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(this page) 2025-02-19 10:23:16 by Adam Ciarcinski | Files touched by this commit (4) |  |
Log message: py-scipy: updated to 1.15.2 Issues closed for 1.15.2 BUG: _lib: crash in uarray on interpreter exit with a free-threaded... BUG: special: Unchecked calls of malloc() and calloc() in specfun.h BUG: Segmentation Fault when passing a special array to ``scipy.cluster.hierarch``... BUG: median_filter on 1D array crashes with memory corruption... BUG: special: Potential memory leak in the function ``besy()``... BUG: ndimage.median_filter: Heap corruption with scipy 1.15 BUG: signal.medfilt and ndimage.median_filter not returning correct... BUG: special: Unchecked malloc in stirling2.h BUG: Matrix multiplication of a coo_matrix with an invalid type... BLD: libhighs.a static library is installed BUG: interpolate test_bary_rational.TestAAA.test_basic_functions... BUG: ``scipy.stats.zmap`` returns incorrect values for complex... BUG: spatial.transform: ``Rotation.from_matrix()`` uses inaccurate... BUG: io.loadmat thinks a file with a lot of zeros is valid BUG: Slicing sparse matrix with ``None`` gives result different... MAINT: scipy.stats: test_regressZEROX SIMD warning for certain... Pull requests for 1.15.2 BUG: immortalize uarray global strings in order to prevent negative... BUG: special: Fix unchecked memory allocations in ``specfun.h`` BUG: cluster: ``cophenet`` intercept invalid linkage matrix count REL, MAINT: prep for 1.15.2 MAINT: stats.Mixture: make return type consistent when ``shape``... MAINT: stats.Mixture: fix inverse functions when mean is undefined BUG: special: Fix unchecked malloc in stirling2.h TST: turn off dtype check due to endianness BUG: sparse: fix selecting wrong dtype for coo coords TST: interpolate: small tolerance bump to TestAAA.test_basic_functions MAINT: Stop installing ``libhighs`` BUG: sparse.linalg.norm: add test for and fix return type BUG: sparse: revert NotImplemented return values in dot and matmul DOC: sparse.linalg: add two recent functions to namespace and... BUG: wrap median_filter stability MAINT: stats.zmap: restore support for complex data MAINT: integrate.cumulative_simpson: bump test tolerance BUG: scipy.spatial: Fix inaccurate orthonormalization in ``Rotation.from_matrix(``... BUG: special: Fix a memory leak in the AMOS function besy(). CI: migrate Linux aarch64 jobs to GitHub Actions, add cp313t... BUG: io.loadmat: throw error on file containing all zeros BUG: sparse: fix spmatrix indexing with None and implicit padding... MAINT: stats: pearsonr SIMD-related shim |
| 2025-01-14 19:18:06 by Greg Troxel | Files touched by this commit (3) |
Log message: math/py-scipy: Add patch for proper use of <complex> in C++ mode Patch originally by Patrick Welche, munged and tested by me. |
| 2025-01-14 19:06:55 by Greg Troxel | Files touched by this commit (1) |
Log message: math/py-scipy: Properly sort USE_LANGUAGES NFCI |
| 2025-01-14 09:10:40 by Adam Ciarcinski | Files touched by this commit (2) | |
Log message: py-scipy: updated to 1.15.1 SciPy 1.15.1 REL, MAINT: prep for 1.15.1 MAINT: fix url for array-api-extra git submodule BLD: fix some issues with undeclared internal build dependencies TST: fix thread safety issue in interpolate.bsplines memmap test TST: stats.Normal: bump tolerance on test of logcdf MAINT: Update highs subproject commit |
| 2025-01-08 13:46:26 by Greg Troxel | Files touched by this commit (1) |
Log message: math/py-scpiy: Fix USE_CC_FEATURES spelling Thanks ryoon@ for pointing this out. |
| 2025-01-07 17:54:12 by Greg Troxel | Files touched by this commit (1) |
Log message: math/py-scpiy: c17 and add comments about compiler requirements Declare that this needs c17, based on meson.build. This has no effect because it was marked for c++17 and both c17 and c++17 currently map to gcc10. Verified to still use gcc10 with the change. Add comments about upstream requirements. No PKGREVISION as this change should never have any effect on the build. |
| 2025-01-07 16:58:01 by Taylor R Campbell | Files touched by this commit (1) |
Log message: math/py-scipy: Fix dependency versions. 1. Upstream is very clear about requiring only gcc>=9.1 in their extensive documentation on toolchain dependencies in doc/source/dev/toolchain.rst. I successfully built this on netbsd-9 with gcc10. Evidently gcc>=14 is not required. 2. Upstream formally declares it needs meson>=1.5.0, causing configure to immediately fail with older meson, so reflect that in our TOOL_DEPENDS. (The comment over TOOL_DEPENDS on meson seems to be obsolete now, so I removed it, but feel free to put it back if I misunderstood.) |
| 2025-01-07 16:38:35 by Jonathan Perkin | Files touched by this commit (2) |
Log message: py-scipy: Avoid WRAP conflict from sys/termios.h on illumos. |
| 2025-01-07 16:35:30 by Jonathan Perkin | Files touched by this commit (1) |
Log message: py-scipy: Lower GCC_REQD requirement to 13. I don't like this change, but the previous setting of 14 is far far worse, and it is unclear why it was made when this project continues to state that GCC 9 is sufficient. GCC 13 certainly builds it absolutely fine. I would recommend that those with even older compilers test them and make any necessary changes to continue to lower the value, or better yet, convert it to USE_*_FEATURES. |
| 2025-01-05 09:58:47 by Adam Ciarcinski | Files touched by this commit (10) | |
Log message: py-scipy: updated to 1.15.0 1.15.0 Highlights of this release Sparse arrays are now fully functional for 1-D and 2-D arrays. We recommend that \ all new code use sparse arrays instead of sparse matrices and that developers \ start to migrate their existing code from sparse matrix to sparse array: \ Migration from spmatrix to sparray. Both sparse.linalg and sparse.csgraph work \ with either sparse matrix or sparse array and work internally with sparse array. Sparse arrays now provide basic support for n-D arrays in the COO format \ including add, subtract, reshape, transpose, matmul, dot, tensordot and others. \ More functionality is coming in future releases. Preliminary support for free-threaded Python 3.13. New probability distribution features in scipy.stats can be used to improve the \ speed and accuracy of existing continuous distributions and perform new \ probability calculations. Several new features support vectorized calculations with Python Array API \ Standard compatible input (see “Array API Standard Support” below): scipy.differentiate is a new top-level submodule for accurate estimation of \ derivatives of black box functions. scipy.optimize.elementwise contains new functions for root-finding and \ minimization of univariate functions. scipy.integrate offers new functions cubature, tanhsinh, and nsum for \ multivariate integration, univariate integration, and univariate series \ summation, respectively. scipy.interpolate.AAA adds the AAA algorithm for barycentric rational \ approximation of real or complex functions. scipy.special adds new functions offering improved Legendre function \ implementations with a more consistent interface. |
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