NumPy 1.16.1 Release Notes¶
The NumPy 1.16.1 release fixes bugs reported against the 1.16.0 release, and also backports several enhancements from master that seem appropriate for a release series that is the last to support Python 2.7. The wheels on PyPI are linked with OpenBLAS v0.3.4+, which should fix the known threading issues found in previous OpenBLAS versions.
Downstream developers building this release should use Cython >= 0.29.2 and, if using OpenBLAS, OpenBLAS > v0.3.4.
If you are installing using pip, you may encounter a problem with older
installed versions of NumPy that pip did not delete becoming mixed with the
current version, resulting in an
ImportError. That problem is particularly
common on Debian derived distributions due to a modified pip. The fix is to
make sure all previous NumPy versions installed by pip have been removed. See
#12736 for discussion of the
issue. Note that previously this problem resulted in an
A total of 16 people contributed to this release. People with a “+” by their names contributed a patch for the first time.
Arcesio Castaneda Medina +
Chris Markiewicz +
Christopher J. Markiewicz +
Daniel Hrisca +
OBATA Akio +
#12767: ENH: add mm->q floordiv
#12768: ENH: port np.core.overrides to C for speed
#12769: ENH: Add np.ctypeslib.as_ctypes_type(dtype), improve np.ctypeslib.as_ctypes
#12773: ENH: add “max difference” messages to np.testing.assert_array_equal…
#12820: ENH: Add mm->qm divmod
#12890: ENH: add _dtype_ctype to namespace for freeze analysis
The changed error message emited by array comparison testing functions may affect doctests. See below for detail.
Casting from double and single denormals to float16 has been corrected. In some rare cases, this may result in results being rounded up instead of down, changing the last bit (ULP) of the result.
divmod operation is now supported for two
The divmod operator now handles two
np.timedelta64 operands, with
Further improvements to
ctypes support in
numpy.ctypeslib.as_ctypes_type function has been added, which can be
used to converts a dtype into a best-guess
ctypes type. Thanks to this
numpy.ctypeslib.as_ctypes now supports a much wider range of
array types, including structures, booleans, and integers of non-native
Array comparison assertions include maximum differences¶
Error messages from array comparison tests such as np.testing.assert_allclose now include “max absolute difference” and “max relative difference,” in addition to the previous “mismatch” percentage. This information makes it easier to update absolute and relative error tolerances.