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 @daletovar)
var. (PR #244)
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
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:
Restructure requirements.txt files. (PR #236)
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
Add pruning of fill-values to COO constructor. (PR #221)
0.5.0 / 2018-10-12¶
COO.reshapeto make it work with
COO.clipmethod (PR #185).
COO.copymethod, and changed pickle of
COOto not include its cache (PR #184).
0.4.1 / 2018-09-12¶
COO.allmethods (PR #175).
COOnow accepts a single one-dimensional array index (PR #172).
The fill-value can now be something other than zero or
sparse.rollfunction (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,
COO, therefore, uses more memory than before (PR #158).
COOis now always canonical (PR #141).
Improve indexing performance (PR #128).
Improve element-wise performance (PR #127).
0.3.0 / 2018-02-22¶
Add NaN-skipping aggregations (PR #102).
Add equivalent to
N-input universal functions now work (PR #98).
dotmore consistent with NumPy (PR #96).
Create a base class
Minimum NumPy version is now 1.13 (PR #90).
0.2.0 / 2018-01-25¶
DOKtype (PR #85).
Documentation added for the package (PR #43).
Minimum required SciPy version is now 0.19 (PR #70).
len(COO)now works (PR #68).
scalar op COOnow works for all operators (PR #67).
Validate axes for
Extend indexing support (PR #57).
randomfunction for generating random sparse arrays (PR #41).
COO(COO)now copies the original object (PR #55).
NumPy universal functions and reductions now work on
COOarrays (PR #49).
Support more operators and remove all special cases (PR #46).
Add support for
Add support for Ellipsis (
Nonewhen indexing (PR #37).
Add support for bitwise bindary operations like
Support broadcasting in element-wise operations (PR #35).