codecov-io
commented
3 years ago Codecov Report
Merging #36 (30ecc73) into main (5f6c0de) will decrease coverage by
0.28%. The diff coverage isn/a.
@@ Coverage Diff @@
## main #36 +/- ##
==========================================
- Coverage 91.85% 91.57% -0.29%
==========================================
Files 23 23
Lines 1044 1044
==========================================
- Hits 959 956 -3
- Misses 85 88 +3 | Impacted Files | Coverage Δ | |
|---|---|---|
| pymapf/centralized/animator.py | 93.47% <0.00%> (-3.27%) |
:arrow_down: |
Continue to review full report at Codecov.
Legend - Click here to learn more
Δ = absolute <relative> (impact),ø = not affected,? = missing dataPowered by Codecov. Last update 5f6c0de...30ecc73. Read the comment docs.
This PR contains the following updates:
==1.20.1->==1.20.2Release Notes
numpy/numpy
### [`v1.20.2`](https://togithub.com/numpy/numpy/releases/v1.20.2) [Compare Source](https://togithub.com/numpy/numpy/compare/v1.20.1...v1.20.2) # NumPy 1.20.2 Release Notes NumPy 1,20.2 is a bugfix release containing several fixes merged to the main branch after the NumPy 1.20.1 release. ## Contributors A total of 7 people contributed to this release. People with a \\"+\\" by their names contributed a patch for the first time. - Allan Haldane - Bas van Beek - Charles Harris - Christoph Gohlke - Mateusz Sokół + - Michael Lamparski - Sebastian Berg ## Pull requests merged A total of 20 pull requests were merged for this release. - [#18382](https://togithub.com/numpy/numpy/pull/18382): MAINT: Update f2py from master. - [#18459](https://togithub.com/numpy/numpy/pull/18459): BUG: `diagflat` could overflow on windows or 32-bit platforms - [#18460](https://togithub.com/numpy/numpy/pull/18460): BUG: Fix refcount leak in f2py `complex_double_from_pyobj`. - [#18461](https://togithub.com/numpy/numpy/pull/18461): BUG: Fix tiny memory leaks when `like=` overrides are used - [#18462](https://togithub.com/numpy/numpy/pull/18462): BUG: Remove temporary change of descr/flags in VOID functions - [#18469](https://togithub.com/numpy/numpy/pull/18469): BUG: Segfault in nditer buffer dealloc for Object arrays - [#18485](https://togithub.com/numpy/numpy/pull/18485): BUG: Remove suspicious type casting - [#18486](https://togithub.com/numpy/numpy/pull/18486): BUG: remove nonsensical comparison of pointer \\< 0 - [#18487](https://togithub.com/numpy/numpy/pull/18487): BUG: verify pointer against NULL before using it - [#18488](https://togithub.com/numpy/numpy/pull/18488): BUG: check if PyArray_malloc succeeded - [#18546](https://togithub.com/numpy/numpy/pull/18546): BUG: incorrect error fallthrough in nditer - [#18559](https://togithub.com/numpy/numpy/pull/18559): CI: Backport CI fixes from main. - [#18599](https://togithub.com/numpy/numpy/pull/18599): MAINT: Add annotations for `__getitem__`, `__mul__` and... - [#18611](https://togithub.com/numpy/numpy/pull/18611): BUG: NameError in numpy.distutils.fcompiler.compaq - [#18612](https://togithub.com/numpy/numpy/pull/18612): BUG: Fixed `where` keyword for `np.mean` & `np.var` methods - [#18617](https://togithub.com/numpy/numpy/pull/18617): CI: Update apt package list before Python install - [#18636](https://togithub.com/numpy/numpy/pull/18636): MAINT: Ensure that re-exported sub-modules are properly annotated - [#18638](https://togithub.com/numpy/numpy/pull/18638): BUG: Fix ma coercion list-of-ma-arrays if they do not cast to... - [#18661](https://togithub.com/numpy/numpy/pull/18661): BUG: Fix small valgrind-found issues - [#18671](https://togithub.com/numpy/numpy/pull/18671): BUG: Fix small issues found with pytest-leaks ## Checksums ##### MD5 a95718df123e0726a7dac5043050b251 numpy-1.20.2-cp37-cp37m-macosx_10_9_x86_64.whl 4cacfe903c60827c0e44d0bed7e3a760 numpy-1.20.2-cp37-cp37m-manylinux1_i686.whl 2879728d4f815f07c7d133347deefe45 numpy-1.20.2-cp37-cp37m-manylinux1_x86_64.whl 97546a3cf4ddcc9fcc7eb41b9558f1de numpy-1.20.2-cp37-cp37m-manylinux2010_i686.whl 65ffbc38abe1c1b92eb3bebf3484f679 numpy-1.20.2-cp37-cp37m-manylinux2010_x86_64.whl 5746efbd42db03518a51adbacbc70fa7 numpy-1.20.2-cp37-cp37m-manylinux2014_aarch64.whl e9b8e30a5c62f003835b374dbc1c9031 numpy-1.20.2-cp37-cp37m-win32.whl b2d0fa9383776ab68a1bbefc84331fc1 numpy-1.20.2-cp37-cp37m-win_amd64.whl 321aa118fbd40fe53a7c82557f3f2772 numpy-1.20.2-cp38-cp38-macosx_10_9_x86_64.whl 518013677b05371bbe7e1d6fa4ef61aa numpy-1.20.2-cp38-cp38-manylinux1_i686.whl 58c61ea025646c391788f7bc7f681fa5 numpy-1.20.2-cp38-cp38-manylinux1_x86_64.whl e8ce1857f017bffeed46b003a0385b11 numpy-1.20.2-cp38-cp38-manylinux2010_i686.whl 8ed52b7194b0953d0b04b88fbabea1ac numpy-1.20.2-cp38-cp38-manylinux2010_x86_64.whl 0a9202dfd47fb02c8eab9f71f084633c numpy-1.20.2-cp38-cp38-manylinux2014_aarch64.whl 8c70e309be1ae43d2938895b56ffbdb7 numpy-1.20.2-cp38-cp38-win32.whl 8aaa91a51b79556643ad93cb1d55b7d3 numpy-1.20.2-cp38-cp38-win_amd64.whl b1b03999df657ccd4e65ff6abcf7e042 numpy-1.20.2-cp39-cp39-macosx_10_9_x86_64.whl 139fef5109539031e570aee9aa3090bf numpy-1.20.2-cp39-cp39-manylinux2010_i686.whl 2c9463187e6a1a0245ed4a2db8e8e656 numpy-1.20.2-cp39-cp39-manylinux2010_x86_64.whl b6cb08e8f56accedc4fdc29720ffb380 numpy-1.20.2-cp39-cp39-manylinux2014_aarch64.whl a3024059b52e7688d3c98b82e2f2688e numpy-1.20.2-cp39-cp39-win32.whl abcd17ffd3b29014ff15e93a74c2c3d6 numpy-1.20.2-cp39-cp39-win_amd64.whl 67704047e60c2b280f7e9f42400cca91 numpy-1.20.2-pp37-pypy37_pp73-manylinux2010_x86_64.whl 6fe93791438f9c1f69c9352680151002 numpy-1.20.2.tar.gz 5e1b381630af4d18db0fedd56b6d8da2 numpy-1.20.2.zip ##### SHA256 e9459f40244bb02b2f14f6af0cd0732791d72232bbb0dc4bab57ef88e75f6935 numpy-1.20.2-cp37-cp37m-macosx_10_9_x86_64.whl a8e6859913ec8eeef3dbe9aed3bf475347642d1cdd6217c30f28dee8903528e6 numpy-1.20.2-cp37-cp37m-manylinux1_i686.whl 9cab23439eb1ebfed1aaec9cd42b7dc50fc96d5cd3147da348d9161f0501ada5 numpy-1.20.2-cp37-cp37m-manylinux1_x86_64.whl 9c0fab855ae790ca74b27e55240fe4f2a36a364a3f1ebcfd1fb5ac4088f1cec3 numpy-1.20.2-cp37-cp37m-manylinux2010_i686.whl 61d5b4cf73622e4d0c6b83408a16631b670fc045afd6540679aa35591a17fe6d numpy-1.20.2-cp37-cp37m-manylinux2010_x86_64.whl d15007f857d6995db15195217afdbddfcd203dfaa0ba6878a2f580eaf810ecd6 numpy-1.20.2-cp37-cp37m-manylinux2014_aarch64.whl d76061ae5cab49b83a8cf3feacefc2053fac672728802ac137dd8c4123397677 numpy-1.20.2-cp37-cp37m-win32.whl bad70051de2c50b1a6259a6df1daaafe8c480ca98132da98976d8591c412e737 numpy-1.20.2-cp37-cp37m-win_amd64.whl 719656636c48be22c23641859ff2419b27b6bdf844b36a2447cb39caceb00935 numpy-1.20.2-cp38-cp38-macosx_10_9_x86_64.whl aa046527c04688af680217fffac61eec2350ef3f3d7320c07fd33f5c6e7b4d5f numpy-1.20.2-cp38-cp38-manylinux1_i686.whl 2428b109306075d89d21135bdd6b785f132a1f5a3260c371cee1fae427e12727 numpy-1.20.2-cp38-cp38-manylinux1_x86_64.whl e8e4fbbb7e7634f263c5b0150a629342cc19b47c5eba8d1cd4363ab3455ab576 numpy-1.20.2-cp38-cp38-manylinux2010_i686.whl edb1f041a9146dcf02cd7df7187db46ab524b9af2515f392f337c7cbbf5b52cd numpy-1.20.2-cp38-cp38-manylinux2010_x86_64.whl c73a7975d77f15f7f68dacfb2bca3d3f479f158313642e8ea9058eea06637931 numpy-1.20.2-cp38-cp38-manylinux2014_aarch64.whl 6c915ee7dba1071554e70a3664a839fbc033e1d6528199d4621eeaaa5487ccd2 numpy-1.20.2-cp38-cp38-win32.whl 471c0571d0895c68da309dacee4e95a0811d0a9f9f532a48dc1bea5f3b7ad2b7 numpy-1.20.2-cp38-cp38-win_amd64.whl 4703b9e937df83f5b6b7447ca5912b5f5f297aba45f91dbbbc63ff9278c7aa98 numpy-1.20.2-cp39-cp39-macosx_10_9_x86_64.whl abc81829c4039e7e4c30f7897938fa5d4916a09c2c7eb9b244b7a35ddc9656f4 numpy-1.20.2-cp39-cp39-manylinux2010_i686.whl 377751954da04d4a6950191b20539066b4e19e3b559d4695399c5e8e3e683bf6 numpy-1.20.2-cp39-cp39-manylinux2010_x86_64.whl 6e51e417d9ae2e7848314994e6fc3832c9d426abce9328cf7571eefceb43e6c9 numpy-1.20.2-cp39-cp39-manylinux2014_aarch64.whl 780ae5284cb770ade51d4b4a7dce4faa554eb1d88a56d0e8b9f35fca9b0270ff numpy-1.20.2-cp39-cp39-win32.whl 924dc3f83de20437de95a73516f36e09918e9c9c18d5eac520062c49191025fb numpy-1.20.2-cp39-cp39-win_amd64.whl 97ce8b8ace7d3b9288d88177e66ee75480fb79b9cf745e91ecfe65d91a856042 numpy-1.20.2-pp37-pypy37_pp73-manylinux2010_x86_64.whl c049f410c78e76ffb0af830a8afbdf8baac09897b4152b97b1a3b8345ee338ff numpy-1.20.2.tar.gz 878922bf5ad7550aa044aa9301d417e2d3ae50f0f577de92051d739ac6096cee numpy-1.20.2.zipConfiguration
:date: Schedule: At any time (no schedule defined).
:vertical_traffic_light: Automerge: Disabled by config. Please merge this manually once you are satisfied.
:recycle: Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
:no_bell: Ignore: Close this PR and you won't be reminded about this update again.
This PR has been generated by WhiteSource Renovate. View repository job log here.