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fix: pass minmax to compute_2d_mutual_info and compute_1d_mutual_info #67

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Merged
dlevenstein merged 1 commit into from
Mar 20, 2026
Merged

fix: pass minmax to compute_2d_mutual_info and compute_1d_mutual_info #67

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66 changes: 32 additions & 34 deletions prnn/utils/predictiveNet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -837,16 +837,17 @@ def calculateSpatialRepresentation(
height = env.height
nb_bins_x, nb_bins_y, minmax = env.get_map_bins()

place_fields, xy = nap.compute_2d_tuning_curves_continuous(
rates, position, ep=rates.time_support, nb_bins=(nb_bins_x, nb_bins_y), minmax=minmax
)
SI = nap.compute_2d_mutual_info(
place_fields, position, position.time_support, bitssec=bitsec
)
# Remove units that aren't active in enough timepoints
numactiveT = np.sum((h > 0).numpy(), axis=1)
inactive_cells = numactiveT < activeTimeThreshold
SI.iloc[inactive_cells.flatten()] = 0
place_fields,xy = nap.compute_2d_tuning_curves_continuous(rates,position,
ep=rates.time_support,
nb_bins=(nb_bins_x, nb_bins_y),
minmax=minmax
)
SI = nap.compute_2d_mutual_info(place_fields, position, position.time_support,
minmax=minmax, bitssec=bitsec)
#Remove units that aren't active in enough timepoints
numactiveT = np.sum((h>0).numpy(),axis=1)
inactive_cells = numactiveT<activeTimeThreshold
SI.iloc[inactive_cells.flatten()]=0

if HDinfo:
# Get HD Tuning
Expand All @@ -857,35 +858,32 @@ def calculateSpatialRepresentation(
time_units="s",
)
nb_bins, minmax = env.get_HD_bins()
HD_tuningcurves = nap.compute_1d_tuning_curves_continuous(
rates, HD, ep=rates.time_support, nb_bins=nb_bins, minmax=minmax
)
HD_info = nap.compute_1d_mutual_info(
HD_tuningcurves, HD, HD.time_support, bitssec=bitsec
)
SI["HDinfo"] = HD_info["SI"]
HD_tuningcurves = nap.compute_1d_tuning_curves_continuous(rates,HD,
ep=rates.time_support,
nb_bins=nb_bins,
minmax=minmax)
HD_info = nap.compute_1d_mutual_info(HD_tuningcurves, HD, HD.time_support,
minmax=minmax, bitssec=bitsec)
SI['HDinfo'] = HD_info['SI']


if inputControl:
if self.env_shell.n_obs == 1:
d = obs.squeeze().detach().numpy()[onsetTransient:-1, :]
else:
d = np.concatenate(
[o.squeeze().detach().numpy()[onsetTransient:-1, :] for o in obs], axis=-1
)
rates_input = nap.TsdFrame(t=np.arange(onsetTransient, timesteps), d=d, time_units="s")
pf_input, xy = nap.compute_2d_tuning_curves_continuous(
rates_input,
position,
ep=rates.time_support,
nb_bins=(nb_bins_x, nb_bins_y),
minmax=minmax,
)
SI_input = nap.compute_2d_mutual_info(
pf_input, position, position.time_support, bitssec=bitsec
)
SI_input["pfs"] = pf_input.values()
SI["inputCtrl"] = SI_input["SI"]
SI["inputFields"] = SI_input["pfs"] # pd.DataFrame.from_dict(pf_input)
d = np.concatenate([o.squeeze().detach().numpy()[onsetTransient:-1,:] for o in obs], axis=-1)
rates_input = nap.TsdFrame(t = np.arange(onsetTransient,timesteps),
d = d, time_units = 's')
pf_input,xy = nap.compute_2d_tuning_curves_continuous(rates_input,position,
ep=rates.time_support,
nb_bins=(nb_bins_x, nb_bins_y),
minmax=minmax
)
SI_input = nap.compute_2d_mutual_info(pf_input, position, position.time_support,
minmax=minmax, bitssec=bitsec)
SI_input['pfs'] = pf_input.values()
SI['inputCtrl'] = SI_input['SI']
SI['inputFields'] = SI_input['pfs']#pd.DataFrame.from_dict(pf_input)

if calculatesRSA:
WAKEactivity = {"state": state, "h": np.squeeze(h.detach().numpy())}
Expand Down