Changelog#

0.4.0#

Major rewrite of the core data structures and significant expansion of the API.

New features#

  • Tensor type system — NdArray replaced with a family of purpose-built tensor classes: PcfTensor, IntPcfTensor, FloatTensor, IntTensor, BoolTensor, PointCloudTensor, DistanceMatrixTensor, SymmetricMatrixTensor, BarcodeTensor. Each has a corresponding dtype sentinel.

  • NumPy-like tensor operations — reshape, transpose/.T, squeeze, expand_dims, swapaxes, concatenate, stack, split, array_split, astype, iteration, ndim, size, len().

  • Advanced indexing — slicing with negative strides, multi-axis boolean masking, mixed integer+boolean indexing, broadcasting assignment.

  • Arithmetic — element-wise +, -, *, /, //, **, unary - on numeric tensors; broadcasting support.

  • Persistence module — compute_persistent_homology (Ripser), Barcode, BarcodeTensor, and barcode summaries: barcode_to_stable_rank, barcode_to_betti_curve, barcode_to_accumulated_persistence.

  • DistanceMatrix and SymmetricMatrix — dedicated types with I/O support, from_dense and to_dense for NumPy interop.

  • Tensor I/O — save/load for all tensor types; from_serial_content for in-memory deserialization.

  • PCF evaluation — evaluate PCFs at given time points.

  • Plotting — built-in plotting for PCFs and barcodes (matplotlib).

  • lp_distance — scalar Lp distance between two individual PCFs.

  • cdist — cross-distance matrices between two collections of PCFs.

  • lp_norm — Lp norms for collections of PCFs.

  • allclose — free function for element-wise approximate equality (FloatTensor, DistanceMatrix, SymmetricMatrix).

  • array_equal — exact element-wise equality check for tensors.

  • iterate_rectangles — iterate over the rectangle decomposition of two PCFs.

  • flatten, copy — tensor methods for flattening and deep-copying.

  • pickle support — all tensor types can be pickled and unpickled.

  • Deterministic random generation — seedable Generator for reproducible output across threads.

  • point_process submodule — sample_poisson for sampling spatial Poisson point processes.

Breaking changes#

  • pdist returns a DistanceMatrix instead of a NumPy array. Call .to_dense() to get the previous behavior.

  • l2_kernel returns a SymmetricMatrix instead of a NumPy array. Call .to_dense() to get the previous behavior.

  • NdArray replaced with Tensor classes (dropped xtensor/xtl dependencies).

  • Pcf construction now only accepts n x 2 arrays (not 2 x n) to avoid ambiguity with 2x2 arrays.

  • I/O format bumped to version 2.

  • Requires C++20 (was C++17). Minimum Python version is 3.10.

Infrastructure#

  • CUDA backend reworked: auto-detection, pip-installed CUDA toolkit support (nvidia.cu12/nvidia.cu13), version-specific modules.

  • Wheels built for Linux (x86_64, aarch64), macOS (x86_64, arm64), and Windows (x86_64).

  • CUDA matrix integration refactored into modular components.

  • GPU occupancy floor added to block scheduler.