +1139,11 @@ def __init__(self, logAge, AKs, distance,
         return
 
     def make_photometry(self, rebin=True, vega=vega):
-        """ 
+        """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
         photometry.
-        
+
         """
         startTime = time.time()
 
@@ -1040,7 +1161,7 @@ def make_photometry(self, rebin=True, vega=vega):
         for ii in self.filters:
             prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
             print( prt_fmt.format(ii, time.time() - startTime))
-            
+
             filt = get_filter_info(ii, rebin=rebin, vega=vega)
             filt_name = get_filter_col_name(ii)
 
@@ -1048,15 +1169,15 @@ def make_photometry(self, rebin=True, vega=vega):
             col_name = 'm_' + filt_name
             mag_col = Column(np.zeros(npoints, dtype=float), name=col_name)
             self.points.add_column(mag_col)
-            
+
             # Loop through each star in the isochrone and do the filter integration
             print('Starting synthetic photometry')
             for ss in range(npoints):
                 star = self.spec_list[ss]  # These are already extincted, observed spectra.
                 star_mag = mag_in_filter(star, filt)
-                
+
                 self.points[col_name][ss] = star_mag
-        
+
                 if (self.verbose and (ss % 100) == 0):
                     print( verbose_fmt.format(self.points['mass'][ss], self.points['Teff'][ss],
                                              filt_name, star_mag))
@@ -1073,27 +1194,27 @@ def make_photometry(self, rebin=True, vega=vega):
 
     def check_save_file(self, evo_model, atm_func, red_law):
         """
-        Check to see if save_file exists, as saved by the save_file 
-        and save_file_legacy objects. If the filename exists, check the 
+        Check to see if save_file exists, as saved by the save_file
+        and save_file_legacy objects. If the filename exists, check the
         meta-data as well.
 
         returns a boolean: True is file exists, false otherwise
         """
         out_bool = False
-        
+
         if os.path.exists(self.save_file) | os.path.exists(self.save_file_legacy):
             try:
                 tmp = Table.read(self.save_file)
             except:
                 tmp = Table.read(self.save_file_legacy)
-            
-        
+
+
             # See if the meta-data matches: evo model, atm_func, redlaw
             if ( (tmp.meta['EVOMODEL'] == type(evo_model).__name__) &
                 (tmp.meta['ATMFUNC'] == atm_func.__name__) &
                  (tmp.meta['REDLAW'] == red_law.name) ):
                 out_bool = True
-            
+
         return out_bool
 
     def plot_CMD(self, mag1, mag2, savefile=None):
@@ -1107,7 +1228,7 @@ def plot_CMD(self, mag1, mag2, savefile=None):
         mag2 : string
             The name of the second magnitude column to be plotted.
         savefile : string (default None)
-            If a savefile is specified, then the plot will be saved to that file. 
+            If a savefile is specified, then the plot will be saved to that file.
         """
         plt.clf()
         plt.plot(self.points[mag1] - self.points[mag2], self.points[mag1],
@@ -1115,7 +1236,7 @@ def plot_CMD(self, mag1, mag2, savefile=None):
         plt.gca().invert_yaxis()
         plt.xlabel(mag1 + ' - ' + mag2 + ' (mag)')
         plt.ylabel(mag1 + ' (mag)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
@@ -1123,34 +1244,34 @@ def plot_CMD(self, mag1, mag2, savefile=None):
 
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
     def plot_mass_magnitude(self, mag, savefile=None):
         """
         Make a standard mass-luminosity relation plot for this isochrone.
-        
+
         Parameters
         ----------
         mag : string
             The name of the magnitude column to be plotted.
         savefile : string (default None)
-            If a savefile is specified, then the plot will be saved to that file. 
+            If a savefile is specified, then the plot will be saved to that file.
         """
         plt.clf()
         plt.semilogx(self.points['mass'], self.points[mag], 'k.')
         plt.gca().invert_yaxis()
         plt.xlabel(r'Mass (M$_\odot$)')
         plt.ylabel(mag + ' (mag)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
                                   self.points.meta['AKS']))
-        
+
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
 #===================================================#
@@ -1172,7 +1293,7 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
         Functions on this object:
         apply_reddening (Apply reddening with defined redlaw and AKs)
         make_photometry (make synthetic photometry for spectra)
-                 
+
         Parameters
         ----------
         logAge : float
@@ -1210,13 +1331,13 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             spectrum. This is very useful to save computation time down the
             road.
         """
-        t1 = time.time()        
+        t1 = time.time()
         c = constants
 
         # Get solar metallicity models for a population at a specific age.
         # Takes about 0.1 seconds.
-        evol = evo_model.isochrone(age=10**logAge)  # solar metallicity 
-        
+        evol = evo_model.isochrone(age=10**logAge)  # solar metallicity
+
         # Eliminate cases where log g is less than 0
         idx = np.where(evol['logg'] > 0)
         evol = evol[idx]
@@ -1227,8 +1348,8 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             evol = evol[idx]
         if max_mass != None:
             idx = np.where(evol['mass'] <= max_mass)
-            evol = evol[idx]            
- 
+            evol = evol[idx]
+
         # Trim down the table by selecting every Nth point where
         # N = mass sampling factor.
         evol = evol[::mass_sampling]
@@ -1263,18 +1384,18 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             # Get the atmosphere model now. Wavelength is in Angstroms
             # This is the time-intensive call... everything else is negligable.
             star = atm_func(temperature=T, gravity=gravity)
-            
+
             # Trim wavelength range down to JHKL range (0.5 - 5.2 microns)
             star = spectrum.trimSpectrum(star, wave_range[0], wave_range[1])
 
             # Convert into flux observed at Earth (unreddened)
             star *= (R / distance)**2  # in erg s^-1 cm^-2 A^-1
-            
-            # Save the final spectrum to our spec_list for later use.            
+
+            # Save the final spectrum to our spec_list for later use.
             self.spec_list.append(star)
 
         # Append all the meta data to the summary table.
-        
+
         tab.meta['ATMFUNC'] = atm_func.__name__
         tab.meta['EVOMODEL'] = type(evo_model).__name__
         tab.meta['LOGAGE'] = logAge
@@ -1283,10 +1404,10 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
         tab.meta['WAVEMAX'] = wave_range[1]
 
         self.points = tab
-    
+
         t2 = time.time()
         print('Isochrone generation took {0:f} s.'.format(t2-t1))
-        
+
         return
 
     def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=None):
@@ -1298,7 +1419,7 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
         ----------
         AKs: float
             Total extinction in AKs
-            
+
         extinction_law: SPISEA extinction object
             Extinction law to be used on the spectra
 
@@ -1308,13 +1429,13 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
 
         dAKs_max: float or None
             If not none, defines the maximum |dAKs| a star can
-            have in gaussian distribution case 
+            have in gaussian distribution case
 
         dist: string, 'uniform' or 'gaussian'
             Distribution to draw differential reddening from. If uniform,
             dAKs will cut off at Aks +/- dAKs. Otherwise, will draw
             from Gaussian of width AKs +/- dAks
-            
+
         """
         self.AKs = np.ones(len(self.spec_list))
         # Apply reddening to each object in the spec list
@@ -1325,25 +1446,25 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
             # extinction law
             if dAKs != 0:
                 if dist == 'gaussian':
-                    AKs_act = np.random.normal(loc=AKs, scale=dAKs)
+                    AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
                     # Apply dAKs_max if desired. Redo if diff > dAKs_max
                     if dAKs_max != None:
                         diff = abs(AKs_act - AKs)
                         while diff > dAKs_max:
                             print('While loop active')
-                            AKs_act = np.random.normal(loc=AKs, scale=dAKs)
+                            AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
                             diff = abs(AKs_act - AKs)
                 elif dist == 'uniform':
                     low = AKs - dAKs
                     high = AKs + dAKs
-                    AKs_act = np.random.uniform(low=low, high=high)
+                    AKs_act = self.rng.uniform(low=low, high=high)
                 else:
                     print('dist {0} undefined'.format(dist))
                     return
             else:
                 AKs_act = AKs
 
-            red = extinction_law.reddening(AKs_act).resample(star.wave) 
+            red = extinction_law.reddening(AKs_act).resample(star.wave)
             star *= red
 
             # Update the spectrum in spec list
@@ -1356,7 +1477,7 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
         return
 
     def make_photometry(self, filters, rebin=True):
-        """ 
+        """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
         photometry.
@@ -1366,11 +1487,11 @@ def make_photometry(self, filters, rebin=True):
         filters : dictionary
             A dictionary containing the filter name (for the output columns)
             and the filter specification string that can be processed by pysynphot.
-                   
+
         rebin: boolean
-            True to rebin filter function (only used if non-zero transmission points are 
+            True to rebin filter function (only used if non-zero transmission points are
             larger than 1500 points)
- 
+
         """
         npoints = len(self.points)
 
@@ -1387,35 +1508,35 @@ def make_photometry(self, filters, rebin=True):
             col_name = 'mag_' + filt_name
             mag_col = Column(np.zeros(npoints, dtype=float), name=col_name)
             self.points.add_column(mag_col)
-            
+
             # Loop through each star in the isochrone and do the filter integration
             for ss in range(npoints):
                 star = self.spec_list[ss]  # These are already extincted, observed spectra.
                 star_mag = mag_in_filter(star, filt)
-                
+
                 self.points[col_name][ss] = star_mag
-        
-            
+
+
         endTime = time.time()
         print( '      Time taken: {0:.2f} seconds'.format(endTime - ts))
 
         return
 
 def get_filter_info(name, vega=vega, rebin=True):
-    """ 
+    """
     Define filter functions, setting ZP according to
     Vega spectrum. Input name is the SPISEA
     obs_string
     """
     tmp = name.split(',')
     filterName = tmp[-1]
-        
+
     if name.startswith('nirc2'):
         filt = filters.get_nirc2_filt(filterName)
 
     elif name.startswith('2mass'):
         filt = filters.get_2mass_filt(filterName)
-        
+
     elif name.startswith('vista'):
         filt = filters.get_vista_filt(filterName)
 
@@ -1430,10 +1551,10 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('jg'):
         filt = filters.get_Johnson_Glass_filt(filterName)
-        
+
     elif name.startswith('nirc1'):
         filt = filters.get_nirc1_filt(filterName)
-        
+
     elif name.startswith('ctio_osiris'):
         filt = filters.get_ctio_osiris_filt(filterName)
 
@@ -1445,7 +1566,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('ukirt'):
         filt = filters.get_ukirt_filt(filterName)
-        
+
     elif name.startswith('keck_osiris'):
         filt = filters.get_keck_osiris_filt(filterName)
 
@@ -1458,17 +1579,17 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('hawki'):
         filt = filters.get_hawki_filt(filterName)
-     
+
     elif name.startswith('rubin'):
         filt = filters.get_rubin_filt(filterName)
-        
+
     else:
         # Otherwise, look for the filter info in the cdbs/mtab and cdbs/comp files
         try:
             filt = ObsBandpass(name)
         except:
             raise Exception('Filter {0} not understood. Check spelling and make sure cdbs/mtab and cdbs/comp files are up to date'.format(name))
-        
+
         # Convert to ArraySpectralElement for resampling.
         filt = spectrum.ArraySpectralElement(filt.wave, filt.throughput,
                                              waveunits=filt.waveunits,
@@ -1486,14 +1607,14 @@ def get_filter_info(name, vega=vega, rebin=True):
     # Otherwise, throw an error
     idx = np.where(filt.throughput > 0.001)[0]
     if (min(filt.wave[idx]) < min(vega.wave)) | (max(filt.wave[idx]) > max(vega.wave)):
-        raise ValueError('Vega spectrum doesnt cover filter wavelength range!')  
+        raise ValueError('Vega spectrum doesnt cover filter wavelength range!')
 
     vega_obs = obs.Observation(vega, filt, binset=filt.wave, force='taper')
     #vega_flux = vega_obs.binflux.sum()
     diff = np.diff(vega_obs.binwave)
     diff = np.append(diff, diff[-1])
     vega_flux = np.sum(vega_obs.binflux * diff)
-    
+
     vega_mag = 0.03
 
     filt.flux0 = vega_flux
@@ -1504,7 +1625,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
 def get_filter_col_name(obs_str):
     """
-    Get standard column name for synthetic photometry based on 
+    Get standard column name for synthetic photometry based on
     the input string. The input string is expected to be an
     appropriate SPISEA obs_string
     """
@@ -1523,7 +1644,7 @@ def get_filter_col_name(obs_str):
             filt_name = 'hst_{0}'.format(tmp[-1])
     else:
         filt_name = '{0}_{1}'.format(tmp[0], tmp[1])
-        
+
     return filt_name
 
 def get_obs_str(col):
@@ -1533,7 +1654,7 @@ def get_obs_str(col):
     """
     # Remove the trailing m_
     name = col[2:]
-    
+
     # Define dictionary for filters
     filt_list = {'hst_f127m': 'wfc3,ir,f127m', 'hst_f139m': 'wfc3,ir,f139m', 'hst_f153m': 'wfc3,ir,f153m',
                  'hst_f814w': 'acs,wfc1,f814w', 'hst_f125w': 'wfc3,ir,f125w', 'hst_f160w': 'wfc3,ir,f160w',
@@ -1555,7 +1676,7 @@ def get_obs_str(col):
                  'jwst_F187N': 'jwst,F187N',
                  'jwst_F200W': 'jwst,F200W',
                  'jwst_F210M': 'jwst,F210M',
-                 'jwst_F250M': 'jwst,F250M', 
+                 'jwst_F250M': 'jwst,F250M',
                  'jwst_F277W': 'jwst,F277W',
                  'jwst_F300M': 'jwst,F300M',
                  'jwst_F322W2': 'jwst,F322W2',
@@ -1575,7 +1696,7 @@ def get_obs_str(col):
                  'nirc2_FeII': 'nirc2,FeII', 'nirc2_Brgamma': 'nirc2,Brgamma',
                  '2mass_J': '2mass,J', '2mass_H': '2mass,H', '2mass_Ks': '2mass,Ks',
                  'ubv_U':'ubv,U', 'ubv_B':'ubv,B', 'ubv_V':'ubv,V', 'ubv_R':'ubv,R',
-                 'ubv_I':'ubv,I', 
+                 'ubv_I':'ubv,I',
                  'jg_J': 'jg,J', 'jg_H': 'jg,H', 'jg_K': 'jg,K',
                  'nirc1_K':'nirc1,K', 'nirc1_H':'nirc1,H',
                  'naco_J':'naco,J', 'naco_H':'naco,H', 'naco_Ks':'naco,Ks',
@@ -1603,7 +1724,7 @@ def get_obs_str(col):
                  'rubin_y':'rubin,y'}
 
     obs_str = filt_list[name]
-        
+
     return obs_str
 
 def rebin_spec(wave, specin, wavnew):
@@ -1616,7 +1737,7 @@ def rebin_spec(wave, specin, wavnew):
     f = np.ones(len(wave))
     filt = spectrum.ArraySpectralElement(wave, f, waveunits='angstrom')
     obs_f = obs.Observation(spec, filt, binset=wavnew, force='taper')
- 
+
     return obs_f.binflux
 
 def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
@@ -1627,7 +1748,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
                                  'wfc3,ir,f153m']):
     """
     Wrapper routine to generate a grid of isochrones of different ages,
-    extinctions, and distances. 
+    extinctions, and distances.
 
     Parameters:
     ----------
@@ -1639,7 +1760,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
 
     dist_arr: array
         Array of distances to loop over (pc)
- 
+
     evo_models: SPISEA evolution object
         Which evolution models to use
 
@@ -1656,7 +1777,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
         Mass sampling of isochrone, relative to original mass sampling
 
     filters: dictionary
-        Which filters to do the synthetic photometry on    
+        Which filters to do the synthetic photometry on
     """
     print( '**************************************')
     print( 'Start generating isochrones')
@@ -1701,7 +1822,7 @@ def mag_in_filter(star, filt):
     diff = np.diff(star_in_filter.binwave)
     diff = np.append(diff, diff[-1])
     star_flux = np.sum(star_in_filter.binflux * diff)
-    
+
     star_mag = -2.5 * math.log10(star_flux / filt.flux0) + filt.mag0
     return star_mag
 
@@ -1724,10 +1845,10 @@ def match_model_masses(isoMasses, starMasses):
 
     idx = np.where(dm_frac > 0.1)[0]
     indices[idx] = -1
-    
+
     return indices
 
-    
+
 def get_evo_model_by_string(evo_model_string):
     return getattr(evolution, evo_model_string)
 
@@ -1738,7 +1859,7 @@ def calc_ab_vega_filter_conversion(filt_str):
     AB and Vega magnitudes for a given filter:
     m_AB - m_vega
 
-    Note: this conversion is just the vega magnitude in 
+    Note: this conversion is just the vega magnitude in
     AB system
 
     Parameters:
@@ -1758,14 +1879,14 @@ def calc_ab_vega_filter_conversion(filt_str):
     filt_wave = filt.wave
     filt_mu = c / filt_wave
     s_filt = filt.throughput
-    
+
     # Interpolate the filter function, determine what the
     # filter function is at the exact sampling of the
     # vega spectrum (in freq space)
     filt_interp = scipy.interpolate.interp1d(filt_mu, s_filt, kind='linear', bounds_error=False,
                                                  fill_value=0)
     s_interp = filt_interp(vega_mu)
-    
+
     # Now for the m_ab calculation
     mu_diff = np.diff(vega_mu)
     numerator = np.sum(vega_flux_mu[:-1] * s_interp[:-1] * mu_diff)
@@ -1783,10 +1904,10 @@ def calc_ab_vega_filter_conversion(filt_str):
     #                                             fill_value=0)
     #s_interp = filt_interp(vega.wave)
 
-    # Calculate the numerator 
+    # Calculate the numerator
     #diff = np.diff(vega.wave)
     #numerator2 = np.sum((vega.wave[:-1]**2. / c) * vega.flux[:-1] * s_interp[:-1] * diff)
-    
+
     # Now we need to intergrate the filter response for the denominator
     #denominator2 = np.sum(s_interp[:-1] * diff)
 

From 3a9abd443a2d14cd6933c2cc0fcc9f4e89b4dde5 Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Thu, 15 May 2025 11:46:37 -0700
Subject: [PATCH 06/55] Added verbose control in IsochronePhot; Switched to
 super init

---
 spisea/synthetic.py | 98 ++++++++++++++++++++++++++++-----------------
 1 file changed, 61 insertions(+), 37 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 883fae76..c1d71741 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -146,7 +146,7 @@ class ResolvedCluster(Cluster):
     vebose: boolean
         True for verbose output.
     """
-    def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
+    def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=False,
                      seed=None):
         Cluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                              seed=seed)
@@ -587,7 +587,7 @@ def _remove_bad_systems(self, star_systems, compMass):
             idx = (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0)
 
         if self.verbose and sum(idx) != N_systems:
-            print( 'Found {0:d} stars out of mass range'.format(N_systems - len(idx)))
+            print( 'Found {0:d} stars out of mass range'.format(N_systems - sum(idx)))
 
         star_systems = star_systems[idx]
         N_systems = len(star_systems)
@@ -839,10 +839,11 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
                  wd_atm_func = default_wd_atm_func,
                  red_law=default_red_law, mass_sampling=1,
                  wave_range=[3000, 52000], min_mass=None, max_mass=None,
-                 rebin=True):
+                 rebin=True, verbose=False):
 
-
-        t1 = time.time()
+        self.verbose = verbose
+        if self.verbose:
+            t1 = time.time()
 
         c = constants
 
@@ -939,9 +940,10 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
         tab.meta['WAVEMAX'] = wave_range[1]
 
         self.points = tab
-
-        t2 = time.time()
-        print( 'Isochrone generation took {0:f} s.'.format(t2-t1))
+        
+        if self.verbose:
+            t2 = time.time()
+            print( 'Isochrone generation took {0:f} s.'.format(t2-t1))
         return
 
     def plot_HR_diagram(self, savefile=None):
@@ -1079,8 +1081,8 @@ def __init__(self, logAge, AKs, distance,
                  red_law=default_red_law, mass_sampling=1, iso_dir='./',
                  min_mass=None, max_mass=None, rebin=True, recomp=False,
                  filters=['ubv,U', 'ubv,B', 'ubv,V',
-                          'ubv,R', 'ubv,I']):
-
+                          'ubv,R', 'ubv,I'],
+                verbose=False):
         self.metallicity = metallicity
 
         # Make the iso_dir, if it doesn't already exist
@@ -1093,10 +1095,10 @@ def __init__(self, logAge, AKs, distance,
         # properly
         if metallicity == 0.0:
             save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_p00.fits'
-            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5))
+            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5))
 
             save_file_legacy = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}.fits'
-            self.save_file_legacy = save_file_legacy.format(iso_dir, logAge, AKs, str(distance).zfill(5))
+            self.save_file_legacy = save_file_legacy.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5))
         else:
             # Set metallicity flag
             if metallicity < 0:
@@ -1106,34 +1108,42 @@ def __init__(self, logAge, AKs, distance,
             metal_flag = int(abs(metallicity)*10)
 
             save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_{4}{5:2s}.fits'
-            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
-            self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
-
+            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(2))
+            self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(2))
+        
         # Expected filters
         self.filters = filters
 
         # Recalculate isochrone if save_file doesn't exist or recomp == True
-        file_exists = self.check_save_file(evo_model, atm_func, red_law)
+        file_exists = self.check_save_file(evo_model, atm_func, red_law, verbose=verbose)
 
         if (not file_exists) | (recomp==True):
             self.recalc = True
-            Isochrone.__init__(self, logAge, AKs, distance,
-                               metallicity=metallicity,
-                               evo_model=evo_model, atm_func=atm_func,
-                               wd_atm_func=wd_atm_func,
-                               wave_range=wave_range,
-                               red_law=red_law, mass_sampling=mass_sampling,
-                               min_mass=min_mass, max_mass=max_mass, rebin=rebin)
-            self.verbose = True
+            if verbose:
+                print(f'Generating new isochrone of log(t)={logAge:.2f}, AKs={AKs:.2f}, d={distance} pc')
+            # user_input = input(f"Isochrone file {self.save_file} does not exist or needs to be regenerated. Do you want to proceed? (yes/no): ").strip().lower()
+            # if user_input != 'yes':
+            #     print("Operation canceled by the user.")
+            #     return
+            super().__init__(logAge, AKs, distance,
+                             metallicity=metallicity,
+                             evo_model=evo_model, atm_func=atm_func,
+                             wd_atm_func=wd_atm_func,
+                             wave_range=wave_range,
+                             red_law=red_law, mass_sampling=mass_sampling,
+                             min_mass=min_mass, max_mass=max_mass, rebin=rebin, verbose=verbose)
 
             # Make photometry
             self.make_photometry(rebin=rebin, vega=vega)
+            if self.verbose:
+                print(f'Isochrone saved to {self.save_file}')
         else:
             self.recalc = False
             try:
                 self.points = Table.read(self.save_file)
             except:
                 self.points = Table.read(self.save_file_legacy)
+            # print(f'Isochrone loaded from existing file: {self.save_file}')
             # Add some error checking.
 
         return
@@ -1145,13 +1155,12 @@ def make_photometry(self, rebin=True, vega=vega):
         photometry.
 
         """
-        startTime = time.time()
-
-        meta = self.points.meta
+        if self.verbose:
+            startTime = time.time()
 
-        print( 'Making photometry for isochrone: log(t) = %.2f  AKs = %.2f  dist = %d' % \
-            (meta['LOGAGE'], meta['AKS'], meta['DISTANCE']))
-        print( '     Starting at: ', datetime.datetime.now(), '  Usually takes ~5 minutes')
+        # print('Making photometry for isochrone: log(t) = %.2f  AKs = %.2f  dist = %d' % \
+        #     (meta['LOGAGE'], meta['AKS'], meta['DISTANCE']))
+        # print( 'Starting at: ', datetime.datetime.now(), '  Usually takes ~5 minutes')
 
         npoints = len(self.points)
         verbose_fmt = 'M = {0:7.3f} Msun  T = {1:5.0f} K  m_{2:s} = {3:4.2f}'
@@ -1159,8 +1168,9 @@ def make_photometry(self, rebin=True, vega=vega):
         # Loop through the filters, get filter info, make photometry for
         # all stars in this filter.
         for ii in self.filters:
-            prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
-            print( prt_fmt.format(ii, time.time() - startTime))
+            if self.verbose:
+                prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
+                print( prt_fmt.format(ii, time.time() - startTime))
 
             filt = get_filter_info(ii, rebin=rebin, vega=vega)
             filt_name = get_filter_col_name(ii)
@@ -1171,19 +1181,21 @@ def make_photometry(self, rebin=True, vega=vega):
             self.points.add_column(mag_col)
 
             # Loop through each star in the isochrone and do the filter integration
-            print('Starting synthetic photometry')
+            if self.verbose:
+                print('Starting synthetic photometry')
             for ss in range(npoints):
                 star = self.spec_list[ss]  # These are already extincted, observed spectra.
                 star_mag = mag_in_filter(star, filt)
 
                 self.points[col_name][ss] = star_mag
 
-                if (self.verbose and (ss % 100) == 0):
+                if self.verbose and (ss % 100) == 0:
                     print( verbose_fmt.format(self.points['mass'][ss], self.points['Teff'][ss],
                                              filt_name, star_mag))
 
-        endTime = time.time()
-        print( '      Time taken: {0:.2f} seconds'.format(endTime - startTime))
+        if self.verbose:
+            endTime = time.time()
+            print( 'Time taken: {0:.2f} seconds'.format(endTime - startTime))
 
         if self.save_file != None:
             with warnings.catch_warnings():
@@ -1192,7 +1204,7 @@ def make_photometry(self, rebin=True, vega=vega):
 
         return
 
-    def check_save_file(self, evo_model, atm_func, red_law):
+    def check_save_file(self, evo_model, atm_func, red_law, verbose=False):
         """
         Check to see if save_file exists, as saved by the save_file
         and save_file_legacy objects. If the filename exists, check the
@@ -1214,6 +1226,18 @@ def check_save_file(self, evo_model, atm_func, red_law):
                 (tmp.meta['ATMFUNC'] == atm_func.__name__) &
                  (tmp.meta['REDLAW'] == red_law.name) ):
                 out_bool = True
+            else:
+                if verbose:
+                    print(f'Isochrone file {self.save_file} exists, but meta-data does not match.')
+                    if tmp.meta['EVOMODEL'] != type(evo_model).__name__:
+                        print(f'  EVOMODEL: {tmp.meta["EVOMODEL"]} != {type(evo_model).__name__}')
+                    if tmp.meta['ATMFUNC'] != atm_func.__name__:
+                        print(f'  ATMFUNC: {tmp.meta["ATMFUNC"]} != {atm_func.__name__}')
+                    if tmp.meta['REDLAW'] != red_law.name:
+                        print(f'  REDLAW: {tmp.meta["REDLAW"]} != {red_law.name}')
+        else:
+            if verbose:
+                print(f'Isochrone file {self.save_file} or {self.save_file_legacy} does not exist, generating new one.')
 
         return out_bool
 

From a452fa79892b540b894e361939a9bde78244c108 Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Wed, 8 Oct 2025 22:01:09 -0700
Subject: [PATCH 07/55] Raise informative error message for age and metallicity
 ranges

---
 spisea/evolution.py | 68 ++++++++++++++++++++++-----------------------
 1 file changed, 34 insertions(+), 34 deletions(-)

diff --git a/spisea/evolution.py b/spisea/evolution.py
index de5de196..82a74df8 100755
--- a/spisea/evolution.py
+++ b/spisea/evolution.py
@@ -131,12 +131,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # convert age (in yrs) to log scale and find nearest value in grid
         log_age = np.log10(age)
 
@@ -206,12 +206,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
@@ -437,12 +437,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
@@ -584,12 +584,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+            return
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds for evolution model. Available z-vals: {1}.'.format(z_defined, self.z_list))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds for evolution model. Available z-vals: {self.z_list}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
@@ -743,12 +743,12 @@ def isochrone(self, age=5.e7, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
@@ -1080,11 +1080,11 @@ def isochrone(self, age=1.e8, metallicity=0.0):
 
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
 
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
@@ -1273,11 +1273,11 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
 
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
@@ -1365,11 +1365,11 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if (log_age < self.age_list[0]) or (log_age > self.age_list[-1]):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if not z_defined in self.z_list:
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
@@ -1476,11 +1476,11 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         
         # check age and metallicity are within bounds
         if (log_age < self.age_list[0]) or (log_age > self.age_list[-1]):
-            logger.error('Requested age {0} is out of bounds.'.format(log_age))
-            
+            raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
+
         if not z_defined in self.z_list:
-            logger.error('Requested metallicity {0} is out of bounds.'.format(z_defined))
-        
+            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])

From 8704f540b8f7ee81fd3540a18945e0b02280c00e Mon Sep 17 00:00:00 2001
From: Lingfeng Wei <lingfeng-wei@outlook.com>
Date: Wed, 8 Oct 2025 22:03:54 -0700
Subject: [PATCH 08/55] Add confirmation before generating isochrone when
 verbose=True; Change metallicity flag to z*100 in file names

---
 spisea/synthetic.py | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index c1d71741..866bb6bd 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1105,11 +1105,11 @@ def __init__(self, logAge, AKs, distance,
                 metal_pre = 'm'
             else:
                 metal_pre = 'p'
-            metal_flag = int(abs(metallicity)*10)
+            metal_flag = int(abs(metallicity)*100)
 
             save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_{4}{5:2s}.fits'
-            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(2))
-            self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(2))
+            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(3))
+            self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(3))
         
         # Expected filters
         self.filters = filters
@@ -1121,10 +1121,12 @@ def __init__(self, logAge, AKs, distance,
             self.recalc = True
             if verbose:
                 print(f'Generating new isochrone of log(t)={logAge:.2f}, AKs={AKs:.2f}, d={distance} pc')
-            # user_input = input(f"Isochrone file {self.save_file} does not exist or needs to be regenerated. Do you want to proceed? (yes/no): ").strip().lower()
-            # if user_input != 'yes':
-            #     print("Operation canceled by the user.")
-            #     return
+
+                user_input = input(f"Isochrone file {self.save_file} does not exist or needs to be regenerated. Do you want to proceed? (yes/no): ").strip().lower()
+                if user_input != 'yes':
+                    print("Operation canceled by the user.")
+                    return
+
             super().__init__(logAge, AKs, distance,
                              metallicity=metallicity,
                              evo_model=evo_model, atm_func=atm_func,

From ff7015ba4d57329e370a372ad73bf0bc0000ed80 Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@laser.astro.berkeley.edu>
Date: Mon, 26 Jan 2026 15:03:47 -0800
Subject: [PATCH 09/55] adding euclid VIS

---
 docs/add_filters.rst        |   6 +-
 docs/filters.rst            |   5 +-
 filt_func/euclid/VIS.dat    | 551 ++++++++++++++++++++++++++++++++++++
 spisea/synthetic.py         |   1 +
 spisea/tests/test_models.py |   2 +-
 5 files changed, 560 insertions(+), 5 deletions(-)
 create mode 100755 filt_func/euclid/VIS.dat

diff --git a/docs/add_filters.rst b/docs/add_filters.rst
index 1bbfef12..4fe10c88 100644
--- a/docs/add_filters.rst
+++ b/docs/add_filters.rst
@@ -12,8 +12,10 @@ If the user wants to add new photometric filters to SPISEA, there are 4 main ste
      call the new function in ``filters.py`` when the new filter
      string is called.
   4) Edit the ``get_obs_str()`` function in ``synthetic.py`` to
-      convert between column name and filter string (e.g input string
-      for get_filter_info) for the new filters.
+     convert between column name and filter string (e.g input string
+     for get_filter_info) for the new filters.
+  5) Add the filter to the ``filt_list`` in the ``test_filters()`` function in ``tests/test_models.py`` to
+     ensure the filter can be loaded properly.
 
 Additional documentation on this is coming soon. In the meantime, let us know on the  Github `issue tracker
 <https://github.com/astropy/SPISEA/issues>`_ if you'd like to
diff --git a/docs/filters.rst b/docs/filters.rst
index ab2e5418..87bc99ab 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -83,9 +83,10 @@ Example: ``'decam,r'``
 
 **Euclid**
 
-`Euclid (NISP) space telescope filters <https://doi.org/10.5270/esa-kx8w57c>`_
+Euclid space telescope `NISP filters <https://doi.org/10.5270/esa-kx8w57c>`_ 
+and `VIS filter-free detector transmission curve <https://svo2.cab.inta-csic.es/svo/theory/fps/index.php?id=Euclid/VIS.vis>`_
 
-Filters: Y, J, H
+Filters: VIS, Y, J, H
 
 Example: ``'euclid,Y'``
 
diff --git a/filt_func/euclid/VIS.dat b/filt_func/euclid/VIS.dat
new file mode 100755
index 00000000..8071c831
--- /dev/null
+++ b/filt_func/euclid/VIS.dat
@@ -0,0 +1,551 @@
+4369.190 0.00056679011507854
+4379.190 0.00095861003123264
+4389.180 0.0014222192668852
+4399.180 0.0017743627364614
+4409.170 0.0017759292855133
+4419.170 0.0015893083675879
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+4449.150 0.0017004749033207
+4459.140 0.001630730073096
+4469.140 0.0021505801024037
+4479.130 0.0038159666691211
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+4529.100 0.0023998297521869
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+4549.090 0.0041725310261388
+4559.080 0.0031289801957178
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+4579.070 0.0019870963483393
+4589.070 0.002191420037652
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+4609.050 0.0011385280750117
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+4649.030 0.0011341370502031
+4659.020 0.0011462535246013
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+4679.010 0.0024726424098241
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+9696.060 0.0007481979450244
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+9716.050 0.00085253228420119
+9726.040 0.00086729775556006
+9736.040 0.00078571303618106
+9746.030 0.00087756426995614
+9756.030 0.00078327224179827
+9766.020 0.00071942994733045
+9776.010 0.00073511791287835
+9786.010 0.00069026505263581
+9796.000 0.00061793427523083
+9806.000 0.00052330574625916
+9815.990 0.0004866337237607
+9825.980 0.00051533510351816
+9835.980 0.0005196795904907
+9845.970 0.00044117052286289
+9855.970 0.00041505572377556
+9865.960 0.00040388144251169
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index d8f17d87..fa8220f6 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1695,6 +1695,7 @@ def get_obs_str(col):
                  'rubin_u':'rubin,u',
                  'rubin_z':'rubin,z',
                  'rubin_y':'rubin,y',
+                 'euclid_VIS':'euclid,VIS',
                  'euclid_Y':'euclid,Y',
                  'euclid_J':'euclid,J',
                  'euclid_H':'euclid,H'}
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index 78d8e9e1..4c1af45e 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -186,7 +186,7 @@ def test_filters():
                      'roman,wfi,f158', 'roman,wfi,f146', 'roman,wfi,f213',
                      'roman,wfi,f184', 'rubin,g', 'rubin,i', 'rubin,r',
                      'rubin,u', 'rubin,z', 'rubin,y',
-                     'euclid,Y', 'euclid,J', 'euclid,H']
+                     'euclid,VIS', 'euclid,Y', 'euclid,J', 'euclid,H']
 
     # Loop through filters to test that they work: get_filter_info
     for ii in filt_list:

From d8391c96bbd70e4d99375215cccde2ef08119756 Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@berkeley.edu>
Date: Mon, 26 Jan 2026 15:13:44 -0800
Subject: [PATCH 10/55] Update filters.rst

---
 docs/filters.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/filters.rst b/docs/filters.rst
index 87bc99ab..918f27f4 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -84,7 +84,7 @@ Example: ``'decam,r'``
 **Euclid**
 
 Euclid space telescope `NISP filters <https://doi.org/10.5270/esa-kx8w57c>`_ 
-and `VIS filter-free detector transmission curve <https://svo2.cab.inta-csic.es/svo/theory/fps/index.php?id=Euclid/VIS.vis>`_
+and `VIS single filter <https://svo2.cab.inta-csic.es/svo/theory/fps/index.php?id=Euclid/VIS.vis>`_
 
 Filters: VIS, Y, J, H
 

From d43fbf1138a784b1ac443ad57d77346e0eda500f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Sun, 1 Feb 2026 22:16:41 -0800
Subject: [PATCH 11/55] Passed all tests after merging with masked array
 companion mass update, except the model_young_cluster_object function in
 test_synthetic

---
 .gitignore                      |   5 +-
 spisea/ifmr.py                  |   2 +-
 spisea/imf/multiplicity.py      |  32 +--
 spisea/synthetic.py             |  34 ++--
 spisea/tests/test_exceptions.py |   8 +-
 spisea/tests/test_models.py     |  24 +--
 spisea/tests/test_reddening.py  |  23 ++-
 spisea/tests/test_synthetic.py  | 345 +++++++++++++++++++++++---------
 8 files changed, 311 insertions(+), 162 deletions(-)

diff --git a/.gitignore b/.gitignore
index 7909d367..b29e4f96 100755
--- a/.gitignore
+++ b/.gitignore
@@ -51,4 +51,7 @@ distribute-*.tar.gz
 
 # OS Generated Files
 .DS_Store
-._*
\ No newline at end of file
+._*
+
+# Test files generated
+spisea/tests/isochrones
diff --git a/spisea/ifmr.py b/spisea/ifmr.py
index 2b67ca7c..cafa66d6 100755
--- a/spisea/ifmr.py
+++ b/spisea/ifmr.py
@@ -771,7 +771,7 @@ def generate_death_mass(self, mass_array):
         output_array = np.zeros((2, len(mass_array)))
 
         #Random array to get probabilities for what type of object will form
-        random_array = self.rng.intergers(1, 1001, size = len(mass_array))
+        random_array = self.rng.integers(1, 1001, size = len(mass_array))
 
         codes = {'WD': 101, 'NS': 102, 'BH': 103}
         
diff --git a/spisea/imf/multiplicity.py b/spisea/imf/multiplicity.py
index 0d28ced6..685d5917 100755
--- a/spisea/imf/multiplicity.py
+++ b/spisea/imf/multiplicity.py
@@ -1,6 +1,7 @@
 import numpy as np
 import astropy.modeling
 from random import choice
+from scipy.stats import truncnorm
 
 defaultMF_amp = 0.44
 defaultMF_power = 0.51
@@ -249,29 +250,34 @@ def log_semimajoraxis(self, mass):
         
         Parameters
         ----------
-        mass : float
-            Mass of primary star
+        mass : array-like
+            Mass array of primary star
 
         Returns
         -------
-        log_semimajoraxis : float
+        log_semimajoraxis : array-like
             Log of the semimajor axis/separation between the stars in units of AU
         """
         a_mean_func = astropy.modeling.powerlaws.BrokenPowerLaw1D(amplitude=self.a_amp, x_break=self.a_break, alpha_1=self.a_slope1, alpha_2=self.a_slope2)
         log_a_mean = np.log10(a_mean_func(mass)) #mean log(a)
         log_a_std_func = astropy.modeling.models.Linear1D(slope=self.a_std_slope, intercept=self.a_std_intercept)
         log_a_std = log_a_std_func(np.log10(mass)) #sigma_log(a)
-        if mass >= 2.9:
-            log_a_std = log_a_std_func(np.log10(2.9)) #sigma_log(a)
-        if log_a_std < 0.1:
-            log_a_std = 0.1
-            
-        log_semimajoraxis = np.random.normal(log_a_mean, log_a_std)
-        while 10**log_semimajoraxis > 2000 or log_semimajoraxis < -2: #AU
-            log_semimajoraxis = np.random.normal(log_a_mean, log_a_std)
-            
+        
+        large_mass_idx = mass >= 2.9
+        log_a_std[large_mass_idx] = log_a_std_func(np.log10(2.9)) #sigma_log(a)
+        log_a_std = np.clip(log_a_std, 0.1, None)
+
+        # Trunc normal distribution between -2 and 2000 AU
+        log_a_lower = np.log10(0.01)
+        log_a_upper = np.log10(2000)
+
+        # Convert bounds to standard normal space
+        a_lower_std = (log_a_lower - log_a_mean) / log_a_std
+        a_upper_std = (log_a_upper - log_a_mean) / log_a_std
+
+        log_semimajoraxis = truncnorm.rvs(a_lower_std, a_upper_std, loc=log_a_mean, scale=log_a_std)            
         return log_semimajoraxis
-    
+
     def random_e(self, x):
         """
         Generate random eccentricity from the inverse of the CDF where the PDF is f(e) = 2e from Duchene and Kraus 2013
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 73f222a8..697e36c6 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -677,10 +677,6 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         ResolvedCluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                                      seed=seed)
 
-        # Set random seed, if desired
-        if seed is not None:
-            np.random.seed(seed=seed)
-
         # Extract the extinction law from the isochrone object
         redlaw_str = iso.points.meta['REDLAW']
         red_law = reddening.get_red_law(redlaw_str)
@@ -1134,24 +1130,17 @@ def __init__(self, logAge, AKs, distance,
         # For solar metallicity case, allow for legacy isochrones (which didn't have
         # metallicity tag since they were all solar metallicity) to be read
         # properly
-        if metallicity == 0.0:
-            save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_p00.fits'
-            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5))
+        
+        # Set save file name
+        metal_value = round(abs(metallicity), 2)
+        metal_sign = 'm' if metallicity < 0 else 'p'
+        self.save_file = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value:.2f}.fits'
 
-            save_file_legacy = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}.fits'
-            self.save_file_legacy = save_file_legacy.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5))
+        if metallicity == 0.0:            
+            self.save_file_legacy = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
         else:
-            # Set metallicity flag
-            if metallicity < 0:
-                metal_pre = 'm'
-            else:
-                metal_pre = 'p'
-            metal_flag = int(abs(metallicity)*100)
+            self.save_file_legacy = self.save_file
 
-            save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_{4}{5:2s}.fits'
-            self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(3))
-            self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(round(distance)).zfill(5), metal_pre, str(metal_flag).zfill(3))
-        
         # Expected filters
         self.filters = filters
 
@@ -1259,9 +1248,10 @@ def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
         # Loop through the filters, get filter info, make photometry for
         # all stars in this filter.
         for ii in comp_filters:
-            prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
-            print( prt_fmt.format(ii, time.time() - startTime))
-            
+            if self.verbose:
+                prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
+                print( prt_fmt.format(ii, time.time() - startTime))
+
             filt = get_filter_info(ii, rebin=rebin, vega=vega)
             filt_name = get_filter_col_name(ii)
 
diff --git a/spisea/tests/test_exceptions.py b/spisea/tests/test_exceptions.py
index 4996bb3c..4fe73e5f 100644
--- a/spisea/tests/test_exceptions.py
+++ b/spisea/tests/test_exceptions.py
@@ -34,10 +34,4 @@ def test_grid_number_exception():
 
     evolution.check_evo_grid_number(required_grid, models_dir)    
 
-    return
-
-
-
-        
-
-    
+    return
\ No newline at end of file
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index 78d8e9e1..2fd66f22 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -35,7 +35,7 @@ def test_evolution_models():
     evo_models = [evolution.MISTv1(version=1.2), evolution.MergedBaraffePisaEkstromParsec(), 
                       evolution.Parsec(), evolution.Baraffe15(), evolution.Ekstrom12(), evolution.Pisa()]
 
-    
+
     # Array of age_ranges for the specific evolution models to test
     age_vals = [age_all_MIST_arr, age_all_arr, age_all_arr, age_young_arr, age_young_arr, age_young_arr]
 
@@ -190,25 +190,19 @@ def test_filters():
 
     # Loop through filters to test that they work: get_filter_info
     for ii in filt_list:
-        try:
-            filt = synthetic.get_filter_info(ii, rebin=True, vega=vega)
-        except:
-            raise Exception('get_filter_info TEST FAILED for {0}'.format(ii))
+        filt = synthetic.get_filter_info(ii, rebin=True, vega=vega)
 
     print('get_filter_info pass')
     
     # Loop through filters to test that they work: get_obs_str
     for ii in filt_list:
-        try:
-            # Test going from col_name to obs_str
-            col_name = synthetic.get_filter_col_name(ii)
-            obs_str = synthetic.get_obs_str('m_{0}'.format(col_name))
-            # Does the obs_str work?
-            filt_info = synthetic.get_filter_info(obs_str)
-        except:
-            raise Exception('get_obs_str TEST FAILED for {0}'.format(ii)) 
-            
+        # Test going from col_name to obs_str
+        col_name = synthetic.get_filter_col_name(ii)
+        obs_str = synthetic.get_obs_str('m_{0}'.format(col_name))
+        # Does the obs_str work?
+        filt_info = synthetic.get_filter_info(obs_str)
+
     print('get_obs_str pass')
     print('Filters done')
 
-    return
+    return
\ No newline at end of file
diff --git a/spisea/tests/test_reddening.py b/spisea/tests/test_reddening.py
index d4b99d88..2df86a9a 100644
--- a/spisea/tests/test_reddening.py
+++ b/spisea/tests/test_reddening.py
@@ -214,15 +214,22 @@ def test_red_law_IsochronePhot():
         aks = aks_arr[ii]
 
         # Try to run isochrone phot
-        iso_test = synthetic.IsochronePhot(logAge, aks, dist, metallicity=0,
-                                               evo_model=evo_model, atm_func=atm_func,
-                                               red_law=redlaw, filters=filt_list,
-                                               min_mass=0.95, max_mass=1.05)
-        # Now remove the iso file to make sure we recalc each time
-        cmd = 'rm iso_6.70_*_08000_p00.fits'
-        os.system(cmd)
+        iso_test = synthetic.IsochronePhot(
+            logAge, 
+            aks, 
+            dist, 
+            metallicity=0,
+            evo_model=evo_model, 
+            atm_func=atm_func,
+            red_law=redlaw, 
+            filters=filt_list,
+            min_mass=0.95, 
+            max_mass=1.05,
+            iso_dir='isochrones/',
+            recomp=True
+        )
         print('----EL {0} works OK!-----'.format(redlaw_arr[ii]))
-        
+
     return
 
 def test_all_EL():
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index ec2628a2..45dbbe6f 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -46,6 +46,7 @@ def test_iso_wave():
     logAge = np.log10(5*10**6.) # Age in log(years)
     AKs = 0.8 # extinction in mags
     dist = 4000 # distance in parsec
+    iso_dir = 'isochrones/'
 
     # Define evolution/atmosphere models and extinction law (optional)
     evo_model = evolution.MergedBaraffePisaEkstromParsec() 
@@ -65,11 +66,17 @@ def test_iso_wave():
     # Make Isochrone object. Will use wave_range = [3000,52000].
     # Make sure range matches to resolution of atmosphere.
     wave_range1 = [3000, 52000]
-    my_iso = syn.IsochronePhot(logAge, AKs, dist,
-                            evo_model=evo_model, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=10, wave_range=wave_range1,
-                            recomp=True)
+    my_iso = syn.IsochronePhot(
+        logAge, AKs, dist,
+        evo_model=evo_model, 
+        atm_func=atm_func,
+        red_law=red_law, 
+        filters=filt_list,
+        mass_sampling=10, 
+        wave_range=wave_range1,
+        recomp=True, 
+        iso_dir=iso_dir
+    )
 
     test = my_iso.spec_list[0]
 
@@ -79,11 +86,19 @@ def test_iso_wave():
     # Now let's try changing the wave range. Is it carried through
     # properly?
     wave_range2 = [1200, 90000]
-    my_iso = syn.IsochronePhot(logAge, AKs, dist,
-                            evo_model=evo_model, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=10, wave_range=wave_range2,
-                            recomp=True)
+    my_iso = syn.IsochronePhot(
+        logAge, 
+        AKs, 
+        dist,
+        evo_model=evo_model, 
+        atm_func=atm_func,
+        red_law=red_law, 
+        filters=filt_list,
+        mass_sampling=10, 
+        wave_range=wave_range2,
+        recomp=True,
+        iso_dir=iso_dir
+    )
 
     test2 = my_iso.spec_list[0]
 
@@ -93,11 +108,19 @@ def test_iso_wave():
     # Does the error exception catch the bad wave_range?
     wave_range3 = [1200, 1000000]
     try:
-        my_iso = syn.IsochronePhot(logAge, AKs, dist,
-                                evo_model=evo_model, atm_func=atm_func,
-                                red_law=red_law, filters=filt_list,
-                                mass_sampling=10, wave_range=wave_range3,
-                                recomp=True)
+        my_iso = syn.IsochronePhot(
+            logAge, 
+            AKs, 
+            dist,
+            evo_model=evo_model,
+            atm_func=atm_func,
+            red_law=red_law,
+            filters=filt_list,
+            mass_sampling=10,
+            wave_range=wave_range3,
+            recomp=True, 
+            iso_dir=iso_dir
+        )
         print('WAVE TEST FAILED!!! Should have crashed here, wavelength range out of bounds')
         raise ValueError() 
     except:
@@ -111,17 +134,24 @@ def test_IsochronePhot(plot=False):
     distance = 4000
     filt_list = ['wfc3,ir,f127m', 'nirc2,J']
     mass_sampling=1
-    iso_dir = 'iso/'
+    iso_dir = 'isochrones/'
 
     evo_model = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
     redlaw = reddening.RedLawNishiyama09()
 
     startTime = time.time()
-    iso = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo_model,
-                                atm_func=atm_func, red_law=redlaw,
-                                filters=filt_list,
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso = syn.IsochronePhot(
+        logAge, 
+        AKs,
+        distance, 
+        evo_model=evo_model,
+        atm_func=atm_func,
+        red_law=redlaw,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
     endTime = time.time()
     print('IsochronePhot generated in: %d seconds' % (endTime - startTime))
     # Typically takes 120 seconds if file is regenerated.
@@ -142,35 +172,57 @@ def test_IsochronePhot(plot=False):
         iso.plot_mass_magnitude('mag160w')
 
     # Finally, let's test the isochronePhot file generation
-    assert os.path.exists('{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_p00.fits'.format(iso_dir, logAge,
-                                                                                AKs, str(distance).zfill(5)))
-    
+    metal_value = 0.
+    metal_sign = 'm' if metal_value < 0 else 'p'
+    assert os.path.exists(f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(distance).zfill(5)}_{metal_sign}{metal_value:.2f}.fits')
+
     # Check 1: If we try to remake the isochrone, does it read the file rather than
     # making a new one
-    iso_new = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo_model,
-                                atm_func=atm_func, red_law=redlaw,
-                                filters=filt_list,
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso_new = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo_model,
+        atm_func=atm_func,
+        red_law=redlaw,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     assert iso_new.recalc == False
     
     # Check 2: Confirm that adding a new column to an existing isochrone works properly.
     #    Does the new filter get added to the isochrone? And the old ones still there?
     #    Does the computed data for the new filter match the same result if you fully regenerate the isochrone?
-    iso_new_addfilt = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo_model,
-                                atm_func=atm_func, red_law=redlaw,
-                                filters=filt_list+['2mass,Ks'],
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso_new_addfilt = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance, 
+        evo_model=evo_model,
+        atm_func=atm_func, 
+        red_law=redlaw,
+        filters=filt_list+['2mass,Ks'],
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     assert iso_new_addfilt.recalc == False
     assert 'm_2mass_Ks' in iso_new_addfilt.points.colnames
     assert 'm_nirc2_J' in iso_new_addfilt.points.colnames
     
-    iso_new_3filt = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo_model,
-                                atm_func=atm_func, red_law=redlaw,
-                                filters=filt_list+['2mass,Ks'],
-                                mass_sampling=mass_sampling, iso_dir=iso_dir,
-                                recomp=True)
+    iso_new_3filt = syn.IsochronePhot(
+        logAge, 
+        AKs,
+        distance, 
+        evo_model=evo_model,
+        atm_func=atm_func,
+        red_law=redlaw,
+        filters=filt_list+['2mass,Ks'],
+        mass_sampling=mass_sampling,
+        recomp=True,
+        iso_dir=iso_dir
+    )
     np.testing.assert_almost_equal(iso_new_addfilt.points['m_2mass_Ks'], iso_new_3filt.points['m_2mass_Ks'])
     assert iso_new_3filt.recalc==True
 
@@ -179,26 +231,47 @@ def test_IsochronePhot(plot=False):
     evo2 = evolution.MergedBaraffePisaEkstromParsec()
     mass_sampling=20
 
-    iso_new = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo2,
-                                atm_func=atm_func, red_law=redlaw,
-                                filters=filt_list,
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso_new = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo2,
+        atm_func=atm_func,
+        red_law=redlaw,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     assert iso_new.recalc == True
 
     redlaw2 = reddening.RedLawHosek18b()
-    iso_new = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo2,
-                                atm_func=atm_func, red_law=redlaw2,
-                                filters=filt_list,
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso_new = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo2,
+        atm_func=atm_func,
+        red_law=redlaw2,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     assert iso_new.recalc == True
 
     atm2 = atmospheres.get_castelli_atmosphere
-    iso_new = syn.IsochronePhot(logAge, AKs, distance, evo_model=evo2,
-                                atm_func=atm2, red_law=redlaw2,
-                                filters=filt_list,
-                                mass_sampling=mass_sampling, iso_dir=iso_dir)
+    iso_new = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo2,
+        atm_func=atm2,
+        red_law=redlaw2,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     assert iso_new.recalc == True
 
@@ -211,6 +284,7 @@ def test_ResolvedCluster():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling=5
+    iso_dir = 'isochrones/'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -222,10 +296,17 @@ def test_ResolvedCluster():
 
     red_law = reddening.RedLawNishiyama09()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
 
@@ -287,7 +368,7 @@ def test_ResolvedCluster():
     plt.plot(iso.points['m_nirc2_J'] - iso.points['m_nirc2_Kp'], iso.points['m_nirc2_J'], 'c-')
     plt.gca().invert_yaxis()
     plt.xlabel('J - Kp (mag)')
-    plt.ylabel('J (mag')
+    plt.ylabel('J (mag)')
 
     # Plot a mass-magnitude relationship.
     plt.figure(2)
@@ -317,6 +398,7 @@ def test_ResolvedClusterDiffRedden():
     cluster_mass = 10**5.
     deltaAKs = 0.05
     mass_sampling=5
+    iso_dir = 'isochrones/'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -328,10 +410,17 @@ def test_ResolvedClusterDiffRedden():
 
     red_law = reddening.RedLawNishiyama09()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                                mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
 
@@ -434,6 +523,7 @@ def test_ifmr_multiplicity():
     distance = 1000
     cluster_mass = 1e6
     mass_sampling = 5
+    iso_dir = 'isochrones/'
 
     # Test all filters
     filt_list = ['nirc2,Kp', 'nirc2,H', 'nirc2,J']
@@ -446,10 +536,17 @@ def test_ifmr_multiplicity():
 
     red_law = reddening.RedLawNishiyama09()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
 
@@ -519,28 +616,46 @@ def test_metallicity():
     atm_func = atmospheres.get_phoenixv16_atmosphere
     red_law = reddening.RedLawHosek18b()
     filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m']
+    iso_dir = 'isochrones/'
 
     # Start with a solar metallicity isochrone    
-    metallicity= 0.0
+    metallicity= 0.
+    metal_sign = 'm' if metallicity < 0 else 'p'
 
     # Make Isochrone object, with high mass_sampling to decrease compute time
-    my_iso = syn.IsochronePhot(logAge, AKs, dist, metallicity=metallicity,
-                            evo_model=evo_model, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=10)
-
+    my_iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        dist,
+        metallicity=metallicity,
+        evo_model=evo_model,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=10,
+        iso_dir=iso_dir
+    )
+    
     # Test isochrone properties
     assert my_iso.points.meta['METAL_IN'] == 0.0
-    assert os.path.exists('iso_6.70_0.80_04000_p00.fits')
+    assert os.path.exists(f'{iso_dir}/iso_6.70_0.80_04000_p0.00.fits')
 
     # Now for non-solar metallicity
     metallicity= -1.5
 
     # Make Isochrone object, with high mass_sampling to decrease compute time
-    my_iso = syn.IsochronePhot(logAge, AKs, dist, metallicity=metallicity,
-                            evo_model=evo_model, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=10)
+    my_iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        dist,
+        metallicity=metallicity,
+        evo_model=evo_model,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=10,
+        iso_dir=iso_dir
+    )
 
     # MIST model sub-directory names changed in SPISEA v2.1.4 update;
     # changing what "metal_act" value was. version 1 of MIST grid
@@ -555,12 +670,12 @@ def test_metallicity():
         metal_act = np.log10(0.00047 / 0.0142) # For Mist isochrones
     else:
         metal_act = np.log10(0.00045 / 0.0142) # For Mist isochrones
-        
+
     # Test isochrone properties
     assert my_iso.points.meta['METAL_IN'] == -1.5
     assert np.isclose(my_iso.points.meta['METAL_ACT'], metal_act)
-    assert os.path.exists('iso_6.70_0.80_04000_m15.fits')
-    
+    assert os.path.exists(f'{iso_dir}/iso_6.70_0.80_04000_m1.50.fits')
+
     return
 
 def test_cluster_mass():
@@ -570,6 +685,7 @@ def test_cluster_mass():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling = 5
+    iso_dir = 'isochrones/'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -581,10 +697,17 @@ def test_cluster_mass():
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawHosek18b()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
 
@@ -651,6 +774,7 @@ def test_keep_low_mass_stars():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling = 5
+    iso_dir = 'isochrones/'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -660,10 +784,17 @@ def test_keep_low_mass_stars():
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawHosek18b()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     # Get the minimum mass in the isochrones. This should be the lowest
     # mass psosbile when keep_low_mass_stars == False.
@@ -707,6 +838,7 @@ def test_compact_object_companions():
     distance = 4000
     cluster_mass = 10**4.
     mass_sampling=5
+    iso_dir = 'isochrones/'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -718,10 +850,17 @@ def test_compact_object_companions():
 
     red_law = reddening.RedLawNishiyama09()
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list,
-                            mass_sampling=mass_sampling)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=mass_sampling,
+        iso_dir=iso_dir
+    )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
     
@@ -748,6 +887,7 @@ def time_test_cluster():
     AKs = 2.7
     distance = 4000
     cluster_mass = 10**4
+    iso_dir = 'isochrones/'
 
     startTime = time.time()
     
@@ -756,9 +896,16 @@ def time_test_cluster():
     red_law = reddening.RedLawNishiyama09()
     filt_list = ['nirc2,J', 'nirc2,Kp']
     
-    iso = syn.IsochronePhot(logAge, AKs, distance,
-                            evo_model=evo, atm_func=atm_func,
-                            red_law=red_law, filters=filt_list)
+    iso = syn.IsochronePhot(
+        logAge,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        iso_dir=iso_dir
+    )
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
 
     imf_limits = np.array([0.07, 0.5, 150])
@@ -782,7 +929,14 @@ def model_young_cluster_object(resolved=False):
     imf_in = imf.Kroupa_2001(multiplicity=multi)
     evo = evolution.MergedPisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
-    iso = syn.Isochrone(log_age, AKs, distance, evo, mass_sampling=10)
+    iso = syn.Isochrone(
+        log_age, 
+        AKs, 
+        distance, 
+        evo_model=evo, 
+        atm_func=atm_func,
+        mass_sampling=10
+    )
 
     if resolved:
         cluster = syn.ResolvedCluster(iso, imf_in, cluster_mass)
@@ -804,17 +958,18 @@ def model_young_cluster_object(resolved=False):
     plt.plot(wave, flux, 'k.')
 
     return
-    
+
 def time_test_mass_match():
     log_age = 6.7
     AKs = 2.7
     distance = 4000
     cluster_mass = 5e3
-    
+    iso_dir = 'isochrones/'
+
     imf_in = imf.Kroupa_2001(multiplicity=None)
 
     start_time = time.time()
-    iso = syn.IsochronePhot(log_age, AKs, distance)
+    iso = syn.IsochronePhot(log_age, AKs, distance, iso_dir=iso_dir)
     iso_masses = iso.points['mass']
     print('Generated iso masses in {0:.0f} s'.format(time.time() - start_time))
 
@@ -1051,4 +1206,4 @@ def test_Raithel18_IFMR_5():
 
     assert len(WD_idx) == 2 , "There are not the right number of WDs for the Raithel18 IFMR"
 
-    return
+    return
\ No newline at end of file

From 1279e317966529dcb92dff13bcc82e5f82419f18 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 2 Feb 2026 13:48:07 -0800
Subject: [PATCH 12/55] Fixed evo model error in test, passed all tests

---
 spisea/tests/test_synthetic.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 45dbbe6f..ada9544f 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -924,10 +924,10 @@ def model_young_cluster_object(resolved=False):
     AKs = 0.1
     distance = 8000.0
     cluster_mass = 10000.
-    
+
     multi = multiplicity.MultiplicityUnresolved()
     imf_in = imf.Kroupa_2001(multiplicity=multi)
-    evo = evolution.MergedPisaEkstromParsec()
+    evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
     iso = syn.Isochrone(
         log_age, 

From 9d051cbabe09da0ecfd6c9024f209108e8dea87c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Thu, 5 Feb 2026 22:58:01 -0800
Subject: [PATCH 13/55] Nothing but remove trailing white spaces

---
 spisea/imf/imf.py | 142 +++++++++++++++++++++++-----------------------
 1 file changed, 71 insertions(+), 71 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 5df02afa..2c493f54 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -4,7 +4,7 @@
 # Original code was taken from libimf package written by Jan Pflamm-Altenburg
 # and has been modified only marginally. The libimf code was licensed under
 # a GNU General Public License.
-# 
+#
 # When I use this code, I should cite Pflamm-Altenburg & Kroupa 2006
 #
 # Unfortunately, the code was almost completely un-commented, so all
@@ -22,29 +22,29 @@
 
 class IMF(object):
     """
-    The IMF base class. The mass sampling and multiplicity 
-    implementation is here. 
+    The IMF base class. The mass sampling and multiplicity
+    implementation is here.
 
     Notes
     -----
-    Code author: J. Lu. 
+    Code author: J. Lu.
 
     Original code was taken from libimf package written by Jan Pflamm-Altenburg
     (`Pflamm-Altenburg & Kroupa 2006 <https://ui.adsabs.harvard.edu/abs/2006MNRAS.373..295P/abstract>`_)
     and has been modified only marginally, though more convinient and general purpose
     functions have been added. The libimf code was licensed under
-    a GNU General Public License. 
+    a GNU General Public License.
 
 
     Parameters
     ----------
     massLimits : 2 element array; optional
-        Define the minimum and maximum stellar masses in the IMF, in 
-        solar masses. First element is taken as the min, second element 
+        Define the minimum and maximum stellar masses in the IMF, in
+        solar masses. First element is taken as the min, second element
         the max (e.g. `massLimits` = [min_mass, max_mass]).
 
     multiplicity : Multiplicity object or None
-        If None, no multiplicity is assumed. Otherwise, use 
+        If None, no multiplicity is assumed. Otherwise, use
         multiplicity object to create multiple star systems.
     """
     def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None):
@@ -52,19 +52,19 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         self._mass_limits = np.atleast_1d(massLimits)
         self.seed = seed
         self.rng = np.random.default_rng(seed)
-        
+
         if multiplicity:
             self.make_multiples = True
         else:
             self.make_multiples = False
- 
+
         return
-            
+
 
     def generate_cluster(self, totalMass):
         """
         Generate a cluster of stellar systems with the specified IMF.
-        
+
         Randomly sample from an IMF with specified mass
         limits until the desired total mass is reached. The maximum
         stellar mass is not allowed to exceed the total cluster mass.
@@ -96,8 +96,8 @@ def generate_cluster(self, totalMass):
             system and False for each single star.
 
         companionMasses : numpy float array
-            List of 
-        
+            List of
+
         """
         initial_mass_limit = self._mass_limits[-1]
 
@@ -124,19 +124,19 @@ def generate_cluster(self, totalMass):
         # the desired total cluster mass.
         totalMassTally = 0
         loopCnt = 0
-        
+
         # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
             uniX = self.rng.random(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
-            
+
             # Testing for Nans produced in masses
             test = np.isnan(newMasses)
             if np.sum(test) > 0:
                 raise ValueError('Nan detected in cluster mass')
-            
+
             # Dealing with multiplicity
             if self._multi_props:
                 # newCompMasses = np.empty((len(newMasses),), dtype=object)
@@ -163,7 +163,7 @@ def generate_cluster(self, totalMass):
             # print('Time taken for while loop: ', end_while - start_while)
             # Append to our primary masses array
             masses = np.append(masses, newMasses)
-            
+
             if (loopCnt >= 0):
                 log.info('sample_imf: Loop %d added %.2e Msun to previous total of %.2e Msun' %
                          (loopCnt, newTotalMassTally, totalMassTally))
@@ -171,27 +171,27 @@ def generate_cluster(self, totalMass):
             totalMassTally += newTotalMassTally
             newStarCount = mean_number * 0.1  # increase by 20% each pass
             loopCnt += 1
-        
+
         # Make a running sum of the system masses
         if self._multi_props:
             # Concatenate the companion masses
             if len(compMasses) > 1:
                 max_cols = max(compMass.shape[1] for compMass in compMasses)
-                
+
                 # Pad each array to have the same number of columns
                 padded_arrays = [
                     np.ma.masked_all((compMass.shape[0], max_cols)) for compMass in compMasses
                 ]
-                
+
                 for i, compMass in enumerate(compMasses):
                     padded_arrays[i][:, :compMass.shape[1]] = compMass
-                
+
                 # Vertically stack the padded arrays
                 compMasses = np.ma.vstack(padded_arrays)
-            
+
             else:
                 compMasses = compMasses[0]
-            
+
             # Make a running sum of the system masses
             massCumSum = systemMasses.cumsum()
         else:
@@ -214,7 +214,7 @@ def generate_cluster(self, totalMass):
         self._mass_limits[-1] = initial_mass_limit
 
         return (masses, isMultiple, compMasses, systemMasses)
-        
+
     def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
         """
         Helper function to calculate multiples more efficiently.
@@ -222,8 +222,8 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
         """
         # Copy over the primary masses. Eventually add the companions.
         newSystemMasses = newMasses.copy()
-        
-        # Identify multiple systems, calculate number of companions for each 
+
+        # Identify multiple systems, calculate number of companions for each
         multiple_idx = np.where(newIsMultiple)[0]
         comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
         if self._multi_props.companion_max:
@@ -236,21 +236,21 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
         comp_unique = np.unique(comp_nums)
         comp_indices = [np.where(comp_nums == i)[0] for i in comp_unique]
         compMasses = np.zeros((len(newMasses), max(comp_unique)))
-        
+
         for comp_num, comp_index in zip(comp_unique, comp_indices):
             # Calculate masses of companions
             q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
             m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
             compMasses[multiple_idx[comp_index], :comp_num] = m_comp
-        
+
         # Mask out companions that are less than the minimum mass
         compMasses = np.ma.MaskedArray(compMasses, mask=compMasses < self._mass_limits[0])
         newSystemMasses[multiple_idx] += compMasses[multiple_idx].sum(axis=1)
         newIsMultiple = np.any(~compMasses.mask, axis=1)
-        
+
         return compMasses, newSystemMasses, newIsMultiple
-        
-    
+
+
 class IMF_broken_powerlaw(IMF):
     """
     Initialize a multi-part power-law with N parts. Each part of the
@@ -263,7 +263,7 @@ class IMF_broken_powerlaw(IMF):
     Parameters
     ----------
     mass_limits : numpy array
-        Array of length (N + 1) with lower and upper limits of 
+        Array of length (N + 1) with lower and upper limits of
         the power-law segments.
 
     powers : numpy array
@@ -271,7 +271,7 @@ class IMF_broken_powerlaw(IMF):
         power-law segment.
 
     multiplicity : Multiplicity object or None
-        If None, no multiplicity is assumed. Otherwise, use 
+        If None, no multiplicity is assumed. Otherwise, use
         multiplicity object to create multiple star systems.
     """
     def __init__(self, mass_limits, powers, multiplicity=None, seed=None):
@@ -316,7 +316,7 @@ def xi(self, m):
         xi - probability of measuring that mass.
         """
         returnFloat = type(m) == float
-        
+
         m = np.atleast_1d(m)
 
         # Temporary arrays
@@ -333,7 +333,7 @@ def xi(self, m):
             # Maybe we are all done?
             if len(idx) == 0:
                 break
-            
+
             m_tmp = m[idx]
             aux_tmp = aux[idx]
 
@@ -346,7 +346,7 @@ def xi(self, m):
             z *= delta(m - self._m_limits_high[i])
 
         xi = self.k * z * y
-        
+
         if returnFloat:
             return xi[0]
         else:
@@ -374,7 +374,7 @@ def m_xi(self, m):
             # Maybe we are all done?
             if len(idx) == 0:
                 break
-            
+
             m_tmp = m[idx]
             aux_tmp = aux[idx]
 
@@ -387,7 +387,7 @@ def m_xi(self, m):
             z *= delta(m - self._m_limits_high[i])
 
         mxi = self.k * z * y
-        
+
         if returnFloat:
             return mxi[0]
         else:
@@ -395,23 +395,23 @@ def m_xi(self, m):
 
 
     def getProbabilityBetween(self, massLo, massHi):
-        """Return the integrated probability between some low and high 
+        """Return the integrated probability between some low and high
         mass value.
         """
         return self.int_xi(massLo, massHi)
 
     def int_xi(self, massLo, massHi):
-        """Return the integrated probability between some low and high 
+        """Return the integrated probability between some low and high
         mass value.
         """
         return self.prim_xi(massHi) - self.prim_xi(massLo)
-    
+
     def getMassBetween(self, massLo, massHi):
-        """Return the integrated mass between some low and high 
+        """Return the integrated mass between some low and high
         mass value.
         """
         return self.int_mxi(massLo, massHi)
-    
+
     def int_mxi(self, massLo, massHi):
         """Return the integrated total mass between some low and high stellar
         mass value. Be sure to normalize the IMF instance beforehand.
@@ -433,7 +433,7 @@ def prim_xi(self, a):
             t3 = prim_power(self._m_limits_low, self._powers)
             y1 = (t1 * (t2 - t3)).sum()
 
-            t1 = gamma_closed(a[i], self._m_limits_low, self._m_limits_high) 
+            t1 = gamma_closed(a[i], self._m_limits_low, self._m_limits_high)
             t1 *= self.coeffs
             t2 = prim_power(a[i], self._powers)
             t3 = prim_power(self._m_limits_low, self._powers)
@@ -451,7 +451,7 @@ def prim_mxi(self, a):
         Helper function
         """
         returnFloat = type(a) == float
-        
+
         a = np.atleast_1d(a)
         val = np.zeros(len(a), dtype=float)
 
@@ -460,8 +460,8 @@ def prim_mxi(self, a):
             t2 = prim_power(self._m_limits_high, self._powers+1)
             t3 = prim_power(self._m_limits_low, self._powers+1)
             y1 = (t1 * (t2 - t3)).sum()
-            
-            t1 = gamma_closed(a[i], self._m_limits_low, self._m_limits_high) 
+
+            t1 = gamma_closed(a[i], self._m_limits_low, self._m_limits_high)
             t1 *= self.coeffs
             t2 = prim_power(a[i], self._powers+1)
             t3 = prim_power(self._m_limits_low, self._powers+1)
@@ -481,7 +481,7 @@ def normalize(self, Mcl, Mmin=None, Mmax=None):
         """
         self.k = 1.0
         self.Mcl = Mcl
-        
+
         if Mmax == None:
             Mmax = self._m_limits_high[-1]
 
@@ -491,7 +491,7 @@ def normalize(self, Mcl, Mmin=None, Mmax=None):
 
         if Mmax > Mcl:
             Mmax = Mcl
-            
+
         if Mmax > self._m_limits_high[-1]:
             Mmax = self._m_limits_high[-1]
 
@@ -500,7 +500,7 @@ def normalize(self, Mcl, Mmin=None, Mmax=None):
 
         self.norm_Mmin = Mmin
         self.norm_Mmax = Mmax
-        
+
         self.k = Mcl / self.int_mxi(self.norm_Mmin, self.norm_Mmax)
         self.lamda = self.int_xi_cl(self._m_limits_low[0], self._mass_limits)
 
@@ -519,7 +519,7 @@ def norm_cl_wk04(self, Mcl, Mmax=None, Mmin=None):
 
         if Mmax > Mcl:
             Mmax = Mcl
-            
+
         if Mmax > self._m_limits_high[-1]:
             Mmax = self._m_limits_high[-1]
 
@@ -587,24 +587,24 @@ def dice_star_cl(self, r):
         returnFloat = type(r) == float
         r = np.atleast_1d(r)  # Make sure it is an array
 
-        x = r * self.lamda[-1] 
+        x = r * self.lamda[-1]
         y = np.zeros_like(r)
         z = np.ones_like(r)
 
         # Loop through the different parts of the power law.
         for i in range(self.nterms): #-----For i = 0 --> n, where n is the number of intervals
             aux = x - self.lamda[i] #---Should this be i - 1?
-            
+
             # Only continue for those entries that are in later segments
             idx = aux >= 0
 
             # Maybe we are all done?
             if sum(idx) == 0:
                 break
-            
+
             x_tmp = x[idx]
             aux_tmp = aux[idx]
-            
+
             t1 = aux_tmp / (self.coeffs[i] * self.k)
             t1 += prim_power(self._m_limits_low[i], self._powers[i])
             y_i = gamma_closed(x_tmp, self.lamda[i], self.lamda[i+1])
@@ -684,7 +684,7 @@ def __init__(self, multiplicity=None):
                                      multiplicity=multiplicity)
 
 ##################################################
-# 
+#
 # Generic functions -- see if we can move these up.
 #
 ##################################################
@@ -708,7 +708,7 @@ def prim_power(m, power):
     valid_idx = power != -1
     val[valid_idx] = (m[valid_idx]**z[valid_idx]) / z[valid_idx]
     val[~valid_idx] = np.log(m[~valid_idx])
-    
+
     if returnFloat:
         return val[0]
     else:
@@ -716,7 +716,7 @@ def prim_power(m, power):
 
 def inv_prim_power(x, power):
     """
-    returns ((1+power) * x)**(1.0 / (1 + power)) and handles the case 
+    returns ((1+power) * x)**(1.0 / (1 + power)) and handles the case
     when power == -1.
     """
     returnFloat = (type(x) == float) and (type(power) == float)
@@ -731,7 +731,7 @@ def inv_prim_power(x, power):
 
     if x.shape != power.shape:
         raise ValueError('spisea.imf.inv_prim_power: Dimension mismatch, x and power must have the same shape')
-    
+
     z = 1.0 + power
     val = np.empty_like(x)
     valid_idx = power != -1
@@ -742,7 +742,7 @@ def inv_prim_power(x, power):
         return val[0]
     else:
         return val
-    
+
 
 def log_normal(m, mean_logm, sigma_logm):
     returnFloat = (type(m) == float) and (type(mean_logm) == float) and \
@@ -754,7 +754,7 @@ def log_normal(m, mean_logm, sigma_logm):
 
     z = np.log10(m) - mean_logm
     val = np.exp(-z**2 / (2.0 * sigma_logm**2)) / m
-    
+
     if returnFloat:
         return val[0]
     else:
@@ -770,7 +770,7 @@ def prim_log_normal(m, mean_logm, sigma_logm):
 
     mu = (np.log10(m) - mean_logm) / (1.4142135623731 * sigma_logm)
     val = 2.88586244942136 * sigma_logm * error(mu)
-    
+
     if returnFloat:
         return val[0]
     else:
@@ -783,10 +783,10 @@ def inv_prim_log_normal(x, mean_logm, sigma_logm):
     m = np.atleast_1d(m)
     mean_logm = np.atleat_1d(mean_logm)
     sigma_logm = np.atleat_1d(sigma_logm)
-    
+
     mu = inv_error(0.346516861952484 * x / sigma_logm)
     val = 10.0**(1.4142135623731 * sigma_logm * mu + mean_logm)
-    
+
     if returnFloat:
         return val[0]
     else:
@@ -802,7 +802,7 @@ def mlog_normal(x, mean_logm, sigma_logm):
 
     z = np.log10(m) - mean_logm
     val = np.exp(-z**2 / (2.0 * sigma_logm**2))
-    
+
     if returnFloat:
         return val[0]
     else:
@@ -823,12 +823,12 @@ def prim_mlog_normal(x, mean_logm, sigma_logm):
 
     val = error(eta)
     val *= 2.88586244942136 * sigma_logm * np.exp(2.30258509299405 * t1)
-    
+
     if returnFloat:
         return val[0]
     else:
         return val
-    
+
 
 def theta_closed(x):
     """
@@ -878,7 +878,7 @@ def delta(x):
 
 def gamma_closed(m, left, right):
     """
-    
+
     """
     return theta_closed(m - left) * theta_closed(right - m)
 
@@ -886,7 +886,7 @@ def gamma_closed(m, left, right):
 def error(x):
     x2 = x**2
     ax2 = 0.140012288686666 * x2
-    
+
     val = np.sqrt(1.0 - np.exp(-x2*(1.27323954473516+ax2)/(1+ax2)))
 
     if x >=0:
@@ -899,7 +899,7 @@ def inv_error(x):
     lnx2 = np.log(1.0 - x2)
     aux = 4.54688497944829 + (lnx2 / 2.0)
     y = -aux + np.sqrt(aux**2 - (lnx2 / 0.140012288686666))
-    
+
     val = np.sqrt(y)
 
     if x>=0:

From 4cccd8c02d0e6b13741058af9aa3ce08c0bae697 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Fri, 6 Feb 2026 11:09:44 -0800
Subject: [PATCH 14/55] Complete missing docstring

---
 spisea/imf/imf.py | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 2c493f54..8dfc0e64 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -89,14 +89,17 @@ def generate_cluster(self, totalMass):
         Returns
         -------
         masses : numpy float array
-            List of primary star masses.
+            Array of primary star masses.
 
         isMultiple : numpy boolean array
-            List of booleans with True for each primary star that is in a multiple
+            Array of booleans with True for each primary star that is in a multiple
             system and False for each single star.
 
-        companionMasses : numpy float array
-            List of
+        companionMasses : numpy masked array
+            Masked array of companion masses. Each row corresponds to a primary star, and each column corresponds to a companion. The mask is True for entries that are not valid companions (e.g. for single stars or for companions that are below the minimum mass limit).
+
+        systemMasses : numpy float array
+            Array of total system masses (primary + companions) for each primary star.
 
         """
         initial_mass_limit = self._mass_limits[-1]

From 3237c57edc6e9226eab2233b936b0f438d373a92 Mon Sep 17 00:00:00 2001
From: Rocketpack23 <apusack@gmail.com>
Date: Wed, 11 Feb 2026 13:36:18 -0800
Subject: [PATCH 15/55] Added IRTF NSFCam L filter, updated filters.py and
 synthetic.py

---
 filt_func/nsfcam/L.dat | 390 +++++++++++++++++++++++++++++++++++
 spisea/filters.py      |  86 ++++----
 spisea/synthetic.py    | 446 ++++++++++++++++-------------------------
 3 files changed, 606 insertions(+), 316 deletions(-)
 create mode 100755 filt_func/nsfcam/L.dat

diff --git a/filt_func/nsfcam/L.dat b/filt_func/nsfcam/L.dat
new file mode 100755
index 00000000..43589640
--- /dev/null
+++ b/filt_func/nsfcam/L.dat
@@ -0,0 +1,390 @@
+30156.8 0.000962257
+30175 0.00120592
+30193.2 0.00134921
+30211.5 0.00127125
+30229.7 0.00150251
+30248 0.00161243
+30266.3 0.00188732
+30284.7 0.00170279
+30303 0.00204206
+30321.4 0.00192571
+30339.8 0.00215411
+30358.2 0.0022676
+30376.7 0.00244951
+30395.1 0.00242066
+30413.6 0.0025301
+30432.1 0.00248027
+30450.7 0.0023284
+30469.2 0.00224257
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+30506.4 0.0024693
+30525 0.00250125
+30543.7 0.00249219
+30562.3 0.00242495
+30581 0.00247026
+30599.8 0.00256109
+30618.5 0.00265122
+30637.3 0.00268054
+30656 0.0026195
+30674.8 0.00252914
+30693.7 0.0025599
+30712.5 0.00271273
+30731.4 0.00289178
+30750.3 0.0028379
+30769.2 0.0027976
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+30807.1 0.00294924
+30826.1 0.00277042
+30845.2 0.00315022
+30864.2 0.00310421
+30883.3 0.0032618
+30902.3 0.00327802
+30921.5 0.00363994
+30940.6 0.00354338
+30959.8 0.00367117
+30978.9 0.00364733
+30998.1 0.00382757
+31017.4 0.00397182
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+31094.5 0.00489855
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+31133.3 0.00551271
+31152.6 0.00583959
+31172.1 0.00608921
+31191.5 0.00644302
+31211 0.00705314
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+31705.8 0.100346
+31725.9 0.115176
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+32010.2 0.646355
+32030.7 0.69369
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+32133.7 0.865207
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+34459 0.922568
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+34626 0.925369
+34650 0.926424
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+34698.1 0.927742
+34722.2 0.927231
+34746.4 0.928697
+34770.5 0.928282
+34794.7 0.928515
+34818.9 0.928225
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+34940.6 0.933056
+34965 0.931511
+34989.5 0.93317
+35014 0.932156
+35038.5 0.933175
+35063.1 0.93295
+35087.7 0.933402
+35112.4 0.93237
+35137 0.932794
+35161.7 0.933112
+35186.5 0.933091
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+35236.1 0.931611
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+35310.7 0.931367
+35335.7 0.930309
+35360.7 0.930468
+35385.7 0.928837
+35410.8 0.929125
+35435.9 0.927485
+35461 0.928169
+35486.2 0.926087
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+39215.7 0.00293064
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diff --git a/spisea/filters.py b/spisea/filters.py
index 23c029b3..23221c6b 100755
--- a/spisea/filters.py
+++ b/spisea/filters.py
@@ -29,7 +29,7 @@ def get_nirc2_filt(name):
 
     while len(idx) != 0:
         wavelength[idx+1] += 1.0e-8
-        
+
         diff = np.diff(wavelength)
         idx = np.where(diff <= 0)[0]
         #print( 'Duplicate entry loop' )
@@ -68,7 +68,7 @@ def get_2mass_filt(name):
                                            name='2MASS_{0}'.format(name))
 
     return spectrum
-    
+
 
 def get_vista_filt(name):
     """
@@ -79,21 +79,21 @@ def get_vista_filt(name):
         t = Table.read('{0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name),
                            format='ascii')
     except:
-        raise ValueError('Could not find VISTA filter file {0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name))    
+        raise ValueError('Could not find VISTA filter file {0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name))
 
    # Wavelength must be in angstroms, transmission in fraction
     wave = t['col1'] * 10
     trans = t['col2'] * 0.01
-    
+
     # Change any negative numbers to 0, as well as anything shortward
     # of 0.4 microns or longward of 2.9 microns
     # (no VISTA filter transmissions beyond these boundaries)
     bad = np.where( (trans < 0) | (wave < 4000) | (wave > 29000) )
     trans[bad] = 0
-    
+
     # Now we can define the VISTA filter bandpass objects
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='VISTA_{0}'.format(name))
-    
+
     return spectrum
 
 def get_decam_filt(name):
@@ -104,18 +104,18 @@ def get_decam_filt(name):
     try:
         t = Table.read('{0}/decam/DECam_filters.txt'.format(filters_dir), format='ascii')
         t.rename_column('Y', 'y')
-        
+
         cols = np.array(t.keys())
         idx = np.where(cols == name)[0][0]
 
         trans = t[cols[idx]]
     except:
-        raise ValueError('Could not find DECAM filter {0} in {1}/decam/DECam_filters.txt'.format(name, filters_dir))         
+        raise ValueError('Could not find DECAM filter {0} in {1}/decam/DECam_filters.txt'.format(name, filters_dir))
 
     # Limit to unmasked regions only
     mask = np.ma.getmask(trans)
     good = np.where(mask == False)
-    
+
     # Convert wavelengths from nm to angstroms, while eliminating masked regions
     wave = t['wavelength'][good] * 10.
     trans = trans[good]
@@ -126,7 +126,7 @@ def get_decam_filt(name):
 
     return spectrum
 
-def get_PS1_filt(name):  
+def get_PS1_filt(name):
     """
     Define PS1 filter as pysynphot object
     """
@@ -145,11 +145,11 @@ def get_PS1_filt(name):
 
         trans = t[cols[idx]]
     except:
-        raise ValueError('Could not find PS1 filter {0} in {1}/ps1'.format(name, filters_dir))         
+        raise ValueError('Could not find PS1 filter {0} in {1}/ps1'.format(name, filters_dir))
 
     # Convert wavelengths from nm to angstroms
     wave = t['wave'] * 10.
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='ps1_{0}'.format(name))
 
     return spectrum
@@ -161,7 +161,7 @@ def get_jwst_filt(name):
     try:
         t = Table.read('{0}/jwst/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find JWST filter {0} in {1}/jwst'.format(name, filters_dir))         
+        raise ValueError('Could not find JWST filter {0} in {1}/jwst'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['microns'] * 10**4.
@@ -170,10 +170,10 @@ def get_jwst_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='jwst_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_Johnson_Glass_filt(name):
     """
@@ -182,7 +182,7 @@ def get_Johnson_Glass_filt(name):
     try:
         t = Table.read('{0}/Johnson_Glass/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find Johnson-Glass filter {0} in {1}/Johnson_Glass'.format(name, filters_dir))         
+        raise ValueError('Could not find Johnson-Glass filter {0} in {1}/Johnson_Glass'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10.
@@ -191,10 +191,10 @@ def get_Johnson_Glass_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='jg_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_nirc1_filt(name):
     """
@@ -203,12 +203,12 @@ def get_nirc1_filt(name):
     try:
         t = Table.read('{0}/nirc1/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find NIRC1 filter {0} in {1}/nirc1'.format(name, filters_dir))         
+        raise ValueError('Could not find NIRC1 filter {0} in {1}/nirc1'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
     trans = t['col2']
-    
+
     # Lets fix wavelength array for duplicate values or negative vals;
     # delete these entries
     diff = np.diff(wave)
@@ -222,14 +222,14 @@ def get_nirc1_filt(name):
 
         diff = np.diff(wave)
         idx = np.where(diff <= 0)[0]
-        
+
     # Change any negative transmission vals to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
 
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='nirc1_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_ctio_osiris_filt(name):
     """
@@ -238,7 +238,7 @@ def get_ctio_osiris_filt(name):
     try:
         t = Table.read('{0}/CTIO_OSIRIS/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find CTIO/OSIRIS filter {0} in {1}/CTIO_OSIRIS'.format(name, filters_dir))         
+        raise ValueError('Could not find CTIO/OSIRIS filter {0} in {1}/CTIO_OSIRIS'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
@@ -247,7 +247,7 @@ def get_ctio_osiris_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='ctio_osiris_{0}'.format(name))
 
     return spectrum
@@ -259,7 +259,7 @@ def get_naco_filt(name):
     try:
         t = Table.read('{0}/naco/{1}.dat'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find NACO filter {0} in {1}/naco'.format(name, filters_dir))         
+        raise ValueError('Could not find NACO filter {0} in {1}/naco'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
@@ -268,7 +268,7 @@ def get_naco_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='naco_{0}'.format(name))
 
     return spectrum
@@ -282,7 +282,7 @@ def get_ubv_filt(name):
     except:
         raise ValueError('Could not find ubv filter {0} in {1}/ubv'.format(name, filters_dir))
 
-    # Convert wavelength from nm to angstroms 
+    # Convert wavelength from nm to angstroms
     wave = t[t.keys()[0]] * 10.
     # Convert transmission to ratio (from percent)
     trans = t[t.keys()[1]] / 100.
@@ -336,8 +336,8 @@ def get_keck_osiris_filt(name):
 def get_gaia_filt(version, name):
     """
     Define Gaia filters as pysynphot object.
-    To avoid confusion, we will only support 
-    the revised DR2 zeropoints from 
+    To avoid confusion, we will only support
+    the revised DR2 zeropoints from
     Evans+18.
 
     version: specify dr1, dr2, or dr2_rev
@@ -357,7 +357,7 @@ def get_gaia_filt(version, name):
         path = '{0}/gaia/dr2_rev/'.format(filters_dir)
     else:
         raise ValueError('GAIA filter version {0} not understood. Please use dr1, dr2, or dr2_rev'.format(version))
-        
+
     # Get the filter info
     try:
         t = Table.read('{0}/Gaia_passbands.txt'.format(path), format='ascii')
@@ -380,7 +380,7 @@ def get_gaia_filt(version, name):
         bad = np.where(trans > 90)
         trans[bad] = 0
     except:
-        raise ValueError('Could not find Gaia filter {0}'.format(name))   
+        raise ValueError('Could not find Gaia filter {0}'.format(name))
 
     # Convert wavelengths to angstroms (from nm)
     wave = t['LAMBDA'] * 10
@@ -437,7 +437,7 @@ def get_rubin_filt(name):
     try:
         t = Table.read('{0}/rubin/{1}.dat'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find Rubin LSST filter file {0}/rubin/{1}.dat'.format(filters_dir, name))
+        raise ValueError('Could not find Rubin LSST filter file {0}/total_/{1}.dat'.format(filters_dir, name))
 
     wavelength = t[t.keys()[0]]
     transmission = t[t.keys()[1]]
@@ -451,24 +451,20 @@ def get_rubin_filt(name):
 
     return spectrum
 
-def get_euclid_filt(name):
+def get_nsfcam_filt(name):
+
     """
-    Define the Euclid filters as a pysynphot spectrum object
+    Define irtf nsfcam filters as pysynphot object
     """
-    # Read in filter info
     try:
-        t = Table.read('{0}/euclid/{1}.dat'.format(filters_dir, name), format='ascii')
+        t = Table.read('{0}/nsfcam/{1}.dat'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find Euclid filter file {0}/euclid/{1}.dat'.format(filters_dir, name))
-
-    wavelength = t[t.keys()[0]]
-    transmission = t[t.keys()[1]]
+        raise ValueError('Could not find nsfcam filter {0} in {1}/nsfcam'.format(name, filters_dir))
 
-    # Convert wavelength to Angstroms
-    wavelength = wavelength * 10
+    # Wavelength already in angstrom and and transmission in fraction
+    wave = t['col1']
+    trans = t['col2']
 
-    # Make spectrum object
-    spectrum = pysynphot.ArrayBandpass(wavelength, transmission, waveunits='angstrom',
-                                       name='euclid_{0}'.format(name))
+    spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='nsfcam_{0}'.format(name))
 
     return spectrum
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index fa8220f6..882a18d3 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -37,7 +37,7 @@
 def Vega():
     # Use Vega as our zeropoint... assume V=0.03 mag and all colors = 0.0
     # These parameters are defined in Girardi+02
-    vega = atm.get_kurucz_atmosphere(temperature=9550, 
+    vega = atm.get_kurucz_atmosphere(temperature=9550,
                                      gravity=3.95,
                                      metallicity=-0.5)
 
@@ -47,8 +47,8 @@ def Vega():
 
     # This is (R/d)**2 as reported by Girardi et al. 2002, page 198, col 1.
     # and is used to convert to flux observed at Earth.
-    vega *= 6.247e-17 
-    
+    vega *= 6.247e-17
+
     return vega
 
 vega = Vega()
@@ -56,13 +56,13 @@ def Vega():
 class Cluster(object):
     """
     Base class to create a cluster with user-specified isochrone,
-    imf, ifmr, and total mass. 
+    imf, ifmr, and total mass.
 
     Parameters
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -90,17 +90,17 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=False,
         self.ifmr = ifmr
         self.cluster_mass = cluster_mass
         self.seed = seed
-        
+
         return
-    
+
 class ResolvedCluster(Cluster):
     """
     Cluster sub-class that produces a *resolved* stellar cluster.
-    A table is output with the synthetic photometry and intrinsic 
-    properties of the individual stars (or stellar systems, if 
+    A table is output with the synthetic photometry and intrinsic
+    properties of the individual stars (or stellar systems, if
     mutliplicity is used in the IMF object).
 
-    If multiplicity is used, than a second table is produced that 
+    If multiplicity is used, than a second table is produced that
     contains the properties of the companion stars independent of their
     primary stars.
 
@@ -108,7 +108,7 @@ class ResolvedCluster(Cluster):
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -120,12 +120,6 @@ class ResolvedCluster(Cluster):
         produced by the cluster at the given isochrone age. Otherwise,
         no compact remnants are produced.
 
-    keep_low_mass_stars: boolean (default False)
-        If True, the cluster will not cut out stars below the isochrone grid 
-        on initial mass. They are assigned a current mass equal to their initial 
-        mass, a phase of 98, and no other evolutionary properties or photometry.
-        If False, stars below the isochrone initial mass limit are cut out.
-
     seed: int
         If set to non-None, all random sampling will be seeded with the
         specified seed, forcing identical output.
@@ -135,7 +129,7 @@ class ResolvedCluster(Cluster):
         True for verbose output.
     """
     def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
-                     seed=None, keep_low_mass_stars=False):
+                     seed=None):
         Cluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                              seed=seed)
         # Provide a user warning is random seed is set
@@ -143,7 +137,7 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
             print('WARNING: random seed set to %i' % seed)
 
         t1 = time.time()
-        ##### 
+        #####
         # Sample the IMF to build up our cluster mass.
         #####
         mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass,
@@ -161,27 +155,27 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         for ikey in interp_keys:
             self.iso_interps[ikey] = interpolate.interp1d(self.iso.points['mass'], self.iso.points[ikey],
                                                           kind='linear', bounds_error=False, fill_value=np.nan)
-        
-        ##### 
+
+        #####
         # Make a table to contain all the information about each stellar system.
         #####
         star_systems = self._make_star_systems_table(mass, isMulti, sysMass)
-        
+
         # Trim out bad systems; specifically, stars with masses outside those provided
         # by the model isochrone (except for compact objects).
-        star_systems, compMass = self._remove_bad_systems(star_systems, compMass, keep_low_mass_stars)
+        star_systems, compMass = self._remove_bad_systems(star_systems, compMass)
 
-        ##### 
+        #####
         # Make a table to contain all the information about companions.
         #####
         if self.imf.make_multiples:
             companions = self._make_companions_table(star_systems, compMass)
-            
+
         #####
         # Save our arrays to the object
         #####
         self.star_systems = star_systems
-        
+
         if self.imf.make_multiples:
             self.companions = companions
 
@@ -192,13 +186,13 @@ def set_filter_names(self):
         Set filter column names
         """
         filt_names = []
-        
+
         for col_name in self.iso.points.colnames:
             if 'm_' in col_name:
                 filt_names.append(col_name)
 
         return filt_names
-        
+
     def _make_star_systems_table(self, mass, isMulti, sysMass):
         """
         Make a star_systems table and get synthetic photometry for each primary star.
@@ -245,7 +239,7 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
             for ii in range(len(bad[0])):
                 print('WARNING: changing phase {0} to 5'.format(star_systems['phase'][bad[0][ii]]))
         star_systems['phase'][bad] = 5
-        
+
         for filt in self.filt_names:
             star_systems[filt] = self.iso_interps[filt](star_systems['mass'])
 
@@ -253,14 +247,14 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
         # Make Remnants
         #     Note: Some models already have WDs in them. If they do, then they shouldn't
         #     be handled by this code here (because their Teff > 0).
-        # 
+        #
         # Remnants have flux = 0 in all bands if they are generated here.
-        ##### 
+        #####
         if self.ifmr != None:
             # Identify compact objects as those with Teff = 0 or with phase > 100.
             highest_mass_iso = self.iso.points['mass'].max()
             idx_rem = np.where((np.isnan(star_systems['Teff'])) & (star_systems['mass'] > highest_mass_iso))[0]
-            
+
             # Calculate remnant mass and ID for compact objects; update remnant_id and
             # remnant_mass arrays accordingly
             if 'metallicity_array' in inspect.getfullargspec(self.ifmr.generate_death_mass).args:
@@ -282,13 +276,13 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
                 star_systems[filt][idx_rem_good] = np.full(len(idx_rem_good), np.nan)
 
         return star_systems
-        
+
     def _make_companions_table(self, star_systems, compMass):
 
         N_systems = len(star_systems)
-        
+
         #####
-        #    MULTIPLICITY                 
+        #    MULTIPLICITY
         # Make a second table containing all the companion-star masses.
         # This table will be much longer... here are the arrays:
         #    sysIndex - the index of the system this star belongs too
@@ -312,17 +306,17 @@ def _make_companions_table(self, star_systems, compMass):
         companions.add_column( Column(np.empty(N_comp_tot, dtype=float), name='metallicity') )
         for filt in self.filt_names:
             companions.add_column( Column(np.empty(N_comp_tot, dtype=float), name=filt) )
-            
+
         if isinstance(self.imf._multi_props, multiplicity.MultiplicityResolvedDK):
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='log_a') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='e') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='i', description = 'degrees') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='Omega') )
             companions.add_column( Column(np.zeros(N_comp_tot, dtype=float), name='omega') )
-            
+
             for ii in range(len(companions)):
                 companions['log_a'][ii] = self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx'][ii]])
-            
+
             companions['e'] = self.imf._multi_props.random_e(np.random.rand(N_comp_tot))
             companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(np.random.rand(N_comp_tot),np.random.rand(N_comp_tot),np.random.rand(N_comp_tot))
 
@@ -330,7 +324,7 @@ def _make_companions_table(self, star_systems, compMass):
         # Make an array that maps system index (ii), companion index (cc) to
         # the place in the 1D companions array.
         N_comp_max = N_companions.max()
-        
+
         comp_index = np.zeros((N_systems, N_comp_max), dtype=int)
         kk = 0
         for ii in range(N_systems):
@@ -346,9 +340,9 @@ def _make_companions_table(self, star_systems, compMass):
             idx = np.where(N_companions >= cc)[0]
 
             # Get the location in the companions array for each system and
-            # the cc'th companion. 
+            # the cc'th companion.
             cdx = comp_index[idx, cc-1]
-            
+
             companions['mass'][cdx] = [compMass[ii][cc-1] for ii in idx]
             comp_mass = companions['mass'][cdx]
 
@@ -397,13 +391,13 @@ def _make_companions_table(self, star_systems, compMass):
                     # as np.nan. Otherwise, add fluxes together
                     good = np.where( (f1 != 0) | (f2 != 0) )
                     bad = np.where( (f1 == 0) & (f2 == 0) )
-                    
+
                     star_systems[filt][idx[good]] = -2.5 * np.log10(f1[good] + f2[good])
                     star_systems[filt][idx[bad]] = np.nan
 
         #####
         # Make Remnants with flux = 0 in all bands.
-        ##### 
+        #####
         if self.ifmr != None:
             # Identify compact objects as those with Teff = 0 or with masses above the max iso mass
             highest_mass_iso = self.iso.points['mass'].max()
@@ -417,7 +411,7 @@ def _make_companions_table(self, star_systems, compMass):
                                                                      metallicity_array=companions['metallicity'][cdx_rem])
             else:
                 r_mass_tmp, r_id_tmp = self.ifmr.generate_death_mass(mass_array=companions['mass'][cdx_rem])
-            
+
 
             # Drop remnants where it is not relevant (e.g. not a compact object or
             # outside mass range IFMR is defined for)
@@ -426,7 +420,7 @@ def _make_companions_table(self, star_systems, compMass):
 
             companions['mass_current'][cdx_rem_good] = r_mass_tmp[good]
             companions['phase'][cdx_rem_good] = r_id_tmp[good]
-                
+
             # Give remnants a magnitude of nan, so they can be filtered out later when calculating flux.
             for filt in self.filt_names:
                 companions[filt][cdx_rem_good] = np.full(len(cdx_rem_good), np.nan)
@@ -439,25 +433,19 @@ def _make_companions_table(self, star_systems, compMass):
         if len(idx) != N_comp_tot and self.verbose:
             print( 'Found {0:d} companions out of stellar mass range'.format(N_comp_tot - len(idx)))
 
-        # For low-mass stars and substellar objects below isochrone, assume no mass loss and set phase to 98
-        low_mass_idxs = (companions['mass']<np.min(self.iso.points['mass']))
-        companions['mass_current'][low_mass_idxs] = companions['mass'][low_mass_idxs]
-        companions['phase'][low_mass_idxs] = 98
-
         # Double check that everything behaved properly.
-        if len(idx)>0:
-            assert companions['mass'][idx].min() > 0
+        assert companions['mass'][idx].min() > 0
 
         return companions
 
-    
-    def _remove_bad_systems(self, star_systems, compMass, keep_low_mass_stars):
+
+    def _remove_bad_systems(self, star_systems, compMass):
         """
         Helper function to remove stars with masses outside the isochrone
-        mass range from the cluster. These stars are identified by having 
+        mass range from the cluster. These stars are identified by having
         a Teff = 0, as set up by _make_star_systems_table_interp.
-        If self.ifmr == None, then both high and low-mass bad systems are 
-        removed. If self.ifmr != None, then we will save the high mass systems 
+        If self.ifmr == None, then both high and low-mass bad systems are
+        removed. If self.ifmr != None, then we will save the high mass systems
         since they will be plugged into an ifmr later.
         """
         N_systems = len(star_systems)
@@ -466,41 +454,23 @@ def _remove_bad_systems(self, star_systems, compMass, keep_low_mass_stars):
         # Convert nan_to_num to avoid errors on greater than, less than comparisons
         star_systems_teff_non_nan = np.nan_to_num(star_systems['Teff'], nan=-99)
         star_systems_phase_non_nan = np.nan_to_num(star_systems['phase'], nan=-99)
-        if (self.ifmr == None) and (not keep_low_mass_stars):
-            print('Remove low mass stars below grid and compact objects')
+        if self.ifmr == None:
             # Keep only those stars with Teff assigned.
             idx = np.where(star_systems_teff_non_nan > 0)[0]
-        elif not keep_low_mass_stars:
-            print('Remove low mass stars, keep compact objects')
-            # Keep stars (with Teff) and any other compact objects (with phase info). 
-            idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) )[0]
-        elif self.ifmr == None:
-            print('Remove compact objects, keep low mass stars below grid')
-            # Keep stars (with Teff) and objects below mass grid
-            idx = np.where( (star_systems_teff_non_nan > 0) | ((star_systems['mass']<np.min(self.iso.points['mass']))) )[0]
         else:
-            print('Keep low mass stars below grid and compact objects')
-            # Keep all
-            idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) |
-                            ((star_systems['mass']<np.min(self.iso.points['mass']))) )[0]
+            # Keep stars (with Teff) and any other compact objects (with phase info).
+            idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) )[0]
 
         if len(idx) != N_systems and self.verbose:
             print( 'Found {0:d} stars out of mass range'.format(N_systems - len(idx)))
 
-        if keep_low_mass_stars:
-            lm_idx = np.where(star_systems['mass']<np.min(self.iso.points['mass']))[0]
-            # Adjust the properties as needed
-            star_systems['mass_current'][lm_idx] = star_systems['mass'][lm_idx]
-            star_systems['phase'][lm_idx] = 98
-            #pdb.set_trace()
-
         star_systems = star_systems[idx]
         N_systems = len(star_systems)
 
         if self.imf.make_multiples:
             # Clean up companion stuff (which we haven't handled yet)
             compMass = [compMass[ii] for ii in idx]
-        
+
         return star_systems, compMass
 
 
@@ -513,7 +483,7 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -523,7 +493,7 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
     delta_AKs: float
         Amount of differential extinction to apply to synthetic photometry,
         in terms of magnitudes of extinction in the Ks filter. Specifically,
-        delta_AKs defines the standard deviation of a Gaussian distribution 
+        delta_AKs defines the standard deviation of a Gaussian distribution
         from which the delta_AKs values will be drawn from for each individual
         system.
 
@@ -541,10 +511,10 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
         True for verbose output.
     """
     def __init__(self, iso, imf, cluster_mass, deltaAKs,
-                 ifmr=None, verbose=False, seed=None, keep_low_mass_stars=False):
+                 ifmr=None, verbose=False, seed=None):
 
         ResolvedCluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
-                                     seed=seed, keep_low_mass_stars=keep_low_mass_stars)
+                                     seed=seed)
 
         # Set random seed, if desired
         if seed is not None:
@@ -553,7 +523,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         # Extract the extinction law from the isochrone object
         redlaw_str = iso.points.meta['REDLAW']
         red_law = reddening.get_red_law(redlaw_str)
-            
+
         # For a given delta_AKs (Gaussian sigma of reddening distribution at Ks),
         # figure out the equivalent delta_filt values for all other filters.
         #t1 = time.time()
@@ -565,7 +535,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         for filt in self.filt_names:
             obs_str = get_obs_str(filt)
             filt_info = get_filter_info(obs_str)
-            
+
             mag_lo = mag_in_filter(red_vega_lo, filt_info)
             mag_hi = mag_in_filter(red_vega_hi, filt_info)
             delta_red_filt[filt] = mag_hi - mag_lo
@@ -593,18 +563,18 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         #t2 = time.time()
         #print 'Diff redden: {0}'.format(t2 - t1)
         return
-    
+
 class UnresolvedCluster(Cluster):
     """
     Cluster sub-class that produces an *unresolved* stellar cluster.
-    Output is a combined spectrum that is the sum of the individual 
+    Output is a combined spectrum that is the sum of the individual
     spectra of the cluster stars.
 
     Parameters
     -----------
     iso: isochrone object
         SPISEA isochrone object
-    
+
     imf: imf object
         SPISEA IMF object
 
@@ -622,10 +592,10 @@ def __init__(self, iso, imf, cluster_mass,
                  wave_range=[3000, 52000], verbose=False):
         # Doesn't do much.
         Cluster.__init__(self, iso, imf, cluster_mass, verbose=verbose)
-        
+
         # Sample a power-law IMF randomly
         self.mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass)
-        
+
         temp = np.zeros(len(self.mass), dtype=float)
         self.mass_all = np.zeros(len(self.mass), dtype=float)
         self.spec_list = [None] * len(self.mass)
@@ -659,7 +629,7 @@ def __init__(self, iso, imf, cluster_mass,
             tmpspectrim = spectrum.trimSpectrum(tmpspecresamp,wave_range[0],wave_range[1])
             self.spec_list_trim[ii] = tmpspectrim
             spec_list_trim_np[:,ii] = np.asarray(tmpspectrim._fluxtable)
-            
+
 
         t2 = time.time()
         print( 'Mass matching took {0:f} s.'.format(t2-t1))
@@ -681,7 +651,7 @@ def __init__(self, iso, imf, cluster_mass,
 
         self.spec_trim = np.sum(spec_list_trim_np,1)
         self.wave_trim = self.spec_list_trim[0].wave
-        
+
         t4 = time.time()
         print( 'Spec trimming took {0:f}s'.format(t4-t3))
 
@@ -689,10 +659,10 @@ def __init__(self, iso, imf, cluster_mass,
         print( 'Total cluster mass is {0:f} M_sun'.format(self.mass_tot))
 
         return
-        
+
 class Isochrone(object):
     """
-    Base Isochrone class. 
+    Base Isochrone class.
 
     Parameters
     ----------
@@ -710,20 +680,20 @@ class Isochrone(object):
         Default is 0.
 
     evo_model: model evolution class, optional
-        Set the stellar evolution model class. 
+        Set the stellar evolution model class.
         Default is evolution.MISTv1().
 
     atm_func: model atmosphere function, optional
-        Set the stellar atmosphere models for the stars. 
+        Set the stellar atmosphere models for the stars.
         Default is get_merged_atmosphere.
 
     wd_atm_func: white dwarf model atmosphere function, optional
-        Set the stellar atmosphere models for the white dwafs. 
-        Default is get_wd_atmosphere   
+        Set the stellar atmosphere models for the white dwafs.
+        Default is get_wd_atmosphere
 
     mass_sampling : int, optional
         Sample the raw isochrone every `mass_sampling` steps. The default
-        is mass_sampling = 0, which is the native isochrone mass sampling 
+        is mass_sampling = 0, which is the native isochrone mass sampling
         of the evolution model.
 
     wave_range : list, optional
@@ -752,7 +722,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
 
 
         t1 = time.time()
-        
+
         c = constants
 
         # Assert that the wavelength ranges are within the limits of the
@@ -763,7 +733,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
         except:
             print('Desired wavelength range invalid. Limit to 1000 - 10000 A')
             return
-        
+
         # Get solar metallicity models for a population at a specific age.
         # Takes about 0.1 seconds.
         evol = evo_model.isochrone(age=10**logAge,
@@ -779,7 +749,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
             evol = evol[idx]
         if max_mass != None:
             idx = np.where(evol['mass'] <= max_mass)
-            evol = evol[idx] 
+            evol = evol[idx]
 
         # Trim down the table by selecting every Nth point where
         # N = mass sampling factor.
@@ -829,17 +799,16 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
             star *= (R / distance)**2  # in erg s^-1 cm^-2 A^-1
 
             # Redden the spectrum. This doesn't take much time at all.
-            red = red_law.reddening(AKs).resample(star.wave) 
+            red = red_law.reddening(AKs).resample(star.wave)
             star *= red
-            
-            # Save the final spectrum to our spec_list for later use.            
+
+            # Save the final spectrum to our spec_list for later use.
             self.spec_list.append(star)
 
         # Append all the meta data to the summary table.
         tab.meta['REDLAW'] = red_law.name
         tab.meta['ATMFUNC'] = atm_func.__name__
         tab.meta['EVOMODEL'] = type(evo_model).__name__
-        tab.meta['EVOMODELVERSION'] = evo_model.model_version_name
         tab.meta['LOGAGE'] = logAge
         tab.meta['AKS'] = AKs
         tab.meta['DISTANCE'] = distance
@@ -861,7 +830,7 @@ def plot_HR_diagram(self, savefile=None):
         Parameters
         -----------
         savefile: path or None, optional
-             Path to file plot too, if desired. 
+             Path to file plot too, if desired.
              Default is None
         """
         plt.clf()
@@ -870,7 +839,7 @@ def plot_HR_diagram(self, savefile=None):
         plt.gca().invert_xaxis()
         plt.xlabel(r'T$_{\mathrm{eff}}$ (K)')
         plt.ylabel('Luminosity (erg / s)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
@@ -878,7 +847,7 @@ def plot_HR_diagram(self, savefile=None):
 
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
     def plot_mass_luminosity(self, savefile=None):
@@ -888,28 +857,28 @@ def plot_mass_luminosity(self, savefile=None):
         Parameters
         -----------
         savefile: path or None, optional
-             Path to file plot too, if desired. 
+             Path to file plot too, if desired.
              Default is None
         """
         plt.clf()
         plt.loglog(self.points['mass'], self.points['L'], 'k.')
         plt.xlabel(r'Mass (M$_\odot$)')
         plt.ylabel('Luminosity (erg / s)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
                                   self.points.meta['AKS']))
-        
+
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
 class IsochronePhot(Isochrone):
     """
-    Make an isochrone with synthetic photometry in various filters. 
-    Load from file if possible. 
+    Make an isochrone with synthetic photometry in various filters.
+    Load from file if possible.
 
     Parameters
     ----------
@@ -927,16 +896,16 @@ class IsochronePhot(Isochrone):
         Default is 0.
 
     evo_model: model evolution class, optional
-        Set the stellar evolution model class. 
+        Set the stellar evolution model class.
         Default is evolution.MISTv1().
 
     atm_func: model atmosphere function, optional
-        Set the stellar atmosphere models for the stars. 
+        Set the stellar atmosphere models for the stars.
         Default is atmospheres.get_merged_atmosphere.
 
     wd_atm_func: white dwarf model atmosphere function, optional
-        Set the stellar atmosphere models for the white dwafs. 
-        Default is atmospheres.get_wd_atmosphere   
+        Set the stellar atmosphere models for the white dwafs.
+        Default is atmospheres.get_wd_atmosphere
 
     red_law : reddening law object, optional
         Define the reddening law for the synthetic photometry.
@@ -944,14 +913,14 @@ class IsochronePhot(Isochrone):
 
     iso_dir : path, optional
          Path to isochrone directory. Code will check isochrone
-         directory to see if isochrone file already exists; if it 
-         does, it will just read the isochrone. If the isochrone 
+         directory to see if isochrone file already exists; if it
+         does, it will just read the isochrone. If the isochrone
          file doesn't exist, then save isochrone to the isochrone
          directory.
 
     mass_sampling : int, optional
         Sample the raw isochrone every `mass_sampling` steps. The default
-        is mass_sampling = 0, which is the native isochrone mass sampling 
+        is mass_sampling = 0, which is the native isochrone mass sampling
         of the evolution model.
 
     wave_range : list, optional
@@ -972,14 +941,14 @@ class IsochronePhot(Isochrone):
         which is often sufficient synthetic photometry in most cases.
 
     recomp : boolean, optional
-        If true, recalculate the isochrone photometry even if 
+        If true, recalculate the isochrone photometry even if
         the savefile exists. You should recompute anytime you change
         the filter set (see filters below).
 
     filters : array of strings, optional
         Define what filters the synthetic photometry
-        will be calculated for, via the filter string 
-        identifier. 
+        will be calculated for, via the filter string
+        identifier.
     """
     def __init__(self, logAge, AKs, distance,
                  metallicity=0.0,
@@ -1014,11 +983,11 @@ def __init__(self, logAge, AKs, distance,
             else:
                 metal_pre = 'p'
             metal_flag = int(abs(metallicity)*10)
-            
+
             save_file_fmt = '{0}/iso_{1:.2f}_{2:4.2f}_{3:4s}_{4}{5:2s}.fits'
             self.save_file = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
             self.save_file_legacy = save_file_fmt.format(iso_dir, logAge, AKs, str(distance).zfill(5), metal_pre, str(metal_flag).zfill(2))
-            
+
         # Expected filters
         self.filters = filters
 
@@ -1035,7 +1004,7 @@ def __init__(self, logAge, AKs, distance,
                                red_law=red_law, mass_sampling=mass_sampling,
                                min_mass=min_mass, max_mass=max_mass, rebin=rebin)
             self.verbose = True
-            
+
             # Make photometry
             self.make_photometry(rebin=rebin, vega=vega)
         else:
@@ -1046,58 +1015,14 @@ def __init__(self, logAge, AKs, distance,
                 self.points = Table.read(self.save_file_legacy)
             # Add some error checking.
 
-        # Next: do we have all the filters we need?
-        comp_filters = []
-        for ii in self.filters:
-            col_name = 'm_' + get_filter_col_name(ii)
-            if col_name not in self.points.keys():
-                comp_filters.append(ii)
-        # Compute additional filters if needed
-        if len(comp_filters)>0:
-            self.verbose = True
-            print('Missing photometry for',len(comp_filters),'filter - recomputing these columns:',comp_filters)
-
-            print('Loading stellar spectra')
-            # Initialize output for stellar spectra
-            self.spec_list = []
-            # For each isochrone point, extract the synthetic photometry.
-            for ii in range(len(self.points['Teff'])):
-                # Loop is currently taking about 0.11 s per iteration
-                gravity = float( self.points['logg'][ii] )
-                L = float( (self.points['L'][ii]*units.W).cgs / (units.erg / units.s)) # in erg/s
-                T = float( self.points['Teff'][ii] )               # in Kelvin
-                R = float( (self.points['R'][ii]*units.m).to('pc') / units.pc)              # in pc
-                phase = int(self.points['phase'][ii])
-                # Get the atmosphere model now. Wavelength is in Angstroms
-                # This is the time-intensive call... everything else is negligable.
-                # If source is a star, pull from star atmospheres. If it is a WD,
-                # pull from WD atmospheres
-                if phase == 101:
-                    star = wd_atm_func(temperature=T, gravity=gravity, metallicity=metallicity,
-                                           verbose=False)
-                else:
-                    star = atm_func(temperature=T, gravity=gravity, metallicity=metallicity,
-                                        rebin=rebin)
-                # Trim wavelength range down to appropriate range
-                star = spectrum.trimSpectrum(star, wave_range[0], wave_range[1])
-                # Convert into flux observed at Earth (unreddened)
-                star *= (R / self.points.meta["DISTANCE"])**2  # in erg s^-1 cm^-2 A^-1
-                # Redden the spectrum. This doesn't take much time at all.
-                red = red_law.reddening(AKs).resample(star.wave) 
-                star *= red
-                # Save the final spectrum to our spec_list for later use.            
-                self.spec_list.append(star)
-
-            self.make_photometry(rebin=rebin, vega=vega, comp_filters=comp_filters)
-
         return
 
-    def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
-        """ 
+    def make_photometry(self, rebin=True, vega=vega):
+        """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
         photometry.
-        
+
         """
         startTime = time.time()
 
@@ -1110,16 +1035,12 @@ def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
         npoints = len(self.points)
         verbose_fmt = 'M = {0:7.3f} Msun  T = {1:5.0f} K  m_{2:s} = {3:4.2f}'
 
-        #Calculate all filters, or select filters
-        if comp_filters is None:
-            comp_filters = self.filters
-
         # Loop through the filters, get filter info, make photometry for
         # all stars in this filter.
-        for ii in comp_filters:
+        for ii in self.filters:
             prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
             print( prt_fmt.format(ii, time.time() - startTime))
-            
+
             filt = get_filter_info(ii, rebin=rebin, vega=vega)
             filt_name = get_filter_col_name(ii)
 
@@ -1127,15 +1048,15 @@ def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
             col_name = 'm_' + filt_name
             mag_col = Column(np.zeros(npoints, dtype=float), name=col_name)
             self.points.add_column(mag_col)
-            
+
             # Loop through each star in the isochrone and do the filter integration
             print('Starting synthetic photometry')
             for ss in range(npoints):
                 star = self.spec_list[ss]  # These are already extincted, observed spectra.
                 star_mag = mag_in_filter(star, filt)
-                
+
                 self.points[col_name][ss] = star_mag
-        
+
                 if (self.verbose and (ss % 100) == 0):
                     print( verbose_fmt.format(self.points['mass'][ss], self.points['Teff'][ss],
                                              filt_name, star_mag))
@@ -1152,34 +1073,27 @@ def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
 
     def check_save_file(self, evo_model, atm_func, red_law):
         """
-        Check to see if save_file exists, as saved by the save_file 
-        and save_file_legacy objects. If the filename exists, check the 
+        Check to see if save_file exists, as saved by the save_file
+        and save_file_legacy objects. If the filename exists, check the
         meta-data as well.
 
         returns a boolean: True is file exists, false otherwise
         """
         out_bool = False
-        
+
         if os.path.exists(self.save_file) | os.path.exists(self.save_file_legacy):
             try:
                 tmp = Table.read(self.save_file)
             except:
                 tmp = Table.read(self.save_file_legacy)
-            
-        
+
+
             # See if the meta-data matches: evo model, atm_func, redlaw
             if ( (tmp.meta['EVOMODEL'] == type(evo_model).__name__) &
                 (tmp.meta['ATMFUNC'] == atm_func.__name__) &
                  (tmp.meta['REDLAW'] == red_law.name) ):
                 out_bool = True
 
-            # Check model version if it was logged
-            if 'EVOMODELVERSION' in tmp.meta:
-                if tmp.meta['EVOMODELVERSION']!=evo_model.model_version_name:
-                    out_bool=False
-            else:
-                print(f"No version information found for evolution model {type(evo_model).__name__}.")
-            
         return out_bool
 
     def plot_CMD(self, mag1, mag2, savefile=None):
@@ -1193,7 +1107,7 @@ def plot_CMD(self, mag1, mag2, savefile=None):
         mag2 : string
             The name of the second magnitude column to be plotted.
         savefile : string (default None)
-            If a savefile is specified, then the plot will be saved to that file. 
+            If a savefile is specified, then the plot will be saved to that file.
         """
         plt.clf()
         plt.plot(self.points[mag1] - self.points[mag2], self.points[mag1],
@@ -1201,7 +1115,7 @@ def plot_CMD(self, mag1, mag2, savefile=None):
         plt.gca().invert_yaxis()
         plt.xlabel(mag1 + ' - ' + mag2 + ' (mag)')
         plt.ylabel(mag1 + ' (mag)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
@@ -1209,34 +1123,34 @@ def plot_CMD(self, mag1, mag2, savefile=None):
 
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
     def plot_mass_magnitude(self, mag, savefile=None):
         """
         Make a standard mass-luminosity relation plot for this isochrone.
-        
+
         Parameters
         ----------
         mag : string
             The name of the magnitude column to be plotted.
         savefile : string (default None)
-            If a savefile is specified, then the plot will be saved to that file. 
+            If a savefile is specified, then the plot will be saved to that file.
         """
         plt.clf()
         plt.semilogx(self.points['mass'], self.points[mag], 'k.')
         plt.gca().invert_yaxis()
         plt.xlabel(r'Mass (M$_\odot$)')
         plt.ylabel(mag + ' (mag)')
-        
+
         fmt_title = 'logAge={0:.2f}, d={1:.2f} kpc, AKs={2:.2f}'
         plt.title(fmt_title.format(self.points.meta['LOGAGE'],
                                   self.points.meta['DISTANCE']/1e3,
                                   self.points.meta['AKS']))
-        
+
         if savefile != None:
             plt.savefig(savefile)
-        
+
         return
 
 #===================================================#
@@ -1258,7 +1172,7 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
         Functions on this object:
         apply_reddening (Apply reddening with defined redlaw and AKs)
         make_photometry (make synthetic photometry for spectra)
-                 
+
         Parameters
         ----------
         logAge : float
@@ -1296,13 +1210,13 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             spectrum. This is very useful to save computation time down the
             road.
         """
-        t1 = time.time()        
+        t1 = time.time()
         c = constants
 
         # Get solar metallicity models for a population at a specific age.
         # Takes about 0.1 seconds.
-        evol = evo_model.isochrone(age=10**logAge)  # solar metallicity 
-        
+        evol = evo_model.isochrone(age=10**logAge)  # solar metallicity
+
         # Eliminate cases where log g is less than 0
         idx = np.where(evol['logg'] > 0)
         evol = evol[idx]
@@ -1313,8 +1227,8 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             evol = evol[idx]
         if max_mass != None:
             idx = np.where(evol['mass'] <= max_mass)
-            evol = evol[idx]            
- 
+            evol = evol[idx]
+
         # Trim down the table by selecting every Nth point where
         # N = mass sampling factor.
         evol = evol[::mass_sampling]
@@ -1349,31 +1263,30 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
             # Get the atmosphere model now. Wavelength is in Angstroms
             # This is the time-intensive call... everything else is negligable.
             star = atm_func(temperature=T, gravity=gravity)
-            
+
             # Trim wavelength range down to JHKL range (0.5 - 5.2 microns)
             star = spectrum.trimSpectrum(star, wave_range[0], wave_range[1])
 
             # Convert into flux observed at Earth (unreddened)
             star *= (R / distance)**2  # in erg s^-1 cm^-2 A^-1
-            
-            # Save the final spectrum to our spec_list for later use.            
+
+            # Save the final spectrum to our spec_list for later use.
             self.spec_list.append(star)
 
         # Append all the meta data to the summary table.
-        
+
         tab.meta['ATMFUNC'] = atm_func.__name__
         tab.meta['EVOMODEL'] = type(evo_model).__name__
-        tab.meta['EVOMODELVERSION'] = evo_model.model_version_name
         tab.meta['LOGAGE'] = logAge
         tab.meta['DISTANCE'] = distance
         tab.meta['WAVEMIN'] = wave_range[0]
         tab.meta['WAVEMAX'] = wave_range[1]
 
         self.points = tab
-    
+
         t2 = time.time()
         print('Isochrone generation took {0:f} s.'.format(t2-t1))
-        
+
         return
 
     def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=None):
@@ -1385,7 +1298,7 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
         ----------
         AKs: float
             Total extinction in AKs
-            
+
         extinction_law: SPISEA extinction object
             Extinction law to be used on the spectra
 
@@ -1395,13 +1308,13 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
 
         dAKs_max: float or None
             If not none, defines the maximum |dAKs| a star can
-            have in gaussian distribution case 
+            have in gaussian distribution case
 
         dist: string, 'uniform' or 'gaussian'
             Distribution to draw differential reddening from. If uniform,
             dAKs will cut off at Aks +/- dAKs. Otherwise, will draw
             from Gaussian of width AKs +/- dAks
-            
+
         """
         self.AKs = np.ones(len(self.spec_list))
         # Apply reddening to each object in the spec list
@@ -1430,7 +1343,7 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
             else:
                 AKs_act = AKs
 
-            red = extinction_law.reddening(AKs_act).resample(star.wave) 
+            red = extinction_law.reddening(AKs_act).resample(star.wave)
             star *= red
 
             # Update the spectrum in spec list
@@ -1443,7 +1356,7 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
         return
 
     def make_photometry(self, filters, rebin=True):
-        """ 
+        """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
         photometry.
@@ -1453,11 +1366,11 @@ def make_photometry(self, filters, rebin=True):
         filters : dictionary
             A dictionary containing the filter name (for the output columns)
             and the filter specification string that can be processed by pysynphot.
-                   
+
         rebin: boolean
-            True to rebin filter function (only used if non-zero transmission points are 
+            True to rebin filter function (only used if non-zero transmission points are
             larger than 1500 points)
- 
+
         """
         npoints = len(self.points)
 
@@ -1474,35 +1387,35 @@ def make_photometry(self, filters, rebin=True):
             col_name = 'mag_' + filt_name
             mag_col = Column(np.zeros(npoints, dtype=float), name=col_name)
             self.points.add_column(mag_col)
-            
+
             # Loop through each star in the isochrone and do the filter integration
             for ss in range(npoints):
                 star = self.spec_list[ss]  # These are already extincted, observed spectra.
                 star_mag = mag_in_filter(star, filt)
-                
+
                 self.points[col_name][ss] = star_mag
-        
-            
+
+
         endTime = time.time()
         print( '      Time taken: {0:.2f} seconds'.format(endTime - ts))
 
         return
 
 def get_filter_info(name, vega=vega, rebin=True):
-    """ 
+    """
     Define filter functions, setting ZP according to
     Vega spectrum. Input name is the SPISEA
     obs_string
     """
     tmp = name.split(',')
     filterName = tmp[-1]
-        
+
     if name.startswith('nirc2'):
         filt = filters.get_nirc2_filt(filterName)
 
     elif name.startswith('2mass'):
         filt = filters.get_2mass_filt(filterName)
-        
+
     elif name.startswith('vista'):
         filt = filters.get_vista_filt(filterName)
 
@@ -1517,10 +1430,10 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('jg'):
         filt = filters.get_Johnson_Glass_filt(filterName)
-        
+
     elif name.startswith('nirc1'):
         filt = filters.get_nirc1_filt(filterName)
-        
+
     elif name.startswith('ctio_osiris'):
         filt = filters.get_ctio_osiris_filt(filterName)
 
@@ -1532,7 +1445,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('ukirt'):
         filt = filters.get_ukirt_filt(filterName)
-        
+
     elif name.startswith('keck_osiris'):
         filt = filters.get_keck_osiris_filt(filterName)
 
@@ -1545,20 +1458,20 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('hawki'):
         filt = filters.get_hawki_filt(filterName)
-     
+
     elif name.startswith('rubin'):
         filt = filters.get_rubin_filt(filterName)
 
-    elif name.startswith('euclid'):
-        filt = filters.get_euclid_filt(filterName)
-        
+    elif name.startswith('nsfcam'):
+        filt = filters.get_nsfcam_filt(filterName)
+
     else:
         # Otherwise, look for the filter info in the cdbs/mtab and cdbs/comp files
         try:
             filt = ObsBandpass(name)
         except:
             raise Exception('Filter {0} not understood. Check spelling and make sure cdbs/mtab and cdbs/comp files are up to date'.format(name))
-        
+
         # Convert to ArraySpectralElement for resampling.
         filt = spectrum.ArraySpectralElement(filt.wave, filt.throughput,
                                              waveunits=filt.waveunits,
@@ -1576,14 +1489,14 @@ def get_filter_info(name, vega=vega, rebin=True):
     # Otherwise, throw an error
     idx = np.where(filt.throughput > 0.001)[0]
     if (min(filt.wave[idx]) < min(vega.wave)) | (max(filt.wave[idx]) > max(vega.wave)):
-        raise ValueError('Vega spectrum doesnt cover filter wavelength range!')  
+        raise ValueError('Vega spectrum doesnt cover filter wavelength range!')
 
     vega_obs = obs.Observation(vega, filt, binset=filt.wave, force='taper')
     #vega_flux = vega_obs.binflux.sum()
     diff = np.diff(vega_obs.binwave)
     diff = np.append(diff, diff[-1])
     vega_flux = np.sum(vega_obs.binflux * diff)
-    
+
     vega_mag = 0.03
 
     filt.flux0 = vega_flux
@@ -1594,7 +1507,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
 def get_filter_col_name(obs_str):
     """
-    Get standard column name for synthetic photometry based on 
+    Get standard column name for synthetic photometry based on
     the input string. The input string is expected to be an
     appropriate SPISEA obs_string
     """
@@ -1613,7 +1526,7 @@ def get_filter_col_name(obs_str):
             filt_name = 'hst_{0}'.format(tmp[-1])
     else:
         filt_name = '{0}_{1}'.format(tmp[0], tmp[1])
-        
+
     return filt_name
 
 def get_obs_str(col):
@@ -1623,7 +1536,7 @@ def get_obs_str(col):
     """
     # Remove the trailing m_
     name = col[2:]
-    
+
     # Define dictionary for filters
     filt_list = {'hst_f127m': 'wfc3,ir,f127m', 'hst_f139m': 'wfc3,ir,f139m', 'hst_f153m': 'wfc3,ir,f153m',
                  'hst_f814w': 'acs,wfc1,f814w', 'hst_f125w': 'wfc3,ir,f125w', 'hst_f160w': 'wfc3,ir,f160w',
@@ -1645,7 +1558,7 @@ def get_obs_str(col):
                  'jwst_F187N': 'jwst,F187N',
                  'jwst_F200W': 'jwst,F200W',
                  'jwst_F210M': 'jwst,F210M',
-                 'jwst_F250M': 'jwst,F250M', 
+                 'jwst_F250M': 'jwst,F250M',
                  'jwst_F277W': 'jwst,F277W',
                  'jwst_F300M': 'jwst,F300M',
                  'jwst_F322W2': 'jwst,F322W2',
@@ -1665,14 +1578,10 @@ def get_obs_str(col):
                  'nirc2_FeII': 'nirc2,FeII', 'nirc2_Brgamma': 'nirc2,Brgamma',
                  '2mass_J': '2mass,J', '2mass_H': '2mass,H', '2mass_Ks': '2mass,Ks',
                  'ubv_U':'ubv,U', 'ubv_B':'ubv,B', 'ubv_V':'ubv,V', 'ubv_R':'ubv,R',
-                 'ubv_I':'ubv,I', 
+                 'ubv_I':'ubv,I',
                  'jg_J': 'jg,J', 'jg_H': 'jg,H', 'jg_K': 'jg,K',
                  'nirc1_K':'nirc1,K', 'nirc1_H':'nirc1,H',
                  'naco_J':'naco,J', 'naco_H':'naco,H', 'naco_Ks':'naco,Ks',
-                 'naco_IB_2.00': 'naco,IB_2.00', 'naco_IB_2.03':'naco,IB_2.03', 'naco_IB_2.06':'naco,IB_2.06',
-                 'naco_IB_2.24':'naco,IB_2.24', 'naco_IB_2.27':'naco,IB_2.27',
-                 'naco_IB_2.30':'naco,IB_2.30', 'naco_IB_2.33':'naco,IB_2.33',
-                 'naco_IB_2.36':'naco,IB_2.36',
                  'ukirt_J':'ukirt,J', 'ukirt_H':'ukirt,H', 'ukirt_K':'ukirt,K',
                  'ctio_osiris_H': 'ctio_osiris,H', 'ctio_osiris_K': 'ctio_osiris,K',
                  'ztf_g':'ztf,g', 'ztf_r':'ztf,r', 'ztf_i':'ztf,i',
@@ -1686,7 +1595,7 @@ def get_obs_str(col):
                  'roman_f106': 'roman,wfi,f106',
                  'roman_f129': 'roman,wfi,f129',
                  'roman_f158': 'roman,wfi,f158',
-                 'roman_f146': 'roman,wfi,f146',
+                 'roman_w146': 'roman,wfi,w146',
                  'roman_f213': 'roman,wfi,f213',
                  'roman_f184': 'roman,wfi,f184',
                  'rubin_g':'rubin,g',
@@ -1694,14 +1603,10 @@ def get_obs_str(col):
                  'rubin_r':'rubin,r',
                  'rubin_u':'rubin,u',
                  'rubin_z':'rubin,z',
-                 'rubin_y':'rubin,y',
-                 'euclid_VIS':'euclid,VIS',
-                 'euclid_Y':'euclid,Y',
-                 'euclid_J':'euclid,J',
-                 'euclid_H':'euclid,H'}
+                 'rubin_y':'rubin,y'}
 
     obs_str = filt_list[name]
-        
+
     return obs_str
 
 def rebin_spec(wave, specin, wavnew):
@@ -1714,7 +1619,7 @@ def rebin_spec(wave, specin, wavnew):
     f = np.ones(len(wave))
     filt = spectrum.ArraySpectralElement(wave, f, waveunits='angstrom')
     obs_f = obs.Observation(spec, filt, binset=wavnew, force='taper')
- 
+
     return obs_f.binflux
 
 def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
@@ -1725,7 +1630,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
                                  'wfc3,ir,f153m']):
     """
     Wrapper routine to generate a grid of isochrones of different ages,
-    extinctions, and distances. 
+    extinctions, and distances.
 
     Parameters:
     ----------
@@ -1737,7 +1642,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
 
     dist_arr: array
         Array of distances to loop over (pc)
- 
+
     evo_models: SPISEA evolution object
         Which evolution models to use
 
@@ -1754,7 +1659,7 @@ def make_isochrone_grid(age_arr, AKs_arr, dist_arr, evo_model=default_evo_model,
         Mass sampling of isochrone, relative to original mass sampling
 
     filters: dictionary
-        Which filters to do the synthetic photometry on    
+        Which filters to do the synthetic photometry on
     """
     print( '**************************************')
     print( 'Start generating isochrones')
@@ -1799,7 +1704,7 @@ def mag_in_filter(star, filt):
     diff = np.diff(star_in_filter.binwave)
     diff = np.append(diff, diff[-1])
     star_flux = np.sum(star_in_filter.binflux * diff)
-    
+
     star_mag = -2.5 * math.log10(star_flux / filt.flux0) + filt.mag0
     return star_mag
 
@@ -1822,10 +1727,10 @@ def match_model_masses(isoMasses, starMasses):
 
     idx = np.where(dm_frac > 0.1)[0]
     indices[idx] = -1
-    
+
     return indices
 
-    
+
 def get_evo_model_by_string(evo_model_string):
     return getattr(evolution, evo_model_string)
 
@@ -1836,7 +1741,7 @@ def calc_ab_vega_filter_conversion(filt_str):
     AB and Vega magnitudes for a given filter:
     m_AB - m_vega
 
-    Note: this conversion is just the vega magnitude in 
+    Note: this conversion is just the vega magnitude in
     AB system
 
     Parameters:
@@ -1856,14 +1761,14 @@ def calc_ab_vega_filter_conversion(filt_str):
     filt_wave = filt.wave
     filt_mu = c / filt_wave
     s_filt = filt.throughput
-    
+
     # Interpolate the filter function, determine what the
     # filter function is at the exact sampling of the
     # vega spectrum (in freq space)
     filt_interp = scipy.interpolate.interp1d(filt_mu, s_filt, kind='linear', bounds_error=False,
                                                  fill_value=0)
     s_interp = filt_interp(vega_mu)
-    
+
     # Now for the m_ab calculation
     mu_diff = np.diff(vega_mu)
     numerator = np.sum(vega_flux_mu[:-1] * s_interp[:-1] * mu_diff)
@@ -1881,10 +1786,10 @@ def calc_ab_vega_filter_conversion(filt_str):
     #                                             fill_value=0)
     #s_interp = filt_interp(vega.wave)
 
-    # Calculate the numerator 
+    # Calculate the numerator
     #diff = np.diff(vega.wave)
     #numerator2 = np.sum((vega.wave[:-1]**2. / c) * vega.flux[:-1] * s_interp[:-1] * diff)
-    
+
     # Now we need to intergrate the filter response for the denominator
     #denominator2 = np.sum(s_interp[:-1] * diff)
 
@@ -1892,4 +1797,3 @@ def calc_ab_vega_filter_conversion(filt_str):
     #vega_mag_ab2 = -2.5 * np.log10(numerator2 / denominator2) - 48.6
 
     return vega_mag_ab
-

From c100459d619b000d6866ce77a37c1d3c10d3c059 Mon Sep 17 00:00:00 2001
From: Rocketpack23 <apusack@gmail.com>
Date: Wed, 11 Feb 2026 13:45:25 -0800
Subject: [PATCH 16/55] Edited filters.py to include irtf/nsfcam

---
 spisea/filters.py | 24 +++++++++++++++++++++++-
 1 file changed, 23 insertions(+), 1 deletion(-)

diff --git a/spisea/filters.py b/spisea/filters.py
index 23221c6b..e2a2aee9 100755
--- a/spisea/filters.py
+++ b/spisea/filters.py
@@ -437,7 +437,7 @@ def get_rubin_filt(name):
     try:
         t = Table.read('{0}/rubin/{1}.dat'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find Rubin LSST filter file {0}/total_/{1}.dat'.format(filters_dir, name))
+        raise ValueError('Could not find Rubin LSST filter file {0}/rubin/{1}.dat'.format(filters_dir, name))
 
     wavelength = t[t.keys()[0]]
     transmission = t[t.keys()[1]]
@@ -451,6 +451,28 @@ def get_rubin_filt(name):
 
     return spectrum
 
+def get_euclid_filt(name):
+    """
+    Define the Euclid filters as a pysynphot spectrum object
+    """
+    # Read in filter info
+    try:
+        t = Table.read('{0}/euclid/{1}.dat'.format(filters_dir, name), format='ascii')
+    except:
+        raise ValueError('Could not find Euclid filter file {0}/euclid/{1}.dat'.format(filters_dir, name))
+
+    wavelength = t[t.keys()[0]]
+    transmission = t[t.keys()[1]]
+
+    # Convert wavelength to Angstroms
+    wavelength = wavelength * 10
+
+    # Make spectrum object
+    spectrum = pysynphot.ArrayBandpass(wavelength, transmission, waveunits='angstrom',
+                                       name='euclid_{0}'.format(name))
+
+    return spectrum
+
 def get_nsfcam_filt(name):
 
     """

From e3f520c558f5a419c31ad62c3dc65fb38fac12ce Mon Sep 17 00:00:00 2001
From: Rocketpack23 <apusack@gmail.com>
Date: Wed, 11 Feb 2026 13:47:11 -0800
Subject: [PATCH 17/55] Edited synthetic.py to include irtf/nsfcam

---
 spisea/synthetic.py | 124 +++++++++++++++++++++++++++++++++++++++-----
 1 file changed, 111 insertions(+), 13 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 882a18d3..4c98dc57 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -120,6 +120,12 @@ class ResolvedCluster(Cluster):
         produced by the cluster at the given isochrone age. Otherwise,
         no compact remnants are produced.
 
+    keep_low_mass_stars: boolean (default False)
+        If True, the cluster will not cut out stars below the isochrone grid
+        on initial mass. They are assigned a current mass equal to their initial
+        mass, a phase of 98, and no other evolutionary properties or photometry.
+        If False, stars below the isochrone initial mass limit are cut out.
+
     seed: int
         If set to non-None, all random sampling will be seeded with the
         specified seed, forcing identical output.
@@ -129,7 +135,7 @@ class ResolvedCluster(Cluster):
         True for verbose output.
     """
     def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
-                     seed=None):
+                     seed=None, keep_low_mass_stars=False):
         Cluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                              seed=seed)
         # Provide a user warning is random seed is set
@@ -163,7 +169,7 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
 
         # Trim out bad systems; specifically, stars with masses outside those provided
         # by the model isochrone (except for compact objects).
-        star_systems, compMass = self._remove_bad_systems(star_systems, compMass)
+        star_systems, compMass = self._remove_bad_systems(star_systems, compMass, keep_low_mass_stars)
 
         #####
         # Make a table to contain all the information about companions.
@@ -433,13 +439,19 @@ def _make_companions_table(self, star_systems, compMass):
         if len(idx) != N_comp_tot and self.verbose:
             print( 'Found {0:d} companions out of stellar mass range'.format(N_comp_tot - len(idx)))
 
+        # For low-mass stars and substellar objects below isochrone, assume no mass loss and set phase to 98
+        low_mass_idxs = (companions['mass']<np.min(self.iso.points['mass']))
+        companions['mass_current'][low_mass_idxs] = companions['mass'][low_mass_idxs]
+        companions['phase'][low_mass_idxs] = 98
+
         # Double check that everything behaved properly.
-        assert companions['mass'][idx].min() > 0
+        if len(idx)>0:
+            assert companions['mass'][idx].min() > 0
 
         return companions
 
 
-    def _remove_bad_systems(self, star_systems, compMass):
+    def _remove_bad_systems(self, star_systems, compMass, keep_low_mass_stars):
         """
         Helper function to remove stars with masses outside the isochrone
         mass range from the cluster. These stars are identified by having
@@ -454,16 +466,34 @@ def _remove_bad_systems(self, star_systems, compMass):
         # Convert nan_to_num to avoid errors on greater than, less than comparisons
         star_systems_teff_non_nan = np.nan_to_num(star_systems['Teff'], nan=-99)
         star_systems_phase_non_nan = np.nan_to_num(star_systems['phase'], nan=-99)
-        if self.ifmr == None:
+        if (self.ifmr == None) and (not keep_low_mass_stars):
+            print('Remove low mass stars below grid and compact objects')
             # Keep only those stars with Teff assigned.
             idx = np.where(star_systems_teff_non_nan > 0)[0]
-        else:
+        elif not keep_low_mass_stars:
+            print('Remove low mass stars, keep compact objects')
             # Keep stars (with Teff) and any other compact objects (with phase info).
             idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) )[0]
+        elif self.ifmr == None:
+            print('Remove compact objects, keep low mass stars below grid')
+            # Keep stars (with Teff) and objects below mass grid
+            idx = np.where( (star_systems_teff_non_nan > 0) | ((star_systems['mass']<np.min(self.iso.points['mass']))) )[0]
+        else:
+            print('Keep low mass stars below grid and compact objects')
+            # Keep all
+            idx = np.where( (star_systems_teff_non_nan > 0) | (star_systems_phase_non_nan >= 0) |
+                            ((star_systems['mass']<np.min(self.iso.points['mass']))) )[0]
 
         if len(idx) != N_systems and self.verbose:
             print( 'Found {0:d} stars out of mass range'.format(N_systems - len(idx)))
 
+        if keep_low_mass_stars:
+            lm_idx = np.where(star_systems['mass']<np.min(self.iso.points['mass']))[0]
+            # Adjust the properties as needed
+            star_systems['mass_current'][lm_idx] = star_systems['mass'][lm_idx]
+            star_systems['phase'][lm_idx] = 98
+            #pdb.set_trace()
+
         star_systems = star_systems[idx]
         N_systems = len(star_systems)
 
@@ -511,10 +541,10 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
         True for verbose output.
     """
     def __init__(self, iso, imf, cluster_mass, deltaAKs,
-                 ifmr=None, verbose=False, seed=None):
+                 ifmr=None, verbose=False, seed=None, keep_low_mass_stars=False):
 
         ResolvedCluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
-                                     seed=seed)
+                                     seed=seed, keep_low_mass_stars=keep_low_mass_stars)
 
         # Set random seed, if desired
         if seed is not None:
@@ -809,6 +839,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
         tab.meta['REDLAW'] = red_law.name
         tab.meta['ATMFUNC'] = atm_func.__name__
         tab.meta['EVOMODEL'] = type(evo_model).__name__
+        tab.meta['EVOMODELVERSION'] = evo_model.model_version_name
         tab.meta['LOGAGE'] = logAge
         tab.meta['AKS'] = AKs
         tab.meta['DISTANCE'] = distance
@@ -1015,9 +1046,53 @@ def __init__(self, logAge, AKs, distance,
                 self.points = Table.read(self.save_file_legacy)
             # Add some error checking.
 
+        # Next: do we have all the filters we need?
+        comp_filters = []
+        for ii in self.filters:
+            col_name = 'm_' + get_filter_col_name(ii)
+            if col_name not in self.points.keys():
+                comp_filters.append(ii)
+        # Compute additional filters if needed
+        if len(comp_filters)>0:
+            self.verbose = True
+            print('Missing photometry for',len(comp_filters),'filter - recomputing these columns:',comp_filters)
+
+            print('Loading stellar spectra')
+            # Initialize output for stellar spectra
+            self.spec_list = []
+            # For each isochrone point, extract the synthetic photometry.
+            for ii in range(len(self.points['Teff'])):
+                # Loop is currently taking about 0.11 s per iteration
+                gravity = float( self.points['logg'][ii] )
+                L = float( (self.points['L'][ii]*units.W).cgs / (units.erg / units.s)) # in erg/s
+                T = float( self.points['Teff'][ii] )               # in Kelvin
+                R = float( (self.points['R'][ii]*units.m).to('pc') / units.pc)              # in pc
+                phase = int(self.points['phase'][ii])
+                # Get the atmosphere model now. Wavelength is in Angstroms
+                # This is the time-intensive call... everything else is negligable.
+                # If source is a star, pull from star atmospheres. If it is a WD,
+                # pull from WD atmospheres
+                if phase == 101:
+                    star = wd_atm_func(temperature=T, gravity=gravity, metallicity=metallicity,
+                                           verbose=False)
+                else:
+                    star = atm_func(temperature=T, gravity=gravity, metallicity=metallicity,
+                                        rebin=rebin)
+                # Trim wavelength range down to appropriate range
+                star = spectrum.trimSpectrum(star, wave_range[0], wave_range[1])
+                # Convert into flux observed at Earth (unreddened)
+                star *= (R / self.points.meta["DISTANCE"])**2  # in erg s^-1 cm^-2 A^-1
+                # Redden the spectrum. This doesn't take much time at all.
+                red = red_law.reddening(AKs).resample(star.wave)
+                star *= red
+                # Save the final spectrum to our spec_list for later use.
+                self.spec_list.append(star)
+
+            self.make_photometry(rebin=rebin, vega=vega, comp_filters=comp_filters)
+
         return
 
-    def make_photometry(self, rebin=True, vega=vega):
+    def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
         """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
@@ -1035,9 +1110,13 @@ def make_photometry(self, rebin=True, vega=vega):
         npoints = len(self.points)
         verbose_fmt = 'M = {0:7.3f} Msun  T = {1:5.0f} K  m_{2:s} = {3:4.2f}'
 
+        #Calculate all filters, or select filters
+        if comp_filters is None:
+            comp_filters = self.filters
+
         # Loop through the filters, get filter info, make photometry for
         # all stars in this filter.
-        for ii in self.filters:
+        for ii in comp_filters:
             prt_fmt = 'Starting filter: {0:s}   Elapsed time: {1:.2f} seconds'
             print( prt_fmt.format(ii, time.time() - startTime))
 
@@ -1094,6 +1173,13 @@ def check_save_file(self, evo_model, atm_func, red_law):
                  (tmp.meta['REDLAW'] == red_law.name) ):
                 out_bool = True
 
+            # Check model version if it was logged
+            if 'EVOMODELVERSION' in tmp.meta:
+                if tmp.meta['EVOMODELVERSION']!=evo_model.model_version_name:
+                    out_bool=False
+            else:
+                print(f"No version information found for evolution model {type(evo_model).__name__}.")
+
         return out_bool
 
     def plot_CMD(self, mag1, mag2, savefile=None):
@@ -1277,6 +1363,7 @@ def __init__(self, logAge, distance, evo_model=default_evo_model,
 
         tab.meta['ATMFUNC'] = atm_func.__name__
         tab.meta['EVOMODEL'] = type(evo_model).__name__
+        tab.meta['EVOMODELVERSION'] = evo_model.model_version_name
         tab.meta['LOGAGE'] = logAge
         tab.meta['DISTANCE'] = distance
         tab.meta['WAVEMIN'] = wave_range[0]
@@ -1462,9 +1549,12 @@ def get_filter_info(name, vega=vega, rebin=True):
     elif name.startswith('rubin'):
         filt = filters.get_rubin_filt(filterName)
 
+    elif name.startswith('euclid'):
+        filt = filters.get_euclid_filt(filterName)
+
     elif name.startswith('nsfcam'):
         filt = filters.get_nsfcam_filt(filterName)
-
+        
     else:
         # Otherwise, look for the filter info in the cdbs/mtab and cdbs/comp files
         try:
@@ -1582,6 +1672,10 @@ def get_obs_str(col):
                  'jg_J': 'jg,J', 'jg_H': 'jg,H', 'jg_K': 'jg,K',
                  'nirc1_K':'nirc1,K', 'nirc1_H':'nirc1,H',
                  'naco_J':'naco,J', 'naco_H':'naco,H', 'naco_Ks':'naco,Ks',
+                 'naco_IB_2.00': 'naco,IB_2.00', 'naco_IB_2.03':'naco,IB_2.03', 'naco_IB_2.06':'naco,IB_2.06',
+                 'naco_IB_2.24':'naco,IB_2.24', 'naco_IB_2.27':'naco,IB_2.27',
+                 'naco_IB_2.30':'naco,IB_2.30', 'naco_IB_2.33':'naco,IB_2.33',
+                 'naco_IB_2.36':'naco,IB_2.36',
                  'ukirt_J':'ukirt,J', 'ukirt_H':'ukirt,H', 'ukirt_K':'ukirt,K',
                  'ctio_osiris_H': 'ctio_osiris,H', 'ctio_osiris_K': 'ctio_osiris,K',
                  'ztf_g':'ztf,g', 'ztf_r':'ztf,r', 'ztf_i':'ztf,i',
@@ -1595,7 +1689,7 @@ def get_obs_str(col):
                  'roman_f106': 'roman,wfi,f106',
                  'roman_f129': 'roman,wfi,f129',
                  'roman_f158': 'roman,wfi,f158',
-                 'roman_w146': 'roman,wfi,w146',
+                 'roman_f146': 'roman,wfi,f146',
                  'roman_f213': 'roman,wfi,f213',
                  'roman_f184': 'roman,wfi,f184',
                  'rubin_g':'rubin,g',
@@ -1603,7 +1697,11 @@ def get_obs_str(col):
                  'rubin_r':'rubin,r',
                  'rubin_u':'rubin,u',
                  'rubin_z':'rubin,z',
-                 'rubin_y':'rubin,y'}
+                 'rubin_y':'rubin,y',
+                 'euclid_VIS':'euclid,VIS',
+                 'euclid_Y':'euclid,Y',
+                 'euclid_J':'euclid,J',
+                 'euclid_H':'euclid,H'}
 
     obs_str = filt_list[name]
 

From cde187d959e17912cce9c1ee488674b1102ae8ae Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 11 Feb 2026 17:15:23 -0800
Subject: [PATCH 18/55] Add random state testing

---
 spisea/synthetic.py            |  3 ++-
 spisea/tests/test_synthetic.py | 37 ++++++++++++++++++++++++++++++++++
 2 files changed, 39 insertions(+), 1 deletion(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 697e36c6..49acbaa4 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -159,7 +159,8 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         # Provide a user warning is random seed is set
         if seed is not None and verbose:
             print('WARNING: random seed set to %i' % seed)
-
+            imf.rng = self.rng
+        
         #####
         # Sample the IMF to build up our cluster mass.
         #####
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index ada9544f..1969ad21 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1206,4 +1206,41 @@ def test_Raithel18_IFMR_5():
 
     assert len(WD_idx) == 2 , "There are not the right number of WDs for the Raithel18 IFMR"
 
+    return
+
+def test_ResolvedCluster_random_state():
+    """
+    Test that the random state is properly set in ResolvedCluster, such that two clusters with the same seed have the same stars.
+    """
+    log_age = 6.7
+    AKs = 2.7
+    distance = 4000
+    cluster_mass = 10**4.
+    iso_dir = 'isochrones/'
+
+    evo = evolution.MergedBaraffePisaEkstromParsec()
+    atm_func = atmospheres.get_merged_atmosphere
+    red_law = reddening.RedLawNishiyama09()
+    filt_list = ['nirc2,J', 'nirc2,Kp']
+    
+    iso = syn.IsochronePhot(
+        log_age,
+        AKs,
+        distance,
+        evo_model=evo,
+        atm_func=atm_func,
+        red_law=red_law,
+        filters=filt_list,
+        mass_sampling=10,
+        iso_dir=iso_dir
+    )
+
+    imf_limits = np.array([0.07, 0.5, 150])
+    imf_powers = np.array([-1.3, -2.35])
+    imf_multi = multiplicity.MultiplicityUnresolved()
+    imf_test = imf.IMF_broken_powerlaw(imf_limits, imf_powers, multiplicity=imf_multi)
+
+    cluster1 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
+    cluster2 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
+    np.testing.assert_array_equal(cluster1.star_systems, cluster2.star_systems)
     return
\ No newline at end of file

From 1d845f3c25480372203f1a8936d148e0e27a6159 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 18 Feb 2026 22:45:08 -0800
Subject: [PATCH 19/55] Revert back to np.random.seed and check companion
 consistency

---
 .gitignore                                    |   2 +-
 spisea/imf/imf.py                             |  15 +--
 spisea/synthetic.py                           |  30 +++---
 .../isochrones/iso_6.70_0.80_04000_m1.50.fits |  20 ++++
 .../isochrones/iso_6.70_0.80_04000_p0.00.fits |  14 +++
 .../isochrones/iso_6.70_1.67_08000_p0.00.fits |   2 +
 .../isochrones/iso_6.70_2.30_08000_p0.00.fits |   1 +
 .../isochrones/iso_6.70_2.40_04000_p0.00.fits |  93 ++++++++++++++++++
 .../isochrones/iso_6.70_2.46_08000_p0.00.fits |   1 +
 .../isochrones/iso_6.70_2.62_08000_p0.00.fits |   1 +
 .../isochrones/iso_6.70_2.70_04000_p0.00.fits |  44 +++++++++
 .../isochrones/iso_9.70_0.00_01000_p0.00.fits |  53 ++++++++++
 spisea/tests/test_data/companions.pkl         | Bin 0 -> 251721 bytes
 spisea/tests/test_synthetic.py                |  35 ++++---
 14 files changed, 277 insertions(+), 34 deletions(-)
 create mode 100644 spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
 create mode 100644 spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits
 create mode 100644 spisea/tests/test_data/companions.pkl

diff --git a/.gitignore b/.gitignore
index b29e4f96..ae231559 100755
--- a/.gitignore
+++ b/.gitignore
@@ -54,4 +54,4 @@ distribute-*.tar.gz
 ._*
 
 # Test files generated
-spisea/tests/isochrones
+# spisea/tests/isochrones
diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 8dfc0e64..cb6866e6 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -51,7 +51,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         self._multi_props = multiplicity
         self._mass_limits = np.atleast_1d(massLimits)
         self.seed = seed
-        self.rng = np.random.default_rng(seed)
+        # self.rng = np.random.default_rng(seed)
 
         if multiplicity:
             self.make_multiples = True
@@ -61,7 +61,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         return
 
 
-    def generate_cluster(self, totalMass):
+    def generate_cluster(self, totalMass, seed=None):
         """
         Generate a cluster of stellar systems with the specified IMF.
 
@@ -128,10 +128,13 @@ def generate_cluster(self, totalMass):
         totalMassTally = 0
         loopCnt = 0
 
+        if seed:
+            np.random.seed(seed=seed)
+
         # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
-            uniX = self.rng.random(int(newStarCount))
+            uniX = np.random.rand(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
 
@@ -148,7 +151,7 @@ def generate_cluster(self, totalMass):
                 MF = self._multi_props.multiplicity_fraction(newMasses)
                 CSF = self._multi_props.companion_star_fraction(newMasses)
 
-                newIsMultiple = self.rng.random(int(newStarCount)) < MF
+                newIsMultiple = np.random.rand(int(newStarCount)) < MF
 
                 # Function to calculate multiple systems more efficiently
                 # start_calc = time.time()
@@ -228,7 +231,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
 
         # Identify multiple systems, calculate number of companions for each
         multiple_idx = np.where(newIsMultiple)[0]
-        comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
+        comp_nums = 1 + np.random.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
         if self._multi_props.companion_max:
             too_many = np.where(comp_nums > self._multi_props.CSF_max)[0]
             comp_nums[too_many] = self._multi_props.CSF_max
@@ -242,7 +245,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
 
         for comp_num, comp_index in zip(comp_unique, comp_indices):
             # Calculate masses of companions
-            q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
+            q_values = self._multi_props.random_q(np.random.rand(len(comp_index), comp_num))
             m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
             compMasses[multiple_idx[comp_index], :comp_num] = m_comp
 
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 49acbaa4..932198bf 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -107,7 +107,7 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=False,
         self.ifmr = ifmr
         self.cluster_mass = cluster_mass
         self.seed = seed
-        self.rng = np.random.default_rng(self.seed)
+        # self.rng = np.random.default_rng(self.seed)
 
         return
 
@@ -159,13 +159,13 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         # Provide a user warning is random seed is set
         if seed is not None and verbose:
             print('WARNING: random seed set to %i' % seed)
-            imf.rng = self.rng
+            # imf.rng = self.rng
         
         #####
         # Sample the IMF to build up our cluster mass.
         #####
         # start0 = time.time()
-        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass)
+        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass, seed=seed)
         # end0 = time.time()
         # print('IMF sampling took {0:f} s.'.format(end0 - start0))
 
@@ -328,11 +328,11 @@ def _make_companions_table_new(self, star_systems, compMass):
 
         if isinstance(self.imf._multi_props, multiplicity.MultiplicityResolvedDK):
             companions.add_column(Column(self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx']]), name='log_a'))
-            companions.add_column(Column(self.imf._multi_props.random_e(self.rng.random(N_comp_tot)), name='e'))
+            companions.add_column(Column(self.imf._multi_props.random_e(np.random.rand(N_comp_tot)), name='e'))
             companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
-                self.rng.random(N_comp_tot),
-                self.rng.random(N_comp_tot),
-                self.rng.random(N_comp_tot)
+                np.random.rand(N_comp_tot),
+                np.random.rand(N_comp_tot),
+                np.random.rand(N_comp_tot)
             )
 
         companions['mass'] = compMass.compressed()
@@ -441,11 +441,11 @@ def _make_companions_table(self, star_systems, compMass):
             for ii in range(len(companions)):
                 companions['log_a'][ii] = self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx'][ii]])
 
-            companions['e'] = self.imf._multi_props.random_e(self.rng.random(N_comp_tot))
+            companions['e'] = self.imf._multi_props.random_e(np.random.rand(N_comp_tot))
             companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
-                self.rng.random(N_comp_tot),
-                self.rng.random(N_comp_tot),
-                self.rng.random(N_comp_tot)
+                np.random.rand(N_comp_tot),
+                np.random.rand(N_comp_tot),
+                np.random.rand(N_comp_tot)
             )
 
 
@@ -701,7 +701,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         # Perturb all of star systems' photometry by a random amount corresponding to
         # differential de-reddening. The distribution is normal with a width of
         # Aks +/- deltaAKs in each filter
-        rand_red = self.rng.standard_normal(len(self.star_systems))
+        rand_red = np.random.randn(len(self.star_systems))
 
         for filt in self.filt_names:
             self.star_systems[filt] += rand_red * delta_red_filt[filt]
@@ -1561,18 +1561,18 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
             # extinction law
             if dAKs != 0:
                 if dist == 'gaussian':
-                    AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
+                    AKs_act = np.random.normal(loc=AKs, scale=dAKs)
                     # Apply dAKs_max if desired. Redo if diff > dAKs_max
                     if dAKs_max != None:
                         diff = abs(AKs_act - AKs)
                         while diff > dAKs_max:
                             print('While loop active')
-                            AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
+                            AKs_act = np.random.normal(loc=AKs, scale=dAKs)
                             diff = abs(AKs_act - AKs)
                 elif dist == 'uniform':
                     low = AKs - dAKs
                     high = AKs + dAKs
-                    AKs_act = self.rng.uniform(low=low, high=high)
+                    AKs_act = np.random.uniform(low=low, high=high)
                 else:
                     print('dist {0} undefined'.format(dist))
                     return
diff --git a/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits b/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
new file mode 100644
index 00000000..4f7413bb
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
@@ -0,0 +1,20 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                   71 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f139m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_hst_f153m'                                                         TFORM11 = 'D       '                                                            REDLAW  = 'H18b    '                                                            ATMFUNC = 'get_phoenixv16_atmosphere'                                           EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  0.8                                                  DISTANCE=                 4000                                                  METAL_IN=                 -1.5                                                  HIERARCH METAL_ACT = -1.4990758306077128                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
new file mode 100644
index 00000000..b027b3cd
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
@@ -0,0 +1,14 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                   73 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f139m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_hst_f153m'                                                         TFORM11 = 'D       '                                                            REDLAW  = 'H18b    '                                                            ATMFUNC = 'get_phoenixv16_atmosphere'                                           EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  0.8                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             EQ�?��@�Reb��A��a��.�?�������@��q��F?����Oֿ�@6H�N��@5��)�z@5:8���E$����+@�(X�h�A�� �?���#�O@�ޘM�F?����%��@5�t�yr@5j|�}Of@4ȿ��E1���]��@�8��ͼA�6�c��=?�I+ٓ�;@�Ar���F?�I)��*#��@5T�d>@4��O�@41����E;�>��@�9G�}%SA�)AHY�x?�A���8@}Z6kF?�AؘRr���@4���'q@4ZcXR�@3��;��E@���
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diff --git a/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
new file mode 100644
index 00000000..95db4468
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
@@ -0,0 +1,2 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'NL20    '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 1.67                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@7��C�/�@5��r�+@4�w
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\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
new file mode 100644
index 00000000..baf4705a
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
@@ -0,0 +1 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'broken_pl,[2.3, 1.63, 0.9],[2.23, 3.0],2.12'                         ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  2.3                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@:��7ό�@6�����V@5Ł!�M�@3ς���)Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@:�4Az�@6�y/zT@5�~]��H@3���|�EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@:�Gbpp@6����r@5�3�8h�@3�1w_@
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
new file mode 100644
index 00000000..7b66a4ce
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
@@ -0,0 +1,93 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   73 / length of dimension 1                          NAXIS2  =                  321 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   10 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'K       '                                                            TTYPE9  = 'm_nirc2_J'                                                           TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_Kp'                                                          TFORM10 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MergedBaraffePisaEkstromParsec'                                      HIERARCH EVOMODELVERSION = 'None    '                                           LOGAGE  =                  6.7                                                  AKS     =                  2.4                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = 0.0                                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
new file mode 100644
index 00000000..a582318f
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
@@ -0,0 +1 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'S10     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 2.46                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@7������@6����n�@62wj�H|@4,"��2Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@7�(з�U@6�!9V�@6!k�~@4r�}��EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@7�$fZf@6�����@6l,}@4���q
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
new file mode 100644
index 00000000..dcd17c25
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
@@ -0,0 +1 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'F11     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 2.62                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@:EZ� ��@7-����@6b�]��@4E�g���Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@:/�لT�@7���m�@6Q���@�@46չ��EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@:#��o�e@7��ۇ�@6H[��@4-{Pm�
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
new file mode 100644
index 00000000..d8d7bbbe
--- /dev/null
+++ b/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
@@ -0,0 +1,44 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   73 / length of dimension 1                          NAXIS2  =                  161 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   10 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'K       '                                                            TTYPE9  = 'm_nirc2_J'                                                           TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_Kp'                                                          TFORM10 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MergedBaraffePisaEkstromParsec'                                      HIERARCH EVOMODELVERSION = 'None    '                                           LOGAGE  =                  6.7                                                  AKS     =                  2.7                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = 0.0                                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits b/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits
new file mode 100644
index 00000000..d8eb7cd1
--- /dev/null
+++ b/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits
@@ -0,0 +1,53 @@
+SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                  231 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_nirc2_Kp'                                                          TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_H'                                                           TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_J'                                                           TFORM11 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =                  9.7                                                  AKS     =                  0.0                                                  DISTANCE=                 1000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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HcmV?d00001

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 1969ad21..e3850ae4 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -2,6 +2,8 @@
 import numpy as np
 import pylab as plt
 import numpy as np
+import pickle
+import spisea
 from spisea import reddening, evolution, atmospheres, ifmr
 from spisea import synthetic as syn
 from spisea.imf import imf
@@ -11,6 +13,8 @@
 import pdb
 from scipy.spatial import cKDTree as KDTree
 
+spisea_path = os.path.dirname(spisea.__file__)
+
 def test_isochrone(plot=False):
     logAge = 6.7
     AKs = 2.7
@@ -46,7 +50,7 @@ def test_iso_wave():
     logAge = np.log10(5*10**6.) # Age in log(years)
     AKs = 0.8 # extinction in mags
     dist = 4000 # distance in parsec
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Define evolution/atmosphere models and extinction law (optional)
     evo_model = evolution.MergedBaraffePisaEkstromParsec() 
@@ -134,7 +138,7 @@ def test_IsochronePhot(plot=False):
     distance = 4000
     filt_list = ['wfc3,ir,f127m', 'nirc2,J']
     mass_sampling=1
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     evo_model = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
@@ -284,7 +288,7 @@ def test_ResolvedCluster():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling=5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -398,7 +402,7 @@ def test_ResolvedClusterDiffRedden():
     cluster_mass = 10**5.
     deltaAKs = 0.05
     mass_sampling=5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -523,7 +527,7 @@ def test_ifmr_multiplicity():
     distance = 1000
     cluster_mass = 1e6
     mass_sampling = 5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test all filters
     filt_list = ['nirc2,Kp', 'nirc2,H', 'nirc2,J']
@@ -616,7 +620,7 @@ def test_metallicity():
     atm_func = atmospheres.get_phoenixv16_atmosphere
     red_law = reddening.RedLawHosek18b()
     filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m']
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Start with a solar metallicity isochrone    
     metallicity= 0.
@@ -685,7 +689,7 @@ def test_cluster_mass():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling = 5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -774,7 +778,7 @@ def test_keep_low_mass_stars():
     distance = 4000
     cluster_mass = 10**5.
     mass_sampling = 5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -838,7 +842,7 @@ def test_compact_object_companions():
     distance = 4000
     cluster_mass = 10**4.
     mass_sampling=5
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
@@ -887,7 +891,7 @@ def time_test_cluster():
     AKs = 2.7
     distance = 4000
     cluster_mass = 10**4
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     startTime = time.time()
     
@@ -964,7 +968,7 @@ def time_test_mass_match():
     AKs = 2.7
     distance = 4000
     cluster_mass = 5e3
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     imf_in = imf.Kroupa_2001(multiplicity=None)
 
@@ -1216,7 +1220,7 @@ def test_ResolvedCluster_random_state():
     AKs = 2.7
     distance = 4000
     cluster_mass = 10**4.
-    iso_dir = 'isochrones/'
+    iso_dir = f'{spisea_path}/tests/isochrones'
 
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
@@ -1243,4 +1247,11 @@ def test_ResolvedCluster_random_state():
     cluster1 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
     cluster2 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
     np.testing.assert_array_equal(cluster1.star_systems, cluster2.star_systems)
+
+    with open(f'{spisea_path}/tests/test_data/companions.pkl', 'rb') as file:
+        old_companion = pickle.load(file)
+
+    for key in old_companion.colnames:
+        np.testing.assert_array_equal(cluster1.companions[key], old_companion[key])
+
     return
\ No newline at end of file

From 7fcfb2f5cc4373e81c7d74caa59ec8f848295d10 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Thu, 19 Feb 2026 14:26:47 -0800
Subject: [PATCH 20/55] Added star system random state test with the main
 branch

---
 spisea/tests/test_data/star_systems.pkl | Bin 0 -> 1516177 bytes
 spisea/tests/test_synthetic.py          |   6 ++++++
 2 files changed, 6 insertions(+)
 create mode 100644 spisea/tests/test_data/star_systems.pkl

diff --git a/spisea/tests/test_data/star_systems.pkl b/spisea/tests/test_data/star_systems.pkl
new file mode 100644
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HcmV?d00001

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index e3850ae4..349667c9 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1248,9 +1248,15 @@ def test_ResolvedCluster_random_state():
     cluster2 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
     np.testing.assert_array_equal(cluster1.star_systems, cluster2.star_systems)
 
+    with open(f'{spisea_path}/tests/test_data/star_systems.pkl', 'rb') as file:
+        old_star_systems = pickle.load(file)
     with open(f'{spisea_path}/tests/test_data/companions.pkl', 'rb') as file:
         old_companion = pickle.load(file)
 
+    for key in old_star_systems.colnames:
+        # Equal to the 7th decimal
+        np.testing.assert_almost_equal(cluster1.star_systems[key], old_star_systems[key])
+
     for key in old_companion.colnames:
         np.testing.assert_array_equal(cluster1.companions[key], old_companion[key])
 

From a81ad27fdc1056bf418c0824243c7d0d382758d8 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Thu, 19 Feb 2026 16:43:40 -0800
Subject: [PATCH 21/55] Updating to next version

---
 docs/conf.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/conf.py b/docs/conf.py
index c72f260d..18901890 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -25,9 +25,9 @@
 author = 'Matthew Hosek Jr, Jessica R. Lu, Casey Y. Lam'
 
 # The short X.Y version
-version = '2.2'
+version = '2.3'
 # The full version, including alpha/beta/rc tags
-release = '2.2'
+release = '2.3'
 
 
 

From fbdbb1128059a429cd34a9659896902d39f808cc Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Thu, 19 Feb 2026 16:43:55 -0800
Subject: [PATCH 22/55] updating changelog

---
 docs/index.rst | 10 ++++++++++
 1 file changed, 10 insertions(+)

diff --git a/docs/index.rst b/docs/index.rst
index 11e1e44e..71878d34 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -82,6 +82,16 @@ releases will be co-authors in future SPISEA software papers.
 
 Change Log
 ----------
+2.3 (2026-02-10)
+  * Achieves faster cluster generation (factor of about 2x) by using
+    replacing ragged arrays with masked arrays when calculating
+    multiplicity properties
+  * Added new test functions (and associated test data files) ensuring
+    that the primary mass and companion
+    mass distibutions remain the same as generated with SPISEA <= v2.2
+  * Added support to Euclid VIS filter
+    
+
 2.2 (2026-01-16)
   * Compatibility updates for SPISEA to work with `SynthPop
     <https://synthpop.readthedocs.io/en/latest/>`_. Updates include:

From 604319a5ec9a7afd1f6e8bb8f9ef3a9ef7c106be Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Thu, 19 Feb 2026 17:11:27 -0800
Subject: [PATCH 23/55] small cleanup, using np.isclose for reasonable value
 comparison tests

---
 spisea/tests/test_synthetic.py | 19 ++++++++++++-------
 1 file changed, 12 insertions(+), 7 deletions(-)

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 349667c9..f02bbfa3 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -47,9 +47,10 @@ def test_iso_wave():
     range (propagated through IsochronePhot)
     """
     # Define isochrone parameters
-    logAge = np.log10(5*10**6.) # Age in log(years)
-    AKs = 0.8 # extinction in mags
+    logAge = 6.7 # Age in log(years)
+    AKs = 2.7 # extinction in mags
     dist = 4000 # distance in parsec
+    metal = 0.0 # metallicity
     iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Define evolution/atmosphere models and extinction law (optional)
@@ -72,6 +73,7 @@ def test_iso_wave():
     wave_range1 = [3000, 52000]
     my_iso = syn.IsochronePhot(
         logAge, AKs, dist,
+        metallicity=metal,
         evo_model=evo_model, 
         atm_func=atm_func,
         red_law=red_law, 
@@ -155,6 +157,7 @@ def test_IsochronePhot(plot=False):
         filters=filt_list,
         mass_sampling=mass_sampling,
         iso_dir=iso_dir
+        recomp=True
     )
     endTime = time.time()
     print('IsochronePhot generated in: %d seconds' % (endTime - startTime))
@@ -309,7 +312,8 @@ def test_ResolvedCluster():
         red_law=red_law,
         filters=filt_list,
         mass_sampling=mass_sampling,
-        iso_dir=iso_dir
+        iso_dir=iso_dir,
+        recomp=True
     )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
@@ -1254,10 +1258,11 @@ def test_ResolvedCluster_random_state():
         old_companion = pickle.load(file)
 
     for key in old_star_systems.colnames:
-        # Equal to the 7th decimal
-        np.testing.assert_almost_equal(cluster1.star_systems[key], old_star_systems[key])
+        # Require values are consistent within reasonable bounds
+        assert np.all(np.isclose(cluster1.star_systems[key], old_star_systems[key], rtol=1e-05, atol=1e-08))
 
     for key in old_companion.colnames:
-        np.testing.assert_array_equal(cluster1.companions[key], old_companion[key])
+        # Require values are consistent within reasonable bounds
+        assert np.all(np.isclose(cluster1.companions[key], old_companion[key], rtol=1e-05, atol=1e-08))
 
-    return
\ No newline at end of file
+    return

From 4e2407f1aa4030132516fab4db49f85d8ff31f0c Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Feb 2026 16:15:05 -0800
Subject: [PATCH 24/55] adding tests/isochrones/ so not tracked

---
 .gitignore | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.gitignore b/.gitignore
index ae231559..4fc5dfe3 100755
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,6 @@
+# SPISEA-generated isochrones from test functions
+spisea/tests/isochrones/
+
 # Compiled files
 *.py[co]
 *.a

From 5f36da8fe2c22d9db7b2f21bd8908e210101a260 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Feb 2026 16:15:25 -0800
Subject: [PATCH 25/55] removing test isochrones from git tracking

---
 .../isochrones/iso_6.70_0.80_04000_m1.50.fits | 20 ----
 .../isochrones/iso_6.70_0.80_04000_p0.00.fits | 14 ---
 .../isochrones/iso_6.70_1.67_08000_p0.00.fits |  2 -
 .../isochrones/iso_6.70_2.30_08000_p0.00.fits |  1 -
 .../isochrones/iso_6.70_2.40_04000_p0.00.fits | 93 -------------------
 .../isochrones/iso_6.70_2.46_08000_p0.00.fits |  1 -
 .../isochrones/iso_6.70_2.62_08000_p0.00.fits |  1 -
 .../isochrones/iso_6.70_2.70_04000_p0.00.fits | 44 ---------
 .../isochrones/iso_9.70_0.00_01000_p0.00.fits | 53 -----------
 9 files changed, 229 deletions(-)
 delete mode 100644 spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
 delete mode 100644 spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits

diff --git a/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits b/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
deleted file mode 100644
index 4f7413bb..00000000
--- a/spisea/tests/isochrones/iso_6.70_0.80_04000_m1.50.fits
+++ /dev/null
@@ -1,20 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                   71 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f139m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_hst_f153m'                                                         TFORM11 = 'D       '                                                            REDLAW  = 'H18b    '                                                            ATMFUNC = 'get_phoenixv16_atmosphere'                                           EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  0.8                                                  DISTANCE=                 4000                                                  METAL_IN=                 -1.5                                                  HIERARCH METAL_ACT = -1.4990758306077128                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
deleted file mode 100644
index b027b3cd..00000000
--- a/spisea/tests/isochrones/iso_6.70_0.80_04000_p0.00.fits
+++ /dev/null
@@ -1,14 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                   73 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f139m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_hst_f153m'                                                         TFORM11 = 'D       '                                                            REDLAW  = 'H18b    '                                                            ATMFUNC = 'get_phoenixv16_atmosphere'                                           EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  0.8                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
deleted file mode 100644
index 95db4468..00000000
--- a/spisea/tests/isochrones/iso_6.70_1.67_08000_p0.00.fits
+++ /dev/null
@@ -1,2 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'NL20    '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 1.67                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@7��C�/�@5��r�+@4�w
-��@3B<*�I*Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@7��xZ�@5m���B@4�S:/��@32}o
�EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@7�!�*"@5c�WX�a@4��00�@3)�2$�
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
deleted file mode 100644
index baf4705a..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.30_08000_p0.00.fits
+++ /dev/null
@@ -1 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'broken_pl,[2.3, 1.63, 0.9],[2.23, 3.0],2.12'                         ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                  2.3                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@:��7ό�@6�����V@5Ł!�M�@3ς���)Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@:�4Az�@6�y/zT@5�~]��H@3���|�EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@:�Gbpp@6����r@5�3�8h�@3�1w_@
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
deleted file mode 100644
index 7b66a4ce..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.40_04000_p0.00.fits
+++ /dev/null
@@ -1,93 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   73 / length of dimension 1                          NAXIS2  =                  321 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   10 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'K       '                                                            TTYPE9  = 'm_nirc2_J'                                                           TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_Kp'                                                          TFORM10 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MergedBaraffePisaEkstromParsec'                                      HIERARCH EVOMODELVERSION = 'None    '                                           LOGAGE  =                  6.7                                                  AKS     =                  2.4                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = 0.0                                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
deleted file mode 100644
index a582318f..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.46_08000_p0.00.fits
+++ /dev/null
@@ -1 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'S10     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 2.46                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@7������@6����n�@62wj�H|@4,"��2Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@7�(з�U@6�!9V�@6!k�~@4r�}��EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@7�$fZf@6�����@6l,}@4���q
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
deleted file mode 100644
index dcd17c25..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.62_08000_p0.00.fits
+++ /dev/null
@@ -1 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   89 / length of dimension 1                          NAXIS2  =                    3 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   12 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_hst_f127m'                                                         TFORM9  = 'D       '                                                            TTYPE10 = 'm_hst_f153m'                                                         TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_H'                                                           TFORM11 = 'D       '                                                            TTYPE12 = 'm_nirc2_Kp'                                                          TFORM12 = 'D       '                                                            REDLAW  = 'F11     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =    6.698970004336019                                                  AKS     =                 2.62                                                  DISTANCE=                 8000                                                  METAL_IN=                    0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             Eg��!溑@����%^�A�$}Y(3,?�L�҄�@��F٠aF?�L��7���@:EZ� ��@7-����@6b�]��@4E�g���Ei�1��6@���c�hAͦ�1�� ?�Waq�+@���9��F?�W_��IG��@:/�لT�@7���m�@6Q���@�@46չ��EkVH�C@����(�A���G-@?�&ѓ.N@�����pF?�%#�,��@:#��o�e@7��ۇ�@6H[��@4-{Pm�
\ No newline at end of file
diff --git a/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
deleted file mode 100644
index d8d7bbbe..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
+++ /dev/null
@@ -1,44 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   73 / length of dimension 1                          NAXIS2  =                  161 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   10 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'K       '                                                            TTYPE9  = 'm_nirc2_J'                                                           TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_Kp'                                                          TFORM10 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MergedBaraffePisaEkstromParsec'                                      HIERARCH EVOMODELVERSION = 'None    '                                           LOGAGE  =                  6.7                                                  AKS     =                  2.7                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = 0.0                                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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diff --git a/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits b/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits
deleted file mode 100644
index d8eb7cd1..00000000
--- a/spisea/tests/isochrones/iso_9.70_0.00_01000_p0.00.fits
+++ /dev/null
@@ -1,53 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   81 / length of dimension 1                          NAXIS2  =                  231 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   11 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'D       '                                                            TTYPE9  = 'm_nirc2_Kp'                                                          TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_H'                                                           TFORM10 = 'D       '                                                            TTYPE11 = 'm_nirc2_J'                                                           TFORM11 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MISTv1  '                                                            HIERARCH EVOMODELVERSION = 'MISTv1.2'                                           LOGAGE  =                  9.7                                                  AKS     =                  0.0                                                  DISTANCE=                 1000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = -0.00616030870481844                                       WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                      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\ No newline at end of file

From 984e34f4cf804cf0ed2f815d5c7c1d190f1769c7 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Feb 2026 16:16:36 -0800
Subject: [PATCH 26/55] fixing typo bug

---
 spisea/tests/test_synthetic.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index f02bbfa3..2a909585 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -156,7 +156,7 @@ def test_IsochronePhot(plot=False):
         red_law=redlaw,
         filters=filt_list,
         mass_sampling=mass_sampling,
-        iso_dir=iso_dir
+        iso_dir=iso_dir,
         recomp=True
     )
     endTime = time.time()

From 2beaf10f471096c84927bb5dd2b92627f608a015 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Feb 2026 16:18:50 -0800
Subject: [PATCH 27/55] adding v2.3 work

---
 docs/contributors.rst | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/docs/contributors.rst b/docs/contributors.rst
index 714e4f94..6dac7d1e 100644
--- a/docs/contributors.rst
+++ b/docs/contributors.rst
@@ -37,7 +37,9 @@ what operating system is used
 
 Sage Hironaka Remulla -- added Rubin Observatory filters
 
-Lingfeng Wei -- bugfix to improve creation of iso_dir in IsochronePhot
+Lingfeng Wei -- bugfix to improve creation of iso_dir in
+IsochronePhot, implemented faster cluster generation and test
+functions for primary and companion star mass generation (v2.3)
 
 Macy Huston -- New metallicity bound + isochrone filter checks,
 imf_mass_lim bugfix, roman filter bugfix, added Euclid filters, Synthpop compatibility

From e384cf19fda8d51d7e69dd207e11ee34ec53b228 Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@berkeley.edu>
Date: Mon, 23 Feb 2026 12:32:36 +0100
Subject: [PATCH 28/55] add ST mag conversion

---
 spisea/synthetic.py | 51 +++++++++++++++++++++++++++++++++++++++++++--
 1 file changed, 49 insertions(+), 2 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index d8f17d87..6ddd4ecb 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -238,7 +238,8 @@ def _make_star_systems_table(self, mass, isMulti, sysMass):
         # effect is so small
         # Convert nan_to_num to avoid errors on greater than, less than comparisons
         star_systems_phase_non_nan = np.nan_to_num(star_systems['phase'], nan=-99)
-        bad = np.where( (star_systems_phase_non_nan > 5) & (star_systems_phase_non_nan < 101) & (star_systems_phase_non_nan != 9) & (star_systems_phase_non_nan != -99))
+        bad = np.where( (star_systems_phase_non_nan > 5) & (star_systems_phase_non_nan < 101) & 
+                        (star_systems_phase_non_nan != 9) & (star_systems_phase_non_nan != -99))
         # Print warning, if desired
         verbose=False
         if verbose:
@@ -324,7 +325,8 @@ def _make_companions_table(self, star_systems, compMass):
                 companions['log_a'][ii] = self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx'][ii]])
             
             companions['e'] = self.imf._multi_props.random_e(np.random.rand(N_comp_tot))
-            companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(np.random.rand(N_comp_tot),np.random.rand(N_comp_tot),np.random.rand(N_comp_tot))
+            companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
+                                            np.random.rand(N_comp_tot),np.random.rand(N_comp_tot),np.random.rand(N_comp_tot))
 
 
         # Make an array that maps system index (ii), companion index (cc) to
@@ -1090,6 +1092,12 @@ def __init__(self, logAge, AKs, distance,
 
             self.make_photometry(rebin=rebin, vega=vega, comp_filters=comp_filters)
 
+        # Drop filters in the saved file that we don't actually want here
+        all_filters = ['m_'+get_filter_col_name(f) for f in filters]
+        drop_columns = [col for col in self.points.columns if (col[:2]=='m_' and 
+                        (col not in all_filters))]
+        self.points.remove_columns(drop_columns)
+
         return
 
     def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
@@ -1892,3 +1900,42 @@ def calc_ab_vega_filter_conversion(filt_str):
 
     return vega_mag_ab
 
+def calc_st_vega_filter_conversion(filt_str):
+    """
+    Function to calculate the conversion between
+    ST and Vega magnitudes for a given filter:
+    m_ST - m_vega
+
+    Note: this conversion is just the vega magnitude in 
+    ST system
+
+    Parameters:
+    -----------
+    filt_str: string
+        Filter identification string
+    """
+    # Get filter info
+    filt = get_filter_info(filt_str)
+    
+    # Interpolate the filter function to be the exact same sampling as the
+    # vega spectrum
+    c = 2.997*10**18 # A / s
+    filt_interp = scipy.interpolate.interp1d(filt.wave, filt.throughput, kind='linear', bounds_error=False,
+                                                fill_value=0)
+    s_interp = filt_interp(vega.wave)
+
+    # Calculate the numerator 
+    diff = np.diff(vega.wave)
+    numerator = np.sum(vega.flux[:-1] * s_interp[:-1] * diff)
+    
+    # Now we need to intergrate the filter response for the denominator
+    denominator = np.sum(s_interp[:-1] * diff)
+    # Fλ must be in erg cm–2 sec–1 Å–1
+
+    # Calculate vega AB magnitude. This is the conversion
+    vega_mag_st = -2.5 * np.log10(numerator / denominator) - 21.1
+
+    print('For {0}, m_st - m_vega = {1}'.format(filt_str, vega_mag_st))
+
+    return vega_mag_st
+

From 5f299902d4968f48fb5efccdb7895e89e59c1e5e Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@berkeley.edu>
Date: Mon, 23 Feb 2026 17:01:52 +0100
Subject: [PATCH 29/55] store verbose variable in IsochronePhot

---
 spisea/synthetic.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 70b9b6e1..22958efe 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1118,6 +1118,7 @@ def __init__(self, logAge, AKs, distance,
                           'ubv,R', 'ubv,I'],
                 verbose=False):
         self.metallicity = metallicity
+        self.verbose=verbose
 
         # Make the iso_dir, if it doesn't already exist
         if not os.path.exists(iso_dir):

From b6c47af04eb750b8341b55d487ca858396f83ae2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 18:29:38 -0800
Subject: [PATCH 30/55] Trim trailing white spaces

---
 spisea/atmospheres.py           | 390 ++++++++++++++++----------------
 spisea/conftest.py              |   4 +-
 spisea/evolution.py             | 340 ++++++++++++++--------------
 spisea/exceptions.py            |   4 +-
 spisea/filters.py               |  62 ++---
 spisea/ifmr.py                  | 248 ++++++++++----------
 spisea/reddening.py             | 390 ++++++++++++++++----------------
 spisea/synthetic.py             |  24 +-
 spisea/tests/test_exceptions.py |   2 +-
 spisea/tests/test_models.py     |  26 +--
 spisea/tests/test_reddening.py  |  30 +--
 spisea/tests/test_synthetic.py  | 178 +++++++--------
 12 files changed, 849 insertions(+), 849 deletions(-)

diff --git a/spisea/atmospheres.py b/spisea/atmospheres.py
index 5c206ee8..9867db81 100755
--- a/spisea/atmospheres.py
+++ b/spisea/atmospheres.py
@@ -18,7 +18,7 @@ def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4
     """
     # Open catalog fits file and break out row indices
     catalog = Table.read('{0}/grid/{1}/catalog.fits'.format(os.environ['PYSYN_CDBS'], model_dir))
-    
+
     teff_arr = []
     z_arr = []
     logg_arr = []
@@ -36,11 +36,11 @@ def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4
     metal_list = np.unique(np.array(z_arr))
     metal_idx = np.argmin(np.abs(metal_list - metallicity))
     metallicity_new = metal_list[metal_idx]
-    
+
     z_filt = np.where(z_arr == metal_list[metal_idx])
     teff_arr = teff_arr[z_filt]
     logg_arr = logg_arr[z_filt]
-    
+
     # # Now find the closest atmosphere in parameter space to
     # # the one we want. We'll find the match with the lowest
     # # fractional difference
@@ -52,38 +52,38 @@ def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4
     #
     # temperature_new = teff_arr[idx_f]
     # gravity_new = logg_arr[idx_f]
-    
+
     # First check if temperature within bounds
     temperature_new = temperature
     if temperature > np.max(teff_arr):
         temperature_new = np.max(teff_arr)
     if temperature < np.min(teff_arr):
         temperature_new = np.min(teff_arr)
-    
+
     # If temperature within bounds, then check if metallicity within bounds
     teff_diff = np.abs(teff_arr - temperature)
     sorted_min_diffs = np.unique(teff_diff)
-    
+
     ## Find two closest temperatures
     teff_close_1 = teff_arr[np.where(teff_diff == sorted_min_diffs[0])[0][0]]
     teff_close_2 = teff_arr[np.where(teff_diff == sorted_min_diffs[1])[0][0]]
-    
+
     logg_arr_1 = logg_arr[np.where(teff_arr == teff_close_1)]
     logg_arr_2 = logg_arr[np.where(teff_arr == teff_close_2)]
-    
+
     ## Switch to most conservative bound of logg out of two closest temps
     gravity_new = gravity
     if gravity > np.min([np.max(logg_arr_1), np.max(logg_arr_2)]):
         gravity_new = np.min([np.max(logg_arr_1), np.max(logg_arr_2)])
     if gravity < np.max([np.min(logg_arr_1), np.min(logg_arr_2)]):
         gravity_new = np.max([np.min(logg_arr_1), np.min(logg_arr_2)])
-    
+
     if verbose:
         # Print out changes, if any
         if temperature_new != temperature:
             teff_msg = 'Changing to T={0:6.0f} for met={1:4.2f} T={2:6.0f} logg={3:4.2f}'
             print( teff_msg.format(temperature_new, metallicity, temperature, gravity))
-        
+
         if gravity_new != gravity:
             logg_msg = 'Changing to logg={0:4.2f} for met={1:4.2f} T={2:6.0f} logg={3:4.2f}'
             print( logg_msg.format(gravity_new, metallicity, temperature, gravity))
@@ -91,12 +91,12 @@ def get_atmosphere_bounds(model_dir, metallicity=0, temperature=20000, gravity=4
     if metallicity_new != metallicity:
         logg_msg = 'Changing to met={0:4.2f} for met={1:4.2f} T={2:6.0f} logg={3:4.2f}'
         print( logg_msg.format(metallicity_new, metallicity, temperature, gravity))
-    
+
     return (temperature_new, gravity_new, metallicity_new)
 
 def get_kurucz_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=False):
     """
-    Return atmosphere from the Kurucz pysnphot grid 
+    Return atmosphere from the Kurucz pysnphot grid
     (`Kurucz 1993 <http://www.stsci.edu/hst/observatory/crds/k93models.html>`_).
 
     Grid Range:
@@ -115,7 +115,7 @@ def get_kurucz_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=Fal
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         Always false for this particular function
     """
@@ -127,7 +127,7 @@ def get_kurucz_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=Fal
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('k93models', temperature, metallicity, gravity)
 
     # Do some error checking
@@ -142,10 +142,10 @@ def get_kurucz_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=Fal
 
 def get_castelli_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=False):
     """
-    Return atmospheres from the pysynphot ATLAS9 atlas 
+    Return atmospheres from the pysynphot ATLAS9 atlas
     (`Castelli & Kurucz 2004 <http://www.stsci.edu/hst/observatory/crds/castelli_kurucz_atlas.html>`_).
 
-    Grid Range: 
+    Grid Range:
 
     * Teff: 3500 - 50000 K
     * gravity: 0 - 5.0 cgs
@@ -161,7 +161,7 @@ def get_castelli_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=F
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -178,9 +178,9 @@ def get_castelli_atmosphere(metallicity=0, temperature=20000, gravity=4, rebin=F
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('ck04models', temperature, metallicity, gravity)
-        
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -205,7 +205,7 @@ def get_nextgen_atmosphere(metallicity=0, temperature=5000, gravity=4, rebin=Fal
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('nextgen', temperature, metallicity, gravity)
 
     # Do some error checking
@@ -239,7 +239,7 @@ def get_amesdusty_atmosphere(metallicity=0, temperature=5000, gravity=4, rebin=F
 def get_phoenix_atmosphere(metallicity=0, temperature=5000, gravity=4,
                                rebin=False):
     """
-    Return atmosphere from the pysynphot 
+    Return atmosphere from the pysynphot
     `PHOENIX atlas <http://www.stsci.edu/hst/observatory/crds/SIfileInfo/pysynphottables/index_phoenix_models_html>`_.
 
     Parameters
@@ -252,7 +252,7 @@ def get_phoenix_atmosphere(metallicity=0, temperature=5000, gravity=4,
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -267,7 +267,7 @@ def get_phoenix_atmosphere(metallicity=0, temperature=5000, gravity=4,
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('phoenix', temperature, metallicity, gravity)
 
     # Do some error checking
@@ -294,12 +294,12 @@ def get_cmfgenRot_atmosphere(metallicity=0, temperature=24000, gravity=4.3, rebi
         if verbose:
             print( logg_msg.format(4.3, temperature, gravity))
         gravity = 4.3
-        
+
     if rebin:
         sp = pysynphot.Icat('cmfgen_rot_rebin', temperature, metallicity, gravity)
     else:
         sp = pysynphot.Icat('cmfgen_rot', temperature, metallicity, gravity)
-        
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -313,7 +313,7 @@ def get_cmfgenRot_atmosphere(metallicity=0, temperature=24000, gravity=4.3, rebi
 def get_cmfgenRot_atmosphere_closest(metallicity=0, temperature=24000, gravity=4.3, rebin=True,
                                          verbose=False):
     """
-    For a given stellar atmosphere, get extract the closest possible match in 
+    For a given stellar atmosphere, get extract the closest possible match in
     Teff/logg space. Note that this is different from the normal routine
     which interpolates along the input grid to get final spectrum. We can't
     do this here because the Fierro+15 atmosphere grid is so sparse
@@ -348,7 +348,7 @@ def get_cmfgenRot_atmosphere_closest(metallicity=0, temperature=24000, gravity=4
     # fractional difference
     teff_diff = (teff_arr - temperature) / temperature
     logg_diff = (logg_arr - gravity) / gravity
-    
+
     diff_tot = abs(teff_diff) + abs(logg_diff)
     idx_f = np.where(diff_tot == min(diff_tot))[0][0]
 
@@ -356,7 +356,7 @@ def get_cmfgenRot_atmosphere_closest(metallicity=0, temperature=24000, gravity=4
     # pysynphot object
     infile = cat[idx_f]['FILENAME'].split('.')
     spec = Table.read('{0}/{1}.fits'.format(root_dir, infile[0]))
-    
+
     # Now, the CMFGEN atmospheres assume a distance of 1 kpc, while the the
     # ATLAS models are in FLAM at the surface. So, we need to multiply the
     # CMFGEN atmospheres by (1000/R)**2. in order to convert to FLAM on surface.
@@ -370,13 +370,13 @@ def get_cmfgenRot_atmosphere_closest(metallicity=0, temperature=24000, gravity=4
 
     radius = np.sqrt( lum / (4.0 * np.pi * teff**4. * sigma) ) # in cm
     radius /= 3.08*10**18 # in pc
-    
+
 
     # Make the pysynphot spectrum
     w = spec['Wavelength']
     f = spec['Flux'] * (1000 / radius)**2.
     sp = pysynphot.ArraySpectrum(w,f)
-    
+
     #sp = pysynphot.FileSpectrum('{0}/{1}.fits'.format(root_dir, infile[0]))
 
     # Print out parameters of match, if desired
@@ -398,7 +398,7 @@ def get_cmfgenNoRot_atmosphere(metallicity=0, temperature=22500, gravity=3.98, r
         sp = pysynphot.Icat('cmfgen_norot_rebin', temperature, metallicity, gravity)
     else:
         sp = pysynphot.Icat('cmfgen_norot', temperature, metallicity, gravity)
-        
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -429,9 +429,9 @@ def get_cmfgenNoRot_atmosphere(metallicity=0, temperature=30000, gravity=4.14):
 
 def get_phoenixv16_atmosphere(metallicity=0, temperature=4000, gravity=4, rebin=True):
     """
-    Return PHOENIX v16 atmospheres from  
-    `Husser et al. 2013 <https://ui.adsabs.harvard.edu/abs/2013A%26A...553A...6H/abstract>`_. 
-    
+    Return PHOENIX v16 atmospheres from
+    `Husser et al. 2013 <https://ui.adsabs.harvard.edu/abs/2013A%26A...553A...6H/abstract>`_.
+
     Models originally downloaded via `ftp <http://phoenix.astro.physik.uni-goettingen.de/?page_id=15>`_.
     Solar metallicity and [alpha/Fe] is used.
 
@@ -451,7 +451,7 @@ def get_phoenixv16_atmosphere(metallicity=0, temperature=4000, gravity=4, rebin=
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -472,9 +472,9 @@ def get_phoenixv16_atmosphere(metallicity=0, temperature=4000, gravity=4, rebin=
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat(atm_model_name, temperature, metallicity, gravity)
-    
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -487,14 +487,14 @@ def get_phoenixv16_atmosphere(metallicity=0, temperature=4000, gravity=4, rebin=
 
 def get_BTSettl_2015_atmosphere(metallicity=0, temperature=2500, gravity=4, rebin=True):
     """
-    Return atmosphere from CIFIST2011_2015 grid 
-    (`Allard et al. 2012 <https://ui.adsabs.harvard.edu/abs/2012RSPTA.370.2765A/abstract>`_, 
+    Return atmosphere from CIFIST2011_2015 grid
+    (`Allard et al. 2012 <https://ui.adsabs.harvard.edu/abs/2012RSPTA.370.2765A/abstract>`_,
     `Baraffe et al. 2015 <https://ui.adsabs.harvard.edu/abs/2015A%26A...577A..42B/abstract>`_ )
 
     Grid originally downloaded from `website <https://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011_2015/FITS/>`_.
 
     Grid Range:
-    
+
     * Teff: 1200 - 7000 K
     * gravity: 2.5 - 5.5 cgs
     * [M/H] = 0
@@ -509,11 +509,11 @@ def get_BTSettl_2015_atmosphere(metallicity=0, temperature=2500, gravity=4, rebi
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
-        which is often sufficient synthetic photometry in most cases.    
+        which is often sufficient synthetic photometry in most cases.
     """
     if rebin == True:
         atm_name = 'BTSettl_2015_rebin'
@@ -528,10 +528,10 @@ def get_BTSettl_2015_atmosphere(metallicity=0, temperature=2500, gravity=4, rebi
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat(atm_name, temperature, metallicity, gravity)
-        
-    
+
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -544,7 +544,7 @@ def get_BTSettl_2015_atmosphere(metallicity=0, temperature=2500, gravity=4, rebi
 
 def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=True):
     """
-    Return atmosphere from CIFIST2011 grid 
+    Return atmosphere from CIFIST2011 grid
     (`Allard et al. 2012 <https://ui.adsabs.harvard.edu/abs/2012RSPTA.370.2765A/abstract>`_)
 
     Grid originally downloaded `here <https://phoenix.ens-lyon.fr/Grids/BT-Settl/>`_
@@ -552,16 +552,16 @@ def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=T
     Notes
     ------
     Grid Range:
-    
+
     * [M/H] = -2.5, -2.0, -1.5, -1.0, -0.5, 0, 0.5
-    
+
     Teff and gravity ranges depend on metallicity:
 
     [M/H] = -2.5
 
     * Teff: 2600 - 4600 K
     * gravity: 4.5 - 5.5
-    
+
     [M/H] = -2.0
 
     * Teff: 2600 - 7000
@@ -575,7 +575,7 @@ def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=T
     [M/H] = -1.0
 
     * Teff: 2600 - 7000
-    * gravity: Teff < 3200 --> 4.5 - 5.5; Teff > 3200 --> 2.5 - 5.5 
+    * gravity: Teff < 3200 --> 4.5 - 5.5; Teff > 3200 --> 2.5 - 5.5
 
     [M/H] = -0.5
 
@@ -609,7 +609,7 @@ def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=T
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -628,10 +628,10 @@ def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=T
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat(atm_name, temperature, metallicity, gravity)
-        
-    
+
+
     # Do some error checking
     idx = np.where(sp.flux != 0)[0]
     if len(idx) == 0:
@@ -644,7 +644,7 @@ def get_BTSettl_atmosphere(metallicity=0, temperature=2500, gravity=4.5, rebin=T
 
 def get_wdKoester_atmosphere(metallicity=0, temperature=20000, gravity=7):
     """
-    Return white dwarf atmospheres from  
+    Return white dwarf atmospheres from
     `Koester et al. 2010 <https://ui.adsabs.harvard.edu/abs/2010MmSAI..81..921K/abstract>`_
 
     Parameters
@@ -657,7 +657,7 @@ def get_wdKoester_atmosphere(metallicity=0, temperature=20000, gravity=7):
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -672,14 +672,14 @@ def get_wdKoester_atmosphere(metallicity=0, temperature=20000, gravity=7):
         print( '  temperature = %d' % temperature)
         print( '  metallicity = %.1f' % metallicity)
         print( '  log gravity = %.1f' % gravity)
-        
+
     return sp
 
 def get_atlas_phoenix_atmosphere(metallicity=0, temperature=5250, gravity=4):
     """
     Return atmosphere that is a linear merge of atlas ck04 model and phoenixV16.
 
-    Only valid for temps between 5000 - 5500K, gravity from 0 = 5.0 
+    Only valid for temps between 5000 - 5500K, gravity from 0 = 5.0
     """
     try:
         sp = pysynphot.Icat('merged_atlas_phoenix', temperature, metallicity, gravity)
@@ -689,7 +689,7 @@ def get_atlas_phoenix_atmosphere(metallicity=0, temperature=5250, gravity=4):
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('merged_atlas_phoenix', temperature, metallicity, gravity)
 
     # Do some error checking
@@ -707,7 +707,7 @@ def get_BTSettl_phoenix_atmosphere(metallicity=0, temperature=5250, gravity=4):
     Return atmosphere that is a linear merge of BTSettl_CITFITS2011_2015 model
     and phoenixV16.
 
-    Only valid for temps between 3200 - 3800K, gravity from 2.5 - 5.5 
+    Only valid for temps between 3200 - 3800K, gravity from 2.5 - 5.5
     """
     try:
         sp = pysynphot.Icat('merged_BTSettl_phoenix', temperature, metallicity, gravity)
@@ -717,7 +717,7 @@ def get_BTSettl_phoenix_atmosphere(metallicity=0, temperature=5250, gravity=4):
                                                    metallicity=metallicity,
                                                    temperature=temperature,
                                                    gravity=gravity)
-    
+
         sp = pysynphot.Icat('merged_BTSettl_phoenix', temperature, metallicity, gravity)
 
     # Do some error checking
@@ -734,7 +734,7 @@ def get_BTSettl_phoenix_atmosphere(metallicity=0, temperature=5250, gravity=4):
 def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose=False,
                               rebin=True):
     """
-    Return a stellar atmosphere from a suite of different model grids, 
+    Return a stellar atmosphere from a suite of different model grids,
     depending  on the input temperature, (all values in K).
 
     Parameters
@@ -747,7 +747,7 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -758,7 +758,7 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
 
     Notes
     -----
-    The underlying stellar model grid used changes as a function of 
+    The underlying stellar model grid used changes as a function of
     stellar temperature (in K):
 
     * T > 20,000: ATLAS
@@ -769,14 +769,14 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
     For T < 3800, there is an additional gravity and metallicity
     dependence:
 
-    If T < 3800 and [M/H] = 0: 
-    
+    If T < 3800 and [M/H] = 0:
+
     * T < 3800, logg < 2.5: PHOENIX v16
     * 3200 <= T < 3800, logg > 2.5: BTSettl_CIFITS2011_2015/PHOENIXV16 merge
     * 3200 < T <= 1200, logg > 2.5: BTSettl_CIFITS2011_2015
 
     Otherwise, if T < 3800 and [M/H] != 0:
-    
+
     * T < 3800: PHOENIX v16
 
     References:
@@ -785,21 +785,21 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
     * PHOENIXv16 (`Husser et al. 2013 <https://ui.adsabs.harvard.edu/abs/2013A%26A...553A...6H/abstract>`_)
     * BTSettl_CIFITS2011_2015: Baraffee+15, Allard+ (https://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011_2015/SPECTRA/)
 
-    LTE WARNING: 
+    LTE WARNING:
 
     The ATLAS atmospheres are calculated with LTE, and so they
     are less accurate when non-LTE conditions apply (e.g. T > 20,000
     K). Ultimately we'd like to add a non-LTE atmosphere grid for
     the hottest stars in the future.
 
-    HOW BOUNDARIES BETWEEN MODELS ARE TREATED: 
+    HOW BOUNDARIES BETWEEN MODELS ARE TREATED:
 
-    At the boundary between two models grids a temperature range is defined 
-    where the resulting atmosphere is a weighted average between the two 
+    At the boundary between two models grids a temperature range is defined
+    where the resulting atmosphere is a weighted average between the two
     grids. Near one boundary one model
-    is weighted more heavily, while at the other boundary the other 
-    model is weighted more heavily. These are calculated in the 
-    temperature ranges where we switch between model grids, to 
+    is weighted more heavily, while at the other boundary the other
+    model is weighted more heavily. These are calculated in the
+    temperature ranges where we switch between model grids, to
     ensure a smooth transition.
     """
     # For T < 3800, atmosphere depends on metallicity + gravity.
@@ -815,7 +815,7 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
                                                 temperature=temperature,
                                                 gravity=gravity,
                                                 rebin=rebin)
- 
+
         if (temperature >= 3200) & (temperature < 3800) & (gravity > 2.5):
             if verbose:
                 print( 'BTSettl/Phoenixv16 merged atmosphere')
@@ -831,7 +831,7 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
                                             temperature=temperature,
                                             gravity=gravity,
                                             rebin=rebin)
-        
+
     if (temperature <= 3800) & (metallicity != 0):
         if verbose:
             print( 'Phoenixv16 atmosphere')
@@ -855,7 +855,7 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
         return get_atlas_phoenix_atmosphere(metallicity=metallicity,
                                         temperature=temperature,
                                         gravity=gravity)
-    
+
     if (temperature >= 5500) & (temperature < 20000):
         if verbose:
             print( 'ATLAS merged atmosphere')
@@ -875,14 +875,14 @@ def get_merged_atmosphere(metallicity=0, temperature=20000, gravity=4.5, verbose
         #                               temperature=temperature,
         #                               gravity=gravity)
 
-    
+
 
 
 def get_wd_atmosphere(metallicity=0, temperature=20000, gravity=4, verbose=False):
     """
-    Return the white dwarf atmosphere from 
-    `Koester et al. 2010 <https://ui.adsabs.harvard.edu/abs/2010MmSAI..81..921K/abstract>`_. 
-    If desired parameters are 
+    Return the white dwarf atmosphere from
+    `Koester et al. 2010 <https://ui.adsabs.harvard.edu/abs/2010MmSAI..81..921K/abstract>`_.
+    If desired parameters are
     outside of grid, return a blackbody spectrum instead
 
     Parameters
@@ -895,7 +895,7 @@ def get_wd_atmosphere(metallicity=0, temperature=20000, gravity=4, verbose=False
 
     gravity: float
         The stellar gravity, in cgs units
-        
+
     rebin: boolean
         If true, rebins the atmospheres so that they are the same
         resolution as the Castelli+04 atmospheres. Default is False,
@@ -911,7 +911,7 @@ def get_wd_atmosphere(metallicity=0, temperature=20000, gravity=4, verbose=False
         return get_wdKoester_atmosphere(metallicity=metallicity,
                                             temperature=temperature,
                                             gravity=gravity)
-    
+
     except pysynphot.exceptions.ParameterOutOfBounds:
         # Use a black-body atmosphere.
         bbspec = get_bb_atmosphere(temperature=temperature, verbose=verbose)
@@ -942,29 +942,29 @@ def get_bb_atmosphere(metallicity=None, temperature=20_000, gravity=None,
         warnings.warn(
             'Only `temperature` keyword is used for black-body atmosphere'
         )
-    
+
     if verbose:
         print('Black-body atmosphere')
-    
+
     # Modify pysynphot's default waveset to specified bounds
     pysynphot.refs.set_default_waveset(
         minwave=wave_min, maxwave=wave_max, num=wave_num
     )
-        
+
     # Get black-body atmosphere for specified temperature from pysynphot
     bbspec = pysynphot.spectrum.BlackBody(temperature)
-    
+
     # pysynphot `BlackBody` generates spectrum in `photlam`, need in `flam`
     bbspec.convert('flam')
-    
+
     # `BlackBody` spectrum is normalized to solar radius star at 1 kiloparsec.
     # Need to remove this normalization for SPISEA by multiplying bbspec
     # by (1000 * 1 parsec / 1 Rsun)**2 = (1000 * 3.08e18 cm / 6.957e10 cm)**2
     bbspec *= (1000 * 3.086e18 / 6.957e10)**2
-    
+
     return bbspec
 
-    
+
 #--------------------------------------#
 # Atmosphere formatting functions
 #--------------------------------------#
@@ -980,7 +980,7 @@ def download_CMFGEN_atmospheres(Table_rot, Table_norot):
     Fierro+15 paper
 
     Website addresses are hardcoded
-    
+
     Puts downloaded models in the current working directory.
     """
     print( 'WARNING: THIS DOES NOT COMPLETELY WORK')
@@ -1049,7 +1049,7 @@ def organize_CMFGEN_atmospheres(path_to_dir):
     """
     # First, record current working directory to return to later
     start_dir = os.getcwd()
-    
+
     # Enter atmosphere directory, collect rotating and non-rotating
     # file names (assumed to all start with "t")
     os.chdir(path_to_dir)
@@ -1074,10 +1074,10 @@ def organize_CMFGEN_atmospheres(path_to_dir):
     # Also move Tables with model parameters into correct directory
     os.system('mv Table_rot.txt cmfgenF15_rot')
     os.system('mv Table_noRot.txt cmfgenF15_noRot')
-    
+
     # Return to original directory
     os.chdir(start_dir)
-        
+
     return
 
 def make_CMFGEN_catalog(path_to_dir):
@@ -1099,10 +1099,10 @@ def make_CMFGEN_catalog(path_to_dir):
     """
     # Record current working directory for later
     start_dir = os.getcwd()
-    
+
     # Enter atmosphere directory
     os.chdir(path_to_dir)
-   
+
     # Extract parameters for each atmosphere
     # Note: can't rely on filename for this because not precise enough!!
 
@@ -1117,7 +1117,7 @@ def make_CMFGEN_catalog(path_to_dir):
     #    lum = float(lumtmp[0][:-5]) * 1000.0 # In L_sun
 
     #    mass = float(lumtmp[0][5:-1]) # In M_sun
-        
+
         # Need to calculate log g from T and L (cgs)
     #    lum_sun = 3.846 * 10**33 # erg/s
     #    M_sun = 2 * 10**33 # g
@@ -1145,18 +1145,18 @@ def make_CMFGEN_catalog(path_to_dir):
         #---NOTE: THE FOLLOWING DEPENDS ON FINAL LOCATION OF CATALOG FILE---#
         #path = path_to_dir + '/' + names[i]
         path = names[i] + '.fits[Flux]'
-        
+
         index_str.append(index)
         name_str.append(path)
-    
+
     catalog = Table([index_str, name_str], names = ('INDEX', 'FILENAME'))
 
     # Create catalog.fits file in directory with the models
     catalog.write('catalog.fits', format = 'fits')
-    
+
     # Move back to original directory, create the catalog.fits file
     os.chdir(start_dir)
-    
+
     return
 
 def cdbs_cmfgen(path_to_dir, path_to_cdbs_dir):
@@ -1192,23 +1192,23 @@ def cdbs_cmfgen(path_to_dir, path_to_cdbs_dir):
         unique = np.unique(wave, return_index=True)
         wave = wave[unique[1]]
         flux = flux[unique[1]]
-        
-        # Make fits table from individual columns. 
+
+        # Make fits table from individual columns.
         c0 = fits.Column(name='Wavelength', format='D', array=wave)
         c1 = fits.Column(name='Flux', format='E', array=flux)
 
         cols = fits.ColDefs([c0, c1])
         tbhdu = fits.BinTableHDU.from_columns(cols)
 
-        #Adding unit keywords        
+        #Adding unit keywords
         tbhdu.header['TUNIT1'] = 'ANGSTROM'
         tbhdu.header['TUNIT2'] = 'FLAM'
 
         prihdu = fits.PrimaryHDU()
-    
+
         finalhdu = fits.HDUList([prihdu, tbhdu])
         finalhdu.writeto(i[:-4]+'.fits', overwrite=True)
-        
+
         print( 'Done {0:2.0f} of {1:2.0f}'.format(counter, len(files)))
 
     # Return to original directory, copy over new .fits files to cdbs directory
@@ -1225,7 +1225,7 @@ def rebin_cmfgen(cdbs_path, rot=True):
 
     cdbs_path: path to cdbs directory
     rot=True for rotating models (cmfgen_rot), False for non-rotating models
-    
+
     makes new directory in cdbs/grid: cmfgen_rot_rebin or cmfgen_norot_rebin
     """
     # Get an atlas ck04 model, we will use this to set wavelength grid
@@ -1241,7 +1241,7 @@ def rebin_cmfgen(cdbs_path, rot=True):
         tmp = cdbs_path+'/grid/cmfgen_norot/t0200l0007m009n.fits'
         path = cdbs_path+'/grid/cmfgen_norot_rebin/'
         orig_path = cdbs_path+'/grid/cmfgen_norot/'
-        
+
     cmfgen_hdu = fits.open(tmp)
     header0 = cmfgen_hdu[0].header
     # Create rebin directories if they don't already exist. Copy over
@@ -1256,7 +1256,7 @@ def rebin_cmfgen(cdbs_path, rot=True):
     files_all = [cat[ii][1].split('[')[0] for ii in range(len(cat))]
 
     # First column in new files will be for [atlas] wavelength
-    c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)   
+    c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)
 
     # For each catalog.fits entry, read the unbinned spectrum and rebin to
     # the atlas resolution. Make a new fits file in rebin directory
@@ -1268,16 +1268,16 @@ def rebin_cmfgen(cdbs_path, rot=True):
         temp = float(vals[0])
         metal = float(vals[1])
         grav = float(vals[2])
-    
+
         # Fetch the spectrum
-        if rot == True:           
+        if rot == True:
             sp = pysynphot.Icat('cmfgen_rot', temp, metal, grav)
         else:
             sp = pysynphot.Icat('cmfgen_norot', temp, metal, grav)
 
         # Rebin
         flux_rebin = rebin_spec(sp.wave, sp.flux, sp_atlas.wave)
-        c1 = fits.Column(name='Flux', format='E', array=flux_rebin)                
+        c1 = fits.Column(name='Flux', format='E', array=flux_rebin)
 
         # Make the FITS file from the columns with header
         cols = fits.ColDefs([c0,c1])
@@ -1302,7 +1302,7 @@ def organize_PHOENIXv16_atmospheres(path_to_dir, met_str='m00'):
 
     path_to_dir is the path to the directory containing all of the downloaded
     files
-    
+
     met_str is the name of the current metallicity
 
     Creates new fits files for each atmosphere: phoenix<metallicity>_<temp>.fits,
@@ -1319,7 +1319,7 @@ def organize_PHOENIXv16_atmospheres(path_to_dir, met_str='m00'):
         pass
     else:
         os.mkdir(sub_dir)
-    
+
     # Extract wavelength array, make column for later
     wavefile = fits.open('WAVE_PHOENIX-ACES-AGSS-COND-2011.fits')
     wave = wavefile[0].data
@@ -1342,7 +1342,7 @@ def organize_PHOENIXv16_atmospheres(path_to_dir, met_str='m00'):
         for f in files:
             # Extract the logg out of filename
             logg = f[9:13]
-            
+
             # Extract fluxes from file
             spectrum = fits.open(f)
             flux = spectrum[0].data
@@ -1351,11 +1351,11 @@ def organize_PHOENIXv16_atmospheres(path_to_dir, met_str='m00'):
             # Make Column object with fluxes, add to table
             col = Column(flux, name = 'g{0:2.1f}'.format(float(logg)))
             t.add_column(col)
-            
+
         # Now, construct final fits file for the given temp
         outname = 'phoenix{0}_{1:05d}.fits'.format(met_str, temp)
-        t.write('{0}/{1}'.format(sub_dir, outname), format = 'fits', overwrite = True) 
-        
+        t.write('{0}/{1}'.format(sub_dir, outname), format = 'fits', overwrite = True)
+
         # Progress counter for user
         i += 1
         print( 'Done {0:d} of {1:d}'.format(i, len(temp_arr)))
@@ -1372,18 +1372,18 @@ def make_PHOENIXv16_catalog(path_to_dir, met_str='m00'):
 
     path_to_directory is the path to the directory with the reformatted
     models (i.e. the output from construct_atmospheres, phoenix[met_str])
-    
+
     Puts catalog.fits file in directory the user starts in
     """
     # Save starting directory for later, move into working directory
     start_dir = os.getcwd()
     os.chdir(path_to_dir)
-    
+
     # Extract metallicity from metallicity string
     met = float(met_str[1]) + (float(met_str[2]) * 0.1)
     if 'm' in met_str:
         met *= -1.
-    
+
     # Collect the filenames. Each is a unique temp with many different log g's
     files = glob.glob('phoenix*.fits')
     files.sort()
@@ -1396,7 +1396,7 @@ def make_PHOENIXv16_catalog(path_to_dir, met_str='m00'):
         t = Table.read(i, format='fits')
         keys = t.keys()
         logg_vals = keys[1:]
-        
+
         # Extract temp from filename
         name = i.split('_')
         temp = float(name[1][:-5])
@@ -1409,20 +1409,20 @@ def make_PHOENIXv16_catalog(path_to_dir, met_str='m00'):
             filename_arr.append(filename)
 
     catalog = Table([index_arr, filename_arr], names=('INDEX', 'FILENAME'))
-    
+
     # Return to starting directory, write catalog
     os.chdir(start_dir)
-    
+
     if os.path.exists('catalog.fits'):
         from astropy.table import vstack
-        
+
         prev_catalog = Table.read('catalog.fits', format='fits')
         joined_catalog = vstack([prev_catalog, catalog])
-        
+
         joined_catalog.write('catalog.fits', format='fits', overwrite=True)
     else:
         catalog.write('catalog.fits', format='fits', overwrite=True)
-    
+
     return
 
 def cdbs_PHOENIXv16(path_to_cdbs_dir):
@@ -1443,7 +1443,7 @@ def cdbs_PHOENIXv16(path_to_cdbs_dir):
 
     # Collect the filenames, make necessary changes to each one
     files = glob.glob('phoenix*.fits')
-    
+
     ## Need to sort filenames; glob doesn't always give them in order
     files.sort()
 
@@ -1451,28 +1451,28 @@ def cdbs_PHOENIXv16(path_to_cdbs_dir):
     counter = 0
     for i in files:
         counter += 1
-        
+
         # Read in current FITS table
         cur_table = Table.read(i, format='fits')
-        
+
         cur_table.columns[0].name = 'Wavelength'
-        
+
         num_cols = len(cur_table.colnames)
-        
-        # Multiplying each flux column by 10^-8 for conversion        
+
+        # Multiplying each flux column by 10^-8 for conversion
         for cur_col_index in range(1, num_cols, 1):
             cur_col_name = cur_table.colnames[cur_col_index]
             cur_table[cur_col_name] = cur_table[cur_col_name] * 10.**-8
-        
-        
+
+
         # Construct new FITS file based on old one
         hdu = fits.open(i)
         header_0 = hdu[0].header
         header_1 = hdu[1].header
         sci = hdu[1].data
-        
+
         tbhdu = fits.table_to_hdu(cur_table)
-        
+
         # Copying over the older headers, adding unit keywords
         prihdu = fits.PrimaryHDU(header=header_0)
         tbhdu.header['TUNIT1'] = 'ANGSTROM'
@@ -1489,17 +1489,17 @@ def cdbs_PHOENIXv16(path_to_cdbs_dir):
         tbhdu.header['TUNIT12'] = 'FLAM'
         tbhdu.header['TUNIT13'] = 'FLAM'
         tbhdu.header['TUNIT14'] = 'FLAM'
-        
+
         # Construct and write out final FITS file
         finalhdu = fits.HDUList([prihdu, tbhdu])
         finalhdu.writeto(i, overwrite=True)
-        
+
         hdu.close()
         print( 'Done {0:2.0f} of {1:2.0f}'.format(counter, len(files)))
-    
+
     # Change back to starting directory
     os.chdir(start_dir)
-    
+
     return
 
 def rebin_phoenixV16(cdbs_path):
@@ -1524,7 +1524,7 @@ def rebin_phoenixV16(cdbs_path):
     path = cdbs_path+'/grid/phoenix_v16_rebin/'
     if not os.path.exists(path):
         os.mkdir(path)
-    
+
 
     # Read in the existing catalog.fits file and rebin every spectrum.
     cat = fits.getdata(cdbs_path + '/grid/phoenix_v16/catalog.fits')
@@ -1539,51 +1539,51 @@ def rebin_phoenixV16(cdbs_path):
         temp_arr[ff] = float(vals[0])
         metal_arr[ff] = float(vals[1])
         logg_arr[ff] = float(vals[2])
-    
+
 
     metal_uniq = np.unique(metal_arr)
     temp_uniq = np.unique(temp_arr)
-    
+
     for mm in range(len(metal_uniq)):
         metal = metal_uniq[mm] # metallicity
-        
+
         # Construct str for metallicity (for appropriate directory name)
         met_str = str(int(np.abs(metal))) + str(int((metal % 1.0)*10))
         if metal > 0:
             met_str = 'p' + met_str
         else:
             met_str = 'm' + met_str
-        
+
         # Make directory for current metallicity if it does not exist yet
         if not os.path.exists(path + 'phoenix' + met_str):
             os.mkdir(path + 'phoenix' + met_str)
-        
+
         for tt in range(len(temp_uniq)):
             temp = temp_uniq[tt] # temperature
 
-            # Pick out the list of gravities for this T, Z combo            
+            # Pick out the list of gravities for this T, Z combo
             idx = np.where((metal_arr == metal) & (temp_arr == temp))[0]
             logg_exist = logg_arr[idx]
-            
+
             # All gravities will go in one file. Here is the output
             # file name.
             outfile = path + files_all[idx[0]].split('[')[0]
-            
+
             ## If the rebinned file already exists, continue
             if os.path.exists(outfile):
                 continue
-            
+
             # Build a columns array. One column for each gravity.
             cols_arr = []
 
             # Make the wavelength column, which is first in the cols array.
             c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)
             cols_arr.append(c0)
-            
+
             for gg in range(len(logg_exist)):
                 grav = logg_exist[gg] # gravity
 
-                # Fetch the spectrum                
+                # Fetch the spectrum
                 sp = pysynphot.Icat('phoenix_v16', temp, metal, grav)
                 flux_rebin = rebin_spec(sp.wave, sp.flux, sp_atlas.wave)
 
@@ -1591,7 +1591,7 @@ def rebin_phoenixV16(cdbs_path):
                 name = 'g{0:3.1f}'.format(grav)
                 col = fits.Column(name=name, format='E', array=flux_rebin)
                 cols_arr.append(col)
-                
+
 
             # Make the FITS file from the columns with header.
             cols = fits.ColDefs(cols_arr)
@@ -1607,7 +1607,7 @@ def rebin_phoenixV16(cdbs_path):
             finalhdu.writeto(outfile)
 
             print( 'Finished file ' + outfile + ' with gravities: ', logg_exist)
-            
+
 
     return
 
@@ -1622,7 +1622,7 @@ def rebin_spec(wave, specin, wavnew):
     f = np.ones(len(wave))
     filt = pysynphot.spectrum.ArraySpectralElement(wave, f, waveunits='angstrom')
     obs = pysynphot.observation.Observation(spec, filt, binset=wavnew, force='taper')
- 
+
     return obs.binflux
 
 def organize_BTSettl_2015_atmospheres(path_to_dir):
@@ -1653,7 +1653,7 @@ def organize_BTSettl_2015_atmospheres(path_to_dir):
         spec = hdu[1].data
         header_0 = hdu[0].header
         header_1 = hdu[1].header
-        
+
         wave = spec.field(0)
         flux = spec.field(1)
 
@@ -1674,13 +1674,13 @@ def organize_BTSettl_2015_atmospheres(path_to_dir):
         tbhdu.header['TUNIT1'] = 'ANGSTROM'
         tbhdu.header['TUNIT2'] = 'FLAM'
         hdu_new = fits.HDUList([prihdu, tbhdu])
-        
+
         # Write new fits table in cdbs directory
         hdu_new.writeto(os.environ['PYSYN_CDBS']+'grid/BTSettl_2015/'+i, overwrite=True)
 
         hdu.close()
         hdu_new.close()
-    
+
     # Return to original directory
     os.chdir(start_dir)
     return
@@ -1697,10 +1697,10 @@ def make_BTSettl_2015_catalog(path_to_dir):
     """
     # Record current working directory for later
     start_dir = os.getcwd()
-    
+
     # Enter atmosphere directory
     os.chdir(path_to_dir)
-   
+
     # Extract parameters for each atmosphere from the filename,
     # construct columns for catalog file
     files = glob.glob("*spec.fits")
@@ -1719,10 +1719,10 @@ def make_BTSettl_2015_catalog(path_to_dir):
 
     # Create catalog.fits file in directory with the models
     catalog.write('catalog.fits', format = 'fits', overwrite=True)
-    
+
     # Move back to original directory, create the catalog.fits file
     os.chdir(start_dir)
-    
+
     return
 
 def rebin_BTSettl_2015(cdbs_path=os.environ['PYSYN_CDBS']):
@@ -1765,8 +1765,8 @@ def rebin_BTSettl_2015(cdbs_path=os.environ['PYSYN_CDBS']):
 
         # Make new output
         c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)
-        c1 = fits.Column(name='Flux', format='E', array=flux_rebin) 
-        
+        c1 = fits.Column(name='Flux', format='E', array=flux_rebin)
+
         cols = fits.ColDefs([c0, c1])
         tbhdu = fits.BinTableHDU.from_columns(cols)
         prihdu = fits.PrimaryHDU(header=header0)
@@ -1775,7 +1775,7 @@ def rebin_BTSettl_2015(cdbs_path=os.environ['PYSYN_CDBS']):
 
         outfile = path + files_all[ff].split('[')[0]
         finalhdu = fits.HDUList([prihdu, tbhdu])
-        finalhdu.writeto(outfile, overwrite=True)        
+        finalhdu.writeto(outfile, overwrite=True)
 
     return
 
@@ -1794,7 +1794,7 @@ def make_wavelength_unique(files, dirname):
 
         if len(t) != len(test[0]):
             t = t[test[1]]
-            
+
             c0 = fits.Column(name='Wavelength', format='D', array=t['Wavelength'])
             c1 = fits.Column(name='Flux', format='E', array=t['Flux'])
             cols = fits.ColDefs([c0, c1])
@@ -1832,14 +1832,14 @@ def organize_BTSettl_atmospheres():
     """
     Construct cdbs-ready atmospheres for the BTSettl grid (CIFITS2011).
     The code expects tp be run in cdbs/grid/BTSettl, and expects that the
-    individual model files have been downloaded from online 
+    individual model files have been downloaded from online
     (https://phoenix.ens-lyon.fr/Grids/BT-Settl/CIFIST2011/SPECTRA/)
-    and processed into python-readable ascii files. 
+    and processed into python-readable ascii files.
     """
     orig_dir = os.getcwd()
     dirs = ['btm25', 'btm20', 'btm15', 'btm10', 'btm05', 'btp00', 'btp05']
     #dirs = ['btm10', 'btm05', 'btp00', 'btp05']
-    
+
 
     # Go through each directory, turning each spectrum into a cdbs-ready file.
     # Will convert flux into Ergs/sec/cm**2/A (FLAM) units and save as a fits file,
@@ -1871,13 +1871,13 @@ def organize_BTSettl_atmospheres():
             tbhdu.header['TUNIT1'] = 'ANGSTROM'
             tbhdu.header['TUNIT2'] = 'FLAM'
             hdu_new = fits.HDUList([prihdu, tbhdu])
-        
+
             # Write new fits table in cdbs directory
             hdu_new.writeto('{0}.fits'.format(jj[:-4]), overwrite=True)
             hdu_new.close()
             count += 1
             print('Done {0} of {1}'.format(count, len(files)))
-            
+
         # Now, clean up all the files made when unzipping the spectra
         cmd1 = 'rm *.bz2'
         cmd2 = 'rm *.tmp'
@@ -1888,7 +1888,7 @@ def organize_BTSettl_atmospheres():
         print('==============================')
         print('Done {0}'.format(ii))
         print('==============================')
-        
+
         # Go back to original directory, move to next metallicity directory
         os.chdir(orig_dir)
 
@@ -1924,7 +1924,7 @@ def make_BTSettl_catalog():
             metal_flag = -1 * float(ii[3:])*0.1
         else:
             metal_flag = float(ii[3:])*0.1
-            
+
         # Now collect the info from the files
         for jj in files:
             tmp = jj.split('-')
@@ -1938,7 +1938,7 @@ def make_BTSettl_catalog():
             else:
                 temp = float(tmp[0][3:]) * 100.0 # In kelvin
                 logg = float(tmp[1])
-            
+
             index_str.append('{0},{1},{2:3.2f}'.format(int(temp), metal_flag, logg))
             name_str.append('{0}/{1}[Flux]'.format(ii, jj))
 
@@ -1951,10 +1951,10 @@ def make_BTSettl_catalog():
 
     # Create catalog.fits file in directory with the models
     catalog.write('catalog.fits', format = 'fits', overwrite=True)
-    
+
     # Move back to original directory, create the catalog.fits file
     os.chdir(start_dir)
-    
+
     return
 
 def rebin_BTSettl(make_unique=False):
@@ -1985,7 +1985,7 @@ def rebin_BTSettl(make_unique=False):
     #        tmp.append(ii)
     #files_all = tmp
     #=============================#
-    
+
     print( 'Rebinning BTSettl spectra')
     if make_unique:
         print('Making unique')
@@ -2005,14 +2005,14 @@ def rebin_BTSettl(make_unique=False):
 
             # Make new output
             c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)
-            c1 = fits.Column(name='Flux', format='E', array=flux_rebin) 
-        
+            c1 = fits.Column(name='Flux', format='E', array=flux_rebin)
+
             cols = fits.ColDefs([c0, c1])
             tbhdu = fits.BinTableHDU.from_columns(cols)
             prihdu = fits.PrimaryHDU()
             tbhdu.header['TUNIT1'] = 'ANGSTROM'
             tbhdu.header['TUNIT2'] = 'FLAM'
-            
+
             outfile = path + files_all[ff].split('[')[0]
             finalhdu = fits.HDUList([prihdu, tbhdu])
             finalhdu.writeto(outfile, overwrite=True)
@@ -2022,9 +2022,9 @@ def rebin_BTSettl(make_unique=False):
             outfile = path + files_all[ff].split('[')[0]
             cmd = 'cp {0} {1}'.format(orig_file, outfile)
             os.system(cmd)
-            
+
         print('Done {0} of {1}'.format(ff, len(files_all)))
-        
+
     return
 
 def organize_WDKoester_atmospheres(path_to_dir):
@@ -2048,7 +2048,7 @@ def organize_WDKoester_atmospheres(path_to_dir):
 
     for i in files:
         data = Table.read(i, format='ascii')
-        
+
         wave = data['col1']   # angstrom
         flux = data['col2']   # erg/s/cm^2/A
 
@@ -2064,12 +2064,12 @@ def organize_WDKoester_atmospheres(path_to_dir):
         tbhdu.header['TUNIT1'] = 'ANGSTROM'
         tbhdu.header['TUNIT2'] = 'FLAM'
         hdu_new = fits.HDUList([prihdu, tbhdu])
-        
+
         # Write new fits table in cdbs directory
         hdu_new.writeto(os.environ['PYSYN_CDBS']+'/grid/wdKoester/'+i.replace('.txt', '.fits'), overwrite=True)
 
         hdu_new.close()
-    
+
     # Return to original directory
     os.chdir(start_dir)
     return
@@ -2086,10 +2086,10 @@ def make_WDKoester_catalog(path_to_dir):
     """
     # Record current working directory for later
     start_dir = os.getcwd()
-    
+
     # Enter atmosphere directory
     os.chdir(path_to_dir)
-   
+
     # Extract parameters for each atmosphere from the filename,
     # construct columns for catalog file
     files = glob.glob("*dk.dat.fits")
@@ -2109,10 +2109,10 @@ def make_WDKoester_catalog(path_to_dir):
 
     # Create catalog.fits file in directory with the models
     catalog.write('catalog.fits', format = 'fits', overwrite=True)
-    
+
     # Move back to original directory, create the catalog.fits file
     os.chdir(start_dir)
-    
+
     return
 
 def rebin_WDKoester(cdbs_path=os.environ['PYSYN_CDBS']):
@@ -2155,8 +2155,8 @@ def rebin_WDKoester(cdbs_path=os.environ['PYSYN_CDBS']):
 
         # Make new output
         c0 = fits.Column(name='Wavelength', format='D', array=sp_atlas.wave)
-        c1 = fits.Column(name='Flux', format='E', array=flux_rebin) 
-        
+        c1 = fits.Column(name='Flux', format='E', array=flux_rebin)
+
         cols = fits.ColDefs([c0, c1])
         tbhdu = fits.BinTableHDU.from_columns(cols)
         prihdu = fits.PrimaryHDU(header=header0)
@@ -2165,8 +2165,8 @@ def rebin_WDKoester(cdbs_path=os.environ['PYSYN_CDBS']):
 
         outfile = path + files_all[ff].split('[')[0]
         finalhdu = fits.HDUList([prihdu, tbhdu])
-        finalhdu.writeto(outfile, overwrite=True)        
+        finalhdu.writeto(outfile, overwrite=True)
 
     return
-            
-    
+
+
diff --git a/spisea/conftest.py b/spisea/conftest.py
index 142ae511..fab9a899 100755
--- a/spisea/conftest.py
+++ b/spisea/conftest.py
@@ -18,10 +18,10 @@
         ASTROPY_HEADER = True
     except ImportError:
         ASTROPY_HEADER = False
-        
+
 else:
     # As of Astropy 5.1, the pytest plugins provided by Astropy have been removed
-    # and are instead provided by pytest-astropy-header 
+    # and are instead provided by pytest-astropy-header
     # (https://github.com/astropy/pytest-astropy-header)
     from pytest_astropy_header.display import PYTEST_HEADER_MODULES, TESTED_VERSIONS
     ASTROPY_HEADER = True
diff --git a/spisea/evolution.py b/spisea/evolution.py
index fea75ab3..895b9bb6 100755
--- a/spisea/evolution.py
+++ b/spisea/evolution.py
@@ -30,7 +30,7 @@ def get_installed_grid_num(input_models_dir):
     """
     # Define the installed model grid number
     file_name = input_models_dir + '/grid_version.txt'
-        
+
     # Read in the file. In the case where it doesn't
     # exist, then grid version is assumed to be 1.0
     # (since this didn't always exist)
@@ -51,15 +51,15 @@ def check_evo_grid_number(required_num, input_models_dir):
     grid version number. Installed grid number must
     be greater than or equal to this number
     """
-        
+
     # Get installed gridnumber
     grid_num = get_installed_grid_num(input_models_dir)
-    
+
     # Check: is installed grid number < required_num?
     # If not, raise mismatch error
     if grid_num < required_num:
         raise exceptions.ModelMismatch(required_num, grid_num, 'evolution')
-        
+
     return grid_num
 
 class StellarEvolution(object):
@@ -90,9 +90,9 @@ def __init__(self, model_dir, age_list, mass_list, z_list):
         self.mass_list = mass_list
         self.age_list = age_list
         self.model_version_name = "None"
-      
+
         return
-    
+
 class Geneva(StellarEvolution):
     def __init__(self):
         r"""
@@ -101,17 +101,17 @@ def __init__(self):
         self.model_version_name = "Geneva"
         # populate list of model masses (in solar masses)
         mass_list = [(0.1 + i*0.005) for i in range(181)]
-        
+
         # define metallicity parameters for Geneva models
         z_list = [0.01, 0.02, 0.03]
-        
+
         # populate list of isochrone ages (log scale)
         age_list = [round(5.5 + 0.01*i, 2) for i in range(190)]
         age_list += [round(7.4 + 0.05*i, 2) for i in range(12)]
         age_list += [round(math.log10(1.e8*x), 2) for x in range(1, 10)]
         age_list += [round(math.log10(1.e9*x), 2) for x in range(1, 10)]
         age_list = age_list
-        
+
         # specify location of model files
         model_dir = models_dir + 'geneva/'
 
@@ -122,7 +122,7 @@ def __init__(self):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-            
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Geneva collection.
@@ -131,10 +131,10 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -148,14 +148,14 @@ def isochrone(self, age=1.e8, metallicity=0.0):
 
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_' + str(self.age_list[age_idx]) + '.fits'
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-        
+
         # generate isochrone file string
         full_iso_file = self.model_dir + 'iso/' + z_dir + iso_file
-        
+
         # return isochrone data
         return genfromtxt(full_iso_file, comments='#')
 
@@ -166,7 +166,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
 
 class Ekstrom12(StellarEvolution):
     """
-    Evolution models from 
+    Evolution models from
     `Ekstrom et al. 2012 <https://ui.adsabs.harvard.edu/abs/2012A%26A...537A.146E/abstract>`_.
 
     Downloaded from `website <http://obswww.unige.ch/Recherche/evoldb/index/Isochrone/>`_.
@@ -183,10 +183,10 @@ def __init__(self, rot=True):
             self.model_version_name = "Ekstrom12-norot"
         # define metallicity parameters for Ekstrom+12 models
         self.z_list = [0.014]
-        
+
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.0+0.005, 0.01)
-        
+
         # Specify location of model files
         self.model_dir = models_dir+'Ekstrom2012/'
 
@@ -199,7 +199,7 @@ def __init__(self, rot=True):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-    
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Ekstrom+12 Geneva collection.
@@ -208,34 +208,34 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
 
         if ((z_defined < np.min(self.z_list)) or
                 (z_defined > np.max(self.z_list))):
-            raise ValueError(f'Requested metallicity {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
+            raise ValueError(f'Requested metallicity z_solar * 10^{metallicity} = {z_defined} is out of bounds between {np.min(self.z_list)} and {np.max(self.z_list)}.')
 
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-        
+
         # generate isochrone file string
-        if self.rot:  
+        if self.rot:
             full_iso_file = self.model_dir + 'iso/' + z_dir + 'rot/' + iso_file
         else:
             full_iso_file = self.model_dir + 'iso/' + z_dir + 'norot/' + iso_file
-        
+
         # Return isochrone data
         iso = Table.read(full_iso_file, format='fits')
         iso.rename_column('col4', 'Z')
@@ -267,11 +267,11 @@ def format_isochrones(input_iso_dir):
         Parse iso.fits (filename hardcoded) file downloaded from Ekstrom+12
         models, create individual isochrone files for the different ages.
 
-        input_iso_directory should lead to 
-            Ekstrom2012/iso/<metallicity> 
+        input_iso_directory should lead to
+            Ekstrom2012/iso/<metallicity>
         directory, where iso.fits file should be located.
 
-        Creates two new directories, rot and norot, which contain their 
+        Creates two new directories, rot and norot, which contain their
         respective isochrones.
         """
         # Store current directory for later
@@ -279,13 +279,13 @@ def format_isochrones(input_iso_dir):
 
         # Move into metallicity direcotry, read iso.fits file
         os.chdir(input_iso_dir)
-    
+
         print( 'Read Input: this is slow')
         iso = Table.read('iso.fits')
         print( 'Done'    )
-    
+
         ages_all = iso['col1']
-    
+
         # Extract the unique ages
         age_arr = np.unique(ages_all)
 
@@ -299,7 +299,7 @@ def format_isochrones(input_iso_dir):
         else:
             os.mkdir('rot')
             os.mkdir('norot')
-    
+
         print( 'Making individual isochrone files')
         for age in age_arr:
             good = np.where(ages_all == age)
@@ -310,7 +310,7 @@ def format_isochrones(input_iso_dir):
 
             tmp_r = iso[good][idx_r]
             tmp_n = iso[good][idx_n]
-        
+
             # Write tables
             tmp_r.write('rot/iso_{0:4.2f}.fits'.format(age))
             tmp_n.write('norot/iso_{0:4.2f}.fits'.format(age))
@@ -327,14 +327,14 @@ def create_iso(fileList, ageList, rot=True):
         iso.fits format for parse_iso code.
 
         fileList: list of downloaded isochrone files (could be one)
-    
+
         ageList: list of lists of ages associated with each file in filelist.
         MUST BE IN SAME ORDER AS ISOCHRONES IN FILE! Also needs to be in logAge
-    
+
         rot = TRUE: assumes that models are rotating, will add appropriate column
-    
+
         This code writes the individual files, which is then easiest to combine by hand
-        in aquamacs 
+        in aquamacs
         """
         # Read each file in fileList individually, add necessary columns
         for i in range(len(fileList)):
@@ -345,14 +345,14 @@ def create_iso(fileList, ageList, rot=True):
             start = np.where(t['M_ini'] == 0.8)
 
             # Now, each identified start is assumed to be associated with the
-            # corresponding age in ages        
+            # corresponding age in ages
             if len(start[0]) != len(ages):
                 print( 'Ages mismatched in file! Quitting...')
                 return
 
             age_arr = np.zeros(len(t))
 
-        
+
             for j in range(len(start[0])):
                 low_ind = start[0][j]
                 # Deal with case at end of file
@@ -371,9 +371,9 @@ def create_iso(fileList, ageList, rot=True):
             rot_val[:] = 'r'
             if not rot:
                 rot_val[:] = 'n'
-            
+
             col_rot = Column(rot_val, name='Rot')
-        
+
             t.add_column(col_rot, index=0)
             t.add_column(col_age, index=0)
 
@@ -387,7 +387,7 @@ def create_iso(fileList, ageList, rot=True):
 
 class Parsec(StellarEvolution):
     """
-    Evolution models from 
+    Evolution models from
     `Bressan et al. 2012 <https://ui.adsabs.harvard.edu/abs/2012MNRAS.427..127B/abstract>`_,
     version 1.2s.
 
@@ -413,14 +413,14 @@ def __init__(self):
         # populate list of model masses (in solar masses)
         self.model_version_name = "Parsec1.2s"
         #mass_list = [(0.1 + i*0.005) for i in range(181)]
-        
+
         # define metallicity parameters for Parsec models
         self.z_list = [0.005, 0.015, 0.04]
-        
+
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.6, 10.12+0.005, 0.01)
         self.age_list = np.append(6.40, self.age_list)
-        
+
         # Specify location of model files
         self.model_dir = models_dir+'ParsecV1.2s/'
 
@@ -429,8 +429,8 @@ def __init__(self):
         self.z_file_map = {0.005: 'z005/', 0.015: 'z015/', 0.04: 'z04/'}
 
         # Define required evo_grid number
-        self.evo_grid_min = 1.0        
-        
+        self.evo_grid_min = 1.0
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Parsec version 1.2s
@@ -440,12 +440,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -457,14 +457,14 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-        
+
         # generate isochrone file string
         full_iso_file = self.model_dir + 'iso/' + z_dir + iso_file
-        
+
         # return isochrone data
         iso = Table.read(full_iso_file, format='fits')
         iso.rename_column('col1', 'Z')
@@ -480,19 +480,19 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Parsec doesn't identify WR stars, so identify all as "False"
         isWR = Column([False] * len(iso), name='isWR')
         iso.add_column(isWR)
-        
+
         iso.meta['log_age'] = log_age
         iso.meta['metallicity_in'] = metallicity
         iso.meta['metallicity_act'] = np.log10(self.z_list[z_idx] / self.z_solar)
 
         return iso
-        
+
 
     def format_isochrones(input_iso_dir, metallicity_list):
         r"""
         Parse isochrone file downloaded from Parsec version 1.2 for different
         metallicities, create individual isochrone files for the different ages.
-    
+
         input_iso_dir: points to ParsecV1.2s/iso directory. Assumes metallicity
         subdirectories already exist with isochrone files downloaded in them
         (isochrones files expected to start with "output*")
@@ -505,7 +505,7 @@ def format_isochrones(input_iso_dir, metallicity_list):
 
         # Move into isochrone directory
         os.chdir(input_iso_dir)
-        
+
         # Work on each metallicity isochrones individually
         for metal in metallicity_list:
             # More into metallicity directory, read isochrone file
@@ -515,7 +515,7 @@ def format_isochrones(input_iso_dir, metallicity_list):
             print( 'Read Input: this is slow')
             iso = Table.read(isoFile[0], format='fits')
             print( 'Done')
-    
+
             ages_all = iso['col2']
 
             # Extract the unique ages
@@ -544,9 +544,9 @@ def format_isochrones(input_iso_dir, metallicity_list):
 
 class Pisa(StellarEvolution):
     """
-    Evolution models from 
+    Evolution models from
     `Tognelli et al. 2011 <https://ui.adsabs.harvard.edu/abs/2011A%26A...533A.109T/abstract>`_.
-    
+
     Downloaded `online <http://astro.df.unipi.it/stellar-models/index.php?m=1>`_
 
     Notes
@@ -565,10 +565,10 @@ def __init__(self):
         self.model_version_name = "Pisa"
         # define metallicity parameters for Pisa models
         self.z_list = [0.015]
-        
+
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.01+0.005, 0.01)
-        
+
         # Specify location of model files
         self.model_dir = models_dir+'Pisa2011/'
 
@@ -578,7 +578,7 @@ def __init__(self):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-    
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Pisa (Tognelli+11)
@@ -588,12 +588,12 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -605,14 +605,14 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-        
+
         # generate isochrone file string
         full_iso_file = self.model_dir + 'iso/' + z_dir + iso_file
-        
+
         # return isochrone data
         iso = Table.read(full_iso_file, format='fits')
         iso.rename_column('col1', 'logL')
@@ -625,7 +625,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         isWR = Column([False] * len(iso), name='isWR')
         iso.add_column(isWR)
 
-        # Add columns for current mass and phase. 
+        # Add columns for current mass and phase.
         iso.add_column( Column(np.zeros(len(iso)), name = 'phase'))
         iso.add_column( Column(iso['mass'], name = 'mass_current'))
 
@@ -643,7 +643,7 @@ def format_isochrones(input_iso_dir, metallicity_list):
         input_iso_dir: points to Pisa2011/iso directory. Individual
         metallicity directories with the downloaded isochrones are
         expected to already exist there
-        
+
         metallicity_list is the list of metallicities on which function
         is to be run.
 
@@ -665,7 +665,7 @@ def format_isochrones(input_iso_dir, metallicity_list):
             else:
                 # Create a ReadMe with the original file names to preserve the
                 # model details
-        
+
                 cmd = "ls *.FITS > ReadMe"
                 os.system(cmd)
 
@@ -699,14 +699,14 @@ def make_isochrone_grid(metallicity=0.015):
         while 0.0150 would not)
         """
         logAge_arr = np.arange(6.0, 8.0+0.005, 0.01)
-    
+
         count = 0
         for logAge in logAge_arr:
             # Could interpolate using evolutionary tracks, but less accurate.
             make_isochrone_pisa_interp(logAge, metallicity=metallicity)
 
             count += 1
-        
+
             print( 'Done {0} of {1} models'.format(count, (len(logAge_arr))))
 
         return
@@ -716,7 +716,7 @@ def make_isochrone_grid(metallicity=0.015):
 #==============================#
 class Baraffe15(StellarEvolution):
     """
-    Evolution models published in 
+    Evolution models published in
     `Baraffe et al. 2015 <https://ui.adsabs.harvard.edu/abs/2015A%26A...577A..42B/abstract>`_.
 
     Downloaded from `BHAC15 site <http://perso.ens-lyon.fr/isabelle.baraffe/BHAC15dir/BHAC15_tracks>`_.
@@ -725,10 +725,10 @@ def __init__(self):
         self.model_version_name = "Baraffe15"
         # define metallicity parameters for Baraffe models
         self.z_list = [0.015]
-        
+
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.0+0.005, 0.01)
-        
+
         # Specify location of model files
         self.model_dir = models_dir+'Baraffe15/'
 
@@ -738,7 +738,7 @@ def __init__(self):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-    
+
     def isochrone(self, age=5.e7, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Baraffe+15
@@ -748,12 +748,12 @@ def isochrone(self, age=5.e7, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -765,26 +765,26 @@ def isochrone(self, age=5.e7, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-        
+
         # generate isochrone file string
         full_iso_file = self.model_dir + 'iso/' + z_dir + iso_file
-        
+
         # Read isochrone, get in proper format
         iso = Table.read(full_iso_file, format='fits')
         iso.rename_column('Mass', 'mass')
         iso.rename_column('logG', 'logg')
         iso['logT'] = np.log10(iso['Teff'])
-        
+
         # Pisa models are too low for WR phase, add WR column with all False
         iso['logT_WR'] = iso['logT']
         isWR = Column([False] * len(iso), name='isWR')
         iso.add_column(isWR)
 
-        # Add columns for current mass and phase. 
+        # Add columns for current mass and phase.
         iso.add_column( Column(np.zeros(len(iso)), name = 'phase'))
         iso.add_column( Column(iso['mass'], name = 'mass_current'))
 
@@ -798,11 +798,11 @@ def tracks_to_isochrones(self, tracksFile):
         r"""
         Create isochrones at desired age sampling (6.0 < logAge < 8.0,
         steps of 0.01; hardcoded) from the Baraffe+15 tracks downloaded
-        online. 
+        online.
 
         tracksFile: tracks.dat file downloaded from Baraffe+15, with format
         modified to be read in python
-        
+
         Writes isochrones in iso/ subdirectory off of work directory. Will
         create this subdirectory if it doesn't already exist
         """
@@ -810,7 +810,7 @@ def tracks_to_isochrones(self, tracksFile):
 
         age_arr = np.arange(6.0, 8.0+0.005, 0.01)
         #age_arr = [6.28]
-        
+
         # Loop through the masses, interpolating track over time at each.
         # Resample track properties at hardcoded ages
         masses = np.unique(tracks['col1'])
@@ -835,13 +835,13 @@ def tracks_to_isochrones(self, tracksFile):
             # Interpolate Teff, logL, and logG using linear interpolator
             tck_Teff = interpolate.interp1d(tmp['col2'], tmp['col3'])
             tck_logL = interpolate.interp1d(tmp['col2'], tmp['col4'])
-            tck_logG = interpolate.interp1d(tmp['col2'], tmp['col5'])            
+            tck_logG = interpolate.interp1d(tmp['col2'], tmp['col5'])
 
 
             Teff = tck_Teff(age_arr)
             logL = tck_logL(age_arr)
             logG = tck_logG(age_arr)
-            
+
             # Test interpolation if desired
             test=False
             if test:
@@ -868,9 +868,9 @@ def tracks_to_isochrones(self, tracksFile):
                 py.xlabel('logAge')
                 py.ylabel('logG')
                 py.savefig('test_logG.png')
-                
+
                 pdb.set_trace()
-           
+
             # Build upon arrays of interpolated values
             mass_interp = np.concatenate((mass_interp, np.ones(len(Teff)) * mass))
             age_interp = np.concatenate((age_interp, age_arr))
@@ -905,11 +905,11 @@ def tracks_to_isochrones(self, tracksFile):
     def test_age_interp(self, onlineIso, interpIso):
         r"""
         Compare one of our interpolated ischrones with one
-        of the isochrones provided online by Baraffe+15. 
+        of the isochrones provided online by Baraffe+15.
         """
         true_iso = Table.read(onlineIso, format='ascii')
         our_iso = Table.read(interpIso, format='fits')
-        
+
         # Compare the two isochrones using plots. Look at mass vs. Teff,
         # mass vs. logG, mass vs. logL. Ideally these isochrones should
         # be identical
@@ -941,7 +941,7 @@ def test_age_interp(self, onlineIso, interpIso):
         Teff_diff = np.mean(abs(true_iso['col2'][7:] - our_iso['Teff']))
         logL_diff = np.mean(abs(true_iso['col3'][7:] - our_iso['logL']))
         logG_diff = np.mean(abs(true_iso['col4'][7:] - our_iso['logG']))
-    
+
         print( 'Average abs difference in Teff: {0}'.format(Teff_diff))
         print( 'Average abs difference in logL: {0}'.format(logL_diff))
         print( 'Average abs difference in logg: {0}'.format(logG_diff))
@@ -958,7 +958,7 @@ def compare_Baraffe_Pisa(BaraffeIso, PisaIso):
 
     name = BaraffeIso.split('_')
     age = name[1][:4]
-    
+
     # Extract paramters we need
     b_mass = b['Mass']
     b_logT = np.log10(b['Teff'])
@@ -972,7 +972,7 @@ def compare_Baraffe_Pisa(BaraffeIso, PisaIso):
 
     m05_b = np.where( abs(b_mass - 0.5) == min(abs(b_mass - 0.5)) )
     m05_p = np.where( abs(p_mass - 0.5) == min(abs(p_mass - 0.5)) )
-    
+
     # Comparison plots
     py.figure(1, figsize=(10,10))
     py.clf()
@@ -1000,7 +1000,7 @@ def compare_Baraffe_Pisa(BaraffeIso, PisaIso):
     #py.axis([4.4, 3.4, -3, 4])
     #py.gca().invert_xaxis()
     py.legend()
-    py.savefig('BaraffePisa_comp_mass_{0}.png'.format(age))    
+    py.savefig('BaraffePisa_comp_mass_{0}.png'.format(age))
 
     return
 
@@ -1010,7 +1010,7 @@ def compare_Baraffe_Pisa(BaraffeIso, PisaIso):
 class MISTv1(StellarEvolution):
     """
     Define intrinsic properties for the MIST v1 stellar
-    models. 
+    models.
 
     Models originally downloaded from `online server <http://waps.cfa.harvard.edu/MIST/interp_isos.html>`_.
 
@@ -1021,11 +1021,11 @@ class MISTv1(StellarEvolution):
         was downloaded from MIST website on 2/2017, while Version 1.2
         was downloaded on 8/2018 (solar metallicity)
         and 4/2019 (other metallicities). Default is 1.2.
-        
+
     synthpop_extension: boolean (default False)
         If True, the isochrones are extended down to a minimum initial
         mass of 0.1Msun using grids interpolated via SynthPop. If False,
-        the web-downloaded MIST isochrones are used with their varying  
+        the web-downloaded MIST isochrones are used with their varying
         lower mass limits. True option is only valid for version=1.2.
     """
     def __init__(self, version=1.2, synthpop_extension=False):
@@ -1045,7 +1045,7 @@ def __init__(self, version=1.2, synthpop_extension=False):
                        0.014,   # [Fe/H] = 0.00
                        0.025,   # [Fe/H] = 0.25
                        0.045]   # [Fe/H] = 0.50
-        
+
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(5.01, 10.30+0.005, 0.01)
 
@@ -1062,7 +1062,7 @@ def __init__(self, version=1.2, synthpop_extension=False):
             version_dir = 'v1.2/'
         else:
             raise ValueError('Version {0} not supported for MIST isochrones'.format(version))
-        
+
         # Specify location of model files
         self.model_dir = models_dir+'MISTv1/' + version_dir
         if self.synthpop_extension:
@@ -1094,7 +1094,7 @@ def __init__(self, version=1.2, synthpop_extension=False):
 
         # Define required evo_grid number (now 1.2 for synthpop extension)
         self.evo_grid_min = 1.2
-                
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the MISTv1
@@ -1104,7 +1104,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar * (10.**metallicity)
 
@@ -1121,16 +1121,16 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
-            
+
         # generate isochrone file string
         full_iso_file = self.model_dir + 'iso/' + z_dir + iso_file
         if self.synthpop_extension:
             addl_iso_file = self.model_extension_dir + 'iso/' + z_dir + iso_file
-        
+
         # return isochrone data. Column locations depend on
         # version
         iso = Table.read(full_iso_file, format='fits')
@@ -1174,7 +1174,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         iso.meta['metallicity_act'] = np.log10(self.z_list[z_idx] / self.z_solar)
 
         return iso
-        
+
     def format_isochrones(self):
         r"""
         Parse isochrone file downloaded from MIST web server,
@@ -1199,7 +1199,7 @@ def format_isochrones(self):
 
         # Move into isochrone directory
         os.chdir(input_iso_dir)
-        
+
         # Work on each metallicity isochrones individually
         for metal in metallicity_list:
             # More into metallicity directory, read isochrone file
@@ -1253,19 +1253,19 @@ class MergedBaraffePisaEkstromParsec(StellarEvolution):
 
     The model used depends on the age of the population and what stellar masses
     are being modeled:
-    
+
 
     For logAge < 7.4:
 
     * Baraffe: 0.08 - 0.4 M_sun
-    * Baraffe/Pisa transition: 0.4 - 0.5 M_sun 
+    * Baraffe/Pisa transition: 0.4 - 0.5 M_sun
     * Pisa: 0.5 M_sun to the highest mass in Pisa isochrone (typically 5 - 7 Msun)
     * Geneva: Highest mass of Pisa models to 120 M_sun
 
     For logAge > 7.4:
 
     * Parsec v1.2s: full mass range
-    
+
     Parameters
     ----------
     rot: boolean, optional
@@ -1278,18 +1278,18 @@ def __init__(self, rot=True):
             self.model_version_name = "MergedBaraffePisaEkstromParsec-norot"
         # populate list of model masses (in solar masses)
         mass_list = [(0.1 + i*0.005) for i in range(181)]
-        
+
         # define metallicity parameters for Geneva models
         z_list = [0.015]
-        
+
         # populate list of isochrone ages (log scale)
         age_list = np.arange(6.0, 10.091, 0.01).tolist()
-        
+
         # specify location of model files
         model_dir = models_dir + 'merged/baraffe_pisa_ekstrom_parsec/'
         StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
         self.z_solar = 0.015
-        
+
         # Switch to specify rotating/non-rotating models
         if rot:
             self.z_file_map = {0.015: 'z015_rot/'}
@@ -1298,23 +1298,23 @@ def __init__(self, rot=True):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-        
-    
+
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
-        Extract an individual isochrone from the Baraffe-Pisa-Ekstrom-Parsec 
+        Extract an individual isochrone from the Baraffe-Pisa-Ekstrom-Parsec
         collection
         """
         # Error check to see if installed evolution model
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
+
         # convert metallicity to mass fraction
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if ((log_age < np.min(self.age_list)) or (log_age > np.max(self.age_list))):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -1326,8 +1326,8 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
-        
+
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
@@ -1343,9 +1343,9 @@ def isochrone(self, age=1.e8, metallicity=0.0):
             # ASCII version of files (newer model evo grids
             iso_file = 'iso_{0:.2f}.dat'.format(self.age_list[age_idx])
             full_iso_file = self.model_dir + z_dir + iso_file
-            
+
             iso = Table.read(full_iso_file, format='ascii')
-            
+
         iso.rename_column('col1', 'mass')
         iso.rename_column('col2', 'logT')
         iso.rename_column('col3', 'logL')
@@ -1360,18 +1360,18 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         idx_WR = np.where(iso['logT'] != iso['logT_WR'])
         isWR[idx_WR] = True
         iso.add_column(isWR)
-        
+
         iso.meta['log_age'] = log_age
         iso.meta['metallicity_in'] = metallicity
         iso.meta['metallicity_act'] = np.log10(self.z_list[z_idx] / self.z_solar)
-        
+
         return iso
 
 
 class MergedPisaEkstromParsec(StellarEvolution):
     """
     Same as MergedBaraffePisaEkstromParsec, but without
-    the Baraffe models. 
+    the Baraffe models.
 
     Parameters
     ----------
@@ -1385,13 +1385,13 @@ def __init__(self, rot=True):
             self.model_version_name = "MergedPisaEkstromParsec-norot"
         # populate list of model masses (in solar masses)
         mass_list = [(0.1 + i*0.005) for i in range(181)]
-        
+
         # define metallicity parameters for Geneva models
         z_list = [0.015]
-        
+
         # populate list of isochrone ages (log scale)
         age_list = np.arange(6.0, 8.001, 0.01).tolist()
-        
+
         # specify location of model files
         model_dir = models_dir + 'merged/pisa_ekstrom_parsec/'
         StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
@@ -1405,13 +1405,13 @@ def __init__(self, rot=True):
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-        
+
         # Error check to see if installed evolution model
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
-    
+
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Pisa-Ekstrom-Parsec collection.
@@ -1420,7 +1420,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if (log_age < self.age_list[0]) or (log_age > self.age_list[-1]):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -1431,7 +1431,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
@@ -1451,7 +1451,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         iso.meta['log_age'] = log_age
         iso.meta['metallicity_in'] = metallicity
         iso.meta['metallicity_act'] = np.log10(self.z_list[z_idx] / self.z_solar)
-        
+
         return iso
 
 class MergedSiessGenevaPadova(StellarEvolution):
@@ -1466,27 +1466,27 @@ class MergedSiessGenevaPadova(StellarEvolution):
     * Padova (`Marigo et al. 2008 <https://ui.adsabs.harvard.edu/abs/2008A%26A...482..883M/abstract>`_)
 
     For logAge < 7.4:
-    
+
     * Siess: 0.1 - 7 M_sun
     * Siess/Geneva transition: 7 - 9 M_sun
     * Geneva: > 9 M_sun
 
     For logAge > 7.4:
-    
+
     * Padova: full mass range
     """
     def __init__(self):
         """
-        Define intrinsic properties for merged Siess-meynetMaeder-Padova 
+        Define intrinsic properties for merged Siess-meynetMaeder-Padova
         stellar models.
         """
         self.model_version_name = "MergedSiessGenevaPadova"
         # populate list of model masses (in solar masses)
         mass_list = [(0.1 + i*0.005) for i in range(181)]
-        
+
         # define metallicity parameters for Geneva models
         z_list = [0.02]
-        
+
         # populate list of isochrone ages (log scale)
         age_list = np.arange(5.5, 7.41, 0.01).tolist()
         age_list.append(7.48)
@@ -1506,24 +1506,24 @@ def __init__(self):
         age_list.append(9.60)
         age_list.append(9.70)
         age_list.append(9.78)
-        
+
         # specify location of model files
         model_dir = models_dir + 'merged/siess_meynetMaeder_padova/'
         StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
         self.z_solar = 0.02
-        
+
         # Metallicity map
         self.z_file_map = {0.02: 'z02/'}
 
         # Define required evo_grid number
         self.evo_grid_min = 1.0
-        
+
         # Error check to see if installed evolution model
         # grid is compatible with code version. Also return
         # current grid num
         self.evo_grid_num = check_evo_grid_number(self.evo_grid_min, models_dir)
-        
-    
+
+
     def isochrone(self, age=1.e8, metallicity=0.0):
         r"""
         Extract an individual isochrone from the Siess-Geneva-Padova collection.
@@ -1532,7 +1532,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         z_defined = self.z_solar*10.**metallicity
 
         log_age = math.log10(age)
-        
+
         # check age and metallicity are within bounds
         if (log_age < self.age_list[0]) or (log_age > self.age_list[-1]):
             raise ValueError(f'Requested age {log_age} is out of bounds between {np.min(self.age_list)} and {np.max(self.age_list)}.')
@@ -1543,7 +1543,7 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         # Find nearest age in grid to input grid
         age_idx = np.where(abs(np.array(self.age_list) - log_age) == min(abs(np.array(self.age_list) - log_age)) )[0][0]
         iso_file = 'iso_{0:.2f}.fits'.format(self.age_list[age_idx])
-        
+
         # find closest metallicity value
         z_idx = np.where(abs(np.array(self.z_list) - z_defined) == min(abs(np.array(self.z_list) - z_defined)) )[0][0]
         z_dir = self.z_file_map[self.z_list[z_idx]]
@@ -1559,16 +1559,16 @@ def isochrone(self, age=1.e8, metallicity=0.0):
         iso.rename_column('col4', 'logg')
         iso.rename_column('col5', 'logT_WR')
         iso.rename_column('col6', 'model_ref')
-        
+
         iso.meta['log_age'] = log_age
         iso.meta['metallicity_in'] = metallicity
         iso.meta['metallicity_act'] = np.log10(self.z_list[z_idx] / self.z_solar)
-        
+
         return iso
 
 #================================================#
-    
-def make_isochrone_pisa_interp(log_age, metallicity=0.015, 
+
+def make_isochrone_pisa_interp(log_age, metallicity=0.015,
                          tracks=None, test=False):
     """
     Read in a set of isochrones and generate an isochrone at log_age
@@ -1595,7 +1595,7 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
     if os.path.exists(rootDir+'iso_{0:3.2f}.fits'.format(log_age)):
         print( 'Isochrone at logAge = {0:3.2f} already exists'.format(log_age))
         return
-    
+
     # Name/directory for interpolated isochrone
     isoFile = rootDir+'iso_%3.2f.fits' % log_age
     outSuffix = '_%.2f' % (log_age)
@@ -1616,7 +1616,7 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
     good = np.where(tmp == log_age)
     young_model_logage = tmp[good[0]-1]
     old_model_logage = tmp[good[0]+1]
-    
+
     # Isolate younger/older isochrones
     young_ind = np.where(iso.log_ages == young_model_logage)
     old_ind = np.where(iso.log_ages == old_model_logage)
@@ -1629,7 +1629,7 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
     if abs(young_model_logage - log_age) <= abs(old_model_logage - log_age):
         # Use young model mass grid
         young_iso, old_iso = interpolate_iso_tempgrid(young_iso, old_iso)
-        
+
     else:
         # Use old model mass grid
         old_iso, young_iso = interpolate_iso_tempgrid(old_iso, young_iso)
@@ -1637,25 +1637,25 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
     # Now, can interpolate in time over the two models. Do this star by star.
     # Work in linear time here!!
     numStars = len(young_iso.M)
-    
+
     interp_iso = Isochrone(log_age)
     interp_iso.log_Teff = np.zeros(numStars, dtype=float)
     interp_iso.log_L = np.zeros(numStars, dtype=float)
     interp_iso.log_g = np.zeros(numStars, dtype=float)
     interp_iso.M = young_iso.M # Since mass grids should already be matched
-    
+
     for i in range(numStars):
         # Do interpolations in linear space
         model_ages = [10**young_model_logage[0], 10**old_model_logage[0]]
         target_age = 10**log_age
         #model_ages = [young_model_logage[0], old_model_logage[0]]
         #target_age = log_age
-        
+
         # Build interpolation functions
         Teff_arr = [10**young_iso.log_Teff[i], 10**old_iso.log_Teff[i]]
         logL_arr = [10**young_iso.log_L[i], 10**old_iso.log_L[i]]
         logg_arr = [10**young_iso.log_g[i], 10**old_iso.log_g[i]]
-        
+
         f_log_Teff = interpolate.interp1d(model_ages, Teff_arr, kind='linear')
         f_log_L = interpolate.interp1d(model_ages, logL_arr, kind='linear')
         f_log_g = interpolate.interp1d(model_ages, logg_arr, kind='linear')
@@ -1681,15 +1681,15 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
         py.legend()
         py.title('Pisa 2011 Isochrone at log t = %.2f' % log_age)
         py.savefig(rootDir + 'plots/interp_isochrone_at' + outSuffix + '.png')
-    
+
     print( time.asctime(), 'Finished.')
 
     # Write output to file, MUST BE IN SAME ORDER AS ORIG FILES
     _out = open(isoFile, 'w')
-    
-    _out.write('%10s  %10s  %10s  %10s\n' % 
+
+    _out.write('%10s  %10s  %10s  %10s\n' %
                ('# log L', 'log Teff', 'Mass', 'log g'))
-    _out.write('%10s  %10s  %10s  %10s\n' % 
+    _out.write('%10s  %10s  %10s  %10s\n' %
                ('# (Lsun)', '(Kelvin)', '(Msun)', '(cgs)'))
 
     for ii in range(len(interp_iso.M)):
@@ -1713,7 +1713,7 @@ def get_orig_pisa_isochrones(metallicity=0.015):
     if not os.path.exists(pms_dir):
         print( 'Failed to find Siess PMS isochrones for metallicity = ' + metSuffix)
         return
-    
+
     # Collect the isochrones
     files = glob.glob(pms_dir + '*.dat')
     count = len(files)
@@ -1722,7 +1722,7 @@ def get_orig_pisa_isochrones(metallicity=0.015):
 
     data.isochrones = []
     data.log_ages = []
-    
+
     # Extract useful params from isochrones
     for ff in range(len(files)):
         d = Table.read(files[ff], format='ascii')
@@ -1730,7 +1730,7 @@ def get_orig_pisa_isochrones(metallicity=0.015):
         # Extract logAge from filename
         log_age = float(files[ff].split('_')[2][:-4])
 
-        # Create an isochrone object   
+        # Create an isochrone object
         iso = Isochrone(log_age)
         iso.M = d['col3']
         iso.log_Teff = d['col2']
@@ -1739,13 +1739,13 @@ def get_orig_pisa_isochrones(metallicity=0.015):
         # If a log g column exist, extract it. Otherwise, calculate
         # log g from T and L and add column at end
         if len(d.keys()) == 3:
-            
+
             # Calculate log g from T and L
             L_sun = 3.8 * 10**33 #cgs
             SB_sig = 5.67 * 10**-5 #cgs
             M_sun = 2. * 10**33 #cgs
             G_const = 6.67 * 10**-8 #cgs
-        
+
             radius = np.sqrt( (10**d['col1'] * L_sun) /
                           (4 * np.pi * SB_sig *  (10**d['col2'])**4) )
             g = (G_const * d['col3'] * M_sun) / radius**2
@@ -1754,7 +1754,7 @@ def get_orig_pisa_isochrones(metallicity=0.015):
             iso.log_g = np.log10(g.astype(np.float))
         else:
             iso.log_g = d['col4']
-        
+
         data.isochrones.append(iso)
         data.log_ages.append(log_age)
 
diff --git a/spisea/exceptions.py b/spisea/exceptions.py
index 5b45baa1..e0587d90 100644
--- a/spisea/exceptions.py
+++ b/spisea/exceptions.py
@@ -8,12 +8,12 @@ class ModelMismatch(Exception):
     """
     def __init__(self, required_num, grid_num, model_type):
         assert (model_type == 'evolution') | (model_type == 'atmosphere')
-        
+
         if model_type == 'evolution':
             model_file = 'spisea_models.tar.gz'
         elif model_type == 'atmosphere':
             model_file = 'spisea_cdbs.tar.gz'
-        
+
         # Compose error message
         str1 = 'WARNING: Desired {0} model requires model grid version >= {1},'.format(model_type, required_num)
         str2 = 'but model grid version {0} is installed.'.format(grid_num)
diff --git a/spisea/filters.py b/spisea/filters.py
index 23c029b3..d7d0b5e1 100755
--- a/spisea/filters.py
+++ b/spisea/filters.py
@@ -29,7 +29,7 @@ def get_nirc2_filt(name):
 
     while len(idx) != 0:
         wavelength[idx+1] += 1.0e-8
-        
+
         diff = np.diff(wavelength)
         idx = np.where(diff <= 0)[0]
         #print( 'Duplicate entry loop' )
@@ -68,7 +68,7 @@ def get_2mass_filt(name):
                                            name='2MASS_{0}'.format(name))
 
     return spectrum
-    
+
 
 def get_vista_filt(name):
     """
@@ -79,21 +79,21 @@ def get_vista_filt(name):
         t = Table.read('{0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name),
                            format='ascii')
     except:
-        raise ValueError('Could not find VISTA filter file {0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name))    
+        raise ValueError('Could not find VISTA filter file {0}/vista/VISTA_Filters_at80K_forETC_{1}.dat'.format(filters_dir, name))
 
    # Wavelength must be in angstroms, transmission in fraction
     wave = t['col1'] * 10
     trans = t['col2'] * 0.01
-    
+
     # Change any negative numbers to 0, as well as anything shortward
     # of 0.4 microns or longward of 2.9 microns
     # (no VISTA filter transmissions beyond these boundaries)
     bad = np.where( (trans < 0) | (wave < 4000) | (wave > 29000) )
     trans[bad] = 0
-    
+
     # Now we can define the VISTA filter bandpass objects
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='VISTA_{0}'.format(name))
-    
+
     return spectrum
 
 def get_decam_filt(name):
@@ -104,18 +104,18 @@ def get_decam_filt(name):
     try:
         t = Table.read('{0}/decam/DECam_filters.txt'.format(filters_dir), format='ascii')
         t.rename_column('Y', 'y')
-        
+
         cols = np.array(t.keys())
         idx = np.where(cols == name)[0][0]
 
         trans = t[cols[idx]]
     except:
-        raise ValueError('Could not find DECAM filter {0} in {1}/decam/DECam_filters.txt'.format(name, filters_dir))         
+        raise ValueError('Could not find DECAM filter {0} in {1}/decam/DECam_filters.txt'.format(name, filters_dir))
 
     # Limit to unmasked regions only
     mask = np.ma.getmask(trans)
     good = np.where(mask == False)
-    
+
     # Convert wavelengths from nm to angstroms, while eliminating masked regions
     wave = t['wavelength'][good] * 10.
     trans = trans[good]
@@ -126,7 +126,7 @@ def get_decam_filt(name):
 
     return spectrum
 
-def get_PS1_filt(name):  
+def get_PS1_filt(name):
     """
     Define PS1 filter as pysynphot object
     """
@@ -145,11 +145,11 @@ def get_PS1_filt(name):
 
         trans = t[cols[idx]]
     except:
-        raise ValueError('Could not find PS1 filter {0} in {1}/ps1'.format(name, filters_dir))         
+        raise ValueError('Could not find PS1 filter {0} in {1}/ps1'.format(name, filters_dir))
 
     # Convert wavelengths from nm to angstroms
     wave = t['wave'] * 10.
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='ps1_{0}'.format(name))
 
     return spectrum
@@ -161,7 +161,7 @@ def get_jwst_filt(name):
     try:
         t = Table.read('{0}/jwst/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find JWST filter {0} in {1}/jwst'.format(name, filters_dir))         
+        raise ValueError('Could not find JWST filter {0} in {1}/jwst'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['microns'] * 10**4.
@@ -170,10 +170,10 @@ def get_jwst_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='jwst_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_Johnson_Glass_filt(name):
     """
@@ -182,7 +182,7 @@ def get_Johnson_Glass_filt(name):
     try:
         t = Table.read('{0}/Johnson_Glass/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find Johnson-Glass filter {0} in {1}/Johnson_Glass'.format(name, filters_dir))         
+        raise ValueError('Could not find Johnson-Glass filter {0} in {1}/Johnson_Glass'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10.
@@ -191,10 +191,10 @@ def get_Johnson_Glass_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='jg_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_nirc1_filt(name):
     """
@@ -203,12 +203,12 @@ def get_nirc1_filt(name):
     try:
         t = Table.read('{0}/nirc1/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find NIRC1 filter {0} in {1}/nirc1'.format(name, filters_dir))         
+        raise ValueError('Could not find NIRC1 filter {0} in {1}/nirc1'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
     trans = t['col2']
-    
+
     # Lets fix wavelength array for duplicate values or negative vals;
     # delete these entries
     diff = np.diff(wave)
@@ -222,14 +222,14 @@ def get_nirc1_filt(name):
 
         diff = np.diff(wave)
         idx = np.where(diff <= 0)[0]
-        
+
     # Change any negative transmission vals to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
 
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='nirc1_{0}'.format(name))
 
-    return spectrum    
+    return spectrum
 
 def get_ctio_osiris_filt(name):
     """
@@ -238,7 +238,7 @@ def get_ctio_osiris_filt(name):
     try:
         t = Table.read('{0}/CTIO_OSIRIS/{1}.txt'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find CTIO/OSIRIS filter {0} in {1}/CTIO_OSIRIS'.format(name, filters_dir))         
+        raise ValueError('Could not find CTIO/OSIRIS filter {0} in {1}/CTIO_OSIRIS'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
@@ -247,7 +247,7 @@ def get_ctio_osiris_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='ctio_osiris_{0}'.format(name))
 
     return spectrum
@@ -259,7 +259,7 @@ def get_naco_filt(name):
     try:
         t = Table.read('{0}/naco/{1}.dat'.format(filters_dir, name), format='ascii')
     except:
-        raise ValueError('Could not find NACO filter {0} in {1}/naco'.format(name, filters_dir))         
+        raise ValueError('Could not find NACO filter {0} in {1}/naco'.format(name, filters_dir))
 
     # Convert wavelengths to angstroms
     wave = t['col1'] * 10**4
@@ -268,7 +268,7 @@ def get_naco_filt(name):
     # Change any negative numbers to 0
     bad = np.where(trans < 0)
     trans[bad] = 0
-    
+
     spectrum = pysynphot.ArrayBandpass(wave, trans, waveunits='angstrom', name='naco_{0}'.format(name))
 
     return spectrum
@@ -282,7 +282,7 @@ def get_ubv_filt(name):
     except:
         raise ValueError('Could not find ubv filter {0} in {1}/ubv'.format(name, filters_dir))
 
-    # Convert wavelength from nm to angstroms 
+    # Convert wavelength from nm to angstroms
     wave = t[t.keys()[0]] * 10.
     # Convert transmission to ratio (from percent)
     trans = t[t.keys()[1]] / 100.
@@ -336,8 +336,8 @@ def get_keck_osiris_filt(name):
 def get_gaia_filt(version, name):
     """
     Define Gaia filters as pysynphot object.
-    To avoid confusion, we will only support 
-    the revised DR2 zeropoints from 
+    To avoid confusion, we will only support
+    the revised DR2 zeropoints from
     Evans+18.
 
     version: specify dr1, dr2, or dr2_rev
@@ -357,7 +357,7 @@ def get_gaia_filt(version, name):
         path = '{0}/gaia/dr2_rev/'.format(filters_dir)
     else:
         raise ValueError('GAIA filter version {0} not understood. Please use dr1, dr2, or dr2_rev'.format(version))
-        
+
     # Get the filter info
     try:
         t = Table.read('{0}/Gaia_passbands.txt'.format(path), format='ascii')
@@ -380,7 +380,7 @@ def get_gaia_filt(version, name):
         bad = np.where(trans > 90)
         trans[bad] = 0
     except:
-        raise ValueError('Could not find Gaia filter {0}'.format(name))   
+        raise ValueError('Could not find Gaia filter {0}'.format(name))
 
     # Convert wavelengths to angstroms (from nm)
     wave = t['LAMBDA'] * 10
diff --git a/spisea/ifmr.py b/spisea/ifmr.py
index cafa66d6..b7cc7235 100755
--- a/spisea/ifmr.py
+++ b/spisea/ifmr.py
@@ -12,7 +12,7 @@
 #https://ui.adsabs.harvard.edu/abs/2014ApJ...783...10S/abstract
 #BH/NS IFMR based on Sukhbold et al. 2016 for solar-Z models::
 #https://ui.adsabs.harvard.edu/abs/2016ApJ...821...38S/abstract
-#PPISN based on Woosley 2017: 
+#PPISN based on Woosley 2017:
 #https://ui.adsabs.harvard.edu/abs/2017ApJ...836..244W/abstract
 #PPSIN based on Woosley et al. 2020:
 #https://ui.adsabs.harvard.edu/abs/2020ApJ...896...56W/abstract
@@ -38,7 +38,7 @@ def get_Z(self, Fe_H):
         return 10**(Fe_H - 1.85387)
 
     def Kalirai_mass(self, MZAMS):
-        """                                                                                                      
+        """
         From Kalirai+08 https://ui.adsabs.harvard.edu/abs/2008ApJ...676..594K/abstract
         1.16 < MZAMS < 6.5
         But we use this function for anything between 0.5 and 9 depending on the IFMR.
@@ -48,34 +48,34 @@ def Kalirai_mass(self, MZAMS):
         result = 0.109*MZAMS + 0.394
 
         final = np.zeros(len(MZAMS))
-        
+
         good_idx = MZAMS >= 0.5
         final[good_idx] = result[good_idx]
         final[~good_idx] = -99
 
         return final
-        
-        
+
+
 
 
 class IFMR_Spera15(IFMR):
     """
     The BH/NS IFMR (used for MZAMS>= 7 M_sun) comes from
     `Spera et. al. (2015) Appendix C <https://ui.adsabs.harvard.edu/abs/2015MNRAS.451.4086S/abstract>`_.
-    The WD IFMR (used for MZAMS< 7_Msun) comes from 
+    The WD IFMR (used for MZAMS< 7_Msun) comes from
     `Kalirai et al. (2008) <https://ui.adsabs.harvard.edu/abs/2008ApJ...676..594K/abstract>`_.
 
     See Rose et al. (submitted) for more details.
-    
+
     """
-    
+
     #The get_Mco functions come from C11 of Spera
     def get_Mco_low_metal(self, Z, MZAMS):
         """
         C15 of Spera, valid for Z < 1.0e-3
-    
+
         """
-        
+
         B1 = 67.07
         K1 = 46.89
         K2 = 1.138e2
@@ -94,7 +94,7 @@ def get_Mco_med_metal(self, Z, MZAMS):
         C14 of Spera, valid for Z >= 1.0e-3 and Z <= 4.0e-3
 
         """
-        
+
         B1 = 40.98 + 3.415e4*Z - 8.064e6*Z**2
         K1 = 35.17 + 1.548e4*Z - 3.759e6*Z**2
         K2 = 20.36 + 1.162e5*Z - 2.276e7*Z**2
@@ -113,7 +113,7 @@ def get_Mco_high_metal(self, Z, MZAMS):
         C13 of Spera, valid for Z > 4.0e-3
 
         """
-        
+
         B1 = 59.63 - 2.969e3*Z + 4.988e4*Z**2
         K1 = 45.04 - 2.176e3*Z + 3.806e4*Z**2
         K2 = 1.389e2 - 4.664e3*Z + 5.106e4*Z**2
@@ -123,7 +123,7 @@ def get_Mco_high_metal(self, Z, MZAMS):
         g1 = 0.5/(1+10**((K1-MZAMS)*(d1))) #C12 of Spera
         g2 = 0.5/(1+10**((K2-MZAMS)*(d2))) #C12 of Spera
 
-        
+
         return -2.0 + (B1 + 2.0)*(g1 + g2) #C11 of Spera
 
 
@@ -132,8 +132,8 @@ def get_Mco(self, Z, MZAMS):
         This function uses Spera C11-C15 in order to reurn an array of core masses from an array of metallicities
         and ZAMS masses. It will be the same length as these two arrays with -99 entries where invalid (ie MZAMS< 7 M_sun)
 
-        Parameters: 
-        
+        Parameters:
+
         Z: an array with metallicities reported as Z where Z is metal_mass/total_mass
         MZAMS: an array of ZAMS masses in solar masses. The Spera functions are valid for MZAMS> 7 M_sun
 
@@ -158,28 +158,28 @@ def get_Mco(self, Z, MZAMS):
         core_masses[high_metal_idx] = self.get_Mco_high_metal(Z[high_metal_idx], MZAMS[high_metal_idx])
 
         return core_masses
-        
+
 
 
     def M_rem_very_low_metal_low_mass(self, Z, Mco):
         """
         C1 of Spera, valid for Z <= 5.0e-4 and Mco <= 5.0
-        
+
         Parameters:
 
         Z: an array of metallicities reported as metal_mass/total_mass
         Mco: an arrray of core masses in M_sun
 
         """
-        
+
         p = -2.333 + 0.1559*Mco + 0.2700*Mco**2 #C2 of Spera
 
         #need to return p or 1.27, whichever is greater
         final = np.zeros(len(p))
-        
+
         p_max_idx = np.where(p >= 1.27)
         final[p_max_idx] = p[p_max_idx]
-        
+
         p_min_idx = np.where(p < 1.27)
         final[p_min_idx] = 1.27
 
@@ -217,7 +217,7 @@ def M_rem_very_low_metal_high_mass(self, Z, Mco):
 
         m = -6.476e2*Z + 1.911 #C3 of Spera
         q = 2.300e3*Z + 11.67 #C3 of Spera
-            
+
         f = m*Mco + q #C2 of Spera
 
         #need to return either p or f, whichever is less
@@ -228,7 +228,7 @@ def M_rem_very_low_metal_high_mass(self, Z, Mco):
 
         f_min_idx = np.where(f < p)
         final[f_min_idx] = f[f_min_idx]
-        
+
         return final
 
     def M_rem_low_metal_low_mass(self, Z, Mco):
@@ -252,15 +252,15 @@ def M_rem_low_metal_low_mass(self, Z, Mco):
 
         #need to return h or 1.27, whichever is greater
         final = np.zeros(len(h))
-        
+
         h_max_idx = np.where(h >= 1.27)
         final[h_max_idx] = h[h_max_idx]
-        
+
         h_min_idx = np.where(h < 1.27)
         final[h_min_idx] = 1.27
 
         return final
-    
+
 
     def M_rem_low_metal_med_mass(self, Z, Mco):
         """
@@ -316,9 +316,9 @@ def M_rem_low_metal_high_mass(self, Z, Mco):
 
         f_max_idx = np.where(f > h)
         final[f_max_idx] = f[f_max_idx]
-        
+
         return final
-            
+
 
     def M_rem_med_metal_low_mass(self, Z, Mco):
         """
@@ -341,10 +341,10 @@ def M_rem_med_metal_low_mass(self, Z, Mco):
 
         #need to return h or 1.27, whichever is greater
         final = np.zeros(len(h))
-        
+
         h_max_idx = np.where(h >= 1.27)
         final[h_max_idx] = h[h_max_idx]
-        
+
         h_min_idx = np.where(h < 1.27)
         final[h_min_idx] = 1.27
 
@@ -395,7 +395,7 @@ def M_rem_med_metal_high_mass_1(self, Z, Mco):
         q = -1.296e4*Z + 26.98
 
         f = m*Mco + q #C5 of Spera
-            
+
         #need to return either h or f, whichever is greater
         final = np.zeros(len(h))
 
@@ -404,7 +404,7 @@ def M_rem_med_metal_high_mass_1(self, Z, Mco):
 
         f_max_idx = np.where(f > h)
         final[f_max_idx] = f[f_max_idx]
-        
+
         return final
 
     def M_rem_med_metal_high_mass_2(self, Z, Mco):
@@ -431,7 +431,7 @@ def M_rem_med_metal_high_mass_2(self, Z, Mco):
         q = 1.061
 
         f = m*Mco + q #C5 of Spera
-            
+
         #need to return either h or f, whichever is greater
         final = np.zeros(len(h))
 
@@ -440,7 +440,7 @@ def M_rem_med_metal_high_mass_2(self, Z, Mco):
 
         f_max_idx = np.where(f > h)
         final[f_max_idx] = f[f_max_idx]
-        
+
         return final
 
 
@@ -465,10 +465,10 @@ def M_rem_high_metal_low_mass(self, Z, Mco):
 
         #need to return h or 1.27, whichever is greater
         final = np.zeros(len(h))
-        
+
         h_max_idx = np.where(h >= 1.27)
         final[h_max_idx] = h[h_max_idx]
-        
+
         h_min_idx = np.where(h < 1.27)
         final[h_min_idx] = 1.27
 
@@ -519,7 +519,7 @@ def M_rem_high_metal_high_mass(self, Z, Mco):
         q = 1.061
 
         f = m*Mco + q #C5 of Spera
-            
+
         #need to return either h or f, whichever is greater
         final = np.zeros(len(h))
 
@@ -528,15 +528,15 @@ def M_rem_high_metal_high_mass(self, Z, Mco):
 
         f_max_idx = np.where(f > h)
         final[f_max_idx] = f[f_max_idx]
-        
+
         return final
 
 
     def generate_death_mass(self, mass_array, metallicity_array):
         """
-        The top-level function that assigns the remnant type 
-        and mass based on the stellar initial mass. 
-        
+        The top-level function that assigns the remnant type
+        and mass based on the stellar initial mass.
+
         Parameters
         ----------
         mass_array: array of floats
@@ -547,20 +547,20 @@ def generate_death_mass(self, mass_array, metallicity_array):
         Notes
         ------
         The output typecode tells what compact object formed:
-        
+
         * WD: typecode = 101
         * NS: typecode = 102
         * BH: typecode = 103
-        A typecode of value -1 means you're outside the range of 
-        validity for applying the ifmr formula. 
-        A remnant mass of -99 means you're outside the range of 
+        A typecode of value -1 means you're outside the range of
+        validity for applying the ifmr formula.
+        A remnant mass of -99 means you're outside the range of
         validity for applying the ifmr formula.
-        Range of validity: MZAMS > 0.5 
-        
+        Range of validity: MZAMS > 0.5
+
         Returns
         -------
         output_arr: 2-element array
-            output_array[0] contains the remnant mass, and 
+            output_array[0] contains the remnant mass, and
             output_array[1] contains the typecode
         """
 
@@ -585,10 +585,10 @@ def generate_death_mass(self, mass_array, metallicity_array):
         Kal_idx = np.where(core_mass < 0)
         rem_mass_array[Kal_idx] = self.Kalirai_mass(mass_array[Kal_idx])
 
-        
+
 
         ##### very low metallicity Z < 5.0e-4
-        
+
         #remnant masses of stars with Z < 5.0e-4 and Mco < 5.0
         very_low_metal_low_mass_idx = np.where((Z_array < 5.0e-4) & (core_mass < 5.0) & (core_mass >= 0))
         rem_mass_array[very_low_metal_low_mass_idx] = self.M_rem_very_low_metal_low_mass(Z_array[very_low_metal_low_mass_idx], core_mass[very_low_metal_low_mass_idx])
@@ -602,7 +602,7 @@ def generate_death_mass(self, mass_array, metallicity_array):
         rem_mass_array[very_low_metal_high_mass_idx] = self.M_rem_very_low_metal_high_mass(Z_array[very_low_metal_high_mass_idx], core_mass[very_low_metal_high_mass_idx])
 
         #### low metallicity 5.0e-4 <= Z < 1.0e-3
-        
+
         #remnant masses of stars with 5.0e-4 <= Z < 1.0e-3 and Mco < 5.0
         low_metal_low_mass_idx = np.where((Z_array >= 5.0e-4) & (Z_array < 1.0e-3) & (core_mass < 5.0) & (core_mass >= 0))
         rem_mass_array[low_metal_low_mass_idx] = self.M_rem_low_metal_low_mass(Z_array[low_metal_low_mass_idx], core_mass[low_metal_low_mass_idx])
@@ -614,9 +614,9 @@ def generate_death_mass(self, mass_array, metallicity_array):
         #remnant masses of stars with 5.0e-4 <= Z < 1.0e-3 and Mco > 10.0
         low_metal_high_mass_idx = np.where((Z_array >= 5.0e-4) & (Z_array < 1.0e-3) & (core_mass > 10.0))
         rem_mass_array[low_metal_high_mass_idx] = self.M_rem_low_metal_high_mass(Z_array[low_metal_high_mass_idx], core_mass[low_metal_high_mass_idx])
-                
+
         #### medium metallicity 1.0e-3 <= Z <= 4.0e-3
-        
+
         #remnant masses of stars with 1.0e-3 <= Z <= 4.0e-3 and Mco < 5.0
         med_metal_low_mass_idx = np.where((Z_array >= 1.0e-3) & (Z_array <= 4.0e-3) & (core_mass < 5.0) & (core_mass >= 0))
         rem_mass_array[med_metal_low_mass_idx] = self.M_rem_med_metal_low_mass(Z_array[med_metal_low_mass_idx],core_mass[med_metal_low_mass_idx])
@@ -632,9 +632,9 @@ def generate_death_mass(self, mass_array, metallicity_array):
         #remnant masses of stars with 2.0e-3 <= Z <= 4.0e-3 and Mco > 10.0
         med_metal_high_mass_idx_2 = np.where((Z_array >= 2.0e-3) & (Z_array <= 4.0e-3) & (core_mass > 10.0))
         rem_mass_array[med_metal_high_mass_idx_2] = self.M_rem_med_metal_high_mass_2(Z_array[med_metal_high_mass_idx_2], core_mass[med_metal_high_mass_idx_2])
-        
+
         #### high metallicity Z > 4.0e-3
-        
+
         #remnant masses of stars with Z > 4.0e-3 and Mco < 5.0
         high_metal_low_mass_idx = np.where((Z_array > 4.0e-3) & (core_mass < 5.0) & (core_mass >= 0))
         rem_mass_array[high_metal_low_mass_idx] = self.M_rem_high_metal_low_mass(Z_array[high_metal_low_mass_idx], core_mass[high_metal_low_mass_idx])
@@ -646,16 +646,16 @@ def generate_death_mass(self, mass_array, metallicity_array):
         #remnant masses of stars with Z > 4.0e-3 and MZAMS > 10.0
         high_metal_high_mass_idx = np.where((Z_array > 4.0e-3) & (core_mass > 10.0))
         rem_mass_array[high_metal_high_mass_idx] = self.M_rem_high_metal_high_mass(Z_array[high_metal_high_mass_idx], core_mass[high_metal_high_mass_idx])
-        
+
         #assign object types based on remnant mass
         bad_idx = np.where(rem_mass_array < 0) #outside the range of validity for the ifmr
         WD_idx = np.where((rem_mass_array <= 1.4) & (rem_mass_array >= 0 )) #based on the Chandresekhar limit
-        NS_idx = np.where((rem_mass_array > 1.4) & (rem_mass_array <= 3.0)) #based on figures 15-17 of Spera 
+        NS_idx = np.where((rem_mass_array > 1.4) & (rem_mass_array <= 3.0)) #based on figures 15-17 of Spera
         BH_idx = np.where(rem_mass_array > 3.0) #based on figures 15-17 of Spera
 
         output_array[0][bad_idx] = rem_mass_array[bad_idx]
         output_array[1][bad_idx] = -1
-        
+
         output_array[0][WD_idx] = rem_mass_array[WD_idx]
         output_array[1][WD_idx] = codes['WD']
 
@@ -666,76 +666,76 @@ def generate_death_mass(self, mass_array, metallicity_array):
         output_array[1][BH_idx] = codes['BH']
 
         return output_array
-        
+
 
 
 class IFMR_Raithel18(IFMR):
     """
-    The IFMR is a combination of the WD IFMR from 
+    The IFMR is a combination of the WD IFMR from
     `Kalirai et al. (2008) <https://ui.adsabs.harvard.edu/abs/2008ApJ...676..594K/abstract>`_
     and the NS/BH IFMR from
     `Raithel et al. (2018) <https://ui.adsabs.harvard.edu/abs/2018ApJ...856...35R/abstract>`_.
-    Note that the NS masses are NOT assigned based on the above results. 
+    Note that the NS masses are NOT assigned based on the above results.
     We do take the NS/BH formation ratio and the BH masses.
-    NS masses are assigned based on random draws from a Gaussian (see NS_mass function). 
+    NS masses are assigned based on random draws from a Gaussian (see NS_mass function).
 
-    See 
+    See
     `Lam et al. (2020) <https://ui.adsabs.harvard.edu/abs/2020ApJ...889...31L/abstract>`_
     and Rose et al. (submitted)  for more details.
     """
 
     def BH_mass_core_low(self, MZAMS):
-        """                                                                                                      
-        Eqn (1)                                                                                                  
-        Paper: 15 < MZAMS < 40                                                                                   
-        Us extending: 15 < MZAMS < 42.22                                                                         
+        """
+        Eqn (1)
+        Paper: 15 < MZAMS < 40
+        Us extending: 15 < MZAMS < 42.22
         """
         return -2.024 + 0.4130*MZAMS
 
     def BH_mass_all_low(self, MZAMS):
-        """                                                                                                      
-        Eqn (2)                                                                                                  
-        Paper: 15 < MZAMS < 40                                                                                   
-        Us extending: 15 < MZAMS < 42.22                                                                         
+        """
+        Eqn (2)
+        Paper: 15 < MZAMS < 40
+        Us extending: 15 < MZAMS < 42.22
         """
         return 16.28 + 0.00694 * (MZAMS - 21.872) - 0.05973 * (MZAMS - 21.872)**2 + 0.003112 * (MZAMS - 21.872)**3
 
     def BH_mass_high(self, MZAMS):
-        """                                                                                                      
-        Eqn (3)                                                                                                  
-        Paper: 45 < MZAMS < 120                                                                                  
-        Us extending: 42.22 < MZAMS < 120                                                                        
+        """
+        Eqn (3)
+        Paper: 45 < MZAMS < 120
+        Us extending: 42.22 < MZAMS < 120
         """
         return 5.795 + 1.007 * 10**9 * MZAMS**-4.926
 
     def BH_mass_low(self, MZAMS, f_ej):
-        """                                                                                                      
-        Eqn (4)                                                                                                  
-        Paper: 15 < MZAMS < 40                                                                                   
-        Us extending: 15 < MZAMS < 42.22                                                                         
+        """
+        Eqn (4)
+        Paper: 15 < MZAMS < 40
+        Us extending: 15 < MZAMS < 42.22
         """
         return f_ej * self.BH_mass_core_low(MZAMS) + (1 - f_ej) * self.BH_mass_all_low(MZAMS)
 
     def NS_mass(self, MZAMS):
-        """                                                                                                      
+        """
         Drawing the NS mass from a Gaussian distrobuton based on observational data.
 
         Gaussian fit by Emily Ramey and Sergiy Vasylyev of University of Caifornia, Berkeley using a
-        sample of NSs from Ozel & Freire (2016) — J1811+2405 Ng et al. (2020), 
-        J2302+4442 Kirichenko et al. (2018), J2215+5135 Linares et al. (2018), 
-        J1913+1102 Ferdman & Collaboration (2017), J1411+2551 Martinez et al. (2017), 
+        sample of NSs from Ozel & Freire (2016) — J1811+2405 Ng et al. (2020),
+        J2302+4442 Kirichenko et al. (2018), J2215+5135 Linares et al. (2018),
+        J1913+1102 Ferdman & Collaboration (2017), J1411+2551 Martinez et al. (2017),
         J1757+1854 Cameron et al. (2018), J0030+0451 Riley et al. (2019), J1301+0833 Romani et al. (2016)
         The Gaussian distribution was fit using this data and a Bayesian MCMC method adapted from
         Kiziltan et al. (2010).
-        
+
         """
         return self.rng.normal(loc=1.36, scale=0.09, size=len(MZAMS))
 
     def generate_death_mass(self, mass_array):
         """
-        The top-level function that assigns the remnant type 
-        and mass based on the stellar initial mass. 
-        
+        The top-level function that assigns the remnant type
+        and mass based on the stellar initial mass.
+
         Parameters
         ----------
         mass_array: array of floats
@@ -746,15 +746,15 @@ def generate_death_mass(self, mass_array):
         Notes
         ------
         The output typecode tells what compact object formed:
-        
+
         * WD: typecode = 101
         * NS: typecode = 102
         * BH: typecode = 103
 
-        A typecode of value -1 means you're outside the range of 
-        validity for applying the ifmr formula. 
+        A typecode of value -1 means you're outside the range of
+        validity for applying the ifmr formula.
 
-        A remnant mass of -99 means you're outside the range of 
+        A remnant mass of -99 means you're outside the range of
         validity for applying the ifmr formula.
 
         Range of validity: 0.5 < MZAMS < 120
@@ -762,7 +762,7 @@ def generate_death_mass(self, mass_array):
         Returns
         -------
         output_arr: 2-element array
-            output_array[0] contains the remnant mass, and 
+            output_array[0] contains the remnant mass, and
             output_array[1] contains the typecode
         """
 
@@ -774,7 +774,7 @@ def generate_death_mass(self, mass_array):
         random_array = self.rng.integers(1, 1001, size = len(mass_array))
 
         codes = {'WD': 101, 'NS': 102, 'BH': 103}
-        
+
         """
         The id_arrays are to separate all the different formation regimes
         """
@@ -801,7 +801,7 @@ def generate_death_mass(self, mass_array):
         id_array4_BH = np.where((mass_array >= 17.8) & (mass_array < 18.5) & (random_array > 833))
         output_array[0][id_array4_BH]= self.BH_mass_low(mass_array[id_array4_BH], 0.9)
         output_array[1][id_array4_BH] = codes['BH']
-        
+
         id_array4_NS = np.where((mass_array >= 17.8) & (mass_array < 18.5) & (random_array <= 833))
         output_array[0][id_array4_NS] = self.NS_mass(mass_array[id_array4_NS])
         output_array[1][id_array4_NS] = codes['NS']
@@ -809,7 +809,7 @@ def generate_death_mass(self, mass_array):
         id_array5_BH = np.where((mass_array >= 18.5) & (mass_array < 21.7) & (random_array > 500))
         output_array[0][id_array5_BH] = self.BH_mass_low(mass_array[id_array5_BH], 0.9)
         output_array[1][id_array5_BH] = codes['BH']
-        
+
         id_array5_NS = np.where((mass_array >= 18.5) & (mass_array < 21.7) & (random_array <= 500))
         output_array[0][id_array5_NS] = self.NS_mass(mass_array[id_array5_NS])
         output_array[1][id_array5_NS] = codes['NS']
@@ -821,7 +821,7 @@ def generate_death_mass(self, mass_array):
         id_array7_BH = np.where((mass_array >= 25.2) & (mass_array < 27.5) & (random_array > 652))
         output_array[0][id_array7_BH] = self.BH_mass_low(mass_array[id_array7_BH], 0.9)
         output_array[1][id_array7_BH] = codes['BH']
-        
+
         id_array7_NS = np.where((mass_array >= 25.2) & (mass_array < 27.5) & (random_array <= 652))
         output_array[0][id_array7_NS] = self.NS_mass(mass_array[id_array7_NS])
         output_array[1][id_array7_NS] = codes['NS']
@@ -837,7 +837,7 @@ def generate_death_mass(self, mass_array):
         id_array10_BH = np.where((mass_array >= 60) & (mass_array < 120) & (random_array > 400))
         output_array[0][id_array10_BH] = self.BH_mass_high(mass_array[id_array10_BH])
         output_array[1][id_array10_BH] = codes['BH']
-        
+
         id_array10_NS = np.where((mass_array >= 60) & (mass_array < 120) & (random_array <= 400))
         output_array[0][id_array10_NS] = self.NS_mass(mass_array[id_array10_NS])
         output_array[1][id_array10_NS] = codes['NS']
@@ -850,11 +850,11 @@ class IFMR_N20_Sukhbold(IFMR):
     `Sukhbold & Woosley (2014) <https://ui.adsabs.harvard.edu/abs/2014ApJ...783...10S/abstract>`_.
     The BH/NS IFMR for solar metallicity progenitors comes from
     `Sukhbold et al. (2016) <https://ui.adsabs.harvard.edu/abs/2016ApJ...821...38S/abstract>`_.
-    The PPISN models are from 
+    The PPISN models are from
     `Woosley (2017) <https://ui.adsabs.harvard.edu/abs/2017ApJ...836..244W/abstract>`_
     and
     `Woosley et al. (2020) <https://ui.adsabs.harvard.edu/abs/2020ApJ...896...56W/abstract>`_.
-    The WD IFMR is from 
+    The WD IFMR is from
     `Kalirai et al. (2008) <https://ui.adsabs.harvard.edu/abs/2008ApJ...676..594K/abstract>`_.
     Note that the NS masses are NOT assigned based on the above results.
     We do take the NS/BH formation ratio and the BH masses.
@@ -869,7 +869,7 @@ def zero_BH_mass(self, MZAMS):
         #func = np.poly1d(zero_coeff)
         #result = func(MZAMS)
         return 0.46522639*MZAMS + -3.29170817
-    
+
     def solar_BH_mass(self, MZAMS):
         #solar_coeff = [-0.27079245, 24.74320755]
         #func = np.poly1d(solar_coeff)
@@ -879,24 +879,24 @@ def solar_BH_mass(self, MZAMS):
     Zsun = 0.014
 
     def NS_mass(self, MZAMS):
-        """                                                                                                      
+        """
         Drawing the NS mass from a Gaussian distrobuton based on observational data.
 
         Gaussian fit by Emily Ramey and Sergiy Vasylyev of University of Caifornia, Berkeley using a
-        sample of NSs from Ozel & Freire (2016) — J1811+2405 Ng et al. (2020), 
-        J2302+4442 Kirichenko et al. (2018), J2215+5135 Linares et al. (2018), 
-        J1913+1102 Ferdman & Collaboration (2017), J1411+2551 Martinez et al. (2017), 
+        sample of NSs from Ozel & Freire (2016) — J1811+2405 Ng et al. (2020),
+        J2302+4442 Kirichenko et al. (2018), J2215+5135 Linares et al. (2018),
+        J1913+1102 Ferdman & Collaboration (2017), J1411+2551 Martinez et al. (2017),
         J1757+1854 Cameron et al. (2018), J0030+0451 Riley et al. (2019), J1301+0833 Romani et al. (2016)
         The Gaussian distribution was fit using this data and a Bayesian MCMC method adapted from
         Kiziltan et al. (2010).
-        
+
         """
         if isinstance(MZAMS, np.ndarray):
             return self.rng.normal(loc=1.36, scale=0.09, size=len(MZAMS))
         else:
             return self.rng.normal(loc=1.36, scale=0.09, size=1)[0]
- 
- 
+
+
     def BH_mass_low(self, MZAMS):
         """
         9 < MZAMS < 40 Msun
@@ -912,7 +912,7 @@ def BH_mass_high(self, MZAMS, Z):
         """
         # Solar metallicity (what Sam is using)
         Zsun = 0.014
-        
+
         zfrac = np.atleast_1d(Z/Zsun)
         # super-solar Z gives identical results as solar Z
         above_idx = np.where(zfrac > 1)
@@ -935,15 +935,15 @@ def prob_BH_high(self, Z):
         """
         # Solar metallicity (what Sam is using)
         Zsun = 0.014
-        
+
         Z = np.atleast_1d(Z)
         # Convert from [Fe/H] to Z
         zfrac = Z / Zsun
-        
+
         # super-solar Z gives identical results as solar Z
         zfrac[zfrac > 1] = 1.0
         zfrac[zfrac < 0] = np.nan
-        
+
         pBH = 1 - 0.8*zfrac
 
         return pBH
@@ -951,9 +951,9 @@ def prob_BH_high(self, Z):
 
     def generate_death_mass(self, mass_array, metallicity_array):
         """
-        The top-level function that assigns the remnant type 
-        and mass based on the stellar initial mass. 
-        
+        The top-level function that assigns the remnant type
+        and mass based on the stellar initial mass.
+
         Parameters
         ----------
         mass_array: array of floats
@@ -964,27 +964,27 @@ def generate_death_mass(self, mass_array, metallicity_array):
         Notes
         ------
         The output typecode tells what compact object formed:
-        
+
         * WD: typecode = 101
         * NS: typecode = 102
         * BH: typecode = 103
-        A typecode of value -1 means you're outside the range of 
-        validity for applying the ifmr formula. 
-        A remnant mass of -99 means you're outside the range of 
+        A typecode of value -1 means you're outside the range of
+        validity for applying the ifmr formula.
+        A remnant mass of -99 means you're outside the range of
         validity for applying the ifmr formula.
-        Range of validity: MZAMS > 0.5 
-        
+        Range of validity: MZAMS > 0.5
+
         Returns
         -------
         output_arr: 2-element array
-            output_array[0] contains the remnant mass, and 
+            output_array[0] contains the remnant mass, and
             output_array[1] contains the typecode
         """
         #output_array[0] holds the remnant mass
         #output_array[1] holds the remnant type
         mass_array = np.atleast_1d(mass_array)
         metallicity_array = np.atleast_1d(metallicity_array)
-        
+
         output_array = np.zeros((2, len(mass_array)))
 
         codes = {'WD': 101, 'NS': 102, 'BH': 103}
@@ -1042,14 +1042,14 @@ def generate_death_mass(self, mass_array, metallicity_array):
         BH_or_NS = np.where((mass_array >= 60) & (mass_array < 120))[0]
         pBH = self.prob_BH_high(Z_array[BH_or_NS])
         is_BH = random_array[BH_or_NS] > 100 * pBH
-        
+
         id_array8 = BH_or_NS[is_BH]
         id_array9 = BH_or_NS[~is_BH]
-        
+
         # Assign BH masses and types for BH-forming indices
         output_array[0][id_array8] = self.BH_mass_high(mass_array[id_array8], Z_array[id_array8])
         output_array[1][id_array8] = codes['BH']
-        
+
         # Assign NS masses and types for NS-forming indices
         output_array[0][id_array9] = self.NS_mass(mass_array[id_array9])
         output_array[1][id_array9] = codes['NS']
diff --git a/spisea/reddening.py b/spisea/reddening.py
index 2754719b..677999a8 100755
--- a/spisea/reddening.py
+++ b/spisea/reddening.py
@@ -24,12 +24,12 @@ def get_red_law(str):
     ----------
     str: str
         Reddening law name and additional params (comma-separated).
-        Name must match 
+        Name must match
     """
     # Parse the string, extracting redlaw name and other params
     tmp = str.split(',')
     name = tmp[0]
-    
+
     # How we split this up changes for the broken power law EL
     # versus the other ELs (since we have arrays for broken power law EL)
     if name == 'broken_pl':
@@ -86,12 +86,12 @@ def get_red_law(str):
 
 class RedLawNishiyama09(pysynphot.reddening.CustomRedLaw):
     """
-    The extinction law towards the Galactic Center 
-    from `Nishiyama et al. 2009 
+    The extinction law towards the Galactic Center
+    from `Nishiyama et al. 2009
     <https://ui.adsabs.harvard.edu/abs/2009ApJ...696.1407N/abstract>`_,
-    combined with the Av / AKs value from `Nishiyama et al. 2008 
-    <https://ui.adsabs.harvard.edu/abs/2008ApJ...680.1174N/abstract>`_.    
-    This law is defined between 0.5 - 8.0 microns. 
+    combined with the Av / AKs value from `Nishiyama et al. 2008
+    <https://ui.adsabs.harvard.edu/abs/2008ApJ...680.1174N/abstract>`_.
+    This law is defined between 0.5 - 8.0 microns.
 
     This law is constructed in 3 segments:
 
@@ -107,7 +107,7 @@ class RedLawNishiyama09(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Fetch the extinction curve, pre-interpolate across 3-8 microns
         wave = np.arange(0.5, 8.0, 0.001)
-        
+
         # This will eventually be scaled by AKs when you
         # call reddening(). Right now, calc for AKs=1
         wave_vals, Alambda_scaled = RedLawNishiyama09._derive_nishiyama09(wave)
@@ -115,7 +115,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave_vals *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave_vals, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave_vals,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Nishiyama09',
@@ -128,10 +128,10 @@ def __init__(self):
         # Other info
         self.scale_lambda = 2.14
         self.name = 'N09'
-    
+
     @staticmethod
     def _derive_nishiyama09(wavelength):
-        """ 
+        """
         Calculate the N09 extinction law as defined in the paper:
         a A_lambda/AKs = power law of exponent -2.0 between JHK. Then
         use a *linear* interpolation in 1/lambda space to go from J to the V-band observation,
@@ -148,7 +148,7 @@ def _derive_nishiyama09(wavelength):
         #-----Define power law extinction law between JHK----#
         jhk_idx = np.where( (wavelength >= 1.25) & (wavelength <= 2.14) )
         #jhk_idx = np.where( (wavelength >= 1.25) & (wavelength <= 2.3) )
-        
+
         alpha = 2.0
         wave_jhk = wavelength[jhk_idx]
         idx_scale = np.where(abs(wave_jhk - 2.14) == min(abs(wave_jhk - 2.14)) )
@@ -177,10 +177,10 @@ def _derive_nishiyama09(wavelength):
         #wave = np.array([0.551, 1.25, 1.63, 2.14, wave_jhk[-1], 3.545, 4.442, 5.675, 7.760])
         #A_AKs = np.array([16.13, 3.02, 1.73, 1.00, A_Ks_jhk[-1], 0.500, 0.390, 0.360, 0.430])
         #interp_idx = np.where(wave > 2.2)
-        
+
         spline_interp = interpolate.splrep(wave[interp_idx], A_AKs[interp_idx], k=3, s=0)
         A_AKs_long = interpolate.splev(wavelength[long_idx], spline_interp)
-        
+
         # Stitch together sections for the final law
         wave_vals = np.concatenate((wavelength[jv_idx[0]], wavelength[jhk_idx[0]]))
         A_AKs_vjhk = np.concatenate((A_Ks_jv, A_Ks_jhk))
@@ -192,8 +192,8 @@ def _derive_nishiyama09(wavelength):
         return wave_vals, A_AKs_final
 
     def Nishiyama09(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -213,7 +213,7 @@ def Nishiyama09(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -261,33 +261,33 @@ def plot_Nishiyama09(self):
         py.savefig('nishiyama09_el.png')
 
         return
-    
+
 class RedLawCardelli(pysynphot.reddening.CustomRedLaw):
     """
-    Defines the extinction law from  
-    `Cardelli et al. 1989 <https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C/abstract>`_. 
+    Defines the extinction law from
+    `Cardelli et al. 1989 <https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C/abstract>`_.
     The law is defined from 0.3 - 3 microns, and in terms
     of :math:`A_{\lambda} / A_{Ks}`, where Ks is 2.174 microns.
 
     Parameters
     ----------
     Rv : float
-        Ratio of absolute to selective extinction, :math:`A(V) / E(B-V)`. 
+        Ratio of absolute to selective extinction, :math:`A(V) / E(B-V)`.
         The standard value for the diffuse ISM is 3.1.
     """
     def __init__(self, Rv):
         # Fetch the extinction curve, pre-interpolate across 0.3-3 microns
         wave = np.arange(0.3, 3.0, 0.001)
-        
+
         # This will eventually be scaled by AKs when you
-        # call reddening(). Produces A_lambda for AKs = 1, which will be 
+        # call reddening(). Produces A_lambda for AKs = 1, which will be
         # scaled later. Expects wavelength in microns
         Alambda_scaled = RedLawCardelli._derive_cardelli(wave, Rv)
 
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Cardelli89',
@@ -298,7 +298,7 @@ def __init__(self, Rv):
         self.high_lim = max(wave)
 
         # other info
-        self.scale_lambda = 2.174 
+        self.scale_lambda = 2.174
         self.name = 'C89,{0}'.format(Rv)
 
     @staticmethod
@@ -317,7 +317,7 @@ def _derive_cardelli(wavelength, Rv):
         if (np.max(x) > 8.0):
             print( 'wavelength is shorter than applicable range for Cardelli law')
             return None
-        
+
         # Set up some arrays for coefficients that we will need
         a = np.zeros(len(x), dtype=float)
         b = np.zeros(len(x), dtype=float)
@@ -366,14 +366,14 @@ def _derive_cardelli(wavelength, Rv):
         k_ind = np.where(abs(x-0.46) == min(abs(x-0.46)))
         Aks_Av = a[k_ind] + b[k_ind]/Rv # Aks / Av
         Av_Aks = 1.0 / Aks_Av # Av / Aks
-        
+
         output = extinction * Av_Aks # (A(lamb) / Av) * (Av / Aks) = (A(lamb) / Aks)
 
         return output
 
     def Cardelli89(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -393,7 +393,7 @@ def Cardelli89(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -409,12 +409,12 @@ def Cardelli89(self, wavelength, AKs):
         A_at_wave = np.array(A_AKs_at_wave) * AKs
 
         return A_at_wave
-    
+
 class RedLawRomanZuniga07(pysynphot.reddening.CustomRedLaw):
     """
     Defines extinction law from `Roman-Zuniga et al. 2007
     <https://ui.adsabs.harvard.edu/abs/2007ApJ...664..357R/abstract>`_
-    for the dense cloud core Barnard 59. The law is a cubic spline fit 
+    for the dense cloud core Barnard 59. The law is a cubic spline fit
     to the values of A_lambda / A_Ks derived using the color-color
     diagrams slopes in their Table 1. It is defined between 1.0 - 8.0
     microns.
@@ -424,7 +424,7 @@ class RedLawRomanZuniga07(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Fetch the extinction curve, pre-interpolate across 1-8 microns
         wave = np.arange(1.0, 8.0, 0.01)
-        
+
         # This will eventually be scaled by AKs when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawRomanZuniga07._derive_romanzuniga07(wave)
@@ -432,7 +432,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10**4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='RomanZuniga07',
@@ -452,7 +452,7 @@ def _derive_romanzuniga07(wavelength):
         wave =      np.array([1.240, 1.664, 2.164, 3.545, 4.442, 5.675, 7.760])
         A_AKs =     np.array([2.299, 1.550, 1.000, 0.618, 0.525, 0.462, 0.455])
         A_AKs_err = np.array([0.530, 0.080, 0.000, 0.077, 0.063, 0.055, 0.059])
-        
+
         # Interpolate over the curve
         spline_interp = interpolate.splrep(wave, A_AKs, k=3, s=0)
         A_AKs_at_wave = interpolate.splev(wavelength, spline_interp)
@@ -460,8 +460,8 @@ def _derive_romanzuniga07(wavelength):
         return A_AKs_at_wave
 
     def RomanZuniga07(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -481,7 +481,7 @@ def RomanZuniga07(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -538,7 +538,7 @@ class RedLawRiekeLebofsky(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Define the wavelength range of the extinction law
         wave = np.arange(1.0, 5.0, 0.001)
-        
+
         # This will eventually be scaled by AKs when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawRiekeLebofsky._derive_RiekeLebofsky(wave)
@@ -546,7 +546,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='RiekeLebofsky',
@@ -569,17 +569,17 @@ def _derive_RiekeLebofsky(wavelength):
 
         Data pulled from Rieke+Lebofsky 1985, Table 3. Note that their
         Table contains values from 0.3 - 13 microns, but only 1 - 5 microns
-        is measured directly. 
+        is measured directly.
 
         Wavelengths for filters I - M are from Rieke+89, table 4.
         """
         # Arrays with the values from the paper
-        filters = ['U', 'B', 'V', 'R', 'I', 'J', 'H', 'K', 'L', 'M', 
-                   '[8.0]', '[8.5]', '[9.0]', '[9.5]', '[10.0]', '[10.5]', 
+        filters = ['U', 'B', 'V', 'R', 'I', 'J', 'H', 'K', 'L', 'M',
+                   '[8.0]', '[8.5]', '[9.0]', '[9.5]', '[10.0]', '[10.5]',
                    '[11.0]', '[11.5]', '[12.0]', '[12.5]', '[13.0]']
-        wave = np.array([0.365, 0.445, 0.551, 0.658, 0.9, 1.25, 1.60, 2.2, 
+        wave = np.array([0.365, 0.445, 0.551, 0.658, 0.9, 1.25, 1.60, 2.2,
                          3.50, 4.8, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0,
-                        11.5, 12.0, 12.5, 13.0])            
+                        11.5, 12.0, 12.5, 13.0])
         A_Av = np.array([1.531, 1.324, 1.00, 0.748, 0.482, 0.282, 0.175, 0.112,
                          0.058, 0.023, 0.02, 0.043, 0.074, 0.087, 0.083,
                          0.074, 0.060, 0.047, 0.037, 0.030, 0.027])
@@ -597,7 +597,7 @@ def _derive_RiekeLebofsky(wavelength):
         wave_interp = wave[idx1:idx2+1]
         A_Ak_interp = A_Ak[idx1:idx2+1]
         assert len(wave_interp) == 6
-        
+
         # Interpolate over the curve over desired wavelength range
         spline_interp = interpolate.splrep(wave_interp, A_Ak_interp, k=3, s=0)
         A_Ak_at_wave = interpolate.splev(wavelength, spline_interp)
@@ -605,8 +605,8 @@ def _derive_RiekeLebofsky(wavelength):
         return A_Ak_at_wave
 
     def RiekeLebofsky85(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -626,7 +626,7 @@ def RiekeLebofsky85(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -657,12 +657,12 @@ def plot_RiekeLebofsky85(self):
         # Get the observed values from their Table 3. Note only JHKLM is
         # measured directly by RL85, other values come from elsewhere.
         # Wavelengths are from Rieke+89, Table 4
-        filters = ['U', 'B', 'V', 'R', 'I', 'J', 'H', 'K', 'L', 'M', 
-                   '[8.0]', '[8.5]', '[9.0]', '[9.5]', '[10.0]', '[10.5]', 
+        filters = ['U', 'B', 'V', 'R', 'I', 'J', 'H', 'K', 'L', 'M',
+                   '[8.0]', '[8.5]', '[9.0]', '[9.5]', '[10.0]', '[10.5]',
                    '[11.0]', '[11.5]', '[12.0]', '[12.5]', '[13.0]']
-        wave_obs = np.array([0.365, 0.445, 0.551, 0.658, 0.9, 1.25, 1.60, 2.2, 
+        wave_obs = np.array([0.365, 0.445, 0.551, 0.658, 0.9, 1.25, 1.60, 2.2,
                          3.50, 4.8, 8.0, 8.5, 9.0, 9.5, 10.0, 10.5, 11.0,
-                        11.5, 12.0, 12.5, 13.0]) 
+                        11.5, 12.0, 12.5, 13.0])
         A_Av = np.array([1.531, 1.324, 1.00, 0.748, 0.482, 0.282, 0.175, 0.112,
                          0.058, 0.023, 0.02, 0.043, 0.074, 0.087, 0.083,
                          0.074, 0.060, 0.047, 0.037, 0.030, 0.027])
@@ -708,7 +708,7 @@ class RedLawDamineli16(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Fetch the extinction curve, pre-interpolate across 0.4-4.8 microns
         wave = np.arange(0.4, 4.8, 0.001)
-        
+
         # This will eventually be scaled by AKs when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawDamineli16._derive_Damineli16(wave)
@@ -716,7 +716,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Damineli16',
@@ -730,7 +730,7 @@ def __init__(self):
         self.name = 'D16'
 
         return
-    
+
     @staticmethod
     def _derive_Damineli16(wavelength):
         """
@@ -748,13 +748,13 @@ def _derive_Damineli16(wavelength):
         log_A_AKs = -0.015 + 2.33*x + 0.522*x**2. - 3.001*x**3. + 2.034*x**4.
 
         # Now to convert this back to linear space
-        A_AKs_at_wave = 10**log_A_AKs 
+        A_AKs_at_wave = 10**log_A_AKs
 
         return A_AKs_at_wave
 
     def Damineli16(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -774,7 +774,7 @@ def Damineli16(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -821,7 +821,7 @@ def plot_Damineli16(self):
         py.legend()
         py.savefig('damineli16_el.png')
         return
-    
+
 class RedLawDeMarchi16(pysynphot.reddening.CustomRedLaw):
     """
     Defines extinction law from `De Marchi et al. 2016
@@ -831,7 +831,7 @@ class RedLawDeMarchi16(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Fetch the extinction curve, pre-interpolate across 1-8 microns
         wave = np.arange(0.3, 8.0, 0.001)
-        
+
         # This will eventually be scaled by AK when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawDeMarchi16._derive_DeMarchi16(wave)
@@ -839,7 +839,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='DeMarchi16',
@@ -891,8 +891,8 @@ def _derive_DeMarchi16(wavelength):
         return A_AK_at_wave
 
     def DeMarchi16(self, wavelength, AK):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -912,7 +912,7 @@ def DeMarchi16(self, wavelength, AK):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -928,32 +928,32 @@ def DeMarchi16(self, wavelength, AK):
         A_at_wave = np.array(A_AKs_at_wave) * AK
 
         return A_at_wave
-    
+
 class RedLawFitzpatrick09(pysynphot.reddening.CustomRedLaw):
     """
-    Defines the extinction law from 
+    Defines the extinction law from
     `Fitzpatrick et al. 2009 <https://ui.adsabs.harvard.edu/abs/2009ApJ...699.1209F/abstract>`_.
     The law is defined between 0.5 -- 3 microns.
 
     The extinction law is as defined in their equation 5, and has two
     free parameters: :math:`\alpha` and R(V). Averaged over 14 sight-lines,
-    the authors generally find either :math:`alpha` ~ 2.5, R(V) ~ 3, or 
-    :math:`alpha` ~ 1.8, R(V) ~ 5 (their Figure 6). 
+    the authors generally find either :math:`alpha` ~ 2.5, R(V) ~ 3, or
+    :math:`alpha` ~ 1.8, R(V) ~ 5 (their Figure 6).
 
     A_lambda / A_K = 1 at lambda = 2.18
 
     Parameters
     ----------
     alpha : float
-         alpha parameter for extinction law. 
+         alpha parameter for extinction law.
 
     RV : float
-        R(V) parameter for extinction law. 
+        R(V) parameter for extinction law.
     """
     def __init__(self, alpha, RV):
         # Fetch the extinction curve, pre-interpolate across 1-8 microns
         wave = np.arange(0.5, 3.0, 0.001)
-        
+
         # This will eventually be scaled by AK when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawFitzpatrick09._derive_Fitzpatrick09(wave, alpha, RV)
@@ -961,7 +961,7 @@ def __init__(self, alpha, RV):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Fitzpatrick09',
@@ -995,14 +995,14 @@ def _derive_Fitzpatrick09(wavelength, alpha, RV):
         """
         alpha = float(alpha)
         RV = float(RV)
-        
+
         # First we'll calculate k(lambda - V) = E(lambda - V) / E(B - V),
         # directly from equation 5
         k = (0.349 + 2.087*RV) * (1.0 / (1.0 + (wavelength / 0.507)**alpha)) - RV
 
         # We'll calculate Alam/Av from K + Rv
-        Alam_Av = (k / RV) + 1. 
-        
+        Alam_Av = (k / RV) + 1.
+
         # Finally, to get A_lambda/Aks we need to divide Alam_Av by AKs_Av.
         # We'll assume a wavelength of 2.18 for Ks, since it is the wavelength
         # they report for K-band
@@ -1013,8 +1013,8 @@ def _derive_Fitzpatrick09(wavelength, alpha, RV):
         return A_AKs_at_wave
 
     def Fitzpatrick09(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -1034,7 +1034,7 @@ def Fitzpatrick09(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1053,7 +1053,7 @@ def Fitzpatrick09(self, wavelength, AKs):
 
 class RedLawSchlafly16(pysynphot.reddening.CustomRedLaw):
     """
-    Defines the extinction law from `Schlafly et al. 2016 
+    Defines the extinction law from `Schlafly et al. 2016
     <https://ui.adsabs.harvard.edu/abs/2016ApJ...821...78S/abstract>`_.
     The law is defined between 0.5 - 4.8 microns.
 
@@ -1069,7 +1069,7 @@ class RedLawSchlafly16(pysynphot.reddening.CustomRedLaw):
     def __init__(self, AH_AKs, x):
         # Fetch the extinction curve, pre-interpolate across 0.5-4.8 microns
         wave = np.arange(0.5, 4.8, 0.001)
-        
+
         # This will eventually be scaled by AK when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawSchlafly16._derive_Schlafly16(wave, AH_AKs, x)
@@ -1077,7 +1077,7 @@ def __init__(self, AH_AKs, x):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Schlafly16',
@@ -1091,7 +1091,7 @@ def __init__(self, AH_AKs, x):
     @staticmethod
     def _derive_Schlafly16(wavelength, AH_AKs, x):
         """
-        Calculate Schalfly+16 extinction law according to 
+        Calculate Schalfly+16 extinction law according to
         code provided in appendix of the paper. AH_AKs sets the
         gray component while x sets the shape of the law in an
         Rv-like way
@@ -1102,20 +1102,20 @@ def _derive_Schlafly16(wavelength, AH_AKs, x):
 
         # Evaluate function for desired wavelengths (in angstroms)
         law = law_func(wavelength*10**4)
-        
+
         # Now normalize to A_lambda/AKs, rather than A_lambda/A(5420)
         idx = np.where( abs(wavelength - 2.151) == min(abs(wavelength - 2.151)) )
         law_out = law / law[idx]
-        
+
         return law_out
 
     @staticmethod
     def _Schlafly_appendix(x, rhk):
-        """ 
+        """
         Schlafly+16 extinction law as defined in paper appendix. We've modified
-        the wrapper slightly so that the user has control of rhk and x. Here is 
+        the wrapper slightly so that the user has control of rhk and x. Here is
         the comments from that code:
-         
+
         Returns the extinction curve, A(lambda)/A(5420 A), according to
         Schlafly+2016, for the parameter "x," which controls the overall shape of
         the extinction curve in an R(V)-like way.  The extinction curve returned
@@ -1137,7 +1137,7 @@ def _Schlafly_appendix(x, rhk):
             lam: anchor wavelengths (angstroms), default to Schlafly+2016
 
         Returns: the extinction curve E, so the extinction alam = A(lam)/A(5420 A)
-        is given by: 
+        is given by:
             A = extcurve(x)
             alam = A(lam)
         """
@@ -1162,8 +1162,8 @@ def _Schlafly_appendix(x, rhk):
         return CubicSpline(lam, anchors/cs0(5420.), yp='3d=0')
 
     def Schlafly16(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -1183,7 +1183,7 @@ def Schlafly16(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1202,7 +1202,7 @@ def Schlafly16(self, wavelength, AKs):
 
 class RedLawIndebetouw05(pysynphot.reddening.CustomRedLaw):
     """
-    Defines the extinction law from `Indebetouw et al. 2005 
+    Defines the extinction law from `Indebetouw et al. 2005
     <https://ui.adsabs.harvard.edu/abs/2005ApJ...619..931I/abstract>`_.
     The law is defined between 1.25 - 8 microns using Equation 4
     in their paper.
@@ -1217,7 +1217,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Indebetouw05',
@@ -1244,8 +1244,8 @@ def _derive_Indebetouw05(wave):
         return Alambda_AK
 
     def Indebetouw05(self, wavelength, AK):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall extinction at AK (2.164 microns)
 
         Parameters
@@ -1265,7 +1265,7 @@ def Indebetouw05(self, wavelength, AK):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1284,7 +1284,7 @@ def Indebetouw05(self, wavelength, AK):
 
     def plot_Indebetouw05(self):
         """
-        Plot Indebetouw+05 extinciton curve versus their 
+        Plot Indebetouw+05 extinciton curve versus their
         actual measured values (their Table 1).
         This is similar to their Figure 6.
 
@@ -1296,13 +1296,13 @@ def plot_Indebetouw05(self):
 
         # Convert wave to microns for plot
         wave *= 10**-4
-        
+
         # Their average measurements across sight lines
         # from Table 1
         wave_arr = [1.240, 1.664, 2.164, 3.545, 4.442, 5.675, 7.760]
         law_obs_arr = [2.50, 1.55, 1.0, 0.56, 0.43, 0.43, 0.43]
         law_obs_err_arr = [0.15, 0.08, 0.0, 0.06, 0.08, 0.10, 0.10]
-        
+
         # Make plot
         py.figure(figsize=(10,10))
         py.plot(wave, law, 'r-', label='EL Function')
@@ -1317,14 +1317,14 @@ def plot_Indebetouw05(self):
         py.savefig('indebetouw05_el.png')
 
         return
-        
+
 class RedLawPowerLaw(pysynphot.reddening.CustomRedLaw):
     """
-    Extinction object that is a power-law extinction law: 
+    Extinction object that is a power-law extinction law:
     :math:`A_{\lambda} \propto \lambda^{\alpha}`.
 
-    For example, to create an extinction law between 
-    0.8 and 3 microns where :math:`\alpha = 2.21`, 
+    For example, to create an extinction law between
+    0.8 and 3 microns where :math:`\alpha = 2.21`,
     where :math:`A_{\lambda} / A_{Ks} = 1` at 2.12 microns:
 
     >>> from spisea import reddening
@@ -1349,7 +1349,7 @@ class RedLawPowerLaw(pysynphot.reddening.CustomRedLaw):
     def __init__(self, alpha, K_wave, wave_min=0.5, wave_max=5.0):
         # Fetch the extinction curve, pre-interpolate across wave_min to wave_max
         wave = np.arange(wave_min, wave_max, 0.001)
-        
+
         # This will eventually be scaled by AK when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawPowerLaw._derive_powerlaw(wave, alpha, K_wave)
@@ -1357,7 +1357,7 @@ def __init__(self, alpha, K_wave, wave_min=0.5, wave_max=5.0):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Power law')
@@ -1379,8 +1379,8 @@ def _derive_powerlaw(wavelength, alpha, K_wave):
             in microns
 
         alpha: float
-            -1.0 * (power law exponent) 
-             
+            -1.0 * (power law exponent)
+
         K_wave: float
             Desired K-band wavelength, in microns
         """
@@ -1394,8 +1394,8 @@ def _derive_powerlaw(wavelength, alpha, K_wave):
         return A_AKs_at_wave
 
     def powerlaw(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -1415,7 +1415,7 @@ def powerlaw(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1434,22 +1434,22 @@ def powerlaw(self, wavelength, AKs):
 
 class RedLawBrokenPowerLaw(pysynphot.reddening.CustomRedLaw):
     """
-    Extinction object that is a broken power-law extinction law: 
+    Extinction object that is a broken power-law extinction law:
     :math:`A_{\lambda} \propto \lambda^{\alpha[n]}`
 
-    for: 
+    for:
     :math: `\lambda_{limits}[n] < \lambda <= \lambda_{limits}[n+1]`
 
-    Note: lambda_limits must be continuous in wavelength and K_wave must be 
-    within one of the section defined by the lambda_limits array. 
+    Note: lambda_limits must be continuous in wavelength and K_wave must be
+    within one of the section defined by the lambda_limits array.
     Extinction law is only defined over lambda_limits
-    
+
     Units of lambda_limits array is microns.
 
     Parameters
     ----------
     lambda_limits : numpy array
-        Array of length (N + 1) with lower and upper wavelength limits of 
+        Array of length (N + 1) with lower and upper wavelength limits of
         the power-law segments. Units are microns.
 
     alpha_vals : numpy array
@@ -1480,7 +1480,7 @@ def __init__(self, lambda_limits, alpha_vals, K_wave):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Broken Power law')
@@ -1502,8 +1502,8 @@ def _derive_broken_powerlaw(wave, lambda_limits, alpha_vals, K_wave):
             in microns
 
         alpha: float
-            -1.0 * (power law exponent) 
-             
+            -1.0 * (power law exponent)
+
         K_wave: float
             Desired K-band wavelength, in microns
         """
@@ -1529,14 +1529,14 @@ def _derive_broken_powerlaw(wave, lambda_limits, alpha_vals, K_wave):
                     #print('wave_connect = {0}'.format(wave_connect))
                     #print('alph_num = {0}'.format(alpha_vals[jj]))
                     #print('alpha_den = {0}'.format(alpha_vals[jj+1]))
-        
+
                     coeff *= val
-                    
+
             law[idx] = coeff * (wave[idx]**(-1.0 * alpha))
 
         # Let's make sure we didn't miss updating any parts of the law
         assert np.sum(np.isnan(law)) == 0
-        
+
         # We'll identify K-band as 2.14 microns
         idx = np.where(abs(wave - K_wave) == min(abs(wave - K_wave)))
         A_AKs_at_wave = law / law[idx]
@@ -1544,8 +1544,8 @@ def _derive_broken_powerlaw(wave, lambda_limits, alpha_vals, K_wave):
         return A_AKs_at_wave
 
     def broken_powerlaw(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -1565,7 +1565,7 @@ def broken_powerlaw(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1584,7 +1584,7 @@ def broken_powerlaw(self, wavelength, AKs):
 
 class RedLawFritz11(pysynphot.reddening.CustomRedLaw):
     """
-    Defines extinction law from `Fritz et al. 2011 
+    Defines extinction law from `Fritz et al. 2011
     <https://ui.adsabs.harvard.edu/abs/2011ApJ...737...73F/abstract>`_
     for the Galactic Center. The law is defined from 1.0 -- 26 microns.
 
@@ -1613,12 +1613,12 @@ def __init__(self, scale_lambda=2.166):
         ext_scale = ext / ext[idx]
 
         # Make custom reddening law
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=ext_scale,
                                                   name='Fritz11',
                                                   litref='Fritz+2011')
-        
+
         # Set the upper/lower wavelength limits of law (in angstroms)
         self.low_lim = min(wave)
         self.high_lim = max(wave)
@@ -1628,13 +1628,13 @@ def __init__(self, scale_lambda=2.166):
         self.name = 'F11'
 
         return
-    
+
     @staticmethod
     def _read_Fritz11():
         """
-        Return the interpolated extinction curve from Fritz+11, 
-        as defined in their Table 8. 
-        
+        Return the interpolated extinction curve from Fritz+11,
+        as defined in their Table 8.
+
         Output:
         ------
         wave: array
@@ -1649,7 +1649,7 @@ def _read_Fritz11():
         # Read in file with Table 8 info (published with Fritz+11 paper)
         inpath = os.path.dirname(os.path.abspath(__file__))
         infile = os.path.join(inpath, 'el_files', 'fritz11_EL_table8.fits')
-        
+
         t = Table.read(infile, format='fits')
         wave = t['lambda']
         ext = t['A']
@@ -1661,7 +1661,7 @@ def _read_Fritz11():
     def _read_Fritz11_obs():
         """
         Return the Fritz+11 observed values, from their Table 2
-        
+
         Output:
         -------
         wave: array
@@ -1703,7 +1703,7 @@ def plot_Fritz11(self):
         # extinction at 2.166 microns. Remember that this produces
         # throughput = 10^-0.4*Alambda
         ext_scaled = self.reddening(2.62)
-        
+
         # Make plot
         py.figure(figsize=(10,10))
         py.plot(wave, ext, 'r-', label='Interpolated EL')
@@ -1723,8 +1723,8 @@ def plot_Fritz11(self):
         return
 
     def Fritz11(self, wavelength, A_scale_lambda):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and a total extinction at the scale_lambda
         (the wavelength where the extinction law = 1)
 
@@ -1745,7 +1745,7 @@ def Fritz11(self, wavelength, A_scale_lambda):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/A_scale_lambda from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1768,18 +1768,18 @@ def Fritz11(self, wavelength, A_scale_lambda):
 #==============================================#
 #class RedLawHosek18(pysynphot.reddening.CustomRedLaw):
 #    """
-#    Defines extinction law from `Hosek et al. 2018 
+#    Defines extinction law from `Hosek et al. 2018
 #    <https://ui.adsabs.harvard.edu/abs/2018ApJ...855...13H/abstract>`_
-#    for the Arches Cluster and Wd1. The law is defined between 
+#    for the Arches Cluster and Wd1. The law is defined between
 #    0.7 - 3.54 microns.
 #
-#    WARNING: DEPRECATED! This law has revised to RedLawHosek18b, which 
+#    WARNING: DEPRECATED! This law has revised to RedLawHosek18b, which
 #    should be used instead
 #    """
 #    def __init__(self):
 #        # Fetch the extinction curve, pre-interpolate across 3-8 microns
 #        wave = np.arange(0.7, 3.545, 0.001)
-#        
+#
 #        # This will eventually be scaled by AKs when you
 #        # call reddening(). Right now, calc for AKs=1
 #        Alambda_scaled = RedLawHosek18._derive_Hosek18(wave)
@@ -1787,7 +1787,7 @@ def Fritz11(self, wavelength, A_scale_lambda):
 #        # Convert wavelength to angstrom
 #        wave *= 10 ** 4
 #
-#        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+#        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
 #                                                  waveunits='angstrom',
 #                                                  Avscaled=Alambda_scaled,
 #                                                  name='Hosek+18',
@@ -1797,12 +1797,12 @@ def Fritz11(self, wavelength, A_scale_lambda):
 #        self.low_lim = min(wave)
 #        self.high_lim = max(wave)
 #        self.name = 'H18'
-#        
+#
 #    @staticmethod
 #    def _derive_Hosek18(wavelength):
-#        """ 
-#        Derive the Hosek+18 extinction law, using the data from Table 4. 
-#        
+#        """
+#        Derive the Hosek+18 extinction law, using the data from Table 4.
+#
 #        Calculate the resulting extinction for an array of wavelengths.
 #        The extinction is normalized with A_Ks.
 #
@@ -1816,19 +1816,19 @@ def Fritz11(self, wavelength, A_scale_lambda):
 #        # Extinction law definition
 #        wave = np.array([0.8059, 0.962, 1.25, 1.53, 2.14, 3.545])
 #        A_AKs = np.array([9.66, 6.29, 3.56, 2.33, 1.0, 0.50])
-#        
+#
 #
 #        # Following Hosek+18, Interpolate over the curve with cubic spline interpolation
 #        spline_interp = interpolate.splrep(wave, A_AKs, k=3, s=0)
 #        A_AKs_at_wave = interpolate.splev(wavelength, spline_interp)
 #
 #        # This curve already assumes A_Ks = 1.0, so we can go straight to
-#        # output        
+#        # output
 #        return A_AKs_at_wave
 #
 #    def Hosek18(self, wavelength, AKs):
-#        """ 
-#        Return the extinction at a given wavelength assuming the 
+#        """
+#        Return the extinction at a given wavelength assuming the
 #        extinction law and an overall `AKs` value.
 #
 #        Parameters
@@ -1848,7 +1848,7 @@ def Fritz11(self, wavelength, A_scale_lambda):
 #        # extinction law
 #        if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
 #            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-#            
+#
 #        # Extract wave and A/AKs from law, turning wave into micron units
 #        wave = self.wave * (10**-4)
 #        law = self.obscuration
@@ -1868,7 +1868,7 @@ def Fritz11(self, wavelength, A_scale_lambda):
 
 class RedLawHosek18b(pysynphot.reddening.CustomRedLaw):
     """
-    Defines extinction law from `Hosek et al. 2019 
+    Defines extinction law from `Hosek et al. 2019
     <https://ui.adsabs.harvard.edu/abs/2019ApJ...870...44H/abstract>`_
     for the Arches cluster and Wd1.
     The law is derived between 0.7 - 3.54 microns
@@ -1876,7 +1876,7 @@ class RedLawHosek18b(pysynphot.reddening.CustomRedLaw):
     def __init__(self):
         # Fetch the extinction curve, pre-interpolate across 3-8 microns
         wave = np.arange(0.7, 3.545, 0.001)
-        
+
         # This will eventually be scaled by AKs when you
         # call reddening(). Right now, calc for AKs=1
         Alambda_scaled = RedLawHosek18b._derive_Hosek18b(wave)
@@ -1884,7 +1884,7 @@ def __init__(self):
         # Convert wavelength to angstrom
         wave *= 10 ** 4
 
-        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave, 
+        pysynphot.reddening.CustomRedLaw.__init__(self, wave=wave,
                                                   waveunits='angstrom',
                                                   Avscaled=Alambda_scaled,
                                                   name='Hosek+18b',
@@ -1894,12 +1894,12 @@ def __init__(self):
         self.low_lim = min(wave)
         self.high_lim = max(wave)
         self.name = 'H18b'
-        
+
     @staticmethod
     def _derive_Hosek18b(wavelength):
-        """ 
-        Derive the Hosek+18 extinction law, using the data from Table 4. 
-        
+        """
+        Derive the Hosek+18 extinction law, using the data from Table 4.
+
         Calculate the resulting extinction for an array of wavelengths.
         The extinction is normalized with A_Ks.
 
@@ -1913,18 +1913,18 @@ def _derive_Hosek18b(wavelength):
         # Extinction law definition
         wave = np.array([0.8059, 0.962, 1.25, 1.53, 2.14, 3.545])
         A_AKs = np.array([7.943, 5.715, 3.142, 2.04, 1.0, 0.50])
-        
+
         # Following Hosek+18, Interpolate over the curve with cubic spline interpolation
         spline_interp = interpolate.splrep(wave, A_AKs, k=3, s=0)
         A_AKs_at_wave = interpolate.splev(wavelength, spline_interp)
 
         # This curve already assumes A_Ks = 1.0, so we can go straight to
-        # output        
+        # output
         return A_AKs_at_wave
 
     def Hosek18b(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -1944,7 +1944,7 @@ def Hosek18b(self, wavelength, AKs):
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
             return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
-            
+
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
         law = self.obscuration
@@ -1967,15 +1967,15 @@ class RedLawSchoedel10(RedLawBrokenPowerLaw):
     <https://ui.adsabs.harvard.edu/abs/2010A%26A...511A..18S/abstract>`_
     for the Galactic Center. It is defined between 1.5 - 3.8 microns.
 
-    Power law indices: 
+    Power law indices:
 
     * 1.677 - 2.168 microns ---> alpha = 2.21 +/- 0.24
     * 2.168 - 3.636 microns ---> alpha = 1.34 +/- 0.29
 
-    Wavelengths come from effective wavelengths of observations (some buffer 
+    Wavelengths come from effective wavelengths of observations (some buffer
     is added to either side of these values).
-    
-    Reddening law is scaled such that A_lambda / A_Ks = 1 at 
+
+    Reddening law is scaled such that A_lambda / A_Ks = 1 at
     lambda = 2.168 microns.
     """
     def __init__(self):
@@ -1983,7 +1983,7 @@ def __init__(self):
         alpha_vals = [1.34, 2.21]
         K_wave = 2.168
         RedLawBrokenPowerLaw.__init__(self, lambda_limits, alpha_vals, K_wave)
-        
+
         # Set the upper/lower wavelength limits of law (in angstroms)
         self.low_lim = np.min(lambda_limits)*10**4
         self.high_lim = np.max(lambda_limits)*10**4
@@ -1995,8 +1995,8 @@ def __init__(self):
         return
 
     def Schoedel10(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and a total extinction at scale_lambda
         (the wavelength where the extinction law = 1)
 
@@ -2016,7 +2016,7 @@ def Schoedel10(self, wavelength, AKs):
         # Return error if any wavelength is beyond interpolation range of
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
-            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))    
+            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
 
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
@@ -2032,21 +2032,21 @@ def Schoedel10(self, wavelength, AKs):
         # Now multiply by AKs (since law assumes AKs = 1)
         A_at_wave = np.array(A_AKs_at_wave) * AKs
 
-        return A_at_wave  
+        return A_at_wave
+
 
-    
 class RedLawNoguerasLara18(RedLawPowerLaw):
     """
-    Defines extinction law from `Nogueras-Lara et al. 2018 
+    Defines extinction law from `Nogueras-Lara et al. 2018
     <https://ui.adsabs.harvard.edu/abs/2018A%26A...610A..83N/abstract>`_
     for the Galactic Center.  It is defined between 1.0 - 3.0 microns.
-    Measurements were made in JHK, with effective wavelengths 
+    Measurements were made in JHK, with effective wavelengths
     of 1.2685, 1.6506, and 2.1629 microns, respectively.
 
-    This extinction law is a single power law with exponent 
+    This extinction law is a single power law with exponent
     of alpha = 2.3 +/- 0.08.
 
-    Reddening law is scaled such that A_lambda / A_Ks = 1 at 
+    Reddening law is scaled such that A_lambda / A_Ks = 1 at
     lambda = 2.163 microns (the observed K-band)
     """
     def __init__(self):
@@ -2054,7 +2054,7 @@ def __init__(self):
         wave_max = 3.0
         K_wave = 2.163
         RedLawPowerLaw.__init__(self, 2.30, K_wave, wave_min=wave_min, wave_max=wave_max)
-        
+
         # Set the upper/lower wavelength limits of law (in angstroms)
         self.low_lim = wave_min*10**4
         self.high_lim = wave_max*10**4
@@ -2063,8 +2063,8 @@ def __init__(self):
         self.name = 'NL18'
 
     def NoguerasLara18(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and an overall `AKs` value.
 
         Parameters
@@ -2083,7 +2083,7 @@ def NoguerasLara18(self, wavelength, AKs):
         # Return error if any wavelength is beyond interpolation range of
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
-            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))    
+            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
 
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
@@ -2106,18 +2106,18 @@ class RedLawNoguerasLara20(RedLawBrokenPowerLaw):
     Defines extinction law from `Nogueras-Lara et al. 2020
     <https://ui.adsabs.harvard.edu/abs/2020A%26A...641A.141N/abstract>`_
     for the Galactic Center. It is defined between 1.0 -- 3 microns.
-    Measurements were made in JHK, with effective wavelengths 
+    Measurements were made in JHK, with effective wavelengths
     of 1.2685, 1.6506, and 2.1629 microns, respectively
 
-    Measured power law indices: 
- 
+    Measured power law indices:
+
     * 1.2685 - 1.6505 microns ---> alpha = 2.44 +/- 0.05
     * 1.6505 - 2.1629 microns ---> alpha = 2.23 +/- 0.05
 
-    Wavelengths come from effective wavelengths of observations (some buffer 
+    Wavelengths come from effective wavelengths of observations (some buffer
     is added to either side of these values).
-    
-    Reddening law is scaled such that A_lambda / A_Ks = 1 at 
+
+    Reddening law is scaled such that A_lambda / A_Ks = 1 at
     lambda = 2.163 microns (the observed K-band)
     """
     def __init__(self):
@@ -2125,7 +2125,7 @@ def __init__(self):
         alpha_vals = [2.44, 2.23]
         K_wave = 2.163
         RedLawBrokenPowerLaw.__init__(self, lambda_limits, alpha_vals, K_wave)
-        
+
         # Set the upper/lower wavelength limits of law (in angstroms)
         self.low_lim = np.min(lambda_limits)*10**4
         self.high_lim = np.max(lambda_limits)*10**4
@@ -2137,8 +2137,8 @@ def __init__(self):
         return
 
     def NoguerasLara20(self, wavelength, AKs):
-        """ 
-        Return the extinction at a given wavelength assuming the 
+        """
+        Return the extinction at a given wavelength assuming the
         extinction law and a total extinction at scale_lambda
         (the wavelength where the extinction law = 1)
 
@@ -2158,7 +2158,7 @@ def NoguerasLara20(self, wavelength, AKs):
         # Return error if any wavelength is beyond interpolation range of
         # extinction law
         if ((min(wavelength) < (self.low_lim*10**-4)) | (max(wavelength) > (self.high_lim*10**-4))):
-            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))    
+            return ValueError('{0}: wavelength values beyond interpolation range'.format(self))
 
         # Extract wave and A/AKs from law, turning wave into micron units
         wave = self.wave * (10**-4)
@@ -2174,7 +2174,7 @@ def NoguerasLara20(self, wavelength, AKs):
         # Now multiply by AKs (since law assumes AKs = 1)
         A_at_wave = np.array(A_AKs_at_wave) * AKs
 
-        return A_at_wave  
+        return A_at_wave
 
 #---------------------------#
 # Cubic spline function from Schalfly+16 appendix
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 932198bf..69b61d2e 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -139,8 +139,8 @@ class ResolvedCluster(Cluster):
         no compact remnants are produced.
 
     keep_low_mass_stars: boolean (default False)
-        If True, the cluster will not cut out stars below the isochrone grid 
-        on initial mass. They are assigned a current mass equal to their initial 
+        If True, the cluster will not cut out stars below the isochrone grid
+        on initial mass. They are assigned a current mass equal to their initial
         mass, a phase of 98, and no other evolutionary properties or photometry.
         If False, stars below the isochrone initial mass limit are cut out.
 
@@ -160,7 +160,7 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         if seed is not None and verbose:
             print('WARNING: random seed set to %i' % seed)
             # imf.rng = self.rng
-        
+
         #####
         # Sample the IMF to build up our cluster mass.
         #####
@@ -573,7 +573,7 @@ def _make_companions_table(self, star_systems, compMass):
 
         return star_systems, companions
 
-    
+
     def _remove_bad_systems(self, star_systems, compMass, keep_low_mass_stars):
         """
         Helper function to remove stars with masses outside the isochrone
@@ -607,7 +607,7 @@ def _remove_bad_systems(self, star_systems, compMass, keep_low_mass_stars):
             idx =   (star_systems_teff_non_nan > 0) | \
                     (star_systems_phase_non_nan >= 0) | \
                     (star_systems['mass'] < np.min(self.iso.points['mass']))
-        
+
         n_out_of_range = N_systems - sum(idx)
         if self.verbose and n_out_of_range > 0:
             print( 'Found {0:d} stars out of mass range'.format(n_out_of_range))
@@ -978,7 +978,7 @@ def __init__(self, logAge, AKs, distance, metallicity=0.0,
         tab.meta['WAVEMAX'] = wave_range[1]
 
         self.points = tab
-        
+
         if self.verbose:
             t2 = time.time()
             print( 'Isochrone generation took {0:f} s.'.format(t2-t1))
@@ -1131,13 +1131,13 @@ def __init__(self, logAge, AKs, distance,
         # For solar metallicity case, allow for legacy isochrones (which didn't have
         # metallicity tag since they were all solar metallicity) to be read
         # properly
-        
+
         # Set save file name
         metal_value = round(abs(metallicity), 2)
         metal_sign = 'm' if metallicity < 0 else 'p'
         self.save_file = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value:.2f}.fits'
 
-        if metallicity == 0.0:            
+        if metallicity == 0.0:
             self.save_file_legacy = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
         else:
             self.save_file_legacy = self.save_file
@@ -1216,9 +1216,9 @@ def __init__(self, logAge, AKs, distance,
                 # Convert into flux observed at Earth (unreddened)
                 star *= (R / self.points.meta["DISTANCE"])**2  # in erg s^-1 cm^-2 A^-1
                 # Redden the spectrum. This doesn't take much time at all.
-                red = red_law.reddening(AKs).resample(star.wave) 
+                red = red_law.reddening(AKs).resample(star.wave)
                 star *= red
-                # Save the final spectrum to our spec_list for later use.            
+                # Save the final spectrum to our spec_list for later use.
                 self.spec_list.append(star)
 
             self.make_photometry(rebin=rebin, vega=vega, comp_filters=comp_filters)
@@ -1226,7 +1226,7 @@ def __init__(self, logAge, AKs, distance,
         return
 
     def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
-        """ 
+        """
         Make synthetic photometry for the specified filters. This function
         udpates the self.points table to include new columns with the
         photometry.
@@ -1700,7 +1700,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('euclid'):
         filt = filters.get_euclid_filt(filterName)
-        
+
     else:
         # Otherwise, look for the filter info in the cdbs/mtab and cdbs/comp files
         try:
diff --git a/spisea/tests/test_exceptions.py b/spisea/tests/test_exceptions.py
index 4fe73e5f..b20a132d 100644
--- a/spisea/tests/test_exceptions.py
+++ b/spisea/tests/test_exceptions.py
@@ -32,6 +32,6 @@ def test_grid_number_exception():
     # Case 3: installed model grid is higher than required grid (no error)
     required_grid = installed_grid - 1.0
 
-    evolution.check_evo_grid_number(required_grid, models_dir)    
+    evolution.check_evo_grid_number(required_grid, models_dir)
 
     return
\ No newline at end of file
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index 2fd66f22..1225d682 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -5,17 +5,17 @@
 
 def test_evo_model_grid_num():
     """
-    Make sure evolution models have both evo_grid_num 
+    Make sure evolution models have both evo_grid_num
     and evo_grid_min (e.g., make sure these functions
     are working). Try it on one evolution model here;
     we'll test on all evo models in another function.
     """
     from spisea import evolution
-    
+
     # Make MIST evolution model, check evo grid variables
     evo = evolution.MISTv1()
     assert isinstance(evo.evo_grid_min, float)
-    
+
     return
 
 def test_evolution_models():
@@ -32,7 +32,7 @@ def test_evolution_models():
     metal_solar = [0]
 
     # Array of evolution models to test
-    evo_models = [evolution.MISTv1(version=1.2), evolution.MergedBaraffePisaEkstromParsec(), 
+    evo_models = [evolution.MISTv1(version=1.2), evolution.MergedBaraffePisaEkstromParsec(),
                       evolution.Parsec(), evolution.Baraffe15(), evolution.Ekstrom12(), evolution.Pisa()]
 
 
@@ -68,12 +68,12 @@ def test_evolution_models():
                     raise Exception('EVO TEST FAILED: {0}, age = {1}, metal = {2}'.format(evo, kk, jj))
 
         print('Done {0}'.format(evo))
-        
+
     return
 
 def test_synthpop_MIST_extension():
     """
-    Testing the synthpop MIST extension to consistently lower masses 
+    Testing the synthpop MIST extension to consistently lower masses
     """
     evo1_grid = evolution.MISTv1(version=1.2, synthpop_extension=False)
     evo2_grid = evolution.MISTv1(version=1.2, synthpop_extension=True)
@@ -116,9 +116,9 @@ def test_atmosphere_models():
                 test = atm_func(metallicity=jj)
             except:
                 raise Exception('ATM TEST FAILED: {0}, metal = {1}'.format(atm_func, jj))
-                
+
         print('Done {0}'.format(atm_func))
-        
+
     # Test get_merged_atmospheres at different temps
     temp_range = [2000, 3500, 4000, 5250, 6000, 12000]
     atm_func = atm.get_merged_atmosphere
@@ -131,7 +131,7 @@ def test_atmosphere_models():
 
 
     print('get_merged_atmosphere: all temps/metallicities passed')
-    
+
     # Test get_bb_atmosphere at different temps
     # This func only requests temp
     temp_range = [2000, 3500, 4000, 5250, 6000, 12000]
@@ -141,9 +141,9 @@ def test_atmosphere_models():
             test = atm_func(temperature=jj, verbose=True)
         except:
             raise Exception('ATM TEST FAILED: {0}, temp = {2}'.format(atm_func, jj))
-    
+
     print('get_bb_atmosphere: all temps passed')
-    
+
     return
 
 def test_filters():
@@ -154,7 +154,7 @@ def test_filters():
 
     # Define vega spectrum
     vega = synthetic.Vega()
-    
+
     # Filter list to test
     filt_list = ['wfc3,ir,f127m','acs,wfc1,f814w',
                      '2mass,J', '2mass,H','2mass,Ks',
@@ -193,7 +193,7 @@ def test_filters():
         filt = synthetic.get_filter_info(ii, rebin=True, vega=vega)
 
     print('get_filter_info pass')
-    
+
     # Loop through filters to test that they work: get_obs_str
     for ii in filt_list:
         # Test going from col_name to obs_str
diff --git a/spisea/tests/test_reddening.py b/spisea/tests/test_reddening.py
index 2df86a9a..99bbf78b 100644
--- a/spisea/tests/test_reddening.py
+++ b/spisea/tests/test_reddening.py
@@ -39,7 +39,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
 
     # Compare law_test and the output from the redlaw object
     law_output = red_law.broken_powerlaw(wave_test, 1)
-    
+
     assert len(law_test) == len(law_output)
     assert np.sum(np.isnan(law_output)) == 0
 
@@ -62,7 +62,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
     idx2 = np.where(abs(wave_test-2.1) == np.min(abs(wave_test-2.1)))
     slope = (log_output[idx1] - log_output[idx2]) / (log_wave[idx1] - log_wave[idx2])
     assert abs(slope - (-1.0 * alpha1)) < 10**-4
-    
+
     # If desired (debug only), make plot to see what law looks like
     if plots:
         # Test plot: these should match nearly exactly
@@ -109,7 +109,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
     idx = np.where( (wave_test >= 1.27) & (wave_test < 1.63))
     coeff  = (1.63 ** (-1*alpha1)) / (1.63 ** (-1*alpha2))
     law_test[idx] = coeff * wave_test[idx] ** (-1*alpha2)
-    
+
     # 1.27 - 0.8
     idx = np.where( (wave_test >= 0.8) & (wave_test < 1.27))
     coeff1 = (1.63 ** (-1*alpha1)) / (1.63 ** (-1*alpha2))
@@ -124,7 +124,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
     coeff3 = (0.8 ** (-1*alpha3)) / (0.8 ** (-1*alpha4))
     coeff_f = coeff1 * coeff2 * coeff3
     law_test[idx] = coeff_f * wave_test[idx] ** (-1*alpha4)
-    
+
     assert np.sum(np.isnan(law_test)) == 0
 
     # Put in terms of A_lambda / A_Ks, like the reddening object
@@ -133,7 +133,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
 
     # Compare law_test and the output from the redlaw object
     law_output = red_law.broken_powerlaw(wave_test, 1)
-    
+
     assert len(law_test) == len(law_output)
     assert np.sum(np.isnan(law_output)) == 0
 
@@ -166,7 +166,7 @@ def test_RedLawBrokenPowerLaw(plots=False):
     idx2 = np.where(abs(wave_test-0.7) == np.min(abs(wave_test-0.7)))
     slope = (log_output[idx1] - log_output[idx2]) / (log_wave[idx1] - log_wave[idx2])
     assert abs(slope - (-1.0 * alpha4)) < 10**-4
-    
+
     # If desired (debug only), make plot to see what law looks like
     if plots:
         # Test plot: these should match nearly exactly
@@ -195,9 +195,9 @@ def test_red_law_IsochronePhot():
     metallicity = 0 # Metallicity in [M/H]
 
     # Define evolution/atmosphere models and extinction law
-    evo_model = evolution.MISTv1() 
+    evo_model = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
-    
+
     # Also specify filters for synthetic photometry.
     filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f153m', 'nirc2,H', 'nirc2,Kp']
 
@@ -206,7 +206,7 @@ def test_red_law_IsochronePhot():
                       'RL85', 'D16', 'F09,2.5,3', 'S16,1.55,0', 'DM16',
                       'H18b', 'NL18', 'C89,3.1', 'pl,2.12,0.9,2.4',
                       'broken_pl,[2.3,1.63,0.9],[2.23, 3.0],2.12']
-        
+
     aks_arr = [2.62, 2.46, 1.67, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3, 2.3]
     for ii in range(len(redlaw_arr)):
         redlaw = reddening.get_red_law(redlaw_arr[ii])
@@ -215,15 +215,15 @@ def test_red_law_IsochronePhot():
 
         # Try to run isochrone phot
         iso_test = synthetic.IsochronePhot(
-            logAge, 
-            aks, 
-            dist, 
+            logAge,
+            aks,
+            dist,
             metallicity=0,
-            evo_model=evo_model, 
+            evo_model=evo_model,
             atm_func=atm_func,
-            red_law=redlaw, 
+            red_law=redlaw,
             filters=filt_list,
-            min_mass=0.95, 
+            min_mass=0.95,
             max_mass=1.05,
             iso_dir='isochrones/',
             recomp=True
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 349667c9..80284505 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -30,11 +30,11 @@ def test_isochrone(plot=False):
     assert iso.points.meta['AKS'] == AKs
     assert iso.points.meta['DISTANCE'] == distance
     assert len(iso.points) > 100
-    
+
     if plot:
-        plt.figure(1) 
+        plt.figure(1)
         iso.plot_HR_diagram()
-        
+
         plt.figure(2)
         iso.plot_mass_luminosity()
 
@@ -42,7 +42,7 @@ def test_isochrone(plot=False):
 
 def test_iso_wave():
     """
-    Test to make sure isochrones generated have spectra with the proper 
+    Test to make sure isochrones generated have spectra with the proper
     wavelength range, and that the user has control over that wavelength
     range (propagated through IsochronePhot)
     """
@@ -53,11 +53,11 @@ def test_iso_wave():
     iso_dir = f'{spisea_path}/tests/isochrones'
 
     # Define evolution/atmosphere models and extinction law (optional)
-    evo_model = evolution.MergedBaraffePisaEkstromParsec() 
+    evo_model = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawHosek18b()
 
-    # Also specify filters for synthetic photometry (optional). Here we use 
+    # Also specify filters for synthetic photometry (optional). Here we use
     # the HST WFC3-IR F127M, F139M, and F153M filters
     filt_list = ['wfc3,ir,f127m']
 
@@ -72,13 +72,13 @@ def test_iso_wave():
     wave_range1 = [3000, 52000]
     my_iso = syn.IsochronePhot(
         logAge, AKs, dist,
-        evo_model=evo_model, 
+        evo_model=evo_model,
         atm_func=atm_func,
-        red_law=red_law, 
+        red_law=red_law,
         filters=filt_list,
-        mass_sampling=10, 
+        mass_sampling=10,
         wave_range=wave_range1,
-        recomp=True, 
+        recomp=True,
         iso_dir=iso_dir
     )
 
@@ -91,14 +91,14 @@ def test_iso_wave():
     # properly?
     wave_range2 = [1200, 90000]
     my_iso = syn.IsochronePhot(
-        logAge, 
-        AKs, 
+        logAge,
+        AKs,
         dist,
-        evo_model=evo_model, 
+        evo_model=evo_model,
         atm_func=atm_func,
-        red_law=red_law, 
+        red_law=red_law,
         filters=filt_list,
-        mass_sampling=10, 
+        mass_sampling=10,
         wave_range=wave_range2,
         recomp=True,
         iso_dir=iso_dir
@@ -113,8 +113,8 @@ def test_iso_wave():
     wave_range3 = [1200, 1000000]
     try:
         my_iso = syn.IsochronePhot(
-            logAge, 
-            AKs, 
+            logAge,
+            AKs,
             dist,
             evo_model=evo_model,
             atm_func=atm_func,
@@ -122,11 +122,11 @@ def test_iso_wave():
             filters=filt_list,
             mass_sampling=10,
             wave_range=wave_range3,
-            recomp=True, 
+            recomp=True,
             iso_dir=iso_dir
         )
         print('WAVE TEST FAILED!!! Should have crashed here, wavelength range out of bounds')
-        raise ValueError() 
+        raise ValueError()
     except:
         print('Wavelength out of bound condition passed. Test is good')
         pass
@@ -146,9 +146,9 @@ def test_IsochronePhot(plot=False):
 
     startTime = time.time()
     iso = syn.IsochronePhot(
-        logAge, 
+        logAge,
         AKs,
-        distance, 
+        distance,
         evo_model=evo_model,
         atm_func=atm_func,
         red_law=redlaw,
@@ -169,9 +169,9 @@ def test_IsochronePhot(plot=False):
     assert 'm_nirc2_J' in iso.points.colnames
 
     if plot:
-        plt.figure(1) 
+        plt.figure(1)
         iso.plot_CMD('mag814w', 'mag160w')
-        
+
         plt.figure(2)
         iso.plot_mass_magnitude('mag160w')
 
@@ -195,16 +195,16 @@ def test_IsochronePhot(plot=False):
     )
 
     assert iso_new.recalc == False
-    
+
     # Check 2: Confirm that adding a new column to an existing isochrone works properly.
     #    Does the new filter get added to the isochrone? And the old ones still there?
     #    Does the computed data for the new filter match the same result if you fully regenerate the isochrone?
     iso_new_addfilt = syn.IsochronePhot(
         logAge,
         AKs,
-        distance, 
+        distance,
         evo_model=evo_model,
-        atm_func=atm_func, 
+        atm_func=atm_func,
         red_law=redlaw,
         filters=filt_list+['2mass,Ks'],
         mass_sampling=mass_sampling,
@@ -214,11 +214,11 @@ def test_IsochronePhot(plot=False):
     assert iso_new_addfilt.recalc == False
     assert 'm_2mass_Ks' in iso_new_addfilt.points.colnames
     assert 'm_nirc2_J' in iso_new_addfilt.points.colnames
-    
+
     iso_new_3filt = syn.IsochronePhot(
-        logAge, 
+        logAge,
         AKs,
-        distance, 
+        distance,
         evo_model=evo_model,
         atm_func=atm_func,
         red_law=redlaw,
@@ -294,12 +294,12 @@ def test_ResolvedCluster():
     filt_list = ['nirc2,J', 'nirc2,Kp']
 
     startTime = time.time()
-    
+
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
 
     red_law = reddening.RedLawNishiyama09()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -324,7 +324,7 @@ def test_ResolvedCluster():
     my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=None)
     print('Constructed IMF: %d seconds' % (time.time() - startTime))
-    
+
     cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass)
     clust1 = cluster1.star_systems
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
@@ -352,7 +352,7 @@ def test_ResolvedCluster():
     my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=multi)
     print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
-    
+
     cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass)
     clust2 = cluster2.star_systems
     print('Constructed cluster with multiples: %d seconds' % (time.time() - startTime))
@@ -362,7 +362,7 @@ def test_ResolvedCluster():
     assert np.sum(clust2['N_companions']) == len(cluster2.companions)
 
     ##########
-    # Plots 
+    # Plots
     ##########
     # Plot an IR CMD and compare cluster members to isochrone.
     plt.figure(1)
@@ -382,7 +382,7 @@ def test_ResolvedCluster():
     plt.gca().invert_yaxis()
     plt.xlabel('Mass (Msun)')
     plt.ylabel('J (mag)')
-    
+
     # # Plot the spectrum of the most massive star
     # idx = cluster.mass.argmax()
     # plt.clf()
@@ -406,14 +406,14 @@ def test_ResolvedClusterDiffRedden():
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
-    
+
     startTime = time.time()
-    
+
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
 
     red_law = reddening.RedLawNishiyama09()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -437,13 +437,13 @@ def test_ResolvedClusterDiffRedden():
     my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=None)
     print('Constructed IMF: %d seconds' % (time.time() - startTime))
-    
+
     cluster1 = syn.ResolvedClusterDiffRedden(iso, my_imf1, cluster_mass, deltaAKs)
     clust1 = cluster1.star_systems
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
 
     assert len(clust1) > 0
-    
+
     plt.figure(3)
     plt.clf()
     plt.plot(clust1['m_nirc2_J'] - clust1['m_nirc2_Kp'], clust1['m_nirc2_J'], 'r.')
@@ -460,7 +460,7 @@ def test_ResolvedClusterDiffRedden():
     my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=multi)
     print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
-    
+
     cluster2 = syn.ResolvedClusterDiffRedden(iso, my_imf2, cluster_mass, deltaAKs)
     clust2 = cluster2.star_systems
     print('Constructed cluster with multiples: %d seconds' % (time.time() - startTime))
@@ -470,7 +470,7 @@ def test_ResolvedClusterDiffRedden():
     assert np.sum(clust2['N_companions']) == len(cluster2.companions)
 
     ##########
-    # Plots 
+    # Plots
     ##########
     # Plot an IR CMD and compare cluster members to isochrone.
     plt.figure(1)
@@ -492,7 +492,7 @@ def test_ResolvedClusterDiffRedden():
     plt.ylabel('J (mag)')
 
     return
-    
+
 def test_UnresolvedCluster():
     log_age = 6.7
     AKs = 0.0
@@ -500,7 +500,7 @@ def test_UnresolvedCluster():
     metallicity=0
     cluster_mass = 10**4.
 
-    startTime = time.time()    
+    startTime = time.time()
     multi = multiplicity.MultiplicityUnresolved()
     imf_in = imf.Kroupa_2001(multiplicity=multi)
     evo = evolution.MergedBaraffePisaEkstromParsec()
@@ -533,13 +533,13 @@ def test_ifmr_multiplicity():
     filt_list = ['nirc2,Kp', 'nirc2,H', 'nirc2,J']
 
     startTime = time.time()
-    
+
     evo = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
     ifmr_obj = ifmr.IFMR_Raithel18()
 
     red_law = reddening.RedLawNishiyama09()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -563,13 +563,13 @@ def test_ifmr_multiplicity():
     ##########
     my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=None)
-    print('Constructed IMF: %d seconds' % (time.time() - startTime)) 
-    
+    print('Constructed IMF: %d seconds' % (time.time() - startTime))
+
     cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass, ifmr=ifmr_obj)
     clust1 = cluster1.star_systems
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
 
-   
+
     ##########
     # Test with multiplicity and IFMR
     ##########
@@ -577,7 +577,7 @@ def test_ifmr_multiplicity():
     my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=multi)
     print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
-    
+
     cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass, ifmr=ifmr_obj)
     clust2 = cluster2.star_systems
     comps2 = cluster2.companions
@@ -613,16 +613,16 @@ def test_metallicity():
     Test isochrone generation at different metallicities
     """
     # Define isochrone parameters
-    logAge = np.log10(5*10**6.) 
-    AKs = 0.8 
-    dist = 4000 
+    logAge = np.log10(5*10**6.)
+    AKs = 0.8
+    dist = 4000
     evo_model = evolution.MISTv1()
     atm_func = atmospheres.get_phoenixv16_atmosphere
     red_law = reddening.RedLawHosek18b()
     filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f139m', 'wfc3,ir,f153m']
     iso_dir = f'{spisea_path}/tests/isochrones'
 
-    # Start with a solar metallicity isochrone    
+    # Start with a solar metallicity isochrone
     metallicity= 0.
     metal_sign = 'm' if metallicity < 0 else 'p'
 
@@ -639,7 +639,7 @@ def test_metallicity():
         mass_sampling=10,
         iso_dir=iso_dir
     )
-    
+
     # Test isochrone properties
     assert my_iso.points.meta['METAL_IN'] == 0.0
     assert os.path.exists(f'{iso_dir}/iso_6.70_0.80_04000_p0.00.fits')
@@ -695,12 +695,12 @@ def test_cluster_mass():
     filt_list = ['nirc2,J', 'nirc2,Kp']
 
     startTime = time.time()
-    
+
     # Define evolution/atmosphere models and extinction law
-    evo = evolution.MISTv1() 
+    evo = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawHosek18b()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -721,7 +721,7 @@ def test_cluster_mass():
 
     # IFMR
     my_ifmr = ifmr.IFMR_Raithel18()
-    
+
 
     ##########
     # Start without multiplicity
@@ -729,7 +729,7 @@ def test_cluster_mass():
     my_imf1 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=None)
     print('Constructed IMF: %d seconds' % (time.time() - startTime))
-    
+
     cluster1 = syn.ResolvedCluster(iso, my_imf1, cluster_mass, ifmr=my_ifmr)
     clust1 = cluster1.star_systems
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
@@ -755,7 +755,7 @@ def test_cluster_mass():
     my_imf2 = imf.IMF_broken_powerlaw(imf_mass_limits, imf_powers,
                                       multiplicity=multi)
     print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
-    
+
     cluster2 = syn.ResolvedCluster(iso, my_imf2, cluster_mass, ifmr=my_ifmr)
     clust2 = cluster2.star_systems
     print('Constructed cluster with multiples: %d seconds' % (time.time() - startTime))
@@ -769,7 +769,7 @@ def test_cluster_mass():
 
 def test_keep_low_mass_stars():
     """
-    Test "keep_low_mass_stars = True" functionality introduced in v2.2 
+    Test "keep_low_mass_stars = True" functionality introduced in v2.2
     """
     # Define cluster parameters, pulling on an isochrone generated in an earlier test (since
     # we don't care about isochrone generation here
@@ -782,12 +782,12 @@ def test_keep_low_mass_stars():
 
     # Test filters
     filt_list = ['nirc2,J', 'nirc2,Kp']
-    
+
     # Define evolution/atmosphere models and extinction law
-    evo = evolution.MISTv1() 
+    evo = evolution.MISTv1()
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawHosek18b()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -805,7 +805,7 @@ def test_keep_low_mass_stars():
     # Make sure this min mass is low enough for a reasonalbe test
     min_mass_iso = np.min(iso.points['mass'])
     assert min_mass_iso >= 0.05
-    
+
     # Define IMF + IFMR. Make sure IMF goes to really low masses,
     # below the 0.08 Msun limit of the MIST isochrones
     imf_min = 0.01
@@ -833,9 +833,9 @@ def test_keep_low_mass_stars():
 
     return
 
-        
+
 def test_compact_object_companions():
-    
+
     # Define cluster parameters
     logAge = 6.7
     AKs = 2.4
@@ -848,12 +848,12 @@ def test_compact_object_companions():
     filt_list = ['nirc2,J', 'nirc2,Kp']
 
     startTime = time.time()
-    
+
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
 
     red_law = reddening.RedLawNishiyama09()
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -867,7 +867,7 @@ def test_compact_object_companions():
     )
 
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
-    
+
     clust_multiplicity = multiplicity.MultiplicityResolvedDK()
 
     massLimits = np.array([0.2, 0.5, 1, 120]) # mass segments
@@ -894,12 +894,12 @@ def time_test_cluster():
     iso_dir = f'{spisea_path}/tests/isochrones'
 
     startTime = time.time()
-    
+
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawNishiyama09()
     filt_list = ['nirc2,J', 'nirc2,Kp']
-    
+
     iso = syn.IsochronePhot(
         logAge,
         AKs,
@@ -917,12 +917,12 @@ def time_test_cluster():
     multi = multiplicity.MultiplicityUnresolved()
     my_imf = imf.IMF_broken_powerlaw(imf_limits, imf_powers, multiplicity=multi)
     print('Constructed IMF with multiples: %d seconds' % (time.time() - startTime))
-    
+
     cluster = syn.ResolvedCluster(iso, my_imf, cluster_mass)
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
 
     return
-    
+
 def model_young_cluster_object(resolved=False):
     log_age = 6.5
     AKs = 0.1
@@ -934,10 +934,10 @@ def model_young_cluster_object(resolved=False):
     evo = evolution.MergedBaraffePisaEkstromParsec()
     atm_func = atmospheres.get_merged_atmosphere
     iso = syn.Isochrone(
-        log_age, 
-        AKs, 
-        distance, 
-        evo_model=evo, 
+        log_age,
+        AKs,
+        distance,
+        evo_model=evo,
         atm_func=atm_func,
         mass_sampling=10
     )
@@ -980,13 +980,13 @@ def time_test_mass_match():
     start_time = time.time()
     star_masses, isMulti, compMass, sysMass = imf_in.generate_cluster(cluster_mass)
     print('Generated cluster masses in {0:.0f} s'.format(time.time() - start_time))
-    
+
     def match_model_masses1(isoMasses, starMasses):
         indices = np.empty(len(starMasses), dtype=int)
-        
+
         for ii in range(len(starMasses)):
             theMass = starMasses[ii]
-            
+
             dm = np.abs(isoMasses - theMass)
             mdx = dm.argmin()
 
@@ -997,12 +997,12 @@ def match_model_masses1(isoMasses, starMasses):
                 indices[ii] = mdx
 
         return indices
-            
+
 
     def match_model_masses2(isoMasses, starMasses):
         isoMasses_tmp = isoMasses.reshape((len(isoMasses), 1))
         kdt = KDTree(isoMasses_tmp)
- 
+
         starMasses_tmp = starMasses.reshape((len(starMasses), 1))
         q_results = kdt.query(starMasses_tmp, k=1)
         indices = q_results[1]
@@ -1011,7 +1011,7 @@ def match_model_masses2(isoMasses, starMasses):
 
         idx = np.where(dm_frac > 0.1)[0]
         indices[idx] = -1
-        
+
         return indices
 
     print('Test #1 START')
@@ -1042,7 +1042,7 @@ def FeH_from_Z(Z):
     metal = np.array([2.0e-4, 1.0e-3, 2.0e-3, 2.0e-2]) #ensure that all Spera metallicity regimes are represented
 
     FeH = FeH_from_Z(metal) #generate death mass takes metallicty as [Fe/H]
-    #want to get a good range of masses for Spera, should expect 8 invalids, 8 WDs, 3 NSs, and 9 BHs 
+    #want to get a good range of masses for Spera, should expect 8 invalids, 8 WDs, 3 NSs, and 9 BHs
     ZAMS = np.array([-0.2*np.ones(len(FeH)), 0.2*np.ones(len(FeH)), 4.0*np.ones(len(FeH)), 9.2*np.ones(len(FeH)),
                     15.0*np.ones(len(FeH)), 30.0*np.ones(len(FeH)), 150.0*np.ones(len(FeH))])
 
@@ -1134,7 +1134,7 @@ def test_Spera15_IFMR_7():
     assert len(BH_idx) == 10 , "There are not the right number of BHs for the Spera15 IFMR"
 
     return
-    
+
 def generate_Raithel18_IFMR():
     """
     Make a set of objects using the Raithel18 IFMR for the purposes of testing
@@ -1143,7 +1143,7 @@ def generate_Raithel18_IFMR():
     """
 
     Raithel = ifmr.IFMR_Raithel18()
-    ZAMS = np.array([-0.2, 0.2, 1.0, 7.0, 10.0, 14.0, 16.0, 18.0, 18.6, 22.0, 26.0, 28.0, 50.0, 61.0, 119.0, 121.0]) 
+    ZAMS = np.array([-0.2, 0.2, 1.0, 7.0, 10.0, 14.0, 16.0, 18.0, 18.6, 22.0, 26.0, 28.0, 50.0, 61.0, 119.0, 121.0])
     #3 invalid indices, 2 WDs, cannot make statements about #of BHs and NSs because the Raithel IFMR has some randomness
 
     output_array = Raithel.generate_death_mass(ZAMS)
@@ -1226,7 +1226,7 @@ def test_ResolvedCluster_random_state():
     atm_func = atmospheres.get_merged_atmosphere
     red_law = reddening.RedLawNishiyama09()
     filt_list = ['nirc2,J', 'nirc2,Kp']
-    
+
     iso = syn.IsochronePhot(
         log_age,
         AKs,

From 941dc92b9cdb420f5033b35f60a91392cc8d62a5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 19:04:28 -0800
Subject: [PATCH 31/55] Fixed minor typos and missing import

---
 spisea/evolution.py | 2 +-
 spisea/reddening.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/spisea/evolution.py b/spisea/evolution.py
index 895b9bb6..be6a1d3f 100755
--- a/spisea/evolution.py
+++ b/spisea/evolution.py
@@ -1602,7 +1602,7 @@ def make_isochrone_pisa_interp(log_age, metallicity=0.015,
 
     print( '*** Generating Pisa isochrone for log t = %3.2f and Z = %.3f' % \
         (log_age, metallicity))
-
+    import time
     print( time.asctime(), 'Getting original Pisa isochrones.')
     iso = get_orig_pisa_isochrones(metallicity=metallicity)
 
diff --git a/spisea/reddening.py b/spisea/reddening.py
index 677999a8..a4eb7b92 100755
--- a/spisea/reddening.py
+++ b/spisea/reddening.py
@@ -1243,7 +1243,7 @@ def _derive_Indebetouw05(wave):
         Alambda_AK = 10**log_Alambda_AK
         return Alambda_AK
 
-    def Indebetouw05(self, wavelength, AK):
+    def Indebetouw05(self, wavelength, AKs):
         """
         Return the extinction at a given wavelength assuming the
         extinction law and an overall extinction at AK (2.164 microns)

From c42b10fcdaa87c46180c7e15a974bf898e80f808 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 19:06:09 -0800
Subject: [PATCH 32/55] Added backward compatibility for isochrone file names

---
 spisea/synthetic.py | 119 ++++++++++++++++++++++++--------------------
 1 file changed, 64 insertions(+), 55 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 69b61d2e..9ae64359 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1135,20 +1135,31 @@ def __init__(self, logAge, AKs, distance,
         # Set save file name
         metal_value = round(abs(metallicity), 2)
         metal_sign = 'm' if metallicity < 0 else 'p'
-        self.save_file = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value:.2f}.fits'
 
-        if metallicity == 0.0:
-            self.save_file_legacy = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
+        oldest_file     = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
+        older_file      = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value*10:02.0f}.fits'
+        self.save_file  = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value:.2f}.fits'
+
+        oldest_file_exists = check_save_file(oldest_file, evo_model, atm_func, red_law, verbose=verbose)
+        older_file_exists = check_save_file(older_file, evo_model, atm_func, red_law, verbose=verbose)
+        new_file_exists = check_save_file(self.save_file, evo_model, atm_func, red_law, verbose=verbose)
+
+        if new_file_exists:
+            self.save_file_legacy = None
+        elif older_file_exists:
+            self.save_file_legacy = older_file
+        elif oldest_file_exists and metallicity == 0.0:
+            self.save_file_legacy = oldest_file
         else:
-            self.save_file_legacy = self.save_file
+            self.save_file_legacy = None
 
         # Expected filters
         self.filters = filters
 
         # Recalculate isochrone if save_file doesn't exist or recomp == True
-        file_exists = self.check_save_file(evo_model, atm_func, red_law, verbose=verbose)
+        file_exists = new_file_exists or (self.save_file_legacy is not None)
 
-        if (not file_exists) | (recomp==True):
+        if  (recomp==True) or (not file_exists):
             self.recalc = True
             if verbose:
                 print(f'Generating new isochrone of log(t)={logAge:.2f}, AKs={AKs:.2f}, d={distance} pc')
@@ -1172,12 +1183,12 @@ def __init__(self, logAge, AKs, distance,
                 print(f'Isochrone saved to {self.save_file}')
         else:
             self.recalc = False
-            try:
+            if new_file_exists:
                 self.points = Table.read(self.save_file)
-            except:
+                print(f'Isochrone loaded from existing file: {self.save_file}')
+            else:
                 self.points = Table.read(self.save_file_legacy)
-            # print(f'Isochrone loaded from existing file: {self.save_file}')
-            # Add some error checking.
+                print(f'Isochrone loaded from existing file: {self.save_file_legacy}')
 
         # Next: do we have all the filters we need?
         comp_filters = []
@@ -1285,51 +1296,6 @@ def make_photometry(self, rebin=True, vega=vega, comp_filters=None):
 
         return
 
-    def check_save_file(self, evo_model, atm_func, red_law, verbose=False):
-        """
-        Check to see if save_file exists, as saved by the save_file
-        and save_file_legacy objects. If the filename exists, check the
-        meta-data as well.
-
-        returns a boolean: True is file exists, false otherwise
-        """
-        out_bool = False
-
-        if os.path.exists(self.save_file) | os.path.exists(self.save_file_legacy):
-            try:
-                tmp = Table.read(self.save_file)
-            except:
-                tmp = Table.read(self.save_file_legacy)
-
-
-            # See if the meta-data matches: evo model, atm_func, redlaw
-            if ( (tmp.meta['EVOMODEL'] == type(evo_model).__name__) &
-                (tmp.meta['ATMFUNC'] == atm_func.__name__) &
-                 (tmp.meta['REDLAW'] == red_law.name) ):
-                out_bool = True
-            else:
-                # If out_bool is false, print out what doesn't match
-                if verbose:
-                    print(f'Isochrone file {self.save_file} exists, but meta-data does not match.')
-                    if tmp.meta['EVOMODEL'] != type(evo_model).__name__:
-                        print(f'  EVOMODEL: {tmp.meta["EVOMODEL"]} != {type(evo_model).__name__}')
-                    if tmp.meta['ATMFUNC'] != atm_func.__name__:
-                        print(f'  ATMFUNC: {tmp.meta["ATMFUNC"]} != {atm_func.__name__}')
-                    if tmp.meta['REDLAW'] != red_law.name:
-                        print(f'  REDLAW: {tmp.meta["REDLAW"]} != {red_law.name}')
-
-            # Check model version if it was logged
-            if 'EVOMODELVERSION' in tmp.meta:
-                if tmp.meta['EVOMODELVERSION'] != evo_model.model_version_name:
-                    out_bool=False
-                    if verbose:
-                        print(f'EVOMODELVERSION does not match: The recorded {tmp.meta["EVOMODELVERSION"]} does not matched the existing version {evo_model.model_version_name}')
-
-        else:
-            if verbose:
-                print(f'Isochrone file {self.save_file} or {self.save_file_legacy} does not exist, generating new one.')
-
-        return out_bool
 
     def plot_CMD(self, mag1, mag2, savefile=None):
         """
@@ -1637,6 +1603,49 @@ def make_photometry(self, filters, rebin=True):
 
         return
 
+def check_save_file(save_file_path, evo_model, atm_func, red_law, verbose=False):
+    """
+    Check to see if save_file exists, as saved by the save_file
+    and save_file_legacy objects. If the filename exists, check the
+    meta-data as well.
+
+    returns a boolean: True is file exists, false otherwise
+    """
+    out_bool = False
+
+    if not os.path.exists(save_file_path):
+        if verbose: print(f'Isochrone file {save_file_path} does not exist.')
+        return out_bool
+
+    tmp = Table.read(save_file_path)
+
+    # See if the meta-data matches: evo model, atm_func, redlaw
+    if ( (tmp.meta['EVOMODEL'] == type(evo_model).__name__) &
+        (tmp.meta['ATMFUNC'] == atm_func.__name__) &
+            (tmp.meta['REDLAW'] == red_law.name) ):
+        out_bool = True
+    else:
+        # If out_bool is false, print out what doesn't match
+        if verbose:
+            print(f'Isochrone file {save_file_path} exists, but meta-data does not match.')
+            if tmp.meta['EVOMODEL'] != type(evo_model).__name__:
+                print(f'  EVOMODEL: {tmp.meta["EVOMODEL"]} != {type(evo_model).__name__}')
+            if tmp.meta['ATMFUNC'] != atm_func.__name__:
+                print(f'  ATMFUNC: {tmp.meta["ATMFUNC"]} != {atm_func.__name__}')
+            if tmp.meta['REDLAW'] != red_law.name:
+                print(f'  REDLAW: {tmp.meta["REDLAW"]} != {red_law.name}')
+
+    # Check model version if it was logged
+    if 'EVOMODELVERSION' in tmp.meta:
+        if tmp.meta['EVOMODELVERSION'] != evo_model.model_version_name:
+            out_bool=False
+            if verbose:
+                print(f'EVOMODELVERSION does not match: The recorded {tmp.meta["EVOMODELVERSION"]} does not matched the existing version {evo_model.model_version_name}')
+
+
+    return out_bool
+
+
 def get_filter_info(name, vega=vega, rebin=True):
     """
     Define filter functions, setting ZP according to

From 02c0feb2a30c59be1e5f85e04ab99a97d815b4d5 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 19:06:40 -0800
Subject: [PATCH 33/55] Added isochrone folder into gitignore

---
 .gitignore                                    |  2 +-
 .../isochrones/iso_6.70_2.70_04000_p0.00.fits | 44 -------------------
 2 files changed, 1 insertion(+), 45 deletions(-)
 delete mode 100644 spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits

diff --git a/.gitignore b/.gitignore
index ae231559..b29e4f96 100755
--- a/.gitignore
+++ b/.gitignore
@@ -54,4 +54,4 @@ distribute-*.tar.gz
 ._*
 
 # Test files generated
-# spisea/tests/isochrones
+spisea/tests/isochrones
diff --git a/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits b/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
deleted file mode 100644
index d8d7bbbe..00000000
--- a/spisea/tests/isochrones/iso_6.70_2.70_04000_p0.00.fits
+++ /dev/null
@@ -1,44 +0,0 @@
-SIMPLE  =                    T / conforms to FITS standard                      BITPIX  =                    8 / array data type                                NAXIS   =                    0 / number of array dimensions                     EXTEND  =                    T                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                             XTENSION= 'BINTABLE'           / binary table extension                         BITPIX  =                    8 / array data type                                NAXIS   =                    2 / number of array dimensions                     NAXIS1  =                   73 / length of dimension 1                          NAXIS2  =                  161 / length of dimension 2                          PCOUNT  =                    0 / number of group parameters                     GCOUNT  =                    1 / number of groups                               TFIELDS =                   10 / number of table fields                         TTYPE1  = 'L       '                                                            TFORM1  = 'D       '                                                            TUNIT1  = 'W       '                                                            TTYPE2  = 'Teff    '                                                            TFORM2  = 'D       '                                                            TUNIT2  = 'K       '                                                            TTYPE3  = 'R       '                                                            TFORM3  = 'D       '                                                            TUNIT3  = 'm       '                                                            TTYPE4  = 'mass    '                                                            TFORM4  = 'D       '                                                            TUNIT4  = 'solMass '                                                            TTYPE5  = 'logg    '                                                            TFORM5  = 'D       '                                                            TTYPE6  = 'isWR    '                                                            TFORM6  = 'L       '                                                            TTYPE7  = 'mass_current'                                                        TFORM7  = 'D       '                                                            TUNIT7  = 'solMass '                                                            TTYPE8  = 'phase   '                                                            TFORM8  = 'K       '                                                            TTYPE9  = 'm_nirc2_J'                                                           TFORM9  = 'D       '                                                            TTYPE10 = 'm_nirc2_Kp'                                                          TFORM10 = 'D       '                                                            REDLAW  = 'N09     '                                                            ATMFUNC = 'get_merged_atmosphere'                                               EVOMODEL= 'MergedBaraffePisaEkstromParsec'                                      HIERARCH EVOMODELVERSION = 'None    '                                           LOGAGE  =                  6.7                                                  AKS     =                  2.7                                                  DISTANCE=                 4000                                                  METAL_IN=                  0.0                                                  HIERARCH METAL_ACT = 0.0                                                        WAVEMIN =                 3000                                                  WAVEMAX =                52000                                                  END                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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From 9283afdf4c771377c5e194c99c13213106a9507e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 19:14:13 -0800
Subject: [PATCH 34/55] Fixed r string warnings

---
 spisea/reddening.py | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/spisea/reddening.py b/spisea/reddening.py
index a4eb7b92..0d25e5ae 100755
--- a/spisea/reddening.py
+++ b/spisea/reddening.py
@@ -253,7 +253,7 @@ def plot_Nishiyama09(self):
         py.errorbar(wave_obs, A_AKs, yerr=A_AKs_err, fmt='k.', ms=10,
                         label='Measured')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Nishiyama+09 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')
@@ -263,7 +263,7 @@ def plot_Nishiyama09(self):
         return
 
 class RedLawCardelli(pysynphot.reddening.CustomRedLaw):
-    """
+    r"""
     Defines the extinction law from
     `Cardelli et al. 1989 <https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C/abstract>`_.
     The law is defined from 0.3 - 3 microns, and in terms
@@ -519,7 +519,7 @@ def plot_RomanZuniga07(self):
         py.errorbar(wave_obs, A_AKs, yerr=A_AKs_err, fmt='k.', ms=10,
                         label='Measured')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Roman-Zuniga+07 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')
@@ -687,7 +687,7 @@ def plot_RiekeLebofsky85(self):
         py.plot(wave_obs_f, A_Ak_f, 'k.', ms=10,
                         label='Measured')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Rieke+Lebofsky+85 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')
@@ -814,7 +814,7 @@ def plot_Damineli16(self):
         py.errorbar(wave_obs, A_AKs, fmt='k.', ms=10,
                         label='Measured')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Damineli+16 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')
@@ -1309,7 +1309,7 @@ def plot_Indebetouw05(self):
         py.errorbar(wave_arr, law_obs_arr, yerr=law_obs_err_arr, fmt='k.', ms=10,
                         label='Measured')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Indebetouw+05 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')
@@ -1319,7 +1319,7 @@ def plot_Indebetouw05(self):
         return
 
 class RedLawPowerLaw(pysynphot.reddening.CustomRedLaw):
-    """
+    r"""
     Extinction object that is a power-law extinction law:
     :math:`A_{\lambda} \propto \lambda^{\alpha}`.
 
@@ -1433,7 +1433,7 @@ def powerlaw(self, wavelength, AKs):
         return A_at_wave
 
 class RedLawBrokenPowerLaw(pysynphot.reddening.CustomRedLaw):
-    """
+    r"""
     Extinction object that is a broken power-law extinction law:
     :math:`A_{\lambda} \propto \lambda^{\alpha[n]}`
 
@@ -1713,7 +1713,7 @@ def plot_Fritz11(self):
                         label='Measured')
         py.plot(ext_scaled.wave*10**-4, np.log10(ext_scaled.throughput)/-0.4, 'b-', label='Scaled EL')
         py.xlabel('Wavelength (microns)')
-        py.ylabel('Extinction (A$_{\lambda}$)')
+        py.ylabel(r'Extinction (A$_{\lambda}$)')
         py.title('Fritz+11 EL')
         py.gca().set_xscale('log')
         py.gca().set_yscale('log')

From 67228f16bf1e2c71388caa6ce26d6425043ad5ee Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 19:14:35 -0800
Subject: [PATCH 35/55] Adjusted check save file order

---
 spisea/synthetic.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 9ae64359..a91d81c2 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1136,13 +1136,13 @@ def __init__(self, logAge, AKs, distance,
         metal_value = round(abs(metallicity), 2)
         metal_sign = 'm' if metallicity < 0 else 'p'
 
-        oldest_file     = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
-        older_file      = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value*10:02.0f}.fits'
         self.save_file  = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value:.2f}.fits'
+        older_file      = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}_{metal_sign}{metal_value*10:02.0f}.fits'
+        oldest_file     = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
 
-        oldest_file_exists = check_save_file(oldest_file, evo_model, atm_func, red_law, verbose=verbose)
-        older_file_exists = check_save_file(older_file, evo_model, atm_func, red_law, verbose=verbose)
         new_file_exists = check_save_file(self.save_file, evo_model, atm_func, red_law, verbose=verbose)
+        older_file_exists = check_save_file(older_file, evo_model, atm_func, red_law, verbose=verbose)
+        oldest_file_exists = check_save_file(oldest_file, evo_model, atm_func, red_law, verbose=verbose)
 
         if new_file_exists:
             self.save_file_legacy = None

From 21bc2b3831accc7ae9174cc3fcf51e85b3ee14fc Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 22:35:57 -0800
Subject: [PATCH 36/55] Changed global random seed to random generator; Updated
 star systems and companions files for future comparisons

---
 spisea/imf/imf.py                       |  16 +++++--------
 spisea/synthetic.py                     |  30 ++++++++++++------------
 spisea/tests/test_data/companions.pkl   | Bin 251721 -> 231086 bytes
 spisea/tests/test_data/star_systems.pkl | Bin 1516177 -> 1253105 bytes
 spisea/tests/test_synthetic.py          |   3 +--
 5 files changed, 22 insertions(+), 27 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index cb6866e6..4598705d 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -51,7 +51,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         self._multi_props = multiplicity
         self._mass_limits = np.atleast_1d(massLimits)
         self.seed = seed
-        # self.rng = np.random.default_rng(seed)
+        self.rng = np.random.default_rng(seed)
 
         if multiplicity:
             self.make_multiples = True
@@ -61,7 +61,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         return
 
 
-    def generate_cluster(self, totalMass, seed=None):
+    def generate_cluster(self, totalMass):
         """
         Generate a cluster of stellar systems with the specified IMF.
 
@@ -128,13 +128,10 @@ def generate_cluster(self, totalMass, seed=None):
         totalMassTally = 0
         loopCnt = 0
 
-        if seed:
-            np.random.seed(seed=seed)
-
         # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
-            uniX = np.random.rand(int(newStarCount))
+            uniX = self.rng.random(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
 
@@ -151,7 +148,7 @@ def generate_cluster(self, totalMass, seed=None):
                 MF = self._multi_props.multiplicity_fraction(newMasses)
                 CSF = self._multi_props.companion_star_fraction(newMasses)
 
-                newIsMultiple = np.random.rand(int(newStarCount)) < MF
+                newIsMultiple = self.rng.random(int(newStarCount)) < MF
 
                 # Function to calculate multiple systems more efficiently
                 # start_calc = time.time()
@@ -231,7 +228,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
 
         # Identify multiple systems, calculate number of companions for each
         multiple_idx = np.where(newIsMultiple)[0]
-        comp_nums = 1 + np.random.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
+        comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
         if self._multi_props.companion_max:
             too_many = np.where(comp_nums > self._multi_props.CSF_max)[0]
             comp_nums[too_many] = self._multi_props.CSF_max
@@ -245,7 +242,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
 
         for comp_num, comp_index in zip(comp_unique, comp_indices):
             # Calculate masses of companions
-            q_values = self._multi_props.random_q(np.random.rand(len(comp_index), comp_num))
+            q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
             m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
             compMasses[multiple_idx[comp_index], :comp_num] = m_comp
 
@@ -912,4 +909,3 @@ def inv_error(x):
         return y
     else:
         return -y
-
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index a91d81c2..a2bd7b98 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -107,7 +107,7 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=False,
         self.ifmr = ifmr
         self.cluster_mass = cluster_mass
         self.seed = seed
-        # self.rng = np.random.default_rng(self.seed)
+        self.rng = np.random.default_rng(self.seed)
 
         return
 
@@ -159,13 +159,13 @@ def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
         # Provide a user warning is random seed is set
         if seed is not None and verbose:
             print('WARNING: random seed set to %i' % seed)
-            # imf.rng = self.rng
+            imf.rng = self.rng
 
         #####
         # Sample the IMF to build up our cluster mass.
         #####
         # start0 = time.time()
-        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass, seed=seed)
+        mass, isMulti, compMass, sysMass = imf.generate_cluster(cluster_mass)
         # end0 = time.time()
         # print('IMF sampling took {0:f} s.'.format(end0 - start0))
 
@@ -328,11 +328,11 @@ def _make_companions_table_new(self, star_systems, compMass):
 
         if isinstance(self.imf._multi_props, multiplicity.MultiplicityResolvedDK):
             companions.add_column(Column(self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx']]), name='log_a'))
-            companions.add_column(Column(self.imf._multi_props.random_e(np.random.rand(N_comp_tot)), name='e'))
+            companions.add_column(Column(self.imf._multi_props.random_e(self.rng.random(N_comp_tot)), name='e'))
             companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
-                np.random.rand(N_comp_tot),
-                np.random.rand(N_comp_tot),
-                np.random.rand(N_comp_tot)
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot)
             )
 
         companions['mass'] = compMass.compressed()
@@ -441,11 +441,11 @@ def _make_companions_table(self, star_systems, compMass):
             for ii in range(len(companions)):
                 companions['log_a'][ii] = self.imf._multi_props.log_semimajoraxis(star_systems['mass'][companions['system_idx'][ii]])
 
-            companions['e'] = self.imf._multi_props.random_e(np.random.rand(N_comp_tot))
+            companions['e'] = self.imf._multi_props.random_e(self.rng.random(N_comp_tot))
             companions['i'], companions['Omega'], companions['omega'] = self.imf._multi_props.random_keplarian_parameters(
-                np.random.rand(N_comp_tot),
-                np.random.rand(N_comp_tot),
-                np.random.rand(N_comp_tot)
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot),
+                self.rng.random(N_comp_tot)
             )
 
 
@@ -701,7 +701,7 @@ def __init__(self, iso, imf, cluster_mass, deltaAKs,
         # Perturb all of star systems' photometry by a random amount corresponding to
         # differential de-reddening. The distribution is normal with a width of
         # Aks +/- deltaAKs in each filter
-        rand_red = np.random.randn(len(self.star_systems))
+        rand_red = self.rng.standard_normal(len(self.star_systems))
 
         for filt in self.filt_names:
             self.star_systems[filt] += rand_red * delta_red_filt[filt]
@@ -1527,18 +1527,18 @@ def apply_reddening(self, AKs, extinction_law, dAKs=0, dist='uniform', dAKs_max=
             # extinction law
             if dAKs != 0:
                 if dist == 'gaussian':
-                    AKs_act = np.random.normal(loc=AKs, scale=dAKs)
+                    AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
                     # Apply dAKs_max if desired. Redo if diff > dAKs_max
                     if dAKs_max != None:
                         diff = abs(AKs_act - AKs)
                         while diff > dAKs_max:
                             print('While loop active')
-                            AKs_act = np.random.normal(loc=AKs, scale=dAKs)
+                            AKs_act = self.rng.normal(loc=AKs, scale=dAKs)
                             diff = abs(AKs_act - AKs)
                 elif dist == 'uniform':
                     low = AKs - dAKs
                     high = AKs + dAKs
-                    AKs_act = np.random.uniform(low=low, high=high)
+                    AKs_act = self.rng.uniform(low=low, high=high)
                 else:
                     print('dist {0} undefined'.format(dist))
                     return
diff --git a/spisea/tests/test_data/companions.pkl b/spisea/tests/test_data/companions.pkl
index a6852ef4abad97afe33e9c25d5e1798df2caf679..0395d75d828740e3bd040811cc8926271a26676c 100644
GIT binary patch
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N`hJ$%+V6ciy#UeRw~hb+

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 80284505..a39a6505 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1254,8 +1254,7 @@ def test_ResolvedCluster_random_state():
         old_companion = pickle.load(file)
 
     for key in old_star_systems.colnames:
-        # Equal to the 7th decimal
-        np.testing.assert_almost_equal(cluster1.star_systems[key], old_star_systems[key])
+        np.testing.assert_array_equal(cluster1.star_systems[key], old_star_systems[key])
 
     for key in old_companion.colnames:
         np.testing.assert_array_equal(cluster1.companions[key], old_companion[key])

From 5fd75f5b6fda39a4232c6bf6ecc6748dcc0e0a14 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Mon, 23 Feb 2026 22:50:45 -0800
Subject: [PATCH 37/55] Remove unnecessary checkings

---
 spisea/synthetic.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index a2bd7b98..cf6848db 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1141,14 +1141,12 @@ def __init__(self, logAge, AKs, distance,
         oldest_file     = f'{iso_dir}/iso_{logAge:.2f}_{AKs:4.2f}_{str(round(distance)).zfill(5)}.fits'
 
         new_file_exists = check_save_file(self.save_file, evo_model, atm_func, red_law, verbose=verbose)
-        older_file_exists = check_save_file(older_file, evo_model, atm_func, red_law, verbose=verbose)
-        oldest_file_exists = check_save_file(oldest_file, evo_model, atm_func, red_law, verbose=verbose)
 
         if new_file_exists:
             self.save_file_legacy = None
-        elif older_file_exists:
+        elif check_save_file(older_file, evo_model, atm_func, red_law, verbose=verbose):
             self.save_file_legacy = older_file
-        elif oldest_file_exists and metallicity == 0.0:
+        elif metallicity == 0.0 and check_save_file(oldest_file, evo_model, atm_func, red_law, verbose=verbose):
             self.save_file_legacy = oldest_file
         else:
             self.save_file_legacy = None

From e753199062dda23c4904c05c972bf8aefe031177 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 25 Feb 2026 15:03:25 -0800
Subject: [PATCH 38/55] Added documentation on random number generator
 behavior; Added support of overriding random number generator in
 generate_cluster and calc_multi function; Added testing of generate_cluster
 random reproducibility

---
 spisea/imf/imf.py              |  79 ++++++++++++++++------
 spisea/synthetic.py            | 119 +++++++++++++++++++++++++++------
 spisea/tests/test_synthetic.py |   6 ++
 3 files changed, 163 insertions(+), 41 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 4598705d..4f2e20a5 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -25,16 +25,6 @@ class IMF(object):
     The IMF base class. The mass sampling and multiplicity
     implementation is here.
 
-    Notes
-    -----
-    Code author: J. Lu.
-
-    Original code was taken from libimf package written by Jan Pflamm-Altenburg
-    (`Pflamm-Altenburg & Kroupa 2006 <https://ui.adsabs.harvard.edu/abs/2006MNRAS.373..295P/abstract>`_)
-    and has been modified only marginally, though more convinient and general purpose
-    functions have been added. The libimf code was licensed under
-    a GNU General Public License.
-
 
     Parameters
     ----------
@@ -46,11 +36,53 @@ class IMF(object):
     multiplicity : Multiplicity object or None
         If None, no multiplicity is assumed. Otherwise, use
         multiplicity object to create multiple star systems.
+    
+    seed : int, optional
+        Seed for the random generator numpy.random.default_rng(seed).
+        All random functions in the class will use this generator, unless a different generator is passed in as an argument to the function. Default None.
+        Behavior:
+        ::
+
+            imf = IMF(..., seed=42)
+            result1 = imf.generate_cluster()
+            result2 = imf.generate_cluster()
+            imf = IMF(..., seed=42)
+            result3 = imf.generate_cluster()
+            result4 = imf.generate_cluster()
+
+        result1==result3, result2==result4, but result1≠result2, result3≠result4.
+        This is the same behavior as
+        ::
+
+            rng = np.random.default_rng(seed=42)
+            result1 = rng.random(1)
+            result2 = rng.random(1)
+            rng = np.random.default_rng(seed=42)
+            result3 = rng.random(1)
+            result4 = rng.random(1)
+
+        If identical output is desired over each run, the same generator can be passed in as an argument to the generate_cluster function, e.g.
+        ::
+
+            result1 = imf.generate_cluster(rng=np.random.default_rng(42))            
+            result2 = imf.generate_cluster(rng=np.random.default_rng(42))
+
+        In this case, result1==result2
+
+    Notes
+    -----
+    Code author: J. Lu.
+
+    Original code was taken from libimf package written by Jan Pflamm-Altenburg
+    (`Pflamm-Altenburg & Kroupa 2006 <https://ui.adsabs.harvard.edu/abs/2006MNRAS.373..295P/abstract>`_)
+    and has been modified only marginally, though more convinient and general purpose
+    functions have been added. The libimf code was licensed under
+    a GNU General Public License.
+
     """
     def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None):
         self._multi_props = multiplicity
         self._mass_limits = np.atleast_1d(massLimits)
-        self.seed = seed
         self.rng = np.random.default_rng(seed)
 
         if multiplicity:
@@ -61,7 +93,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
         return
 
 
-    def generate_cluster(self, totalMass):
+    def generate_cluster(self, totalMass, rng=None):
         """
         Generate a cluster of stellar systems with the specified IMF.
 
@@ -81,10 +113,10 @@ def generate_cluster(self, totalMass):
         totalMass : float
             The total mass of the cluster (including companions) in solar masses.
 
-        seed: int
-            If set to non-None, all random sampling will be seeded with the
-            specified seed, forcing identical output.
-            Default None
+        rng: numpy.random.Generator, optional
+            If not provided, will use the random number generator specified by the seed in the IMF instance.
+            If provided, will override the random generator in the IMF instance and use the specified generator,
+            by default None.
 
         Returns
         -------
@@ -102,6 +134,8 @@ def generate_cluster(self, totalMass):
             Array of total system masses (primary + companions) for each primary star.
 
         """
+        rng = self.rng if rng is None else rng
+
         initial_mass_limit = self._mass_limits[-1]
 
         if (self._mass_limits[-1] > totalMass):
@@ -131,7 +165,7 @@ def generate_cluster(self, totalMass):
         # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
-            uniX = self.rng.random(int(newStarCount))
+            uniX = rng.random(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
 
@@ -148,11 +182,11 @@ def generate_cluster(self, totalMass):
                 MF = self._multi_props.multiplicity_fraction(newMasses)
                 CSF = self._multi_props.companion_star_fraction(newMasses)
 
-                newIsMultiple = self.rng.random(int(newStarCount)) < MF
+                newIsMultiple = rng.random(int(newStarCount)) < MF
 
                 # Function to calculate multiple systems more efficiently
                 # start_calc = time.time()
-                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newIsMultiple, CSF, MF)
+                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newIsMultiple, CSF, MF, rng=rng)
                 # end_calc = time.time()
                 # print('Time taken for calc_multi: ', end_calc - start_calc)
                 newTotalMassTally = newSystemMasses.sum()
@@ -218,17 +252,18 @@ def generate_cluster(self, totalMass):
 
         return (masses, isMultiple, compMasses, systemMasses)
 
-    def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
+    def calc_multi(self, newMasses, newIsMultiple, CSF, MF, rng=None):
         """
         Helper function to calculate multiples more efficiently.
         We will use array operations as much as possible
         """
+        rng = self.rng if rng is None else rng
         # Copy over the primary masses. Eventually add the companions.
         newSystemMasses = newMasses.copy()
 
         # Identify multiple systems, calculate number of companions for each
         multiple_idx = np.where(newIsMultiple)[0]
-        comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
+        comp_nums = 1 + rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
         if self._multi_props.companion_max:
             too_many = np.where(comp_nums > self._multi_props.CSF_max)[0]
             comp_nums[too_many] = self._multi_props.CSF_max
@@ -242,7 +277,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
 
         for comp_num, comp_index in zip(comp_unique, comp_indices):
             # Calculate masses of companions
-            q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
+            q_values = self._multi_props.random_q(rng.random((len(comp_index), comp_num)))
             m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
             compMasses[multiple_idx[comp_index], :comp_num] = m_comp
 
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index cf6848db..63938db8 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -92,9 +92,9 @@ class Cluster(object):
         no compact remnants are produced.
 
     seed: int
-        If set to non-None, all random sampling will be seeded with the
-        specified seed, forcing identical output.
-        Default None
+        Seed for the random number generator numpy.random.default_rng(seed).
+        All random functions in the class will use this generator, 
+        unless a different generator is passed in as an argument to the function, by default None.
 
     vebose: boolean
         True for verbose output.
@@ -133,24 +133,56 @@ class ResolvedCluster(Cluster):
     cluster_mass: float
         Total initial mass of the cluster, in M_sun
 
-    ifmr: ifmr object or None
+    ifmr: ifmr object, optional
         If ifmr object is defined, will create compact remnants
         produced by the cluster at the given isochrone age. Otherwise,
         no compact remnants are produced.
+        By default None.
 
-    keep_low_mass_stars: boolean (default False)
+    keep_low_mass_stars: boolean, optional
         If True, the cluster will not cut out stars below the isochrone grid
         on initial mass. They are assigned a current mass equal to their initial
         mass, a phase of 98, and no other evolutionary properties or photometry.
         If False, stars below the isochrone initial mass limit are cut out.
+        By default False.
 
-    seed: int
-        If set to non-None, all random sampling will be seeded with the
-        specified seed, forcing identical output.
-        Default None
+    seed: int, optional
+        Seed for the random number generator numpy.random.default_rng(seed).
+        All random functions in the class will use this generator, 
+        unless a different generator is passed in as an argument to the function, by default None.
 
-    vebose: boolean
+    vebose: boolean, optional
         True for verbose output.
+
+    Attributes
+    ----------
+    star_systems: astropy.table.Table
+        Table containing the properties of the primary stars (or stellar systems, if multiplicity is used). The columns include:
+            mass: primary mass
+            isMultiple: boolean for whether the star is in a multiple system
+            systemMass: total initial mass of the stellar system (primary + companions)
+            Teff: effective temperature of the star
+            L: luminosity of the star in L_sun
+            logg: surface gravity of the star in cgs
+            isWR: boolean for whether the star is a Wolf-Rayet star
+            mass_current: current mass of the star
+            phase: evolutionary phase of the star, as defined by the isochrone model
+            metallicity: metallicity of the star
+            filter columns: magnitude of the star in each filter defined by the isochrone model
+    
+    companions: astropy.table.Table (only if multiplicity is used in the IMF object)
+        Table containing the properties of the companion stars. The columns include:
+            system_idx: index of the stellar system this companion belongs to, which can be used to match to the star_systems table
+            mass: initial mass of the companion star
+            Teff: effective temperature of the companion star
+            L: luminosity of the companion star in L_sun
+            logg: surface gravity of the companion star in cgs
+            isWR: boolean for whether the companion star is a Wolf-Rayet star
+            mass_current: current mass of the companion star
+            phase: evolutionary phase of the companion star, as defined by the isochrone model
+            metallicity: metallicity of the companion star
+            filter columns: magnitude of the companion star in each filter defined by the isochrone model
+            If multiplicity properties are defined in the IMF object, additional columns for those properties (e.g., log_a, e, i, Omega, omega) are included.
     """
     def __init__(self, iso, imf, cluster_mass, ifmr=None, verbose=True,
                      seed=None, keep_low_mass_stars=False):
@@ -659,21 +691,55 @@ class ResolvedClusterDiffRedden(ResolvedCluster):
         from which the delta_AKs values will be drawn from for each individual
         system.
 
-    ifmr: ifmr object or None
+    ifmr: ifmr object, optional
         If ifmr object is defined, will create compact remnants
         produced by the cluster at the given isochrone age. Otherwise,
         no compact remnants are produced.
 
-    seed: int
-        If set to non-None, all random sampling will be seeded with the
-        specified seed, forcing identical output.
-        Default None
+    seed: int, optional
+        Seed for the random number generator numpy.random.default_rng(seed).
+        All random functions in the class will use this generator, 
+        unless a different generator is passed in as an argument to the function, by default None.
 
-    vebose: boolean
+
+    vebose: boolean, optional
         True for verbose output.
+
+
+    Attributes
+    ----------
+    star_systems: astropy.table.Table
+        Table containing the properties of the primary stars (or stellar systems, if multiplicity is used). The columns include:
+            mass: primary mass
+            isMultiple: boolean for whether the star is in a multiple system
+            systemMass: total initial mass of the stellar system (primary + companions)
+            Teff: effective temperature of the star
+            L: luminosity of the star in L_sun
+            logg: surface gravity of the star in cgs
+            isWR: boolean for whether the star is a Wolf-Rayet star
+            mass_current: current mass of the star
+            phase: evolutionary phase of the star, as defined by the isochrone model
+            metallicity: metallicity of the star
+            filter columns: magnitude of the star in each filter defined by the isochrone model, which have been perturbed by differential reddening according to the delta_AKs parameter
+            AKs_f: the final AKs value for each star, which is the original AKs value from the isochrone plus the differential reddening drawn from the Gaussian distribution defined by delta_AKs
+
+    companions: astropy.table.Table, optional
+        If multiplicity is used, this table contains the properties of the companion stars. The columns include:
+            system_idx: index of the primary star's system in the star_systems table
+            mass: mass of the companion star
+            Teff: effective temperature of the companion star
+            L: luminosity of the companion star in L_sun
+            logg: surface gravity of the companion star in cgs
+            isWR: boolean for whether the companion star is a Wolf-Rayet star
+            mass_current: current mass of the companion star
+            phase: evolutionary phase of the companion star, as defined by the isochrone model
+            metallicity: metallicity of the companion star
+            filter columns: magnitude of the companion star in each filter defined by the isochrone model, which have been perturbed by differential reddening according to the delta_AKs parameter
+            If multiplicity properties are defined in the IMF object, additional columns for those properties (e.g., log_a, e, i, Omega, omega) are included.
+    
     """
     def __init__(self, iso, imf, cluster_mass, deltaAKs,
-                 ifmr=None, verbose=False, seed=None, keep_low_mass_stars=False):
+                 ifmr=None, verbose=False, seed=None):
 
         ResolvedCluster.__init__(self, iso, imf, cluster_mass, ifmr=ifmr, verbose=verbose,
                                      seed=seed)
@@ -743,8 +809,23 @@ class UnresolvedCluster(Cluster):
         Define the minumum and maximum wavelengths of the final
         output spectrum, in Angstroms. Array should be [min_wave, max_wave]
 
-    vebose: boolean
-        True for verbose output.
+    vebose: boolean, optional
+        True for verbose output, by default False.
+
+    Attributes
+    ----------
+    mass_all: numpy array
+        The mass of each star in the cluster, in M_sun.
+    spec_list: list of spectra
+        List of the spectra of each star in the cluster, resampled to a common wavelength grid
+    spec_list_trim: list of spectra
+        List of the spectra of each star in the cluster, resampled to a common wavelength grid and trimmed to the wavelength range defined by wave_range
+    spec_tot_full: numpy array
+        The total spectrum of the cluster, obtained by summing the spectra of all stars in spec_list, before trimming to wave_range
+    spec_trim: numpy array
+        The total spectrum of the cluster, obtained by summing the spectra of all stars in spec_list_trim, which have been trimmed to the wavelength range defined by wave_range
+    wave_trim: numpy array
+        The wavelength grid corresponding to spec_trim, which is the same as the wavelength grid of the individual spectra in spec_list_trim
     """
     def __init__(self, iso, imf, cluster_mass,
                  wave_range=[3000, 52000], verbose=False):
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index a39a6505..d37a8077 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1244,6 +1244,12 @@ def test_ResolvedCluster_random_state():
     imf_multi = multiplicity.MultiplicityUnresolved()
     imf_test = imf.IMF_broken_powerlaw(imf_limits, imf_powers, multiplicity=imf_multi)
 
+    # Test that the same random seed produces the same cluster
+    result1 = imf_test.generate_cluster(cluster_mass, rng=np.random.default_rng(seed=42))
+    result2 = imf_test.generate_cluster(cluster_mass, rng=np.random.default_rng(seed=42))
+    np.testing.assert_equal(result1, result2)
+
+    # Test that two clusters generated with the same seed have the same star systems and companions
     cluster1 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
     cluster2 = syn.ResolvedCluster(iso, imf_test, cluster_mass, seed=42)
     np.testing.assert_array_equal(cluster1.star_systems, cluster2.star_systems)

From 2b9e77ef74fb269f846b35b95de3c5c8b2759bd0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 25 Feb 2026 16:10:23 -0800
Subject: [PATCH 39/55] Moved IMF testing under spisea/tests

---
 spisea/imf/tests/__init__.py                |  1 -
 spisea/{imf => }/tests/test_imf.py          | 67 ++++++++-----------
 spisea/{imf => }/tests/test_multiplicity.py | 74 +++++++++------------
 3 files changed, 58 insertions(+), 84 deletions(-)
 delete mode 100755 spisea/imf/tests/__init__.py
 rename spisea/{imf => }/tests/test_imf.py (92%)
 rename spisea/{imf => }/tests/test_multiplicity.py (85%)

diff --git a/spisea/imf/tests/__init__.py b/spisea/imf/tests/__init__.py
deleted file mode 100755
index 8b137891..00000000
--- a/spisea/imf/tests/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-
diff --git a/spisea/imf/tests/test_imf.py b/spisea/tests/test_imf.py
similarity index 92%
rename from spisea/imf/tests/test_imf.py
rename to spisea/tests/test_imf.py
index 571f6edc..5f465747 100755
--- a/spisea/imf/tests/test_imf.py
+++ b/spisea/tests/test_imf.py
@@ -1,11 +1,10 @@
 import numpy as np
 import time
 import pdb
+import cProfile
+from spisea.imf import imf, multiplicity
 
 def test_generate_cluster():
-    from .. import imf
-    from .. import multiplicity
-    
     # Make multiplicity object
     imf_multi = multiplicity.MultiplicityUnresolved()
 
@@ -32,8 +31,6 @@ def test_generate_cluster():
     return
 
 def test_prim_power():
-    from .. import imf
-
     #mass_limits = np.array([0.1, 1.0, 100.0])
     #powers = np.array([-2.0, -1.8])
     mass_limits = np.array([1.0, 100.0])
@@ -60,9 +57,6 @@ def test_prim_power():
     return
 
 def test_xi():
-    from .. import imf
-
-    import cProfile, pstats, io
     #from pstats import SortKey
     pr = cProfile.Profile()
 
@@ -72,14 +66,14 @@ def test_xi():
 
     ##########
     #
-    # Test validity of returned values. 
-    # 
+    # Test validity of returned values.
+    #
     ##########
     N_size = 10
     m = np.linspace(0.2, 20, N_size)
     val_good = np.array([1.6206566 , 0.26895718, 0.10135922, 0.05639448, 0.03703704,
                          0.0243668 , 0.01613091, 0.01137139, 0.00839526, 0.00642142])
-    
+
     val_test = np.zeros(len(m), dtype=float)
     for ii in range(len(m)):
         val_test[ii] = imf_tmp.xi(m[ii])
@@ -90,26 +84,26 @@ def test_xi():
     ##########
     #
     # Performance testing
-    # 
+    #
     ##########
     t1 = time.time()
     # pr.enable()
-    
+
     # Run a time test
     N_size = int(1e4)
     m = np.random.uniform(1.1, 99.0, size=N_size)
     foo1 = imf_tmp.xi(m)
-    
+
     # pr.disable()
     t2 = time.time()
 
     print('test_xi() runtime = {0:.3f} s for {1:d} masses'.format(t2 - t1, N_size))
-    
+
     # s = io.StringIO()
     # sortby = SortKey.CUMULATIVE
     # ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
     # ps.print_stats()
-    # print(s.getvalue())    
+    # print(s.getvalue())
 
     return
 
@@ -118,9 +112,6 @@ def test_xi2():
     Test that xi() produces the correct probability for
     a given slope.
     """
-    from .. import imf
-
-    import cProfile, pstats, io
     #from pstats import SortKey
     pr = cProfile.Profile()
 
@@ -173,13 +164,10 @@ def test_xi2():
 
     return
 
-    
 
 
-def test_mxi():
-    from .. import imf
 
-    import cProfile, pstats, io
+def test_mxi():
     #from pstats import SortKey
     pr = cProfile.Profile()
 
@@ -189,8 +177,8 @@ def test_mxi():
 
     ##########
     #
-    # Test validity of returned values. 
-    # 
+    # Test validity of returned values.
+    #
     ##########
     N_size = 10
     m = np.linspace(0.2, 20, N_size)
@@ -207,11 +195,11 @@ def test_mxi():
     ##########
     #
     # Performance testing
-    # 
+    #
     ##########
     t1 = time.time()
     # pr.enable()
-    
+
     # Run a time test
     N_size = int(1e4)
     m = np.random.uniform(1.1, 99.0, size=N_size)
@@ -222,29 +210,26 @@ def test_mxi():
     t2 = time.time()
 
     print('test_mxi() runtime = {0:.3f} s for {1:d} masses'.format(t2 - t1, N_size))
-    
+
     # s = io.StringIO()
     # sortby = SortKey.CUMULATIVE
     # ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
     # ps.print_stats()
-    # print(s.getvalue())    
+    # print(s.getvalue())
 
     return
 
 def test_theta_closed():
-    from .. import imf
-
-    import cProfile, pstats, io
     #from pstats import SortKey
-    
+
     mass_limits = np.array([0.1, 1.0, 10.0, 100.0])
     powers = np.array([-0.3, -1.5, -2.3])
     imf_tmp = imf.IMF_broken_powerlaw(mass_limits, powers)
 
     ##########
     #
-    # Test validity of returned values. 
-    # 
+    # Test validity of returned values.
+    #
     ##########
     N_size = 10
     m = np.linspace(0.2, 20, N_size)
@@ -265,22 +250,22 @@ def test_theta_closed():
 
     np.testing.assert_equal(val_test, val_good)
 
-    
+
 
     ##########
     #
     # Speed tests and performance profiling.
-    # 
+    #
     ##########
     N_size = 10000
     m = np.linspace(1.1, 99, N_size)
-    
+
     tmp = np.zeros((len(m), len(powers)), dtype=float)
 
     t1 = time.time()
     # pr = cProfile.Profile()
     # pr.enable()
-    
+
     for ii in range(len(m)):
         tmp[ii] = imf.theta_closed(m[ii] - imf_tmp._m_limits_low)
 
@@ -288,7 +273,7 @@ def test_theta_closed():
     t2 = time.time()
 
     print('Runtime = {0:.3f} s for {1:d} masses'.format(t2 - t1, N_size))
-    
+
     # s = io.StringIO()
     # sortby = SortKey.CUMULATIVE
     # ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
@@ -297,4 +282,4 @@ def test_theta_closed():
 
 
     return
-    
+
diff --git a/spisea/imf/tests/test_multiplicity.py b/spisea/tests/test_multiplicity.py
similarity index 85%
rename from spisea/imf/tests/test_multiplicity.py
rename to spisea/tests/test_multiplicity.py
index 3a9dc9b7..9df0776d 100755
--- a/spisea/imf/tests/test_multiplicity.py
+++ b/spisea/tests/test_multiplicity.py
@@ -1,12 +1,12 @@
 import numpy as np
 import time
-    
+import spisea
+from spisea.imf import imf, multiplicity
+
 def test_create_MultiplicityUnresolved():
     """
     Tests creating and accessing a MultiplicityUnresolved object.
     """
-    from .. import multiplicity
-
     # All default parameters -- check their values
     mu1 = multiplicity.MultiplicityUnresolved()
     assert mu1.MF_amp == 0.44
@@ -18,28 +18,26 @@ def test_create_MultiplicityUnresolved():
     assert mu1.q_min == 0.01
 
     # Test setting different parameters
-    mu2 = multiplicity.MultiplicityUnresolved(MF_amp=0.4, 
+    mu2 = multiplicity.MultiplicityUnresolved(MF_amp=0.4,
                                              MF_power=0.4,
-                                             CSF_amp=0.4, 
-                                             CSF_power=0.4, 
+                                             CSF_amp=0.4,
+                                             CSF_power=0.4,
                                              CSF_max=4,
-                                             q_power=0.4, 
+                                             q_power=0.4,
                                              q_min=0.04)
-    assert mu2.MF_amp == 0.4 
+    assert mu2.MF_amp == 0.4
     assert mu2.MF_pow == 0.4
-    assert mu2.CSF_amp == 0.4 
-    assert mu2.CSF_pow == 0.4 
+    assert mu2.CSF_amp == 0.4
+    assert mu2.CSF_pow == 0.4
     assert mu2.CSF_max == 4
-    assert mu2.q_pow == 0.4 
+    assert mu2.q_pow == 0.4
     assert mu2.q_min == 0.04
 
 def test_multiplicity_fraction():
     """
     Test creating a MultiplicityUnresolved object and getting
     the multiplicity fraction out.
-    """    
-    from spisea.imf import multiplicity
-    
+    """
     # First set of multiplicity parameters
     mu1 = multiplicity.MultiplicityUnresolved()
 
@@ -57,14 +55,14 @@ def test_multiplicity_fraction():
                                              CSF_amp=0.4, CSF_power=0.4, CSF_max=4,
                                              q_power=0.4, q_min=0.04)
 
-    mf2_1 = mu1.multiplicity_fraction(1.0)
-    np.testing.assert_almost_equal(mf2_1, 0.44, decimal=2)
+    mf2_1 = mu2.multiplicity_fraction(1.0)
+    np.testing.assert_almost_equal(mf2_1, 0.4, decimal=2)
 
-    mf2_2 = mu1.multiplicity_fraction(10.0)
+    mf2_2 = mu2.multiplicity_fraction(10.0)
     np.testing.assert_almost_equal(mf2_2, 1.0, decimal=2)
 
-    mf2_3 = mu1.multiplicity_fraction(0.1)
-    np.testing.assert_almost_equal(mf2_3, 0.136, decimal=2)
+    mf2_3 = mu2.multiplicity_fraction(0.1)
+    np.testing.assert_almost_equal(mf2_3, 0.159, decimal=2)
 
 
 def test_multiplicity_fraction_array():
@@ -72,8 +70,6 @@ def test_multiplicity_fraction_array():
     Test multiplicity_fraction() on the MultiplicityUnresolved object
     where the inputs and outputs are in array form.
     """
-    from spisea.imf import multiplicity
-    
     # First set of multiplicity parameters
     mu1 = multiplicity.MultiplicityUnresolved()
 
@@ -83,14 +79,12 @@ def test_multiplicity_fraction_array():
     np.testing.assert_almost_equal(mf_array[0], 0.44, decimal=2)
     np.testing.assert_almost_equal(mf_array[1], 1.0, decimal=2)
     np.testing.assert_almost_equal(mf_array[2], 0.136, decimal=2)
-    
-    
+
+
 def test_companion_star_fraction():
     """
     Test the companion_star fraction on the MultiplicityUnresolved object.
     """
-    from spisea.imf import multiplicity
-
     # First set of multiplicity parameters
     mu1 = multiplicity.MultiplicityUnresolved()
 
@@ -120,12 +114,10 @@ def test_companion_star_fraction():
 
 def test_resolvedmult():
     """
-    Test creating a MultiplicityResolvedDK object 
+    Test creating a MultiplicityResolvedDK object
     and that the parameters it's populated with are correct.
     """
     from spisea import synthetic, evolution, atmospheres, reddening, ifmr
-    from spisea.imf import imf, multiplicity
-    
     # Fetch isochrone
     logAge = 6.70 # Age in log(years)
     AKs = 1.0 # Ks filter extinction in mags
@@ -135,56 +127,54 @@ def test_resolvedmult():
     evo_merged = evolution.MISTv1()
     redlaw = reddening.RedLawCardelli(3.1) # Rv = 3.1
     filt_list = ['nirc2,J', 'nirc2,Kp']
-    
+
     startTime = time.time()
 
     iso_merged = synthetic.IsochronePhot(logAge, AKs, dist, metallicity=metallicity,
                                  evo_model=evo_merged, atm_func=atm_func,
                                  filters=filt_list, red_law=redlaw,
-                                 mass_sampling=3)
+                                 mass_sampling=3, iso_dir=f'{spisea.__path__[0]}/tests/isochrones')
     print('Constructed isochrone: %d seconds' % (time.time() - startTime))
-    
-    # Now we can make the cluster. 
+
+    # Now we can make the cluster.
     clust_mtot = 10**4.
     clust_multiplicity = multiplicity.MultiplicityResolvedDK()
 
     # Multiplicity is defined in the IMF object
     clust_imf_Mult = imf.Kroupa_2001(multiplicity=clust_multiplicity)
-    
+
     # Make clusters
     clust_Mult = synthetic.ResolvedCluster(iso_merged, clust_imf_Mult, clust_mtot)
 
     clust_Mult_ss = clust_Mult.star_systems
-    
+
     print('Constructed cluster: %d seconds' % (time.time() - startTime))
-    
+
     #check if columns were created
     assert 'log_a' in clust_Mult.companions.colnames
     assert 'e' in clust_Mult.companions.colnames
     assert 'i' in clust_Mult.companions.colnames
     assert 'Omega' in clust_Mult.companions.colnames
     assert 'omega' in clust_Mult.companions.colnames
-    
+
     #check values are in correct range
     assert all(10**i<= 2000 and 10**i>= 0 for i in clust_Mult.companions['log_a']) #max separation is 2000 AU
     assert all(i<= 1 and i>= 0 for i in clust_Mult.companions['e'])
     assert all(i<= 180 and i>= 0 for i in clust_Mult.companions['i'])
     assert all(i<= 360 and i>= 0 for i in clust_Mult.companions['omega'])
     assert all(i<= 360 and i>= 0 for i in clust_Mult.companions['Omega'])
-    
+
     #checks sign for inclination is being randomly genarated
     assert any(i > 90 for i in clust_Mult.companions['i']) and any(i < 90 for i in clust_Mult.companions['i'])
-    
+
     #checks eccentricity follows f(e) = 2e pdf
     n, bins = np.histogram(clust_Mult.companions['e'], density = True)
     bin_centers = 0.5*(bins[1:] + bins[:-1])
     assert all(np.abs(i) < 0.3 for i in 2*bin_centers - n)
-    
+
     #checks shape of inclination histogram is sin(i)
     n, bins = np.histogram(clust_Mult.companions['i'])
     bin_centers = 0.5*(bins[1:] + bins[:-1])
     assert all(np.abs(i) < 0.15 for i in n/max(n) - np.sin(np.pi*bin_centers/180))
-    
-    return
 
-    
+    return

From 138ca290dc1e31a6ced5bbae710ae57ec667003d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 25 Feb 2026 16:12:29 -0800
Subject: [PATCH 40/55] Optimized import and removed unused imports

---
 spisea/synthetic.py            | 46 +++++++++++++---------------------
 spisea/tests/test_models.py    | 24 ++++++++++--------
 spisea/tests/test_synthetic.py |  2 +-
 3 files changed, 31 insertions(+), 41 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index ac25af93..ad0c781a 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1,33 +1,21 @@
+import os
+import time
+import math
+import scipy
+import inspect
+import warnings
 import numpy as np
 import pylab as plt
-from spisea import reddening
-from spisea import evolution
+import matplotlib.pyplot as plt
+from spisea import reddening, evolution, filters
 from spisea import atmospheres as atm
-from spisea import filters
-from spisea.imf import imf, multiplicity
-from scipy import interpolate
-from scipy import stats
-from scipy.special import erf
+from scipy.spatial import cKDTree as KDTree
+from spisea.imf import multiplicity
 from pysynphot import spectrum
 from pysynphot import ObsBandpass
 from pysynphot import observation as obs
-import pysynphot
 from astropy import constants, units
-from astropy.table import Table, Column, MaskedColumn
-import pickle
-import time, datetime
-import math
-import os, glob
-import tempfile
-import scipy
-import matplotlib
-import matplotlib.pyplot as plt
-import time
-import warnings
-import pdb
-from scipy.spatial import cKDTree as KDTree
-import inspect
-import astropy.modeling
+from astropy.table import Table, Column
 
 default_evo_model = evolution.MISTv1()
 default_red_law = reddening.RedLawNishiyama09()
@@ -525,12 +513,12 @@ def _make_companions_table(self, star_systems, compMass):
                 bad = np.where( (companions_phase_non_nan > 5) &
                                 (companions_phase_non_nan < 101) &
                                 (companions_phase_non_nan != 9) &
-                                (companions_phase_non_nan != -99))
+                                (companions_phase_non_nan != -99))[0]
                 # Print warning, if desired
                 verbose=False
                 if verbose:
-                    for ii in range(len(bad[0])):
-                        print('WARNING: changing phase {0} to 5'.format(companions['phase'][bad[0][ii]]))
+                    for ii in range(len(bad)):
+                        print('WARNING: changing phase {0} to 5'.format(companions['phase'][bad[ii]]))
                 companions['phase'][bad] = 5
 
                 for filt in self.filt_names:
@@ -550,8 +538,8 @@ def _make_companions_table(self, star_systems, compMass):
 
                     # If *both* objects are dark, then keep the magnitude
                     # as np.nan. Otherwise, add fluxes together
-                    good = np.where( (f1 != 0) | (f2 != 0) )
-                    bad = np.where( (f1 == 0) & (f2 == 0) )
+                    good = np.where( (f1 != 0) | (f2 != 0) )[0]
+                    bad = np.where( (f1 == 0) & (f2 == 0) )[0]
 
                     star_systems[filt][idx[good]] = -2.5 * np.log10(f1[good] + f2[good])
                     star_systems[filt][idx[bad]] = np.nan
@@ -576,7 +564,7 @@ def _make_companions_table(self, star_systems, compMass):
 
             # Drop remnants where it is not relevant (e.g. not a compact object or
             # outside mass range IFMR is defined for)
-            good = np.where(r_id_tmp > 0)
+            good = np.where(r_id_tmp > 0)[0]
             cdx_rem_good = cdx_rem[good]
 
             companions['mass_current'][cdx_rem_good] = r_mass_tmp[good]
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index 5dc85282..5f81438d 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -1,5 +1,5 @@
 # Test functions for the different stellar evolution and atmosphere models
-from spisea import evolution
+from spisea import evolution, atmospheres, synthetic
 import numpy as np
 import pdb
 
@@ -10,8 +10,6 @@ def test_evo_model_grid_num():
     are working). Try it on one evolution model here;
     we'll test on all evo models in another function.
     """
-    from spisea import evolution
-
     # Make MIST evolution model, check evo grid variables
     evo = evolution.MISTv1()
     assert isinstance(evo.evo_grid_min, float)
@@ -93,11 +91,17 @@ def test_atmosphere_models():
     """
     Test the rebinned atmosphere models used for synthetic photometry
     """
-    from spisea import atmospheres as atm
-
     # Array of atmospheres
-    atm_arr = [atm.get_merged_atmosphere, atm.get_castelli_atmosphere, atm.get_phoenixv16_atmosphere, atm.get_BTSettl_2015_atmosphere,
-                   atm.get_BTSettl_atmosphere, atm.get_kurucz_atmosphere, atm.get_phoenix_atmosphere, atm.get_wdKoester_atmosphere]
+    atm_arr = [
+        atmospheres.get_merged_atmosphere, 
+        atmospheres.get_castelli_atmosphere, 
+        atmospheres.get_phoenixv16_atmosphere, 
+        atmospheres.get_BTSettl_2015_atmosphere,
+        atmospheres.get_BTSettl_atmosphere, 
+        atmospheres.get_kurucz_atmosphere, 
+        atmospheres.get_phoenix_atmosphere, 
+        atmospheres.get_wdKoester_atmosphere
+    ]
 
     # Array of metallicities
     metals_range = [-2.0, 0, 0.15]
@@ -121,7 +125,7 @@ def test_atmosphere_models():
 
     # Test get_merged_atmospheres at different temps
     temp_range = [2000, 3500, 4000, 5250, 6000, 12000]
-    atm_func = atm.get_merged_atmosphere
+    atm_func = atmospheres.get_merged_atmosphere
     for ii in metals_range:
         for jj in temp_range:
             try:
@@ -135,7 +139,7 @@ def test_atmosphere_models():
     # Test get_bb_atmosphere at different temps
     # This func only requests temp
     temp_range = [2000, 3500, 4000, 5250, 6000, 12000]
-    atm_func = atm.get_bb_atmosphere
+    atm_func = atmospheres.get_bb_atmosphere
     for jj in temp_range:
         try:
             test = atm_func(temperature=jj, verbose=True)
@@ -150,8 +154,6 @@ def test_filters():
     """
     Test to make sure all of the filters work as expected
     """
-    from spisea import synthetic
-
     # Define vega spectrum
     vega = synthetic.Vega()
 
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 386faf58..94914add 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -161,7 +161,7 @@ def test_IsochronePhot(plot=False):
     )
     endTime = time.time()
     print('IsochronePhot generated in: %d seconds' % (endTime - startTime))
-    # Typically takes 120 seconds if file is regenerated.
+    # Typically takes 40 seconds if file is regenerated.
     # Limited by pysynphot.Icat call in atmospheres.py
 
     assert iso.points.meta['LOGAGE'] == logAge

From bf01acb6a6468958ba0fe3fff9c278f45a8a3c4e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Wed, 25 Feb 2026 16:50:52 -0800
Subject: [PATCH 41/55] Removed the extra parameter rng in generate_cluster and
 calc_multi, as it can be set before running the function

---
 spisea/imf/imf.py              | 39 +++++++++++++---------------------
 spisea/tests/test_synthetic.py |  6 ++++--
 2 files changed, 19 insertions(+), 26 deletions(-)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 4f2e20a5..8e6e1454 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -39,7 +39,7 @@ class IMF(object):
     
     seed : int, optional
         Seed for the random generator numpy.random.default_rng(seed).
-        All random functions in the class will use this generator, unless a different generator is passed in as an argument to the function. Default None.
+        All random functions in the class will use this generator, by default None.
         Behavior:
         ::
 
@@ -61,11 +61,12 @@ class IMF(object):
             result3 = rng.random(1)
             result4 = rng.random(1)
 
-        If identical output is desired over each run, the same generator can be passed in as an argument to the generate_cluster function, e.g.
+        If identical output is desired over each run, the random state can be reset before running the function, e.g.
         ::
-
-            result1 = imf.generate_cluster(rng=np.random.default_rng(42))            
-            result2 = imf.generate_cluster(rng=np.random.default_rng(42))
+            imf.rng = np.random.default_rng(seed=42)
+            result1 = imf.generate_cluster()
+            imf.rng = np.random.default_rng(seed=42)
+            result2 = imf.generate_cluster()
 
         In this case, result1==result2
 
@@ -92,8 +93,7 @@ def __init__(self, massLimits=np.array([0.1,150]), multiplicity=None, seed=None)
 
         return
 
-
-    def generate_cluster(self, totalMass, rng=None):
+    def generate_cluster(self, totalMass):
         """
         Generate a cluster of stellar systems with the specified IMF.
 
@@ -113,11 +113,6 @@ def generate_cluster(self, totalMass, rng=None):
         totalMass : float
             The total mass of the cluster (including companions) in solar masses.
 
-        rng: numpy.random.Generator, optional
-            If not provided, will use the random number generator specified by the seed in the IMF instance.
-            If provided, will override the random generator in the IMF instance and use the specified generator,
-            by default None.
-
         Returns
         -------
         masses : numpy float array
@@ -134,8 +129,6 @@ def generate_cluster(self, totalMass, rng=None):
             Array of total system masses (primary + companions) for each primary star.
 
         """
-        rng = self.rng if rng is None else rng
-
         initial_mass_limit = self._mass_limits[-1]
 
         if (self._mass_limits[-1] > totalMass):
@@ -165,7 +158,7 @@ def generate_cluster(self, totalMass, rng=None):
         # start_while = time.time()
         while totalMassTally < totalMass:
             # Generate a random number array.
-            uniX = rng.random(int(newStarCount))
+            uniX = self.rng.random(int(newStarCount))
             # Convert into the IMF from the inverted CDF
             newMasses = self.dice_star_cl(uniX)
 
@@ -182,11 +175,11 @@ def generate_cluster(self, totalMass, rng=None):
                 MF = self._multi_props.multiplicity_fraction(newMasses)
                 CSF = self._multi_props.companion_star_fraction(newMasses)
 
-                newIsMultiple = rng.random(int(newStarCount)) < MF
+                newIsMultiple = self.rng.random(int(newStarCount)) < MF
 
                 # Function to calculate multiple systems more efficiently
                 # start_calc = time.time()
-                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newIsMultiple, CSF, MF, rng=rng)
+                newCompMasses, newSystemMasses, newIsMultiple = self.calc_multi(newMasses, newIsMultiple, CSF, MF)
                 # end_calc = time.time()
                 # print('Time taken for calc_multi: ', end_calc - start_calc)
                 newTotalMassTally = newSystemMasses.sum()
@@ -252,18 +245,17 @@ def generate_cluster(self, totalMass, rng=None):
 
         return (masses, isMultiple, compMasses, systemMasses)
 
-    def calc_multi(self, newMasses, newIsMultiple, CSF, MF, rng=None):
+    def calc_multi(self, newMasses, newIsMultiple, CSF, MF):
         """
         Helper function to calculate multiples more efficiently.
         We will use array operations as much as possible
         """
-        rng = self.rng if rng is None else rng
         # Copy over the primary masses. Eventually add the companions.
         newSystemMasses = newMasses.copy()
 
         # Identify multiple systems, calculate number of companions for each
         multiple_idx = np.where(newIsMultiple)[0]
-        comp_nums = 1 + rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
+        comp_nums = 1 + self.rng.poisson((CSF[multiple_idx] / MF[multiple_idx]) - 1)
         if self._multi_props.companion_max:
             too_many = np.where(comp_nums > self._multi_props.CSF_max)[0]
             comp_nums[too_many] = self._multi_props.CSF_max
@@ -277,7 +269,7 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF, rng=None):
 
         for comp_num, comp_index in zip(comp_unique, comp_indices):
             # Calculate masses of companions
-            q_values = self._multi_props.random_q(rng.random((len(comp_index), comp_num)))
+            q_values = self._multi_props.random_q(self.rng.random((len(comp_index), comp_num)))
             m_comp = np.multiply(q_values, np.transpose([primary[comp_index]]))
             compMasses[multiple_idx[comp_index], :comp_num] = m_comp
 
@@ -288,7 +280,6 @@ def calc_multi(self, newMasses, newIsMultiple, CSF, MF, rng=None):
 
         return compMasses, newSystemMasses, newIsMultiple
 
-
 class IMF_broken_powerlaw(IMF):
     """
     Initialize a multi-part power-law with N parts. Each part of the
@@ -318,8 +309,8 @@ def __init__(self, mass_limits, powers, multiplicity=None, seed=None):
         if len(mass_limits) != len(powers) + 1:
             msg = 'Incorrect specification of multi-part powerlaw.\n'
             msg += '    len(massLimts) != len(powers)+1\n'
-            msg += '    len(massLimits) = \n' + len(mass_limits)
-            msg += '    len(powers) = \n' + len(powers)
+            msg += '    len(massLimits) = \n' + str(len(mass_limits))
+            msg += '    len(powers) = \n' + str(len(powers))
 
             raise RuntimeError(msg)
         mass_limits = np.atleast_1d(mass_limits)
diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 94914add..72331850 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1249,8 +1249,10 @@ def test_ResolvedCluster_random_state():
     imf_test = imf.IMF_broken_powerlaw(imf_limits, imf_powers, multiplicity=imf_multi)
 
     # Test that the same random seed produces the same cluster
-    result1 = imf_test.generate_cluster(cluster_mass, rng=np.random.default_rng(seed=42))
-    result2 = imf_test.generate_cluster(cluster_mass, rng=np.random.default_rng(seed=42))
+    imf_test.rng = np.random.default_rng(seed=42)
+    result1 = imf_test.generate_cluster(cluster_mass)
+    imf_test.rng = np.random.default_rng(seed=42)
+    result2 = imf_test.generate_cluster(cluster_mass)
     np.testing.assert_equal(result1, result2)
 
     # Test that two clusters generated with the same seed have the same star systems and companions

From b2ea3fb3dbcd21e0ca56c80fba862fbe29b72b8c Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@berkeley.edu>
Date: Thu, 26 Feb 2026 10:24:55 +0100
Subject: [PATCH 42/55] started interp_AKs_grid setup with kwargs and variables

---
 spisea/evolution.py | 66 ++++++++++++++++++++++++---------------------
 spisea/synthetic.py | 11 +++++++-
 2 files changed, 46 insertions(+), 31 deletions(-)

diff --git a/spisea/evolution.py b/spisea/evolution.py
index fea75ab3..60e30887 100755
--- a/spisea/evolution.py
+++ b/spisea/evolution.py
@@ -66,8 +66,8 @@ class StellarEvolution(object):
     """
     Base Stellar evolution class.
 
-    Parameters
-    ----------
+    Subclasses must define the following parameters:
+    ------------------------------------------------
     model_dir: path
         Directory path to evolution model files
 
@@ -83,14 +83,11 @@ class StellarEvolution(object):
     model_version_name: string
         Name of the model class plus additional details like version
         numbers and rotation if relevant.
+
+    AKs_grid_age_list: list
+        Sparser list of ages to use for AKs interpolation grid
     """
-    def __init__(self, model_dir, age_list, mass_list, z_list):
-        self.model_dir = model_dir
-        self.z_list = z_list
-        self.mass_list = mass_list
-        self.age_list = age_list
-        self.model_version_name = "None"
-      
+    def __init__(self):
         return
     
 class Geneva(StellarEvolution):
@@ -100,22 +97,22 @@ def __init__(self):
         """
         self.model_version_name = "Geneva"
         # populate list of model masses (in solar masses)
-        mass_list = [(0.1 + i*0.005) for i in range(181)]
+        self.mass_list = [(0.1 + i*0.005) for i in range(181)]
         
         # define metallicity parameters for Geneva models
-        z_list = [0.01, 0.02, 0.03]
+        self.z_list = [0.01, 0.02, 0.03]
         
         # populate list of isochrone ages (log scale)
         age_list = [round(5.5 + 0.01*i, 2) for i in range(190)]
         age_list += [round(7.4 + 0.05*i, 2) for i in range(12)]
         age_list += [round(math.log10(1.e8*x), 2) for x in range(1, 10)]
         age_list += [round(math.log10(1.e9*x), 2) for x in range(1, 10)]
-        age_list = age_list
+        self.age_list = age_list
+        # Add AKs_grid_age_list after clarifying data set
+        #self.AKs_grid_age_list = np.linspace(5.5, , 0.05)
         
         # specify location of model files
-        model_dir = models_dir + 'geneva/'
-
-        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
+        self.model_dir = models_dir + 'geneva/'
 
         self.z_solar = 0.02
         self.z_file_map = {0.01: 'z01/', 0.02: 'z02/', 0.03: 'z03/'}
@@ -186,6 +183,7 @@ def __init__(self, rot=True):
         
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.0+0.005, 0.01)
+        self.AKs_grid_age_list = np.arange(6.0, 8.0+0.005, 0.05)
         
         # Specify location of model files
         self.model_dir = models_dir+'Ekstrom2012/'
@@ -420,7 +418,9 @@ def __init__(self):
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.6, 10.12+0.005, 0.01)
         self.age_list = np.append(6.40, self.age_list)
-        
+        self.AKs_grid_age_list = np.arange(6.6, 10.12+0.005, 0.05)
+        self.AKs_grid_age_list = [6.40] + list(self.AKs_grid_age_list) + [10.12]
+
         # Specify location of model files
         self.model_dir = models_dir+'ParsecV1.2s/'
 
@@ -568,6 +568,7 @@ def __init__(self):
         
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.01+0.005, 0.01)
+        self.AKs_grid_age_list = np.arange(6.0, 8.01+0.005, 0.05)
         
         # Specify location of model files
         self.model_dir = models_dir+'Pisa2011/'
@@ -728,6 +729,7 @@ def __init__(self):
         
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(6.0, 8.0+0.005, 0.01)
+        self.AKs_grid_age_list = np.arange(6.0, 8.0+0.005, 0.05)
         
         # Specify location of model files
         self.model_dir = models_dir+'Baraffe15/'
@@ -1048,6 +1050,8 @@ def __init__(self, version=1.2, synthpop_extension=False):
         
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(5.01, 10.30+0.005, 0.01)
+        self.AKs_grid_age_list = np.linspace(5.0,10.3,107)
+        self.AKs_grid_age_list[0] = 5.01
 
         # Set version directory
         self.version = version
@@ -1277,17 +1281,18 @@ def __init__(self, rot=True):
         else:
             self.model_version_name = "MergedBaraffePisaEkstromParsec-norot"
         # populate list of model masses (in solar masses)
-        mass_list = [(0.1 + i*0.005) for i in range(181)]
+        self.mass_list = [(0.1 + i*0.005) for i in range(181)]
         
         # define metallicity parameters for Geneva models
-        z_list = [0.015]
+        self.z_list = [0.015]
         
         # populate list of isochrone ages (log scale)
-        age_list = np.arange(6.0, 10.091, 0.01).tolist()
+        self.age_list = np.arange(6.0, 10.091, 0.01).tolist()
+        self.AKs_grid_age_list = np.arange(6.0, 10.091, 0.05).tolist()
+        self.AKs_grid_age_list += [10.09]
         
         # specify location of model files
-        model_dir = models_dir + 'merged/baraffe_pisa_ekstrom_parsec/'
-        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
+        self.model_dir = models_dir + 'merged/baraffe_pisa_ekstrom_parsec/'
         self.z_solar = 0.015
         
         # Switch to specify rotating/non-rotating models
@@ -1384,17 +1389,17 @@ def __init__(self, rot=True):
         else:
             self.model_version_name = "MergedPisaEkstromParsec-norot"
         # populate list of model masses (in solar masses)
-        mass_list = [(0.1 + i*0.005) for i in range(181)]
+        self.mass_list = [(0.1 + i*0.005) for i in range(181)]
         
         # define metallicity parameters for Geneva models
-        z_list = [0.015]
+        self.z_list = [0.015]
         
         # populate list of isochrone ages (log scale)
-        age_list = np.arange(6.0, 8.001, 0.01).tolist()
+        self.age_list = np.arange(6.0, 8.001, 0.01).tolist()
+        self.AKs_grid_age_list = np.arange(6.0, 8.001, 0.05).tolist()
         
         # specify location of model files
-        model_dir = models_dir + 'merged/pisa_ekstrom_parsec/'
-        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
+        self.model_dir = models_dir + 'merged/pisa_ekstrom_parsec/'
         self.z_solar = 0.015
 
         #Switch to specify rot/notot
@@ -1482,10 +1487,10 @@ def __init__(self):
         """
         self.model_version_name = "MergedSiessGenevaPadova"
         # populate list of model masses (in solar masses)
-        mass_list = [(0.1 + i*0.005) for i in range(181)]
+        self.mass_list = [(0.1 + i*0.005) for i in range(181)]
         
         # define metallicity parameters for Geneva models
-        z_list = [0.02]
+        self.z_list = [0.02]
         
         # populate list of isochrone ages (log scale)
         age_list = np.arange(5.5, 7.41, 0.01).tolist()
@@ -1506,10 +1511,11 @@ def __init__(self):
         age_list.append(9.60)
         age_list.append(9.70)
         age_list.append(9.78)
+        self.age_list = age_list
+        # TODO: define AKs_grid_age_list after clarifying isochrones
         
         # specify location of model files
-        model_dir = models_dir + 'merged/siess_meynetMaeder_padova/'
-        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
+        self.model_dir = models_dir + 'merged/siess_meynetMaeder_padova/'
         self.z_solar = 0.02
         
         # Metallicity map
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index e6390844..82f87a30 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1110,6 +1110,14 @@ class IsochronePhot(Isochrone):
         Define what filters the synthetic photometry
         will be calculated for, via the filter string
         identifier.
+
+    verbose : bool
+        Determines whether certain information gets printed
+
+    interp_AKs_grid : bool
+        If true, interpolate over existing grid for AKs values, instead of
+        re-generating all photometry from scratch. If False, re-generate all
+        photometry from scratch if the file does not already exist.
     """
     def __init__(self, logAge, AKs, distance,
                  metallicity=0.0,
@@ -1120,7 +1128,8 @@ def __init__(self, logAge, AKs, distance,
                  min_mass=None, max_mass=None, rebin=True, recomp=False,
                  filters=['ubv,U', 'ubv,B', 'ubv,V',
                           'ubv,R', 'ubv,I'],
-                verbose=False):
+                verbose=False,
+                interp_AKs_grid=False):
         self.metallicity = metallicity
 
         # Make the iso_dir, if it doesn't already exist

From fc5b408c5fc23ba0b5bfc18e8c2f9391f139a394 Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@berkeley.edu>
Date: Thu, 26 Feb 2026 17:03:17 +0100
Subject: [PATCH 43/55] add Gaia EDR3 filters

---
 docs/filters.rst                       |   9 +-
 filt_func/gaia/edr3/Gaia_passbands.txt | 781 +++++++++++++++++++++++++
 filt_func/gaia/edr3/ReadMe             | 134 +++++
 spisea/filters.py                      |  12 +-
 spisea/synthetic.py                    |   3 +
 spisea/tests/test_models.py            |   1 +
 6 files changed, 931 insertions(+), 9 deletions(-)
 create mode 100644 filt_func/gaia/edr3/Gaia_passbands.txt
 create mode 100644 filt_func/gaia/edr3/ReadMe

diff --git a/docs/filters.rst b/docs/filters.rst
index 918f27f4..b7254cb9 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -93,12 +93,13 @@ Example: ``'euclid,Y'``
 **GAIA**
 
 The `GAIA Space Telescope filters <https://www.cosmos.esa.int/web/gaia/iow_20180316>`_.
-Note that three sets are available: the pre-launch passbands used in DR1
+Note that four sets are available: the pre-launch passbands used in DR1
 (`Jordi+10
 <https://ui.adsabs.harvard.edu/abs/2010A%26A...523A..48J/abstract>`_),
-the passbands used for the DR2 published photometry, and
-the *revised* DR2 passbands based on the DR2 data (October 2017).
-ONLY THE REVISED DR2 PASSBANDS ARE SUPPORTED BY SPISEA.
+the passbands used for the DR2 published photometry, 
+the *revised* DR2 passbands based on the DR2 data (October 2017),
+and the EDR3 passbands from Riello et al (2021).
+ONLY THE REVISED DR2 and EDR3 PASSBANDS ARE SUPPORTED BY SPISEA.
 
 Filters: G, Gbp, Grp
 
diff --git a/filt_func/gaia/edr3/Gaia_passbands.txt b/filt_func/gaia/edr3/Gaia_passbands.txt
new file mode 100644
index 00000000..cc733830
--- /dev/null
+++ b/filt_func/gaia/edr3/Gaia_passbands.txt
@@ -0,0 +1,781 @@
+ 320.00  2.37366962e-08  2.34103325e-11           99.99           99.99           99.99           99.99
+ 321.00  1.57774443e-07  1.54036935e-10           99.99           99.99           99.99           99.99
+ 322.00  9.08554755e-07  8.78053229e-10           99.99           99.99           99.99           99.99
+ 323.00  4.78072331e-06  4.57325370e-09           99.99           99.99           99.99           99.99
+ 324.00  2.39428071e-05  2.26698640e-08           99.99           99.99           99.99           99.99
+ 325.00  1.03648276e-04  9.71310542e-08  3.87054116e-05  6.46801629e-08           99.99           99.99
+ 326.00  3.72280534e-04  3.45277531e-07  1.75771984e-04  2.88785224e-07           99.99           99.99
+ 327.00  1.09381843e-03  1.00397934e-06  6.49485416e-04  1.04897855e-06           99.99           99.99
+ 328.00  2.65174642e-03  2.40864304e-06  1.96690820e-03  3.12246976e-06           99.99           99.99
+ 329.00  5.45098195e-03  4.89953932e-06  5.01083084e-03  7.81780663e-06           99.99           99.99
+ 330.00  9.76875472e-03  8.68837731e-06  1.09458069e-02  1.67813576e-05           99.99           99.99
+ 331.00  1.56275855e-02  1.37527326e-05  2.07035425e-02  3.11867542e-05           99.99           99.99
+ 332.00  2.27741233e-02  1.98296421e-05  3.46967871e-02  5.13454545e-05           99.99           99.99
+ 333.00  3.07613294e-02  2.64991906e-05  5.25319303e-02  7.63595340e-05           99.99           99.99
+ 334.00  3.93617092e-02  3.35454579e-05  7.35388438e-02  1.04983900e-04           99.99           99.99
+ 335.00  4.81051591e-02  4.05565884e-05  9.60352312e-02  1.34629478e-04           99.99           99.99
+ 336.00  5.65974619e-02  4.72013222e-05  1.18775774e-01  1.63484887e-04           99.99           99.99
+ 337.00  6.48652284e-02  5.35098603e-05  1.42278579e-01  1.92249270e-04           99.99           99.99
+ 338.00  7.25998465e-02  5.92378341e-05  1.65557648e-01  2.19575501e-04           99.99           99.99
+ 339.00  7.99799035e-02  6.45450034e-05  1.88569139e-01  2.45441174e-04           99.99           99.99
+ 340.00  8.68837415e-02  6.93449692e-05  2.09777042e-01  2.67921956e-04           99.99           99.99
+ 341.00  9.34892114e-02  7.37919125e-05  2.28816153e-01  2.86708496e-04           99.99           99.99
+ 342.00  9.95098198e-02  7.76711769e-05  2.43876762e-01  2.99748075e-04           99.99           99.99
+ 343.00  1.04821332e-01  8.09032295e-05  2.51683002e-01  3.03388456e-04           99.99           99.99
+ 344.00  1.09567735e-01  8.36173462e-05  2.52028055e-01  2.97905690e-04           99.99           99.99
+ 345.00  1.13844787e-01  8.59012196e-05  2.46237110e-01  2.85359373e-04           99.99           99.99
+ 346.00  1.17322246e-01  8.75212888e-05  2.36607056e-01  2.68780280e-04           99.99           99.99
+ 347.00  1.20248035e-01  8.86814605e-05  2.24177192e-01  2.49581774e-04           99.99           99.99
+ 348.00  1.22616478e-01  8.93921212e-05  2.09227858e-01  2.28250423e-04           99.99           99.99
+ 349.00  1.24481362e-01  8.97065212e-05  1.94530288e-01  2.07906013e-04           99.99           99.99
+ 350.00  1.25910068e-01  8.96856201e-05  1.84648618e-01  1.93298657e-04           99.99           99.99
+ 351.00  1.26873854e-01  8.93203092e-05  1.79305755e-01  1.83820199e-04           99.99           99.99
+ 352.00  1.27349628e-01  8.86062202e-05  1.78271311e-01  1.78940210e-04           99.99           99.99
+ 353.00  1.27444244e-01  8.76289419e-05  1.81390624e-01  1.78228831e-04           99.99           99.99
+ 354.00  1.27427159e-01  8.65809136e-05  1.87815712e-01  1.80608699e-04           99.99           99.99
+ 355.00  1.26991649e-01  8.52589136e-05  1.96988564e-01  1.85351498e-04           99.99           99.99
+ 356.00  1.26294051e-01  8.37767037e-05  2.08368927e-01  1.91795652e-04           99.99           99.99
+ 357.00  1.25245997e-01  8.20825558e-05  2.18816761e-01  1.96986759e-04           99.99           99.99
+ 358.00  1.24229812e-01  8.04322087e-05  2.27393150e-01  2.00162108e-04           99.99           99.99
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+ 361.00  1.20078061e-01  7.49270011e-05  2.35236779e-01  1.93290792e-04           99.99           99.99
+ 362.00  1.18415896e-01  7.29759642e-05  2.32622220e-01  1.86709820e-04           99.99           99.99
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+ 365.00  1.14320018e-01  6.78401021e-05  2.23965129e-01  1.67267385e-04           99.99           99.99
+ 366.00  1.13098680e-01  6.62655802e-05  2.20851952e-01  1.60936288e-04           99.99           99.99
+ 367.00  1.11837348e-01  6.46919462e-05  2.17141260e-01  1.54342673e-04           99.99           99.99
+ 368.00  1.10897166e-01  6.33261142e-05  2.13344154e-01  1.47870140e-04           99.99           99.99
+ 369.00  1.10137634e-01  6.20815889e-05  2.09205477e-01  1.41348083e-04           99.99           99.99
+ 370.00  1.09349045e-01  6.08375773e-05  2.04351616e-01  1.34545402e-04           99.99           99.99
+ 371.00  1.08993010e-01  5.98480540e-05  1.99662718e-01  1.28060137e-04           99.99           99.99
+ 372.00  1.08528360e-01  5.88102745e-05  1.94047545e-01  1.21198962e-04           99.99           99.99
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+ 376.00  1.09108058e-01  5.60313630e-05  1.73890313e-01  9.73046852e-05           99.99           99.99
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+ 383.00  1.30901086e-01  6.09767771e-05  1.69961239e-01  7.71728942e-05           99.99           99.99
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+ 412.00  4.47897608e-01  1.31187499e-04  5.46430076e-01  6.78866075e-05           99.99           99.99
+ 413.00  4.54324711e-01  1.30673733e-04  5.51528478e-01  6.40216505e-05           99.99           99.99
+ 414.00  4.60313158e-01  1.29988922e-04  5.55995849e-01  6.01552475e-05           99.99           99.99
+ 415.00  4.66419545e-01  1.29295002e-04  5.60569552e-01  5.63904118e-05           99.99           99.99
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+1003.00  2.20616877e-02  5.63421173e-06           99.99           99.99  7.20496541e-02  7.07739018e-06
+1004.00  2.12750382e-02  5.53820000e-06           99.99           99.99  6.93747773e-02  6.32863973e-06
+1005.00  2.05393730e-02  5.44886029e-06           99.99           99.99  6.61172781e-02  5.55974638e-06
+1006.00  1.98252817e-02  5.35890794e-06           99.99           99.99  6.28712013e-02  4.83041022e-06
+1007.00  1.91392465e-02  5.27035993e-06           99.99           99.99  6.04979441e-02  4.20190213e-06
+1008.00  1.84634887e-02  5.17856647e-06           99.99           99.99  5.77320676e-02  3.57806521e-06
+1009.00  1.77940347e-02  5.08246182e-06           99.99           99.99  5.43783149e-02  2.95908684e-06
+1010.00  1.71045299e-02  4.97439134e-06           99.99           99.99  5.21648656e-02  2.44185213e-06
+1011.00  1.64408885e-02  4.86754556e-06           99.99           99.99  4.98818943e-02  1.95659652e-06
+1012.00  1.57992794e-02  4.76108931e-06           99.99           99.99  4.67519123e-02  1.48638653e-06
+1013.00  1.51890084e-02  4.65814131e-06           99.99           99.99  4.43954393e-02  1.10153766e-06
+1014.00  1.46000832e-02  4.55600402e-06           99.99           99.99  4.25383196e-02  8.08250351e-07
+1015.00  1.40438991e-02  4.45856143e-06           99.99           99.99  4.00457635e-02  6.39634047e-07
+1016.00  1.35152060e-02  4.36457675e-06           99.99           99.99  3.75725452e-02  6.57599871e-07
+1017.00  1.29890078e-02  4.26622064e-06           99.99           99.99  3.60426235e-02  8.24444806e-07
+1018.00  1.24326267e-02  4.15254975e-06           99.99           99.99  3.41708897e-02  1.03344034e-06
+1019.00  1.19180270e-02  4.04742612e-06           99.99           99.99  3.18119130e-02  1.22781920e-06
+1020.00  1.13958923e-02  3.93445631e-06           99.99           99.99  3.01690233e-02  1.43343869e-06
+1021.00  1.09115390e-02  3.82934607e-06           99.99           99.99  2.88635385e-02  1.63984439e-06
+1022.00  1.04521107e-02  3.72808976e-06           99.99           99.99  2.69578199e-02  1.79024786e-06
+1023.00  1.00129018e-02  3.62934884e-06           99.99           99.99  2.52710953e-02  1.92702652e-06
+1024.00  9.59084092e-03  3.53228361e-06           99.99           99.99  2.41169738e-02  2.08183755e-06
+1025.00  9.19348122e-03  3.43996297e-06           99.99           99.99  2.28553054e-02  2.20779080e-06
+1026.00  8.79047352e-03  3.34123277e-06           99.99           99.99  2.12025816e-02  2.27021949e-06
+1027.00  8.38172296e-03  3.23590106e-06           99.99           99.99  2.00423128e-02  2.35975791e-06
+1028.00  7.98808843e-03  3.13198744e-06           99.99           99.99  1.90770916e-02  2.45317319e-06
+1029.00  7.61580777e-03  3.03219424e-06           99.99           99.99  1.77731553e-02  2.48169437e-06
+1030.00  7.25157056e-03  2.93147781e-06           99.99           99.99  1.65918440e-02  2.50294782e-06
+1031.00  6.91641033e-03  2.83856768e-06           99.99           99.99  1.57559173e-02  2.55654060e-06
+1032.00  6.59050148e-03  2.74569488e-06           99.99           99.99  1.48486139e-02  2.58137167e-06
+1033.00  6.28198777e-03  2.65643006e-06           99.99           99.99  1.37182572e-02  2.54630826e-06
+1034.00  5.97895856e-03  2.56594492e-06           99.99           99.99  1.29141151e-02  2.55137556e-06
+1035.00  5.68605069e-03  2.47632016e-06           99.99           99.99  1.22217690e-02  2.56286993e-06
+1036.00  5.40603194e-03  2.38893053e-06           99.99           99.99  1.13707307e-02  2.52443512e-06
+1037.00  5.12860149e-03  2.29936564e-06           99.99           99.99  1.05711368e-02  2.47902675e-06
+1038.00  4.86306725e-03  2.21186994e-06           99.99           99.99  9.99104989e-03  2.46968395e-06
+1039.00  4.60737466e-03  2.12568959e-06           99.99           99.99  9.37161738e-03  2.43712840e-06
+1040.00  4.36700622e-03  2.04354688e-06           99.99           99.99  8.61890823e-03  2.35385282e-06
+1041.00  4.13684231e-03  1.96328070e-06           99.99           99.99  8.07236638e-03  2.31142408e-06
+1042.00  3.91409777e-03  1.88372090e-06           99.99           99.99  7.60517614e-03  2.27971565e-06
+1043.00  3.70426533e-03  1.80766479e-06           99.99           99.99  7.04576714e-03  2.20790291e-06
+1044.00  3.49768928e-03  1.73056560e-06           99.99           99.99  6.49708839e-03  2.12559375e-06
+1045.00  3.29787242e-03  1.65421684e-06           99.99           99.99  6.11395300e-03  2.08574191e-06
+1046.00  3.10114462e-03  1.57686195e-06           99.99           99.99  5.72535895e-03  2.03432038e-06
+1047.00  2.91166362e-03  1.50067909e-06           99.99           99.99  5.22217613e-03  1.93053762e-06
+1048.00  2.73715363e-03  1.42982625e-06           99.99           99.99  4.85607994e-03  1.86587543e-06
+1049.00  2.57163006e-03  1.36142302e-06           99.99           99.99  4.56761733e-03  1.82239296e-06
+1050.00  2.41251048e-03  1.29424919e-06           99.99           99.99  4.22677141e-03  1.74954577e-06
+1051.00           99.99           99.99           99.99           99.99  3.84829941e-03  1.65112407e-06
+1052.00           99.99           99.99           99.99           99.99  3.59845977e-03  1.59908480e-06
+1053.00           99.99           99.99           99.99           99.99  3.36810276e-03  1.54900173e-06
+1054.00           99.99           99.99           99.99           99.99  3.07450240e-03  1.46230352e-06
+1055.00           99.99           99.99           99.99           99.99  2.81129339e-03  1.38186233e-06
+1056.00           99.99           99.99           99.99           99.99  2.63746389e-03  1.33892150e-06
+1057.00           99.99           99.99           99.99           99.99  2.45553507e-03  1.28662516e-06
+1058.00           99.99           99.99           99.99           99.99  2.20908009e-03  1.19397247e-06
+1059.00           99.99           99.99           99.99           99.99  2.03073979e-03  1.13152773e-06
+1060.00           99.99           99.99           99.99           99.99  1.90498995e-03  1.09368821e-06
+1061.00           99.99           99.99           99.99           99.99  1.75292299e-03  1.03639534e-06
+1062.00           99.99           99.99           99.99           99.99  1.56799085e-03  9.54221377e-07
+1063.00           99.99           99.99           99.99           99.99  1.45283230e-03  9.09607707e-07
+1064.00           99.99           99.99           99.99           99.99  1.35710511e-03  8.73742431e-07
+1065.00           99.99           99.99           99.99           99.99  1.23235835e-03  8.15538149e-07
+1066.00           99.99           99.99           99.99           99.99  1.10451616e-03  7.50982817e-07
+1067.00           99.99           99.99           99.99           99.99  1.02517422e-03  7.15857321e-07
+1068.00           99.99           99.99           99.99           99.99  9.52947059e-04  6.83117073e-07
+1069.00           99.99           99.99           99.99           99.99  8.54406689e-04  6.28523345e-07
+1070.00           99.99           99.99           99.99           99.99  7.69338960e-04  5.80555231e-07
+1071.00           99.99           99.99           99.99           99.99  7.13493700e-04  5.52114467e-07
+1072.00           99.99           99.99           99.99           99.99  6.58462324e-04  5.22314893e-07
+1073.00           99.99           99.99           99.99           99.99  5.84632519e-04  4.75227106e-07
+1074.00           99.99           99.99           99.99           99.99  5.28503009e-04  4.40089902e-07
+1075.00           99.99           99.99           99.99           99.99  4.90531778e-04  4.18311871e-07
+1076.00           99.99           99.99           99.99           99.99  4.49461985e-04  3.92403384e-07
+1077.00           99.99           99.99           99.99           99.99  3.96150459e-04  3.53979690e-07
+1078.00           99.99           99.99           99.99           99.99  3.59992587e-04  3.29128619e-07
+1079.00           99.99           99.99           99.99           99.99  3.33217606e-04  3.11625587e-07
+1080.00           99.99           99.99           99.99           99.99  3.02837270e-04  2.89621124e-07
+1081.00           99.99           99.99           99.99           99.99           99.99           99.99
+1082.00           99.99           99.99           99.99           99.99           99.99           99.99
+1083.00           99.99           99.99           99.99           99.99           99.99           99.99
+1084.00           99.99           99.99           99.99           99.99           99.99           99.99
+1085.00           99.99           99.99           99.99           99.99           99.99           99.99
+1086.00           99.99           99.99           99.99           99.99           99.99           99.99
+1087.00           99.99           99.99           99.99           99.99           99.99           99.99
+1088.00           99.99           99.99           99.99           99.99           99.99           99.99
+1089.00           99.99           99.99           99.99           99.99           99.99           99.99
+1090.00           99.99           99.99           99.99           99.99           99.99           99.99
+1091.00           99.99           99.99           99.99           99.99           99.99           99.99
+1092.00           99.99           99.99           99.99           99.99           99.99           99.99
+1093.00           99.99           99.99           99.99           99.99           99.99           99.99
+1094.00           99.99           99.99           99.99           99.99           99.99           99.99
+1095.00           99.99           99.99           99.99           99.99           99.99           99.99
+1096.00           99.99           99.99           99.99           99.99           99.99           99.99
+1097.00           99.99           99.99           99.99           99.99           99.99           99.99
+1098.00           99.99           99.99           99.99           99.99           99.99           99.99
+1099.00           99.99           99.99           99.99           99.99           99.99           99.99
+1100.00           99.99           99.99           99.99           99.99           99.99           99.99
diff --git a/filt_func/gaia/edr3/ReadMe b/filt_func/gaia/edr3/ReadMe
new file mode 100644
index 00000000..bd3e2f27
--- /dev/null
+++ b/filt_func/gaia/edr3/ReadMe
@@ -0,0 +1,134 @@
+J/A+A/649/A3     Gaia Early Data Release 3 photometric passbands (Riello+, 2021)
+================================================================================
+Gaia Early Data Release 3: Photometric content and validation.
+    Riello M., De Angeli F., Evans D.W., Montegriffo P., Carrasco J.M,
+    Busso G., Palaversa L., Burgess P., Diener C., Davidson M., Rowell N.,
+    Fabricius C., Jordi C., Bellazzini M., Pancino E., Harrison D.L.,
+    Cacciari C., van Leeuwen F., Hambly N.C., Hodgkin S.T., Osborne P.J.,
+    Altavilla G., Barstow M.A., Brown A.G.A., Castellani M., Cowell S.,
+    De Luise F., Gilmore G., Giuffrida G., Hidalgo S., Holland G., Marinoni S.,
+    Pagani C., Piersimoni A.M., Pulone L., Ragaini S., Rainer M., Richards P.J.,
+    Sanna N., Walton N.A., Weiler M., Yoldas A.
+    <Astron. Astrophys. 649, A3 (2021)>
+    =2021A&A...649A...3R        (SIMBAD/NED BibCode)
+================================================================================
+ADC_Keywords: Surveys ; Photometry, G band
+Keywords: catalogues - surveys - instrumentation: photometers -
+          techniques: photometric - Galaxy: general
+
+Abstract:
+    Gaia Early Data Release 3 (Gaia EDR3) contains astrometry and
+    photometry results for about 1.8 billion sources based on
+    observations collected by the European Space Agency Gaia satellite
+    during the first 34 months of its operational phase.
+
+    In this paper, we focus on the photometric content, describing the
+    input data, the algorithms, the processing, and the validation of the
+    results. Particular attention is given to the quality of the data and
+    to a number of features that users may need to take into account to
+    make the best use of the Gaia EDR3 catalogue.
+
+    The processing broadly followed the same procedure as for Gaia DR2,
+    but with significant improvements in several aspects of the blue and
+    red photometer (BP and RP) preprocessing and in the photometric
+    calibration process. In particular, the treatment of the BP and RP
+    background has been updated to include a better estimation of the
+    local background, and the detection of crowding effects has been used
+    to exclude affected data from the calibrations. The photometric
+    calibration models have also been updated to account for flux loss
+    over the whole magnitude range. Significant improvements in the
+    modelling and calibration of the Gaia point and line spread functions
+    have also helped to reduce a number of instrumental effects that were
+    still present in DR2.
+
+    Gaia EDR3 contains 1.806 billion sources with G-band photometry and
+    1.540 billion sources with GBP and GRP photometry. The median
+    uncertainty in the G-band photometry, as measured from the standard
+    deviation of the internally calibrated mean photometry for a given
+    source, is 0.2mmag at magnitude G=10 to 14, 0.8mmag at G~17, and
+    2.6mmag at G~19. The significant magnitude term found in the Gaia DR2
+    photometry is no longer visible, and overall there are no trends
+    larger than 1mmag/mag. Using one passband over the whole colour and
+    magnitude range leaves no systematics above the 1% level in magnitude
+    in any of the bands, and a larger systematic is present for a very
+    small sample of bright and blue sources. A detailed description of the
+    residual systematic effects is provided. Overall the quality of the
+    calibrated mean photometry in Gaia EDR3 is superior with respect to
+    DR2 for all bands.
+
+Description:
+    These tabular data describes the photometric system defined by the G,
+    G_BP_ and G_RP_ Gaia bands for Gaia Early Data Release 3.
+
+    The tables provide the full passband and the corresponding zero point
+    for each of the photometric bands. The zero points are available both
+    in the VEGAMAG and AB systems.
+
+    The passband calibration is based on the modelling of a set of
+    corrections applied to pre-launch knowledge of the instrument, to find
+    the best match between observed and synthetic photometry for a set of
+    calibrators. For EDR3 a large set of calibrators covering a wide range
+    of spectra types was used for the passband calibration.
+
+    For these sources reconstructed SEDs were obtained from externally
+    calibrated Gaia BP/RP spectra.
+
+File Summary:
+--------------------------------------------------------------------------------
+ FileName      Lrecl  Records   Explanations
+--------------------------------------------------------------------------------
+ReadMe            80        .   This file
+passband.dat     103      781   G, G_BP_ anf G_RP_ passbands used to generate
+                                 the magnitudes and astrophysical parameters
+                                 included in Gaia EDR3
+zeropt.dat        97        2   G, G_BP_ and G_RP_ zero points used to generate
+                                 the magnitudes and astrophysical parameters
+                                 included in Gaia EDR3
+--------------------------------------------------------------------------------
+
+See also:
+        I/350 : Gaia EDR3 (Gaia Collaboration, 2020)
+ J/A+A/649/A6 : Gaia Catalogue of Nearby Stars - GCNS (Gaia collaboration, 2021)
+ J/A+A/649/A7 : MC structure and properties (Gaia Collaboration+, 2021)
+
+Byte-by-byte Description of file: passband.dat
+--------------------------------------------------------------------------------
+   Bytes Format Units   Label     Explanations
+--------------------------------------------------------------------------------
+   1-  7  F7.2  nm      lambda    Wavelength
+  10- 23  E14.9 mag     GPb       ?=99.99 G transmissivity curve at the
+                                   corresponding wavelength (1)
+  26- 39  E14.9 mag   e_GPb       ?=99.99 Uncertainty on the G transmissivity
+                                   curve (1)
+  42- 55  E14.9 mag     BPPb      ?=99.99 BP transmissivity curve at the
+                                   corresponding wavelength (1)
+  58- 71  E14.9 mag   e_BPPb      ?=99.99 Uncertainty on the BP transmissivity
+                                   curve (1)
+  74- 87  E14.9 mag     RPPb      ?=99.99 RP transmissivity curve at the
+                                   corresponding wavelength (1)
+  90-103  E14.9 mag   e_RPPb      ?=99.99 Uncertainty on the RP transmissivity
+                                   curve (1)
+--------------------------------------------------------------------------------
+Note (1): In correspondence to wavelength values where the passband is not
+   defined, both transmissivity and uncertainty are set to 99.99.
+--------------------------------------------------------------------------------
+
+Byte-by-byte Description of file: zeropt.dat
+--------------------------------------------------------------------------------
+   Bytes Format Units   Label     Explanations
+--------------------------------------------------------------------------------
+   2- 14 F13.10 ---     GZp       G band zero point
+  18- 29 F12.10 ---   e_GZp       G band zero point uncertainty
+  32- 44 F13.10 ---     BPZp      G_BP_ band zero point
+  48- 59 F12.10 ---   e_BPZp      G_BP_ band zero point uncertainty
+  62- 74 F13.10 ---     RPZp      G_RP_ band zero point
+  78- 89 F12.10 ---   e_RPZp      G_RP_ band zero point uncertainty
+  91- 97  A7    ---     System    [VEGAMAG, AB] Photometric system
+--------------------------------------------------------------------------------
+
+Acknowledgements:
+    Marco Riello, mriello(at)ast.cam.ac.uk
+    Francesca De Angeli, fda(at)ast.cam.ac.uk
+
+================================================================================
+(End)     Francesca De Angeli [IoA, UK], Patricia Vannier [CDS]      05-Jan-2021
diff --git a/spisea/filters.py b/spisea/filters.py
index 23c029b3..4b100d71 100755
--- a/spisea/filters.py
+++ b/spisea/filters.py
@@ -338,14 +338,14 @@ def get_gaia_filt(version, name):
     Define Gaia filters as pysynphot object.
     To avoid confusion, we will only support 
     the revised DR2 zeropoints from 
-    Evans+18.
+    Evans+18 and EDR3 from Riello+21.
 
-    version: specify dr1, dr2, or dr2_rev
+    version: specify dr1, dr2, dr2_rev, edr3
     name: filter name
     """
     # Assert that we are using the revised DR2 zeropoints
-    if version != 'dr2_rev':
-        msg = 'Gaia version {0} not supported, use dr2_rev instead'.format(version)
+    if version not in ['dr2_rev', 'edr3']:
+        msg = 'Gaia version {0} not supported, use dr2_rev or edr3 instead'.format(version)
         raise ValueError(msg)
 
     # Set the filter directory
@@ -355,8 +355,10 @@ def get_gaia_filt(version, name):
         path = '{0}/gaia/dr2/'.format(filters_dir)
     elif version == 'dr2_rev':
         path = '{0}/gaia/dr2_rev/'.format(filters_dir)
+    elif version == 'edr3':
+        path = '{0}/gaia/edr3/'.format(filters_dir)
     else:
-        raise ValueError('GAIA filter version {0} not understood. Please use dr1, dr2, or dr2_rev'.format(version))
+        raise ValueError('GAIA filter version {0} not understood. Please use dr1, dr2, dr2_rev, or edr3'.format(version))
         
     # Get the filter info
     try:
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 82f87a30..bda6f9d7 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1765,6 +1765,8 @@ def get_filter_col_name(obs_str):
         # Catch Gaia filter cases. Otherwise, it is HST filter
         if 'dr2_rev' in tmp:
             filt_name = 'gaiaDR2_{0}'.format(tmp[-1])
+        elif 'edr3' in tmp:
+            filt_name = 'gaiaEDR3_{0}'.format(tmp[-1])
         elif 'roman' in tmp:
             filt_name = 'roman_{0}'.format(tmp[-1])
         else:
@@ -1836,6 +1838,7 @@ def get_obs_str(col):
                  'ztf_g':'ztf,g', 'ztf_r':'ztf,r', 'ztf_i':'ztf,i',
                  'gaiaDR2_G': 'gaia,dr2_rev,G', 'gaiaDR2_Gbp':'gaia,dr2_rev,Gbp',
                  'gaiaDR2_Grp':'gaia,dr2_rev,Grp',
+                 'gaiaEDR3_G': 'gaia,edr3,G', 'gaiaEDR3_Gbp':'gaia,edr3,Gbp', 'gaiaEDR3_Grp':'gaia,edr3,Grp',
                  'hawki_J': 'hawki,J',
                  'hawki_H': 'hawki,H',
                  'hawki_Ks': 'hawki,Ks',
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index be7b9307..05b7305f 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -164,6 +164,7 @@ def test_filters():
                      'decam,y', 'decam,i', 'decam,z',
                      'decam,u', 'decam,g', 'decam,r',
                      'gaia,dr2_rev,G', 'gaia,dr2_rev,Gbp', 'gaia,dr2_rev,Grp',
+                     'gaia,edr3,G', 'gaia,edr3,Gbp', 'gaia,edr3,Grp',
                      'jwst,F070W', 'jwst,F090W', 'jwst,F115W', 'jwst,F140M',
                      'jwst,F150W', 'jwst,F150W2', 'jwst,F162M', 'jwst,F164N',
                      'jwst,F182M', 'jwst,F187N', 'jwst,F200W', 'jwst,F212N',

From 6bcc97223cecea3776a603d9f8a785284988f8b9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E2=80=9CLingfeng?= <lingfeng-wei@outlook.com>
Date: Thu, 26 Feb 2026 11:08:50 -0800
Subject: [PATCH 44/55] Added missing blank line in docstring code block

---
 spisea/imf/imf.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/spisea/imf/imf.py b/spisea/imf/imf.py
index 8e6e1454..df6a8887 100755
--- a/spisea/imf/imf.py
+++ b/spisea/imf/imf.py
@@ -63,6 +63,7 @@ class IMF(object):
 
         If identical output is desired over each run, the random state can be reset before running the function, e.g.
         ::
+
             imf.rng = np.random.default_rng(seed=42)
             result1 = imf.generate_cluster()
             imf.rng = np.random.default_rng(seed=42)

From 1d9cdc2ba4fb8f6660b7064e6f7d2460a5466e7a Mon Sep 17 00:00:00 2001
From: Rocketpack23 <apusack@gmail.com>
Date: Thu, 5 Mar 2026 11:18:24 -0800
Subject: [PATCH 45/55] updated filters.rst and dictionary in synthetic.py

---
 docs/filters.rst    | 26 +++++++++++++++++---------
 spisea/synthetic.py |  5 +++--
 2 files changed, 20 insertions(+), 11 deletions(-)

diff --git a/docs/filters.rst b/docs/filters.rst
index 918f27f4..6efb28fc 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -7,16 +7,16 @@ Photometric Filters
 The user can specify what filters are used for synthetic photometry
 when defining the :ref:`isochrone_objects`.  Each filter is
 identified by a unique string, and an array of such strings
-are passed into the Isochrone call. 
+are passed into the Isochrone call.
 
 For example::
-  
+
     # Use the HST WFC3-IR F127M and F153M filters, along with NIRC2 Kp
     filt_list = ['wfc3,ir,f127m', 'wfc3,ir,f153m', 'nirc2,Kp']
     my_iso = synthetic.IsochronePhot(logAge, AKs, dist, metallicity=0,
                             evo_model=evo_model, atm_func=atm_func,
                             red_law=red_law, filters=filt_list)
-    
+
 These strings follow the format ``<telescope/filter_set>,<filter>``.
 Note that there is no space after the comma, and case matters.
 
@@ -40,7 +40,7 @@ Available filters:
 * JWST
 * Keck NIRC
 * Keck NIRC2
-* NACO 
+* NACO
 * PanStarrs 1
 * Roman Space Telescope
 * UKIRT
@@ -48,11 +48,11 @@ Available filters:
 * VISTA
 * ZTF
 
-  
+
 Filter Sets
 ------------
 
-   
+
 **2MASS**
 
 `Two-Micron Sky Survey <https://old.ipac.caltech.edu/2mass/>`_
@@ -83,7 +83,7 @@ Example: ``'decam,r'``
 
 **Euclid**
 
-Euclid space telescope `NISP filters <https://doi.org/10.5270/esa-kx8w57c>`_ 
+Euclid space telescope `NISP filters <https://doi.org/10.5270/esa-kx8w57c>`_
 and `VIS single filter <https://svo2.cab.inta-csic.es/svo/theory/fps/index.php?id=Euclid/VIS.vis>`_
 
 Filters: VIS, Y, J, H
@@ -146,10 +146,10 @@ Example: ``'jg,K'``
 
 JWST NIRCam filters, downloaded from `NIRCam website <https://jwst-docs.stsci.edu/display/JTI/NIRCam+Filters#NIRCamFilters-filt_trans>`_. The filter functions in the nircam_throughputs/modAB_mean/nrc_plus_ote folder is used.
 
-Filters: F070W, F090W,  F115W, F140M, F150W, F150W2, F162M, F164N, F182M, F187N, F200W, F210M, F212N, F250M, F277W, F300M, F322W2, F323N, F335M, F356W, F360M, F405N, F410M, F430M,  F444W, F460M, F466N, F470N, F480M 
+Filters: F070W, F090W,  F115W, F140M, F150W, F150W2, F162M, F164N, F182M, F187N, F200W, F210M, F212N, F250M, F277W, F300M, F322W2, F323N, F335M, F356W, F360M, F405N, F410M, F430M,  F444W, F460M, F466N, F470N, F480M
 
 Example: ``'jwst,F356W'``
-						
+
 
 **Keck NIRC**
 
@@ -237,3 +237,11 @@ Example: ``'vista,Y'``
 Filters: g, r, i
 
 Example: ``'ztf,g'``
+
+**IRTF**
+
+`IRTF NSFCam <https://irtfweb.ifa.hawaii.edu/~nsfcam2/Filter_Profiles.html>`_
+
+Filters: L
+
+Example: ``'nsfcam,L'``
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 4c98dc57..171d0bda 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1554,7 +1554,7 @@ def get_filter_info(name, vega=vega, rebin=True):
 
     elif name.startswith('nsfcam'):
         filt = filters.get_nsfcam_filt(filterName)
-        
+
     else:
         # Otherwise, look for the filter info in the cdbs/mtab and cdbs/comp files
         try:
@@ -1701,7 +1701,8 @@ def get_obs_str(col):
                  'euclid_VIS':'euclid,VIS',
                  'euclid_Y':'euclid,Y',
                  'euclid_J':'euclid,J',
-                 'euclid_H':'euclid,H'}
+                 'euclid_H':'euclid,H',
+                 'nsfcam_L':'nsfcam,L'}
 
     obs_str = filt_list[name]
 

From 5da97c8fc8ac9dec85750893ba35d6cd1972cf38 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 11:23:45 -0700
Subject: [PATCH 46/55] adding nsfcam,L to test_filters

---
 spisea/tests/test_models.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index be7b9307..68139ecb 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -186,7 +186,8 @@ def test_filters():
                      'roman,wfi,f158', 'roman,wfi,f146', 'roman,wfi,f213',
                      'roman,wfi,f184', 'rubin,g', 'rubin,i', 'rubin,r',
                      'rubin,u', 'rubin,z', 'rubin,y',
-                     'euclid,VIS', 'euclid,Y', 'euclid,J', 'euclid,H']
+                     'euclid,VIS', 'euclid,Y', 'euclid,J', 'euclid,H',
+                     'nsfcam,L']
 
     # Loop through filters to test that they work: get_filter_info
     for ii in filt_list:
@@ -205,4 +206,4 @@ def test_filters():
     print('get_obs_str pass')
     print('Filters done')
 
-    return
\ No newline at end of file
+    return

From c958a0acbb38e012a74d71547e19beceeb774185 Mon Sep 17 00:00:00 2001
From: Macy Huston <mhuston@laser.astro.berkeley.edu>
Date: Fri, 20 Mar 2026 12:54:37 -0700
Subject: [PATCH 47/55] resolve merge mistakes

---
 docs/filters.rst                       |   9 +-
 filt_func/gaia/edr3/Gaia_passbands.txt | 781 -------------------------
 filt_func/gaia/edr3/ReadMe             | 134 -----
 spisea/evolution.py                    |  20 +-
 spisea/filters.py                      |   8 +-
 spisea/synthetic.py                    |  14 +-
 spisea/tests/test_models.py            |   1 -
 7 files changed, 18 insertions(+), 949 deletions(-)
 delete mode 100644 filt_func/gaia/edr3/Gaia_passbands.txt
 delete mode 100644 filt_func/gaia/edr3/ReadMe

diff --git a/docs/filters.rst b/docs/filters.rst
index 2d8eedf9..6efb28fc 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -93,13 +93,12 @@ Example: ``'euclid,Y'``
 **GAIA**
 
 The `GAIA Space Telescope filters <https://www.cosmos.esa.int/web/gaia/iow_20180316>`_.
-Note that four sets are available: the pre-launch passbands used in DR1
+Note that three sets are available: the pre-launch passbands used in DR1
 (`Jordi+10
 <https://ui.adsabs.harvard.edu/abs/2010A%26A...523A..48J/abstract>`_),
-the passbands used for the DR2 published photometry, 
-the *revised* DR2 passbands based on the DR2 data (October 2017),
-and the EDR3 passbands from Riello et al (2021).
-ONLY THE REVISED DR2 and EDR3 PASSBANDS ARE SUPPORTED BY SPISEA.
+the passbands used for the DR2 published photometry, and
+the *revised* DR2 passbands based on the DR2 data (October 2017).
+ONLY THE REVISED DR2 PASSBANDS ARE SUPPORTED BY SPISEA.
 
 Filters: G, Gbp, Grp
 
diff --git a/filt_func/gaia/edr3/Gaia_passbands.txt b/filt_func/gaia/edr3/Gaia_passbands.txt
deleted file mode 100644
index cc733830..00000000
--- a/filt_func/gaia/edr3/Gaia_passbands.txt
+++ /dev/null
@@ -1,781 +0,0 @@
- 320.00  2.37366962e-08  2.34103325e-11           99.99           99.99           99.99           99.99
- 321.00  1.57774443e-07  1.54036935e-10           99.99           99.99           99.99           99.99
- 322.00  9.08554755e-07  8.78053229e-10           99.99           99.99           99.99           99.99
- 323.00  4.78072331e-06  4.57325370e-09           99.99           99.99           99.99           99.99
- 324.00  2.39428071e-05  2.26698640e-08           99.99           99.99           99.99           99.99
- 325.00  1.03648276e-04  9.71310542e-08  3.87054116e-05  6.46801629e-08           99.99           99.99
- 326.00  3.72280534e-04  3.45277531e-07  1.75771984e-04  2.88785224e-07           99.99           99.99
- 327.00  1.09381843e-03  1.00397934e-06  6.49485416e-04  1.04897855e-06           99.99           99.99
- 328.00  2.65174642e-03  2.40864304e-06  1.96690820e-03  3.12246976e-06           99.99           99.99
- 329.00  5.45098195e-03  4.89953932e-06  5.01083084e-03  7.81780663e-06           99.99           99.99
- 330.00  9.76875472e-03  8.68837731e-06  1.09458069e-02  1.67813576e-05           99.99           99.99
- 331.00  1.56275855e-02  1.37527326e-05  2.07035425e-02  3.11867542e-05           99.99           99.99
- 332.00  2.27741233e-02  1.98296421e-05  3.46967871e-02  5.13454545e-05           99.99           99.99
- 333.00  3.07613294e-02  2.64991906e-05  5.25319303e-02  7.63595340e-05           99.99           99.99
- 334.00  3.93617092e-02  3.35454579e-05  7.35388438e-02  1.04983900e-04           99.99           99.99
- 335.00  4.81051591e-02  4.05565884e-05  9.60352312e-02  1.34629478e-04           99.99           99.99
- 336.00  5.65974619e-02  4.72013222e-05  1.18775774e-01  1.63484887e-04           99.99           99.99
- 337.00  6.48652284e-02  5.35098603e-05  1.42278579e-01  1.92249270e-04           99.99           99.99
- 338.00  7.25998465e-02  5.92378341e-05  1.65557648e-01  2.19575501e-04           99.99           99.99
- 339.00  7.99799035e-02  6.45450034e-05  1.88569139e-01  2.45441174e-04           99.99           99.99
- 340.00  8.68837415e-02  6.93449692e-05  2.09777042e-01  2.67921956e-04           99.99           99.99
- 341.00  9.34892114e-02  7.37919125e-05  2.28816153e-01  2.86708496e-04           99.99           99.99
- 342.00  9.95098198e-02  7.76711769e-05  2.43876762e-01  2.99748075e-04           99.99           99.99
- 343.00  1.04821332e-01  8.09032295e-05  2.51683002e-01  3.03388456e-04           99.99           99.99
- 344.00  1.09567735e-01  8.36173462e-05  2.52028055e-01  2.97905690e-04           99.99           99.99
- 345.00  1.13844787e-01  8.59012196e-05  2.46237110e-01  2.85359373e-04           99.99           99.99
- 346.00  1.17322246e-01  8.75212888e-05  2.36607056e-01  2.68780280e-04           99.99           99.99
- 347.00  1.20248035e-01  8.86814605e-05  2.24177192e-01  2.49581774e-04           99.99           99.99
- 348.00  1.22616478e-01  8.93921212e-05  2.09227858e-01  2.28250423e-04           99.99           99.99
- 349.00  1.24481362e-01  8.97065212e-05  1.94530288e-01  2.07906013e-04           99.99           99.99
- 350.00  1.25910068e-01  8.96856201e-05  1.84648618e-01  1.93298657e-04           99.99           99.99
- 351.00  1.26873854e-01  8.93203092e-05  1.79305755e-01  1.83820199e-04           99.99           99.99
- 352.00  1.27349628e-01  8.86062202e-05  1.78271311e-01  1.78940210e-04           99.99           99.99
- 353.00  1.27444244e-01  8.76289419e-05  1.81390624e-01  1.78228831e-04           99.99           99.99
- 354.00  1.27427159e-01  8.65809136e-05  1.87815712e-01  1.80608699e-04           99.99           99.99
- 355.00  1.26991649e-01  8.52589136e-05  1.96988564e-01  1.85351498e-04           99.99           99.99
- 356.00  1.26294051e-01  8.37767037e-05  2.08368927e-01  1.91795652e-04           99.99           99.99
- 357.00  1.25245997e-01  8.20825558e-05  2.18816761e-01  1.96986759e-04           99.99           99.99
- 358.00  1.24229812e-01  8.04322087e-05  2.27393150e-01  2.00162108e-04           99.99           99.99
- 359.00  1.22847822e-01  7.85703870e-05  2.32695680e-01  2.00232971e-04           99.99           99.99
- 360.00  1.21442511e-01  7.67218639e-05  2.35262373e-01  1.97849301e-04           99.99           99.99
- 361.00  1.20078061e-01  7.49270011e-05  2.35236779e-01  1.93290792e-04           99.99           99.99
- 362.00  1.18415896e-01  7.29759642e-05  2.32622220e-01  1.86709820e-04           99.99           99.99
- 363.00  1.17082052e-01  7.12563815e-05  2.30119196e-01  1.80368975e-04           99.99           99.99
- 364.00  1.15602744e-01  6.94757408e-05  2.26963302e-01  1.73675037e-04           99.99           99.99
- 365.00  1.14320018e-01  6.78401021e-05  2.23965129e-01  1.67267385e-04           99.99           99.99
- 366.00  1.13098680e-01  6.62655802e-05  2.20851952e-01  1.60936288e-04           99.99           99.99
- 367.00  1.11837348e-01  6.46919462e-05  2.17141260e-01  1.54342673e-04           99.99           99.99
- 368.00  1.10897166e-01  6.33261142e-05  2.13344154e-01  1.47870140e-04           99.99           99.99
- 369.00  1.10137634e-01  6.20815889e-05  2.09205477e-01  1.41348083e-04           99.99           99.99
- 370.00  1.09349045e-01  6.08375773e-05  2.04351616e-01  1.34545402e-04           99.99           99.99
- 371.00  1.08993010e-01  5.98480540e-05  1.99662718e-01  1.28060137e-04           99.99           99.99
- 372.00  1.08528360e-01  5.88102745e-05  1.94047545e-01  1.21198962e-04           99.99           99.99
- 373.00  1.08229538e-01  5.78732561e-05  1.88483494e-01  1.14598899e-04           99.99           99.99
- 374.00  1.08180230e-01  5.70775306e-05  1.83208476e-01  1.08394301e-04           99.99           99.99
- 375.00  1.08450962e-01  5.64544647e-05  1.78318209e-01  1.02622421e-04           99.99           99.99
- 376.00  1.09108058e-01  5.60313630e-05  1.73890313e-01  9.73046852e-05           99.99           99.99
- 377.00  1.09989532e-01  5.57181217e-05  1.69635287e-01  9.22585016e-05           99.99           99.99
- 378.00  1.11262658e-01  5.55937491e-05  1.65792693e-01  8.75993781e-05           99.99           99.99
- 379.00  1.13409497e-01  5.58878519e-05  1.63149992e-01  8.37095375e-05           99.99           99.99
- 380.00  1.16293195e-01  5.65162267e-05  1.62143918e-01  8.07496089e-05           99.99           99.99
- 381.00  1.20058072e-01  5.75333720e-05  1.62970621e-01  7.87395616e-05           99.99           99.99
- 382.00  1.25004759e-01  5.90639780e-05  1.65710956e-01  7.76359346e-05           99.99           99.99
- 383.00  1.30901086e-01  6.09767771e-05  1.69961239e-01  7.71728942e-05           99.99           99.99
- 384.00  1.38026499e-01  6.33819265e-05  1.76098800e-01  7.74534948e-05           99.99           99.99
- 385.00  1.46290114e-01  6.62148860e-05  1.84059158e-01  7.83733729e-05           99.99           99.99
- 386.00  1.55929479e-01  6.95603548e-05  1.94238295e-01  8.00237624e-05           99.99           99.99
- 387.00  1.66606022e-01  7.32439232e-05  2.06356006e-01  8.22071974e-05           99.99           99.99
- 388.00  1.78362874e-01  7.72656322e-05  2.20657102e-01  8.49460620e-05           99.99           99.99
- 389.00  1.91168005e-01  8.15926343e-05  2.37116719e-01  8.81519075e-05           99.99           99.99
- 390.00  2.04618287e-01  8.60371583e-05  2.54352193e-01  9.12530836e-05           99.99           99.99
- 391.00  2.18642941e-01  9.05595191e-05  2.72190884e-01  9.41699440e-05           99.99           99.99
- 392.00  2.33241881e-01  9.51508141e-05  2.90902882e-01  9.69800486e-05           99.99           99.99
- 393.00  2.47757369e-01  9.95380828e-05  3.09720582e-01  9.94151930e-05           99.99           99.99
- 394.00  2.62449781e-01  1.03827905e-04  3.28957214e-01  1.01579398e-04           99.99           99.99
- 395.00  2.76561595e-01  1.07723995e-04  3.47617390e-01  1.03173385e-04           99.99           99.99
- 396.00  2.90484469e-01  1.11389111e-04  3.66115424e-01  1.04347107e-04           99.99           99.99
- 397.00  3.03786844e-01  1.14665706e-04  3.83814919e-01  1.04943355e-04           99.99           99.99
- 398.00  3.16444340e-01  1.17557727e-04  4.00577473e-01  1.04964250e-04           99.99           99.99
- 399.00  3.29036320e-01  1.20290235e-04  4.17033309e-01  1.04610013e-04           99.99           99.99
- 400.00  3.40847770e-01  1.22608902e-04  4.32175816e-01  1.03659523e-04           99.99           99.99
- 401.00  3.51727560e-01  1.24475578e-04  4.45724674e-01  1.02101210e-04           99.99           99.99
- 402.00  3.62523374e-01  1.26203093e-04  4.58577354e-01  1.00191259e-04           99.99           99.99
- 403.00  3.73395293e-01  1.27849161e-04  4.71165073e-01  9.80498107e-05           99.99           99.99
- 404.00  3.83168700e-01  1.29018418e-04  4.82197230e-01  9.54380401e-05           99.99           99.99
- 405.00  3.92487346e-01  1.29944019e-04  4.92469156e-01  9.25606166e-05           99.99           99.99
- 406.00  4.01706247e-01  1.30750441e-04  5.02413396e-01  8.95249205e-05           99.99           99.99
- 407.00  4.10080494e-01  1.31202243e-04  5.11097031e-01  8.61910068e-05           99.99           99.99
- 408.00  4.18111383e-01  1.31472202e-04  5.19143948e-01  8.27018813e-05           99.99           99.99
- 409.00  4.25897751e-01  1.31597569e-04  5.26682329e-01  7.91023513e-05           99.99           99.99
- 410.00  4.33235889e-01  1.31521515e-04  5.33465853e-01  7.53796903e-05           99.99           99.99
- 411.00  4.40713666e-01  1.31427573e-04  5.40222840e-01  7.16592676e-05           99.99           99.99
- 412.00  4.47897608e-01  1.31187499e-04  5.46430076e-01  6.78866075e-05           99.99           99.99
- 413.00  4.54324711e-01  1.30673733e-04  5.51528478e-01  6.40216505e-05           99.99           99.99
- 414.00  4.60313158e-01  1.29988922e-04  5.55995849e-01  6.01552475e-05           99.99           99.99
- 415.00  4.66419545e-01  1.29295002e-04  5.60569552e-01  5.63904118e-05           99.99           99.99
- 416.00  4.72245468e-01  1.28482518e-04  5.64778087e-01  5.26977737e-05           99.99           99.99
- 417.00  4.77786567e-01  1.27555367e-04  5.68622415e-01  4.91059447e-05           99.99           99.99
- 418.00  4.83212885e-01  1.26563138e-04  5.72312056e-01  4.56642170e-05           99.99           99.99
- 419.00  4.88154684e-01  1.25413260e-04  5.75414198e-01  4.23745078e-05           99.99           99.99
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- 724.00  6.90406445e-01  1.22086767e-05  5.30301365e-07  2.65915036e-10  7.33875536e-01  1.68726649e-04
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- 752.00  6.51626270e-01  2.98635157e-05           99.99           99.99  7.39291051e-01  2.01552689e-04
- 753.00  6.49032293e-01  3.04252496e-05           99.99           99.99  7.38602134e-01  2.01412431e-04
- 754.00  6.47150544e-01  3.10134232e-05           99.99           99.99  7.38787481e-01  2.01443024e-04
- 755.00  6.46231665e-01  3.16423606e-05           99.99           99.99  7.40073712e-01  2.01706815e-04
- 756.00  6.44301161e-01  3.22161602e-05           99.99           99.99  7.40090085e-01  2.01558118e-04
- 757.00  6.42591901e-01  3.27944347e-05           99.99           99.99  7.40343842e-01  2.01408464e-04
- 758.00  6.40525269e-01  3.33475935e-05           99.99           99.99  7.40136266e-01  2.01068464e-04
- 759.00  6.38859881e-01  3.39146683e-05           99.99           99.99  7.40311577e-01  2.00768358e-04
- 760.00  6.36105955e-01  3.44161514e-05           99.99           99.99  7.39191603e-01  2.00054088e-04
- 761.00  6.34343902e-01  3.49632734e-05           99.99           99.99  7.39099803e-01  1.99556137e-04
- 762.00  6.32896096e-01  3.55208963e-05           99.99           99.99  7.39420194e-01  1.99107394e-04
- 763.00  6.30976684e-01  3.60449577e-05           99.99           99.99  7.38936831e-01  1.98381150e-04
- 764.00  6.29296421e-01  3.65752454e-05           99.99           99.99  7.38716800e-01  1.97665707e-04
- 765.00  6.27303744e-01  3.70797660e-05           99.99           99.99  7.37826166e-01  1.96712132e-04
- 766.00  6.25030680e-01  3.75594235e-05           99.99           99.99  7.36639044e-01  1.95622647e-04
- 767.00  6.22227291e-01  3.79980450e-05           99.99           99.99  7.34544013e-01  1.94237498e-04
- 768.00  6.20911861e-01  3.85192178e-05           99.99           99.99  7.34212987e-01  1.93264278e-04
- 769.00  6.17873955e-01  3.89249199e-05           99.99           99.99  7.31627838e-01  1.91644868e-04
- 770.00  6.15501457e-01  3.93628396e-05           99.99           99.99  7.29990507e-01  1.90223617e-04
- 771.00  6.13840826e-01  3.98378328e-05           99.99           99.99  7.29097892e-01  1.88945106e-04
- 772.00  6.11354644e-01  4.02506234e-05           99.99           99.99  7.27382044e-01  1.87403067e-04
- 773.00  6.09068523e-01  4.06673109e-05           99.99           99.99  7.25771532e-01  1.85840077e-04
- 774.00  6.07479810e-01  4.11220653e-05           99.99           99.99  7.25137891e-01  1.84478413e-04
- 775.00  6.05089456e-01  4.15139016e-05           99.99           99.99  7.23438736e-01  1.82798001e-04
- 776.00  6.02636396e-01  4.18919392e-05           99.99           99.99  7.21850197e-01  1.81100489e-04
- 777.00  5.99457487e-01  4.22092712e-05           99.99           99.99  7.19261348e-01  1.79109675e-04
- 778.00  5.97541445e-01  4.26057205e-05           99.99           99.99  7.18329759e-01  1.77489036e-04
- 779.00  5.95929448e-01  4.30153949e-05           99.99           99.99  7.17642151e-01  1.75883479e-04
- 780.00  5.92399976e-01  4.32767512e-05           99.99           99.99  7.14835253e-01  1.73718060e-04
- 781.00  5.89922928e-01  4.36042964e-05           99.99           99.99  7.13275435e-01  1.71818084e-04
- 782.00  5.88498932e-01  4.40007707e-05           99.99           99.99  7.13181348e-01  1.70228766e-04
- 783.00  5.86177867e-01  4.43213608e-05           99.99           99.99  7.11970462e-01  1.68330578e-04
- 784.00  5.82739383e-01  4.45469256e-05           99.99           99.99  7.09605551e-01  1.66123307e-04
- 785.00  5.79941538e-01  4.48105193e-05           99.99           99.99  7.08105796e-01  1.64084018e-04
- 786.00  5.77515441e-01  4.50927198e-05           99.99           99.99  7.07276904e-01  1.62162952e-04
- 787.00  5.74941869e-01  4.53534573e-05           99.99           99.99  7.06274165e-01  1.60164477e-04
- 788.00  5.72573190e-01  4.56204402e-05           99.99           99.99  7.05780241e-01  1.58243837e-04
- 789.00  5.70267159e-01  4.58826951e-05           99.99           99.99  7.05322576e-01  1.56293192e-04
- 790.00  5.67402553e-01  4.60898912e-05           99.99           99.99  7.04541773e-01  1.54234359e-04
- 791.00  5.64846737e-01  4.63118555e-05           99.99           99.99  7.04016212e-01  1.52195802e-04
- 792.00  5.62591010e-01  4.65485686e-05           99.99           99.99  7.04292896e-01  1.50292948e-04
- 793.00  5.60125763e-01  4.67581525e-05           99.99           99.99  7.04105005e-01  1.48253016e-04
- 794.00  5.57100029e-01  4.69105868e-05           99.99           99.99  7.03726619e-01  1.46137618e-04
- 795.00  5.53910813e-01  4.70383815e-05           99.99           99.99  7.02904404e-01  1.43897317e-04
- 796.00  5.51199750e-01  4.71961510e-05           99.99           99.99  7.03217428e-01  1.41855404e-04
- 797.00  5.48455714e-01  4.73407982e-05           99.99           99.99  7.03217911e-01  1.39714709e-04
- 798.00  5.45932611e-01  4.74943582e-05           99.99           99.99  7.04036301e-01  1.37699904e-04
- 799.00  5.42721649e-01  4.75776214e-05           99.99           99.99  7.03688727e-01  1.35422219e-04
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- 804.00  5.28403880e-01  4.79891708e-05           99.99           99.99  7.04359599e-01  1.24016841e-04
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- 808.00  5.15840113e-01  4.80298665e-05           99.99           99.99  7.02003614e-01  1.13881572e-04
- 809.00  5.13186641e-01  4.80595151e-05           99.99           99.99  7.02159197e-01  1.11409818e-04
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- 813.00  5.02115590e-01  4.80362068e-05           99.99           99.99  7.00321700e-01  1.00915948e-04
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- 815.00  4.95971510e-01  4.79067814e-05           99.99           99.99  6.98328955e-01  9.54101531e-05
- 816.00  4.91996429e-01  4.77394608e-05           99.99           99.99  6.96403737e-01  9.25152005e-05
- 817.00  4.88823768e-01  4.76396702e-05           99.99           99.99  6.94931033e-01  8.96746479e-05
- 818.00  4.86045767e-01  4.75685983e-05           99.99           99.99  6.94217419e-01  8.69228236e-05
- 819.00  4.82688992e-01  4.74311334e-05           99.99           99.99  6.92814859e-01  8.40763659e-05
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- 821.00  4.75897338e-01  4.71188460e-05           99.99           99.99  6.89373845e-01  7.82988158e-05
- 822.00  4.73142654e-01  4.70117269e-05           99.99           99.99  6.88244735e-01  7.54749580e-05
- 823.00  4.69907593e-01  4.68474808e-05           99.99           99.99  6.86825967e-01  7.26176911e-05
- 824.00  4.66919323e-01  4.66984387e-05           99.99           99.99  6.85778518e-01  6.97991726e-05
- 825.00  4.63232702e-01  4.64700995e-05           99.99           99.99  6.83017896e-01  6.68126615e-05
- 826.00  4.59884631e-01  4.62662566e-05           99.99           99.99  6.81721426e-01  6.39784578e-05
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- 828.00  4.53346951e-01  4.58468993e-05           99.99           99.99  6.78107696e-01  5.82399459e-05
- 829.00  4.50045780e-01  4.56203532e-05           99.99           99.99  6.76209938e-01  5.53825636e-05
- 830.00  4.47393833e-01  4.54508203e-05           99.99           99.99  6.75018496e-01  5.25972726e-05
- 831.00  4.44309807e-01  4.52287323e-05           99.99           99.99  6.73710351e-01  4.98178683e-05
- 832.00  4.41085939e-01  4.49837214e-05           99.99           99.99  6.71397570e-01  4.69872172e-05
- 833.00  4.38000883e-01  4.47442784e-05           99.99           99.99  6.69966893e-01  4.42461065e-05
- 834.00  4.35105537e-01  4.45157808e-05           99.99           99.99  6.68895327e-01  4.15567957e-05
- 835.00  4.32121809e-01  4.42699177e-05           99.99           99.99  6.66883106e-01  3.88457377e-05
- 836.00  4.28620861e-01  4.39627647e-05           99.99           99.99  6.65359978e-01  3.62094855e-05
- 837.00  4.24482653e-01  4.35819371e-05           99.99           99.99  6.61003683e-01  3.34840709e-05
- 838.00  4.21066579e-01  4.32670859e-05           99.99           99.99  6.59287732e-01  3.09706146e-05
- 839.00  4.18041166e-01  4.29844385e-05           99.99           99.99  6.57443751e-01  2.85362132e-05
- 840.00  4.14784905e-01  4.26702447e-05           99.99           99.99  6.55245302e-01  2.61945028e-05
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- 842.00  4.07626467e-01  4.19523924e-05           99.99           99.99  6.49910845e-01  2.19273378e-05
- 843.00  4.04648726e-01  4.16441265e-05           99.99           99.99  6.48182851e-01  2.01338121e-05
- 844.00  4.02525287e-01  4.14164335e-05           99.99           99.99  6.47767170e-01  1.86536631e-05
- 845.00  3.98521565e-01  4.09880691e-05           99.99           99.99  6.43749713e-01  1.74137460e-05
- 846.00  3.94418335e-01  4.05424859e-05           99.99           99.99  6.40826913e-01  1.66168486e-05
- 847.00  3.90756327e-01  4.01354226e-05           99.99           99.99  6.37501423e-01  1.62695606e-05
- 848.00  3.87320969e-01  3.97449158e-05           99.99           99.99  6.34389967e-01  1.64034053e-05
- 849.00  3.84182575e-01  3.93782548e-05           99.99           99.99  6.32650221e-01  1.70254875e-05
- 850.00  3.80351910e-01  3.89342076e-05           99.99           99.99  6.27862580e-01  1.79597665e-05
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- 852.00  3.74020127e-01  3.81634312e-05           99.99           99.99  6.23607819e-01  2.08803995e-05
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-1004.00  2.12750382e-02  5.53820000e-06           99.99           99.99  6.93747773e-02  6.32863973e-06
-1005.00  2.05393730e-02  5.44886029e-06           99.99           99.99  6.61172781e-02  5.55974638e-06
-1006.00  1.98252817e-02  5.35890794e-06           99.99           99.99  6.28712013e-02  4.83041022e-06
-1007.00  1.91392465e-02  5.27035993e-06           99.99           99.99  6.04979441e-02  4.20190213e-06
-1008.00  1.84634887e-02  5.17856647e-06           99.99           99.99  5.77320676e-02  3.57806521e-06
-1009.00  1.77940347e-02  5.08246182e-06           99.99           99.99  5.43783149e-02  2.95908684e-06
-1010.00  1.71045299e-02  4.97439134e-06           99.99           99.99  5.21648656e-02  2.44185213e-06
-1011.00  1.64408885e-02  4.86754556e-06           99.99           99.99  4.98818943e-02  1.95659652e-06
-1012.00  1.57992794e-02  4.76108931e-06           99.99           99.99  4.67519123e-02  1.48638653e-06
-1013.00  1.51890084e-02  4.65814131e-06           99.99           99.99  4.43954393e-02  1.10153766e-06
-1014.00  1.46000832e-02  4.55600402e-06           99.99           99.99  4.25383196e-02  8.08250351e-07
-1015.00  1.40438991e-02  4.45856143e-06           99.99           99.99  4.00457635e-02  6.39634047e-07
-1016.00  1.35152060e-02  4.36457675e-06           99.99           99.99  3.75725452e-02  6.57599871e-07
-1017.00  1.29890078e-02  4.26622064e-06           99.99           99.99  3.60426235e-02  8.24444806e-07
-1018.00  1.24326267e-02  4.15254975e-06           99.99           99.99  3.41708897e-02  1.03344034e-06
-1019.00  1.19180270e-02  4.04742612e-06           99.99           99.99  3.18119130e-02  1.22781920e-06
-1020.00  1.13958923e-02  3.93445631e-06           99.99           99.99  3.01690233e-02  1.43343869e-06
-1021.00  1.09115390e-02  3.82934607e-06           99.99           99.99  2.88635385e-02  1.63984439e-06
-1022.00  1.04521107e-02  3.72808976e-06           99.99           99.99  2.69578199e-02  1.79024786e-06
-1023.00  1.00129018e-02  3.62934884e-06           99.99           99.99  2.52710953e-02  1.92702652e-06
-1024.00  9.59084092e-03  3.53228361e-06           99.99           99.99  2.41169738e-02  2.08183755e-06
-1025.00  9.19348122e-03  3.43996297e-06           99.99           99.99  2.28553054e-02  2.20779080e-06
-1026.00  8.79047352e-03  3.34123277e-06           99.99           99.99  2.12025816e-02  2.27021949e-06
-1027.00  8.38172296e-03  3.23590106e-06           99.99           99.99  2.00423128e-02  2.35975791e-06
-1028.00  7.98808843e-03  3.13198744e-06           99.99           99.99  1.90770916e-02  2.45317319e-06
-1029.00  7.61580777e-03  3.03219424e-06           99.99           99.99  1.77731553e-02  2.48169437e-06
-1030.00  7.25157056e-03  2.93147781e-06           99.99           99.99  1.65918440e-02  2.50294782e-06
-1031.00  6.91641033e-03  2.83856768e-06           99.99           99.99  1.57559173e-02  2.55654060e-06
-1032.00  6.59050148e-03  2.74569488e-06           99.99           99.99  1.48486139e-02  2.58137167e-06
-1033.00  6.28198777e-03  2.65643006e-06           99.99           99.99  1.37182572e-02  2.54630826e-06
-1034.00  5.97895856e-03  2.56594492e-06           99.99           99.99  1.29141151e-02  2.55137556e-06
-1035.00  5.68605069e-03  2.47632016e-06           99.99           99.99  1.22217690e-02  2.56286993e-06
-1036.00  5.40603194e-03  2.38893053e-06           99.99           99.99  1.13707307e-02  2.52443512e-06
-1037.00  5.12860149e-03  2.29936564e-06           99.99           99.99  1.05711368e-02  2.47902675e-06
-1038.00  4.86306725e-03  2.21186994e-06           99.99           99.99  9.99104989e-03  2.46968395e-06
-1039.00  4.60737466e-03  2.12568959e-06           99.99           99.99  9.37161738e-03  2.43712840e-06
-1040.00  4.36700622e-03  2.04354688e-06           99.99           99.99  8.61890823e-03  2.35385282e-06
-1041.00  4.13684231e-03  1.96328070e-06           99.99           99.99  8.07236638e-03  2.31142408e-06
-1042.00  3.91409777e-03  1.88372090e-06           99.99           99.99  7.60517614e-03  2.27971565e-06
-1043.00  3.70426533e-03  1.80766479e-06           99.99           99.99  7.04576714e-03  2.20790291e-06
-1044.00  3.49768928e-03  1.73056560e-06           99.99           99.99  6.49708839e-03  2.12559375e-06
-1045.00  3.29787242e-03  1.65421684e-06           99.99           99.99  6.11395300e-03  2.08574191e-06
-1046.00  3.10114462e-03  1.57686195e-06           99.99           99.99  5.72535895e-03  2.03432038e-06
-1047.00  2.91166362e-03  1.50067909e-06           99.99           99.99  5.22217613e-03  1.93053762e-06
-1048.00  2.73715363e-03  1.42982625e-06           99.99           99.99  4.85607994e-03  1.86587543e-06
-1049.00  2.57163006e-03  1.36142302e-06           99.99           99.99  4.56761733e-03  1.82239296e-06
-1050.00  2.41251048e-03  1.29424919e-06           99.99           99.99  4.22677141e-03  1.74954577e-06
-1051.00           99.99           99.99           99.99           99.99  3.84829941e-03  1.65112407e-06
-1052.00           99.99           99.99           99.99           99.99  3.59845977e-03  1.59908480e-06
-1053.00           99.99           99.99           99.99           99.99  3.36810276e-03  1.54900173e-06
-1054.00           99.99           99.99           99.99           99.99  3.07450240e-03  1.46230352e-06
-1055.00           99.99           99.99           99.99           99.99  2.81129339e-03  1.38186233e-06
-1056.00           99.99           99.99           99.99           99.99  2.63746389e-03  1.33892150e-06
-1057.00           99.99           99.99           99.99           99.99  2.45553507e-03  1.28662516e-06
-1058.00           99.99           99.99           99.99           99.99  2.20908009e-03  1.19397247e-06
-1059.00           99.99           99.99           99.99           99.99  2.03073979e-03  1.13152773e-06
-1060.00           99.99           99.99           99.99           99.99  1.90498995e-03  1.09368821e-06
-1061.00           99.99           99.99           99.99           99.99  1.75292299e-03  1.03639534e-06
-1062.00           99.99           99.99           99.99           99.99  1.56799085e-03  9.54221377e-07
-1063.00           99.99           99.99           99.99           99.99  1.45283230e-03  9.09607707e-07
-1064.00           99.99           99.99           99.99           99.99  1.35710511e-03  8.73742431e-07
-1065.00           99.99           99.99           99.99           99.99  1.23235835e-03  8.15538149e-07
-1066.00           99.99           99.99           99.99           99.99  1.10451616e-03  7.50982817e-07
-1067.00           99.99           99.99           99.99           99.99  1.02517422e-03  7.15857321e-07
-1068.00           99.99           99.99           99.99           99.99  9.52947059e-04  6.83117073e-07
-1069.00           99.99           99.99           99.99           99.99  8.54406689e-04  6.28523345e-07
-1070.00           99.99           99.99           99.99           99.99  7.69338960e-04  5.80555231e-07
-1071.00           99.99           99.99           99.99           99.99  7.13493700e-04  5.52114467e-07
-1072.00           99.99           99.99           99.99           99.99  6.58462324e-04  5.22314893e-07
-1073.00           99.99           99.99           99.99           99.99  5.84632519e-04  4.75227106e-07
-1074.00           99.99           99.99           99.99           99.99  5.28503009e-04  4.40089902e-07
-1075.00           99.99           99.99           99.99           99.99  4.90531778e-04  4.18311871e-07
-1076.00           99.99           99.99           99.99           99.99  4.49461985e-04  3.92403384e-07
-1077.00           99.99           99.99           99.99           99.99  3.96150459e-04  3.53979690e-07
-1078.00           99.99           99.99           99.99           99.99  3.59992587e-04  3.29128619e-07
-1079.00           99.99           99.99           99.99           99.99  3.33217606e-04  3.11625587e-07
-1080.00           99.99           99.99           99.99           99.99  3.02837270e-04  2.89621124e-07
-1081.00           99.99           99.99           99.99           99.99           99.99           99.99
-1082.00           99.99           99.99           99.99           99.99           99.99           99.99
-1083.00           99.99           99.99           99.99           99.99           99.99           99.99
-1084.00           99.99           99.99           99.99           99.99           99.99           99.99
-1085.00           99.99           99.99           99.99           99.99           99.99           99.99
-1086.00           99.99           99.99           99.99           99.99           99.99           99.99
-1087.00           99.99           99.99           99.99           99.99           99.99           99.99
-1088.00           99.99           99.99           99.99           99.99           99.99           99.99
-1089.00           99.99           99.99           99.99           99.99           99.99           99.99
-1090.00           99.99           99.99           99.99           99.99           99.99           99.99
-1091.00           99.99           99.99           99.99           99.99           99.99           99.99
-1092.00           99.99           99.99           99.99           99.99           99.99           99.99
-1093.00           99.99           99.99           99.99           99.99           99.99           99.99
-1094.00           99.99           99.99           99.99           99.99           99.99           99.99
-1095.00           99.99           99.99           99.99           99.99           99.99           99.99
-1096.00           99.99           99.99           99.99           99.99           99.99           99.99
-1097.00           99.99           99.99           99.99           99.99           99.99           99.99
-1098.00           99.99           99.99           99.99           99.99           99.99           99.99
-1099.00           99.99           99.99           99.99           99.99           99.99           99.99
-1100.00           99.99           99.99           99.99           99.99           99.99           99.99
diff --git a/filt_func/gaia/edr3/ReadMe b/filt_func/gaia/edr3/ReadMe
deleted file mode 100644
index bd3e2f27..00000000
--- a/filt_func/gaia/edr3/ReadMe
+++ /dev/null
@@ -1,134 +0,0 @@
-J/A+A/649/A3     Gaia Early Data Release 3 photometric passbands (Riello+, 2021)
-================================================================================
-Gaia Early Data Release 3: Photometric content and validation.
-    Riello M., De Angeli F., Evans D.W., Montegriffo P., Carrasco J.M,
-    Busso G., Palaversa L., Burgess P., Diener C., Davidson M., Rowell N.,
-    Fabricius C., Jordi C., Bellazzini M., Pancino E., Harrison D.L.,
-    Cacciari C., van Leeuwen F., Hambly N.C., Hodgkin S.T., Osborne P.J.,
-    Altavilla G., Barstow M.A., Brown A.G.A., Castellani M., Cowell S.,
-    De Luise F., Gilmore G., Giuffrida G., Hidalgo S., Holland G., Marinoni S.,
-    Pagani C., Piersimoni A.M., Pulone L., Ragaini S., Rainer M., Richards P.J.,
-    Sanna N., Walton N.A., Weiler M., Yoldas A.
-    <Astron. Astrophys. 649, A3 (2021)>
-    =2021A&A...649A...3R        (SIMBAD/NED BibCode)
-================================================================================
-ADC_Keywords: Surveys ; Photometry, G band
-Keywords: catalogues - surveys - instrumentation: photometers -
-          techniques: photometric - Galaxy: general
-
-Abstract:
-    Gaia Early Data Release 3 (Gaia EDR3) contains astrometry and
-    photometry results for about 1.8 billion sources based on
-    observations collected by the European Space Agency Gaia satellite
-    during the first 34 months of its operational phase.
-
-    In this paper, we focus on the photometric content, describing the
-    input data, the algorithms, the processing, and the validation of the
-    results. Particular attention is given to the quality of the data and
-    to a number of features that users may need to take into account to
-    make the best use of the Gaia EDR3 catalogue.
-
-    The processing broadly followed the same procedure as for Gaia DR2,
-    but with significant improvements in several aspects of the blue and
-    red photometer (BP and RP) preprocessing and in the photometric
-    calibration process. In particular, the treatment of the BP and RP
-    background has been updated to include a better estimation of the
-    local background, and the detection of crowding effects has been used
-    to exclude affected data from the calibrations. The photometric
-    calibration models have also been updated to account for flux loss
-    over the whole magnitude range. Significant improvements in the
-    modelling and calibration of the Gaia point and line spread functions
-    have also helped to reduce a number of instrumental effects that were
-    still present in DR2.
-
-    Gaia EDR3 contains 1.806 billion sources with G-band photometry and
-    1.540 billion sources with GBP and GRP photometry. The median
-    uncertainty in the G-band photometry, as measured from the standard
-    deviation of the internally calibrated mean photometry for a given
-    source, is 0.2mmag at magnitude G=10 to 14, 0.8mmag at G~17, and
-    2.6mmag at G~19. The significant magnitude term found in the Gaia DR2
-    photometry is no longer visible, and overall there are no trends
-    larger than 1mmag/mag. Using one passband over the whole colour and
-    magnitude range leaves no systematics above the 1% level in magnitude
-    in any of the bands, and a larger systematic is present for a very
-    small sample of bright and blue sources. A detailed description of the
-    residual systematic effects is provided. Overall the quality of the
-    calibrated mean photometry in Gaia EDR3 is superior with respect to
-    DR2 for all bands.
-
-Description:
-    These tabular data describes the photometric system defined by the G,
-    G_BP_ and G_RP_ Gaia bands for Gaia Early Data Release 3.
-
-    The tables provide the full passband and the corresponding zero point
-    for each of the photometric bands. The zero points are available both
-    in the VEGAMAG and AB systems.
-
-    The passband calibration is based on the modelling of a set of
-    corrections applied to pre-launch knowledge of the instrument, to find
-    the best match between observed and synthetic photometry for a set of
-    calibrators. For EDR3 a large set of calibrators covering a wide range
-    of spectra types was used for the passband calibration.
-
-    For these sources reconstructed SEDs were obtained from externally
-    calibrated Gaia BP/RP spectra.
-
-File Summary:
---------------------------------------------------------------------------------
- FileName      Lrecl  Records   Explanations
---------------------------------------------------------------------------------
-ReadMe            80        .   This file
-passband.dat     103      781   G, G_BP_ anf G_RP_ passbands used to generate
-                                 the magnitudes and astrophysical parameters
-                                 included in Gaia EDR3
-zeropt.dat        97        2   G, G_BP_ and G_RP_ zero points used to generate
-                                 the magnitudes and astrophysical parameters
-                                 included in Gaia EDR3
---------------------------------------------------------------------------------
-
-See also:
-        I/350 : Gaia EDR3 (Gaia Collaboration, 2020)
- J/A+A/649/A6 : Gaia Catalogue of Nearby Stars - GCNS (Gaia collaboration, 2021)
- J/A+A/649/A7 : MC structure and properties (Gaia Collaboration+, 2021)
-
-Byte-by-byte Description of file: passband.dat
---------------------------------------------------------------------------------
-   Bytes Format Units   Label     Explanations
---------------------------------------------------------------------------------
-   1-  7  F7.2  nm      lambda    Wavelength
-  10- 23  E14.9 mag     GPb       ?=99.99 G transmissivity curve at the
-                                   corresponding wavelength (1)
-  26- 39  E14.9 mag   e_GPb       ?=99.99 Uncertainty on the G transmissivity
-                                   curve (1)
-  42- 55  E14.9 mag     BPPb      ?=99.99 BP transmissivity curve at the
-                                   corresponding wavelength (1)
-  58- 71  E14.9 mag   e_BPPb      ?=99.99 Uncertainty on the BP transmissivity
-                                   curve (1)
-  74- 87  E14.9 mag     RPPb      ?=99.99 RP transmissivity curve at the
-                                   corresponding wavelength (1)
-  90-103  E14.9 mag   e_RPPb      ?=99.99 Uncertainty on the RP transmissivity
-                                   curve (1)
---------------------------------------------------------------------------------
-Note (1): In correspondence to wavelength values where the passband is not
-   defined, both transmissivity and uncertainty are set to 99.99.
---------------------------------------------------------------------------------
-
-Byte-by-byte Description of file: zeropt.dat
---------------------------------------------------------------------------------
-   Bytes Format Units   Label     Explanations
---------------------------------------------------------------------------------
-   2- 14 F13.10 ---     GZp       G band zero point
-  18- 29 F12.10 ---   e_GZp       G band zero point uncertainty
-  32- 44 F13.10 ---     BPZp      G_BP_ band zero point
-  48- 59 F12.10 ---   e_BPZp      G_BP_ band zero point uncertainty
-  62- 74 F13.10 ---     RPZp      G_RP_ band zero point
-  78- 89 F12.10 ---   e_RPZp      G_RP_ band zero point uncertainty
-  91- 97  A7    ---     System    [VEGAMAG, AB] Photometric system
---------------------------------------------------------------------------------
-
-Acknowledgements:
-    Marco Riello, mriello(at)ast.cam.ac.uk
-    Francesca De Angeli, fda(at)ast.cam.ac.uk
-
-================================================================================
-(End)     Francesca De Angeli [IoA, UK], Patricia Vannier [CDS]      05-Jan-2021
diff --git a/spisea/evolution.py b/spisea/evolution.py
index b99373dd..2f9dd760 100755
--- a/spisea/evolution.py
+++ b/spisea/evolution.py
@@ -66,8 +66,8 @@ class StellarEvolution(object):
     """
     Base Stellar evolution class.
 
-    Subclasses must define the following parameters:
-    ------------------------------------------------
+    Parameters
+    ----------
     model_dir: path
         Directory path to evolution model files
 
@@ -83,9 +83,6 @@ class StellarEvolution(object):
     model_version_name: string
         Name of the model class plus additional details like version
         numbers and rotation if relevant.
-
-    AKs_grid_age_list: list
-        Sparser list of ages to use for AKs interpolation grid
     """
     def __init__(self, model_dir, age_list, mass_list, z_list):
         self.model_dir = model_dir
@@ -117,6 +114,8 @@ def __init__(self):
 
         # specify location of model files
         self.model_dir = models_dir + 'geneva/'
+        
+        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
 
         self.z_solar = 0.02
         self.z_file_map = {0.01: 'z01/', 0.02: 'z02/', 0.03: 'z03/'}
@@ -1049,8 +1048,6 @@ def __init__(self, version=1.2, synthpop_extension=False):
 
         # populate list of isochrone ages (log scale)
         self.age_list = np.arange(5.01, 10.30+0.005, 0.01)
-        self.AKs_grid_age_list = np.linspace(5.0,10.3,107)
-        self.AKs_grid_age_list[0] = 5.01
 
         # Set version directory
         self.version = version
@@ -1289,7 +1286,8 @@ def __init__(self, rot=True):
         age_list = np.arange(6.0, 10.091, 0.01).tolist()
 
         # specify location of model files
-        self.model_dir = models_dir + 'merged/baraffe_pisa_ekstrom_parsec/'
+        model_dir = models_dir + 'merged/baraffe_pisa_ekstrom_parsec/'
+        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
         self.z_solar = 0.015
 
         # Switch to specify rotating/non-rotating models
@@ -1395,7 +1393,8 @@ def __init__(self, rot=True):
         age_list = np.arange(6.0, 8.001, 0.01).tolist()
 
         # specify location of model files
-        self.model_dir = models_dir + 'merged/pisa_ekstrom_parsec/'
+        model_dir = models_dir + 'merged/pisa_ekstrom_parsec/'
+        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
         self.z_solar = 0.015
 
         #Switch to specify rot/notot
@@ -1509,7 +1508,8 @@ def __init__(self):
         age_list.append(9.78)
 
         # specify location of model files
-        self.model_dir = models_dir + 'merged/siess_meynetMaeder_padova/'
+        model_dir = models_dir + 'merged/siess_meynetMaeder_padova/'
+        StellarEvolution.__init__(self, model_dir, age_list, mass_list, z_list)
         self.z_solar = 0.02
 
         # Metallicity map
diff --git a/spisea/filters.py b/spisea/filters.py
index ca295551..e2a2aee9 100755
--- a/spisea/filters.py
+++ b/spisea/filters.py
@@ -340,12 +340,12 @@ def get_gaia_filt(version, name):
     the revised DR2 zeropoints from
     Evans+18.
 
-    version: specify dr1, dr2, dr2_rev, edr3
+    version: specify dr1, dr2, or dr2_rev
     name: filter name
     """
     # Assert that we are using the revised DR2 zeropoints
-    if version not in ['dr2_rev', 'edr3']:
-        msg = 'Gaia version {0} not supported, use dr2_rev or edr3 instead'.format(version)
+    if version != 'dr2_rev':
+        msg = 'Gaia version {0} not supported, use dr2_rev instead'.format(version)
         raise ValueError(msg)
 
     # Set the filter directory
@@ -355,8 +355,6 @@ def get_gaia_filt(version, name):
         path = '{0}/gaia/dr2/'.format(filters_dir)
     elif version == 'dr2_rev':
         path = '{0}/gaia/dr2_rev/'.format(filters_dir)
-    elif version == 'edr3':
-        path = '{0}/gaia/edr3/'.format(filters_dir)
     else:
         raise ValueError('GAIA filter version {0} not understood. Please use dr1, dr2, or dr2_rev'.format(version))
 
diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 1f3f7453..4dec9340 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -1179,14 +1179,6 @@ class IsochronePhot(Isochrone):
         Define what filters the synthetic photometry
         will be calculated for, via the filter string
         identifier.
-
-    verbose : bool
-        Determines whether certain information gets printed
-
-    interp_AKs_grid : bool
-        If true, interpolate over existing grid for AKs values, instead of
-        re-generating all photometry from scratch. If False, re-generate all
-        photometry from scratch if the file does not already exist.
     """
     def __init__(self, logAge, AKs, distance,
                  metallicity=0.0,
@@ -1197,8 +1189,7 @@ def __init__(self, logAge, AKs, distance,
                  min_mass=None, max_mass=None, rebin=True, recomp=False,
                  filters=['ubv,U', 'ubv,B', 'ubv,V',
                           'ubv,R', 'ubv,I'],
-                verbose=False,
-                interp_AKs_grid=False):
+                verbose=False):
         self.metallicity = metallicity
         self.verbose=verbose
 
@@ -1851,8 +1842,6 @@ def get_filter_col_name(obs_str):
         # Catch Gaia filter cases. Otherwise, it is HST filter
         if 'dr2_rev' in tmp:
             filt_name = 'gaiaDR2_{0}'.format(tmp[-1])
-        elif 'edr3' in tmp:
-            filt_name = 'gaiaEDR3_{0}'.format(tmp[-1])
         elif 'roman' in tmp:
             filt_name = 'roman_{0}'.format(tmp[-1])
         else:
@@ -1924,7 +1913,6 @@ def get_obs_str(col):
                  'ztf_g':'ztf,g', 'ztf_r':'ztf,r', 'ztf_i':'ztf,i',
                  'gaiaDR2_G': 'gaia,dr2_rev,G', 'gaiaDR2_Gbp':'gaia,dr2_rev,Gbp',
                  'gaiaDR2_Grp':'gaia,dr2_rev,Grp',
-                 'gaiaEDR3_G': 'gaia,edr3,G', 'gaiaEDR3_Gbp':'gaia,edr3,Gbp', 'gaiaEDR3_Grp':'gaia,edr3,Grp',
                  'hawki_J': 'hawki,J',
                  'hawki_H': 'hawki,H',
                  'hawki_Ks': 'hawki,Ks',
diff --git a/spisea/tests/test_models.py b/spisea/tests/test_models.py
index 77c5945e..4ba0e683 100644
--- a/spisea/tests/test_models.py
+++ b/spisea/tests/test_models.py
@@ -166,7 +166,6 @@ def test_filters():
                      'decam,y', 'decam,i', 'decam,z',
                      'decam,u', 'decam,g', 'decam,r',
                      'gaia,dr2_rev,G', 'gaia,dr2_rev,Gbp', 'gaia,dr2_rev,Grp',
-                     'gaia,edr3,G', 'gaia,edr3,Gbp', 'gaia,edr3,Grp',
                      'jwst,F070W', 'jwst,F090W', 'jwst,F115W', 'jwst,F140M',
                      'jwst,F150W', 'jwst,F150W2', 'jwst,F162M', 'jwst,F164N',
                      'jwst,F182M', 'jwst,F187N', 'jwst,F200W', 'jwst,F212N',

From 8bfbbde1bb66357a332a4aaf46337d6dac959265 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 13:16:54 -0700
Subject: [PATCH 48/55] fixed assert euqal to isclose

---
 spisea/tests/test_synthetic.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/spisea/tests/test_synthetic.py b/spisea/tests/test_synthetic.py
index 72331850..7694ebfd 100755
--- a/spisea/tests/test_synthetic.py
+++ b/spisea/tests/test_synthetic.py
@@ -1266,7 +1266,8 @@ def test_ResolvedCluster_random_state():
         old_companion = pickle.load(file)
 
     for key in old_star_systems.colnames:
-        np.testing.assert_array_equal(cluster1.star_systems[key], old_star_systems[key])
+        #np.testing.assert_array_equal(cluster1.star_systems[key], old_star_systems[key])
+        assert np.all(np.isclose(cluster1.star_systems[key], old_star_systems[key], rtol=1e-05, atol=1e-08))
 
     for key in old_companion.colnames:
         # Require values are consistent within reasonable bounds

From 4b3ebb0f84172a7de3b2a21ac0a561aed9cd0546 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:48:43 -0700
Subject: [PATCH 49/55] updating version

---
 docs/conf.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/conf.py b/docs/conf.py
index 18901890..f10e26c1 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -25,9 +25,9 @@
 author = 'Matthew Hosek Jr, Jessica R. Lu, Casey Y. Lam'
 
 # The short X.Y version
-version = '2.3'
+version = '2.4'
 # The full version, including alpha/beta/rc tags
-release = '2.3'
+release = '2.4'
 
 
 

From 83b2fd9e948941d09b38428c09be9d92f4a62699 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:48:52 -0700
Subject: [PATCH 50/55] updating contributors

---
 docs/contributors.rst | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/docs/contributors.rst b/docs/contributors.rst
index 6dac7d1e..1944147e 100644
--- a/docs/contributors.rst
+++ b/docs/contributors.rst
@@ -39,8 +39,12 @@ Sage Hironaka Remulla -- added Rubin Observatory filters
 
 Lingfeng Wei -- bugfix to improve creation of iso_dir in
 IsochronePhot, implemented faster cluster generation and test
-functions for primary and companion star mass generation (v2.3)
+functions for primary and companion star mass generation (v2.3),
+updated random state generators (v2.4)
 
 Macy Huston -- New metallicity bound + isochrone filter checks,
 imf_mass_lim bugfix, roman filter bugfix, added Euclid filters, Synthpop compatibility
-updates (v2.2)
+updates (v2.2), improvements for reading in/updated existing isochrone
+files, Vega mag to ST mag conversion function (v2.4)
+
+Anna Pusack -- Added IRTF L-band filter support

From 4cf9e283c0284e7b88fb5056a6a09f956384cecb Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:49:03 -0700
Subject: [PATCH 51/55] adding irtf

---
 docs/filters.rst | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/filters.rst b/docs/filters.rst
index 6efb28fc..3112d4a1 100644
--- a/docs/filters.rst
+++ b/docs/filters.rst
@@ -35,6 +35,7 @@ Available filters:
 * GAIA
 * HAWK-I
 * Hubble Space Telescope
+* IRTF
 * Johnson-Cousins
 * Johnson-Glass
 * JWST

From e774edadf2147b04d096df2a1e4458c24c861b98 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:49:30 -0700
Subject: [PATCH 52/55] updating changelog

---
 docs/index.rst | 11 +++++++++++
 1 file changed, 11 insertions(+)

diff --git a/docs/index.rst b/docs/index.rst
index 71878d34..048f5c8b 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -82,6 +82,17 @@ releases will be co-authors in future SPISEA software papers.
 
 Change Log
 ----------
+2.4 (2026-03-20)
+  * Added backward compatibility for isochrone file names created
+    before v2.3
+  * When reading isochrone from existing file, only keep user
+    requested filters in resulting table.
+  * Changed the global random seed to a random generator within each class,
+    but still retaining the reproducibility. Test cluster files in
+    test_data also updated accordingly for testing purposes
+  * Added filter support for IRTF L-band
+  * Added conversion function between ST mags and Vega mags
+
 2.3 (2026-02-10)
   * Achieves faster cluster generation (factor of about 2x) by using
     replacing ragged arrays with masked arrays when calculating

From 3c1440cef45df6f9caadfac35d5e2b9233ee5452 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:49:58 -0700
Subject: [PATCH 53/55] adding conversion funcs, docs about mag systems

---
 docs/make_isochrone.rst | 27 ++++++++++++++++-----------
 1 file changed, 16 insertions(+), 11 deletions(-)

diff --git a/docs/make_isochrone.rst b/docs/make_isochrone.rst
index c4f3270e..ab070538 100644
--- a/docs/make_isochrone.rst
+++ b/docs/make_isochrone.rst
@@ -9,7 +9,10 @@ total extinction, and metallicity, along with the :ref:`atmo_models`,
 :ref:`evo_models`, and :ref:`ext_law`. 
 
 If the IsochronePhot sub-class is used then synthetic photometry
-will be produced. The :ref:`filters` are defined as additional inputs.
+will be produced. The :ref:`filters` are defined as additional
+inputs. The output photometry is in terms of vega mags, but the user
+can also calculate the required conversion to AB mags or ST mags using
+the functions in :ref:`phot_conversions`
 
 An example of making an IsochronePhot object::
 
@@ -76,10 +79,9 @@ Tips and Tricks: The IsochronePhot Object
 
   * **WARNING**: When IsochronePhot checks to see if the desired
     isochrone table already exists, it checks all isochrone properties
-    except for the photometric filters (evolution models, atmosphere
-    models, and reddening law are encoded in the table meta-data).
+    (evolution models, atmosphere models, and reddening law are encoded in the table meta-data).
     If any of these parameters do not match, then the isochrone will
-    be re-calculated.
+    be re-calculated. 
 
     However, to keep the isochrone filenames reasonable, only the
     age, extinction, distance, and metallicity are encoded in the
@@ -91,13 +93,6 @@ Tips and Tricks: The IsochronePhot Object
     that users specify different iso_dir paths when making isochrones
     with different evolution models, atmosphere models, or reddening
     laws.*
-    
-  * **WARNING**: IsochronePhot does not check existing
-    isochrone tables to see if the photometric filters match
-    those specified by the user. *So, if the user wishes to generate an
-    isochrone with different filters, we recommend either using a
-    different iso_dir path or setting the keyword recomp=True (see
-    docs below).*
 
 Base Isochrone Class
 ----------------------------
@@ -112,3 +107,13 @@ Isochrone Sub-classes
 .. autoclass:: synthetic.IsochronePhot
 	       :show-inheritance:
 		:members: make_photometry, plot_CMD, plot_mass_magnitude
+
+
+Photometry Conversion Functions
+-----------------------------
+.. _phot_conversions:
+
+.. autofunction:: synthetic.calc_ab_vega_filter_conversion
+
+.. autofunction:: synthetic.calc_st_vega_filter_conversion
+

From 39bafec7056e9f7b44da2027d1fc0a6153a8325f Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 14:54:49 -0700
Subject: [PATCH 54/55] fixing links

---
 docs/make_isochrone.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/make_isochrone.rst b/docs/make_isochrone.rst
index ab070538..5f764c93 100644
--- a/docs/make_isochrone.rst
+++ b/docs/make_isochrone.rst
@@ -12,7 +12,7 @@ If the IsochronePhot sub-class is used then synthetic photometry
 will be produced. The :ref:`filters` are defined as additional
 inputs. The output photometry is in terms of vega mags, but the user
 can also calculate the required conversion to AB mags or ST mags using
-the functions in :ref:`phot_conversions`
+the functions in :ref:`Photometry Conversion Functions <phot_conversions>`. 
 
 An example of making an IsochronePhot object::
 

From fb3cdc2b16d337223706b7cdb8923734dbd54f02 Mon Sep 17 00:00:00 2001
From: Matt Hosek <mwhosek@nott.astro.ucla.edu>
Date: Fri, 20 Mar 2026 15:06:20 -0700
Subject: [PATCH 55/55] update doc string

---
 spisea/synthetic.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/spisea/synthetic.py b/spisea/synthetic.py
index 4dec9340..7cbca17c 100755
--- a/spisea/synthetic.py
+++ b/spisea/synthetic.py
@@ -2075,10 +2075,10 @@ def calc_ab_vega_filter_conversion(filt_str):
     Note: this conversion is just the vega magnitude in
     AB system
 
-    Parameters:
-    -----------
+    Parameters
+    ----------
     filt_str: string
-        Filter identification string
+        SPISEA filter identification string (see Photometric Filters doc page)
     """
     # Get filter info
     filt = get_filter_info(filt_str)
@@ -2138,10 +2138,10 @@ def calc_st_vega_filter_conversion(filt_str):
     Note: this conversion is just the vega magnitude in 
     ST system
 
-    Parameters:
-    -----------
+    Parameters
+    ----------
     filt_str: string
-        Filter identification string
+        SPISEA filter identification string (see Photometric Filters doc page)
     """
     # Get filter info
     filt = get_filter_info(filt_str)