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ENH: sparse.linalg.splu: add "splu over non square matrices" #20704
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* the version bound changes are very easy to mess up; the converation from the last release is available here: #16353 * at the moment, I've assumed that NumPy `1.24.0` will be released before SciPy `1.10.0`, so that can perhaps aim to support all the way up to `1.26.0` if we are careful? * one other point of caution--we rely even more on `meson` now than we did at the start of the `1.9.0` release cycle for things like wheel builds, so if you think of anything else that might need adjusting in that regard let me know * I think I've traditionally left the adjustment of some version strings to include `rc1` to the release process proper/`REL` commit * clean up some release notes issues: remove some empty sections, fix the formatting of various nested lists; this is made a bit easier by pasting sections into online RST interactive preview pages--let me know if you see other parts that need fixing * the full testsuite passed locally, but I'll flush the full CI for now because it it useful to know that the maintenance branch CI doesn't have any surprises waiting
DOC: 1.10 release notes updates for scipy.stats
* bump the minimum version of `meson-python` based on reviewer feedback * remove the `meson_version` upper bound based on reviewer feedback
* fix a typo in the relnotes [skip azp] [skip actions] [skip cirrus]
MAINT: version bounds for 1.10.0rc1/relnotes fixes
* SciPy `1.10.0rc1` release commit [wheel build]
* CI: native cp38-macosx_arm64
* update SciPy `1.10.0` release notes following backports and fix suggested from Matt H. [wheel build]
MAINT: 1.10.0rc1 backports round 2
* second attempt at building wheels/tagging for SciPy `1.10.0rc1` [wheel build]
DOC: update version switcher for 1.10
…ures due to infinite bounds (#17448) * MAINT: optimize.minimize_scalar: default method is 'bounded' if bounds are provided * MAINT: optimize.minimize_scalar: raise error if bound is not finite * MAINT: optimize.minimize_scalar: raise error when bounds are provided for unbounded method
* MAINT: stats.pearsonr: raise error for complex input In `pearsonr`, raise a `ValueError` for complex input. Unit test included to show the intended error.
This change is required because the source file has been updated in scipy/dataset-ascent#3
Co-authored-by: boeleman <[email protected]>
* Attempts to deal with the ARM-specific portion of gh-17630 -- these issues appear to be the result of NumPy 1.24.0 change: https://numpy.org/devdocs/release/1.24.0-notes.html#numpy-now-gives-floating-point-errors-in-casts * I was able to reproduce and fix the issues in `scipy/sparse/tests/test_base` on an ARM node * however, for `test_decomp_update` I actually saw more severe problems when working on a Cavium ThunderX2 B0 node; for the latter cases, I'll paste what I saw below for some of the representative failures, but for now I just tried to patch the less severe casting errors I see in the CI for those tests to see if it helps (I'm hoping that my own flavor of OpenBLAS is just throwing things off locally and I can at least delay looking into that for now...) ``` FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_neg_strides_economic_rank_p - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_neg_strides_rank_p - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_non_itemsize_strides_rank_p - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_non_native_byte_order_economic_rank_1 - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_non_unit_strides_rank_p - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_D::test_economic_rank_p - AssertionError: FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_d::test_non_native_byte_order_rank_1 - ValueError: array must not contain infs or NaNs FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_D::test_Mx1_economic_rank_p - AssertionError: FAILED scipy/linalg/tests/test_decomp_update.py::TestQRupdate_D::test_economic_rank_1 - AssertionError: ```
* gh-17630 describes a segfault observed in Cirrus CI (alpine) in `test_random_complex_exact` with NumPy `1.24.0`; it was not reproducible locally in an `alpine` docker container with latest SciPy + NumPy `1.24.0` built from tarball via `pip` * this branch aims to avoid the issue with a very-scoped test skip--only when `glibc` was not used to buid the Python interpreter, and only when NumPy is at `1.24.0` or greater [skip circle]
* update the SciPy `1.10.0` release notes following a series of backports targeted at the second release candidate
MAINT: prepare for SciPy 1.10.0rc2
* SciPy `1.10.0rc2` release commit [wheel build]
* MAINT: stats.rankdata: ensure consistent shape handling This change corrects the behaviour when `axis` is None.
Fixes #17644 (see detailed analysis over there..) * I confirmed locally that `cibuildwheel --platform windows` passes with `pybind11` `2.10.2` excluded, whereas we currently experience a segfault that is blocking the release process on Windows * I suspect we may be able to restrict the exclusion to Windows only in `pyproject.toml`, but I think I'm inclined to just keep the syntax simple there if folks are "ok" with this? * this should also stop our Windows meson job from segfaulting for the same reason
* update SciPy 1.10.0 release notes following more backports
MAINT: 1.10.0rc2 backports, round two
* second attempt at SciPy `1.10.0rc2` wheel builds, after additional backports [wheel build]
Hi @Shay2Shay , this PR was initially made to the old 1.10 branch. I tried switching it to We don't add new functionality to previous versions, and even bug fix backports are typically only to the most recent release. |
Ok, I will |
great, thanks. Do let us know by opening a new issue if you are having problems setting up the dev env following https://scipy.github.io/devdocs/dev/contributor/contributor_toc.html, or send a message on our Slack. |
Tested and working for 3x2 and 4x2 matrices, not working for 2x3 and 2x4 matrices
The pull request is for the issue #20164
Did not write tests yet - 1st need to fix some issues, seeking help - discussed here
Reference issue
#20164
What does this implement/fix?
Splu function can take non square matrices
It can perform LU factorization over it
Additional information
need to fix some issues - discussed here