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Changelog

.. currentmodule:: sparse

0.15.1 / 2024-01-10

  • Fix regression where with XArray by supporting all API functions via the Array API standard. (:pr:622 thanks :ghuser:hameerabbasi)

0.15.0 / 2024-01-09

  • Fix regression where :obj:DeprecationWarnings were being fired unexpectedly. (:pr:581 thanks :ghuser:hameerabbasi)
  • Extended :obj:sparse.einsum support (:pr:579 thanks :ghuser:HadrienNU)
  • General code clean-up (:pr:586 thanks :ghuser:MHRasmy, :pr:598 thanks :ghuser:jamestwebber)
  • Bug fixes with respect to NumPy compatibility (:pr:598 thanks :ghuser:hameerabbasi, :pr:609 thanks :ghuser:Illviljan, :pr:620 thanks :ghuser:mtsokol)
  • Bug fixes with respect to GCXS (:pr:611 thanks :ghuser:EuGig, :pr:601 thanks :ghuser:jamestwebber)
  • Array API standard <https://data-apis.org/array-api/latest/>_ support (:pr:612, :pr:613, :pr:614, :pr:615, :pr:619, :pr:620 thanks :ghuser:mtsokol)
  • matrepr support for display of sparse data (:pr:605, :pr:606 thanks :ghuser:alugowski).
  • Larger code clean-up with Ruff formatter and linter (:pr:617, :pr:621 thanks :ghuser:hameerabbasi)
  • Packaging and maintenance (:pr:616, :commit:b5954e68d3d6e35a62f7401d1d4fb84ea04414dd, :commit:dda93d3ea9521881c721c3ba875c769c9c5a79d4 thanks :ghuser:hameerabbasi)

0.14.0 / 2023-02-24

  • :obj:sparse.einsum support (:pr:564 thanks :ghuser:jcmgray)
  • Some bug-fixes (:pr:524, :pr:527, :pr:555 thanks :ghuser:hameerabbasi, :pr:569, thanks :ghuser:jamestwebber, :pr:534, thanks :ghuser:sarveshbhatnagar)
  • Some performance improvements (:pr:570, thanks :ghuser:jamestwebber, :pr:540, thanks :ghuser:smldub).
  • Miscellaneous maintenance fixes.

0.13.0 / 2021-08-28

  • GCXS improvements and changes. (:pr:448, :pr:450, :pr:455, thanks :ghuser:sayandip18).
  • Maintainence fixes (:pr:462, :pr:466, :commit:1ccb85da581be65a0345b399e00fd3c325700d95, :commit:5547b4e92dc8d61492e9dc10ba00175c1a6637fa :commit:00c0e5514de2aab8b9a0be16b5da470b091d9eb9, :commit:fcd3020dd08c7022a44f709173fe23969d3e8f7c, thanks :ghuser:hameerabbasi)
  • :obj:sparse.DOK.from_scipy_sparse method (:pr:464, :issue:463, thanks :ghuser:hameerabbasi).
  • Black re-formatting (:pr:471, :pr:484, thanks :ghuser:GenevieveBuckley, :ghuser:sayandip18)
  • Add :obj:sparse.pad (:pr:474, :issue:438, thanks :ghuser:H4R5H1T-007)
  • Switch to GitHub Actions (:compare:5547b4e92dc8d61492e9dc10ba00175c1a6637fa..a332f22c96a96e5ab9b4384342df67e8f3966f85)
  • Fix a number of bugs in format conversion. (:pr:504, :issue:503, thanks :ghuser:hameerabbasi)
  • Fix bug in :obj:sparse.matmul for higher-dimensional arrays. (:pr:508, :issue:506, thanks :ghuser:sayandip18).
  • Fix scalar conversion to COO (:issue:510, :pr:511, thanks :ghuser:hameerabbasi)
  • Fix OOB memory accesses (:issue:515, :commit:1e24a7e29786e888dee4c02153309986ae4b5dde thanks :ghuser:hameerabbasi)
  • Fixes element-wise ops with scalar COO array. (:issue:505, :commit:5211441ec685233657ab7156f99eb67e660cee86, thanks :ghuser:hameerabbasi)
  • Fix scalar broadcast_to with nnz==0. (:issue:513, :commit:bfabaa0805e811884e79c4bdbfd14316986d65e4, thanks :ghuser:hameerabbasi)
  • Add order parameter to {zero, ones, full}[_like]. (:issue:514, :commit:37de1d0141c4375962ecdf18337c2dd0f667b60c, thanks :ghuser:hameerabbasi)
  • Fix tensordot typing bugs. (:issue:493, :issue:499, :commit:37de1d0141c4375962ecdf18337c2dd0f667b60c, thanks :ghuser:hameerabbasi).

0.12.0 / 2021-03-19

There are a number of large changes in this release. For example, we have implemented the :obj:GCXS type, and its specializations :obj:CSR and :obj:CSC. We plan on gradually improving the performance of these.

  • A number of :obj:GCXS fixes and additions (:pr:409, :pr:407, :pr:414, :pr:417, :pr:419 thanks :ghuser:daletovar)
  • Ability to change the index dtype for better storage characteristics. (:pr:441, thanks :ghuser:daletovar)
  • Some work on :obj:DOK arrays to bring them closer to the other formats (:pr:435, :pr:437, :pr:439, :pr:440, thanks :ghuser:DragaDoncila)
  • :obj:CSR and :obj:CSC specializations of :obj:GCXS (:pr:442, thanks :ghuser:ivirshup) For now, this is experimental undocumented API, and subject to change.
  • Fix a number of bugs (:pr:407, :issue:406)
  • Add nnz parameter to :obj:sparse.random (:pr:410, thanks :ghuser:emilmelnikov)

0.11.2 / 2020-09-04

  • Fix :obj:TypingError on :obj:sparse.dot with complex dtypes. (:issue:403, :pr:404)

0.11.1 / 2020-08-31

  • Fix :obj:ValueError on :obj:sparse.dot with extremely small values. (:issue:398, :pr:399)

0.11.0 / 2020-08-18

  • Improve the performance of :obj:sparse.dot. (:issue:331, :pr:389, thanks :ghuser:daletovar)
  • Added the :obj:COO.swapaxes method. (:pr:344, thanks :ghuser:lueckem)
  • Added multi-axis 1-D indexing support. (:pr:343, thanks :ghuser:mikeymezher)
  • Fix :obj:outer for arrays that weren't one-dimensional. (:issue:346, :pr:347)
  • Add casting kwarg to :obj:COO.astype. (:issue:391, :pr:392)
  • Fix for :obj:COO constructor accepting invalid inputs. (:issue:385, :pr:386)

0.10.0 / 2020-05-13

  • Fixed a bug where converting an empty DOK array to COO leads to an incorrect dtype. (:issue:314, :pr:315)
  • Change code formatter to black. (:pr:284)
  • Add :obj:COO.flatten and :obj:sparse.outer. (:issue:316, :pr:317).
  • Remove broadcasting restriction between sparse arrays and dense arrays. (:issue:306, :pr:318)
  • Implement deterministic dask tokenization. (:issue:300, :pr:320, thanks :ghuser:danielballan)
  • Improve testing around densification (:pr:321, thanks :ghuser:danielballan)
  • Simplify Numba extension. (:pr:324, thanks :ghuser:eric-wieser).
  • Respect copy=False in astype (:pr:328, thanks :ghuser:eric-wieser).
  • Replace linear_loc with ravel_multi_index, which is 3x faster. (:pr:330, thanks :ghuser:eric-wieser).
  • Add error msg to tensordot operation when ndim==0 (:issue:332, :pr:333, thanks :ghuser:guilhermeleobas).
  • Maintainence fixes for Sphinx 3.0 and Numba 0.49, and dropping support for Python 3.5. (:pr:337).
  • Fixed signature for :obj:numpy.clip.

0.9.1 / 2020-01-23

  • Fixed a bug where indexing with an empty list could lead to issues. (:issue:281, :pr:282)
  • Change code formatter to black. (:pr:284)
  • Add the :obj:diagonal and :obj:diagonalize functions. (:issue:288, :pr:289, thanks :ghuser:pettni)
  • Add HTML repr for notebooks. (:pr:283, thanks :ghuser:daletovar)
  • Avoid making copy of coords when making a new :obj:COO array.
  • Add stack and concatenate for GCXS. (:issue:301, :pr:303, thanks :ghuser:daletovar).
  • Fix issue where functions dispatching to an attribute access wouldn't work with __array_function__. (:issue:308, :pr:309).
  • Add partial support for constructing and mirroring :obj:COO objects to Numba.

0.8.0 / 2019-08-26

This release switches to Numba's new typed lists, a lot of back-end work with the CI infrastructure, so Linux, macOS and Windows are officially tested. It also includes bug fixes.

It also adds in-progress, not yet public support for the GCXS format, which is a generalisation of CSR/CSC. (huge thanks to :ghuser:daletovar)

  • Fixed a bug where an array with size == 1 and nnz == 0 could not be broadcast. (:issue:242, :pr:243)
  • Add std and var. (:pr:244)
  • Move to Azure Pipelines with CI for Windows, macOS and Linux. (:pr:245, :pr:246, :pr:247, :pr:248)
  • Add resize, and change reshape so it raises a ValueError on shapes that don't correspond to the same size. (:issue:241, :issue:250, :pr:256 thanks, :ghuser:daletovar)
  • Add isposinf and isneginf. (:issue:252, :pr:253)
  • Fix tensordot when nnz = 0. (:issue:255, :pr:256)
  • Modifications to __array_function__ to allow for sparse XArrays. (:pr:261, thanks :ghuser:nvictus)
  • Add not-yet-public support for GCXS. (:pr:258, thanks :ghuser:daletovar)
  • Improvements to __array_function__. (:pr:267, :pr:272, thanks :ghuser:crusaderky)
  • Convert all Numba lists to typed lists. (:pr:264)
  • Why write code when it exists elsewhere? (:pr:277)
  • Fix some element-wise operations with scalars. (:pr:278)
  • Private modules should be private, and tests should be in the package. (:pr:280)

0.7.0 / 2019-03-14

This is a release that adds compatibility with NumPy's new __array_function__ protocol, for details refer to NEP-18 <http://www.numpy.org/neps/nep-0018-array-function-protocol.html#coercion-to-a-numpy-array-as-a-catch-all-fallback>_.

The other big change is that we dropped compatibility with Python 2. Users on Python 2 should use version 0.6.0.

There are also some bug-fixes relating to fill-values.

This was mainly a contributor-driven release.

The full list of changes can be found below:

  • Fixed a bug where going between :obj:sparse.DOK and :obj:sparse.COO caused fill-values to be lost. (:issue:225, :pr:226).
  • Fixed warning for a matrix that was incorrectly considered too dense. (:issue:228, :pr:229)
  • Fixed some warnings in Python 3.7, the fix was needed. in preparation for Python 3.8. (:pr:233, thanks :ghuser:nils-werner)
  • Drop support for Python 2.7 (:issue:234, :pr:235, thanks :ghuser:hugovk)
  • Clearer error messages (:issue:230, :issue:231, :pr:232)
  • Restructure requirements.txt files. (:pr:236)
  • Support fill-value in reductions in specific cases. (:issue:237, :pr:238)
  • Add __array_function__ support. (:pr:239, thanks, :ghuser:pentschev)
  • Cleaner code! (:pr:240)

0.6.0 / 2018-12-19

This release breaks backward-compatibility. Previously, if arrays were fed into NumPy functions, an attempt would be made to densify the array and apply the NumPy function. This was unintended behaviour in most cases, with the array filling up memory before raising a MemoryError if the array was too large.

We have now changed this behaviour so that a RuntimeError is now raised if an attempt is made to automatically densify an array. To densify, use the explicit .todense() method.

  • Fixed a bug where np.matrix could sometimes fail to convert to a COO. (:issue:199, :pr:200).
  • Make sure that sparse @ sparse returns a sparse array. (:issue:201, :pr:203)
  • Bring operator.matmul behaviour in line with NumPy for ndim > 2. (:issue:202, :pr:204, :pr:217)
  • Make sure dtype is preserved with the out kwarg. (:issue:205, :pr:206)
  • Fix integer overflow in reduce on Windows. (:issue:207, :pr:208)
  • Disallow auto-densification. (:issue:218, :pr:220)
  • Add auto-densification configuration, and a configurable warning for checking if the array is too dense. (:pr:210, :pr:213)
  • Add pruning of fill-values to COO constructor. (:pr:221)

0.5.0 / 2018-10-12

  • Added :code:COO.real, :code:COO.imag, and :code:COO.conj (:pr:196).
  • Added :code:sparse.kron function (:pr:194, :pr:195).
  • Added :code:order parameter to :code:COO.reshape to make it work with :code:np.reshape (:pr:193).
  • Added :code:COO.mean and :code:sparse.nanmean (:pr:190).
  • Added :code:sparse.full and :code:sparse.full_like (:pr:189).
  • Added :code:COO.clip method (:pr:185).
  • Added :code:COO.copy method, and changed pickle of :code:COO to not include its cache (:pr:184).
  • Added :code:sparse.eye, :code:sparse.zeros, :code:sparse.zeros_like, :code:sparse.ones, and :code:sparse.ones_like (:pr:183).

0.4.1 / 2018-09-12

  • Allow mixed :code:ndarray-:code:COO operations if the result is sparse (:issue:124, via :pr:182).
  • Allow specifying a fill-value when converting from NumPy arrays (:issue:179, via :pr:180).
  • Added :code:COO.any and :code:COO.all methods (:pr:175).
  • Indexing for :code:COO now accepts a single one-dimensional array index (:pr:172).
  • The fill-value can now be something other than zero or :code:False (:pr:165).
  • Added a :code:sparse.roll function (:pr:160).
  • Numba code now releases the GIL. This leads to better multi-threaded performance in Dask (:pr:159).
  • A number of bugs occurred, so to resolve them, :code:COO.coords.dtype is always :code:np.int64. :code:COO, therefore, uses more memory than before (:pr:158).
  • Add support for saving and loading :code:COO files from disk (:issue:153, via :pr:154).
  • Support :code:COO.nonzero and :code:np.argwhere (:issue:145, via :pr:148).
  • Allow faux in-place operations (:issue:80, via :pr:146).
  • :code:COO is now always canonical (:pr:141).
  • Improve indexing performance (:pr:128).
  • Improve element-wise performance (:pr:127).
  • Reductions now support a negative axis (:issue:117, via :pr:118).
  • Match behaviour of :code:ufunc.reduce from NumPy (:issue:107, via :pr:108).

0.3.1 / 2018-04-12

  • Fix packaging error (:pr:138).

0.3.0 / 2018-02-22

  • Add NaN-skipping aggregations (:pr:102).
  • Add equivalent to :code:np.where (:pr:102).
  • N-input universal functions now work (:pr:98).
  • Make :code:dot more consistent with NumPy (:pr:96).
  • Create a base class :code:SparseArray (:pr:92).
  • Minimum NumPy version is now 1.13 (:pr:90).
  • Fix a bug where setting a :code:DOK element to zero did nothing (:issue:93, via :pr:94).

0.2.0 / 2018-01-25

  • Support faster :code:np.array(COO) (:pr:87).
  • Add :code:DOK type (:pr:85).
  • Fix sum for large arrays (:issue:82, via :pr:83).
  • Support :code:.size and :code:.density (:pr:69).
  • Documentation added for the package (:pr:43).
  • Minimum required SciPy version is now 0.19 (:pr:70).
  • :code:len(COO) now works (:pr:68).
  • :code:scalar op COO now works for all operators (:pr:67).
  • Validate axes for :code:.transpose() (:pr:61).
  • Extend indexing support (:pr:57).
  • Add :code:random function for generating random sparse arrays (:pr:41).
  • :code:COO(COO) now copies the original object (:pr:55).
  • NumPy universal functions and reductions now work on :code:COO arrays (:pr:49).
  • Fix concatenate and stack for large arrays (:issue:32, via :pr:51).
  • Fix :code:nnz for scalars (:issue:47, via :pr:48).
  • Support more operators and remove all special cases (:pr:46).
  • Add support for :code:triu and :code:tril (:pr:40).
  • Add support for Ellipsis (:code:...) and :code:None when indexing (:pr:37).
  • Add support for bitwise bindary operations like :code:& and :code:| (:pr:38).
  • Support broadcasting in element-wise operations (:pr:35).