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Releases: scikit-tda/ripser.py

Fixing C++ imports

16 Aug 12:41

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0.6.4

Updating workflow to include python 3.9

Lazy imports of visualization requirements

11 Aug 18:58
9d9b7c4

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This release moves the requirements for visualizations to be loaded lazily so users are not required to having functioning matplotlib dependencies for working with the library.

New faster hashmap backend

15 Mar 15:39
f784e1f

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  • Update C++ backend to commit 286d369 of ripser but keeping same functionalities
  • Add support to robinhood hashmap into the C++ Backend
  • Update CI in order to compile C++ with robinhood enable
  • Enable Enclosing radius when threshold is set to infinity

MSVC Compatibility

16 Jul 14:30

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  • Fixed packing so C++ is MSVC compatible.
  • Updated contact info.

Packaging systems

13 Jul 18:01
5cdc1e1

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This version builds out the necessary infrastructure to package Ripser.py in Conda-Forge.

Greedy Permutation + Refactoring

19 Feb 01:35
b749d0b

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  • Added support for greedy permutations
  • Outsourced plotting to persim.
  • Outsourced data construction in examples to tadasets.
  • Revamped documentation.

Bug fix for Issue #51

13 Nov 20:28
d5cb405

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Bug fix for Issue #51 Pre-release
Pre-release

This release contains a potential bug fix for issue number #51.

0.3.0 JOSS submission

11 Sep 01:45

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Minor modifications to documentation, paper, and examples to improve clarity and consistency. Thanks to @lmcinnes and @arokem.

Polished Interfaces and Documentation

17 Aug 02:19

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- Updating home url
- Update license to MIT.
- Docs and notebooks revamp.
- Support for Windows.
- Interface redesign
- Support for lower star filtrations
- Notebook on lower star filtrations

Sparse matrices

17 May 00:59
47438d3

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This release includes major updates to the structure of C++ bindings allowing more languages to easily interface and provides support for sparse distance matrices.

  • Sparse distance matrix support
  • Two additional notebooks about sparsity
  • Language agnostic bindings support
  • Bug fixes (filtrations with low number of points, int rounding error for small magnitude threshold)