SparseStorage, concurrent_flat_map, and SparseMatrixAtomic#43
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SparseStorage, concurrent_flat_map, and SparseMatrixAtomic#43
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A segmented open-addressing hash map for integer keys supporting concurrent lock-free find / insert / emplace / expansion. State bits are encoded in the two MSBs of each slot's key. Includes tests covering single-threaded correctness, pointer stability across expansion, and multi-threaded concurrent insert/find, plus a test for SparseMatrixAtomic that exercises its public API under concurrent fetch_add. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replaces tbb::concurrent_unordered_map with the new lock-free insert-only flat map, removing the FIXME about lock contention on inserts. reserve() becomes a no-op since the new map grows on demand. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Required so the map can live as a member of other movable types (e.g. a boost::histogram storage class). The moved-from object is left in a destroy-only state. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Adds narf::concurrent_sparse_storage, a boost::histogram Storage type backed by narf::concurrent_flat_map with has_threading_support = true, plus a make_histogram_sparse factory and python-friendly snapshot helpers (boost::histogram does not expose its storage_ member to cppyy directly). HistoBoost gains a SparseStorage marker class taking an estimated fill_fraction (default 0.1) used to pre-size the underlying map and avoid most on-the-fly expansions. Tensor weights are not supported in this mode and conversion to a python hist.Hist is skipped; the raw RResultPtr is returned. Includes an end-to-end RDataFrame test. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
The SparseStorage path now lazily converts the underlying C++ sparse histogram to a wums.sparse_hist.SparseHist on first dereference, snapshotting the concurrent_flat_map into flat indices/values that match the with-flow row-major layout. Pass convert_to_hist=False to get the raw RResultPtr instead. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Previously every thread that observed a saturated tail segment speculatively allocated a doubled-size successor and then either won the CAS or freed it. Under high thread contention this caused a transient memory spike of M_threads * segment_size per growth event, easily inflating peak RSS by an order of magnitude for multi-GB segments and potentially fragmenting the address space. ensure_next now CAS-publishes a "growing" sentinel into the segment's next pointer before allocating; only the winning thread performs the allocation while losers yield-spin until the real successor is published. All segment walks use a new observed_next helper that treats the sentinel as "no successor yet". Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
boost::histogram linearizes axes column-major (leftmost axis has stride 1), but wums.SparseHist expects numpy row-major flat indices. For ND histograms this caused entries to land in the wrong bins (often flow bins) and silently disappear from toarray(flow=False); 1D was unaffected and so the existing test did not catch it. The conversion now un-ravels each boost-linear key under F order and re-ravels under C order before constructing the SparseHist. Adds a 3D test that cross-checks against a dense HistoBoost. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Replace the hard-coded size0*size1/40 initial capacity with a fill_fraction constructor argument (default 0.025 to match the previous behaviour) that sizes the underlying concurrent_flat_map to fill_fraction * size0 * size1 entries. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Treat continuous-axis bins with infinite width or center as flow bins and return zero correction, preventing NaN propagation when an axis uses np.inf as a bin edge. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
MapWrapper wraps an arbitrary callable so that, when invoked, any argument satisfying narf::is_container is zipped element-wise (with scalar arguments broadcast via make_view) and the callable is applied to each resulting tuple via std::apply. If none of the arguments are containers, the callable is invoked directly with the arguments as-is. Also provide a forwarding constructor so the wrapped callable can be constructed in place from MapWrapper's own constructor arguments, and add a unit test exercising both the container and scalar-passthrough code paths.
Rename the core class to HistShiftHelperImpl and drop its is_container_any branch, collapsing compute and compute_impl into a single scalar-only implementation. HistShiftHelper is now a template alias for MapWrapper<HistShiftHelperImpl<Axes...>>, which restores the previous element-wise behavior for container arguments while keeping the per-event code path untouched.
Rename the core classes to QuantileHelperImpl and QuantileHelperStaticImpl and expose QuantileHelper / QuantileHelperStatic as MapWrapper template aliases over them. This gives both helpers automatic element-wise broadcasting over container arguments while leaving their existing scalar call paths and factory/Python entry points source-compatible. Also add a unit test exercising the scalar and RVec call paths of QuantileHelperStatic.
Thread a bool Continuous template parameter through QuantileHelperImpl and QuantileHelperStaticImpl via a shared quantile_lookup helper. In continuous mode the helpers return a double in [0, 1] obtained by linearly interpolating between adjacent stored edges (edges[i] maps to i/(N-1)), with values outside [edges[0], edges[N-1]] clamped to 0 / 1. Expose QuantileHelperContinuous / QuantileHelperStaticContinuous aliases and a make_quantile_helper_continuous factory. Extend the unit test to cover the scalar and RVec continuous code paths.
Add a continuous=False option to build_quantile_hists which preserves the original (Regular / Variable) quantile axes in the returned helper histograms instead of replacing them with Integer axes. define_quantile_ints auto-detects the mode from the axis type and dispatches to the continuous quantile helpers, feeding the resulting CDF-style columns (named _quant instead of _iquant) to subsequent helpers in the chain.
Also compute per-bin minima (via ak.min) alongside the existing maxima so that per-dimension widths and centers of the final transformed quantile bins can be derived. Return two additional histograms: - centers_hist: multidimensional bin centers stored along an extra StrCategory "coord" axis labelled with the input quantile axis names (with a quant_i placeholder for any unnamed or duplicated name). - volume_hist: product of the per-dimension widths of the same bin. Both are indexed by the full set of conditional and quantile axes matching the last helper histogram. Update the existing call site in test/testquantiles.py to unpack the new return tuple.
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Adds a sparse storage backend for HistoBoost and the supporting
data structures (lock-free concurrent map and SparseMatrixAtomic),
plus a generic MapWrapper helper that is then used to extend the
existing HistShiftHelper / QuantileHelper helpers with automatic
broadcasting over container arguments and a new continuous
quantile-transform mode.
Bottom-up commit list:
add python script for testsAdd SymMatrixAtomicminor improvement for SymMatrixAtomic and add initial version of SparseMatrixAtomicfix deprecated storage_type accessfix constnessmake wrapper more flexible/robustflexible column types for quantile helpersadd missing includemake range_to more flexibleadd lock-free insert-only concurrent_flat_mapadd SparseMatrixAtomic test driverSparseMatrixAtomic: switch to narf::concurrent_flat_mapconcurrent_flat_map: add move constructor and assignmentHistoBoost: add SparseStorage option backed by concurrent_flat_mapHistoBoost SparseStorage: convert result to wums.SparseHistconcurrent_flat_map: serialize segment growth via sentinelSparseStorage: fix ND linearization mismatch with SparseHistSparseMatrixAtomic: configurable fill_fractionHistShiftHelper: guard against non-finite bin geometryAdd MapWrapper helper for element-wise application over container argsHistShiftHelper: delegate container broadcasting to MapWrapperQuantileHelper[Static]: delegate container broadcasting to MapWrapperQuantileHelper[Static]: add continuous CDF-style lookup modedefine_quantile_ints: support continuous quantile modebuild_quantile_hists: return bin centers and volumesThis series is the narf side of the larger sparse-input rework that
the rabbit and wums PRs make use of.
WMass/rabbit#129
WMass/wums#25