v1.3.0

What's Changed

• Used GIT_DESCRIBE_TAG and GIT_DESCRIBE_NUMBER in meta.yaml instead of manual stepping the numbers gh-75
• Extended conda build scripts with the use of WHEELS_OUTPUT_FOLDER variable to build wheel packages gh-74
• Updated meta.yaml to have a run dependency on numpy-base package gh-73

Contributors

• @antonwolfy
• @ekomarova
• @vtavana

Full Changelog: v1.2.11...1.3.0

v1.2.10

This release

• Adds support for mkl_random out-of-the-box from virtual environment on Windows

v1.2.8

Incremental bug fix release: updated installation instructions, reverted work-around for a problem in MKL 2024.2.0

v1.2.7

This release addresses technical debt, and fixes the project to work with NumPy 2.0 on both Windows and Linux.

• Removed use of vendored numpy.pxd, replaced with recommended cimport numpy. This resolved the warning of changes struct size for Cython class broadcast.
• Fixed warnings from clang compiler
• Corrected data types for allocation made in Cython which were responsible for test failures with NumPy 2.0 on Windows.

v1.2.6

This is a bug fix release updates mkl_random to support NumPy 2.0

v1.2.5

Transition testing suite to pytest to enable support for Python 3.12

v1.2.4

Change to fix build on mkl_random with clang with new build system introduced in v1.2.3.

v1.2.3

• Modified example of parallel Monte-Carlo work to correctly work on Windows. (gh-26)
• Transitioned away from using numpy.distutils as it went away in NumPy 1.25 (gh-24)

v1.2.2.post2

Update description for Pypi package installation

v1.2.2

Added examples/ folder provided an example of parallel Monte-Carlo estimation of a probability of a certain event.

Added support for ARS5 counter-based basic random number generator available in MKL, see
https://software.intel.com/content/www/us/en/develop/documentation/onemkl-vsnotes/top/testing-of-basic-random-number-generators/basic-random-generator-properties-and-testing-results/ars5.html