diff options
167 files changed, 4177 insertions, 2206 deletions
diff --git a/.travis.yml b/.travis.yml index 5c006cbc0..4afac959d 100644 --- a/.travis.yml +++ b/.travis.yml @@ -40,13 +40,12 @@ env: matrix: include: # Do all python versions without environment variables set - - python: 3.5 - stage: Initial tests - python: 3.6 - - python: 3.7 - - python: 3.8-dev + python: 3.8 + + - python: 3.6 - python: 3.7 - env: INSTALL_PICKLE5=1 + - python: 3.6 dist: bionic env: USE_DEBUG=1 @@ -58,11 +57,14 @@ matrix: - python3-dbg - python3-dev - python3-setuptools + - python: 3.7 env: USE_WHEEL=1 RUN_FULL_TESTS=1 RUN_COVERAGE=1 INSTALL_PICKLE5=1 - - python: 3.6 + + - python: 3.7 env: USE_SDIST=1 - - python: 3.6 + + - python: 3.7 env: - PYTHONOPTIMIZE=2 - BLAS=None @@ -71,24 +73,30 @@ matrix: - NPY_BLAS_ORDER=mkl,blis,openblas,atlas,accelerate,blas - NPY_LAPACK_ORDER=MKL,OPENBLAS,ATLAS,ACCELERATE,LAPACK - USE_ASV=1 - - python: 3.5 + + - python: 3.7 env: NPY_RELAXED_STRIDES_CHECKING=0 - - python: 3.6 + + - python: 3.7 env: USE_WHEEL=1 NPY_RELAXED_STRIDES_DEBUG=1 - - python: 3.6 + + - python: 3.7 env: NUMPY_EXPERIMENTAL_ARRAY_FUNCTION=0 - - python: 3.6 + + - python: 3.7 env: - BLAS=None - LAPACK=None - ATLAS=None - - python: 3.6 + + - python: 3.7 os: linux arch: ppc64le env: # use ppc64le OpenBLAS build, not system ATLAS - ATLAS=None - - python: 3.6 + + - python: 3.7 os: linux arch: s390x env: diff --git a/azure-pipelines.yml b/azure-pipelines.yml index 9e1e52952..29fc6c614 100644 --- a/azure-pipelines.yml +++ b/azure-pipelines.yml @@ -156,11 +156,6 @@ stages: PYTHON_ARCH: 'x86' TEST_MODE: fast BITS: 32 - Python35-64bit-full: - PYTHON_VERSION: '3.5' - PYTHON_ARCH: 'x64' - TEST_MODE: full - BITS: 64 Python36-64bit-full: PYTHON_VERSION: '3.6' PYTHON_ARCH: 'x64' diff --git a/benchmarks/asv.conf.json b/benchmarks/asv.conf.json index 45da9533f..b3c7f9f20 100644 --- a/benchmarks/asv.conf.json +++ b/benchmarks/asv.conf.json @@ -35,7 +35,7 @@ // The Pythons you'd like to test against. If not provided, defaults // to the current version of Python used to run `asv`. - "pythons": ["3.6"], + "pythons": ["3.7"], // The matrix of dependencies to test. Each key is the name of a // package (in PyPI) and the values are version numbers. An empty @@ -43,6 +43,7 @@ // version. "matrix": { "six": [], + "Cython": [], }, // The directory (relative to the current directory) that benchmarks are @@ -68,7 +69,7 @@ // `asv` will cache wheels of the recent builds in each // environment, making them faster to install next time. This is // number of builds to keep, per environment. - "wheel_cache_size": 2, + "build_cache_size": 8, // The commits after which the regression search in `asv publish` // should start looking for regressions. Dictionary whose keys are diff --git a/doc/HOWTO_RELEASE.rst.txt b/doc/HOWTO_RELEASE.rst.txt index 4b485c8b9..f0231293f 100644 --- a/doc/HOWTO_RELEASE.rst.txt +++ b/doc/HOWTO_RELEASE.rst.txt @@ -3,143 +3,147 @@ NumPy. Current build and release info ============================== - The current info on building and releasing NumPy and SciPy is scattered in several places. It should be summarized in one place, updated, and where necessary described in more detail. The sections below list all places where useful info can be found. + Source tree ----------- -* INSTALL.rst.txt -* release.sh -* pavement.py +- INSTALL.rst.txt +- release.sh +- pavement.py + NumPy Docs ---------- -* https://github.com/numpy/numpy/blob/master/doc/HOWTO_RELEASE.rst.txt -* http://projects.scipy.org/numpy/wiki/MicrosoftToolchainSupport (dead link) +- https://github.com/numpy/numpy/blob/master/doc/HOWTO_RELEASE.rst.txt +- http://projects.scipy.org/numpy/wiki/MicrosoftToolchainSupport (dead link) + SciPy.org wiki -------------- -* https://www.scipy.org/Installing_SciPy and links on that page. -* http://new.scipy.org/building/windows.html (dead link) +- https://www.scipy.org/Installing_SciPy and links on that page. +- http://new.scipy.org/building/windows.html (dead link) + Doc wiki -------- -* http://docs.scipy.org/numpy/docs/numpy-docs/user/install.rst/ (dead link) +- http://docs.scipy.org/numpy/docs/numpy-docs/user/install.rst/ (dead link) + Release Scripts --------------- -* https://github.com/numpy/numpy-vendor +- https://github.com/numpy/numpy-vendor + Supported platforms and versions ================================ - Python 2.7 and >=3.4 are the currently supported versions when building from source. We test NumPy against all these versions every time we merge code to master. Binary installers may be available for a subset of these versions (see below). + OS X ---- - Python 2.7 and >=3.4 are the versions for which we provide binary installers. OS X versions >= 10.6 are supported. We build binary wheels for OSX that are compatible with Python.org Python, system Python, homebrew and macports - see this `OSX wheel building summary <https://github.com/MacPython/wiki/wiki/Spinning-wheels>`_ for details. + Windows ------- - We build 32- and 64-bit wheels for Python 2.7, 3.4, 3.5 on Windows. Windows XP, Vista, 7, 8 and 10 are supported. We build NumPy using the MSVC compilers on Appveyor, but we are hoping to update to a `mingw-w64 toolchain <https://mingwpy.github.io>`_. The Windows wheels use ATLAS for BLAS / LAPACK. + Linux ----- - We build and ship `manylinux1 <https://www.python.org/dev/peps/pep-0513>`_ wheels for NumPy. Many Linux distributions include their own binary builds of NumPy. + BSD / Solaris ------------- - No binaries are provided, but successful builds on Solaris and BSD have been reported. + Tool chain ========== - We build all our wheels on cloud infrastructure - so this list of compilers is for information and debugging builds locally. See the ``.travis.yml`` and ``appveyor.yml`` scripts in the `numpy wheels`_ repo for the definitive source of the build recipes. Packages that are available using pip are noted. + Compilers --------- - The same gcc version is used as the one with which Python itself is built on each platform. At the moment this means: -* OS X builds on travis currently use `clang`. It appears that binary wheels +- OS X builds on travis currently use `clang`. It appears that binary wheels for OSX >= 10.6 can be safely built from the travis-ci OSX 10.9 VMs when building against the Python from the Python.org installers; -* Windows builds use the MSVC version corresponding to the Python being built +- Windows builds use the MSVC version corresponding to the Python being built against; -* Manylinux1 wheels use the gcc provided on the Manylinux docker images. +- Manylinux1 wheels use the gcc provided on the Manylinux docker images. You will need Cython for building the binaries. Cython compiles the ``.pyx`` files in the NumPy distribution to ``.c`` files. + Building source archives and wheels ----------------------------------- - You will need write permission for numpy-wheels in order to trigger wheel builds. -* Python(s) from `python.org <https://python.org>`_ or linux distro. -* cython -* virtualenv (pip) -* Paver (pip) -* numpy-wheels `<https://github.com/MacPython/numpy-wheels>`_ (clone) +- Python(s) from `python.org <https://python.org>`_ or linux distro. +- cython +- virtualenv (pip) +- Paver (pip) +- numpy-wheels `<https://github.com/MacPython/numpy-wheels>`_ (clone) + Building docs ------------- - Building the documents requires a number of latex ``.sty`` files. Install them all to avoid aggravation. -* Sphinx (pip) -* numpydoc (pip) -* Matplotlib -* Texlive (or MikTeX on Windows) +- Sphinx (pip) +- numpydoc (pip) +- Matplotlib +- Texlive (or MikTeX on Windows) + Uploading to PyPI ----------------- +- terryfy `<https://github.com/MacPython/terryfy>`_ (clone). +- beautifulsoup4 (pip) +- delocate (pip) +- auditwheel (pip) +- twine (pip) -* terryfy `<https://github.com/MacPython/terryfy>`_ (clone). -* beautifulsoup4 (pip) -* delocate (pip) -* auditwheel (pip) -* twine (pip) Generating author/pr lists -------------------------- - You will need a personal access token `<https://help.github.com/articles/creating-a-personal-access-token-for-the-command-line/>`_ so that scripts can access the github NumPy repository. -* gitpython (pip) -* pygithub (pip) +- gitpython (pip) +- pygithub (pip) + Virtualenv ---------- - Virtualenv is a very useful tool to keep several versions of packages around. It is also used in the Paver script to build the docs. @@ -149,27 +153,28 @@ What is released Wheels ------ +We currently support Python 3.6-3.8 on Windows, OSX, and Linux -* Windows wheels for Python 2.7, 3.4, 3.5, for 32- and 64-bit, built using - Appveyor; -* Dual architecture OSX wheels built via travis-ci; -* 32- and 64-bit Manylinux1 wheels built via travis-ci. +* Windows: 32-bit and 64-bit wheels built using Appveyor; +* OSX: x64_86 OSX wheels built using travis-ci; +* Linux: 32-bit and 64-bit Manylinux1 wheels built using travis-ci. See the `numpy wheels`_ building repository for more detail. .. _numpy wheels : https://github.com/MacPython/numpy-wheels + Other ----- +- Release Notes +- Changelog -* Release Notes -* Changelog Source distribution ------------------- - We build source releases in both .zip and .tar.gz formats. + Release process =============== @@ -182,6 +187,7 @@ After a date is set, create a new maintenance/x.y.z branch, add new empty release notes for the next version in the master branch and update the Trac Milestones. + Make sure current branch builds a package correctly --------------------------------------------------- :: @@ -197,6 +203,7 @@ best to read the pavement.py script. .. note:: The following steps are repeated for the beta(s), release candidates(s) and the final release. + Check deprecations ------------------ Before the release branch is made, it should be checked that all deprecated @@ -244,15 +251,16 @@ There are three steps to the process. The C ABI version number in numpy/core/setup_common.py should only be updated for a major release. + Check the release notes ----------------------- -Use `towncrier`_ to build the release note, copy it to the proper name, and -commit the changes. This will remove all the fragments from ``changelog/*.rst`` -and add ``doc/release/latest-note.rst`` which must be renamed with the proper -version number:: +Use `towncrier`_ to build the release note and +commit the changes. This will remove all the fragments from +``doc/release/upcoming_changes`` and add ``doc/release/<version>-note.rst``. +Note that currently towncrier must be installed from its master branch as the +last release (19.2.0) is outdated. - python -mtowncrier --version "Numpy 1.11.0" - git mv doc/release/latest-note.rst doc/release/1.11.0-notes.rst + towncrier --version "<version>" git commit -m"Create release note" Check that the release notes are up-to-date. @@ -268,6 +276,7 @@ following: .. _towncrier: https://github.com/hawkowl/towncrier + Update the release status and create a release "tag" ---------------------------------------------------- Identify the commit hash of the release, e.g. 1b2e1d63ff. @@ -302,7 +311,7 @@ changes:: And make sure the ``VERSION`` variable is set properly. Now you can make the release commit and tag. We recommend you don't push -the commit or tag immediately, just in case you need to do more cleanup. We +the commit or tag immediately, just in case you need to do more cleanup. We prefer to defer the push of the tag until we're confident this is the exact form of the released code (see: :ref:`push-tag-and-commit`): @@ -325,12 +334,6 @@ to public keyservers, with a command such as:: gpg --send-keys <yourkeyid> -Apply patch to fix bogus strides --------------------------------- -NPY_RELAXED_STRIDE_CHECKING was made the default in NumPy 1.10.0 and bogus -strides are used in the development branch to smoke out problems. The -`patch <https://github.com/numpy/numpy/pull/5996>`_ should be updated if -necessary and applied to the release branch to rationalize the strides. Update the version of the master branch --------------------------------------- @@ -340,15 +343,15 @@ Increment the release number in setup.py. Release candidates should have "rc1" Also create a new version hash in cversions.txt and a corresponding version define NPY_x_y_API_VERSION in numpyconfig.h + Trigger the wheel builds on travis-ci and Appveyor -------------------------------------------------- - See the `numpy wheels` repository. In that repository edit the files: -* ``.travis.yml``; -* ``appveyor.yml``. +- ``.travis.yml``; +- ``appveyor.yml``. In both cases, set the ``BUILD_COMMIT`` variable to the current release tag - e.g. ``v1.11.1``. @@ -365,19 +368,20 @@ Trigger a build by doing a commit of your edits to ``.travis.yml`` and The wheels, once built, appear at a Rackspace container pointed at by: -* http://wheels.scipy.org -* https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com +- http://wheels.scipy.org +- https://3f23b170c54c2533c070-1c8a9b3114517dc5fe17b7c3f8c63a43.ssl.cf2.rackcdn.com The HTTP address may update first, and you should wait 15 minutes after the build finishes before fetching the binaries. + Make the release ---------------- - Build the changelog and notes for upload with:: paver write_release_and_log + Build and archive documentation ------------------------------- Do:: @@ -397,9 +401,9 @@ create an archive of the documentation in the numpy/doc repo:: # Push to numpy/doc repo git -C push + Update PyPI ----------- - The wheels and source should be uploaded to PyPI. You should upload the wheels first, and the source formats last, to make sure @@ -436,9 +440,9 @@ interface. .. _push-tag-and-commit: + Push the release tag and commit ------------------------------- - Finally, now you are confident this tag correctly defines the source code that you released you can push the tag and release commit up to github:: @@ -448,18 +452,18 @@ you released you can push the tag and release commit up to github:: where ``upstream`` points to the main https://github.com/numpy/numpy.git repository. + Update scipy.org ---------------- - A release announcement with a link to the download site should be placed in the sidebar of the front page of scipy.org. The scipy.org should be a PR at https://github.com/scipy/scipy.org. The file that needs modification is ``www/index.rst``. Search for ``News``. + Announce to the lists --------------------- - The release should be announced on the mailing lists of NumPy and SciPy, to python-announce, and possibly also those of Matplotlib, IPython and/or Pygame. @@ -468,12 +472,13 @@ During the beta/RC phase, an explicit request for testing the binaries with several other libraries (SciPy/Matplotlib/Pygame) should be posted on the mailing list. + Announce to Linux Weekly News ----------------------------- - Email the editor of LWN to let them know of the release. Directions at: https://lwn.net/op/FAQ.lwn#contact + After the final release ----------------------- After the final release is announced, a few administrative tasks are left to be diff --git a/doc/Makefile b/doc/Makefile index 3c32cb811..74272fa50 100644 --- a/doc/Makefile +++ b/doc/Makefile @@ -217,7 +217,7 @@ latex-build: generate mkdir -p build/latex build/doctrees $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) build/latex $(FILES) $(PYTHON) postprocess.py tex build/latex/*.tex - perl -pi -e 's/\t(latex.*|pdflatex) (.*)/\t-$$1 -interaction batchmode $$2/' build/latex/Makefile + perl -pi -e 's/LATEXOPTS =/LATEXOPTS ?= --halt-on-error/' build/latex/Makefile @echo @echo "Build finished; the LaTeX files are in build/latex." @echo "Run \`make all-pdf' or \`make all-ps' in that directory to" \ diff --git a/doc/example.py b/doc/example.py index 560775038..8a5f9948f 100644 --- a/doc/example.py +++ b/doc/example.py @@ -112,9 +112,9 @@ def foo(var1, var2, long_var_name='hi'): use the function. >>> a = [1, 2, 3] - >>> print [x + 3 for x in a] + >>> print([x + 3 for x in a]) [4, 5, 6] - >>> print "a\n\nb" + >>> print("a\n\nb") a b diff --git a/doc/neps/nep-0030-duck-array-protocol.rst b/doc/neps/nep-0030-duck-array-protocol.rst index 353c5df1e..f98449ed6 100644 --- a/doc/neps/nep-0030-duck-array-protocol.rst +++ b/doc/neps/nep-0030-duck-array-protocol.rst @@ -114,7 +114,7 @@ An example of how the ``__duckarray__`` protocol could be used to write a seen below. The example here was chosen not only to demonstrate the usage of the ``duckarray`` function, but also to demonstrate its dependency on the NumPy API, demonstrated by checks on the array's ``shape`` attribute. Note that the -example is merely a simplified version of NumPy's actualy implementation of +example is merely a simplified version of NumPy's actually implementation of ``stack`` working on the first axis, and it is assumed that Dask has implemented the ``__duckarray__`` method. diff --git a/doc/neps/nep-0031-uarray.rst b/doc/neps/nep-0031-uarray.rst index 3519b6bc0..737d2b456 100644 --- a/doc/neps/nep-0031-uarray.rst +++ b/doc/neps/nep-0031-uarray.rst @@ -17,12 +17,12 @@ This NEP proposes to make all of NumPy's public API overridable via an extensible backend mechanism. Acceptance of this NEP means NumPy would provide global and context-local -overrides, as well as a dispatch mechanism similar to NEP-18 [2]_. First -experiences with ``__array_function__`` show that it is necessary to be able -to override NumPy functions that *do not take an array-like argument*, and -hence aren't overridable via ``__array_function__``. The most pressing need is -array creation and coercion functions, such as ``numpy.zeros`` or -``numpy.asarray``; see e.g. NEP-30 [9]_. +overrides in a separate namespace, as well as a dispatch mechanism similar +to NEP-18 [2]_. First experiences with ``__array_function__`` show that it +is necessary to be able to override NumPy functions that *do not take an +array-like argument*, and hence aren't overridable via +``__array_function__``. The most pressing need is array creation and coercion +functions, such as ``numpy.zeros`` or ``numpy.asarray``; see e.g. NEP-30 [9]_. This NEP proposes to allow, in an opt-in fashion, overriding any part of the NumPy API. It is intended as a comprehensive resolution to NEP-22 [3]_, and @@ -32,19 +32,6 @@ type of function or object that needs to become overridable. Motivation and Scope -------------------- -The motivation behind ``uarray`` is manyfold: First, there have been several -attempts to allow dispatch of parts of the NumPy API, including (most -prominently), the ``__array_ufunc__`` protocol in NEP-13 [4]_, and the -``__array_function__`` protocol in NEP-18 [2]_, but this has shown the need -for further protocols to be developed, including a protocol for coercion (see -[5]_, [9]_). The reasons these overrides are needed have been extensively -discussed in the references, and this NEP will not attempt to go into the -details of why these are needed; but in short: It is necessary for library -authors to be able to coerce arbitrary objects into arrays of their own types, -such as CuPy needing to coerce to a CuPy array, for example, instead of -a NumPy array. In simpler words, one needs things like ``np.asarray(...)`` or -an alternative to "just work" and return duck-arrays. - The primary end-goal of this NEP is to make the following possible: .. code:: python @@ -94,14 +81,60 @@ vendored into a new namespace within NumPy to give users and downstream dependencies access to these overrides. This vendoring mechanism is similar to what SciPy decided to do for making ``scipy.fft`` overridable (see [10]_). +The motivation behind ``uarray`` is manyfold: First, there have been several +attempts to allow dispatch of parts of the NumPy API, including (most +prominently), the ``__array_ufunc__`` protocol in NEP-13 [4]_, and the +``__array_function__`` protocol in NEP-18 [2]_, but this has shown the need +for further protocols to be developed, including a protocol for coercion (see +[5]_, [9]_). The reasons these overrides are needed have been extensively +discussed in the references, and this NEP will not attempt to go into the +details of why these are needed; but in short: It is necessary for library +authors to be able to coerce arbitrary objects into arrays of their own types, +such as CuPy needing to coerce to a CuPy array, for example, instead of +a NumPy array. In simpler words, one needs things like ``np.asarray(...)`` or +an alternative to "just work" and return duck-arrays. -Detailed description --------------------- +Usage and Impact +---------------- + +This NEP allows for global and context-local overrides, as well as +automatic overrides a-la ``__array_function__``. + +Here are some use-cases this NEP would enable, besides the +first one stated in the motivation section: -Using overrides -~~~~~~~~~~~~~~~ +The first is allowing alternate dtypes to return their +respective arrays. -Here are a few examples of how an end-user would use overrides. +.. code:: python + + # Returns an XND array + x = unp.ones((5, 5), dtype=xnd_dtype) # Or torch dtype + +The second is allowing overrides for parts of the API. +This is to allow alternate and/or optimised implementations +for ``np.linalg``, BLAS, and ``np.random``. + +.. code:: python + + import numpy as np + import pyfftw # Or mkl_fft + + # Makes pyfftw the default for FFT + np.set_global_backend(pyfftw) + + # Uses pyfftw without monkeypatching + np.fft.fft(numpy_array) + + with np.set_backend(pyfftw) # Or mkl_fft, or numpy + # Uses the backend you specified + np.fft.fft(numpy_array) + +This will allow an official way for overrides to work with NumPy without +monkeypatching or distributing a modified version of NumPy. + +Here are a few other use-cases, implied but not already +stated: .. code:: python @@ -110,11 +143,8 @@ Here are a few examples of how an end-user would use overrides. result = library_function(data) result.to_zarr('output.zarr') -This would keep on working, assuming the Dask backend was either set or -registered. Registration can also be done at import-time. - -Now consider another function, and what would need to happen in order to -make this work: +This second one would work if ``magic_library`` was built +on top of ``unumpy``. .. code:: python @@ -126,19 +156,6 @@ make this work: result = pytorch_predict(data) result.to_zarr('output.zarr') -This would work in two scenarios: The first is that ``pytorch_predict`` was a -multimethod, and implemented by the Dask backend. Dask could provide utility -functions to allow external libraries to register implementations. - -The second, and perhaps more useful way, is that ``pytorch_predict`` was defined -in an idiomatic style true to NumPy in terms of other multimethods, and that Dask -implemented the required multimethods itself, e.g. ``np.convolve``. If this -happened, then the above example would work without either ``magic_library`` -or Dask having to do anything specific to the other. - -Composing backends -~~~~~~~~~~~~~~~~~~ - There are some backends which may depend on other backends, for example xarray depending on `numpy.fft`, and transforming a time axis into a frequency axis, or Dask/xarray holding an array other than a NumPy array inside it. This would @@ -147,6 +164,14 @@ be handled in the following manner inside code:: with ua.set_backend(cupy), ua.set_backend(dask.array): # Code that has distributed GPU arrays here +Backward compatibility +---------------------- + +There are no backward incompatible changes proposed in this NEP. + +Detailed description +-------------------- + Proposals ~~~~~~~~~ @@ -463,7 +488,7 @@ of three simple values: ``type``, ``value``, and ``coercible``. ``NotImplemented`` in the case of failure. ``__ua_function__`` has the signature ``(func, args, kwargs)`` and defines -the actual implementation of the function. It recieves the function and its +the actual implementation of the function. It receives the function and its arguments. Returning ``NotImplemented`` will cause a move to the default implementation of the function if one exists, and failing that, the next backend. @@ -562,11 +587,6 @@ manner (as an example):: def full(shape, fill_value, dtype=None, order='C'): # Code here -Backward compatibility ----------------------- - -There are no backward incompatible changes proposed in this NEP. - Alternatives ------------ diff --git a/doc/neps/nep-0034.rst b/doc/neps/nep-0034.rst index d9a9c62f2..4863bad86 100644 --- a/doc/neps/nep-0034.rst +++ b/doc/neps/nep-0034.rst @@ -3,10 +3,10 @@ NEP 34 — Disallow inferring ``dtype=object`` from sequences =========================================================== :Author: Matti Picus -:Status: Draft +:Status: Accepted :Type: Standards Track :Created: 2019-10-10 - +:Resolution: https://mail.python.org/pipermail/numpy-discussion/2019-October/080200.html Abstract -------- diff --git a/doc/release/upcoming_changes/10151.improvement.rst b/doc/release/upcoming_changes/10151.improvement.rst deleted file mode 100644 index 3706a5132..000000000 --- a/doc/release/upcoming_changes/10151.improvement.rst +++ /dev/null @@ -1,9 +0,0 @@ -Different C numeric types of the same size have unique names ------------------------------------------------------------- -On any given platform, two of ``np.intc``, ``np.int_``, and ``np.longlong`` -would previously appear indistinguishable through their ``repr``, despite -their corresponding ``dtype`` having different properties. -A similar problem existed for the unsigned counterparts to these types, and on -some platforms for ``np.double`` and ``np.longdouble`` - -These types now always print with a unique ``__name__``. diff --git a/doc/release/upcoming_changes/12284.new_feature.rst b/doc/release/upcoming_changes/12284.new_feature.rst deleted file mode 100644 index 25321cd9b..000000000 --- a/doc/release/upcoming_changes/12284.new_feature.rst +++ /dev/null @@ -1,5 +0,0 @@ - -Add our own ``*.pxd`` cython import file --------------------------------------------- -Added a ``numpy/__init__.pxd`` file. It will be used for `cimport numpy` - diff --git a/doc/release/upcoming_changes/13605.deprecation.rst b/doc/release/upcoming_changes/13605.deprecation.rst deleted file mode 100644 index bff12e965..000000000 --- a/doc/release/upcoming_changes/13605.deprecation.rst +++ /dev/null @@ -1,9 +0,0 @@ -`np.fromfile` and `np.fromstring` will error on bad data --------------------------------------------------------- - -In future numpy releases, the functions `np.fromfile` and `np.fromstring` -will throw an error when parsing bad data. -This will now give a ``DeprecationWarning`` where previously partial or -even invalid data was silently returned. This deprecation also affects -the C defined functions c:func:`PyArray_FromString`` and -c:func:`PyArray_FromFile` diff --git a/doc/release/upcoming_changes/13610.improvement.rst b/doc/release/upcoming_changes/13610.improvement.rst deleted file mode 100644 index 6f97b43ad..000000000 --- a/doc/release/upcoming_changes/13610.improvement.rst +++ /dev/null @@ -1,5 +0,0 @@ -``argwhere`` now produces a consistent result on 0d arrays ----------------------------------------------------------- -On N-d arrays, `numpy.argwhere` now always produces an array of shape -``(n_non_zero, arr.ndim)``, even when ``arr.ndim == 0``. Previously, the -last axis would have a dimension of 1 in this case. diff --git a/doc/release/upcoming_changes/13794.new_function.rst b/doc/release/upcoming_changes/13794.new_function.rst deleted file mode 100644 index cf8b38bb0..000000000 --- a/doc/release/upcoming_changes/13794.new_function.rst +++ /dev/null @@ -1,5 +0,0 @@ -Multivariate hypergeometric distribution added to `numpy.random` ----------------------------------------------------------------- -The method `multivariate_hypergeometric` has been added to the class -`numpy.random.Generator`. This method generates random variates from -the multivariate hypergeometric probability distribution. diff --git a/doc/release/upcoming_changes/13829.improvement.rst b/doc/release/upcoming_changes/13829.improvement.rst deleted file mode 100644 index ede1b2a53..000000000 --- a/doc/release/upcoming_changes/13829.improvement.rst +++ /dev/null @@ -1,6 +0,0 @@ -Add ``axis`` argument for ``random.permutation`` and ``random.shuffle`` ------------------------------------------------------------------------ - -Previously the ``random.permutation`` and ``random.shuffle`` functions -can only shuffle an array along the first axis; they now have a -new argument ``axis`` which allows shuffle along a specified axis. diff --git a/doc/release/upcoming_changes/13899.change.rst b/doc/release/upcoming_changes/13899.change.rst deleted file mode 100644 index da8277347..000000000 --- a/doc/release/upcoming_changes/13899.change.rst +++ /dev/null @@ -1,4 +0,0 @@ -Incorrect ``threshold`` in ``np.set_printoptions`` raises ``TypeError`` or ``ValueError`` ------------------------------------------------------------------------------------------ -Previously an incorrect ``threshold`` raised ``ValueError``; it now raises ``TypeError`` -for non-numeric types and ``ValueError`` for ``nan`` values. diff --git a/doc/release/upcoming_changes/14036.deprecation.rst b/doc/release/upcoming_changes/14036.deprecation.rst deleted file mode 100644 index 3d997b9a2..000000000 --- a/doc/release/upcoming_changes/14036.deprecation.rst +++ /dev/null @@ -1,4 +0,0 @@ -Deprecate `PyArray_As1D`, `PyArray_As2D` ----------------------------------------- -`PyArray_As1D`, `PyArray_As2D` are deprecated, use -`PyArray_AsCArray` instead
\ No newline at end of file diff --git a/doc/release/upcoming_changes/14036.expired.rst b/doc/release/upcoming_changes/14036.expired.rst deleted file mode 100644 index 05164aa38..000000000 --- a/doc/release/upcoming_changes/14036.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* ``PyArray_As1D`` and ``PyArray_As2D`` have been removed in favor of - ``PyArray_AsCArray`` diff --git a/doc/release/upcoming_changes/14039.expired.rst b/doc/release/upcoming_changes/14039.expired.rst deleted file mode 100644 index effee0626..000000000 --- a/doc/release/upcoming_changes/14039.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* ``np.rank`` has been removed. This was deprecated in NumPy 1.10 - and has been replaced by ``np.ndim``. diff --git a/doc/release/upcoming_changes/14100.expired.rst b/doc/release/upcoming_changes/14100.expired.rst deleted file mode 100644 index e9ea9eeb4..000000000 --- a/doc/release/upcoming_changes/14100.expired.rst +++ /dev/null @@ -1,3 +0,0 @@ -* ``PyArray_FromDimsAndDataAndDescr`` and ``PyArray_FromDims`` have been - removed (they will always raise an error). Use ``PyArray_NewFromDescr`` - and ``PyArray_SimpleNew`` instead. diff --git a/doc/release/upcoming_changes/14181.deprecation.rst b/doc/release/upcoming_changes/14181.deprecation.rst deleted file mode 100644 index 9979b2246..000000000 --- a/doc/release/upcoming_changes/14181.deprecation.rst +++ /dev/null @@ -1,3 +0,0 @@ -Deprecate `np.alen` -------------------- -`np.alen` was deprecated. Use `len` instead. diff --git a/doc/release/upcoming_changes/14197.improvement.rst b/doc/release/upcoming_changes/14197.improvement.rst deleted file mode 100644 index c0c52580a..000000000 --- a/doc/release/upcoming_changes/14197.improvement.rst +++ /dev/null @@ -1,7 +0,0 @@ -``method`` keyword argument for `np.random.multivariate_normal` ---------------------------------------------------------------- -A ``method`` keyword argument is now available for -`np.random.multivariate_normal` with possible values -``{'svd', 'eigh', 'cholesky'}``. To use it, write -``np.random.multivariate_normal(..., method=<method>)``. - diff --git a/doc/release/upcoming_changes/14227.improvement.rst b/doc/release/upcoming_changes/14227.improvement.rst deleted file mode 100644 index 6e45f47c1..000000000 --- a/doc/release/upcoming_changes/14227.improvement.rst +++ /dev/null @@ -1,3 +0,0 @@ -Add complex number support for ``numpy.fromstring`` ---------------------------------------------------- -Now ``numpy.fromstring`` can read complex numbers. diff --git a/doc/release/upcoming_changes/14248.change.rst b/doc/release/upcoming_changes/14248.change.rst deleted file mode 100644 index 9ae0f16bc..000000000 --- a/doc/release/upcoming_changes/14248.change.rst +++ /dev/null @@ -1,10 +0,0 @@ -`numpy.distutils`: append behavior changed for LDFLAGS and similar ------------------------------------------------------------------- -`numpy.distutils` has always overridden rather than appended to ``LDFLAGS`` and -other similar such environment variables for compiling Fortran extensions. Now -the default behavior has changed to appending - which is the expected behavior -in most situations. To preserve the old (overwriting) behavior, set the -``NPY_DISTUTILS_APPEND_FLAGS`` environment variable to 0. This applies to: -``LDFLAGS``, ``F77FLAGS``, ``F90FLAGS``, ``FREEFLAGS``, ``FOPT``, ``FDEBUG``, -and ``FFLAGS``. NumPy 1.16 and 1.17 gave build warnings in situations where this -change in behavior would have affected the compile flags used. diff --git a/doc/release/upcoming_changes/14255.improvement.rst b/doc/release/upcoming_changes/14255.improvement.rst deleted file mode 100644 index e17835efd..000000000 --- a/doc/release/upcoming_changes/14255.improvement.rst +++ /dev/null @@ -1,4 +0,0 @@ -`numpy.unique` has consistent axes order (except the chosen one) when ``axis`` is not None ------------------------------------------------------------------------------------------- -Using ``moveaxis`` instead of ``swapaxes`` in `numpy.unique`, so that the ordering of axes -except the axis in arguments will not be broken. diff --git a/doc/release/upcoming_changes/14256.expired.rst b/doc/release/upcoming_changes/14256.expired.rst deleted file mode 100644 index 229514171..000000000 --- a/doc/release/upcoming_changes/14256.expired.rst +++ /dev/null @@ -1,3 +0,0 @@ -* ``numeric.loads``, ``numeric.load``, ``np.ma.dump``, - ``np.ma.dumps``, ``np.ma.load``, ``np.ma.loads`` are removed, - use ``pickle`` methods instead
\ No newline at end of file diff --git a/doc/release/upcoming_changes/14259.expired.rst b/doc/release/upcoming_changes/14259.expired.rst deleted file mode 100644 index fee44419b..000000000 --- a/doc/release/upcoming_changes/14259.expired.rst +++ /dev/null @@ -1,6 +0,0 @@ -* ``arrayprint.FloatFormat``, ``arrayprint.LongFloatFormat`` has been removed, - use ``FloatingFormat`` instead -* ``arrayprint.ComplexFormat``, ``arrayprint.LongComplexFormat`` has been - removed, use ``ComplexFloatingFormat`` instead -* ``arrayprint.StructureFormat`` has been removed, use ``StructureVoidFormat`` - instead
\ No newline at end of file diff --git a/doc/release/upcoming_changes/14325.expired.rst b/doc/release/upcoming_changes/14325.expired.rst deleted file mode 100644 index 348b3d524..000000000 --- a/doc/release/upcoming_changes/14325.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* ``np.testing.rand`` has been removed. This was deprecated in NumPy 1.11 - and has been replaced by ``np.random.rand``. diff --git a/doc/release/upcoming_changes/14335.expired.rst b/doc/release/upcoming_changes/14335.expired.rst deleted file mode 100644 index 53598cea1..000000000 --- a/doc/release/upcoming_changes/14335.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* Class ``SafeEval`` in ``numpy/lib/utils.py`` has been removed. This was deprecated in NumPy 1.10. - Use ``np.safe_eval`` instead.
\ No newline at end of file diff --git a/doc/release/upcoming_changes/14393.c_api.rst b/doc/release/upcoming_changes/14393.c_api.rst deleted file mode 100644 index 0afd27584..000000000 --- a/doc/release/upcoming_changes/14393.c_api.rst +++ /dev/null @@ -1,5 +0,0 @@ -PyDataType_ISUNSIZED(descr) now returns False for structured datatypes ----------------------------------------------------------------------- -Previously this returned True for any datatype of itemsize 0, but now this -returns false for the non-flexible datatype with itemsize 0, ``np.dtype([])``. - diff --git a/doc/release/upcoming_changes/14464.improvement.rst b/doc/release/upcoming_changes/14464.improvement.rst deleted file mode 100644 index 36ee4090b..000000000 --- a/doc/release/upcoming_changes/14464.improvement.rst +++ /dev/null @@ -1,6 +0,0 @@ -`numpy.matmul` with boolean output now converts to boolean values ------------------------------------------------------------------ -Calling `numpy.matmul` where the output is a boolean array would fill the array -with uint8 equivalents of the result, rather than 0/1. Now it forces the output -to 0 or 1 (``NPY_TRUE`` or ``NPY_FALSE``). - diff --git a/doc/release/upcoming_changes/14498.change.rst b/doc/release/upcoming_changes/14498.change.rst deleted file mode 100644 index fd784e289..000000000 --- a/doc/release/upcoming_changes/14498.change.rst +++ /dev/null @@ -1,7 +0,0 @@ -Remove ``numpy.random.entropy`` without a deprecation ------------------------------------------------------ - -``numpy.random.entropy`` was added to the `numpy.random` namespace in 1.17.0. -It was meant to be a private c-extension module, but was exposed as public. -It has been replaced by `numpy.random.SeedSequence` so the module was -completely removed. diff --git a/doc/release/upcoming_changes/14501.improvement.rst b/doc/release/upcoming_changes/14501.improvement.rst deleted file mode 100644 index f397ecccf..000000000 --- a/doc/release/upcoming_changes/14501.improvement.rst +++ /dev/null @@ -1,6 +0,0 @@ -`numpy.random.randint` produced incorrect value when the range was ``2**32`` ----------------------------------------------------------------------------- -The implementation introduced in 1.17.0 had an incorrect check when -determining whether to use the 32-bit path or the full 64-bit -path that incorrectly redirected random integer generation with a high - low -range of ``2**32`` to the 64-bit generator. diff --git a/doc/release/upcoming_changes/14510.compatibility.rst b/doc/release/upcoming_changes/14510.compatibility.rst deleted file mode 100644 index fc5edbc39..000000000 --- a/doc/release/upcoming_changes/14510.compatibility.rst +++ /dev/null @@ -1,12 +0,0 @@ -`numpy.lib.recfunctions.drop_fields` can no longer return None --------------------------------------------------------------- -If ``drop_fields`` is used to drop all fields, previously the array would -be completely discarded and None returned. Now it returns an array of the -same shape as the input, but with no fields. The old behavior can be retained -with:: - - dropped_arr = drop_fields(arr, ['a', 'b']) - if dropped_arr.dtype.names == (): - dropped_arr = None - -converting the empty recarray to None diff --git a/doc/release/upcoming_changes/14518.change.rst b/doc/release/upcoming_changes/14518.change.rst deleted file mode 100644 index ba3844c85..000000000 --- a/doc/release/upcoming_changes/14518.change.rst +++ /dev/null @@ -1,18 +0,0 @@ -Add options to quiet build configuration and build with ``-Werror`` -------------------------------------------------------------------- -Added two new configuration options. During the ``build_src`` subcommand, as -part of configuring NumPy, the files ``_numpyconfig.h`` and ``config.h`` are -created by probing support for various runtime functions and routines. -Previously, the very verbose compiler output during this stage clouded more -important information. By default the output is silenced. Running ``runtests.py ---debug-info`` will add ``--verbose-cfg`` to the ``build_src`` subcommand, -which will restore the previous behaviour. - -Adding ``CFLAGS=-Werror`` to turn warnings into errors would trigger errors -during the configuration. Now ``runtests.py --warn-error`` will add -``--warn-error`` to the ``build`` subcommand, which will percolate to the -``build_ext`` and ``build_lib`` subcommands. This will add the compiler flag -to those stages and turn compiler warnings into errors while actually building -NumPy itself, avoiding the ``build_src`` subcommand compiler calls. - -(`gh-14527 <https://github.com/numpy/numpy/pull/14527>`__) diff --git a/doc/release/upcoming_changes/14567.expired.rst b/doc/release/upcoming_changes/14567.expired.rst deleted file mode 100644 index 59cb600fb..000000000 --- a/doc/release/upcoming_changes/14567.expired.rst +++ /dev/null @@ -1,5 +0,0 @@ -The files ``numpy/testing/decorators.py``, ``numpy/testing/noseclasses.py`` -and ``numpy/testing/nosetester.py`` have been removed. They were never -meant to be public (all relevant objects are present in the -``numpy.testing`` namespace), and importing them has given a deprecation -warning since NumPy 1.15.0 diff --git a/doc/release/upcoming_changes/14583.expired.rst b/doc/release/upcoming_changes/14583.expired.rst deleted file mode 100644 index 1fad06309..000000000 --- a/doc/release/upcoming_changes/14583.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* Remove deprecated support for boolean and empty condition lists in - `numpy.select` diff --git a/doc/release/upcoming_changes/14596.expired.rst b/doc/release/upcoming_changes/14596.expired.rst deleted file mode 100644 index 3831d5401..000000000 --- a/doc/release/upcoming_changes/14596.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* Array order only accepts 'C', 'F', 'A', and 'K'. More permissive options - were deprecated in NumPy 1.11. diff --git a/doc/release/upcoming_changes/14620.expired.rst b/doc/release/upcoming_changes/14620.expired.rst deleted file mode 100644 index e35589b53..000000000 --- a/doc/release/upcoming_changes/14620.expired.rst +++ /dev/null @@ -1 +0,0 @@ -* np.linspace param num must be an integer. This was deprecated in NumPy 1.12. diff --git a/doc/release/upcoming_changes/14682.expired.rst b/doc/release/upcoming_changes/14682.expired.rst deleted file mode 100644 index e9a8107ec..000000000 --- a/doc/release/upcoming_changes/14682.expired.rst +++ /dev/null @@ -1,2 +0,0 @@ -* UFuncs with multiple outputs must use a tuple for the `out` kwarg. This - finishes a deprecation started in NumPy 1.10. diff --git a/doc/release/upcoming_changes/14717.compatibility.rst b/doc/release/upcoming_changes/14717.compatibility.rst deleted file mode 100644 index f6f0ec8e5..000000000 --- a/doc/release/upcoming_changes/14717.compatibility.rst +++ /dev/null @@ -1,4 +0,0 @@ -``numpy.argmin/argmax/min/max`` returns ``NaT`` if it exists in array ---------------------------------------------------------------------- -``numpy.argmin``, ``numpy.argmax``, ``numpy.min``, and ``numpy.max`` will return -``NaT`` if it exists in the array. diff --git a/doc/release/upcoming_changes/14720.deprecation.rst b/doc/release/upcoming_changes/14720.deprecation.rst deleted file mode 100644 index 46ad6d8f7..000000000 --- a/doc/release/upcoming_changes/14720.deprecation.rst +++ /dev/null @@ -1,8 +0,0 @@ -Deprecate the financial functions ---------------------------------- -In accordance with -`NEP-32 <https://numpy.org/neps/nep-0032-remove-financial-functions.html>`_, -the functions `fv`, `ipmt`, `irr`, `mirr`, `nper`, `npv`, `pmt`, `ppmt`, -`pv` and `rate` are deprecated, and will be removed from NumPy 1.20. -The replacement for these functions is the Python package -`numpy-financial <https://pypi.org/project/numpy-financial>`_. diff --git a/doc/release/upcoming_changes/14730.improvement.rst b/doc/release/upcoming_changes/14730.improvement.rst deleted file mode 100644 index ee073d234..000000000 --- a/doc/release/upcoming_changes/14730.improvement.rst +++ /dev/null @@ -1,3 +0,0 @@ -Add complex number support for ``numpy.fromfile`` -------------------------------------------------- -Now ``numpy.fromfile`` can read complex numbers. diff --git a/doc/release/upcoming_changes/14771.improvement.rst b/doc/release/upcoming_changes/14771.improvement.rst deleted file mode 100644 index aaea8f8ed..000000000 --- a/doc/release/upcoming_changes/14771.improvement.rst +++ /dev/null @@ -1,5 +0,0 @@ -``std=c99`` added if compiler is named ``gcc`` ----------------------------------------------- -GCC before version 5 requires the ``-std=c99`` command line argument. Newer -compilers automatically turn on C99 mode. The compiler setup code will -automatically add the code if the compiler name has ``gcc`` in it. diff --git a/doc/release/upcoming_changes/14777.compatibility.rst b/doc/release/upcoming_changes/14777.compatibility.rst deleted file mode 100644 index d594463de..000000000 --- a/doc/release/upcoming_changes/14777.compatibility.rst +++ /dev/null @@ -1,5 +0,0 @@ -Changed random variate stream from `numpy.random.Generator.integers` --------------------------------------------------------------------- -There was a bug in `numpy.random.Generator.integers` that caused biased -sampling of 8 and 16 bit integer types. Fixing that bug has changed the -output stream from what it was in previous releases. diff --git a/doc/source/conf.py b/doc/source/conf.py index 83cecc917..09770535b 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -178,15 +178,28 @@ latex_elements = { } # Additional stuff for the LaTeX preamble. -latex_preamble = r''' -\usepackage{amsmath} -\DeclareUnicodeCharacter{00A0}{\nobreakspace} - +latex_elements['preamble'] = r''' % In the parameters section, place a newline after the Parameters % header \usepackage{expdlist} \let\latexdescription=\description \def\description{\latexdescription{}{} \breaklabel} +% but expdlist old LaTeX package requires fixes: +% 1) remove extra space +\usepackage{etoolbox} +\makeatletter +\patchcmd\@item{{\@breaklabel} }{{\@breaklabel}}{}{} +\makeatother +% 2) fix bug in expdlist's way of breaking the line after long item label +\makeatletter +\def\breaklabel{% + \def\@breaklabel{% + \leavevmode\par + % now a hack because Sphinx inserts \leavevmode after term node + \def\leavevmode{\def\leavevmode{\unhbox\voidb@x}}% + }% +} +\makeatother % Make Examples/etc section headers smaller and more compact \makeatletter diff --git a/doc/source/dev/development_environment.rst b/doc/source/dev/development_environment.rst index 297502b31..c20b6fe40 100644 --- a/doc/source/dev/development_environment.rst +++ b/doc/source/dev/development_environment.rst @@ -53,12 +53,22 @@ When using pytest as a target (the default), you can .. note:: - Remember that all tests of NumPy should pass before commiting your changes. + Remember that all tests of NumPy should pass before committing your changes. Using ``runtests.py`` is the recommended approach to running tests. There are also a number of alternatives to it, for example in-place build or installing to a virtualenv. See the FAQ below for details. +.. note:: + + Some of the tests in the test suite require a large amount of + memory, and are skipped if your system does not have enough. + + To override the automatic detection of available memory, set the + environment variable ``NPY_AVAILABLE_MEM``, for example + ``NPY_AVAILABLE_MEM=32GB``, or using pytest ``--available-memory=32GB`` + target option. + Building in-place ----------------- @@ -145,7 +155,7 @@ Running tests Besides using ``runtests.py``, there are various ways to run the tests. Inside the interpreter, tests can be run like this:: - >>> np.test() + >>> np.test() # doctest: +SKIPBLOCK >>> np.test('full') # Also run tests marked as slow >>> np.test('full', verbose=2) # Additionally print test name/file diff --git a/doc/source/docs/howto_build_docs.rst b/doc/source/docs/howto_build_docs.rst index 6deacda5c..f46070d78 100644 --- a/doc/source/docs/howto_build_docs.rst +++ b/doc/source/docs/howto_build_docs.rst @@ -5,7 +5,7 @@ Building the NumPy API and reference docs ========================================= We currently use Sphinx_ for generating the API and reference -documentation for NumPy. You will need Sphinx 1.8.3 <= 1.8.5. +documentation for NumPy. You will need Sphinx >= 2.0.0. If you only want to get the documentation, note that pre-built versions can be found at @@ -57,7 +57,9 @@ To build the PDF documentation, do instead:: make latex make -C build/latex all-pdf -You will need to have Latex installed for this. +You will need to have Latex installed for this, inclusive of support for +Greek letters. For example, on Ubuntu xenial ``texlive-lang-greek`` and +``cm-super`` are needed. Also ``latexmk`` is needed on non-Windows systems. Instead of the above, you can also do:: diff --git a/doc/source/reference/alignment.rst b/doc/source/reference/alignment.rst index ebc8f353c..5e4315b38 100644 --- a/doc/source/reference/alignment.rst +++ b/doc/source/reference/alignment.rst @@ -67,7 +67,7 @@ There are 4 relevant uses of the word ``align`` used in numpy: field alignment. In either case ``dtype.isalignedstruct`` is also set to True. * ``IsUintAligned`` is used to determine if an ndarray is "uint aligned" in - an analagous way to how ``IsAligned`` checks for true-alignment. + an analogous way to how ``IsAligned`` checks for true-alignment. Consequences of alignment ------------------------- diff --git a/doc/source/reference/arrays.datetime.rst b/doc/source/reference/arrays.datetime.rst index 2225eedb3..9c45e04c7 100644 --- a/doc/source/reference/arrays.datetime.rst +++ b/doc/source/reference/arrays.datetime.rst @@ -368,7 +368,7 @@ times in UTC. By default, creating a datetime64 object from a string or printing it would convert from or to local time:: # old behavior - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00-0800') # note the timezone offset -08:00 A consensus of datetime64 users agreed that this behavior is undesirable @@ -378,7 +378,7 @@ most use cases, a timezone naive datetime type is preferred, similar to the datetime64 no longer assumes that input is in local time, nor does it print local times:: - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00') For backwards compatibility, datetime64 still parses timezone offsets, which @@ -393,4 +393,4 @@ As a corollary to this change, we no longer prohibit casting between datetimes with date units and datetimes with timeunits. With timezone naive datetimes, the rule for casting from dates to times is no longer ambiguous. -.. _pandas: http://pandas.pydata.org
\ No newline at end of file +.. _pandas: http://pandas.pydata.org diff --git a/doc/source/reference/random/bit_generators/index.rst b/doc/source/reference/random/bit_generators/index.rst index 94d3d8a3c..315657172 100644 --- a/doc/source/reference/random/bit_generators/index.rst +++ b/doc/source/reference/random/bit_generators/index.rst @@ -19,7 +19,7 @@ The included BitGenerators are: and can be advanced by an arbitrary amount. See the documentation for :meth:`~.PCG64.advance`. PCG-64 has a period of :math:`2^{128}`. See the `PCG author's page`_ for more details about this class of PRNG. -* MT19937 - The standard Python BitGenerator. Adds a `~mt19937.MT19937.jumped` +* MT19937 - The standard Python BitGenerator. Adds a `MT19937.jumped` function that returns a new generator with state as-if :math:`2^{128}` draws have been made. * Philox - A counter-based generator capable of being advanced an diff --git a/doc/source/reference/random/bit_generators/pcg64.rst b/doc/source/reference/random/bit_generators/pcg64.rst index 5881b7008..edac4620b 100644 --- a/doc/source/reference/random/bit_generators/pcg64.rst +++ b/doc/source/reference/random/bit_generators/pcg64.rst @@ -1,5 +1,5 @@ -Parallel Congruent Generator (64-bit, PCG64) --------------------------------------------- +Permuted Congruential Generator (64-bit, PCG64) +----------------------------------------------- .. currentmodule:: numpy.random diff --git a/doc/source/reference/random/c-api.rst b/doc/source/reference/random/c-api.rst new file mode 100644 index 000000000..0d60f4d9e --- /dev/null +++ b/doc/source/reference/random/c-api.rst @@ -0,0 +1,192 @@ +Cython API for random +--------------------- + +.. currentmodule:: numpy.random + +Typed versions of many of the `Generator` and `BitGenerator` methods as well as +the classes themselves can be accessed directly from Cython via + +.. code-block:: cython + + cimport numpy.random + +C API for random +---------------- + +Access to various distributions is available via Cython or C-wrapper libraries +like CFFI. All the functions accept a :c:type:`bitgen_t` as their first argument. + +.. c:type:: bitgen_t + + The :c:type:`bitgen_t` holds the current state of the BitGenerator and + pointers to functions that return standard C types while advancing the + state. + + .. code-block:: c + + struct bitgen: + void *state + npy_uint64 (*next_uint64)(void *st) nogil + uint32_t (*next_uint32)(void *st) nogil + double (*next_double)(void *st) nogil + npy_uint64 (*next_raw)(void *st) nogil + + ctypedef bitgen bitgen_t + +See :doc:`extending` for examples of using these functions. + +The functions are named with the following conventions: + +- "standard" refers to the reference values for any parameters. For instance + "standard_uniform" means a uniform distribution on the interval ``0.0`` to + ``1.0`` + +- "fill" functions will fill the provided ``out`` with ``cnt`` values. + +- The functions without "standard" in their name require additional parameters + to describe the distributions. + +- ``zig`` in the name are based on a ziggurat lookup algorithm is used instead + of calculating the ``log``, which is significantly faster. The non-ziggurat + variants are used in corner cases and for legacy compatibility. + + +.. c:function:: double random_standard_uniform(bitgen_t *bitgen_state) + +.. c:function:: void random_standard_uniform_fill(bitgen_t* bitgen_state, npy_intp cnt, double *out) + +.. c:function:: double random_standard_exponential(bitgen_t *bitgen_state) + +.. c:function:: void random_standard_exponential_fill(bitgen_t *bitgen_state, npy_intp cnt, double *out) + +.. c:function:: double random_standard_normal(bitgen_t* bitgen_state) + +.. c:function:: void random_standard_normal_fill(bitgen_t *bitgen_state, npy_intp count, double *out) + +.. c:function:: void random_standard_normal_fill_f(bitgen_t *bitgen_state, npy_intp count, float *out) + +.. c:function:: double random_standard_gamma(bitgen_t *bitgen_state, double shape) + +.. c:function:: float random_standard_uniform_f(bitgen_t *bitgen_state) + +.. c:function:: void random_standard_uniform_fill_f(bitgen_t* bitgen_state, npy_intp cnt, float *out) + +.. c:function:: float random_standard_exponential_f(bitgen_t *bitgen_state) + +.. c:function:: void random_standard_exponential_fill_f(bitgen_t *bitgen_state, npy_intp cnt, float *out) + +.. c:function:: float random_standard_normal_f(bitgen_t* bitgen_state) + +.. c:function:: float random_standard_gamma_f(bitgen_t *bitgen_state, float shape) + +.. c:function:: double random_normal(bitgen_t *bitgen_state, double loc, double scale) + +.. c:function:: double random_gamma(bitgen_t *bitgen_state, double shape, double scale) + +.. c:function:: float random_gamma_f(bitgen_t *bitgen_state, float shape, float scale) + +.. c:function:: double random_exponential(bitgen_t *bitgen_state, double scale) + +.. c:function:: double random_uniform(bitgen_t *bitgen_state, double lower, double range) + +.. c:function:: double random_beta(bitgen_t *bitgen_state, double a, double b) + +.. c:function:: double random_chisquare(bitgen_t *bitgen_state, double df) + +.. c:function:: double random_f(bitgen_t *bitgen_state, double dfnum, double dfden) + +.. c:function:: double random_standard_cauchy(bitgen_t *bitgen_state) + +.. c:function:: double random_pareto(bitgen_t *bitgen_state, double a) + +.. c:function:: double random_weibull(bitgen_t *bitgen_state, double a) + +.. c:function:: double random_power(bitgen_t *bitgen_state, double a) + +.. c:function:: double random_laplace(bitgen_t *bitgen_state, double loc, double scale) + +.. c:function:: double random_gumbel(bitgen_t *bitgen_state, double loc, double scale) + +.. c:function:: double random_logistic(bitgen_t *bitgen_state, double loc, double scale) + +.. c:function:: double random_lognormal(bitgen_t *bitgen_state, double mean, double sigma) + +.. c:function:: double random_rayleigh(bitgen_t *bitgen_state, double mode) + +.. c:function:: double random_standard_t(bitgen_t *bitgen_state, double df) + +.. c:function:: double random_noncentral_chisquare(bitgen_t *bitgen_state, double df, double nonc) +.. c:function:: double random_noncentral_f(bitgen_t *bitgen_state, double dfnum, double dfden, double nonc) +.. c:function:: double random_wald(bitgen_t *bitgen_state, double mean, double scale) + +.. c:function:: double random_vonmises(bitgen_t *bitgen_state, double mu, double kappa) + +.. c:function:: double random_triangular(bitgen_t *bitgen_state, double left, double mode, double right) + +.. c:function:: npy_int64 random_poisson(bitgen_t *bitgen_state, double lam) + +.. c:function:: npy_int64 random_negative_binomial(bitgen_t *bitgen_state, double n, double p) + +.. c:type:: binomial_t + + .. code-block:: c + + typedef struct s_binomial_t { + int has_binomial; /* !=0: following parameters initialized for binomial */ + double psave; + RAND_INT_TYPE nsave; + double r; + double q; + double fm; + RAND_INT_TYPE m; + double p1; + double xm; + double xl; + double xr; + double c; + double laml; + double lamr; + double p2; + double p3; + double p4; + } binomial_t; + + +.. c:function:: npy_int64 random_binomial(bitgen_t *bitgen_state, double p, npy_int64 n, binomial_t *binomial) + +.. c:function:: npy_int64 random_logseries(bitgen_t *bitgen_state, double p) + +.. c:function:: npy_int64 random_geometric_search(bitgen_t *bitgen_state, double p) + +.. c:function:: npy_int64 random_geometric_inversion(bitgen_t *bitgen_state, double p) + +.. c:function:: npy_int64 random_geometric(bitgen_t *bitgen_state, double p) + +.. c:function:: npy_int64 random_zipf(bitgen_t *bitgen_state, double a) + +.. c:function:: npy_int64 random_hypergeometric(bitgen_t *bitgen_state, npy_int64 good, npy_int64 bad, npy_int64 sample) + +.. c:function:: npy_uint64 random_interval(bitgen_t *bitgen_state, npy_uint64 max) + +.. c:function:: void random_multinomial(bitgen_t *bitgen_state, npy_int64 n, npy_int64 *mnix, double *pix, npy_intp d, binomial_t *binomial) + +.. c:function:: int random_multivariate_hypergeometric_count(bitgen_t *bitgen_state, npy_int64 total, size_t num_colors, npy_int64 *colors, npy_int64 nsample, size_t num_variates, npy_int64 *variates) + +.. c:function:: void random_multivariate_hypergeometric_marginals(bitgen_t *bitgen_state, npy_int64 total, size_t num_colors, npy_int64 *colors, npy_int64 nsample, size_t num_variates, npy_int64 *variates) + +Generate a single integer + +.. c:function:: npy_int64 random_positive_int64(bitgen_t *bitgen_state) + +.. c:function:: npy_int32 random_positive_int32(bitgen_t *bitgen_state) + +.. c:function:: npy_int64 random_positive_int(bitgen_t *bitgen_state) + +.. c:function:: npy_uint64 random_uint(bitgen_t *bitgen_state) + + +Generate random uint64 numbers in closed interval [off, off + rng]. + +.. c:function:: npy_uint64 random_bounded_uint64(bitgen_t *bitgen_state, npy_uint64 off, npy_uint64 rng, npy_uint64 mask, bint use_masked) + + diff --git a/doc/source/reference/random/examples/cffi.rst b/doc/source/reference/random/examples/cffi.rst new file mode 100644 index 000000000..04d52203b --- /dev/null +++ b/doc/source/reference/random/examples/cffi.rst @@ -0,0 +1,5 @@ +Extending via CFFI +------------------ + +.. literalinclude:: ../../../../../numpy/random/_examples/cffi/extending.py + :language: python diff --git a/doc/source/reference/random/examples/cython/extending.pyx b/doc/source/reference/random/examples/cython/extending.pyx new file mode 100644 index 000000000..0cfbc146f --- /dev/null +++ b/doc/source/reference/random/examples/cython/extending.pyx @@ -0,0 +1,4 @@ +extending.pyx +------------- + +.. include:: ../../../../../../numpy/random/examples/extending.pyx diff --git a/doc/source/reference/random/examples/cython/extending.pyx.rst b/doc/source/reference/random/examples/cython/extending.pyx.rst new file mode 100644 index 000000000..e2bba5aa4 --- /dev/null +++ b/doc/source/reference/random/examples/cython/extending.pyx.rst @@ -0,0 +1,5 @@ +extending.pyx +------------- + +.. literalinclude:: ../../../../../../numpy/random/_examples/cython/extending.pyx + :language: cython diff --git a/doc/source/reference/random/examples/cython/extending_distributions.pyx.rst b/doc/source/reference/random/examples/cython/extending_distributions.pyx.rst new file mode 100644 index 000000000..f64921c67 --- /dev/null +++ b/doc/source/reference/random/examples/cython/extending_distributions.pyx.rst @@ -0,0 +1,5 @@ +extending_distributions.pyx +--------------------------- + +.. literalinclude:: ../../../../../../numpy/random/_examples/cython/extending_distributions.pyx + :language: cython diff --git a/doc/source/reference/random/examples/cython/index.rst b/doc/source/reference/random/examples/cython/index.rst new file mode 100644 index 000000000..368f5fcd5 --- /dev/null +++ b/doc/source/reference/random/examples/cython/index.rst @@ -0,0 +1,11 @@ + +.. _extending_cython_example: + +Extending `numpy.random` via Cython +----------------------------------- + + +.. toctree:: + setup.py.rst + extending.pyx + extending_distributions.pyx diff --git a/doc/source/reference/random/examples/cython/setup.py.rst b/doc/source/reference/random/examples/cython/setup.py.rst new file mode 100644 index 000000000..bc7a74c59 --- /dev/null +++ b/doc/source/reference/random/examples/cython/setup.py.rst @@ -0,0 +1,5 @@ +setup.py +-------- + +.. literalinclude:: ../../../../../../numpy/random/_examples/cython/setup.py + :language: python diff --git a/doc/source/reference/random/examples/numba.rst b/doc/source/reference/random/examples/numba.rst new file mode 100644 index 000000000..b41a02568 --- /dev/null +++ b/doc/source/reference/random/examples/numba.rst @@ -0,0 +1,5 @@ +Extending via Numba +------------------- + +.. literalinclude:: ../../../../../numpy/random/_examples/numba/extending.py + :language: python diff --git a/doc/source/reference/random/examples/numba_cffi.rst b/doc/source/reference/random/examples/numba_cffi.rst new file mode 100644 index 000000000..fb2f85cce --- /dev/null +++ b/doc/source/reference/random/examples/numba_cffi.rst @@ -0,0 +1,5 @@ +Extending via Numba and CFFI +---------------------------- + +.. literalinclude:: ../../../../../numpy/random/_examples/numba/extending_distributions.py + :language: python diff --git a/doc/source/reference/random/extending.rst b/doc/source/reference/random/extending.rst index 22f9cb7e4..4adb90c06 100644 --- a/doc/source/reference/random/extending.rst +++ b/doc/source/reference/random/extending.rst @@ -1,5 +1,7 @@ .. currentmodule:: numpy.random +.. _extending: + Extending --------- The BitGenerators have been designed to be extendable using standard tools for @@ -12,128 +14,61 @@ Numba Numba can be used with either CTypes or CFFI. The current iteration of the BitGenerators all export a small set of functions through both interfaces. -This example shows how numba can be used to produce Box-Muller normals using +This example shows how numba can be used to produce gaussian samples using a pure Python implementation which is then compiled. The random numbers are provided by ``ctypes.next_double``. -.. code-block:: python - - from numpy.random import PCG64 - import numpy as np - import numba as nb - - x = PCG64() - f = x.ctypes.next_double - s = x.ctypes.state - state_addr = x.ctypes.state_address - - def normals(n, state): - out = np.empty(n) - for i in range((n+1)//2): - x1 = 2.0*f(state) - 1.0 - x2 = 2.0*f(state) - 1.0 - r2 = x1*x1 + x2*x2 - while r2 >= 1.0 or r2 == 0.0: - x1 = 2.0*f(state) - 1.0 - x2 = 2.0*f(state) - 1.0 - r2 = x1*x1 + x2*x2 - g = np.sqrt(-2.0*np.log(r2)/r2) - out[2*i] = g*x1 - if 2*i+1 < n: - out[2*i+1] = g*x2 - return out - - # Compile using Numba - print(normals(10, s).var()) - # Warm up - normalsj = nb.jit(normals, nopython=True) - # Must use state address not state with numba - normalsj(1, state_addr) - %timeit normalsj(1000000, state_addr) - print('1,000,000 Box-Muller (numba/PCG64) randoms') - %timeit np.random.standard_normal(1000000) - print('1,000,000 Box-Muller (NumPy) randoms') - +.. literalinclude:: ../../../../numpy/random/_examples/numba/extending.py + :language: python + :end-before: example 2 Both CTypes and CFFI allow the more complicated distributions to be used -directly in Numba after compiling the file distributions.c into a DLL or so. -An example showing the use of a more complicated distribution is in the -examples folder. +directly in Numba after compiling the file distributions.c into a ``DLL`` or +``so``. An example showing the use of a more complicated distribution is in +the `examples` section below. -.. _randomgen_cython: +.. _random_cython: Cython ====== Cython can be used to unpack the ``PyCapsule`` provided by a BitGenerator. -This example uses `~pcg64.PCG64` and -``random_gauss_zig``, the Ziggurat-based generator for normals, to fill an -array. The usual caveats for writing high-performance code using Cython -- -removing bounds checks and wrap around, providing array alignment information --- still apply. - -.. code-block:: cython - - import numpy as np - cimport numpy as np - cimport cython - from cpython.pycapsule cimport PyCapsule_IsValid, PyCapsule_GetPointer - from numpy.random.common cimport * - from numpy.random.distributions cimport random_gauss_zig - from numpy.random import PCG64 - - - @cython.boundscheck(False) - @cython.wraparound(False) - def normals_zig(Py_ssize_t n): - cdef Py_ssize_t i - cdef bitgen_t *rng - cdef const char *capsule_name = "BitGenerator" - cdef double[::1] random_values - - x = PCG64() - capsule = x.capsule - if not PyCapsule_IsValid(capsule, capsule_name): - raise ValueError("Invalid pointer to anon_func_state") - rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name) - random_values = np.empty(n) - # Best practice is to release GIL and acquire the lock - with x.lock, nogil: - for i in range(n): - random_values[i] = random_gauss_zig(rng) - randoms = np.asarray(random_values) - return randoms +This example uses `PCG64` and the example from above. The usual caveats +for writing high-performance code using Cython -- removing bounds checks and +wrap around, providing array alignment information -- still apply. + +.. literalinclude:: ../../../../numpy/random/_examples/cython/extending_distributions.pyx + :language: cython + :end-before: example 2 The BitGenerator can also be directly accessed using the members of the basic RNG structure. -.. code-block:: cython - - @cython.boundscheck(False) - @cython.wraparound(False) - def uniforms(Py_ssize_t n): - cdef Py_ssize_t i - cdef bitgen_t *rng - cdef const char *capsule_name = "BitGenerator" - cdef double[::1] random_values - - x = PCG64() - capsule = x.capsule - # Optional check that the capsule if from a BitGenerator - if not PyCapsule_IsValid(capsule, capsule_name): - raise ValueError("Invalid pointer to anon_func_state") - # Cast the pointer - rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name) - random_values = np.empty(n) - with x.lock, nogil: - for i in range(n): - # Call the function - random_values[i] = rng.next_double(rng.state) - randoms = np.asarray(random_values) - return randoms - -These functions along with a minimal setup file are included in the -examples folder. +.. literalinclude:: ../../../../numpy/random/_examples/cython/extending_distributions.pyx + :language: cython + :start-after: example 2 + +See :ref:`extending_cython_example` for a complete working example including a +minimal setup and cython files. + +CFFI +==== + +CFFI can be used to directly access the functions in +``include/numpy/random/distributions.h``. Some "massaging" of the header +file is required: + +.. literalinclude:: ../../../../numpy/random/_examples/cffi/extending.py + :language: python + :end-before: dlopen + +Once the header is parsed by ``ffi.cdef``, the functions can be accessed +directly from the ``_generator`` shared object, using the `BitGenerator.cffi` interface. + +.. literalinclude:: ../../../../numpy/random/_examples/cffi/extending.py + :language: python + :start-after: dlopen + New Basic RNGs ============== @@ -163,3 +98,12 @@ the next 64-bit unsigned integer function if not needed. Functions inside .. code-block:: c bitgen_state->next_uint64(bitgen_state->state) + +Examples +======== + +.. toctree:: + Numba <examples/numba> + CFFI + Numba <examples/numba_cffi> + Cython <examples/cython/index> + CFFI <examples/cffi> diff --git a/doc/source/reference/random/index.rst b/doc/source/reference/random/index.rst index 15c161244..bda9c4d96 100644 --- a/doc/source/reference/random/index.rst +++ b/doc/source/reference/random/index.rst @@ -22,34 +22,44 @@ Since Numpy version 1.17.0 the Generator can be initialized with a number of different BitGenerators. It exposes many different probability distributions. See `NEP 19 <https://www.numpy.org/neps/ nep-0019-rng-policy.html>`_ for context on the updated random Numpy number -routines. The legacy `.RandomState` random number routines are still +routines. The legacy `RandomState` random number routines are still available, but limited to a single BitGenerator. -For convenience and backward compatibility, a single `~.RandomState` +For convenience and backward compatibility, a single `RandomState` instance's methods are imported into the numpy.random namespace, see :ref:`legacy` for the complete list. +.. _random-quick-start: + Quick Start ----------- -By default, `~Generator` uses bits provided by `~pcg64.PCG64` which -has better statistical properties than the legacy mt19937 random -number generator in `~.RandomState`. +Call `default_rng` to get a new instance of a `Generator`, then call its +methods to obtain samples from different distributions. By default, +`Generator` uses bits provided by `PCG64` which has better statistical +properties than the legacy `MT19937` used in `RandomState`. .. code-block:: python - # Uses the old numpy.random.RandomState + # Do this + from numpy.random import default_rng + rng = default_rng() + vals = rng.standard_normal(10) + more_vals = rng.standard_normal(10) + + # instead of this from numpy import random - random.standard_normal() + vals = random.standard_normal(10) + more_vals = random.standard_normal(10) -`~Generator` can be used as a replacement for `~.RandomState`. Both class -instances now hold a internal `BitGenerator` instance to provide the bit +`Generator` can be used as a replacement for `RandomState`. Both class +instances hold a internal `BitGenerator` instance to provide the bit stream, it is accessible as ``gen.bit_generator``. Some long-overdue API cleanup means that legacy and compatibility methods have been removed from -`~.Generator` +`Generator` =================== ============== ============ -`~.RandomState` `~.Generator` Notes +`RandomState` `Generator` Notes ------------------- -------------- ------------ ``random_sample``, ``random`` Compatible with `random.random` ``rand`` @@ -58,21 +68,12 @@ cleanup means that legacy and compatibility methods have been removed from ``random_integers`` ------------------- -------------- ------------ ``tomaxint`` removed Use ``integers(0, np.iinfo(np.int_).max,`` - ``endpoint=False)`` + ``endpoint=False)`` ------------------- -------------- ------------ -``seed`` removed Use `~.SeedSequence.spawn` +``seed`` removed Use `SeedSequence.spawn` =================== ============== ============ -See `new-or-different` for more information - -.. code-block:: python - - # As replacement for RandomState(); default_rng() instantiates Generator with - # the default PCG64 BitGenerator. - from numpy.random import default_rng - rg = default_rng() - rg.standard_normal() - rg.bit_generator +See :ref:`new-or-different` for more information Something like the following code can be used to support both ``RandomState`` and ``Generator``, with the understanding that the interfaces are slightly @@ -87,9 +88,9 @@ different a = rg_integers(1000) Seeds can be passed to any of the BitGenerators. The provided value is mixed -via `~.SeedSequence` to spread a possible sequence of seeds across a wider -range of initialization states for the BitGenerator. Here `~.PCG64` is used and -is wrapped with a `~.Generator`. +via `SeedSequence` to spread a possible sequence of seeds across a wider +range of initialization states for the BitGenerator. Here `PCG64` is used and +is wrapped with a `Generator`. .. code-block:: python @@ -100,7 +101,7 @@ is wrapped with a `~.Generator`. Introduction ------------ The new infrastructure takes a different approach to producing random numbers -from the `~.RandomState` object. Random number generation is separated into +from the `RandomState` object. Random number generation is separated into two components, a bit generator and a random generator. The `BitGenerator` has a limited set of responsibilities. It manages state @@ -113,8 +114,8 @@ distributions, e.g., simulated normal random values. This structure allows alternative bit generators to be used with little code duplication. The `Generator` is the user-facing object that is nearly identical to -`.RandomState`. The canonical method to initialize a generator passes a -`~.PCG64` bit generator as the sole argument. +`RandomState`. The canonical method to initialize a generator passes a +`PCG64` bit generator as the sole argument. .. code-block:: python @@ -139,9 +140,9 @@ What's New or Different The Box-Muller method used to produce NumPy's normals is no longer available in `Generator`. It is not possible to reproduce the exact random values using Generator for the normal distribution or any other - distribution that relies on the normal such as the `.RandomState.gamma` or - `.RandomState.standard_t`. If you require bitwise backward compatible - streams, use `.RandomState`. + distribution that relies on the normal such as the `RandomState.gamma` or + `RandomState.standard_t`. If you require bitwise backward compatible + streams, use `RandomState`. * The Generator's normal, exponential and gamma functions use 256-step Ziggurat methods which are 2-10 times faster than NumPy's Box-Muller or inverse CDF @@ -152,20 +153,20 @@ What's New or Different * Optional ``out`` argument that allows existing arrays to be filled for select distributions * All BitGenerators can produce doubles, uint64s and uint32s via CTypes - (`~.PCG64.ctypes`) and CFFI (`~.PCG64.cffi`). This allows the bit generators + (`PCG64.ctypes`) and CFFI (`PCG64.cffi`). This allows the bit generators to be used in numba. * The bit generators can be used in downstream projects via - :ref:`Cython <randomgen_cython>`. -* `~.Generator.integers` is now the canonical way to generate integer + :ref:`Cython <random_cython>`. +* `Generator.integers` is now the canonical way to generate integer random numbers from a discrete uniform distribution. The ``rand`` and - ``randn`` methods are only available through the legacy `~.RandomState`. + ``randn`` methods are only available through the legacy `RandomState`. The ``endpoint`` keyword can be used to specify open or closed intervals. This replaces both ``randint`` and the deprecated ``random_integers``. -* `~.Generator.random` is now the canonical way to generate floating-point - random numbers, which replaces `.RandomState.random_sample`, - `.RandomState.sample`, and `.RandomState.ranf`. This is consistent with +* `Generator.random` is now the canonical way to generate floating-point + random numbers, which replaces `RandomState.random_sample`, + `RandomState.sample`, and `RandomState.ranf`. This is consistent with Python's `random.random`. -* All BitGenerators in numpy use `~SeedSequence` to convert seeds into +* All BitGenerators in numpy use `SeedSequence` to convert seeds into initialized states. See :ref:`new-or-different` for a complete list of improvements and @@ -199,10 +200,12 @@ Features Multithreaded Generation <multithreading> new-or-different Comparing Performance <performance> - extending + c-api + Examples of using Numba, Cython, CFFI <extending> -Original Source -~~~~~~~~~~~~~~~ +Original Source of the Generator and BitGenerators +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This package was developed independently of NumPy and was integrated in version 1.17.0. The original repo is at https://github.com/bashtage/randomgen. + diff --git a/doc/source/reference/random/legacy.rst b/doc/source/reference/random/legacy.rst index 413a42727..922d76a9a 100644 --- a/doc/source/reference/random/legacy.rst +++ b/doc/source/reference/random/legacy.rst @@ -121,3 +121,71 @@ Distributions ~RandomState.wald ~RandomState.weibull ~RandomState.zipf + +Functions in `numpy.random` +=========================== +Many of the RandomState methods above are exported as functions in +`numpy.random` This usage is discouraged, as it is implemented via a gloabl +`RandomState` instance which is not advised on two counts: + +- It uses global state, which means results will change as the code changes + +- It uses a `RandomState` rather than the more modern `Generator`. + +For backward compatible legacy reasons, we cannot change this. See +`random-quick-start`. + +.. autosummary:: + :toctree: generated/ + + beta + binomial + bytes + chisquare + choice + dirichlet + exponential + f + gamma + geometric + get_state + gumbel + hypergeometric + laplace + logistic + lognormal + logseries + multinomial + multivariate_normal + negative_binomial + noncentral_chisquare + noncentral_f + normal + pareto + permutation + poisson + power + rand + randint + randn + random + random_integers + random_sample + ranf + rayleigh + sample + seed + set_state + shuffle + standard_cauchy + standard_exponential + standard_gamma + standard_normal + standard_t + triangular + uniform + vonmises + wald + weibull + zipf + diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst index 0416d6efc..361cf11b9 100644 --- a/doc/source/reference/ufuncs.rst +++ b/doc/source/reference/ufuncs.rst @@ -253,9 +253,9 @@ can generate this table for your system with the code given in the Figure. B - - Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y - Y H - - - Y Y Y Y - Y Y Y Y Y - Y Y Y Y Y Y Y Y Y Y - Y I - - - - Y Y Y - - Y Y Y Y - - Y Y - Y Y Y Y Y Y - Y - L - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - Y - Q - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - Y - P - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - Y + L - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - - + Q - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - - + P - - - - - - - - - - Y Y Y - - Y Y - Y Y Y Y Y Y - - e - - - - - - - - - - - - - Y Y Y Y Y Y Y Y Y Y Y - - f - - - - - - - - - - - - - - Y Y Y Y Y Y Y Y Y Y - - d - - - - - - - - - - - - - - - Y Y - Y Y Y Y Y Y - - diff --git a/doc/source/release.rst b/doc/source/release.rst index 0343275a5..26373ad07 100644 --- a/doc/source/release.rst +++ b/doc/source/release.rst @@ -5,6 +5,7 @@ Release Notes .. toctree:: :maxdepth: 3 + 1.19.0 <release/1.19.0-notes> 1.18.0 <release/1.18.0-notes> 1.17.4 <release/1.17.4-notes> 1.17.3 <release/1.17.3-notes> diff --git a/doc/source/release/1.11.0-notes.rst b/doc/source/release/1.11.0-notes.rst index 1a179657b..36cd1d65a 100644 --- a/doc/source/release/1.11.0-notes.rst +++ b/doc/source/release/1.11.0-notes.rst @@ -85,7 +85,7 @@ times in UTC. By default, creating a datetime64 object from a string or printing it would convert from or to local time:: # old behavior - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00-0800') # note the timezone offset -08:00 @@ -96,7 +96,7 @@ type is preferred, similar to the ``datetime.datetime`` type in the Python standard library. Accordingly, datetime64 no longer assumes that input is in local time, nor does it print local times:: - >>>> np.datetime64('2000-01-01T00:00:00') + >>> np.datetime64('2000-01-01T00:00:00') numpy.datetime64('2000-01-01T00:00:00') For backwards compatibility, datetime64 still parses timezone offsets, which diff --git a/doc/source/release/1.16.0-notes.rst b/doc/source/release/1.16.0-notes.rst index 1034d6e6c..e78e270f4 100644 --- a/doc/source/release/1.16.0-notes.rst +++ b/doc/source/release/1.16.0-notes.rst @@ -506,7 +506,7 @@ become more conspicuous. Now no warnings will be emitted. Umath and multiarray c-extension modules merged into a single module -------------------------------------------------------------------- The two modules were merged, according to `NEP 15`_. Previously `np.core.umath` -and `np.core.multiarray` were seperate c-extension modules. They are now python +and `np.core.multiarray` were separate c-extension modules. They are now python wrappers to the single `np.core/_multiarray_math` c-extension module. .. _`NEP 15` : http://www.numpy.org/neps/nep-0015-merge-multiarray-umath.html diff --git a/doc/source/release/1.16.1-notes.rst b/doc/source/release/1.16.1-notes.rst index 2a190ef91..d6fc25b44 100644 --- a/doc/source/release/1.16.1-notes.rst +++ b/doc/source/release/1.16.1-notes.rst @@ -58,7 +58,7 @@ Enhancements Compatibility notes =================== -* The changed error message emited by array comparison testing functions may +* The changed error message emitted by array comparison testing functions may affect doctests. See below for detail. * Casting from double and single denormals to float16 has been corrected. In diff --git a/doc/source/release/1.18.0-notes.rst b/doc/source/release/1.18.0-notes.rst index e66540410..0cea811fb 100644 --- a/doc/source/release/1.18.0-notes.rst +++ b/doc/source/release/1.18.0-notes.rst @@ -1,8 +1,353 @@ -The NumPy 1.18 release is currently in developement. Please check -the ``numpy/doc/release/upcoming_changes/`` folder for upcoming -release notes. -The ``numpy/doc/release/upcoming_changes/README.txt`` details how -to add new release notes. - -For the work in progress release notes for the current development -version, see the `devdocs <https://numpy.org/devdocs/release.html>`__. +================================ +NumPy NumPy 1.18.0 Release Notes +================================ + + +New functions +============= + +Multivariate hypergeometric distribution added to `numpy.random` +---------------------------------------------------------------- +The method `multivariate_hypergeometric` has been added to the class +`numpy.random.Generator`. This method generates random variates from +the multivariate hypergeometric probability distribution. +(`gh-13794 <https://github.com/numpy/numpy/pull/13794>`__) + + +Deprecations +============ + +`np.fromfile` and `np.fromstring` will error on bad data +-------------------------------------------------------- + +In future numpy releases, the functions `np.fromfile` and `np.fromstring` +will throw an error when parsing bad data. +This will now give a ``DeprecationWarning`` where previously partial or +even invalid data was silently returned. This deprecation also affects +the C defined functions c:func:`PyArray_FromString`` and +c:func:`PyArray_FromFile` +(`gh-13605 <https://github.com/numpy/numpy/pull/13605>`__) + +Deprecate non-scalar arrays as fill values in ``ma.fill_value`` +--------------------------------------------------------------- +Setting a ``MaskedArray.fill_value`` to a non-scalar array is deprecated +since the logic to broadcast the fill value to the array is fragile, +especially when slicing. +(`gh-13698 <https://github.com/numpy/numpy/pull/13698>`__) + +Deprecate `PyArray_As1D`, `PyArray_As2D` +---------------------------------------- +`PyArray_As1D`, `PyArray_As2D` are deprecated, use +`PyArray_AsCArray` instead +(`gh-14036 <https://github.com/numpy/numpy/pull/14036>`__) + +Deprecate `np.alen` +------------------- +`np.alen` was deprecated. Use `len` instead. +(`gh-14181 <https://github.com/numpy/numpy/pull/14181>`__) + +Deprecate the financial functions +--------------------------------- +In accordance with +`NEP-32 <https://numpy.org/neps/nep-0032-remove-financial-functions.html>`_, +the functions `fv`, `ipmt`, `irr`, `mirr`, `nper`, `npv`, `pmt`, `ppmt`, +`pv` and `rate` are deprecated, and will be removed from NumPy 1.20. +The replacement for these functions is the Python package +`numpy-financial <https://pypi.org/project/numpy-financial>`_. +(`gh-14720 <https://github.com/numpy/numpy/pull/14720>`__) + +The ``axis`` argument to `numpy.ma.mask_cols` and `numpy.ma.mask_row` is deprecated +----------------------------------------------------------------------------------- +This argument was always ignored. +(`gh-14996 <https://github.com/numpy/numpy/pull/14996>`__) + + +Expired deprecations +==================== + +* ``PyArray_As1D`` and ``PyArray_As2D`` have been removed in favor of + ``PyArray_AsCArray`` + (`gh-14036 <https://github.com/numpy/numpy/pull/14036>`__) + +* ``np.rank`` has been removed. This was deprecated in NumPy 1.10 + and has been replaced by ``np.ndim``. + (`gh-14039 <https://github.com/numpy/numpy/pull/14039>`__) + +* The deprecation of ``expand_dims`` out-of-range axes in 1.13.0 has + expired. + (`gh-14051 <https://github.com/numpy/numpy/pull/14051>`__) + +* ``PyArray_FromDimsAndDataAndDescr`` and ``PyArray_FromDims`` have been + removed (they will always raise an error). Use ``PyArray_NewFromDescr`` + and ``PyArray_SimpleNew`` instead. + (`gh-14100 <https://github.com/numpy/numpy/pull/14100>`__) + +* ``numeric.loads``, ``numeric.load``, ``np.ma.dump``, + ``np.ma.dumps``, ``np.ma.load``, ``np.ma.loads`` are removed, + use ``pickle`` methods instead + (`gh-14256 <https://github.com/numpy/numpy/pull/14256>`__) + +* ``arrayprint.FloatFormat``, ``arrayprint.LongFloatFormat`` has been removed, + use ``FloatingFormat`` instead +* ``arrayprint.ComplexFormat``, ``arrayprint.LongComplexFormat`` has been + removed, use ``ComplexFloatingFormat`` instead +* ``arrayprint.StructureFormat`` has been removed, use ``StructureVoidFormat`` + instead + (`gh-14259 <https://github.com/numpy/numpy/pull/14259>`__) + +* ``np.testing.rand`` has been removed. This was deprecated in NumPy 1.11 + and has been replaced by ``np.random.rand``. + (`gh-14325 <https://github.com/numpy/numpy/pull/14325>`__) + +* Class ``SafeEval`` in ``numpy/lib/utils.py`` has been removed. This was deprecated in NumPy 1.10. + Use ``np.safe_eval`` instead. + (`gh-14335 <https://github.com/numpy/numpy/pull/14335>`__) + +* Remove deprecated support for boolean and empty condition lists in + `numpy.select` + (`gh-14583 <https://github.com/numpy/numpy/pull/14583>`__) + +* Array order only accepts 'C', 'F', 'A', and 'K'. More permissive options + were deprecated in NumPy 1.11. + (`gh-14596 <https://github.com/numpy/numpy/pull/14596>`__) + +* np.linspace param num must be an integer. This was deprecated in NumPy 1.12. + (`gh-14620 <https://github.com/numpy/numpy/pull/14620>`__) + +* UFuncs with multiple outputs must use a tuple for the `out` kwarg. This + finishes a deprecation started in NumPy 1.10. + (`gh-14682 <https://github.com/numpy/numpy/pull/14682>`__) + +The files ``numpy/testing/decorators.py``, ``numpy/testing/noseclasses.py`` +and ``numpy/testing/nosetester.py`` have been removed. They were never +meant to be public (all relevant objects are present in the +``numpy.testing`` namespace), and importing them has given a deprecation +warning since NumPy 1.15.0 +(`gh-14567 <https://github.com/numpy/numpy/pull/14567>`__) + + +Compatibility notes +=================== + +`numpy.lib.recfunctions.drop_fields` can no longer return None +-------------------------------------------------------------- +If ``drop_fields`` is used to drop all fields, previously the array would +be completely discarded and None returned. Now it returns an array of the +same shape as the input, but with no fields. The old behavior can be retained +with:: + + dropped_arr = drop_fields(arr, ['a', 'b']) + if dropped_arr.dtype.names == (): + dropped_arr = None + +converting the empty recarray to None +(`gh-14510 <https://github.com/numpy/numpy/pull/14510>`__) + +``numpy.argmin/argmax/min/max`` returns ``NaT`` if it exists in array +--------------------------------------------------------------------- +``numpy.argmin``, ``numpy.argmax``, ``numpy.min``, and ``numpy.max`` will return +``NaT`` if it exists in the array. +(`gh-14717 <https://github.com/numpy/numpy/pull/14717>`__) + +``np.can_cast(np.uint64, np.timedelta64, casting='safe')`` is now ``False`` +--------------------------------------------------------------------------- + +Previously this was ``True`` - however, this was inconsistent with ``uint64`` +not being safely castable to ``int64``, and resulting in strange type +resolution. + +If this impacts your code, cast ``uint64`` to ``int64`` first. +(`gh-14718 <https://github.com/numpy/numpy/pull/14718>`__) + +Changed random variate stream from `numpy.random.Generator.integers` +-------------------------------------------------------------------- +There was a bug in `numpy.random.Generator.integers` that caused biased +sampling of 8 and 16 bit integer types. Fixing that bug has changed the +output stream from what it was in previous releases. +(`gh-14777 <https://github.com/numpy/numpy/pull/14777>`__) + +Add more ufunc loops for ``datetime64``, ``timedelta64`` +-------------------------------------------------------- +``np.datetime('NaT')`` should behave more like ``float('Nan')``. Add needed +infrastructure so ``np.isinf(a)`` and ``np.isnan(a)`` will run on +``datetime64`` and ``timedelta64`` dtypes. Also added specific loops for +`numpy.fmin` and `numpy.fmax` that mask ``NaT``. This may require adjustment to user- +facing code. Specifically, code that either disallowed the calls to +`numpy.isinf` or `numpy.isnan` or checked that they raised an exception will +require adaptation, and code that mistakenly called `numpy.fmax` and +`numpy.fmin` instead of `numpy.maximum` or `numpy.minimum` respectively will +requre adjustment. This also affects `numpy.nanmax` and `numpy.nanmin`. +(`gh-14841 <https://github.com/numpy/numpy/pull/14841>`__) + + +C API changes +============= + +PyDataType_ISUNSIZED(descr) now returns False for structured datatypes +---------------------------------------------------------------------- +Previously this returned True for any datatype of itemsize 0, but now this +returns false for the non-flexible datatype with itemsize 0, ``np.dtype([])``. +(`gh-14393 <https://github.com/numpy/numpy/pull/14393>`__) + + +New Features +============ + + +Add our own ``*.pxd`` cython import file +-------------------------------------------- +Added a ``numpy/__init__.pxd`` file. It will be used for `cimport numpy` +(`gh-12284 <https://github.com/numpy/numpy/pull/12284>`__) + +A tuple of axes can now be input to ``expand_dims`` +--------------------------------------------------- +The `numpy.expand_dims` ``axis`` keyword can now accept a tuple of +axes. Previously, ``axis`` was required to be an integer. +(`gh-14051 <https://github.com/numpy/numpy/pull/14051>`__) + +Support for 64-bit OpenBLAS with symbol suffix +---------------------------------------------- +Added support for 64-bit (ILP64) OpenBLAS compiled with +``make INTERFACE64=1 SYMBOLSUFFIX=64_``. See ``site.cfg.example`` +for details. + +Improvements +============ + +Different C numeric types of the same size have unique names +------------------------------------------------------------ +On any given platform, two of ``np.intc``, ``np.int_``, and ``np.longlong`` +would previously appear indistinguishable through their ``repr``, despite +their corresponding ``dtype`` having different properties. +A similar problem existed for the unsigned counterparts to these types, and on +some platforms for ``np.double`` and ``np.longdouble`` + +These types now always print with a unique ``__name__``. +(`gh-10151 <https://github.com/numpy/numpy/pull/10151>`__) + +``argwhere`` now produces a consistent result on 0d arrays +---------------------------------------------------------- +On N-d arrays, `numpy.argwhere` now always produces an array of shape +``(n_non_zero, arr.ndim)``, even when ``arr.ndim == 0``. Previously, the +last axis would have a dimension of 1 in this case. +(`gh-13610 <https://github.com/numpy/numpy/pull/13610>`__) + +Add ``axis`` argument for ``random.permutation`` and ``random.shuffle`` +----------------------------------------------------------------------- + +Previously the ``random.permutation`` and ``random.shuffle`` functions +can only shuffle an array along the first axis; they now have a +new argument ``axis`` which allows shuffle along a specified axis. +(`gh-13829 <https://github.com/numpy/numpy/pull/13829>`__) + +``method`` keyword argument for `np.random.multivariate_normal` +--------------------------------------------------------------- +A ``method`` keyword argument is now available for +`np.random.multivariate_normal` with possible values +``{'svd', 'eigh', 'cholesky'}``. To use it, write +``np.random.multivariate_normal(..., method=<method>)``. +(`gh-14197 <https://github.com/numpy/numpy/pull/14197>`__) + +Add complex number support for ``numpy.fromstring`` +--------------------------------------------------- +Now ``numpy.fromstring`` can read complex numbers. +(`gh-14227 <https://github.com/numpy/numpy/pull/14227>`__) + +`numpy.unique` has consistent axes order (except the chosen one) when ``axis`` is not None +------------------------------------------------------------------------------------------ +Using ``moveaxis`` instead of ``swapaxes`` in `numpy.unique`, so that the ordering of axes +except the axis in arguments will not be broken. +(`gh-14255 <https://github.com/numpy/numpy/pull/14255>`__) + +`numpy.matmul` with boolean output now converts to boolean values +----------------------------------------------------------------- +Calling `numpy.matmul` where the output is a boolean array would fill the array +with uint8 equivalents of the result, rather than 0/1. Now it forces the output +to 0 or 1 (``NPY_TRUE`` or ``NPY_FALSE``). +(`gh-14464 <https://github.com/numpy/numpy/pull/14464>`__) + +`numpy.random.randint` produced incorrect value when the range was ``2**32`` +---------------------------------------------------------------------------- +The implementation introduced in 1.17.0 had an incorrect check when +determining whether to use the 32-bit path or the full 64-bit +path that incorrectly redirected random integer generation with a high - low +range of ``2**32`` to the 64-bit generator. +(`gh-14501 <https://github.com/numpy/numpy/pull/14501>`__) + +Add complex number support for ``numpy.fromfile`` +------------------------------------------------- +Now ``numpy.fromfile`` can read complex numbers. +(`gh-14730 <https://github.com/numpy/numpy/pull/14730>`__) + +``std=c99`` added if compiler is named ``gcc`` +---------------------------------------------- +GCC before version 5 requires the ``-std=c99`` command line argument. Newer +compilers automatically turn on C99 mode. The compiler setup code will +automatically add the code if the compiler name has ``gcc`` in it. +(`gh-14771 <https://github.com/numpy/numpy/pull/14771>`__) + + +Changes +======= + +``NaT`` now sorts to the end of arrays +-------------------------------------- +``NaT`` is now effectively treated as the largest integer for sorting +purposes, so that it sorts to the end of arrays. This change is for consistency +with ``NaN`` sorting behavior. +(`gh-12658 <https://github.com/numpy/numpy/pull/12658>`__) + +Incorrect ``threshold`` in ``np.set_printoptions`` raises ``TypeError`` or ``ValueError`` +----------------------------------------------------------------------------------------- +Previously an incorrect ``threshold`` raised ``ValueError``; it now raises ``TypeError`` +for non-numeric types and ``ValueError`` for ``nan`` values. +(`gh-13899 <https://github.com/numpy/numpy/pull/13899>`__) + +Warn when saving a dtype with metadata +-------------------------------------- +A ``UserWarning`` will be emitted when saving an array via `numpy.save` with +``metadata``. Saving such an array may not preserve metadata, and if metadata +is preserved, loading it will cause a ``ValueError``. This shortcoming in save +and load will be addressed in a future release. +(`gh-14142 <https://github.com/numpy/numpy/pull/14142>`__) + +`numpy.distutils`: append behavior changed for LDFLAGS and similar +------------------------------------------------------------------ +`numpy.distutils` has always overridden rather than appended to ``LDFLAGS`` and +other similar such environment variables for compiling Fortran extensions. Now +the default behavior has changed to appending - which is the expected behavior +in most situations. To preserve the old (overwriting) behavior, set the +``NPY_DISTUTILS_APPEND_FLAGS`` environment variable to 0. This applies to: +``LDFLAGS``, ``F77FLAGS``, ``F90FLAGS``, ``FREEFLAGS``, ``FOPT``, ``FDEBUG``, +and ``FFLAGS``. NumPy 1.16 and 1.17 gave build warnings in situations where this +change in behavior would have affected the compile flags used. +(`gh-14248 <https://github.com/numpy/numpy/pull/14248>`__) + +Remove ``numpy.random.entropy`` without a deprecation +----------------------------------------------------- + +``numpy.random.entropy`` was added to the `numpy.random` namespace in 1.17.0. +It was meant to be a private c-extension module, but was exposed as public. +It has been replaced by `numpy.random.SeedSequence` so the module was +completely removed. +(`gh-14498 <https://github.com/numpy/numpy/pull/14498>`__) + +Add options to quiet build configuration and build with ``-Werror`` +------------------------------------------------------------------- +Added two new configuration options. During the ``build_src`` subcommand, as +part of configuring NumPy, the files ``_numpyconfig.h`` and ``config.h`` are +created by probing support for various runtime functions and routines. +Previously, the very verbose compiler output during this stage clouded more +important information. By default the output is silenced. Running ``runtests.py +--debug-info`` will add ``--verbose-cfg`` to the ``build_src`` subcommand, +which will restore the previous behaviour. + +Adding ``CFLAGS=-Werror`` to turn warnings into errors would trigger errors +during the configuration. Now ``runtests.py --warn-error`` will add +``--warn-error`` to the ``build`` subcommand, which will percolate to the +``build_ext`` and ``build_lib`` subcommands. This will add the compiler flag +to those stages and turn compiler warnings into errors while actually building +NumPy itself, avoiding the ``build_src`` subcommand compiler calls. + +(`gh-14527 <https://github.com/numpy/numpy/pull/14527>`__) +(`gh-14518 <https://github.com/numpy/numpy/pull/14518>`__) diff --git a/doc/source/user/basics.io.genfromtxt.rst b/doc/source/user/basics.io.genfromtxt.rst index 19e37eabc..3fce6a8aa 100644 --- a/doc/source/user/basics.io.genfromtxt.rst +++ b/doc/source/user/basics.io.genfromtxt.rst @@ -98,13 +98,11 @@ This behavior can be overwritten by setting the optional argument >>> # Without autostrip >>> np.genfromtxt(StringIO(data), delimiter=",", dtype="|U5") array([['1', ' abc ', ' 2'], - ['3', ' xxx', ' 4']], - dtype='|U5') + ['3', ' xxx', ' 4']], dtype='<U5') >>> # With autostrip >>> np.genfromtxt(StringIO(data), delimiter=",", dtype="|U5", autostrip=True) array([['1', 'abc', '2'], - ['3', 'xxx', '4']], - dtype='|U5') + ['3', 'xxx', '4']], dtype='<U5') The ``comments`` argument @@ -127,11 +125,11 @@ marker(s) is simply ignored:: ... 9, 0 ... """ >>> np.genfromtxt(StringIO(data), comments="#", delimiter=",") - [[ 1. 2.] - [ 3. 4.] - [ 5. 6.] - [ 7. 8.] - [ 9. 0.]] + array([[1., 2.], + [3., 4.], + [5., 6.], + [7., 8.], + [9., 0.]]) .. versionadded:: 1.7.0 @@ -376,12 +374,12 @@ single element of the wanted type. In the following example, the second column is converted from as string representing a percentage to a float between 0 and 1:: - >>> convertfunc = lambda x: float(x.strip("%"))/100. + >>> convertfunc = lambda x: float(x.strip(b"%"))/100. >>> data = u"1, 2.3%, 45.\n6, 78.9%, 0" >>> names = ("i", "p", "n") >>> # General case ..... >>> np.genfromtxt(StringIO(data), delimiter=",", names=names) - array([(1.0, nan, 45.0), (6.0, nan, 0.0)], + array([(1., nan, 45.), (6., nan, 0.)], dtype=[('i', '<f8'), ('p', '<f8'), ('n', '<f8')]) We need to keep in mind that by default, ``dtype=float``. A float is diff --git a/doc/source/user/building.rst b/doc/source/user/building.rst index b4b4371e5..8e2b5c03b 100644 --- a/doc/source/user/building.rst +++ b/doc/source/user/building.rst @@ -195,6 +195,25 @@ or:: BLAS=None LAPACK=None ATLAS=None python setup.py build +64-bit BLAS and LAPACK with symbol suffix +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Numpy also supports 64-bit OpenBLAS with ``64_`` symbol suffix. Such +library is obtained by compiling OpenBLAS with settings:: + + make INTERFACE64=1 SYMBOLSUFFIX=64_ + +To make Numpy use it, set ``NPY_USE_BLAS64_=1`` environment variable +when building Numpy. You may also need to configure the +``[openblas64_]`` section in ``site.cfg``. + +The symbol suffix avoids symbol name clashes between 32-bit and 64-bit +BLAS/LAPACK libraries, meaning that you can link to both in the same +program. This avoids potential issues when using 64-bit BLAS/LAPACK in +Numpy while simultaneously using other Python software that uses the +32-bit versions. + + Supplying additional compiler flags ----------------------------------- diff --git a/numpy/compat/py3k.py b/numpy/compat/py3k.py index c9ed9d52c..90e17d6d6 100644 --- a/numpy/compat/py3k.py +++ b/numpy/compat/py3k.py @@ -1,9 +1,15 @@ """ -Python 3 compatibility tools. +Python 3.X compatibility tools. -""" -from __future__ import division, absolute_import, print_function +While this file was originally intented for Python 2 -> 3 transition, +it is now used to create a compatibility layer between different +minor versions of Python 3. +While the active version of numpy may not support a given version of python, we +allow downstream libraries to continue to use these shims for forward +compatibility with numpy while they transition their code to newer versions of +Python. +""" __all__ = ['bytes', 'asbytes', 'isfileobj', 'getexception', 'strchar', 'unicode', 'asunicode', 'asbytes_nested', 'asunicode_nested', 'asstr', 'open_latin1', 'long', 'basestring', 'sixu', diff --git a/numpy/conftest.py b/numpy/conftest.py index 18d5d1ce9..1baf4adda 100644 --- a/numpy/conftest.py +++ b/numpy/conftest.py @@ -3,6 +3,8 @@ Pytest configuration and fixtures for the Numpy test suite. """ from __future__ import division, absolute_import, print_function +import os + import pytest import numpy @@ -22,6 +24,22 @@ def pytest_configure(config): "slow: Tests that are very slow.") +def pytest_addoption(parser): + parser.addoption("--available-memory", action="store", default=None, + help=("Set amount of memory available for running the " + "test suite. This can result to tests requiring " + "especially large amounts of memory to be skipped. " + "Equivalent to setting environment variable " + "NPY_AVAILABLE_MEM. Default: determined" + "automatically.")) + + +def pytest_sessionstart(session): + available_mem = session.config.getoption('available_memory') + if available_mem is not None: + os.environ['NPY_AVAILABLE_MEM'] = available_mem + + #FIXME when yield tests are gone. @pytest.hookimpl() def pytest_itemcollected(item): diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index 0225d12b9..2f1273904 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -3953,15 +3953,22 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('tolist', Examples -------- - For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``: + For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``, + except that ``tolist`` changes numpy scalars to Python scalars: - >>> a = np.array([1, 2]) - >>> list(a) + >>> a = np.uint32([1, 2]) + >>> a_list = list(a) + >>> a_list [1, 2] - >>> a.tolist() + >>> type(a_list[0]) + <class 'numpy.uint32'> + >>> a_tolist = a.tolist() + >>> a_tolist [1, 2] + >>> type(a_tolist[0]) + <class 'int'> - However, for a 2D array, ``tolist`` applies recursively: + Additionally, for a 2D array, ``tolist`` applies recursively: >>> a = np.array([[1, 2], [3, 4]]) >>> list(a) @@ -4246,7 +4253,7 @@ add_newdoc('numpy.core.umath', 'frompyfunc', See Also -------- - vectorize : evaluates pyfunc over input arrays using broadcasting rules of numpy + vectorize : Evaluates pyfunc over input arrays using broadcasting rules of numpy. Notes ----- diff --git a/numpy/core/code_generators/cversions.txt b/numpy/core/code_generators/cversions.txt index 00f10df57..5daa52d79 100644 --- a/numpy/core/code_generators/cversions.txt +++ b/numpy/core/code_generators/cversions.txt @@ -47,4 +47,7 @@ # Deprecate PyArray_SetNumericOps and PyArray_GetNumericOps, # Add fields core_dim_flags and core_dim_sizes to PyUFuncObject. # Add PyUFunc_FromFuncAndDataAndSignatureAndIdentity to ufunc_funcs_api. +# Version 13 (NumPy 1.17) No change. +# Version 13 (NumPy 1.18) No change. +# Version 13 (NumPy 1.19) No change. 0x0000000d = 5b0e8bbded00b166125974fc71e80a33 diff --git a/numpy/core/code_generators/generate_umath.py b/numpy/core/code_generators/generate_umath.py index 9e67a45ef..6d76f7ca2 100644 --- a/numpy/core/code_generators/generate_umath.py +++ b/numpy/core/code_generators/generate_umath.py @@ -858,8 +858,8 @@ defdict = { 'isnan': Ufunc(1, 1, None, docstrings.get('numpy.core.umath.isnan'), - None, - TD(nodatetime_or_obj, out='?'), + 'PyUFunc_IsFiniteTypeResolver', + TD(noobj, out='?'), ), 'isnat': Ufunc(1, 1, None, @@ -870,8 +870,8 @@ defdict = { 'isinf': Ufunc(1, 1, None, docstrings.get('numpy.core.umath.isinf'), - None, - TD(nodatetime_or_obj, out='?'), + 'PyUFunc_IsFiniteTypeResolver', + TD(noobj, out='?'), ), 'isfinite': Ufunc(1, 1, None, diff --git a/numpy/core/code_generators/ufunc_docstrings.py b/numpy/core/code_generators/ufunc_docstrings.py index 4dec73505..9560eb31b 100644 --- a/numpy/core/code_generators/ufunc_docstrings.py +++ b/numpy/core/code_generators/ufunc_docstrings.py @@ -37,8 +37,8 @@ subst = { :ref:`ufunc docs <ufuncs.kwargs>`. """).strip(), 'BROADCASTABLE_2': ("If ``x1.shape != x2.shape``, they must be " - "broadcastable to a common shape (which becomes the " - "shape of the output)."), + "broadcastable to a common\n shape (which becomes " + "the shape of the output)."), 'OUT_SCALAR_1': "This is a scalar if `x` is a scalar.", 'OUT_SCALAR_2': "This is a scalar if both `x1` and `x2` are scalars.", } @@ -117,7 +117,8 @@ add_newdoc('numpy.core.umath', 'add', Parameters ---------- x1, x2 : array_like - The arrays to be added. $BROADCASTABLE_2 + The arrays to be added. + $BROADCASTABLE_2 $PARAMS Returns @@ -443,7 +444,8 @@ add_newdoc('numpy.core.umath', 'arctan2', x1 : array_like, real-valued `y`-coordinates. x2 : array_like, real-valued - `x`-coordinates. $BROADCASTABLE_2 + `x`-coordinates. + $BROADCASTABLE_2 $PARAMS Returns @@ -566,7 +568,8 @@ add_newdoc('numpy.core.umath', 'bitwise_and', Parameters ---------- x1, x2 : array_like - Only integer and boolean types are handled. $BROADCASTABLE_2 + Only integer and boolean types are handled. + $BROADCASTABLE_2 $PARAMS Returns @@ -619,7 +622,8 @@ add_newdoc('numpy.core.umath', 'bitwise_or', Parameters ---------- x1, x2 : array_like - Only integer and boolean types are handled. $BROADCASTABLE_2 + Only integer and boolean types are handled. + $BROADCASTABLE_2 $PARAMS Returns @@ -677,7 +681,8 @@ add_newdoc('numpy.core.umath', 'bitwise_xor', Parameters ---------- x1, x2 : array_like - Only integer and boolean types are handled. $BROADCASTABLE_2 + Only integer and boolean types are handled. + $BROADCASTABLE_2 $PARAMS Returns @@ -987,7 +992,8 @@ add_newdoc('numpy.core.umath', 'heaviside', x1 : array_like Input values. x2 : array_like - The value of the function when x1 is 0. $BROADCASTABLE_2 + The value of the function when x1 is 0. + $BROADCASTABLE_2 $PARAMS Returns @@ -1022,7 +1028,8 @@ add_newdoc('numpy.core.umath', 'divide', x1 : array_like Dividend array. x2 : array_like - Divisor array. $BROADCASTABLE_2 + Divisor array. + $BROADCASTABLE_2 $PARAMS Returns @@ -1091,7 +1098,8 @@ add_newdoc('numpy.core.umath', 'equal', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -1223,7 +1231,7 @@ add_newdoc('numpy.core.umath', 'expm1', Parameters ---------- x : array_like - Input values. + Input values. $PARAMS Returns @@ -1338,7 +1346,8 @@ add_newdoc('numpy.core.umath', 'floor_divide', x1 : array_like Numerator. x2 : array_like - Denominator. $BROADCASTABLE_2 + Denominator. + $BROADCASTABLE_2 $PARAMS Returns @@ -1378,7 +1387,8 @@ add_newdoc('numpy.core.umath', 'fmod', x1 : array_like Dividend. x2 : array_like - Divisor. $BROADCASTABLE_2 + Divisor. + $BROADCASTABLE_2 $PARAMS Returns @@ -1428,7 +1438,8 @@ add_newdoc('numpy.core.umath', 'greater', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -1464,7 +1475,8 @@ add_newdoc('numpy.core.umath', 'greater_equal', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -1497,7 +1509,8 @@ add_newdoc('numpy.core.umath', 'hypot', Parameters ---------- x1, x2 : array_like - Leg of the triangle(s). $BROADCASTABLE_2 + Leg of the triangle(s). + $BROADCASTABLE_2 $PARAMS Returns @@ -1832,7 +1845,8 @@ add_newdoc('numpy.core.umath', 'less', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -1860,7 +1874,8 @@ add_newdoc('numpy.core.umath', 'less_equal', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -2044,7 +2059,8 @@ add_newdoc('numpy.core.umath', 'logaddexp', Parameters ---------- x1, x2 : array_like - Input values. $BROADCASTABLE_2 + Input values. + $BROADCASTABLE_2 $PARAMS Returns @@ -2086,7 +2102,8 @@ add_newdoc('numpy.core.umath', 'logaddexp2', Parameters ---------- x1, x2 : array_like - Input values. $BROADCASTABLE_2 + Input values. + $BROADCASTABLE_2 $PARAMS Returns @@ -2177,7 +2194,8 @@ add_newdoc('numpy.core.umath', 'logical_and', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -2282,7 +2300,8 @@ add_newdoc('numpy.core.umath', 'logical_xor', Parameters ---------- x1, x2 : array_like - Logical XOR is applied to the elements of `x1` and `x2`. $BROADCASTABLE_2 + Logical XOR is applied to the elements of `x1` and `x2`. + $BROADCASTABLE_2 $PARAMS Returns @@ -2329,7 +2348,8 @@ add_newdoc('numpy.core.umath', 'maximum', Parameters ---------- x1, x2 : array_like - The arrays holding the elements to be compared. $BROADCASTABLE_2 + The arrays holding the elements to be compared. + $BROADCASTABLE_2 $PARAMS Returns @@ -2387,7 +2407,8 @@ add_newdoc('numpy.core.umath', 'minimum', Parameters ---------- x1, x2 : array_like - The arrays holding the elements to be compared. $BROADCASTABLE_2 + The arrays holding the elements to be compared. + $BROADCASTABLE_2 $PARAMS Returns @@ -2445,7 +2466,8 @@ add_newdoc('numpy.core.umath', 'fmax', Parameters ---------- x1, x2 : array_like - The arrays holding the elements to be compared. $BROADCASTABLE_2 + The arrays holding the elements to be compared. + $BROADCASTABLE_2 $PARAMS Returns @@ -2502,7 +2524,8 @@ add_newdoc('numpy.core.umath', 'fmin', Parameters ---------- x1, x2 : array_like - The arrays holding the elements to be compared. $BROADCASTABLE_2 + The arrays holding the elements to be compared. + $BROADCASTABLE_2 $PARAMS Returns @@ -2755,7 +2778,8 @@ add_newdoc('numpy.core.umath', 'multiply', Parameters ---------- x1, x2 : array_like - Input arrays to be multiplied. $BROADCASTABLE_2 + Input arrays to be multiplied. + $BROADCASTABLE_2 $PARAMS Returns @@ -2836,7 +2860,8 @@ add_newdoc('numpy.core.umath', 'not_equal', Parameters ---------- x1, x2 : array_like - Input arrays. $BROADCASTABLE_2 + Input arrays. + $BROADCASTABLE_2 $PARAMS Returns @@ -2885,7 +2910,8 @@ add_newdoc('numpy.core.umath', 'power', x1 : array_like The bases. x2 : array_like - The exponents. $BROADCASTABLE_2 + The exponents. + $BROADCASTABLE_2 $PARAMS Returns @@ -2944,7 +2970,8 @@ add_newdoc('numpy.core.umath', 'float_power', x1 : array_like The bases. x2 : array_like - The exponents. $BROADCASTABLE_2 + The exponents. + $BROADCASTABLE_2 $PARAMS Returns @@ -3116,7 +3143,8 @@ add_newdoc('numpy.core.umath', 'remainder', x1 : array_like Dividend array. x2 : array_like - Divisor array. $BROADCASTABLE_2 + Divisor array. + $BROADCASTABLE_2 $PARAMS Returns @@ -3162,7 +3190,8 @@ add_newdoc('numpy.core.umath', 'divmod', x1 : array_like Dividend array. x2 : array_like - Divisor array. $BROADCASTABLE_2 + Divisor array. + $BROADCASTABLE_2 $PARAMS Returns @@ -3201,7 +3230,8 @@ add_newdoc('numpy.core.umath', 'right_shift', x1 : array_like, int Input values. x2 : array_like, int - Number of bits to remove at the right of `x1`. $BROADCASTABLE_2 + Number of bits to remove at the right of `x1`. + $BROADCASTABLE_2 $PARAMS Returns @@ -3335,7 +3365,8 @@ add_newdoc('numpy.core.umath', 'copysign', x1 : array_like Values to change the sign of. x2 : array_like - The sign of `x2` is copied to `x1`. $BROADCASTABLE_2 + The sign of `x2` is copied to `x1`. + $BROADCASTABLE_2 $PARAMS Returns @@ -3642,7 +3673,8 @@ add_newdoc('numpy.core.umath', 'subtract', Parameters ---------- x1, x2 : array_like - The arrays to be subtracted from each other. $BROADCASTABLE_2 + The arrays to be subtracted from each other. + $BROADCASTABLE_2 $PARAMS Returns @@ -3783,7 +3815,8 @@ add_newdoc('numpy.core.umath', 'true_divide', x1 : array_like Dividend array. x2 : array_like - Divisor array. $BROADCASTABLE_2 + Divisor array. + $BROADCASTABLE_2 $PARAMS Returns @@ -3880,7 +3913,8 @@ add_newdoc('numpy.core.umath', 'ldexp', x1 : array_like Array of multipliers. x2 : array_like, int - Array of twos exponents. $BROADCASTABLE_2 + Array of twos exponents. + $BROADCASTABLE_2 $PARAMS Returns @@ -3918,7 +3952,8 @@ add_newdoc('numpy.core.umath', 'gcd', Parameters ---------- x1, x2 : array_like, int - Arrays of values. $BROADCASTABLE_2 + Arrays of values. + $BROADCASTABLE_2 Returns ------- @@ -3948,7 +3983,8 @@ add_newdoc('numpy.core.umath', 'lcm', Parameters ---------- x1, x2 : array_like, int - Arrays of values. $BROADCASTABLE_2 + Arrays of values. + $BROADCASTABLE_2 Returns ------- diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 6e5f3dabf..f09f2a465 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -604,15 +604,20 @@ def _transpose_dispatcher(a, axes=None): @array_function_dispatch(_transpose_dispatcher) def transpose(a, axes=None): """ - Permute the dimensions of an array. + Reverse or permute the axes of an array; returns the modified array. + + For an array a with two axes, transpose(a) gives the matrix transpose. Parameters ---------- a : array_like Input array. - axes : list of ints, optional - By default, reverse the dimensions, otherwise permute the axes - according to the values given. + axes : tuple or list of ints, optional + If specified, it must be a tuple or list which contains a permutation of + [0,1,..,N-1] where N is the number of axes of a. The i'th axis of the + returned array will correspond to the axis numbered ``axes[i]`` of the + input. If not specified, defaults to ``range(a.ndim)[::-1]``, which + reverses the order of the axes. Returns ------- @@ -797,7 +802,7 @@ def argpartition(a, kth, axis=-1, kind='introselect', order=None): partition : Describes partition algorithms used. ndarray.partition : Inplace partition. argsort : Full indirect sort. - take_along_axis : Apply ``index_array`` from argpartition + take_along_axis : Apply ``index_array`` from argpartition to an array as if by calling partition. Notes @@ -944,6 +949,10 @@ def sort(a, axis=-1, kind=None, order=None): 'mergesort' and 'stable' are mapped to radix sort for integer data types. Radix sort is an O(n) sort instead of O(n log n). + .. versionchanged:: 1.18.0 + + NaT now sorts to the end of arrays for consistency with NaN. + Examples -------- >>> a = np.array([[1,4],[3,1]]) @@ -1035,7 +1044,7 @@ def argsort(a, axis=-1, kind=None, order=None): lexsort : Indirect stable sort with multiple keys. ndarray.sort : Inplace sort. argpartition : Indirect partial sort. - take_along_axis : Apply ``index_array`` from argsort + take_along_axis : Apply ``index_array`` from argsort to an array as if by calling sort. Notes @@ -1132,7 +1141,7 @@ def argmax(a, axis=None, out=None): ndarray.argmax, argmin amax : The maximum value along a given axis. unravel_index : Convert a flat index into an index tuple. - take_along_axis : Apply ``np.expand_dims(index_array, axis)`` + take_along_axis : Apply ``np.expand_dims(index_array, axis)`` from argmax to an array as if by calling max. Notes @@ -1213,7 +1222,7 @@ def argmin(a, axis=None, out=None): ndarray.argmin, argmax amin : The minimum value along a given axis. unravel_index : Convert a flat index into an index tuple. - take_along_axis : Apply ``np.expand_dims(index_array, axis)`` + take_along_axis : Apply ``np.expand_dims(index_array, axis)`` from argmin to an array as if by calling min. Notes diff --git a/numpy/core/function_base.py b/numpy/core/function_base.py index 42604ec3f..538ac8b84 100644 --- a/numpy/core/function_base.py +++ b/numpy/core/function_base.py @@ -139,7 +139,7 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, # from overriding what class is produced, and thus prevents, e.g. use of Quantities, # see gh-7142. Hence, we multiply in place only for standard scalar types. _mult_inplace = _nx.isscalar(delta) - if num > 1: + if div > 0: step = delta / div if _nx.any(step == 0): # Special handling for denormal numbers, gh-5437 @@ -154,7 +154,8 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None, else: y = y * step else: - # 0 and 1 item long sequences have an undefined step + # sequences with 0 items or 1 item with endpoint=True (i.e. div <= 0) + # have an undefined step step = NaN # Multiply with delta to allow possible override of output class. y = y * delta diff --git a/numpy/core/include/numpy/npy_3kcompat.h b/numpy/core/include/numpy/npy_3kcompat.h index 832bc0599..7ed263796 100644 --- a/numpy/core/include/numpy/npy_3kcompat.h +++ b/numpy/core/include/numpy/npy_3kcompat.h @@ -45,6 +45,7 @@ static NPY_INLINE int PyInt_Check(PyObject *op) { #define PyInt_AsLong PyLong_AsLong #define PyInt_AS_LONG PyLong_AsLong #define PyInt_AsSsize_t PyLong_AsSsize_t +#define PyNumber_Int PyNumber_Long /* NOTE: * diff --git a/numpy/core/include/numpy/numpyconfig.h b/numpy/core/include/numpy/numpyconfig.h index ab198f36b..4df4ea438 100644 --- a/numpy/core/include/numpy/numpyconfig.h +++ b/numpy/core/include/numpy/numpyconfig.h @@ -37,5 +37,9 @@ #define NPY_1_13_API_VERSION 0x00000008 #define NPY_1_14_API_VERSION 0x00000008 #define NPY_1_15_API_VERSION 0x00000008 +#define NPY_1_16_API_VERSION 0x00000008 +#define NPY_1_17_API_VERSION 0x00000008 +#define NPY_1_18_API_VERSION 0x00000008 +#define NPY_1_19_API_VERSION 0x00000008 #endif diff --git a/numpy/random/include/bitgen.h b/numpy/core/include/numpy/random/bitgen.h index 83c2858dd..83c2858dd 100644 --- a/numpy/random/include/bitgen.h +++ b/numpy/core/include/numpy/random/bitgen.h diff --git a/numpy/random/include/distributions.h b/numpy/core/include/numpy/random/distributions.h index c02ea605e..c474c4d14 100644 --- a/numpy/random/include/distributions.h +++ b/numpy/core/include/numpy/random/distributions.h @@ -8,7 +8,7 @@ #include <stdint.h> #include "numpy/npy_math.h" -#include "include/bitgen.h" +#include "numpy/random/bitgen.h" /* * RAND_INT_TYPE is used to share integer generators with RandomState which @@ -24,7 +24,7 @@ #define RAND_INT_MAX INT64_MAX #endif -#ifdef DLL_EXPORT +#ifdef _MSC_VER #define DECLDIR __declspec(dllexport) #else #define DECLDIR extern @@ -71,12 +71,10 @@ DECLDIR uint64_t random_uint(bitgen_t *bitgen_state); DECLDIR double random_standard_exponential(bitgen_t *bitgen_state); DECLDIR float random_standard_exponential_f(bitgen_t *bitgen_state); -DECLDIR double random_standard_exponential_zig(bitgen_t *bitgen_state); -DECLDIR float random_standard_exponential_zig_f(bitgen_t *bitgen_state); DECLDIR void random_standard_exponential_fill(bitgen_t *, npy_intp, double *); DECLDIR void random_standard_exponential_fill_f(bitgen_t *, npy_intp, float *); -DECLDIR void random_standard_exponential_zig_fill(bitgen_t *, npy_intp, double *); -DECLDIR void random_standard_exponential_zig_fill_f(bitgen_t *, npy_intp, float *); +DECLDIR void random_standard_exponential_inv_fill(bitgen_t *, npy_intp, double *); +DECLDIR void random_standard_exponential_inv_fill_f(bitgen_t *, npy_intp, float *); DECLDIR double random_standard_normal(bitgen_t *bitgen_state); DECLDIR float random_standard_normal_f(bitgen_t *bitgen_state); @@ -171,14 +169,14 @@ DECLDIR void random_multinomial(bitgen_t *bitgen_state, RAND_INT_TYPE n, RAND_IN double *pix, npy_intp d, binomial_t *binomial); /* multivariate hypergeometric, "count" method */ -DECLDIR int random_mvhg_count(bitgen_t *bitgen_state, +DECLDIR int random_multivariate_hypergeometric_count(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, size_t num_variates, int64_t *variates); /* multivariate hypergeometric, "marginals" method */ -DECLDIR void random_mvhg_marginals(bitgen_t *bitgen_state, +DECLDIR void random_multivariate_hypergeometric_marginals(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, diff --git a/numpy/core/records.py b/numpy/core/records.py index a1439f9df..a1cad9075 100644 --- a/numpy/core/records.py +++ b/numpy/core/records.py @@ -496,8 +496,7 @@ class recarray(ndarray): except Exception: fielddict = ndarray.__getattribute__(self, 'dtype').fields or {} if attr not in fielddict: - exctype, value = sys.exc_info()[:2] - raise exctype(value) + raise else: fielddict = ndarray.__getattribute__(self, 'dtype').fields or {} if attr not in fielddict: diff --git a/numpy/core/setup.py b/numpy/core/setup.py index a4b5cfe5f..5bbb1c622 100644 --- a/numpy/core/setup.py +++ b/numpy/core/setup.py @@ -91,6 +91,9 @@ def is_npy_no_smp(): # block. return 'NPY_NOSMP' in os.environ +def is_npy_use_blas64_(): + return (os.environ.get('NPY_USE_BLAS64_', "0") != "0") + def win32_checks(deflist): from numpy.distutils.misc_util import get_build_architecture a = get_build_architecture() @@ -394,7 +397,7 @@ def visibility_define(config): def configuration(parent_package='',top_path=None): from numpy.distutils.misc_util import Configuration, dot_join - from numpy.distutils.system_info import get_info + from numpy.distutils.system_info import get_info, dict_append config = Configuration('core', parent_package, top_path) local_dir = config.local_path @@ -753,8 +756,14 @@ def configuration(parent_package='',top_path=None): join('src', 'common', 'numpyos.c'), ] - blas_info = get_info('blas_opt', 0) - if blas_info and ('HAVE_CBLAS', None) in blas_info.get('define_macros', []): + if is_npy_use_blas64_(): + blas_info = get_info('blas64__opt', 2) + have_blas = blas_info and ('HAVE_CBLAS64_', None) in blas_info.get('define_macros', []) + else: + blas_info = get_info('blas_opt', 0) + have_blas = blas_info and ('HAVE_CBLAS', None) in blas_info.get('define_macros', []) + + if have_blas: extra_info = blas_info # These files are also in MANIFEST.in so that they are always in # the source distribution independently of HAVE_CBLAS. diff --git a/numpy/core/shape_base.py b/numpy/core/shape_base.py index 369d956fb..31b1c20b9 100644 --- a/numpy/core/shape_base.py +++ b/numpy/core/shape_base.py @@ -575,7 +575,7 @@ def _concatenate_shapes(shapes, axis): that was computed deeper in the recursion. These are returned as tuples to ensure that they can quickly be added - to existing slice tuple without creating a new tuple everytime. + to existing slice tuple without creating a new tuple every time. """ # Cache a result that will be reused. diff --git a/numpy/core/src/common/cblasfuncs.c b/numpy/core/src/common/cblasfuncs.c index 39572fed4..14d13a6c7 100644 --- a/numpy/core/src/common/cblasfuncs.c +++ b/numpy/core/src/common/cblasfuncs.c @@ -10,10 +10,20 @@ #include <assert.h> #include <numpy/arrayobject.h> #include "npy_cblas.h" +#include "npy_cblas64_.h" #include "arraytypes.h" #include "common.h" +/* + * If 64-bit CBLAS with symbol suffix '64_' is available, use it. + */ +#ifdef HAVE_CBLAS64_ +#define CBLAS_FUNC(name) name ## 64_ +#else +#define CBLAS_FUNC(name) name +#endif + static const double oneD[2] = {1.0, 0.0}, zeroD[2] = {0.0, 0.0}; static const float oneF[2] = {1.0, 0.0}, zeroF[2] = {0.0, 0.0}; @@ -24,28 +34,28 @@ static const float oneF[2] = {1.0, 0.0}, zeroF[2] = {0.0, 0.0}; static void gemm(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE transA, enum CBLAS_TRANSPOSE transB, - int m, int n, int k, - PyArrayObject *A, int lda, PyArrayObject *B, int ldb, PyArrayObject *R) + npy_intp m, npy_intp n, npy_intp k, + PyArrayObject *A, npy_intp lda, PyArrayObject *B, npy_intp ldb, PyArrayObject *R) { const void *Adata = PyArray_DATA(A), *Bdata = PyArray_DATA(B); void *Rdata = PyArray_DATA(R); - int ldc = PyArray_DIM(R, 1) > 1 ? PyArray_DIM(R, 1) : 1; + npy_intp ldc = PyArray_DIM(R, 1) > 1 ? PyArray_DIM(R, 1) : 1; switch (typenum) { case NPY_DOUBLE: - cblas_dgemm(order, transA, transB, m, n, k, 1., + CBLAS_FUNC(cblas_dgemm)(order, transA, transB, m, n, k, 1., Adata, lda, Bdata, ldb, 0., Rdata, ldc); break; case NPY_FLOAT: - cblas_sgemm(order, transA, transB, m, n, k, 1.f, + CBLAS_FUNC(cblas_sgemm)(order, transA, transB, m, n, k, 1.f, Adata, lda, Bdata, ldb, 0.f, Rdata, ldc); break; case NPY_CDOUBLE: - cblas_zgemm(order, transA, transB, m, n, k, oneD, + CBLAS_FUNC(cblas_zgemm)(order, transA, transB, m, n, k, oneD, Adata, lda, Bdata, ldb, zeroD, Rdata, ldc); break; case NPY_CFLOAT: - cblas_cgemm(order, transA, transB, m, n, k, oneF, + CBLAS_FUNC(cblas_cgemm)(order, transA, transB, m, n, k, oneF, Adata, lda, Bdata, ldb, zeroF, Rdata, ldc); break; } @@ -57,29 +67,29 @@ gemm(int typenum, enum CBLAS_ORDER order, */ static void gemv(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, - PyArrayObject *A, int lda, PyArrayObject *X, int incX, + PyArrayObject *A, npy_intp lda, PyArrayObject *X, npy_intp incX, PyArrayObject *R) { const void *Adata = PyArray_DATA(A), *Xdata = PyArray_DATA(X); void *Rdata = PyArray_DATA(R); - int m = PyArray_DIM(A, 0), n = PyArray_DIM(A, 1); + npy_intp m = PyArray_DIM(A, 0), n = PyArray_DIM(A, 1); switch (typenum) { case NPY_DOUBLE: - cblas_dgemv(order, trans, m, n, 1., Adata, lda, Xdata, incX, + CBLAS_FUNC(cblas_dgemv)(order, trans, m, n, 1., Adata, lda, Xdata, incX, 0., Rdata, 1); break; case NPY_FLOAT: - cblas_sgemv(order, trans, m, n, 1.f, Adata, lda, Xdata, incX, + CBLAS_FUNC(cblas_sgemv)(order, trans, m, n, 1.f, Adata, lda, Xdata, incX, 0.f, Rdata, 1); break; case NPY_CDOUBLE: - cblas_zgemv(order, trans, m, n, oneD, Adata, lda, Xdata, incX, + CBLAS_FUNC(cblas_zgemv)(order, trans, m, n, oneD, Adata, lda, Xdata, incX, zeroD, Rdata, 1); break; case NPY_CFLOAT: - cblas_cgemv(order, trans, m, n, oneF, Adata, lda, Xdata, incX, + CBLAS_FUNC(cblas_cgemv)(order, trans, m, n, oneF, Adata, lda, Xdata, incX, zeroF, Rdata, 1); break; } @@ -91,19 +101,19 @@ gemv(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, */ static void syrk(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, - int n, int k, - PyArrayObject *A, int lda, PyArrayObject *R) + npy_intp n, npy_intp k, + PyArrayObject *A, npy_intp lda, PyArrayObject *R) { const void *Adata = PyArray_DATA(A); void *Rdata = PyArray_DATA(R); - int ldc = PyArray_DIM(R, 1) > 1 ? PyArray_DIM(R, 1) : 1; + npy_intp ldc = PyArray_DIM(R, 1) > 1 ? PyArray_DIM(R, 1) : 1; npy_intp i; npy_intp j; switch (typenum) { case NPY_DOUBLE: - cblas_dsyrk(order, CblasUpper, trans, n, k, 1., + CBLAS_FUNC(cblas_dsyrk)(order, CblasUpper, trans, n, k, 1., Adata, lda, 0., Rdata, ldc); for (i = 0; i < n; i++) { @@ -114,7 +124,7 @@ syrk(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, } break; case NPY_FLOAT: - cblas_ssyrk(order, CblasUpper, trans, n, k, 1.f, + CBLAS_FUNC(cblas_ssyrk)(order, CblasUpper, trans, n, k, 1.f, Adata, lda, 0.f, Rdata, ldc); for (i = 0; i < n; i++) { @@ -125,7 +135,7 @@ syrk(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, } break; case NPY_CDOUBLE: - cblas_zsyrk(order, CblasUpper, trans, n, k, oneD, + CBLAS_FUNC(cblas_zsyrk)(order, CblasUpper, trans, n, k, oneD, Adata, lda, zeroD, Rdata, ldc); for (i = 0; i < n; i++) { @@ -136,7 +146,7 @@ syrk(int typenum, enum CBLAS_ORDER order, enum CBLAS_TRANSPOSE trans, } break; case NPY_CFLOAT: - cblas_csyrk(order, CblasUpper, trans, n, k, oneF, + CBLAS_FUNC(cblas_csyrk)(order, CblasUpper, trans, n, k, oneF, Adata, lda, zeroF, Rdata, ldc); for (i = 0; i < n; i++) { @@ -222,7 +232,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, PyArrayObject *out) { PyArrayObject *result = NULL, *out_buf = NULL; - int j, lda, ldb; + npy_intp j, lda, ldb; npy_intp l; int nd; npy_intp ap1stride = 0; @@ -385,14 +395,15 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, *((double *)PyArray_DATA(ap1)); } else if (ap1shape != _matrix) { - cblas_daxpy(l, + CBLAS_FUNC(cblas_daxpy)(l, *((double *)PyArray_DATA(ap2)), (double *)PyArray_DATA(ap1), ap1stride/sizeof(double), (double *)PyArray_DATA(out_buf), 1); } else { - int maxind, oind, i, a1s, outs; + int maxind, oind; + npy_intp i, a1s, outs; char *ptr, *optr; double val; @@ -405,7 +416,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, a1s = PyArray_STRIDE(ap1, maxind) / sizeof(double); outs = PyArray_STRIDE(out_buf, maxind) / sizeof(double); for (i = 0; i < PyArray_DIM(ap1, oind); i++) { - cblas_daxpy(l, val, (double *)ptr, a1s, + CBLAS_FUNC(cblas_daxpy)(l, val, (double *)ptr, a1s, (double *)optr, outs); ptr += PyArray_STRIDE(ap1, oind); optr += PyArray_STRIDE(out_buf, oind); @@ -423,14 +434,15 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, res->imag = ptr1->real * ptr2->imag + ptr1->imag * ptr2->real; } else if (ap1shape != _matrix) { - cblas_zaxpy(l, + CBLAS_FUNC(cblas_zaxpy)(l, (double *)PyArray_DATA(ap2), (double *)PyArray_DATA(ap1), ap1stride/sizeof(npy_cdouble), (double *)PyArray_DATA(out_buf), 1); } else { - int maxind, oind, i, a1s, outs; + int maxind, oind; + npy_intp i, a1s, outs; char *ptr, *optr; double *pval; @@ -443,7 +455,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, a1s = PyArray_STRIDE(ap1, maxind) / sizeof(npy_cdouble); outs = PyArray_STRIDE(out_buf, maxind) / sizeof(npy_cdouble); for (i = 0; i < PyArray_DIM(ap1, oind); i++) { - cblas_zaxpy(l, pval, (double *)ptr, a1s, + CBLAS_FUNC(cblas_zaxpy)(l, pval, (double *)ptr, a1s, (double *)optr, outs); ptr += PyArray_STRIDE(ap1, oind); optr += PyArray_STRIDE(out_buf, oind); @@ -456,14 +468,15 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, *((float *)PyArray_DATA(ap1)); } else if (ap1shape != _matrix) { - cblas_saxpy(l, + CBLAS_FUNC(cblas_saxpy)(l, *((float *)PyArray_DATA(ap2)), (float *)PyArray_DATA(ap1), ap1stride/sizeof(float), (float *)PyArray_DATA(out_buf), 1); } else { - int maxind, oind, i, a1s, outs; + int maxind, oind; + npy_intp i, a1s, outs; char *ptr, *optr; float val; @@ -476,7 +489,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, a1s = PyArray_STRIDE(ap1, maxind) / sizeof(float); outs = PyArray_STRIDE(out_buf, maxind) / sizeof(float); for (i = 0; i < PyArray_DIM(ap1, oind); i++) { - cblas_saxpy(l, val, (float *)ptr, a1s, + CBLAS_FUNC(cblas_saxpy)(l, val, (float *)ptr, a1s, (float *)optr, outs); ptr += PyArray_STRIDE(ap1, oind); optr += PyArray_STRIDE(out_buf, oind); @@ -494,14 +507,15 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, res->imag = ptr1->real * ptr2->imag + ptr1->imag * ptr2->real; } else if (ap1shape != _matrix) { - cblas_caxpy(l, + CBLAS_FUNC(cblas_caxpy)(l, (float *)PyArray_DATA(ap2), (float *)PyArray_DATA(ap1), ap1stride/sizeof(npy_cfloat), (float *)PyArray_DATA(out_buf), 1); } else { - int maxind, oind, i, a1s, outs; + int maxind, oind; + npy_intp i, a1s, outs; char *ptr, *optr; float *pval; @@ -514,7 +528,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, a1s = PyArray_STRIDE(ap1, maxind) / sizeof(npy_cfloat); outs = PyArray_STRIDE(out_buf, maxind) / sizeof(npy_cfloat); for (i = 0; i < PyArray_DIM(ap1, oind); i++) { - cblas_caxpy(l, pval, (float *)ptr, a1s, + CBLAS_FUNC(cblas_caxpy)(l, pval, (float *)ptr, a1s, (float *)optr, outs); ptr += PyArray_STRIDE(ap1, oind); optr += PyArray_STRIDE(out_buf, oind); @@ -537,7 +551,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, /* Matrix vector multiplication -- Level 2 BLAS */ /* lda must be MAX(M,1) */ enum CBLAS_ORDER Order; - int ap2s; + npy_intp ap2s; if (!PyArray_ISONESEGMENT(ap1)) { PyObject *new; @@ -564,7 +578,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, else if (ap1shape != _matrix && ap2shape == _matrix) { /* Vector matrix multiplication -- Level 2 BLAS */ enum CBLAS_ORDER Order; - int ap1s; + npy_intp ap1s; if (!PyArray_ISONESEGMENT(ap2)) { PyObject *new; @@ -601,7 +615,7 @@ cblas_matrixproduct(int typenum, PyArrayObject *ap1, PyArrayObject *ap2, */ enum CBLAS_ORDER Order; enum CBLAS_TRANSPOSE Trans1, Trans2; - int M, N, L; + npy_intp M, N, L; /* Optimization possible: */ /* diff --git a/numpy/core/src/common/npy_cblas.h b/numpy/core/src/common/npy_cblas.h index a083f3bcc..12db55bde 100644 --- a/numpy/core/src/common/npy_cblas.h +++ b/numpy/core/src/common/npy_cblas.h @@ -17,565 +17,21 @@ extern "C" /* * Enumerated and derived types */ -#define CBLAS_INDEX size_t /* this may vary between platforms */ - enum CBLAS_ORDER {CblasRowMajor=101, CblasColMajor=102}; enum CBLAS_TRANSPOSE {CblasNoTrans=111, CblasTrans=112, CblasConjTrans=113}; enum CBLAS_UPLO {CblasUpper=121, CblasLower=122}; enum CBLAS_DIAG {CblasNonUnit=131, CblasUnit=132}; enum CBLAS_SIDE {CblasLeft=141, CblasRight=142}; -/* - * =========================================================================== - * Prototypes for level 1 BLAS functions (complex are recast as routines) - * =========================================================================== - */ -float cblas_sdsdot(const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY); -double cblas_dsdot(const int N, const float *X, const int incX, const float *Y, - const int incY); -float cblas_sdot(const int N, const float *X, const int incX, - const float *Y, const int incY); -double cblas_ddot(const int N, const double *X, const int incX, - const double *Y, const int incY); - -/* - * Functions having prefixes Z and C only - */ -void cblas_cdotu_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotu); -void cblas_cdotc_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotc); - -void cblas_zdotu_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotu); -void cblas_zdotc_sub(const int N, const void *X, const int incX, - const void *Y, const int incY, void *dotc); - - -/* - * Functions having prefixes S D SC DZ - */ -float cblas_snrm2(const int N, const float *X, const int incX); -float cblas_sasum(const int N, const float *X, const int incX); - -double cblas_dnrm2(const int N, const double *X, const int incX); -double cblas_dasum(const int N, const double *X, const int incX); - -float cblas_scnrm2(const int N, const void *X, const int incX); -float cblas_scasum(const int N, const void *X, const int incX); - -double cblas_dznrm2(const int N, const void *X, const int incX); -double cblas_dzasum(const int N, const void *X, const int incX); - - -/* - * Functions having standard 4 prefixes (S D C Z) - */ -CBLAS_INDEX cblas_isamax(const int N, const float *X, const int incX); -CBLAS_INDEX cblas_idamax(const int N, const double *X, const int incX); -CBLAS_INDEX cblas_icamax(const int N, const void *X, const int incX); -CBLAS_INDEX cblas_izamax(const int N, const void *X, const int incX); - -/* - * =========================================================================== - * Prototypes for level 1 BLAS routines - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (s, d, c, z) - */ -void cblas_sswap(const int N, float *X, const int incX, - float *Y, const int incY); -void cblas_scopy(const int N, const float *X, const int incX, - float *Y, const int incY); -void cblas_saxpy(const int N, const float alpha, const float *X, - const int incX, float *Y, const int incY); - -void cblas_dswap(const int N, double *X, const int incX, - double *Y, const int incY); -void cblas_dcopy(const int N, const double *X, const int incX, - double *Y, const int incY); -void cblas_daxpy(const int N, const double alpha, const double *X, - const int incX, double *Y, const int incY); - -void cblas_cswap(const int N, void *X, const int incX, - void *Y, const int incY); -void cblas_ccopy(const int N, const void *X, const int incX, - void *Y, const int incY); -void cblas_caxpy(const int N, const void *alpha, const void *X, - const int incX, void *Y, const int incY); - -void cblas_zswap(const int N, void *X, const int incX, - void *Y, const int incY); -void cblas_zcopy(const int N, const void *X, const int incX, - void *Y, const int incY); -void cblas_zaxpy(const int N, const void *alpha, const void *X, - const int incX, void *Y, const int incY); - - -/* - * Routines with S and D prefix only - */ -void cblas_srotg(float *a, float *b, float *c, float *s); -void cblas_srotmg(float *d1, float *d2, float *b1, const float b2, float *P); -void cblas_srot(const int N, float *X, const int incX, - float *Y, const int incY, const float c, const float s); -void cblas_srotm(const int N, float *X, const int incX, - float *Y, const int incY, const float *P); - -void cblas_drotg(double *a, double *b, double *c, double *s); -void cblas_drotmg(double *d1, double *d2, double *b1, const double b2, double *P); -void cblas_drot(const int N, double *X, const int incX, - double *Y, const int incY, const double c, const double s); -void cblas_drotm(const int N, double *X, const int incX, - double *Y, const int incY, const double *P); - - -/* - * Routines with S D C Z CS and ZD prefixes - */ -void cblas_sscal(const int N, const float alpha, float *X, const int incX); -void cblas_dscal(const int N, const double alpha, double *X, const int incX); -void cblas_cscal(const int N, const void *alpha, void *X, const int incX); -void cblas_zscal(const int N, const void *alpha, void *X, const int incX); -void cblas_csscal(const int N, const float alpha, void *X, const int incX); -void cblas_zdscal(const int N, const double alpha, void *X, const int incX); - -/* - * =========================================================================== - * Prototypes for level 2 BLAS - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (S, D, C, Z) - */ -void cblas_sgemv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const float alpha, const float *A, const int lda, - const float *X, const int incX, const float beta, - float *Y, const int incY); -void cblas_sgbmv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const float alpha, - const float *A, const int lda, const float *X, - const int incX, const float beta, float *Y, const int incY); -void cblas_strmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *A, const int lda, - float *X, const int incX); -void cblas_stbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const float *A, const int lda, - float *X, const int incX); -void cblas_stpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *Ap, float *X, const int incX); -void cblas_strsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *A, const int lda, float *X, - const int incX); -void cblas_stbsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const float *A, const int lda, - float *X, const int incX); -void cblas_stpsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const float *Ap, float *X, const int incX); - -void cblas_dgemv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const double alpha, const double *A, const int lda, - const double *X, const int incX, const double beta, - double *Y, const int incY); -void cblas_dgbmv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const double alpha, - const double *A, const int lda, const double *X, - const int incX, const double beta, double *Y, const int incY); -void cblas_dtrmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *A, const int lda, - double *X, const int incX); -void cblas_dtbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const double *A, const int lda, - double *X, const int incX); -void cblas_dtpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *Ap, double *X, const int incX); -void cblas_dtrsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *A, const int lda, double *X, - const int incX); -void cblas_dtbsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const double *A, const int lda, - double *X, const int incX); -void cblas_dtpsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const double *Ap, double *X, const int incX); - -void cblas_cgemv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *X, const int incX, const void *beta, - void *Y, const int incY); -void cblas_cgbmv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const void *alpha, - const void *A, const int lda, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void cblas_ctrmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, - void *X, const int incX); -void cblas_ctbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ctpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); -void cblas_ctrsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, void *X, - const int incX); -void cblas_ctbsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ctpsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); - -void cblas_zgemv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *X, const int incX, const void *beta, - void *Y, const int incY); -void cblas_zgbmv(const enum CBLAS_ORDER order, - const enum CBLAS_TRANSPOSE TransA, const int M, const int N, - const int KL, const int KU, const void *alpha, - const void *A, const int lda, const void *X, - const int incX, const void *beta, void *Y, const int incY); -void cblas_ztrmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, - void *X, const int incX); -void cblas_ztbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ztpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); -void cblas_ztrsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *A, const int lda, void *X, - const int incX); -void cblas_ztbsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const int K, const void *A, const int lda, - void *X, const int incX); -void cblas_ztpsv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, - const int N, const void *Ap, void *X, const int incX); - - -/* - * Routines with S and D prefixes only - */ -void cblas_ssymv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *A, - const int lda, const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_ssbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const float alpha, const float *A, - const int lda, const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_sspmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *Ap, - const float *X, const int incX, - const float beta, float *Y, const int incY); -void cblas_sger(const enum CBLAS_ORDER order, const int M, const int N, - const float alpha, const float *X, const int incX, - const float *Y, const int incY, float *A, const int lda); -void cblas_ssyr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, float *A, const int lda); -void cblas_sspr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, float *Ap); -void cblas_ssyr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY, float *A, - const int lda); -void cblas_sspr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const float *X, - const int incX, const float *Y, const int incY, float *A); - -void cblas_dsymv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *A, - const int lda, const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dsbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const double alpha, const double *A, - const int lda, const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dspmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *Ap, - const double *X, const int incX, - const double beta, double *Y, const int incY); -void cblas_dger(const enum CBLAS_ORDER order, const int M, const int N, - const double alpha, const double *X, const int incX, - const double *Y, const int incY, double *A, const int lda); -void cblas_dsyr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, double *A, const int lda); -void cblas_dspr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, double *Ap); -void cblas_dsyr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, const double *Y, const int incY, double *A, - const int lda); -void cblas_dspr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const double *X, - const int incX, const double *Y, const int incY, double *A); - - -/* - * Routines with C and Z prefixes only - */ -void cblas_chemv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_chbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_chpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *Ap, - const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_cgeru(const enum CBLAS_ORDER order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_cgerc(const enum CBLAS_ORDER order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_cher(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const void *X, const int incX, - void *A, const int lda); -void cblas_chpr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const float alpha, const void *X, - const int incX, void *A); -void cblas_cher2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_chpr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *Ap); - -void cblas_zhemv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zhbmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const int K, const void *alpha, const void *A, - const int lda, const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zhpmv(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const void *alpha, const void *Ap, - const void *X, const int incX, - const void *beta, void *Y, const int incY); -void cblas_zgeru(const enum CBLAS_ORDER order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zgerc(const enum CBLAS_ORDER order, const int M, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zher(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const void *X, const int incX, - void *A, const int lda); -void cblas_zhpr(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, - const int N, const double alpha, const void *X, - const int incX, void *A); -void cblas_zher2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *A, const int lda); -void cblas_zhpr2(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const int N, - const void *alpha, const void *X, const int incX, - const void *Y, const int incY, void *Ap); - -/* - * =========================================================================== - * Prototypes for level 3 BLAS - * =========================================================================== - */ - -/* - * Routines with standard 4 prefixes (S, D, C, Z) - */ -void cblas_sgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const float alpha, const float *A, - const int lda, const float *B, const int ldb, - const float beta, float *C, const int ldc); -void cblas_ssymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const float alpha, const float *A, const int lda, - const float *B, const int ldb, const float beta, - float *C, const int ldc); -void cblas_ssyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const float *A, const int lda, - const float beta, float *C, const int ldc); -void cblas_ssyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const float *A, const int lda, - const float *B, const int ldb, const float beta, - float *C, const int ldc); -void cblas_strmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const float alpha, const float *A, const int lda, - float *B, const int ldb); -void cblas_strsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const float alpha, const float *A, const int lda, - float *B, const int ldb); - -void cblas_dgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const double alpha, const double *A, - const int lda, const double *B, const int ldb, - const double beta, double *C, const int ldc); -void cblas_dsymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const double alpha, const double *A, const int lda, - const double *B, const int ldb, const double beta, - double *C, const int ldc); -void cblas_dsyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const double *A, const int lda, - const double beta, double *C, const int ldc); -void cblas_dsyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const double *A, const int lda, - const double *B, const int ldb, const double beta, - double *C, const int ldc); -void cblas_dtrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const double alpha, const double *A, const int lda, - double *B, const int ldb); -void cblas_dtrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const double alpha, const double *A, const int lda, - double *B, const int ldb); - -void cblas_cgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const void *alpha, const void *A, - const int lda, const void *B, const int ldb, - const void *beta, void *C, const int ldc); -void cblas_csymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_csyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *beta, void *C, const int ldc); -void cblas_csyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_ctrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); -void cblas_ctrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); - -void cblas_zgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_TRANSPOSE TransB, const int M, const int N, - const int K, const void *alpha, const void *A, - const int lda, const void *B, const int ldb, - const void *beta, void *C, const int ldc); -void cblas_zsymm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_zsyrk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *beta, void *C, const int ldc); -void cblas_zsyr2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_ztrmm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); -void cblas_ztrsm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, - const enum CBLAS_DIAG Diag, const int M, const int N, - const void *alpha, const void *A, const int lda, - void *B, const int ldb); - +#define CBLAS_INDEX size_t /* this may vary between platforms */ -/* - * Routines with prefixes C and Z only - */ -void cblas_chemm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_cherk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const float alpha, const void *A, const int lda, - const float beta, void *C, const int ldc); -void cblas_cher2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const float beta, - void *C, const int ldc); +#define BLASINT int +#define BLASNAME(name) name -void cblas_zhemm(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, - const enum CBLAS_UPLO Uplo, const int M, const int N, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const void *beta, - void *C, const int ldc); -void cblas_zherk(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const double alpha, const void *A, const int lda, - const double beta, void *C, const int ldc); -void cblas_zher2k(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, - const enum CBLAS_TRANSPOSE Trans, const int N, const int K, - const void *alpha, const void *A, const int lda, - const void *B, const int ldb, const double beta, - void *C, const int ldc); +#include "npy_cblas_base.h" -void cblas_xerbla(int p, const char *rout, const char *form, ...); +#undef BLASINT +#undef BLASNAME #ifdef __cplusplus } diff --git a/numpy/core/src/common/npy_cblas64_.h b/numpy/core/src/common/npy_cblas64_.h new file mode 100644 index 000000000..bbc4b3559 --- /dev/null +++ b/numpy/core/src/common/npy_cblas64_.h @@ -0,0 +1,31 @@ +/* + * This header provides numpy a consistent interface to CBLAS code. It is needed + * because not all providers of cblas provide cblas.h. For instance, MKL provides + * mkl_cblas.h and also typedefs the CBLAS_XXX enums. + */ +#ifndef _NPY_CBLAS64__H_ +#define _NPY_CBLAS64__H_ + +#include <stddef.h> + +#include "npy_cblas.h" + +/* Allow the use in C++ code. */ +#ifdef __cplusplus +extern "C" +{ +#endif + +#define BLASINT npy_int64 +#define BLASNAME(name) name##64_ + +#include "npy_cblas_base.h" + +#undef BLASINT +#undef BLASNAME + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/numpy/core/src/common/npy_cblas_base.h b/numpy/core/src/common/npy_cblas_base.h new file mode 100644 index 000000000..792b6f09e --- /dev/null +++ b/numpy/core/src/common/npy_cblas_base.h @@ -0,0 +1,557 @@ +/* + * This header provides numpy a consistent interface to CBLAS code. It is needed + * because not all providers of cblas provide cblas.h. For instance, MKL provides + * mkl_cblas.h and also typedefs the CBLAS_XXX enums. + */ + +/* + * =========================================================================== + * Prototypes for level 1 BLAS functions (complex are recast as routines) + * =========================================================================== + */ +float BLASNAME(cblas_sdsdot)(const BLASINT N, const float alpha, const float *X, + const BLASINT incX, const float *Y, const BLASINT incY); +double BLASNAME(cblas_dsdot)(const BLASINT N, const float *X, const BLASINT incX, const float *Y, + const BLASINT incY); +float BLASNAME(cblas_sdot)(const BLASINT N, const float *X, const BLASINT incX, + const float *Y, const BLASINT incY); +double BLASNAME(cblas_ddot)(const BLASINT N, const double *X, const BLASINT incX, + const double *Y, const BLASINT incY); + +/* + * Functions having prefixes Z and C only + */ +void BLASNAME(cblas_cdotu_sub)(const BLASINT N, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *dotu); +void BLASNAME(cblas_cdotc_sub)(const BLASINT N, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *dotc); + +void BLASNAME(cblas_zdotu_sub)(const BLASINT N, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *dotu); +void BLASNAME(cblas_zdotc_sub)(const BLASINT N, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *dotc); + + +/* + * Functions having prefixes S D SC DZ + */ +float BLASNAME(cblas_snrm2)(const BLASINT N, const float *X, const BLASINT incX); +float BLASNAME(cblas_sasum)(const BLASINT N, const float *X, const BLASINT incX); + +double BLASNAME(cblas_dnrm2)(const BLASINT N, const double *X, const BLASINT incX); +double BLASNAME(cblas_dasum)(const BLASINT N, const double *X, const BLASINT incX); + +float BLASNAME(cblas_scnrm2)(const BLASINT N, const void *X, const BLASINT incX); +float BLASNAME(cblas_scasum)(const BLASINT N, const void *X, const BLASINT incX); + +double BLASNAME(cblas_dznrm2)(const BLASINT N, const void *X, const BLASINT incX); +double BLASNAME(cblas_dzasum)(const BLASINT N, const void *X, const BLASINT incX); + + +/* + * Functions having standard 4 prefixes (S D C Z) + */ +CBLAS_INDEX BLASNAME(cblas_isamax)(const BLASINT N, const float *X, const BLASINT incX); +CBLAS_INDEX BLASNAME(cblas_idamax)(const BLASINT N, const double *X, const BLASINT incX); +CBLAS_INDEX BLASNAME(cblas_icamax)(const BLASINT N, const void *X, const BLASINT incX); +CBLAS_INDEX BLASNAME(cblas_izamax)(const BLASINT N, const void *X, const BLASINT incX); + +/* + * =========================================================================== + * Prototypes for level 1 BLAS routines + * =========================================================================== + */ + +/* + * Routines with standard 4 prefixes (s, d, c, z) + */ +void BLASNAME(cblas_sswap)(const BLASINT N, float *X, const BLASINT incX, + float *Y, const BLASINT incY); +void BLASNAME(cblas_scopy)(const BLASINT N, const float *X, const BLASINT incX, + float *Y, const BLASINT incY); +void BLASNAME(cblas_saxpy)(const BLASINT N, const float alpha, const float *X, + const BLASINT incX, float *Y, const BLASINT incY); + +void BLASNAME(cblas_dswap)(const BLASINT N, double *X, const BLASINT incX, + double *Y, const BLASINT incY); +void BLASNAME(cblas_dcopy)(const BLASINT N, const double *X, const BLASINT incX, + double *Y, const BLASINT incY); +void BLASNAME(cblas_daxpy)(const BLASINT N, const double alpha, const double *X, + const BLASINT incX, double *Y, const BLASINT incY); + +void BLASNAME(cblas_cswap)(const BLASINT N, void *X, const BLASINT incX, + void *Y, const BLASINT incY); +void BLASNAME(cblas_ccopy)(const BLASINT N, const void *X, const BLASINT incX, + void *Y, const BLASINT incY); +void BLASNAME(cblas_caxpy)(const BLASINT N, const void *alpha, const void *X, + const BLASINT incX, void *Y, const BLASINT incY); + +void BLASNAME(cblas_zswap)(const BLASINT N, void *X, const BLASINT incX, + void *Y, const BLASINT incY); +void BLASNAME(cblas_zcopy)(const BLASINT N, const void *X, const BLASINT incX, + void *Y, const BLASINT incY); +void BLASNAME(cblas_zaxpy)(const BLASINT N, const void *alpha, const void *X, + const BLASINT incX, void *Y, const BLASINT incY); + + +/* + * Routines with S and D prefix only + */ +void BLASNAME(cblas_srotg)(float *a, float *b, float *c, float *s); +void BLASNAME(cblas_srotmg)(float *d1, float *d2, float *b1, const float b2, float *P); +void BLASNAME(cblas_srot)(const BLASINT N, float *X, const BLASINT incX, + float *Y, const BLASINT incY, const float c, const float s); +void BLASNAME(cblas_srotm)(const BLASINT N, float *X, const BLASINT incX, + float *Y, const BLASINT incY, const float *P); + +void BLASNAME(cblas_drotg)(double *a, double *b, double *c, double *s); +void BLASNAME(cblas_drotmg)(double *d1, double *d2, double *b1, const double b2, double *P); +void BLASNAME(cblas_drot)(const BLASINT N, double *X, const BLASINT incX, + double *Y, const BLASINT incY, const double c, const double s); +void BLASNAME(cblas_drotm)(const BLASINT N, double *X, const BLASINT incX, + double *Y, const BLASINT incY, const double *P); + + +/* + * Routines with S D C Z CS and ZD prefixes + */ +void BLASNAME(cblas_sscal)(const BLASINT N, const float alpha, float *X, const BLASINT incX); +void BLASNAME(cblas_dscal)(const BLASINT N, const double alpha, double *X, const BLASINT incX); +void BLASNAME(cblas_cscal)(const BLASINT N, const void *alpha, void *X, const BLASINT incX); +void BLASNAME(cblas_zscal)(const BLASINT N, const void *alpha, void *X, const BLASINT incX); +void BLASNAME(cblas_csscal)(const BLASINT N, const float alpha, void *X, const BLASINT incX); +void BLASNAME(cblas_zdscal)(const BLASINT N, const double alpha, void *X, const BLASINT incX); + +/* + * =========================================================================== + * Prototypes for level 2 BLAS + * =========================================================================== + */ + +/* + * Routines with standard 4 prefixes (S, D, C, Z) + */ +void BLASNAME(cblas_sgemv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const float alpha, const float *A, const BLASINT lda, + const float *X, const BLASINT incX, const float beta, + float *Y, const BLASINT incY); +void BLASNAME(cblas_sgbmv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const BLASINT KL, const BLASINT KU, const float alpha, + const float *A, const BLASINT lda, const float *X, + const BLASINT incX, const float beta, float *Y, const BLASINT incY); +void BLASNAME(cblas_strmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const float *A, const BLASINT lda, + float *X, const BLASINT incX); +void BLASNAME(cblas_stbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const float *A, const BLASINT lda, + float *X, const BLASINT incX); +void BLASNAME(cblas_stpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const float *Ap, float *X, const BLASINT incX); +void BLASNAME(cblas_strsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const float *A, const BLASINT lda, float *X, + const BLASINT incX); +void BLASNAME(cblas_stbsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const float *A, const BLASINT lda, + float *X, const BLASINT incX); +void BLASNAME(cblas_stpsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const float *Ap, float *X, const BLASINT incX); + +void BLASNAME(cblas_dgemv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const double alpha, const double *A, const BLASINT lda, + const double *X, const BLASINT incX, const double beta, + double *Y, const BLASINT incY); +void BLASNAME(cblas_dgbmv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const BLASINT KL, const BLASINT KU, const double alpha, + const double *A, const BLASINT lda, const double *X, + const BLASINT incX, const double beta, double *Y, const BLASINT incY); +void BLASNAME(cblas_dtrmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const double *A, const BLASINT lda, + double *X, const BLASINT incX); +void BLASNAME(cblas_dtbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const double *A, const BLASINT lda, + double *X, const BLASINT incX); +void BLASNAME(cblas_dtpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const double *Ap, double *X, const BLASINT incX); +void BLASNAME(cblas_dtrsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const double *A, const BLASINT lda, double *X, + const BLASINT incX); +void BLASNAME(cblas_dtbsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const double *A, const BLASINT lda, + double *X, const BLASINT incX); +void BLASNAME(cblas_dtpsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const double *Ap, double *X, const BLASINT incX); + +void BLASNAME(cblas_cgemv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *X, const BLASINT incX, const void *beta, + void *Y, const BLASINT incY); +void BLASNAME(cblas_cgbmv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const BLASINT KL, const BLASINT KU, const void *alpha, + const void *A, const BLASINT lda, const void *X, + const BLASINT incX, const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_ctrmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ctbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ctpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *Ap, void *X, const BLASINT incX); +void BLASNAME(cblas_ctrsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *A, const BLASINT lda, void *X, + const BLASINT incX); +void BLASNAME(cblas_ctbsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ctpsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *Ap, void *X, const BLASINT incX); + +void BLASNAME(cblas_zgemv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *X, const BLASINT incX, const void *beta, + void *Y, const BLASINT incY); +void BLASNAME(cblas_zgbmv)(const enum CBLAS_ORDER order, + const enum CBLAS_TRANSPOSE TransA, const BLASINT M, const BLASINT N, + const BLASINT KL, const BLASINT KU, const void *alpha, + const void *A, const BLASINT lda, const void *X, + const BLASINT incX, const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_ztrmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ztbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ztpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *Ap, void *X, const BLASINT incX); +void BLASNAME(cblas_ztrsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *A, const BLASINT lda, void *X, + const BLASINT incX); +void BLASNAME(cblas_ztbsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const BLASINT K, const void *A, const BLASINT lda, + void *X, const BLASINT incX); +void BLASNAME(cblas_ztpsv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE TransA, const enum CBLAS_DIAG Diag, + const BLASINT N, const void *Ap, void *X, const BLASINT incX); + + +/* + * Routines with S and D prefixes only + */ +void BLASNAME(cblas_ssymv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *A, + const BLASINT lda, const float *X, const BLASINT incX, + const float beta, float *Y, const BLASINT incY); +void BLASNAME(cblas_ssbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const BLASINT K, const float alpha, const float *A, + const BLASINT lda, const float *X, const BLASINT incX, + const float beta, float *Y, const BLASINT incY); +void BLASNAME(cblas_sspmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *Ap, + const float *X, const BLASINT incX, + const float beta, float *Y, const BLASINT incY); +void BLASNAME(cblas_sger)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const float alpha, const float *X, const BLASINT incX, + const float *Y, const BLASINT incY, float *A, const BLASINT lda); +void BLASNAME(cblas_ssyr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *X, + const BLASINT incX, float *A, const BLASINT lda); +void BLASNAME(cblas_sspr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *X, + const BLASINT incX, float *Ap); +void BLASNAME(cblas_ssyr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *X, + const BLASINT incX, const float *Y, const BLASINT incY, float *A, + const BLASINT lda); +void BLASNAME(cblas_sspr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const float *X, + const BLASINT incX, const float *Y, const BLASINT incY, float *A); + +void BLASNAME(cblas_dsymv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *A, + const BLASINT lda, const double *X, const BLASINT incX, + const double beta, double *Y, const BLASINT incY); +void BLASNAME(cblas_dsbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const BLASINT K, const double alpha, const double *A, + const BLASINT lda, const double *X, const BLASINT incX, + const double beta, double *Y, const BLASINT incY); +void BLASNAME(cblas_dspmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *Ap, + const double *X, const BLASINT incX, + const double beta, double *Y, const BLASINT incY); +void BLASNAME(cblas_dger)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const double alpha, const double *X, const BLASINT incX, + const double *Y, const BLASINT incY, double *A, const BLASINT lda); +void BLASNAME(cblas_dsyr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *X, + const BLASINT incX, double *A, const BLASINT lda); +void BLASNAME(cblas_dspr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *X, + const BLASINT incX, double *Ap); +void BLASNAME(cblas_dsyr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *X, + const BLASINT incX, const double *Y, const BLASINT incY, double *A, + const BLASINT lda); +void BLASNAME(cblas_dspr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const double *X, + const BLASINT incX, const double *Y, const BLASINT incY, double *A); + + +/* + * Routines with C and Z prefixes only + */ +void BLASNAME(cblas_chemv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const void *alpha, const void *A, + const BLASINT lda, const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_chbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const BLASINT K, const void *alpha, const void *A, + const BLASINT lda, const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_chpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const void *alpha, const void *Ap, + const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_cgeru)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_cgerc)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_cher)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const void *X, const BLASINT incX, + void *A, const BLASINT lda); +void BLASNAME(cblas_chpr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const float alpha, const void *X, + const BLASINT incX, void *A); +void BLASNAME(cblas_cher2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_chpr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *Ap); + +void BLASNAME(cblas_zhemv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const void *alpha, const void *A, + const BLASINT lda, const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_zhbmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const BLASINT K, const void *alpha, const void *A, + const BLASINT lda, const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_zhpmv)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const void *alpha, const void *Ap, + const void *X, const BLASINT incX, + const void *beta, void *Y, const BLASINT incY); +void BLASNAME(cblas_zgeru)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_zgerc)(const enum CBLAS_ORDER order, const BLASINT M, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_zher)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const void *X, const BLASINT incX, + void *A, const BLASINT lda); +void BLASNAME(cblas_zhpr)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, + const BLASINT N, const double alpha, const void *X, + const BLASINT incX, void *A); +void BLASNAME(cblas_zher2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *A, const BLASINT lda); +void BLASNAME(cblas_zhpr2)(const enum CBLAS_ORDER order, const enum CBLAS_UPLO Uplo, const BLASINT N, + const void *alpha, const void *X, const BLASINT incX, + const void *Y, const BLASINT incY, void *Ap); + +/* + * =========================================================================== + * Prototypes for level 3 BLAS + * =========================================================================== + */ + +/* + * Routines with standard 4 prefixes (S, D, C, Z) + */ +void BLASNAME(cblas_sgemm)(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_TRANSPOSE TransB, const BLASINT M, const BLASINT N, + const BLASINT K, const float alpha, const float *A, + const BLASINT lda, const float *B, const BLASINT ldb, + const float beta, float *C, const BLASINT ldc); +void BLASNAME(cblas_ssymm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const float alpha, const float *A, const BLASINT lda, + const float *B, const BLASINT ldb, const float beta, + float *C, const BLASINT ldc); +void BLASNAME(cblas_ssyrk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const float alpha, const float *A, const BLASINT lda, + const float beta, float *C, const BLASINT ldc); +void BLASNAME(cblas_ssyr2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const float alpha, const float *A, const BLASINT lda, + const float *B, const BLASINT ldb, const float beta, + float *C, const BLASINT ldc); +void BLASNAME(cblas_strmm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const float alpha, const float *A, const BLASINT lda, + float *B, const BLASINT ldb); +void BLASNAME(cblas_strsm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const float alpha, const float *A, const BLASINT lda, + float *B, const BLASINT ldb); + +void BLASNAME(cblas_dgemm)(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_TRANSPOSE TransB, const BLASINT M, const BLASINT N, + const BLASINT K, const double alpha, const double *A, + const BLASINT lda, const double *B, const BLASINT ldb, + const double beta, double *C, const BLASINT ldc); +void BLASNAME(cblas_dsymm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const double alpha, const double *A, const BLASINT lda, + const double *B, const BLASINT ldb, const double beta, + double *C, const BLASINT ldc); +void BLASNAME(cblas_dsyrk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const double alpha, const double *A, const BLASINT lda, + const double beta, double *C, const BLASINT ldc); +void BLASNAME(cblas_dsyr2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const double alpha, const double *A, const BLASINT lda, + const double *B, const BLASINT ldb, const double beta, + double *C, const BLASINT ldc); +void BLASNAME(cblas_dtrmm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const double alpha, const double *A, const BLASINT lda, + double *B, const BLASINT ldb); +void BLASNAME(cblas_dtrsm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const double alpha, const double *A, const BLASINT lda, + double *B, const BLASINT ldb); + +void BLASNAME(cblas_cgemm)(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_TRANSPOSE TransB, const BLASINT M, const BLASINT N, + const BLASINT K, const void *alpha, const void *A, + const BLASINT lda, const void *B, const BLASINT ldb, + const void *beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_csymm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_csyrk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_csyr2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_ctrmm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + void *B, const BLASINT ldb); +void BLASNAME(cblas_ctrsm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + void *B, const BLASINT ldb); + +void BLASNAME(cblas_zgemm)(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_TRANSPOSE TransB, const BLASINT M, const BLASINT N, + const BLASINT K, const void *alpha, const void *A, + const BLASINT lda, const void *B, const BLASINT ldb, + const void *beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_zsymm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_zsyrk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_zsyr2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_ztrmm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + void *B, const BLASINT ldb); +void BLASNAME(cblas_ztrsm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const enum CBLAS_TRANSPOSE TransA, + const enum CBLAS_DIAG Diag, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + void *B, const BLASINT ldb); + + +/* + * Routines with prefixes C and Z only + */ +void BLASNAME(cblas_chemm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_cherk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const float alpha, const void *A, const BLASINT lda, + const float beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_cher2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const float beta, + void *C, const BLASINT ldc); + +void BLASNAME(cblas_zhemm)(const enum CBLAS_ORDER Order, const enum CBLAS_SIDE Side, + const enum CBLAS_UPLO Uplo, const BLASINT M, const BLASINT N, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const void *beta, + void *C, const BLASINT ldc); +void BLASNAME(cblas_zherk)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const double alpha, const void *A, const BLASINT lda, + const double beta, void *C, const BLASINT ldc); +void BLASNAME(cblas_zher2k)(const enum CBLAS_ORDER Order, const enum CBLAS_UPLO Uplo, + const enum CBLAS_TRANSPOSE Trans, const BLASINT N, const BLASINT K, + const void *alpha, const void *A, const BLASINT lda, + const void *B, const BLASINT ldb, const double beta, + void *C, const BLASINT ldc); + +void BLASNAME(cblas_xerbla)(BLASINT p, const char *rout, const char *form, ...); diff --git a/numpy/core/src/common/python_xerbla.c b/numpy/core/src/common/python_xerbla.c index bdf0b9058..d88562b7a 100644 --- a/numpy/core/src/common/python_xerbla.c +++ b/numpy/core/src/common/python_xerbla.c @@ -1,4 +1,5 @@ #include "Python.h" +#include "numpy/npy_common.h" /* * From f2c.h, this should be safe unless fortran is set to use 64 @@ -49,3 +50,11 @@ int xerbla_(char *srname, integer *info) return 0; } + + +/* Same for LAPACK64_ */ +npy_int64 xerbla_64_(char *srname, npy_int64 *info) +{ + integer info_int = (integer)*info; + return xerbla_(srname, &info_int); +} diff --git a/numpy/core/src/multiarray/convert_datatype.c b/numpy/core/src/multiarray/convert_datatype.c index 025c66013..4326448dc 100644 --- a/numpy/core/src/multiarray/convert_datatype.c +++ b/numpy/core/src/multiarray/convert_datatype.c @@ -877,7 +877,13 @@ PyArray_CanCastTypeTo(PyArray_Descr *from, PyArray_Descr *to, from_order = dtype_kind_to_ordering(from->kind); to_order = dtype_kind_to_ordering(to->kind); - return from_order != -1 && from_order <= to_order; + if (to->kind == 'm') { + /* both types being timedelta is already handled before. */ + int integer_order = dtype_kind_to_ordering('i'); + return (from_order != -1) && (from_order <= integer_order); + } + + return (from_order != -1) && (from_order <= to_order); } else { return 0; diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c index 64933ae1b..7276add75 100644 --- a/numpy/core/src/multiarray/ctors.c +++ b/numpy/core/src/multiarray/ctors.c @@ -453,10 +453,6 @@ copy_and_swap(void *dst, void *src, int itemsize, npy_intp numitems, } } -NPY_NO_EXPORT PyObject * -_array_from_array_like(PyObject *op, PyArray_Descr *requested_dtype, - npy_bool writeable, PyObject *context); - /* * adapted from Numarray, * a: destination array @@ -477,6 +473,11 @@ setArrayFromSequence(PyArrayObject *a, PyObject *s, if (dst == NULL) dst = a; + /* + * This code is to ensure that the sequence access below will + * return a lower-dimensional sequence. + */ + /* INCREF on entry DECREF on exit */ Py_INCREF(s); @@ -502,11 +503,6 @@ setArrayFromSequence(PyArrayObject *a, PyObject *s, return 0; } - /* - * This code is to ensure that the sequence access below will - * return a lower-dimensional sequence. - */ - if (dim > PyArray_NDIM(a)) { PyErr_Format(PyExc_ValueError, "setArrayFromSequence: sequence/array dimensions mismatch."); @@ -517,27 +513,6 @@ setArrayFromSequence(PyArrayObject *a, PyObject *s, if (slen < 0) { goto fail; } - if (slen > 0) { - /* gh-13659: try __array__ before using s as a sequence */ - PyObject *tmp = _array_from_array_like(s, /*dtype*/NULL, /*writeable*/0, - /*context*/NULL); - if (tmp == NULL) { - goto fail; - } - else if (tmp == Py_NotImplemented) { - Py_DECREF(tmp); - } - else { - int r = PyArray_CopyInto(dst, (PyArrayObject *)tmp); - Py_DECREF(tmp); - if (r < 0) { - goto fail; - } - Py_DECREF(s); - return 0; - } - } - /* * Either the dimensions match, or the sequence has length 1 and can * be broadcast to the destination. @@ -1603,90 +1578,6 @@ fail: } - -/* - * Attempts to extract an array from an array-like object. - * - * array-like is defined as either - * - * * an object implementing the PEP 3118 buffer interface; - * * an object with __array_struct__ or __array_interface__ attributes; - * * an object with an __array__ function. - * - * Returns Py_NotImplemented if a given object is not array-like; - * PyArrayObject* in case of success and NULL in case of failure. - */ -NPY_NO_EXPORT PyObject * -_array_from_array_like(PyObject *op, PyArray_Descr *requested_dtype, - npy_bool writeable, PyObject *context) { - PyObject* tmp; - - /* If op supports the PEP 3118 buffer interface */ - if (!PyBytes_Check(op) && !PyUnicode_Check(op)) { - PyObject *memoryview = PyMemoryView_FromObject(op); - if (memoryview == NULL) { - PyErr_Clear(); - } - else { - tmp = _array_from_buffer_3118(memoryview); - Py_DECREF(memoryview); - if (tmp == NULL) { - return NULL; - } - - if (writeable - && PyArray_FailUnlessWriteable((PyArrayObject *) tmp, "PEP 3118 buffer") < 0) { - Py_DECREF(tmp); - return NULL; - } - - return tmp; - } - } - - /* If op supports the __array_struct__ or __array_interface__ interface */ - tmp = PyArray_FromStructInterface(op); - if (tmp == NULL) { - return NULL; - } - if (tmp == Py_NotImplemented) { - tmp = PyArray_FromInterface(op); - if (tmp == NULL) { - return NULL; - } - } - - /* - * If op supplies the __array__ function. - * The documentation says this should produce a copy, so - * we skip this method if writeable is true, because the intent - * of writeable is to modify the operand. - * XXX: If the implementation is wrong, and/or if actual - * usage requires this behave differently, - * this should be changed! - */ - if (!writeable && tmp == Py_NotImplemented) { - tmp = PyArray_FromArrayAttr(op, requested_dtype, context); - if (tmp == NULL) { - return NULL; - } - } - - if (tmp != Py_NotImplemented) { - if (writeable - && PyArray_FailUnlessWriteable((PyArrayObject *) tmp, - "array interface object") < 0) { - Py_DECREF(tmp); - return NULL; - } - return tmp; - } - - Py_INCREF(Py_NotImplemented); - return Py_NotImplemented; -} - - /*NUMPY_API * Retrieves the array parameters for viewing/converting an arbitrary * PyObject* to a NumPy array. This allows the "innate type and shape" @@ -1794,20 +1685,69 @@ PyArray_GetArrayParamsFromObject(PyObject *op, return 0; } - /* If op is an array-like */ - tmp = _array_from_array_like(op, requested_dtype, writeable, context); + /* If op supports the PEP 3118 buffer interface */ + if (!PyBytes_Check(op) && !PyUnicode_Check(op)) { + + PyObject *memoryview = PyMemoryView_FromObject(op); + if (memoryview == NULL) { + PyErr_Clear(); + } + else { + PyObject *arr = _array_from_buffer_3118(memoryview); + Py_DECREF(memoryview); + if (arr == NULL) { + return -1; + } + if (writeable + && PyArray_FailUnlessWriteable((PyArrayObject *)arr, "PEP 3118 buffer") < 0) { + Py_DECREF(arr); + return -1; + } + *out_arr = (PyArrayObject *)arr; + return 0; + } + } + + /* If op supports the __array_struct__ or __array_interface__ interface */ + tmp = PyArray_FromStructInterface(op); if (tmp == NULL) { return -1; } - else if (tmp != Py_NotImplemented) { - *out_arr = (PyArrayObject*) tmp; - return 0; + if (tmp == Py_NotImplemented) { + tmp = PyArray_FromInterface(op); + if (tmp == NULL) { + return -1; + } } - else { - Py_DECREF(Py_NotImplemented); + if (tmp != Py_NotImplemented) { + if (writeable + && PyArray_FailUnlessWriteable((PyArrayObject *)tmp, + "array interface object") < 0) { + Py_DECREF(tmp); + return -1; + } + *out_arr = (PyArrayObject *)tmp; + return (*out_arr) == NULL ? -1 : 0; + } + + /* + * If op supplies the __array__ function. + * The documentation says this should produce a copy, so + * we skip this method if writeable is true, because the intent + * of writeable is to modify the operand. + * XXX: If the implementation is wrong, and/or if actual + * usage requires this behave differently, + * this should be changed! + */ + if (!writeable) { + tmp = PyArray_FromArrayAttr(op, requested_dtype, context); + if (tmp != Py_NotImplemented) { + *out_arr = (PyArrayObject *)tmp; + return (*out_arr) == NULL ? -1 : 0; + } } - /* Try to treat op as a list of lists or array-like objects. */ + /* Try to treat op as a list of lists */ if (!writeable && PySequence_Check(op)) { int check_it, stop_at_string, stop_at_tuple, is_object; int type_num, type; diff --git a/numpy/core/src/multiarray/scalartypes.c.src b/numpy/core/src/multiarray/scalartypes.c.src index 32d712e0c..5da7f7738 100644 --- a/numpy/core/src/multiarray/scalartypes.c.src +++ b/numpy/core/src/multiarray/scalartypes.c.src @@ -4060,8 +4060,11 @@ initialize_casting_tables(void) _npy_can_cast_safely_table[_FROM_NUM][NPY_STRING] = 1; _npy_can_cast_safely_table[_FROM_NUM][NPY_UNICODE] = 1; - /* Allow casts from any integer to the TIMEDELTA type */ -#if @from_isint@ || @from_isuint@ +#if @from_isint@ && NPY_SIZEOF_TIMEDELTA >= _FROM_BSIZE + /* Allow casts from smaller or equal signed integers to the TIMEDELTA type */ + _npy_can_cast_safely_table[_FROM_NUM][NPY_TIMEDELTA] = 1; +#elif @from_isuint@ && NPY_SIZEOF_TIMEDELTA > _FROM_BSIZE + /* Allow casts from smaller unsigned integers to the TIMEDELTA type */ _npy_can_cast_safely_table[_FROM_NUM][NPY_TIMEDELTA] = 1; #endif diff --git a/numpy/core/src/npysort/npysort_common.h b/numpy/core/src/npysort/npysort_common.h index 5fd03b96f..30c0d47f3 100644 --- a/numpy/core/src/npysort/npysort_common.h +++ b/numpy/core/src/npysort/npysort_common.h @@ -329,6 +329,14 @@ UNICODE_LT(const npy_ucs4 *s1, const npy_ucs4 *s2, size_t len) NPY_INLINE static int DATETIME_LT(npy_datetime a, npy_datetime b) { + if (a == NPY_DATETIME_NAT) { + return 0; + } + + if (b == NPY_DATETIME_NAT) { + return 1; + } + return a < b; } diff --git a/numpy/core/src/umath/loops.c.src b/numpy/core/src/umath/loops.c.src index cb627800b..8a2e5bc40 100644 --- a/numpy/core/src/umath/loops.c.src +++ b/numpy/core/src/umath/loops.c.src @@ -235,7 +235,11 @@ PyUFunc_O_O_method(char **args, npy_intp *dimensions, npy_intp *steps, void *fun PyObject **out = (PyObject **)op1; PyObject *ret, *func; func = PyObject_GetAttrString(in1 ? in1 : Py_None, meth); - if (func == NULL || !PyCallable_Check(func)) { + if (func != NULL && !PyCallable_Check(func)) { + Py_DECREF(func); + func = NULL; + } + if (func == NULL) { PyObject *exc, *val, *tb; PyTypeObject *type = in1 ? Py_TYPE(in1) : Py_TYPE(Py_None); PyErr_Fetch(&exc, &val, &tb); @@ -1097,6 +1101,12 @@ NPY_NO_EXPORT void } NPY_NO_EXPORT void +@TYPE@_isinf(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(func)) +{ + UNARY_LOOP_FAST(npy_bool, npy_bool, (void)in; *out = NPY_FALSE); +} + +NPY_NO_EXPORT void @TYPE@__ones_like(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(data)) { OUTPUT_LOOP { @@ -1157,6 +1167,29 @@ NPY_NO_EXPORT void } /**end repeat1**/ +/**begin repeat1 + * #kind = fmax, fmin# + * #OP = >=, <=# + **/ +NPY_NO_EXPORT void +@TYPE@_@kind@(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(func)) +{ + BINARY_LOOP { + const @type@ in1 = *(@type@ *)ip1; + const @type@ in2 = *(@type@ *)ip2; + if (in1 == NPY_DATETIME_NAT) { + *((@type@ *)op1) = in2; + } + else if (in2 == NPY_DATETIME_NAT) { + *((@type@ *)op1) = in1; + } + else { + *((@type@ *)op1) = in1 @OP@ in2 ? in1 : in2; + } + } +} +/**end repeat1**/ + /**end repeat**/ NPY_NO_EXPORT void diff --git a/numpy/core/src/umath/loops.h.src b/numpy/core/src/umath/loops.h.src index 0ef14a809..7558de0bb 100644 --- a/numpy/core/src/umath/loops.h.src +++ b/numpy/core/src/umath/loops.h.src @@ -478,6 +478,11 @@ NPY_NO_EXPORT void @TYPE@_isfinite(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(func)); NPY_NO_EXPORT void +@TYPE@_isinf(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(func)); + +#define @TYPE@_isnan @TYPE@_isnat + +NPY_NO_EXPORT void @TYPE@__ones_like(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(data)); /**begin repeat1 @@ -489,8 +494,7 @@ NPY_NO_EXPORT void /**end repeat1**/ /**begin repeat1 - * #kind = maximum, minimum# - * #OP = >, <# + * #kind = maximum, minimum, fmin, fmax# **/ NPY_NO_EXPORT void @TYPE@_@kind@(char **args, npy_intp *dimensions, npy_intp *steps, void *NPY_UNUSED(func)); @@ -554,10 +558,6 @@ TIMEDELTA_mm_qm_divmod(char **args, npy_intp *dimensions, npy_intp *steps, void #define TIMEDELTA_mq_m_floor_divide TIMEDELTA_mq_m_divide #define TIMEDELTA_md_m_floor_divide TIMEDELTA_md_m_divide /* #define TIMEDELTA_mm_d_floor_divide TIMEDELTA_mm_d_divide */ -#define TIMEDELTA_fmin TIMEDELTA_minimum -#define TIMEDELTA_fmax TIMEDELTA_maximum -#define DATETIME_fmin DATETIME_minimum -#define DATETIME_fmax DATETIME_maximum /* ***************************************************************************** diff --git a/numpy/core/tests/test_datetime.py b/numpy/core/tests/test_datetime.py index a756dc7e7..41b84a69f 100644 --- a/numpy/core/tests/test_datetime.py +++ b/numpy/core/tests/test_datetime.py @@ -75,6 +75,15 @@ class TestDateTime(object): # Can cast safely/same_kind from integer to timedelta assert_(np.can_cast('i8', 'm8', casting='same_kind')) assert_(np.can_cast('i8', 'm8', casting='safe')) + assert_(np.can_cast('i4', 'm8', casting='same_kind')) + assert_(np.can_cast('i4', 'm8', casting='safe')) + assert_(np.can_cast('u4', 'm8', casting='same_kind')) + assert_(np.can_cast('u4', 'm8', casting='safe')) + + # Cannot cast safely from unsigned integer of the same size, which + # could overflow + assert_(np.can_cast('u8', 'm8', casting='same_kind')) + assert_(not np.can_cast('u8', 'm8', casting='safe')) # Cannot cast safely/same_kind from float to timedelta assert_(not np.can_cast('f4', 'm8', casting='same_kind')) @@ -136,6 +145,38 @@ class TestDateTime(object): assert_(np.datetime64('NaT') != np.datetime64('NaT', 'us')) assert_(np.datetime64('NaT', 'us') != np.datetime64('NaT')) + + + @pytest.mark.parametrize("size", [ + 3, 21, 217, 1000]) + def test_nat_argsort_stability(self, size): + # NaT < NaT should be False internally for + # sort stability + expected = np.arange(size) + arr = np.tile(np.datetime64('NaT'), size) + assert_equal(np.argsort(arr, kind='mergesort'), expected) + + @pytest.mark.parametrize("arr, expected", [ + # the example provided in gh-12629 + (np.array(['NaT', 1, 2, 3], dtype='M8[ns]'), + np.array([1, 2, 3, 'NaT'], dtype='M8[ns]')), + # multiple NaTs + (np.array(['NaT', 9, 'NaT', -707], dtype='M8[s]'), + np.array([-707, 9, 'NaT', 'NaT'], dtype='M8[s]')), + # this sort explores another code path for NaT + (np.array([1, -2, 3, 'NaT'], dtype='M8[ns]'), + np.array([-2, 1, 3, 'NaT'], dtype='M8[ns]')), + # 2-D array + (np.array([[51, -220, 'NaT'], + [-17, 'NaT', -90]], dtype='M8[us]'), + np.array([[-220, 51, 'NaT'], + [-90, -17, 'NaT']], dtype='M8[us]')), + ]) + def test_sort_nat(self, arr, expected): + # fix for gh-12629; NaT sorting to end of array + arr.sort() + assert_equal(arr, expected) + def test_datetime_scalar_construction(self): # Construct with different units assert_equal(np.datetime64('1950-03-12', 'D'), @@ -1361,6 +1402,10 @@ class TestDateTime(object): assert_equal(np.minimum(dtnat, a), dtnat) assert_equal(np.maximum(a, dtnat), dtnat) assert_equal(np.maximum(dtnat, a), dtnat) + assert_equal(np.fmin(dtnat, a), a) + assert_equal(np.fmin(a, dtnat), a) + assert_equal(np.fmax(dtnat, a), a) + assert_equal(np.fmax(a, dtnat), a) # Also do timedelta a = np.array(3, dtype='m8[h]') @@ -2232,7 +2277,7 @@ class TestDateTime(object): continue assert_raises(TypeError, np.isnat, np.zeros(10, t)) - def test_isfinite(self): + def test_isfinite_scalar(self): assert_(not np.isfinite(np.datetime64('NaT', 'ms'))) assert_(not np.isfinite(np.datetime64('NaT', 'ns'))) assert_(np.isfinite(np.datetime64('2038-01-19T03:14:07'))) @@ -2240,18 +2285,25 @@ class TestDateTime(object): assert_(not np.isfinite(np.timedelta64('NaT', "ms"))) assert_(np.isfinite(np.timedelta64(34, "ms"))) - res = np.array([True, True, False]) - for unit in ['Y', 'M', 'W', 'D', - 'h', 'm', 's', 'ms', 'us', - 'ns', 'ps', 'fs', 'as']: - arr = np.array([123, -321, "NaT"], dtype='<datetime64[%s]' % unit) - assert_equal(np.isfinite(arr), res) - arr = np.array([123, -321, "NaT"], dtype='>datetime64[%s]' % unit) - assert_equal(np.isfinite(arr), res) - arr = np.array([123, -321, "NaT"], dtype='<timedelta64[%s]' % unit) - assert_equal(np.isfinite(arr), res) - arr = np.array([123, -321, "NaT"], dtype='>timedelta64[%s]' % unit) - assert_equal(np.isfinite(arr), res) + @pytest.mark.parametrize('unit', ['Y', 'M', 'W', 'D', 'h', 'm', 's', 'ms', + 'us', 'ns', 'ps', 'fs', 'as']) + @pytest.mark.parametrize('dstr', ['<datetime64[%s]', '>datetime64[%s]', + '<timedelta64[%s]', '>timedelta64[%s]']) + def test_isfinite_isinf_isnan_units(self, unit, dstr): + '''check isfinite, isinf, isnan for all units of <M, >M, <m, >m dtypes + ''' + arr_val = [123, -321, "NaT"] + arr = np.array(arr_val, dtype= dstr % unit) + pos = np.array([True, True, False]) + neg = np.array([False, False, True]) + false = np.array([False, False, False]) + assert_equal(np.isfinite(arr), pos) + assert_equal(np.isinf(arr), false) + assert_equal(np.isnan(arr), neg) + + def test_assert_equal(self): + assert_raises(AssertionError, assert_equal, + np.datetime64('nat'), np.timedelta64('nat')) def test_corecursive_input(self): # construct a co-recursive list diff --git a/numpy/core/tests/test_function_base.py b/numpy/core/tests/test_function_base.py index 84b60b19c..c8a7cb6ce 100644 --- a/numpy/core/tests/test_function_base.py +++ b/numpy/core/tests/test_function_base.py @@ -351,14 +351,20 @@ class TestLinspace(object): arange(j+1, dtype=int)) def test_retstep(self): - y = linspace(0, 1, 2, retstep=True) - assert_(isinstance(y, tuple) and len(y) == 2) - for num in (0, 1): - for ept in (False, True): + for num in [0, 1, 2]: + for ept in [False, True]: y = linspace(0, 1, num, endpoint=ept, retstep=True) - assert_(isinstance(y, tuple) and len(y) == 2 and - len(y[0]) == num and isnan(y[1]), - 'num={0}, endpoint={1}'.format(num, ept)) + assert isinstance(y, tuple) and len(y) == 2 + if num == 2: + y0_expect = [0.0, 1.0] if ept else [0.0, 0.5] + assert_array_equal(y[0], y0_expect) + assert_equal(y[1], y0_expect[1]) + elif num == 1 and not ept: + assert_array_equal(y[0], [0.0]) + assert_equal(y[1], 1.0) + else: + assert_array_equal(y[0], [0.0][:num]) + assert isnan(y[1]) def test_object(self): start = array(1, dtype='O') diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py index 218106a63..22d550ecc 100644 --- a/numpy/core/tests/test_multiarray.py +++ b/numpy/core/tests/test_multiarray.py @@ -970,29 +970,6 @@ class TestCreation(object): assert_equal(np.array([long(4), 2**80, long(4)]).dtype, object) assert_equal(np.array([2**80, long(4)]).dtype, object) - def test_sequence_of_array_like(self): - class ArrayLike: - def __init__(self): - self.__array_interface__ = { - "shape": (42,), - "typestr": "<i1", - "data": bytes(42) - } - - # Make sure __array_*__ is used instead of Sequence methods. - def __iter__(self): - raise AssertionError("__iter__ was called") - - def __getitem__(self, idx): - raise AssertionError("__getitem__ was called") - - def __len__(self): - return 42 - - assert_equal( - np.array([ArrayLike()]), - np.zeros((1, 42), dtype=np.byte)) - def test_non_sequence_sequence(self): """Should not segfault. diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index b215163ae..f2f9c1457 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -2487,26 +2487,6 @@ class TestRegression(object): np.array([T()]) - def test_2d__array__shape(self): - class T(object): - def __array__(self): - return np.ndarray(shape=(0,0)) - - # Make sure __array__ is used instead of Sequence methods. - def __iter__(self): - return iter([]) - - def __getitem__(self, idx): - raise AssertionError("__getitem__ was called") - - def __len__(self): - return 0 - - - t = T() - #gh-13659, would raise in broadcasting [x=t for x in result] - np.array([t]) - @pytest.mark.skipif(sys.maxsize < 2 ** 31 + 1, reason='overflows 32-bit python') @pytest.mark.skipif(sys.platform == 'win32' and sys.version_info[:2] < (3, 8), reason='overflows on windows, fixed in bpo-16865') diff --git a/numpy/core/tests/test_scalarmath.py b/numpy/core/tests/test_scalarmath.py index 854df5590..c84380cd9 100644 --- a/numpy/core/tests/test_scalarmath.py +++ b/numpy/core/tests/test_scalarmath.py @@ -11,7 +11,7 @@ import numpy as np from numpy.testing import ( assert_, assert_equal, assert_raises, assert_almost_equal, assert_array_equal, IS_PYPY, suppress_warnings, _gen_alignment_data, - assert_warns + assert_warns, assert_raises_regex, ) types = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc, np.uintc, @@ -293,6 +293,16 @@ class TestModulus(object): rem = operator.mod(finf, fone) assert_(np.isnan(rem), 'dt: %s' % dt) + def test_inplace_floordiv_handling(self): + # issue gh-12927 + # this only applies to in-place floordiv //=, because the output type + # promotes to float which does not fit + a = np.array([1, 2], np.int64) + b = np.array([1, 2], np.uint64) + pattern = 'could not be coerced to provided output parameter' + with assert_raises_regex(TypeError, pattern): + a //= b + class TestComplexDivision(object): def test_zero_division(self): diff --git a/numpy/core/tests/test_ufunc.py b/numpy/core/tests/test_ufunc.py index 526925ece..7109de776 100644 --- a/numpy/core/tests/test_ufunc.py +++ b/numpy/core/tests/test_ufunc.py @@ -18,6 +18,11 @@ from numpy.testing import ( from numpy.compat import pickle +UNARY_UFUNCS = [obj for obj in np.core.umath.__dict__.values() + if isinstance(obj, np.ufunc)] +UNARY_OBJECT_UFUNCS = [uf for uf in UNARY_UFUNCS if "O->O" in uf.types] + + class TestUfuncKwargs(object): def test_kwarg_exact(self): assert_raises(TypeError, np.add, 1, 2, castingx='safe') @@ -124,7 +129,7 @@ class TestUfuncGenericLoops(object): x = np.ones(10, dtype=object) assert_(np.all(np.abs(x) == 1)) - def test_unary_PyUFunc_O_O_method(self, foo=foo): + def test_unary_PyUFunc_O_O_method_simple(self, foo=foo): x = np.full(10, foo(), dtype=object) assert_(np.all(np.conjugate(x) == True)) @@ -140,6 +145,39 @@ class TestUfuncGenericLoops(object): x = np.full((10, 2, 3), foo(), dtype=object) assert_(np.all(np.logical_xor(x, x))) + def test_python_complex_conjugate(self): + # The conjugate ufunc should fall back to calling the method: + arr = np.array([1+2j, 3-4j], dtype="O") + assert isinstance(arr[0], complex) + res = np.conjugate(arr) + assert res.dtype == np.dtype("O") + assert_array_equal(res, np.array([1-2j, 3+4j], dtype="O")) + + @pytest.mark.parametrize("ufunc", UNARY_OBJECT_UFUNCS) + def test_unary_PyUFunc_O_O_method_full(self, ufunc): + """Compare the result of the object loop with non-object one""" + val = np.float64(np.pi/4) + + class MyFloat(np.float64): + def __getattr__(self, attr): + try: + return super().__getattr__(attr) + except AttributeError: + return lambda: getattr(np.core.umath, attr)(val) + + num_arr = np.array([val], dtype=np.float64) + obj_arr = np.array([MyFloat(val)], dtype="O") + + with np.errstate(all="raise"): + try: + res_num = ufunc(num_arr) + except Exception as exc: + with assert_raises(type(exc)): + ufunc(obj_arr) + else: + res_obj = ufunc(obj_arr) + assert_array_equal(res_num.astype("O"), res_obj) + class TestUfunc(object): def test_pickle(self): diff --git a/numpy/distutils/misc_util.py b/numpy/distutils/misc_util.py index 7ba8ad862..d46ff8981 100644 --- a/numpy/distutils/misc_util.py +++ b/numpy/distutils/misc_util.py @@ -2329,8 +2329,11 @@ def generate_config_py(target): extra_dll_dir = os.path.join(os.path.dirname(__file__), '.libs') if sys.platform == 'win32' and os.path.isdir(extra_dll_dir): - os.environ.setdefault('PATH', '') - os.environ['PATH'] += os.pathsep + extra_dll_dir + if sys.version_info >= (3, 8): + os.add_dll_directory(extra_dll_dir) + else: + os.environ.setdefault('PATH', '') + os.environ['PATH'] += os.pathsep + extra_dll_dir """)) diff --git a/numpy/distutils/system_info.py b/numpy/distutils/system_info.py index c2b3e118b..fc2902b78 100644 --- a/numpy/distutils/system_info.py +++ b/numpy/distutils/system_info.py @@ -21,9 +21,12 @@ classes are available: blas_info lapack_info openblas_info + openblas64__info blis_info blas_opt_info # usage recommended lapack_opt_info # usage recommended + blas64__opt_info # usage recommended + lapack64__opt_info # usage recommended fftw_info,dfftw_info,sfftw_info fftw_threads_info,dfftw_threads_info,sfftw_threads_info djbfft_info @@ -406,6 +409,8 @@ def get_info(name, notfound_action=0): 'lapack_mkl': lapack_mkl_info, # use lapack_opt instead 'blas_mkl': blas_mkl_info, # use blas_opt instead 'accelerate': accelerate_info, # use blas_opt instead + 'openblas64_': openblas64__info, + 'openblas64__lapack': openblas64__lapack_info, 'x11': x11_info, 'fft_opt': fft_opt_info, 'fftw': fftw_info, @@ -428,7 +433,9 @@ def get_info(name, notfound_action=0): 'numarray': numarray_info, 'numerix': numerix_info, 'lapack_opt': lapack_opt_info, + 'lapack64__opt': lapack64__opt_info, 'blas_opt': blas_opt_info, + 'blas64__opt': blas64__opt_info, 'boost_python': boost_python_info, 'agg2': agg2_info, 'wx': wx_info, @@ -494,6 +501,14 @@ class LapackSrcNotFoundError(LapackNotFoundError): the LAPACK_SRC environment variable.""" +class Lapack64_NotFoundError(NotFoundError): + """ + 64-bit Lapack libraries with '64_' symbol suffix not found. + Known libraries in numpy/distutils/site.cfg file are: + openblas64_ + """ + + class BlasOptNotFoundError(NotFoundError): """ Optimized (vendor) Blas libraries are not found. @@ -508,6 +523,12 @@ class BlasNotFoundError(NotFoundError): numpy/distutils/site.cfg file (section [blas]) or by setting the BLAS environment variable.""" +class Blas64_NotFoundError(NotFoundError): + """ + 64-bit Blas libraries with '64_' symbol suffix not found. + Known libraries in numpy/distutils/site.cfg file are: + openblas64_ + """ class BlasSrcNotFoundError(BlasNotFoundError): """ @@ -1600,10 +1621,10 @@ def get_atlas_version(**config): class lapack_opt_info(system_info): - notfounderror = LapackNotFoundError - # Default order of LAPACK checks + # List of all known BLAS libraries, in the default order lapack_order = ['mkl', 'openblas', 'flame', 'atlas', 'accelerate', 'lapack'] + order_env_var_name = 'NPY_LAPACK_ORDER' def _calc_info_mkl(self): info = get_info('lapack_mkl') @@ -1696,7 +1717,7 @@ class lapack_opt_info(system_info): return False def calc_info(self): - user_order = os.environ.get('NPY_LAPACK_ORDER', None) + user_order = os.environ.get(self.order_env_var_name, None) if user_order is None: lapack_order = self.lapack_order else: @@ -1725,12 +1746,24 @@ class lapack_opt_info(system_info): warnings.warn(LapackNotFoundError.__doc__ or '', stacklevel=2) warnings.warn(LapackSrcNotFoundError.__doc__ or '', stacklevel=2) +class lapack64__opt_info(lapack_opt_info): + notfounderror = Lapack64_NotFoundError + lapack_order = ['openblas64_'] + order_env_var_name = 'NPY_LAPACK64__ORDER' -class blas_opt_info(system_info): + def _calc_info_openblas64_(self): + info = get_info('openblas64__lapack') + if info: + self.set_info(**info) + return True + return False + +class blas_opt_info(system_info): notfounderror = BlasNotFoundError - # Default order of BLAS checks + # List of all known BLAS libraries, in the default order blas_order = ['mkl', 'blis', 'openblas', 'atlas', 'accelerate', 'blas'] + order_env_var_name = 'NPY_BLAS_ORDER' def _calc_info_mkl(self): info = get_info('blas_mkl') @@ -1796,7 +1829,7 @@ class blas_opt_info(system_info): return True def calc_info(self): - user_order = os.environ.get('NPY_BLAS_ORDER', None) + user_order = os.environ.get(self.order_env_var_name, None) if user_order is None: blas_order = self.blas_order else: @@ -1824,6 +1857,19 @@ class blas_opt_info(system_info): warnings.warn(BlasSrcNotFoundError.__doc__ or '', stacklevel=2) +class blas64__opt_info(blas_opt_info): + notfounderror = Blas64_NotFoundError + blas_order = ['openblas64_'] + order_env_var_name = 'NPY_BLAS64__ORDER' + + def _calc_info_openblas64_(self): + info = get_info('openblas64_') + if info: + self.set_info(**info) + return True + return False + + class blas_info(system_info): section = 'blas' dir_env_var = 'BLAS' @@ -1923,12 +1969,10 @@ class openblas_info(blas_info): section = 'openblas' dir_env_var = 'OPENBLAS' _lib_names = ['openblas'] + _require_symbols = [] notfounderror = BlasNotFoundError - def check_embedded_lapack(self, info): - return True - - def calc_info(self): + def _calc_info(self): c = customized_ccompiler() lib_dirs = self.get_lib_dirs() @@ -1946,23 +1990,29 @@ class openblas_info(blas_info): # Try gfortran-compatible library files info = self.check_msvc_gfortran_libs(lib_dirs, openblas_libs) # Skip lapack check, we'd need build_ext to do it - assume_lapack = True + skip_symbol_check = True elif info: - assume_lapack = False + skip_symbol_check = False info['language'] = 'c' if info is None: - return + return None # Add extra info for OpenBLAS extra_info = self.calc_extra_info() dict_append(info, **extra_info) - if not (assume_lapack or self.check_embedded_lapack(info)): - return + if not (skip_symbol_check or self.check_symbols(info)): + return None info['define_macros'] = [('HAVE_CBLAS', None)] - self.set_info(**info) + + return info + + def calc_info(self): + info = self._calc_info() + if info is not None: + self.set_info(**info) def check_msvc_gfortran_libs(self, library_dirs, libraries): # First, find the full path to each library directory @@ -1995,24 +2045,23 @@ class openblas_info(blas_info): return info -class openblas_lapack_info(openblas_info): - section = 'openblas' - dir_env_var = 'OPENBLAS' - _lib_names = ['openblas'] - notfounderror = BlasNotFoundError - - def check_embedded_lapack(self, info): + def check_symbols(self, info): res = False c = customized_ccompiler() tmpdir = tempfile.mkdtemp() + + prototypes = "\n".join("void %s();" % symbol_name + for symbol_name in self._require_symbols) + calls = "\n".join("%s();" % symbol_name + for symbol_name in self._require_symbols) s = textwrap.dedent("""\ - void zungqr_(); + %(prototypes)s int main(int argc, const char *argv[]) { - zungqr_(); + %(calls)s return 0; - }""") + }""") % dict(prototypes=prototypes, calls=calls) src = os.path.join(tmpdir, 'source.c') out = os.path.join(tmpdir, 'a.out') # Add the additional "extra" arguments @@ -2037,9 +2086,38 @@ class openblas_lapack_info(openblas_info): shutil.rmtree(tmpdir) return res +class openblas_lapack_info(openblas_info): + section = 'openblas' + dir_env_var = 'OPENBLAS' + _lib_names = ['openblas'] + _require_symbols = ['zungqr_'] + notfounderror = BlasNotFoundError + class openblas_clapack_info(openblas_lapack_info): _lib_names = ['openblas', 'lapack'] +class openblas64__info(openblas_info): + section = 'openblas64_' + dir_env_var = 'OPENBLAS64_' + _lib_names = ['openblas64_'] + _require_symbols = ['dgemm_64_', 'cblas_dgemm64_'] + notfounderror = Blas64_NotFoundError + + def _calc_info(self): + info = super()._calc_info() + if info is not None: + info['define_macros'] = [('HAVE_CBLAS64_', None)] + return info + +class openblas64__lapack_info(openblas64__info): + _require_symbols = ['dgemm_64_', 'cblas_dgemm64_', 'zungqr_64_', 'LAPACKE_zungqr64_'] + + def _calc_info(self): + info = super()._calc_info() + if info: + info['define_macros'] += [('HAVE_LAPACKE64_', None)] + return info + class blis_info(blas_info): section = 'blis' dir_env_var = 'BLIS' diff --git a/numpy/f2py/cfuncs.py b/numpy/f2py/cfuncs.py index ccb7b3a32..cede06119 100644 --- a/numpy/f2py/cfuncs.py +++ b/numpy/f2py/cfuncs.py @@ -542,7 +542,7 @@ cppmacros[ 'ARRSIZE'] = '#define ARRSIZE(dims,rank) (_PyArray_multiply_list(dims,rank))' cppmacros['OLDPYNUM'] = """\ #ifdef OLDPYNUM -#error You need to install NumPy version 13 or higher. See https://scipy.org/install.html +#error You need to install NumPy version 0.13 or higher. See https://scipy.org/install.html #endif """ ################# C functions ############### diff --git a/numpy/f2py/crackfortran.py b/numpy/f2py/crackfortran.py index 2aaf5d7c6..2db4a47e8 100755 --- a/numpy/f2py/crackfortran.py +++ b/numpy/f2py/crackfortran.py @@ -558,7 +558,8 @@ groupbegins90 = groupbegins77 + \ r'|module(?!\s*procedure)|python\s*module|interface|type(?!\s*\()' beginpattern90 = re.compile( beforethisafter % ('', groupbegins90, groupbegins90, '.*'), re.I), 'begin' -groupends = r'end|endprogram|endblockdata|endmodule|endpythonmodule|endinterface' +groupends = (r'end|endprogram|endblockdata|endmodule|endpythonmodule|' + r'endinterface|endsubroutine|endfunction') endpattern = re.compile( beforethisafter % ('', groupends, groupends, r'[\w\s]*'), re.I), 'end' # endifs='end\s*(if|do|where|select|while|forall)' diff --git a/numpy/f2py/rules.py b/numpy/f2py/rules.py index f2f713bde..28eb9da30 100755 --- a/numpy/f2py/rules.py +++ b/numpy/f2py/rules.py @@ -1064,8 +1064,10 @@ if (#varname#_capi==Py_None) { '\tcapi_#varname#_tmp = array_from_pyobj(#atype#,#varname#_Dims,#varname#_Rank,capi_#varname#_intent,#varname#_capi);'}, """\ \tif (capi_#varname#_tmp == NULL) { -\t\tif (!PyErr_Occurred()) -\t\t\tPyErr_SetString(#modulename#_error,\"failed in converting #nth# `#varname#\' of #pyname# to C/Fortran array\" ); +\t\tPyObject *exc, *val, *tb; +\t\tPyErr_Fetch(&exc, &val, &tb); +\t\tPyErr_SetString(exc ? exc : #modulename#_error,\"failed in converting #nth# `#varname#\' of #pyname# to C/Fortran array\" ); +\t\tnpy_PyErr_ChainExceptionsCause(exc, val, tb); \t} else { \t\t#varname# = (#ctype# *)(PyArray_DATA(capi_#varname#_tmp)); """, @@ -1081,8 +1083,10 @@ if (#varname#_capi==Py_None) { \t\t\twhile ((_i = nextforcomb())) \t\t\t\t#varname#[capi_i++] = #init#; /* fortran way */ \t\t} else { -\t\t\tif (!PyErr_Occurred()) -\t\t\t\tPyErr_SetString(#modulename#_error,\"Initialization of #nth# #varname# failed (initforcomb).\"); +\t\t\tPyObject *exc, *val, *tb; +\t\t\tPyErr_Fetch(&exc, &val, &tb); +\t\t\tPyErr_SetString(exc ? exc : #modulename#_error,\"Initialization of #nth# #varname# failed (initforcomb).\"); +\t\t\tnpy_PyErr_ChainExceptionsCause(exc, val, tb); \t\t\tf2py_success = 0; \t\t} \t} diff --git a/numpy/f2py/src/fortranobject.c b/numpy/f2py/src/fortranobject.c index 8aa55555d..eb1050dd7 100644 --- a/numpy/f2py/src/fortranobject.c +++ b/numpy/f2py/src/fortranobject.c @@ -839,9 +839,10 @@ PyArrayObject* array_from_pyobj(const int type_num, if ((intent & F2PY_INTENT_INOUT) || (intent & F2PY_INTENT_INPLACE) || (intent & F2PY_INTENT_CACHE)) { - PyErr_SetString(PyExc_TypeError, - "failed to initialize intent(inout|inplace|cache) " - "array, input not an array"); + PyErr_Format(PyExc_TypeError, + "failed to initialize intent(inout|inplace|cache) " + "array, input '%s' object is not an array", + Py_TYPE(obj)->tp_name); return NULL; } diff --git a/numpy/f2py/src/fortranobject.h b/numpy/f2py/src/fortranobject.h index 5d0dcf676..21f1977eb 100644 --- a/numpy/f2py/src/fortranobject.h +++ b/numpy/f2py/src/fortranobject.h @@ -11,30 +11,7 @@ extern "C" { #endif #define PY_ARRAY_UNIQUE_SYMBOL _npy_f2py_ARRAY_API #include "numpy/arrayobject.h" - -/* - * Python 3 support macros - */ -#if PY_VERSION_HEX >= 0x03000000 -#define PyString_Check PyBytes_Check -#define PyString_GET_SIZE PyBytes_GET_SIZE -#define PyString_AS_STRING PyBytes_AS_STRING -#define PyString_FromString PyBytes_FromString -#define PyUString_FromStringAndSize PyUnicode_FromStringAndSize -#define PyString_ConcatAndDel PyBytes_ConcatAndDel -#define PyString_AsString PyBytes_AsString - -#define PyInt_Check PyLong_Check -#define PyInt_FromLong PyLong_FromLong -#define PyInt_AS_LONG PyLong_AsLong -#define PyInt_AsLong PyLong_AsLong - -#define PyNumber_Int PyNumber_Long - -#else - -#define PyUString_FromStringAndSize PyString_FromStringAndSize -#endif +#include "numpy/npy_3kcompat.h" #ifdef F2PY_REPORT_ATEXIT diff --git a/numpy/f2py/tests/test_crackfortran.py b/numpy/f2py/tests/test_crackfortran.py new file mode 100644 index 000000000..941696be3 --- /dev/null +++ b/numpy/f2py/tests/test_crackfortran.py @@ -0,0 +1,40 @@ +from __future__ import division, absolute_import, print_function + +import pytest + +import numpy as np +from numpy.testing import assert_array_equal +from . import util + + +class TestNoSpace(util.F2PyTest): + # issue gh-15035: add handling for endsubroutine, endfunction with no space + # between "end" and the block name + code = """ + subroutine subb(k) + real(8), intent(inout) :: k(:) + k=k+1 + endsubroutine + + subroutine subc(w,k) + real(8), intent(in) :: w(:) + real(8), intent(out) :: k(size(w)) + k=w+1 + endsubroutine + + function t0(value) + character value + character t0 + t0 = value + endfunction + """ + + def test_module(self): + k = np.array([1, 2, 3], dtype=np.float64) + w = np.array([1, 2, 3], dtype=np.float64) + self.module.subb(k) + assert_array_equal(k, w + 1) + self.module.subc([w, k]) + assert_array_equal(k, w + 1) + assert self.module.t0(23) == b'2' + diff --git a/numpy/lib/format.py b/numpy/lib/format.py index 1ecd72815..20e2e9c72 100644 --- a/numpy/lib/format.py +++ b/numpy/lib/format.py @@ -242,6 +242,16 @@ def read_magic(fp): major, minor = magic_str[-2:] return major, minor +def _has_metadata(dt): + if dt.metadata is not None: + return True + elif dt.names is not None: + return any(_has_metadata(dt[k]) for k in dt.names) + elif dt.subdtype is not None: + return _has_metadata(dt.base) + else: + return False + def dtype_to_descr(dtype): """ Get a serializable descriptor from the dtype. @@ -265,6 +275,10 @@ def dtype_to_descr(dtype): replicate the input dtype. """ + if _has_metadata(dtype): + warnings.warn("metadata on a dtype may be saved or ignored, but will " + "raise if saved when read. Use another form of storage.", + UserWarning, stacklevel=2) if dtype.names is not None: # This is a record array. The .descr is fine. XXX: parts of the # record array with an empty name, like padding bytes, still get diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 3ad630a7d..499120630 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -2305,7 +2305,7 @@ def cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, >>> m = np.arange(10, dtype=np.float64) >>> f = np.arange(10) * 2 >>> a = np.arange(10) ** 2. - >>> ddof = 9 # N - 1 + >>> ddof = 1 >>> w = f * a >>> v1 = np.sum(w) >>> v2 = np.sum(w * a) diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index 457cca146..8e2a34e70 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -95,7 +95,7 @@ def _replace_nan(a, val): NaNs, otherwise return None. """ - a = np.array(a, subok=True, copy=True) + a = np.asanyarray(a) if a.dtype == np.object_: # object arrays do not support `isnan` (gh-9009), so make a guess @@ -106,6 +106,7 @@ def _replace_nan(a, val): mask = None if mask is not None: + a = np.array(a, subok=True, copy=True) np.copyto(a, val, where=mask) return a, mask diff --git a/numpy/lib/npyio.py b/numpy/lib/npyio.py index 430d44374..3e54ff10c 100644 --- a/numpy/lib/npyio.py +++ b/numpy/lib/npyio.py @@ -833,7 +833,7 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None, fname : file, str, or pathlib.Path File, filename, or generator to read. If the filename extension is ``.gz`` or ``.bz2``, the file is first decompressed. Note that - generators should return byte strings for Python 3k. + generators should return byte strings. dtype : data-type, optional Data-type of the resulting array; default: float. If this is a structured data-type, the resulting array will be 1-dimensional, and @@ -1578,7 +1578,7 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None, fname : file, str, pathlib.Path, list of str, generator File, filename, list, or generator to read. If the filename extension is `.gz` or `.bz2`, the file is first decompressed. Note - that generators must return byte strings in Python 3k. The strings + that generators must return byte strings. The strings in a list or produced by a generator are treated as lines. dtype : dtype, optional Data type of the resulting array. diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index 92d52109e..dbb61c225 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -1,7 +1,6 @@ from __future__ import division, absolute_import, print_function import functools -import warnings import numpy.core.numeric as _nx from numpy.core.numeric import ( @@ -11,6 +10,7 @@ from numpy.core.fromnumeric import reshape, transpose from numpy.core.multiarray import normalize_axis_index from numpy.core import overrides from numpy.core import vstack, atleast_3d +from numpy.core.numeric import normalize_axis_tuple from numpy.core.shape_base import _arrays_for_stack_dispatcher from numpy.lib.index_tricks import ndindex from numpy.matrixlib.defmatrix import matrix # this raises all the right alarm bells @@ -29,7 +29,7 @@ array_function_dispatch = functools.partial( def _make_along_axis_idx(arr_shape, indices, axis): - # compute dimensions to iterate over + # compute dimensions to iterate over if not _nx.issubdtype(indices.dtype, _nx.integer): raise IndexError('`indices` must be an integer array') if len(arr_shape) != indices.ndim: @@ -517,22 +517,26 @@ def expand_dims(a, axis): Insert a new axis that will appear at the `axis` position in the expanded array shape. - .. note:: Previous to NumPy 1.13.0, neither ``axis < -a.ndim - 1`` nor - ``axis > a.ndim`` raised errors or put the new axis where documented. - Those axis values are now deprecated and will raise an AxisError in the - future. - Parameters ---------- a : array_like Input array. - axis : int - Position in the expanded axes where the new axis is placed. + axis : int or tuple of ints + Position in the expanded axes where the new axis (or axes) is placed. + + .. deprecated:: 1.13.0 + Passing an axis where ``axis > a.ndim`` will be treated as + ``axis == a.ndim``, and passing ``axis < -a.ndim - 1`` will + be treated as ``axis == 0``. This behavior is deprecated. + + .. versionchanged:: 1.18.0 + A tuple of axes is now supported. Out of range axes as + described above are now forbidden and raise an `AxisError`. Returns ------- - res : ndarray - View of `a` with the number of dimensions increased by one. + result : ndarray + View of `a` with the number of dimensions increased. See Also -------- @@ -542,11 +546,11 @@ def expand_dims(a, axis): Examples -------- - >>> x = np.array([1,2]) + >>> x = np.array([1, 2]) >>> x.shape (2,) - The following is equivalent to ``x[np.newaxis,:]`` or ``x[np.newaxis]``: + The following is equivalent to ``x[np.newaxis, :]`` or ``x[np.newaxis]``: >>> y = np.expand_dims(x, axis=0) >>> y @@ -554,13 +558,26 @@ def expand_dims(a, axis): >>> y.shape (1, 2) - >>> y = np.expand_dims(x, axis=1) # Equivalent to x[:,np.newaxis] + The following is equivalent to ``x[:, np.newaxis]``: + + >>> y = np.expand_dims(x, axis=1) >>> y array([[1], [2]]) >>> y.shape (2, 1) + ``axis`` may also be a tuple: + + >>> y = np.expand_dims(x, axis=(0, 1)) + >>> y + array([[[1, 2]]]) + + >>> y = np.expand_dims(x, axis=(2, 0)) + >>> y + array([[[1], + [2]]]) + Note that some examples may use ``None`` instead of ``np.newaxis``. These are the same objects: @@ -573,18 +590,16 @@ def expand_dims(a, axis): else: a = asanyarray(a) - shape = a.shape - if axis > a.ndim or axis < -a.ndim - 1: - # 2017-05-17, 1.13.0 - warnings.warn("Both axis > a.ndim and axis < -a.ndim - 1 are " - "deprecated and will raise an AxisError in the future.", - DeprecationWarning, stacklevel=3) - # When the deprecation period expires, delete this if block, - if axis < 0: - axis = axis + a.ndim + 1 - # and uncomment the following line. - # axis = normalize_axis_index(axis, a.ndim + 1) - return a.reshape(shape[:axis] + (1,) + shape[axis:]) + if type(axis) not in (tuple, list): + axis = (axis,) + + out_ndim = len(axis) + a.ndim + axis = normalize_axis_tuple(axis, out_ndim) + + shape_it = iter(a.shape) + shape = [1 if ax in axis else next(shape_it) for ax in range(out_ndim)] + + return a.reshape(shape) row_stack = vstack diff --git a/numpy/lib/tests/test_format.py b/numpy/lib/tests/test_format.py index 062c21725..0592e0b12 100644 --- a/numpy/lib/tests/test_format.py +++ b/numpy/lib/tests/test_format.py @@ -963,3 +963,33 @@ def test_unicode_field_names(): with open(fname, 'wb') as f: with assert_warns(UserWarning): format.write_array(f, arr, version=None) + + +@pytest.mark.parametrize('dt, fail', [ + (np.dtype({'names': ['a', 'b'], 'formats': [float, np.dtype('S3', + metadata={'some': 'stuff'})]}), True), + (np.dtype(int, metadata={'some': 'stuff'}), False), + (np.dtype([('subarray', (int, (2,)))], metadata={'some': 'stuff'}), False), + # recursive: metadata on the field of a dtype + (np.dtype({'names': ['a', 'b'], 'formats': [ + float, np.dtype({'names': ['c'], 'formats': [np.dtype(int, metadata={})]}) + ]}), False) + ]) +def test_metadata_dtype(dt, fail): + # gh-14142 + arr = np.ones(10, dtype=dt) + buf = BytesIO() + with assert_warns(UserWarning): + np.save(buf, arr) + buf.seek(0) + if fail: + with assert_raises(ValueError): + np.load(buf) + else: + arr2 = np.load(buf) + # BUG: assert_array_equal does not check metadata + from numpy.lib.format import _has_metadata + assert_array_equal(arr, arr2) + assert _has_metadata(arr.dtype) + assert not _has_metadata(arr2.dtype) + diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py index 6e2291ca3..a095e250a 100644 --- a/numpy/lib/tests/test_io.py +++ b/numpy/lib/tests/test_io.py @@ -24,6 +24,7 @@ from numpy.testing import ( assert_allclose, assert_array_equal, temppath, tempdir, IS_PYPY, HAS_REFCOUNT, suppress_warnings, assert_no_gc_cycles, assert_no_warnings ) +from numpy.testing._private.utils import requires_memory class TextIO(BytesIO): @@ -575,13 +576,9 @@ class TestSaveTxt(object): @pytest.mark.skipif(sys.platform=='win32', reason="large files cause problems") @pytest.mark.slow + @requires_memory(free_bytes=7e9) def test_large_zip(self): # The test takes at least 6GB of memory, writes a file larger than 4GB - try: - a = 'a' * 6 * 1024 * 1024 * 1024 - del a - except (MemoryError, OverflowError): - pytest.skip("Cannot allocate enough memory for test") test_data = np.asarray([np.random.rand(np.random.randint(50,100),4) for i in range(800000)]) with tempdir() as tmpdir: diff --git a/numpy/lib/tests/test_nanfunctions.py b/numpy/lib/tests/test_nanfunctions.py index b7261c63f..da2d0cc52 100644 --- a/numpy/lib/tests/test_nanfunctions.py +++ b/numpy/lib/tests/test_nanfunctions.py @@ -4,7 +4,7 @@ import warnings import pytest import numpy as np -from numpy.lib.nanfunctions import _nan_mask +from numpy.lib.nanfunctions import _nan_mask, _replace_nan from numpy.testing import ( assert_, assert_equal, assert_almost_equal, assert_no_warnings, assert_raises, assert_array_equal, suppress_warnings @@ -953,3 +953,30 @@ def test__nan_mask(arr, expected): # for types that can't possibly contain NaN if type(expected) is not np.ndarray: assert actual is True + + +def test__replace_nan(): + """ Test that _replace_nan returns the original array if there are no + NaNs, not a copy. + """ + for dtype in [np.bool, np.int32, np.int64]: + arr = np.array([0, 1], dtype=dtype) + result, mask = _replace_nan(arr, 0) + assert mask is None + # do not make a copy if there are no nans + assert result is arr + + for dtype in [np.float32, np.float64]: + arr = np.array([0, 1], dtype=dtype) + result, mask = _replace_nan(arr, 2) + assert (mask == False).all() + # mask is not None, so we make a copy + assert result is not arr + assert_equal(result, arr) + + arr_nan = np.array([0, 1, np.nan], dtype=dtype) + result_nan, mask_nan = _replace_nan(arr_nan, 2) + assert_equal(mask_nan, np.array([False, False, True])) + assert result_nan is not arr_nan + assert_equal(result_nan, np.array([0, 1, 2])) + assert np.isnan(arr_nan[-1]) diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index 01ea028bb..be1604a75 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -289,14 +289,26 @@ class TestExpandDims(object): assert_(b.shape[axis] == 1) assert_(np.squeeze(b).shape == s) - def test_deprecations(self): - # 2017-05-17, 1.13.0 + def test_axis_tuple(self): + a = np.empty((3, 3, 3)) + assert np.expand_dims(a, axis=(0, 1, 2)).shape == (1, 1, 1, 3, 3, 3) + assert np.expand_dims(a, axis=(0, -1, -2)).shape == (1, 3, 3, 3, 1, 1) + assert np.expand_dims(a, axis=(0, 3, 5)).shape == (1, 3, 3, 1, 3, 1) + assert np.expand_dims(a, axis=(0, -3, -5)).shape == (1, 1, 3, 1, 3, 3) + + def test_axis_out_of_range(self): s = (2, 3, 4, 5) a = np.empty(s) - with warnings.catch_warnings(): - warnings.simplefilter("always") - assert_warns(DeprecationWarning, expand_dims, a, -6) - assert_warns(DeprecationWarning, expand_dims, a, 5) + assert_raises(np.AxisError, expand_dims, a, -6) + assert_raises(np.AxisError, expand_dims, a, 5) + + a = np.empty((3, 3, 3)) + assert_raises(np.AxisError, expand_dims, a, (0, -6)) + assert_raises(np.AxisError, expand_dims, a, (0, 5)) + + def test_repeated_axis(self): + a = np.empty((3, 3, 3)) + assert_raises(ValueError, expand_dims, a, axis=(1, 1)) def test_subclasses(self): a = np.arange(10).reshape((2, 5)) diff --git a/numpy/lib/type_check.py b/numpy/lib/type_check.py index 586824743..977117235 100644 --- a/numpy/lib/type_check.py +++ b/numpy/lib/type_check.py @@ -68,16 +68,14 @@ def mintypecode(typechars, typeset='GDFgdf', default='d'): 'G' """ - typecodes = [(isinstance(t, str) and t) or asarray(t).dtype.char - for t in typechars] - intersection = [t for t in typecodes if t in typeset] + typecodes = ((isinstance(t, str) and t) or asarray(t).dtype.char + for t in typechars) + intersection = set(t for t in typecodes if t in typeset) if not intersection: return default if 'F' in intersection and 'd' in intersection: return 'D' - l = [(_typecodes_by_elsize.index(t), t) for t in intersection] - l.sort() - return l[0][1] + return min(intersection, key=_typecodes_by_elsize.index) def _asfarray_dispatcher(a, dtype=None): diff --git a/numpy/linalg/lapack_lite/python_xerbla.c b/numpy/linalg/lapack_lite/python_xerbla.c index dfc195556..c239a3620 100644 --- a/numpy/linalg/lapack_lite/python_xerbla.c +++ b/numpy/linalg/lapack_lite/python_xerbla.c @@ -1,4 +1,5 @@ #include "Python.h" +#include "numpy/npy_common.h" #undef c_abs #include "f2c.h" @@ -46,3 +47,11 @@ int xerbla_(char *srname, integer *info) return 0; } + + +/* Same for LAPACK64_ */ +npy_int64 xerbla_64_(char *srname, npy_int64 *info) +{ + integer info_int = (integer)*info; + return xerbla_(srname, &info_int); +} diff --git a/numpy/linalg/lapack_litemodule.c b/numpy/linalg/lapack_litemodule.c index 696a6d874..c80179fdf 100644 --- a/numpy/linalg/lapack_litemodule.c +++ b/numpy/linalg/lapack_litemodule.c @@ -7,45 +7,80 @@ More modifications by Jeff Whitaker #include "Python.h" #include "numpy/arrayobject.h" + +#ifndef NPY_UMATH_USE_BLAS64_ + +/* + * Standard BLAS + */ #ifdef NO_APPEND_FORTRAN # define FNAME(x) x #else # define FNAME(x) x##_ #endif +#define FINT_PYFMT "i" +typedef int fortran_int; + +#else + +/* + * BLAS64_ + */ + +#define FNAME(x) x##_64_ + +typedef npy_int64 fortran_int; + +#if NPY_BITSOF_SHORT == 64 +#define FINT_PYFMT "h" +#elif NPY_BITSOF_INT == 64 +#define FINT_PYFMT "i" +#elif NPY_BITSOF_LONG == 64 +#define FINT_PYFMT "l" +#elif NPY_BITSOF_LONGLONG == 64 +#define FINT_PYFMT "L" +#else +#error No compatible 64-bit integer size. \ + Please contact NumPy maintainers and give detailed information about your \ + compiler and platform, or set NPY_USE_BLAS64_=0 +#endif + +#endif + typedef struct { float r, i; } f2c_complex; typedef struct { double r, i; } f2c_doublecomplex; /* typedef long int (*L_fp)(); */ -extern int FNAME(dgelsd)(int *m, int *n, int *nrhs, - double a[], int *lda, double b[], int *ldb, - double s[], double *rcond, int *rank, - double work[], int *lwork, int iwork[], int *info); +extern fortran_int FNAME(dgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + double a[], fortran_int *lda, double b[], fortran_int *ldb, + double s[], double *rcond, fortran_int *rank, + double work[], fortran_int *lwork, fortran_int iwork[], fortran_int *info); -extern int FNAME(zgelsd)(int *m, int *n, int *nrhs, - f2c_doublecomplex a[], int *lda, - f2c_doublecomplex b[], int *ldb, - double s[], double *rcond, int *rank, - f2c_doublecomplex work[], int *lwork, - double rwork[], int iwork[], int *info); +extern fortran_int FNAME(zgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + f2c_doublecomplex a[], fortran_int *lda, + f2c_doublecomplex b[], fortran_int *ldb, + double s[], double *rcond, fortran_int *rank, + f2c_doublecomplex work[], fortran_int *lwork, + double rwork[], fortran_int iwork[], fortran_int *info); -extern int FNAME(dgeqrf)(int *m, int *n, double a[], int *lda, +extern fortran_int FNAME(dgeqrf)(fortran_int *m, fortran_int *n, double a[], fortran_int *lda, double tau[], double work[], - int *lwork, int *info); + fortran_int *lwork, fortran_int *info); -extern int FNAME(zgeqrf)(int *m, int *n, f2c_doublecomplex a[], int *lda, +extern fortran_int FNAME(zgeqrf)(fortran_int *m, fortran_int *n, f2c_doublecomplex a[], fortran_int *lda, f2c_doublecomplex tau[], f2c_doublecomplex work[], - int *lwork, int *info); + fortran_int *lwork, fortran_int *info); -extern int FNAME(dorgqr)(int *m, int *n, int *k, double a[], int *lda, +extern fortran_int FNAME(dorgqr)(fortran_int *m, fortran_int *n, fortran_int *k, double a[], fortran_int *lda, double tau[], double work[], - int *lwork, int *info); + fortran_int *lwork, fortran_int *info); -extern int FNAME(zungqr)(int *m, int *n, int *k, f2c_doublecomplex a[], - int *lda, f2c_doublecomplex tau[], - f2c_doublecomplex work[], int *lwork, int *info); +extern fortran_int FNAME(zungqr)(fortran_int *m, fortran_int *n, fortran_int *k, f2c_doublecomplex a[], + fortran_int *lda, f2c_doublecomplex tau[], + f2c_doublecomplex work[], fortran_int *lwork, fortran_int *info); -extern int FNAME(xerbla)(char *srname, int *info); +extern fortran_int FNAME(xerbla)(char *srname, fortran_int *info); static PyObject *LapackError; @@ -90,27 +125,31 @@ check_object(PyObject *ob, int t, char *obname, #define FDATA(p) ((float *) PyArray_DATA((PyArrayObject *)p)) #define CDATA(p) ((f2c_complex *) PyArray_DATA((PyArrayObject *)p)) #define ZDATA(p) ((f2c_doublecomplex *) PyArray_DATA((PyArrayObject *)p)) -#define IDATA(p) ((int *) PyArray_DATA((PyArrayObject *)p)) +#define IDATA(p) ((fortran_int *) PyArray_DATA((PyArrayObject *)p)) static PyObject * lapack_lite_dgelsd(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m; - int n; - int nrhs; + fortran_int lapack_lite_status; + fortran_int m; + fortran_int n; + fortran_int nrhs; PyObject *a; - int lda; + fortran_int lda; PyObject *b; - int ldb; + fortran_int ldb; PyObject *s; double rcond; - int rank; + fortran_int rank; PyObject *work; PyObject *iwork; - int lwork; - int info; - TRY(PyArg_ParseTuple(args,"iiiOiOiOdiOiOi:dgelsd", + fortran_int lwork; + fortran_int info; + + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT FINT_PYFMT "O" FINT_PYFMT "O" + FINT_PYFMT "O" "d" FINT_PYFMT "O" FINT_PYFMT "O" + FINT_PYFMT ":dgelsd"), &m,&n,&nrhs,&a,&lda,&b,&ldb,&s,&rcond, &rank,&work,&lwork,&iwork,&info)); @@ -118,7 +157,11 @@ lapack_lite_dgelsd(PyObject *NPY_UNUSED(self), PyObject *args) TRY(check_object(b,NPY_DOUBLE,"b","NPY_DOUBLE","dgelsd")); TRY(check_object(s,NPY_DOUBLE,"s","NPY_DOUBLE","dgelsd")); TRY(check_object(work,NPY_DOUBLE,"work","NPY_DOUBLE","dgelsd")); +#ifndef NPY_UMATH_USE_BLAS64_ TRY(check_object(iwork,NPY_INT,"iwork","NPY_INT","dgelsd")); +#else + TRY(check_object(iwork,NPY_INT64,"iwork","NPY_INT64","dgelsd")); +#endif lapack_lite_status = FNAME(dgelsd)(&m,&n,&nrhs,DDATA(a),&lda,DDATA(b),&ldb, @@ -128,8 +171,11 @@ lapack_lite_dgelsd(PyObject *NPY_UNUSED(self), PyObject *args) return NULL; } - return Py_BuildValue("{s:i,s:i,s:i,s:i,s:i,s:i,s:d,s:i,s:i,s:i}","dgelsd_", - lapack_lite_status,"m",m,"n",n,"nrhs",nrhs, + return Py_BuildValue(("{s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:d,s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT "}"), + "dgelsd_",lapack_lite_status,"m",m,"n",n,"nrhs",nrhs, "lda",lda,"ldb",ldb,"rcond",rcond,"rank",rank, "lwork",lwork,"info",info); } @@ -137,13 +183,16 @@ lapack_lite_dgelsd(PyObject *NPY_UNUSED(self), PyObject *args) static PyObject * lapack_lite_dgeqrf(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m, n, lwork; + fortran_int lapack_lite_status; + fortran_int m, n, lwork; PyObject *a, *tau, *work; - int lda; - int info; + fortran_int lda; + fortran_int info; - TRY(PyArg_ParseTuple(args,"iiOiOOii:dgeqrf",&m,&n,&a,&lda,&tau,&work,&lwork,&info)); + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT "O" FINT_PYFMT "OO" + FINT_PYFMT FINT_PYFMT ":dgeqrf"), + &m,&n,&a,&lda,&tau,&work,&lwork,&info)); /* check objects and convert to right storage order */ TRY(check_object(a,NPY_DOUBLE,"a","NPY_DOUBLE","dgeqrf")); @@ -157,7 +206,9 @@ lapack_lite_dgeqrf(PyObject *NPY_UNUSED(self), PyObject *args) return NULL; } - return Py_BuildValue("{s:i,s:i,s:i,s:i,s:i,s:i}","dgeqrf_", + return Py_BuildValue(("{s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT "}"), + "dgeqrf_", lapack_lite_status,"m",m,"n",n,"lda",lda, "lwork",lwork,"info",info); } @@ -166,13 +217,17 @@ lapack_lite_dgeqrf(PyObject *NPY_UNUSED(self), PyObject *args) static PyObject * lapack_lite_dorgqr(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m, n, k, lwork; + fortran_int lapack_lite_status; + fortran_int m, n, k, lwork; PyObject *a, *tau, *work; - int lda; - int info; - - TRY(PyArg_ParseTuple(args,"iiiOiOOii:dorgqr", &m, &n, &k, &a, &lda, &tau, &work, &lwork, &info)); + fortran_int lda; + fortran_int info; + + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT FINT_PYFMT "O" + FINT_PYFMT "OO" FINT_PYFMT FINT_PYFMT + ":dorgqr"), + &m, &n, &k, &a, &lda, &tau, &work, &lwork, &info)); TRY(check_object(a,NPY_DOUBLE,"a","NPY_DOUBLE","dorgqr")); TRY(check_object(tau,NPY_DOUBLE,"tau","NPY_DOUBLE","dorgqr")); TRY(check_object(work,NPY_DOUBLE,"work","NPY_DOUBLE","dorgqr")); @@ -191,23 +246,26 @@ lapack_lite_dorgqr(PyObject *NPY_UNUSED(self), PyObject *args) static PyObject * lapack_lite_zgelsd(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m; - int n; - int nrhs; + fortran_int lapack_lite_status; + fortran_int m; + fortran_int n; + fortran_int nrhs; PyObject *a; - int lda; + fortran_int lda; PyObject *b; - int ldb; + fortran_int ldb; PyObject *s; double rcond; - int rank; + fortran_int rank; PyObject *work; - int lwork; + fortran_int lwork; PyObject *rwork; PyObject *iwork; - int info; - TRY(PyArg_ParseTuple(args,"iiiOiOiOdiOiOOi:zgelsd", + fortran_int info; + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT FINT_PYFMT "O" FINT_PYFMT + "O" FINT_PYFMT "Od" FINT_PYFMT "O" FINT_PYFMT + "OO" FINT_PYFMT ":zgelsd"), &m,&n,&nrhs,&a,&lda,&b,&ldb,&s,&rcond, &rank,&work,&lwork,&rwork,&iwork,&info)); @@ -216,7 +274,11 @@ lapack_lite_zgelsd(PyObject *NPY_UNUSED(self), PyObject *args) TRY(check_object(s,NPY_DOUBLE,"s","NPY_DOUBLE","zgelsd")); TRY(check_object(work,NPY_CDOUBLE,"work","NPY_CDOUBLE","zgelsd")); TRY(check_object(rwork,NPY_DOUBLE,"rwork","NPY_DOUBLE","zgelsd")); +#ifndef NPY_UMATH_USE_BLAS64_ TRY(check_object(iwork,NPY_INT,"iwork","NPY_INT","zgelsd")); +#else + TRY(check_object(iwork,NPY_INT64,"iwork","NPY_INT64","zgelsd")); +#endif lapack_lite_status = FNAME(zgelsd)(&m,&n,&nrhs,ZDATA(a),&lda,ZDATA(b),&ldb,DDATA(s),&rcond, @@ -225,7 +287,11 @@ lapack_lite_zgelsd(PyObject *NPY_UNUSED(self), PyObject *args) return NULL; } - return Py_BuildValue("{s:i,s:i,s:i,s:i,s:i,s:i,s:i,s:i,s:i}","zgelsd_", + return Py_BuildValue(("{s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT ",s:" FINT_PYFMT + "}"), + "zgelsd_", lapack_lite_status,"m",m,"n",n,"nrhs",nrhs,"lda",lda, "ldb",ldb,"rank",rank,"lwork",lwork,"info",info); } @@ -233,13 +299,16 @@ lapack_lite_zgelsd(PyObject *NPY_UNUSED(self), PyObject *args) static PyObject * lapack_lite_zgeqrf(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m, n, lwork; + fortran_int lapack_lite_status; + fortran_int m, n, lwork; PyObject *a, *tau, *work; - int lda; - int info; + fortran_int lda; + fortran_int info; - TRY(PyArg_ParseTuple(args,"iiOiOOii:zgeqrf",&m,&n,&a,&lda,&tau,&work,&lwork,&info)); + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT "O" FINT_PYFMT "OO" + FINT_PYFMT "" FINT_PYFMT ":zgeqrf"), + &m,&n,&a,&lda,&tau,&work,&lwork,&info)); /* check objects and convert to right storage order */ TRY(check_object(a,NPY_CDOUBLE,"a","NPY_CDOUBLE","zgeqrf")); @@ -253,20 +322,27 @@ lapack_lite_zgeqrf(PyObject *NPY_UNUSED(self), PyObject *args) return NULL; } - return Py_BuildValue("{s:i,s:i,s:i,s:i,s:i,s:i}","zgeqrf_",lapack_lite_status,"m",m,"n",n,"lda",lda,"lwork",lwork,"info",info); + return Py_BuildValue(("{s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT + ",s:" FINT_PYFMT ",s:" FINT_PYFMT "}"), + "zgeqrf_",lapack_lite_status,"m",m,"n",n,"lda",lda,"lwork",lwork,"info",info); } static PyObject * lapack_lite_zungqr(PyObject *NPY_UNUSED(self), PyObject *args) { - int lapack_lite_status; - int m, n, k, lwork; + fortran_int lapack_lite_status; + fortran_int m, n, k, lwork; PyObject *a, *tau, *work; - int lda; - int info; - - TRY(PyArg_ParseTuple(args,"iiiOiOOii:zungqr", &m, &n, &k, &a, &lda, &tau, &work, &lwork, &info)); + fortran_int lda; + fortran_int info; + + TRY(PyArg_ParseTuple(args, + (FINT_PYFMT FINT_PYFMT FINT_PYFMT "O" + FINT_PYFMT "OO" FINT_PYFMT "" FINT_PYFMT + ":zungqr"), + &m, &n, &k, &a, &lda, &tau, &work, &lwork, &info)); TRY(check_object(a,NPY_CDOUBLE,"a","NPY_CDOUBLE","zungqr")); TRY(check_object(tau,NPY_CDOUBLE,"tau","NPY_CDOUBLE","zungqr")); TRY(check_object(work,NPY_CDOUBLE,"work","NPY_CDOUBLE","zungqr")); @@ -279,7 +355,8 @@ lapack_lite_zungqr(PyObject *NPY_UNUSED(self), PyObject *args) return NULL; } - return Py_BuildValue("{s:i,s:i}","zungqr_",lapack_lite_status, + return Py_BuildValue(("{s:" FINT_PYFMT ",s:" FINT_PYFMT "}"), + "zungqr_",lapack_lite_status, "info",info); } @@ -287,7 +364,7 @@ lapack_lite_zungqr(PyObject *NPY_UNUSED(self), PyObject *args) static PyObject * lapack_lite_xerbla(PyObject *NPY_UNUSED(self), PyObject *args) { - int info = -1; + fortran_int info = -1; NPY_BEGIN_THREADS_DEF; NPY_BEGIN_THREADS; diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index 665b9fbec..6249a57c2 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -2325,16 +2325,19 @@ def norm(x, ord=None, axis=None, keepdims=False): Parameters ---------- x : array_like - Input array. If `axis` is None, `x` must be 1-D or 2-D. + Input array. If `axis` is None, `x` must be 1-D or 2-D, unless `ord` + is None. If both `axis` and `ord` are None, the 2-norm of + ``x.ravel`` will be returned. ord : {non-zero int, inf, -inf, 'fro', 'nuc'}, optional Order of the norm (see table under ``Notes``). inf means numpy's - `inf` object. - axis : {int, 2-tuple of ints, None}, optional + `inf` object. The default is None. + axis : {None, int, 2-tuple of ints}, optional. If `axis` is an integer, it specifies the axis of `x` along which to compute the vector norms. If `axis` is a 2-tuple, it specifies the axes that hold 2-D matrices, and the matrix norms of these matrices are computed. If `axis` is None then either a vector norm (when `x` - is 1-D) or a matrix norm (when `x` is 2-D) is returned. + is 1-D) or a matrix norm (when `x` is 2-D) is returned. The default + is None. .. versionadded:: 1.8.0 @@ -2352,7 +2355,7 @@ def norm(x, ord=None, axis=None, keepdims=False): Notes ----- - For values of ``ord <= 0``, the result is, strictly speaking, not a + For values of ``ord < 1``, the result is, strictly speaking, not a mathematical 'norm', but it may still be useful for various numerical purposes. diff --git a/numpy/linalg/setup.py b/numpy/linalg/setup.py index 66c07c9e1..f5cb04e89 100644 --- a/numpy/linalg/setup.py +++ b/numpy/linalg/setup.py @@ -26,7 +26,12 @@ def configuration(parent_package='', top_path=None): ] all_sources = config.paths(lapack_lite_src) - lapack_info = get_info('lapack_opt', 0) # and {} + if (os.environ.get('NPY_USE_BLAS64_', "0") != "0"): + lapack_info = get_info('lapack64__opt', 2) + lapack_info.setdefault('define_macros', []) + lapack_info['define_macros'] += [('NPY_UMATH_USE_BLAS64_', None)] + else: + lapack_info = get_info('lapack_opt', 0) # and {} def get_lapack_lite_sources(ext, build_dir): if not lapack_info: diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 173e81e9c..bd3df1ca4 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -20,8 +20,9 @@ from numpy.linalg.linalg import _multi_dot_matrix_chain_order from numpy.testing import ( assert_, assert_equal, assert_raises, assert_array_equal, assert_almost_equal, assert_allclose, suppress_warnings, - assert_raises_regex, + assert_raises_regex, HAS_LAPACK64, ) +from numpy.testing._private.utils import requires_memory def consistent_subclass(out, in_): @@ -2002,3 +2003,16 @@ def test_unsupported_commontype(): arr = np.array([[1, -2], [2, 5]], dtype='float16') with assert_raises_regex(TypeError, "unsupported in linalg"): linalg.cholesky(arr) + + +@pytest.mark.slow +@pytest.mark.xfail(not HAS_LAPACK64, run=False, + reason="Numpy not compiled with 64-bit BLAS/LAPACK") +@requires_memory(free_bytes=16e9) +def test_blas64_dot(): + n = 2**32 + a = np.zeros([1, n], dtype=np.float32) + b = np.ones([1, 1], dtype=np.float32) + a[0,-1] = 1 + c = np.dot(b, a) + assert_equal(c[0,-1], 1) diff --git a/numpy/linalg/umath_linalg.c.src b/numpy/linalg/umath_linalg.c.src index ee103c327..b111f75d5 100644 --- a/numpy/linalg/umath_linalg.c.src +++ b/numpy/linalg/umath_linalg.c.src @@ -62,301 +62,318 @@ dbg_stack_trace() ***************************************************************************** */ +#ifndef NPY_UMATH_USE_BLAS64_ + #ifdef NO_APPEND_FORTRAN # define FNAME(x) x #else # define FNAME(x) x##_ #endif +typedef int fortran_int; + +#else + +#define FNAME(x) x##_64_ + +typedef npy_int64 fortran_int; + +#endif + typedef struct { float r, i; } f2c_complex; typedef struct { double r, i; } f2c_doublecomplex; /* typedef long int (*L_fp)(); */ -extern int -FNAME(sgeev)(char *jobvl, char *jobvr, int *n, - float a[], int *lda, float wr[], float wi[], - float vl[], int *ldvl, float vr[], int *ldvr, - float work[], int lwork[], - int *info); -extern int -FNAME(dgeev)(char *jobvl, char *jobvr, int *n, - double a[], int *lda, double wr[], double wi[], - double vl[], int *ldvl, double vr[], int *ldvr, - double work[], int lwork[], - int *info); -extern int -FNAME(cgeev)(char *jobvl, char *jobvr, int *n, - f2c_doublecomplex a[], int *lda, +typedef float fortran_real; +typedef double fortran_doublereal; +typedef f2c_complex fortran_complex; +typedef f2c_doublecomplex fortran_doublecomplex; + +extern fortran_int +FNAME(sgeev)(char *jobvl, char *jobvr, fortran_int *n, + float a[], fortran_int *lda, float wr[], float wi[], + float vl[], fortran_int *ldvl, float vr[], fortran_int *ldvr, + float work[], fortran_int lwork[], + fortran_int *info); +extern fortran_int +FNAME(dgeev)(char *jobvl, char *jobvr, fortran_int *n, + double a[], fortran_int *lda, double wr[], double wi[], + double vl[], fortran_int *ldvl, double vr[], fortran_int *ldvr, + double work[], fortran_int lwork[], + fortran_int *info); +extern fortran_int +FNAME(cgeev)(char *jobvl, char *jobvr, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, f2c_doublecomplex w[], - f2c_doublecomplex vl[], int *ldvl, - f2c_doublecomplex vr[], int *ldvr, - f2c_doublecomplex work[], int *lwork, + f2c_doublecomplex vl[], fortran_int *ldvl, + f2c_doublecomplex vr[], fortran_int *ldvr, + f2c_doublecomplex work[], fortran_int *lwork, double rwork[], - int *info); -extern int -FNAME(zgeev)(char *jobvl, char *jobvr, int *n, - f2c_doublecomplex a[], int *lda, + fortran_int *info); +extern fortran_int +FNAME(zgeev)(char *jobvl, char *jobvr, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, f2c_doublecomplex w[], - f2c_doublecomplex vl[], int *ldvl, - f2c_doublecomplex vr[], int *ldvr, - f2c_doublecomplex work[], int *lwork, + f2c_doublecomplex vl[], fortran_int *ldvl, + f2c_doublecomplex vr[], fortran_int *ldvr, + f2c_doublecomplex work[], fortran_int *lwork, double rwork[], - int *info); - -extern int -FNAME(ssyevd)(char *jobz, char *uplo, int *n, - float a[], int *lda, float w[], float work[], - int *lwork, int iwork[], int *liwork, - int *info); -extern int -FNAME(dsyevd)(char *jobz, char *uplo, int *n, - double a[], int *lda, double w[], double work[], - int *lwork, int iwork[], int *liwork, - int *info); -extern int -FNAME(cheevd)(char *jobz, char *uplo, int *n, - f2c_complex a[], int *lda, + fortran_int *info); + +extern fortran_int +FNAME(ssyevd)(char *jobz, char *uplo, fortran_int *n, + float a[], fortran_int *lda, float w[], float work[], + fortran_int *lwork, fortran_int iwork[], fortran_int *liwork, + fortran_int *info); +extern fortran_int +FNAME(dsyevd)(char *jobz, char *uplo, fortran_int *n, + double a[], fortran_int *lda, double w[], double work[], + fortran_int *lwork, fortran_int iwork[], fortran_int *liwork, + fortran_int *info); +extern fortran_int +FNAME(cheevd)(char *jobz, char *uplo, fortran_int *n, + f2c_complex a[], fortran_int *lda, float w[], f2c_complex work[], - int *lwork, float rwork[], int *lrwork, int iwork[], - int *liwork, - int *info); -extern int -FNAME(zheevd)(char *jobz, char *uplo, int *n, - f2c_doublecomplex a[], int *lda, + fortran_int *lwork, float rwork[], fortran_int *lrwork, fortran_int iwork[], + fortran_int *liwork, + fortran_int *info); +extern fortran_int +FNAME(zheevd)(char *jobz, char *uplo, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, double w[], f2c_doublecomplex work[], - int *lwork, double rwork[], int *lrwork, int iwork[], - int *liwork, - int *info); - -extern int -FNAME(sgelsd)(int *m, int *n, int *nrhs, - float a[], int *lda, float b[], int *ldb, - float s[], float *rcond, int *rank, - float work[], int *lwork, int iwork[], - int *info); -extern int -FNAME(dgelsd)(int *m, int *n, int *nrhs, - double a[], int *lda, double b[], int *ldb, - double s[], double *rcond, int *rank, - double work[], int *lwork, int iwork[], - int *info); -extern int -FNAME(cgelsd)(int *m, int *n, int *nrhs, - f2c_complex a[], int *lda, - f2c_complex b[], int *ldb, - float s[], float *rcond, int *rank, - f2c_complex work[], int *lwork, - float rwork[], int iwork[], - int *info); -extern int -FNAME(zgelsd)(int *m, int *n, int *nrhs, - f2c_doublecomplex a[], int *lda, - f2c_doublecomplex b[], int *ldb, - double s[], double *rcond, int *rank, - f2c_doublecomplex work[], int *lwork, - double rwork[], int iwork[], - int *info); - -extern int -FNAME(sgesv)(int *n, int *nrhs, - float a[], int *lda, - int ipiv[], - float b[], int *ldb, - int *info); -extern int -FNAME(dgesv)(int *n, int *nrhs, - double a[], int *lda, - int ipiv[], - double b[], int *ldb, - int *info); -extern int -FNAME(cgesv)(int *n, int *nrhs, - f2c_complex a[], int *lda, - int ipiv[], - f2c_complex b[], int *ldb, - int *info); -extern int -FNAME(zgesv)(int *n, int *nrhs, - f2c_doublecomplex a[], int *lda, - int ipiv[], - f2c_doublecomplex b[], int *ldb, - int *info); - -extern int -FNAME(sgetrf)(int *m, int *n, - float a[], int *lda, - int ipiv[], - int *info); -extern int -FNAME(dgetrf)(int *m, int *n, - double a[], int *lda, - int ipiv[], - int *info); -extern int -FNAME(cgetrf)(int *m, int *n, - f2c_complex a[], int *lda, - int ipiv[], - int *info); -extern int -FNAME(zgetrf)(int *m, int *n, - f2c_doublecomplex a[], int *lda, - int ipiv[], - int *info); - -extern int -FNAME(spotrf)(char *uplo, int *n, - float a[], int *lda, - int *info); -extern int -FNAME(dpotrf)(char *uplo, int *n, - double a[], int *lda, - int *info); -extern int -FNAME(cpotrf)(char *uplo, int *n, - f2c_complex a[], int *lda, - int *info); -extern int -FNAME(zpotrf)(char *uplo, int *n, - f2c_doublecomplex a[], int *lda, - int *info); - -extern int -FNAME(sgesdd)(char *jobz, int *m, int *n, - float a[], int *lda, float s[], float u[], - int *ldu, float vt[], int *ldvt, float work[], - int *lwork, int iwork[], int *info); -extern int -FNAME(dgesdd)(char *jobz, int *m, int *n, - double a[], int *lda, double s[], double u[], - int *ldu, double vt[], int *ldvt, double work[], - int *lwork, int iwork[], int *info); -extern int -FNAME(cgesdd)(char *jobz, int *m, int *n, - f2c_complex a[], int *lda, - float s[], f2c_complex u[], int *ldu, - f2c_complex vt[], int *ldvt, - f2c_complex work[], int *lwork, - float rwork[], int iwork[], int *info); -extern int -FNAME(zgesdd)(char *jobz, int *m, int *n, - f2c_doublecomplex a[], int *lda, - double s[], f2c_doublecomplex u[], int *ldu, - f2c_doublecomplex vt[], int *ldvt, - f2c_doublecomplex work[], int *lwork, - double rwork[], int iwork[], int *info); - -extern int -FNAME(spotrs)(char *uplo, int *n, int *nrhs, - float a[], int *lda, - float b[], int *ldb, - int *info); -extern int -FNAME(dpotrs)(char *uplo, int *n, int *nrhs, - double a[], int *lda, - double b[], int *ldb, - int *info); -extern int -FNAME(cpotrs)(char *uplo, int *n, int *nrhs, - f2c_complex a[], int *lda, - f2c_complex b[], int *ldb, - int *info); -extern int -FNAME(zpotrs)(char *uplo, int *n, int *nrhs, - f2c_doublecomplex a[], int *lda, - f2c_doublecomplex b[], int *ldb, - int *info); - -extern int -FNAME(spotri)(char *uplo, int *n, - float a[], int *lda, - int *info); -extern int -FNAME(dpotri)(char *uplo, int *n, - double a[], int *lda, - int *info); -extern int -FNAME(cpotri)(char *uplo, int *n, - f2c_complex a[], int *lda, - int *info); -extern int -FNAME(zpotri)(char *uplo, int *n, - f2c_doublecomplex a[], int *lda, - int *info); - -extern int -FNAME(scopy)(int *n, - float *sx, int *incx, - float *sy, int *incy); -extern int -FNAME(dcopy)(int *n, - double *sx, int *incx, - double *sy, int *incy); -extern int -FNAME(ccopy)(int *n, - f2c_complex *sx, int *incx, - f2c_complex *sy, int *incy); -extern int -FNAME(zcopy)(int *n, - f2c_doublecomplex *sx, int *incx, - f2c_doublecomplex *sy, int *incy); + fortran_int *lwork, double rwork[], fortran_int *lrwork, fortran_int iwork[], + fortran_int *liwork, + fortran_int *info); + +extern fortran_int +FNAME(sgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + float a[], fortran_int *lda, float b[], fortran_int *ldb, + float s[], float *rcond, fortran_int *rank, + float work[], fortran_int *lwork, fortran_int iwork[], + fortran_int *info); +extern fortran_int +FNAME(dgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + double a[], fortran_int *lda, double b[], fortran_int *ldb, + double s[], double *rcond, fortran_int *rank, + double work[], fortran_int *lwork, fortran_int iwork[], + fortran_int *info); +extern fortran_int +FNAME(cgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + f2c_complex a[], fortran_int *lda, + f2c_complex b[], fortran_int *ldb, + float s[], float *rcond, fortran_int *rank, + f2c_complex work[], fortran_int *lwork, + float rwork[], fortran_int iwork[], + fortran_int *info); +extern fortran_int +FNAME(zgelsd)(fortran_int *m, fortran_int *n, fortran_int *nrhs, + f2c_doublecomplex a[], fortran_int *lda, + f2c_doublecomplex b[], fortran_int *ldb, + double s[], double *rcond, fortran_int *rank, + f2c_doublecomplex work[], fortran_int *lwork, + double rwork[], fortran_int iwork[], + fortran_int *info); + +extern fortran_int +FNAME(sgesv)(fortran_int *n, fortran_int *nrhs, + float a[], fortran_int *lda, + fortran_int ipiv[], + float b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(dgesv)(fortran_int *n, fortran_int *nrhs, + double a[], fortran_int *lda, + fortran_int ipiv[], + double b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(cgesv)(fortran_int *n, fortran_int *nrhs, + f2c_complex a[], fortran_int *lda, + fortran_int ipiv[], + f2c_complex b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(zgesv)(fortran_int *n, fortran_int *nrhs, + f2c_doublecomplex a[], fortran_int *lda, + fortran_int ipiv[], + f2c_doublecomplex b[], fortran_int *ldb, + fortran_int *info); + +extern fortran_int +FNAME(sgetrf)(fortran_int *m, fortran_int *n, + float a[], fortran_int *lda, + fortran_int ipiv[], + fortran_int *info); +extern fortran_int +FNAME(dgetrf)(fortran_int *m, fortran_int *n, + double a[], fortran_int *lda, + fortran_int ipiv[], + fortran_int *info); +extern fortran_int +FNAME(cgetrf)(fortran_int *m, fortran_int *n, + f2c_complex a[], fortran_int *lda, + fortran_int ipiv[], + fortran_int *info); +extern fortran_int +FNAME(zgetrf)(fortran_int *m, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, + fortran_int ipiv[], + fortran_int *info); + +extern fortran_int +FNAME(spotrf)(char *uplo, fortran_int *n, + float a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(dpotrf)(char *uplo, fortran_int *n, + double a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(cpotrf)(char *uplo, fortran_int *n, + f2c_complex a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(zpotrf)(char *uplo, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, + fortran_int *info); + +extern fortran_int +FNAME(sgesdd)(char *jobz, fortran_int *m, fortran_int *n, + float a[], fortran_int *lda, float s[], float u[], + fortran_int *ldu, float vt[], fortran_int *ldvt, float work[], + fortran_int *lwork, fortran_int iwork[], fortran_int *info); +extern fortran_int +FNAME(dgesdd)(char *jobz, fortran_int *m, fortran_int *n, + double a[], fortran_int *lda, double s[], double u[], + fortran_int *ldu, double vt[], fortran_int *ldvt, double work[], + fortran_int *lwork, fortran_int iwork[], fortran_int *info); +extern fortran_int +FNAME(cgesdd)(char *jobz, fortran_int *m, fortran_int *n, + f2c_complex a[], fortran_int *lda, + float s[], f2c_complex u[], fortran_int *ldu, + f2c_complex vt[], fortran_int *ldvt, + f2c_complex work[], fortran_int *lwork, + float rwork[], fortran_int iwork[], fortran_int *info); +extern fortran_int +FNAME(zgesdd)(char *jobz, fortran_int *m, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, + double s[], f2c_doublecomplex u[], fortran_int *ldu, + f2c_doublecomplex vt[], fortran_int *ldvt, + f2c_doublecomplex work[], fortran_int *lwork, + double rwork[], fortran_int iwork[], fortran_int *info); + +extern fortran_int +FNAME(spotrs)(char *uplo, fortran_int *n, fortran_int *nrhs, + float a[], fortran_int *lda, + float b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(dpotrs)(char *uplo, fortran_int *n, fortran_int *nrhs, + double a[], fortran_int *lda, + double b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(cpotrs)(char *uplo, fortran_int *n, fortran_int *nrhs, + f2c_complex a[], fortran_int *lda, + f2c_complex b[], fortran_int *ldb, + fortran_int *info); +extern fortran_int +FNAME(zpotrs)(char *uplo, fortran_int *n, fortran_int *nrhs, + f2c_doublecomplex a[], fortran_int *lda, + f2c_doublecomplex b[], fortran_int *ldb, + fortran_int *info); + +extern fortran_int +FNAME(spotri)(char *uplo, fortran_int *n, + float a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(dpotri)(char *uplo, fortran_int *n, + double a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(cpotri)(char *uplo, fortran_int *n, + f2c_complex a[], fortran_int *lda, + fortran_int *info); +extern fortran_int +FNAME(zpotri)(char *uplo, fortran_int *n, + f2c_doublecomplex a[], fortran_int *lda, + fortran_int *info); + +extern fortran_int +FNAME(scopy)(fortran_int *n, + float *sx, fortran_int *incx, + float *sy, fortran_int *incy); +extern fortran_int +FNAME(dcopy)(fortran_int *n, + double *sx, fortran_int *incx, + double *sy, fortran_int *incy); +extern fortran_int +FNAME(ccopy)(fortran_int *n, + f2c_complex *sx, fortran_int *incx, + f2c_complex *sy, fortran_int *incy); +extern fortran_int +FNAME(zcopy)(fortran_int *n, + f2c_doublecomplex *sx, fortran_int *incx, + f2c_doublecomplex *sy, fortran_int *incy); extern float -FNAME(sdot)(int *n, - float *sx, int *incx, - float *sy, int *incy); +FNAME(sdot)(fortran_int *n, + float *sx, fortran_int *incx, + float *sy, fortran_int *incy); extern double -FNAME(ddot)(int *n, - double *sx, int *incx, - double *sy, int *incy); +FNAME(ddot)(fortran_int *n, + double *sx, fortran_int *incx, + double *sy, fortran_int *incy); extern void -FNAME(cdotu)(f2c_complex *ret, int *n, - f2c_complex *sx, int *incx, - f2c_complex *sy, int *incy); +FNAME(cdotu)(f2c_complex *ret, fortran_int *n, + f2c_complex *sx, fortran_int *incx, + f2c_complex *sy, fortran_int *incy); extern void -FNAME(zdotu)(f2c_doublecomplex *ret, int *n, - f2c_doublecomplex *sx, int *incx, - f2c_doublecomplex *sy, int *incy); +FNAME(zdotu)(f2c_doublecomplex *ret, fortran_int *n, + f2c_doublecomplex *sx, fortran_int *incx, + f2c_doublecomplex *sy, fortran_int *incy); extern void -FNAME(cdotc)(f2c_complex *ret, int *n, - f2c_complex *sx, int *incx, - f2c_complex *sy, int *incy); +FNAME(cdotc)(f2c_complex *ret, fortran_int *n, + f2c_complex *sx, fortran_int *incx, + f2c_complex *sy, fortran_int *incy); extern void -FNAME(zdotc)(f2c_doublecomplex *ret, int *n, - f2c_doublecomplex *sx, int *incx, - f2c_doublecomplex *sy, int *incy); +FNAME(zdotc)(f2c_doublecomplex *ret, fortran_int *n, + f2c_doublecomplex *sx, fortran_int *incx, + f2c_doublecomplex *sy, fortran_int *incy); -extern int +extern fortran_int FNAME(sgemm)(char *transa, char *transb, - int *m, int *n, int *k, + fortran_int *m, fortran_int *n, fortran_int *k, float *alpha, - float *a, int *lda, - float *b, int *ldb, + float *a, fortran_int *lda, + float *b, fortran_int *ldb, float *beta, - float *c, int *ldc); -extern int + float *c, fortran_int *ldc); +extern fortran_int FNAME(dgemm)(char *transa, char *transb, - int *m, int *n, int *k, + fortran_int *m, fortran_int *n, fortran_int *k, double *alpha, - double *a, int *lda, - double *b, int *ldb, + double *a, fortran_int *lda, + double *b, fortran_int *ldb, double *beta, - double *c, int *ldc); -extern int + double *c, fortran_int *ldc); +extern fortran_int FNAME(cgemm)(char *transa, char *transb, - int *m, int *n, int *k, + fortran_int *m, fortran_int *n, fortran_int *k, f2c_complex *alpha, - f2c_complex *a, int *lda, - f2c_complex *b, int *ldb, + f2c_complex *a, fortran_int *lda, + f2c_complex *b, fortran_int *ldb, f2c_complex *beta, - f2c_complex *c, int *ldc); -extern int + f2c_complex *c, fortran_int *ldc); +extern fortran_int FNAME(zgemm)(char *transa, char *transb, - int *m, int *n, int *k, + fortran_int *m, fortran_int *n, fortran_int *k, f2c_doublecomplex *alpha, - f2c_doublecomplex *a, int *lda, - f2c_doublecomplex *b, int *ldb, + f2c_doublecomplex *a, fortran_int *lda, + f2c_doublecomplex *b, fortran_int *ldb, f2c_doublecomplex *beta, - f2c_doublecomplex *c, int *ldc); + f2c_doublecomplex *c, fortran_int *ldc); #define LAPACK_T(FUNC) \ @@ -369,12 +386,6 @@ FNAME(zgemm)(char *transa, char *transb, #define LAPACK(FUNC) \ FNAME(FUNC) -typedef int fortran_int; -typedef float fortran_real; -typedef double fortran_doublereal; -typedef f2c_complex fortran_complex; -typedef f2c_doublecomplex fortran_doublecomplex; - /* ***************************************************************************** diff --git a/numpy/ma/core.py b/numpy/ma/core.py index bb0d8d412..2baf547a4 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -602,8 +602,10 @@ def filled(a, fill_value=None): ---------- a : MaskedArray or array_like An input object. - fill_value : scalar, optional - Filling value. Default is None. + fill_value : array_like, optional. + Can be scalar or non-scalar. If non-scalar, the + resulting filled array should be broadcastable + over input array. Default is None. Returns ------- @@ -623,10 +625,19 @@ def filled(a, fill_value=None): array([[999999, 1, 2], [999999, 4, 5], [ 6, 7, 8]]) + >>> x.filled(fill_value=333) + array([[333, 1, 2], + [333, 4, 5], + [ 6, 7, 8]]) + >>> x.filled(fill_value=np.arange(3)) + array([[0, 1, 2], + [0, 4, 5], + [6, 7, 8]]) """ if hasattr(a, 'filled'): return a.filled(fill_value) + elif isinstance(a, ndarray): # Should we check for contiguity ? and a.flags['CONTIGUOUS']: return a @@ -3653,6 +3664,14 @@ class MaskedArray(ndarray): @fill_value.setter def fill_value(self, value=None): target = _check_fill_value(value, self.dtype) + if not target.ndim == 0: + # 2019-11-12, 1.18.0 + warnings.warn( + "Non-scalar arrays for the fill value are deprecated. Use " + "arrays with scalar values instead. The filled function " + "still supports any array as `fill_value`.", + DeprecationWarning, stacklevel=2) + _fill_value = self._fill_value if _fill_value is None: # Create the attribute if it was undefined @@ -3673,9 +3692,11 @@ class MaskedArray(ndarray): Parameters ---------- - fill_value : scalar, optional - The value to use for invalid entries (None by default). - If None, the `fill_value` attribute of the array is used instead. + fill_value : array_like, optional + The value to use for invalid entries. Can be scalar or non-scalar. + If non-scalar, the resulting ndarray must be broadcastable over + input array. Default is None, in which case, the `fill_value` + attribute of the array is used instead. Returns ------- @@ -3694,6 +3715,8 @@ class MaskedArray(ndarray): >>> x = np.ma.array([1,2,3,4,5], mask=[0,0,1,0,1], fill_value=-999) >>> x.filled() array([ 1, 2, -999, 4, -999]) + >>> x.filled(fill_value=1000) + array([ 1, 2, 1000, 4, 1000]) >>> type(x.filled()) <class 'numpy.ndarray'> @@ -6220,9 +6243,11 @@ class mvoid(MaskedArray): Parameters ---------- - fill_value : scalar, optional - The value to use for invalid entries (None by default). - If None, the `fill_value` attribute is used instead. + fill_value : array_like, optional + The value to use for invalid entries. Can be scalar or + non-scalar. If latter is the case, the filled array should + be broadcastable over input array. Default is None, in + which case the `fill_value` attribute is used instead. Returns ------- diff --git a/numpy/ma/extras.py b/numpy/ma/extras.py index 4a83ac781..f4a914471 100644 --- a/numpy/ma/extras.py +++ b/numpy/ma/extras.py @@ -937,7 +937,7 @@ def compress_cols(a): raise NotImplementedError("compress_cols works for 2D arrays only.") return compress_rowcols(a, 1) -def mask_rows(a, axis=None): +def mask_rows(a, axis=np._NoValue): """ Mask rows of a 2D array that contain masked values. @@ -979,9 +979,15 @@ def mask_rows(a, axis=None): fill_value=1) """ + if axis is not np._NoValue: + # remove the axis argument when this deprecation expires + # NumPy 1.18.0, 2019-11-28 + warnings.warn( + "The axis argument has always been ignored, in future passing it " + "will raise TypeError", DeprecationWarning, stacklevel=2) return mask_rowcols(a, 0) -def mask_cols(a, axis=None): +def mask_cols(a, axis=np._NoValue): """ Mask columns of a 2D array that contain masked values. @@ -1022,6 +1028,12 @@ def mask_cols(a, axis=None): fill_value=1) """ + if axis is not np._NoValue: + # remove the axis argument when this deprecation expires + # NumPy 1.18.0, 2019-11-28 + warnings.warn( + "The axis argument has always been ignored, in future passing it " + "will raise TypeError", DeprecationWarning, stacklevel=2) return mask_rowcols(a, 1) diff --git a/numpy/ma/mrecords.py b/numpy/ma/mrecords.py index 826fb0f64..ae1a12c2c 100644 --- a/numpy/ma/mrecords.py +++ b/numpy/ma/mrecords.py @@ -260,8 +260,7 @@ class MaskedRecords(MaskedArray, object): fielddict = ndarray.__getattribute__(self, 'dtype').fields or {} optinfo = ndarray.__getattribute__(self, '_optinfo') or {} if not (attr in fielddict or attr in optinfo): - exctype, value = sys.exc_info()[:2] - raise exctype(value) + raise else: # Get the list of names fielddict = ndarray.__getattribute__(self, 'dtype').fields or {} diff --git a/numpy/ma/tests/test_extras.py b/numpy/ma/tests/test_extras.py index 836770378..c75c47801 100644 --- a/numpy/ma/tests/test_extras.py +++ b/numpy/ma/tests/test_extras.py @@ -11,6 +11,7 @@ from __future__ import division, absolute_import, print_function import warnings import itertools +import pytest import numpy as np from numpy.testing import ( @@ -552,6 +553,18 @@ class TestCompressFunctions(object): assert_(mask_rowcols(x, 0).mask.all()) assert_(mask_rowcols(x, 1).mask.all()) + @pytest.mark.parametrize("axis", [None, 0, 1]) + @pytest.mark.parametrize(["func", "rowcols_axis"], + [(np.ma.mask_rows, 0), (np.ma.mask_cols, 1)]) + def test_mask_row_cols_axis_deprecation(self, axis, func, rowcols_axis): + # Test deprecation of the axis argument to `mask_rows` and `mask_cols` + x = array(np.arange(9).reshape(3, 3), + mask=[[1, 0, 0], [0, 0, 0], [0, 0, 0]]) + + with assert_warns(DeprecationWarning): + res = func(x, axis=axis) + assert_equal(res, mask_rowcols(x, rowcols_axis)) + def test_dot(self): # Tests dot product n = np.arange(1, 7) diff --git a/numpy/random/__init__.pxd b/numpy/random/__init__.pxd new file mode 100644 index 000000000..05e073876 --- /dev/null +++ b/numpy/random/__init__.pxd @@ -0,0 +1,14 @@ +cimport numpy as np +from libc.stdint cimport uint32_t, uint64_t + +cdef extern from "numpy/random/bitgen.h": + struct bitgen: + void *state + uint64_t (*next_uint64)(void *st) nogil + uint32_t (*next_uint32)(void *st) nogil + double (*next_double)(void *st) nogil + uint64_t (*next_raw)(void *st) nogil + + ctypedef bitgen bitgen_t + +from numpy.random._bit_generator cimport BitGenerator, SeedSequence diff --git a/numpy/random/_bit_generator.pxd b/numpy/random/_bit_generator.pxd index 30fa4a27d..bd5e47a20 100644 --- a/numpy/random/_bit_generator.pxd +++ b/numpy/random/_bit_generator.pxd @@ -1,7 +1,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t -cdef extern from "include/bitgen.h": +cdef extern from "numpy/random/bitgen.h": struct bitgen: void *state uint64_t (*next_uint64)(void *st) nogil diff --git a/numpy/random/_bounded_integers.pxd.in b/numpy/random/_bounded_integers.pxd.in index 320d35774..5ae5a8067 100644 --- a/numpy/random/_bounded_integers.pxd.in +++ b/numpy/random/_bounded_integers.pxd.in @@ -4,7 +4,7 @@ import numpy as np cimport numpy as np ctypedef np.npy_bool bool_t -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t cdef inline uint64_t _gen_mask(uint64_t max_val) nogil: """Mask generator for use in bounded random numbers""" diff --git a/numpy/random/_bounded_integers.pyx.in b/numpy/random/_bounded_integers.pyx.in index c0068dab2..7e19471e4 100644 --- a/numpy/random/_bounded_integers.pyx.in +++ b/numpy/random/_bounded_integers.pyx.in @@ -8,7 +8,7 @@ __all__ = [] np.import_array() -cdef extern from "include/distributions.h": +cdef extern from "numpy/random/distributions.h": # Generate random numbers in closed interval [off, off + rng]. uint64_t random_bounded_uint64(bitgen_t *bitgen_state, uint64_t off, uint64_t rng, diff --git a/numpy/random/_common.pxd b/numpy/random/_common.pxd index 74bebca83..588f613ae 100644 --- a/numpy/random/_common.pxd +++ b/numpy/random/_common.pxd @@ -5,7 +5,7 @@ from libc.stdint cimport uint32_t, uint64_t, int32_t, int64_t import numpy as np cimport numpy as np -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t cdef double POISSON_LAM_MAX cdef double LEGACY_POISSON_LAM_MAX diff --git a/numpy/random/_examples/cffi/extending.py b/numpy/random/_examples/cffi/extending.py new file mode 100644 index 000000000..8440d400e --- /dev/null +++ b/numpy/random/_examples/cffi/extending.py @@ -0,0 +1,40 @@ +""" +Use cffi to access any of the underlying C functions from distributions.h +""" +import os +import numpy as np +import cffi +from .parse import parse_distributions_h +ffi = cffi.FFI() + +inc_dir = os.path.join(np.get_include(), 'numpy') + +# Basic numpy types +ffi.cdef(''' + typedef intptr_t npy_intp; + typedef unsigned char npy_bool; + +''') + +parse_distributions_h(ffi, inc_dir) + +lib = ffi.dlopen(np.random._generator.__file__) + +# Compare the distributions.h random_standard_normal_fill to +# Generator.standard_random +bit_gen = np.random.PCG64() +rng = np.random.Generator(bit_gen) +state = bit_gen.state + +interface = rng.bit_generator.cffi +n = 100 +vals_cffi = ffi.new('double[%d]' % n) +lib.random_standard_normal_fill(interface.bit_generator, n, vals_cffi) + +# reset the state +bit_gen.state = state + +vals = rng.standard_normal(n) + +for i in range(n): + assert vals[i] == vals_cffi[i] diff --git a/numpy/random/_examples/cffi/parse.py b/numpy/random/_examples/cffi/parse.py new file mode 100644 index 000000000..73d8646c7 --- /dev/null +++ b/numpy/random/_examples/cffi/parse.py @@ -0,0 +1,46 @@ +import os + + +def parse_distributions_h(ffi, inc_dir): + """ + Parse distributions.h located in inc_dir for CFFI, filling in the ffi.cdef + + Read the function declarations without the "#define ..." macros that will + be filled in when loading the library. + """ + + with open(os.path.join(inc_dir, 'random', 'bitgen.h')) as fid: + s = [] + for line in fid: + # massage the include file + if line.strip().startswith('#'): + continue + s.append(line) + ffi.cdef('\n'.join(s)) + + with open(os.path.join(inc_dir, 'random', 'distributions.h')) as fid: + s = [] + in_skip = 0 + for line in fid: + # massage the include file + if line.strip().startswith('#'): + continue + + # skip any inlined function definition + # which starts with 'static NPY_INLINE xxx(...) {' + # and ends with a closing '}' + if line.strip().startswith('static NPY_INLINE'): + in_skip += line.count('{') + continue + elif in_skip > 0: + in_skip += line.count('{') + in_skip -= line.count('}') + continue + + # replace defines with their value or remove them + line = line.replace('DECLDIR', '') + line = line.replace('NPY_INLINE', '') + line = line.replace('RAND_INT_TYPE', 'int64_t') + s.append(line) + ffi.cdef('\n'.join(s)) + diff --git a/numpy/random/examples/cython/extending.pyx b/numpy/random/_examples/cython/extending.pyx index a6a4ba4bf..7a0dfe078 100644 --- a/numpy/random/examples/cython/extending.pyx +++ b/numpy/random/_examples/cython/extending.pyx @@ -8,7 +8,7 @@ import numpy as np cimport numpy as np cimport cython -from numpy.random.common cimport bitgen_t +from numpy.random cimport bitgen_t from numpy.random import PCG64 np.import_array() @@ -39,7 +39,7 @@ def uniform_mean(Py_ssize_t n): return randoms.mean() -# This function is declated nogil so it can be used without the GIL below +# This function is declared nogil so it can be used without the GIL below cdef uint32_t bounded_uint(uint32_t lb, uint32_t ub, bitgen_t *rng) nogil: cdef uint32_t mask, delta, val mask = delta = ub - lb diff --git a/numpy/random/examples/cython/extending_distributions.pyx b/numpy/random/_examples/cython/extending_distributions.pyx index 3cefec97e..1bef506ef 100644 --- a/numpy/random/examples/cython/extending_distributions.pyx +++ b/numpy/random/_examples/cython/extending_distributions.pyx @@ -1,21 +1,25 @@ #!/usr/bin/env python #cython: language_level=3 """ -This file shows how the distributions that are accessed through -distributions.pxd can be used Cython code. +This file shows how the to use a BitGenerator to create a distribution. """ import numpy as np cimport numpy as np cimport cython from cpython.pycapsule cimport PyCapsule_IsValid, PyCapsule_GetPointer -from numpy.random.common cimport * -from numpy.random.distributions cimport random_gauss_zig +from libc.stdint cimport uint16_t, uint64_t +from numpy.random cimport bitgen_t from numpy.random import PCG64 @cython.boundscheck(False) @cython.wraparound(False) -def normals_zig(Py_ssize_t n): +def uniforms(Py_ssize_t n): + """ + Create an array of `n` uniformly distributed doubles. + A 'real' distribution would want to process the values into + some non-uniform distribution + """ cdef Py_ssize_t i cdef bitgen_t *rng cdef const char *capsule_name = "BitGenerator" @@ -23,37 +27,48 @@ def normals_zig(Py_ssize_t n): x = PCG64() capsule = x.capsule + # Optional check that the capsule if from a BitGenerator if not PyCapsule_IsValid(capsule, capsule_name): raise ValueError("Invalid pointer to anon_func_state") + # Cast the pointer rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name) - random_values = np.empty(n) - # Best practice is to release GIL and acquire the lock + random_values = np.empty(n, dtype='float64') with x.lock, nogil: for i in range(n): - random_values[i] = random_gauss_zig(rng) + # Call the function + random_values[i] = rng.next_double(rng.state) randoms = np.asarray(random_values) - return randoms - + return randoms + +# cython example 2 @cython.boundscheck(False) @cython.wraparound(False) -def uniforms(Py_ssize_t n): +def uint10_uniforms(Py_ssize_t n): + """Uniform 10 bit integers stored as 16-bit unsigned integers""" cdef Py_ssize_t i cdef bitgen_t *rng cdef const char *capsule_name = "BitGenerator" - cdef double[::1] random_values + cdef uint16_t[::1] random_values + cdef int bits_remaining + cdef int width = 10 + cdef uint64_t buff, mask = 0x3FF x = PCG64() capsule = x.capsule - # Optional check that the capsule if from a BitGenerator if not PyCapsule_IsValid(capsule, capsule_name): raise ValueError("Invalid pointer to anon_func_state") - # Cast the pointer rng = <bitgen_t *> PyCapsule_GetPointer(capsule, capsule_name) - random_values = np.empty(n) + random_values = np.empty(n, dtype='uint16') + # Best practice is to release GIL and acquire the lock + bits_remaining = 0 with x.lock, nogil: for i in range(n): - # Call the function - random_values[i] = rng.next_double(rng.state) + if bits_remaining < width: + buff = rng.next_uint64(rng.state) + random_values[i] = buff & mask + buff >>= width + randoms = np.asarray(random_values) return randoms + diff --git a/numpy/random/_examples/cython/setup.py b/numpy/random/_examples/cython/setup.py new file mode 100644 index 000000000..19f045fc0 --- /dev/null +++ b/numpy/random/_examples/cython/setup.py @@ -0,0 +1,31 @@ +#!/usr/bin/env python3 +""" +Build the Cython demonstrations of low-level access to NumPy random + +Usage: python setup.py build_ext -i +""" + +import numpy as np +from distutils.core import setup +from Cython.Build import cythonize +from setuptools.extension import Extension +from os.path import join, abspath, dirname + +path = abspath(dirname(__file__)) + +extending = Extension("extending", + sources=[join(path, 'extending.pyx')], + include_dirs=[ + np.get_include(), + join(path, '..', '..') + ], + ) +distributions = Extension("extending_distributions", + sources=[join(path, 'extending_distributions.pyx')], + include_dirs=[np.get_include()]) + +extensions = [extending, distributions] + +setup( + ext_modules=cythonize(extensions) +) diff --git a/numpy/random/_examples/numba/extending.py b/numpy/random/_examples/numba/extending.py new file mode 100644 index 000000000..0d240596b --- /dev/null +++ b/numpy/random/_examples/numba/extending.py @@ -0,0 +1,84 @@ +import numpy as np +import numba as nb + +from numpy.random import PCG64 +from timeit import timeit + +bit_gen = PCG64() +next_d = bit_gen.cffi.next_double +state_addr = bit_gen.cffi.state_address + +def normals(n, state): + out = np.empty(n) + for i in range((n + 1) // 2): + x1 = 2.0 * next_d(state) - 1.0 + x2 = 2.0 * next_d(state) - 1.0 + r2 = x1 * x1 + x2 * x2 + while r2 >= 1.0 or r2 == 0.0: + x1 = 2.0 * next_d(state) - 1.0 + x2 = 2.0 * next_d(state) - 1.0 + r2 = x1 * x1 + x2 * x2 + f = np.sqrt(-2.0 * np.log(r2) / r2) + out[2 * i] = f * x1 + if 2 * i + 1 < n: + out[2 * i + 1] = f * x2 + return out + +# Compile using Numba +normalsj = nb.jit(normals, nopython=True) +# Must use state address not state with numba +n = 10000 + +def numbacall(): + return normalsj(n, state_addr) + +rg = np.random.Generator(PCG64()) + +def numpycall(): + return rg.normal(size=n) + +# Check that the functions work +r1 = numbacall() +r2 = numpycall() +assert r1.shape == (n,) +assert r1.shape == r2.shape + +t1 = timeit(numbacall, number=1000) +print('{:.2f} secs for {} PCG64 (Numba/PCG64) gaussian randoms'.format(t1, n)) +t2 = timeit(numpycall, number=1000) +print('{:.2f} secs for {} PCG64 (NumPy/PCG64) gaussian randoms'.format(t2, n)) + +# example 2 + +next_u32 = bit_gen.ctypes.next_uint32 +ctypes_state = bit_gen.ctypes.state + +@nb.jit(nopython=True) +def bounded_uint(lb, ub, state): + mask = delta = ub - lb + mask |= mask >> 1 + mask |= mask >> 2 + mask |= mask >> 4 + mask |= mask >> 8 + mask |= mask >> 16 + + val = next_u32(state) & mask + while val > delta: + val = next_u32(state) & mask + + return lb + val + + +print(bounded_uint(323, 2394691, ctypes_state.value)) + + +@nb.jit(nopython=True) +def bounded_uints(lb, ub, n, state): + out = np.empty(n, dtype=np.uint32) + for i in range(n): + out[i] = bounded_uint(lb, ub, state) + + +bounded_uints(323, 2394691, 10000000, ctypes_state.value) + + diff --git a/numpy/random/examples/numba/extending_distributions.py b/numpy/random/_examples/numba/extending_distributions.py index 9233ccced..7cf8bf0b0 100644 --- a/numpy/random/examples/numba/extending_distributions.py +++ b/numpy/random/_examples/numba/extending_distributions.py @@ -1,22 +1,28 @@ r""" -On *nix, execute in randomgen/src/distributions +Building the required library in this example requires a source distribution +of NumPy or clone of the NumPy git repository since distributions.c is not +included in binary distributions. +On *nix, execute in numpy/random/src/distributions + +export ${PYTHON_VERSION}=3.8 # Python version export PYTHON_INCLUDE=#path to Python's include folder, usually \ ${PYTHON_HOME}/include/python${PYTHON_VERSION}m export NUMPY_INCLUDE=#path to numpy's include folder, usually \ ${PYTHON_HOME}/lib/python${PYTHON_VERSION}/site-packages/numpy/core/include gcc -shared -o libdistributions.so -fPIC distributions.c \ -I${NUMPY_INCLUDE} -I${PYTHON_INCLUDE} -mv libdistributions.so ../../examples/numba/ +mv libdistributions.so ../../_examples/numba/ On Windows -rem PYTHON_HOME is setup dependent, this is an example +rem PYTHON_HOME and PYTHON_VERSION are setup dependent, this is an example set PYTHON_HOME=c:\Anaconda +set PYTHON_VERSION=38 cl.exe /LD .\distributions.c -DDLL_EXPORT \ -I%PYTHON_HOME%\lib\site-packages\numpy\core\include \ - -I%PYTHON_HOME%\include %PYTHON_HOME%\libs\python36.lib -move distributions.dll ../../examples/numba/ + -I%PYTHON_HOME%\include %PYTHON_HOME%\libs\python%PYTHON_VERSION%.lib +move distributions.dll ../../_examples/numba/ """ import os @@ -35,19 +41,19 @@ else: raise RuntimeError('Required DLL/so file was not found.') ffi.cdef(""" -double random_gauss_zig(void *bitgen_state); +double random_standard_normal(void *bitgen_state); """) x = PCG64() xffi = x.cffi bit_generator = xffi.bit_generator -random_gauss_zig = lib.random_gauss_zig +random_standard_normal = lib.random_standard_normal def normals(n, bit_generator): out = np.empty(n) for i in range(n): - out[i] = random_gauss_zig(bit_generator) + out[i] = random_standard_normal(bit_generator) return out diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx index b6c222cc0..d76cde44c 100644 --- a/numpy/random/_generator.pyx +++ b/numpy/random/_generator.pyx @@ -19,7 +19,7 @@ from ._bounded_integers cimport (_rand_bool, _rand_int32, _rand_int64, _rand_uint8, _gen_mask) from ._bounded_integers import _integers_types from ._pcg64 import PCG64 -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, CONS_NON_NEGATIVE, CONS_BOUNDED_0_1, CONS_BOUNDED_GT_0_1, CONS_GT_1, CONS_POSITIVE_NOT_NAN, CONS_POISSON, @@ -28,7 +28,7 @@ from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, ) -cdef extern from "include/distributions.h": +cdef extern from "numpy/random/distributions.h": struct s_binomial_t: int has_binomial @@ -54,9 +54,11 @@ cdef extern from "include/distributions.h": double random_standard_uniform(bitgen_t *bitgen_state) nogil void random_standard_uniform_fill(bitgen_t* bitgen_state, np.npy_intp cnt, double *out) nogil double random_standard_exponential(bitgen_t *bitgen_state) nogil + double random_standard_exponential_f(bitgen_t *bitgen_state) nogil void random_standard_exponential_fill(bitgen_t *bitgen_state, np.npy_intp cnt, double *out) nogil - double random_standard_exponential_zig(bitgen_t *bitgen_state) nogil - void random_standard_exponential_zig_fill(bitgen_t *bitgen_state, np.npy_intp cnt, double *out) nogil + void random_standard_exponential_fill_f(bitgen_t *bitgen_state, np.npy_intp cnt, double *out) nogil + void random_standard_exponential_inv_fill(bitgen_t *bitgen_state, np.npy_intp cnt, double *out) nogil + void random_standard_exponential_inv_fill_f(bitgen_t *bitgen_state, np.npy_intp cnt, double *out) nogil double random_standard_normal(bitgen_t* bitgen_state) nogil void random_standard_normal_fill(bitgen_t *bitgen_state, np.npy_intp count, double *out) nogil void random_standard_normal_fill_f(bitgen_t *bitgen_state, np.npy_intp count, float *out) nogil @@ -64,10 +66,6 @@ cdef extern from "include/distributions.h": float random_standard_uniform_f(bitgen_t *bitgen_state) nogil void random_standard_uniform_fill_f(bitgen_t* bitgen_state, np.npy_intp cnt, float *out) nogil - float random_standard_exponential_f(bitgen_t *bitgen_state) nogil - float random_standard_exponential_zig_f(bitgen_t *bitgen_state) nogil - void random_standard_exponential_fill_f(bitgen_t *bitgen_state, np.npy_intp cnt, float *out) nogil - void random_standard_exponential_zig_fill_f(bitgen_t *bitgen_state, np.npy_intp cnt, float *out) nogil float random_standard_normal_f(bitgen_t* bitgen_state) nogil float random_standard_gamma_f(bitgen_t *bitgen_state, float shape) nogil @@ -126,12 +124,12 @@ cdef extern from "include/distributions.h": void random_multinomial(bitgen_t *bitgen_state, int64_t n, int64_t *mnix, double *pix, np.npy_intp d, binomial_t *binomial) nogil - int random_mvhg_count(bitgen_t *bitgen_state, + int random_multivariate_hypergeometric_count(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, size_t num_variates, int64_t *variates) nogil - void random_mvhg_marginals(bitgen_t *bitgen_state, + void random_multivariate_hypergeometric_marginals(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, @@ -459,14 +457,14 @@ cdef class Generator: key = np.dtype(dtype).name if key == 'float64': if method == u'zig': - return double_fill(&random_standard_exponential_zig_fill, &self._bitgen, size, self.lock, out) - else: return double_fill(&random_standard_exponential_fill, &self._bitgen, size, self.lock, out) + else: + return double_fill(&random_standard_exponential_inv_fill, &self._bitgen, size, self.lock, out) elif key == 'float32': if method == u'zig': - return float_fill(&random_standard_exponential_zig_fill_f, &self._bitgen, size, self.lock, out) - else: return float_fill(&random_standard_exponential_fill_f, &self._bitgen, size, self.lock, out) + else: + return float_fill(&random_standard_exponential_inv_fill_f, &self._bitgen, size, self.lock, out) else: raise TypeError('Unsupported dtype "%s" for standard_exponential' % key) @@ -1004,6 +1002,12 @@ cdef class Generator: A floating-point array of shape ``size`` of drawn samples, or a single sample if ``size`` was not specified. + See Also + -------- + normal : + Equivalent function with additional ``loc`` and ``scale`` arguments + for setting the mean and standard deviation. + Notes ----- For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: @@ -1011,12 +1015,6 @@ cdef class Generator: mu + sigma * gen.standard_normal(size=...) gen.normal(mu, sigma, size=...) - See Also - -------- - normal : - Equivalent function with additional ``loc`` and ``scale`` arguments - for setting the mean and standard deviation. - Examples -------- >>> rng = np.random.default_rng() @@ -4012,18 +4010,18 @@ cdef class Generator: if method == 'count': with self.lock, nogil: - result = random_mvhg_count(&self._bitgen, total, - num_colors, colors_ptr, nsamp, - num_variates, variates_ptr) + result = random_multivariate_hypergeometric_count(&self._bitgen, + total, num_colors, colors_ptr, nsamp, + num_variates, variates_ptr) if result == -1: raise MemoryError("Insufficent memory for multivariate_" "hypergeometric with method='count' and " "sum(colors)=%d" % total) else: with self.lock, nogil: - random_mvhg_marginals(&self._bitgen, total, - num_colors, colors_ptr, nsamp, - num_variates, variates_ptr) + random_multivariate_hypergeometric_marginals(&self._bitgen, + total, num_colors, colors_ptr, nsamp, + num_variates, variates_ptr) return variates def dirichlet(self, object alpha, size=None): @@ -4393,11 +4391,15 @@ def default_rng(seed=None): Additionally, when passed a `BitGenerator`, it will be wrapped by `Generator`. If passed a `Generator`, it will be returned unaltered. + Returns + ------- + Generator + The initialized generator object. + Notes ----- - When ``seed`` is omitted or ``None``, a new `BitGenerator` and `Generator` will - be instantiated each time. This function does not manage a default global - instance. + If ``seed`` is not a `BitGenerator` or a `Generator`, a new `BitGenerator` + is instantiated. This function does not manage a default global instance. """ if _check_bit_generator(seed): # We were passed a BitGenerator, so just wrap it up. diff --git a/numpy/random/_mt19937.pyx b/numpy/random/_mt19937.pyx index e99652b73..919a96a4c 100644 --- a/numpy/random/_mt19937.pyx +++ b/numpy/random/_mt19937.pyx @@ -4,7 +4,7 @@ import numpy as np cimport numpy as np from libc.stdint cimport uint32_t, uint64_t -from ._bit_generator cimport BitGenerator, SeedSequence +from numpy.random cimport BitGenerator, SeedSequence __all__ = ['MT19937'] diff --git a/numpy/random/_pcg64.pyx b/numpy/random/_pcg64.pyx index 1a5d852a2..05d27db5c 100644 --- a/numpy/random/_pcg64.pyx +++ b/numpy/random/_pcg64.pyx @@ -3,7 +3,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double, wrap_int -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['PCG64'] diff --git a/numpy/random/_philox.pyx b/numpy/random/_philox.pyx index 9f136c32f..7e8880490 100644 --- a/numpy/random/_philox.pyx +++ b/numpy/random/_philox.pyx @@ -10,7 +10,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double, int_to_array, wrap_int -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['Philox'] diff --git a/numpy/random/_sfc64.pyx b/numpy/random/_sfc64.pyx index 1633669d5..1daee34f8 100644 --- a/numpy/random/_sfc64.pyx +++ b/numpy/random/_sfc64.pyx @@ -3,7 +3,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['SFC64'] diff --git a/numpy/random/examples/cython/setup.py b/numpy/random/examples/cython/setup.py deleted file mode 100644 index 69f057ed5..000000000 --- a/numpy/random/examples/cython/setup.py +++ /dev/null @@ -1,27 +0,0 @@ -#!/usr/bin/env python3 -""" -Build the demos - -Usage: python setup.py build_ext -i -""" - -import numpy as np -from distutils.core import setup -from Cython.Build import cythonize -from setuptools.extension import Extension -from os.path import join - -extending = Extension("extending", - sources=['extending.pyx'], - include_dirs=[np.get_include()]) -distributions = Extension("extending_distributions", - sources=['extending_distributions.pyx', - join('..', '..', 'src', - 'distributions', 'distributions.c')], - include_dirs=[np.get_include()]) - -extensions = [extending, distributions] - -setup( - ext_modules=cythonize(extensions) -) diff --git a/numpy/random/examples/numba/extending.py b/numpy/random/examples/numba/extending.py deleted file mode 100644 index d41c2d76f..000000000 --- a/numpy/random/examples/numba/extending.py +++ /dev/null @@ -1,77 +0,0 @@ -import datetime as dt - -import numpy as np -import numba as nb - -from numpy.random import PCG64 - -x = PCG64() -f = x.ctypes.next_uint32 -s = x.ctypes.state - - -@nb.jit(nopython=True) -def bounded_uint(lb, ub, state): - mask = delta = ub - lb - mask |= mask >> 1 - mask |= mask >> 2 - mask |= mask >> 4 - mask |= mask >> 8 - mask |= mask >> 16 - - val = f(state) & mask - while val > delta: - val = f(state) & mask - - return lb + val - - -print(bounded_uint(323, 2394691, s.value)) - - -@nb.jit(nopython=True) -def bounded_uints(lb, ub, n, state): - out = np.empty(n, dtype=np.uint32) - for i in range(n): - out[i] = bounded_uint(lb, ub, state) - - -bounded_uints(323, 2394691, 10000000, s.value) - -g = x.cffi.next_double -cffi_state = x.cffi.state -state_addr = x.cffi.state_address - - -def normals(n, state): - out = np.empty(n) - for i in range((n + 1) // 2): - x1 = 2.0 * g(state) - 1.0 - x2 = 2.0 * g(state) - 1.0 - r2 = x1 * x1 + x2 * x2 - while r2 >= 1.0 or r2 == 0.0: - x1 = 2.0 * g(state) - 1.0 - x2 = 2.0 * g(state) - 1.0 - r2 = x1 * x1 + x2 * x2 - f = np.sqrt(-2.0 * np.log(r2) / r2) - out[2 * i] = f * x1 - if 2 * i + 1 < n: - out[2 * i + 1] = f * x2 - return out - - -print(normals(10, cffi_state).var()) -# Warm up -normalsj = nb.jit(normals, nopython=True) -normalsj(1, state_addr) - -start = dt.datetime.now() -normalsj(1000000, state_addr) -ms = 1000 * (dt.datetime.now() - start).total_seconds() -print('1,000,000 Polar-transform (numba/PCG64) randoms in ' - '{ms:0.1f}ms'.format(ms=ms)) - -start = dt.datetime.now() -np.random.standard_normal(1000000) -ms = 1000 * (dt.datetime.now() - start).total_seconds() -print('1,000,000 Polar-transform (NumPy) randoms in {ms:0.1f}ms'.format(ms=ms)) diff --git a/numpy/random/include/legacy-distributions.h b/numpy/random/include/legacy-distributions.h index 6a0fc7dc4..b8ba0841c 100644 --- a/numpy/random/include/legacy-distributions.h +++ b/numpy/random/include/legacy-distributions.h @@ -2,7 +2,7 @@ #define _RANDOMDGEN__DISTRIBUTIONS_LEGACY_H_ -#include "distributions.h" +#include "numpy/random/distributions.h" typedef struct aug_bitgen { bitgen_t *bit_generator; diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index b21607282..a4d409f37 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -17,7 +17,7 @@ from ._bounded_integers cimport (_rand_bool, _rand_int32, _rand_int64, _rand_uint8,) from ._bounded_integers import _integers_types from ._mt19937 import MT19937 as _MT19937 -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, CONS_NON_NEGATIVE, CONS_BOUNDED_0_1, CONS_BOUNDED_GT_0_1, CONS_GTE_1, CONS_GT_1, LEGACY_CONS_POISSON, @@ -25,7 +25,7 @@ from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, check_array_constraint, check_constraint, disc, discrete_broadcast_iii, ) -cdef extern from "include/distributions.h": +cdef extern from "numpy/random/distributions.h": struct s_binomial_t: int has_binomial double psave @@ -379,6 +379,10 @@ cdef class RandomState: (b - a) * random_sample() + a + .. note:: + New code should use the ``random`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- size : int or tuple of ints, optional @@ -392,6 +396,10 @@ cdef class RandomState: Array of random floats of shape `size` (unless ``size=None``, in which case a single float is returned). + See Also + -------- + Generator.random: which should be used for new code. + Examples -------- >>> np.random.random_sample() @@ -441,6 +449,10 @@ cdef class RandomState: It is often seen in Bayesian inference and order statistics. + .. note:: + New code should use the ``beta`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : float or array_like of floats @@ -458,6 +470,9 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized beta distribution. + See Also + -------- + Generator.beta: which should be used for new code. """ return cont(&legacy_beta, &self._aug_state, size, self.lock, 2, a, 'a', CONS_POSITIVE, @@ -484,6 +499,10 @@ cdef class RandomState: the size of raindrops measured over many rainstorms [1]_, or the time between page requests to Wikipedia [2]_. + .. note:: + New code should use the ``exponential`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- scale : float or array_like of floats @@ -500,6 +519,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized exponential distribution. + See Also + -------- + Generator.exponential: which should be used for new code. + References ---------- .. [1] Peyton Z. Peebles Jr., "Probability, Random Variables and @@ -525,6 +548,10 @@ cdef class RandomState: `standard_exponential` is identical to the exponential distribution with a scale parameter of 1. + .. note:: + New code should use the ``standard_exponential`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- size : int or tuple of ints, optional @@ -537,6 +564,10 @@ cdef class RandomState: out : float or ndarray Drawn samples. + See Also + -------- + Generator.standard_exponential: which should be used for new code. + Examples -------- Output a 3x8000 array: @@ -618,6 +649,10 @@ cdef class RandomState: the specified dtype in the "half-open" interval [`low`, `high`). If `high` is None (the default), then results are from [0, `low`). + .. note:: + New code should use the ``integers`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- low : int or array-like of ints @@ -651,6 +686,7 @@ cdef class RandomState: random_integers : similar to `randint`, only for the closed interval [`low`, `high`], and 1 is the lowest value if `high` is omitted. + Generator.integers: which should be used for new code. Examples -------- @@ -735,6 +771,10 @@ cdef class RandomState: Return random bytes. + .. note:: + New code should use the ``bytes`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- length : int @@ -745,11 +785,14 @@ cdef class RandomState: out : str String of length `length`. + See Also + -------- + Generator.bytes: which should be used for new code. + Examples -------- >>> np.random.bytes(10) ' eh\\x85\\x022SZ\\xbf\\xa4' #random - """ cdef Py_ssize_t n_uint32 = ((length - 1) // 4 + 1) # Interpret the uint32s as little-endian to convert them to bytes @@ -766,6 +809,10 @@ cdef class RandomState: .. versionadded:: 1.7.0 + .. note:: + New code should use the ``choice`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : 1-D array-like or int @@ -799,6 +846,7 @@ cdef class RandomState: See Also -------- randint, shuffle, permutation + Generator.choice: which should be used in new code Examples -------- @@ -958,6 +1006,10 @@ cdef class RandomState: any value within the given interval is equally likely to be drawn by `uniform`. + .. note:: + New code should use the ``uniform`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- low : float or array_like of floats, optional @@ -987,6 +1039,7 @@ cdef class RandomState: rand : Convenience function that accepts dimensions as input, e.g., ``rand(2,2)`` would generate a 2-by-2 array of floats, uniformly distributed over ``[0, 1)``. + Generator.uniform: which should be used for new code. Notes ----- @@ -1114,6 +1167,10 @@ cdef class RandomState: tuple to specify the size of the output, which is consistent with other NumPy functions like `numpy.zeros` and `numpy.ones`. + .. note:: + New code should use the ``standard_normal`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + If positive int_like arguments are provided, `randn` generates an array of shape ``(d0, d1, ..., dn)``, filled with random floats sampled from a univariate "normal" (Gaussian) @@ -1137,6 +1194,7 @@ cdef class RandomState: -------- standard_normal : Similar, but takes a tuple as its argument. normal : Also accepts mu and sigma arguments. + Generator.standard_normal: which should be used for new code. Notes ----- @@ -1263,6 +1321,10 @@ cdef class RandomState: Draw samples from a standard Normal distribution (mean=0, stdev=1). + .. note:: + New code should use the ``standard_normal`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- size : int or tuple of ints, optional @@ -1276,6 +1338,13 @@ cdef class RandomState: A floating-point array of shape ``size`` of drawn samples, or a single sample if ``size`` was not specified. + See Also + -------- + normal : + Equivalent function with additional ``loc`` and ``scale`` arguments + for setting the mean and standard deviation. + Generator.standard_normal: which should be used for new code. + Notes ----- For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: @@ -1283,12 +1352,6 @@ cdef class RandomState: mu + sigma * np.random.standard_normal(size=...) np.random.normal(mu, sigma, size=...) - See Also - -------- - normal : - Equivalent function with additional ``loc`` and ``scale`` arguments - for setting the mean and standard deviation. - Examples -------- >>> np.random.standard_normal() @@ -1333,6 +1396,10 @@ cdef class RandomState: by a large number of tiny, random disturbances, each with its own unique distribution [2]_. + .. note:: + New code should use the ``normal`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- loc : float or array_like of floats @@ -1355,6 +1422,7 @@ cdef class RandomState: -------- scipy.stats.norm : probability density function, distribution or cumulative density function, etc. + Generator.normal: which should be used for new code. Notes ----- @@ -1428,6 +1496,10 @@ cdef class RandomState: Samples are drawn from a Gamma distribution with specified parameters, shape (sometimes designated "k") and scale=1. + .. note:: + New code should use the ``standard_gamma`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- shape : float or array_like of floats @@ -1447,6 +1519,7 @@ cdef class RandomState: -------- scipy.stats.gamma : probability density function, distribution or cumulative density function, etc. + Generator.standard_gamma: which should be used for new code. Notes ----- @@ -1504,6 +1577,10 @@ cdef class RandomState: `shape` (sometimes designated "k") and `scale` (sometimes designated "theta"), where both parameters are > 0. + .. note:: + New code should use the ``gamma`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- shape : float or array_like of floats @@ -1526,6 +1603,7 @@ cdef class RandomState: -------- scipy.stats.gamma : probability density function, distribution or cumulative density function, etc. + Generator.gamma: which should be used for new code. Notes ----- @@ -1588,6 +1666,10 @@ cdef class RandomState: that arises in ANOVA tests, and is the ratio of two chi-square variates. + .. note:: + New code should use the ``f`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- dfnum : float or array_like of floats @@ -1609,6 +1691,7 @@ cdef class RandomState: -------- scipy.stats.f : probability density function, distribution or cumulative density function, etc. + Generator.f: which should be used for new code. Notes ----- @@ -1671,6 +1754,10 @@ cdef class RandomState: freedom in denominator), where both parameters > 1. `nonc` is the non-centrality parameter. + .. note:: + New code should use the ``noncentral_f`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- dfnum : float or array_like of floats @@ -1695,6 +1782,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized noncentral Fisher distribution. + See Also + -------- + Generator.noncentral_f: which should be used for new code. + Notes ----- When calculating the power of an experiment (power = probability of @@ -1748,6 +1839,10 @@ cdef class RandomState: resulting distribution is chi-square (see Notes). This distribution is often used in hypothesis testing. + .. note:: + New code should use the ``chisquare`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- df : float or array_like of floats @@ -1769,6 +1864,10 @@ cdef class RandomState: When `df` <= 0 or when an inappropriate `size` (e.g. ``size=-1``) is given. + See Also + -------- + Generator.chisquare: which should be used for new code. + Notes ----- The variable obtained by summing the squares of `df` independent, @@ -1798,7 +1897,6 @@ cdef class RandomState: -------- >>> np.random.chisquare(2,4) array([ 1.89920014, 9.00867716, 3.13710533, 5.62318272]) # random - """ return cont(&legacy_chisquare, &self._aug_state, size, self.lock, 1, df, 'df', CONS_POSITIVE, @@ -1814,6 +1912,10 @@ cdef class RandomState: The noncentral :math:`\\chi^2` distribution is a generalization of the :math:`\\chi^2` distribution. + .. note:: + New code should use the ``noncentral_chisquare`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- df : float or array_like of floats @@ -1834,6 +1936,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized noncentral chi-square distribution. + See Also + -------- + Generator.noncentral_chisquare: which should be used for new code. + Notes ----- The probability density function for the noncentral Chi-square @@ -1892,6 +1998,10 @@ cdef class RandomState: Also known as the Lorentz distribution. + .. note:: + New code should use the ``standard_cauchy`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- size : int or tuple of ints, optional @@ -1904,6 +2014,10 @@ cdef class RandomState: samples : ndarray or scalar The drawn samples. + See Also + -------- + Generator.standard_cauchy: which should be used for new code. + Notes ----- The probability density function for the full Cauchy distribution is @@ -1960,6 +2074,10 @@ cdef class RandomState: large, the result resembles that of the standard normal distribution (`standard_normal`). + .. note:: + New code should use the ``standard_t`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- df : float or array_like of floats @@ -1975,6 +2093,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized standard Student's t distribution. + See Also + -------- + Generator.standard_t: which should be used for new code. + Notes ----- The probability density function for the t distribution is @@ -2057,6 +2179,10 @@ cdef class RandomState: circle. It may be thought of as the circular analogue of the normal distribution. + .. note:: + New code should use the ``vonmises`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- mu : float or array_like of floats @@ -2078,6 +2204,7 @@ cdef class RandomState: -------- scipy.stats.vonmises : probability density function, distribution, or cumulative density function, etc. + Generator.vonmises: which should be used for new code. Notes ----- @@ -2150,6 +2277,10 @@ cdef class RandomState: 20 percent of the range, while the other 20 percent fill the remaining 80 percent of the range. + .. note:: + New code should use the ``pareto`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : float or array_like of floats @@ -2171,6 +2302,7 @@ cdef class RandomState: cumulative density function, etc. scipy.stats.genpareto : probability density function, distribution or cumulative density function, etc. + Generator.pareto: which should be used for new code. Notes ----- @@ -2239,6 +2371,10 @@ cdef class RandomState: The more common 2-parameter Weibull, including a scale parameter :math:`\\lambda` is just :math:`X = \\lambda(-ln(U))^{1/a}`. + .. note:: + New code should use the ``weibull`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : float or array_like of floats @@ -2260,6 +2396,7 @@ cdef class RandomState: scipy.stats.weibull_min scipy.stats.genextreme gumbel + Generator.weibull: which should be used for new code. Notes ----- @@ -2330,6 +2467,10 @@ cdef class RandomState: Also known as the power function distribution. + .. note:: + New code should use the ``power`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : float or array_like of floats @@ -2350,6 +2491,10 @@ cdef class RandomState: ValueError If a < 1. + See Also + -------- + Generator.power: which should be used for new code. + Notes ----- The probability density function is @@ -2433,6 +2578,10 @@ cdef class RandomState: difference between two independent, identically distributed exponential random variables. + .. note:: + New code should use the ``laplace`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- loc : float or array_like of floats, optional @@ -2451,6 +2600,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Laplace distribution. + See Also + -------- + Generator.laplace: which should be used for new code. + Notes ----- It has the probability density function @@ -2516,6 +2669,10 @@ cdef class RandomState: scale. For more information on the Gumbel distribution, see Notes and References below. + .. note:: + New code should use the ``gumbel`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- loc : float or array_like of floats, optional @@ -2540,6 +2697,7 @@ cdef class RandomState: scipy.stats.gumbel_r scipy.stats.genextreme weibull + Generator.gumbel: which should be used for new code. Notes ----- @@ -2633,6 +2791,10 @@ cdef class RandomState: Samples are drawn from a logistic distribution with specified parameters, loc (location or mean, also median), and scale (>0). + .. note:: + New code should use the ``logistic`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- loc : float or array_like of floats, optional @@ -2655,6 +2817,7 @@ cdef class RandomState: -------- scipy.stats.logistic : probability density function, distribution or cumulative density function, etc. + Generator.logistic: which should be used for new code. Notes ----- @@ -2715,6 +2878,10 @@ cdef class RandomState: deviation are not the values for the distribution itself, but of the underlying normal distribution it is derived from. + .. note:: + New code should use the ``lognormal`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- mean : float or array_like of floats, optional @@ -2737,6 +2904,7 @@ cdef class RandomState: -------- scipy.stats.lognorm : probability density function, distribution, cumulative density function, etc. + Generator.lognormal: which should be used for new code. Notes ----- @@ -2823,6 +2991,10 @@ cdef class RandomState: The :math:`\\chi` and Weibull distributions are generalizations of the Rayleigh. + .. note:: + New code should use the ``rayleigh`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- scale : float or array_like of floats, optional @@ -2838,6 +3010,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Rayleigh distribution. + See Also + -------- + Generator.rayleigh: which should be used for new code. + Notes ----- The probability density function for the Rayleigh distribution is @@ -2897,6 +3073,10 @@ cdef class RandomState: because there is an inverse relationship between the time to cover a unit distance and distance covered in unit time. + .. note:: + New code should use the ``wald`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- mean : float or array_like of floats @@ -2914,6 +3094,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Wald distribution. + See Also + -------- + Generator.wald: which should be used for new code. + Notes ----- The probability density function for the Wald distribution is @@ -2962,6 +3146,10 @@ cdef class RandomState: limit right. Unlike the other distributions, these parameters directly define the shape of the pdf. + .. note:: + New code should use the ``triangular`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- left : float or array_like of floats @@ -2983,6 +3171,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized triangular distribution. + See Also + -------- + Generator.triangular: which should be used for new code. + Notes ----- The probability density function for the triangular distribution is @@ -3061,6 +3253,10 @@ cdef class RandomState: n an integer >= 0 and p is in the interval [0,1]. (n may be input as a float, but it is truncated to an integer in use) + .. note:: + New code should use the ``binomial`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- n : int or array_like of ints @@ -3084,6 +3280,7 @@ cdef class RandomState: -------- scipy.stats.binom : probability density function, distribution or cumulative density function, etc. + Generator.binomial: which should be used for new code. Notes ----- @@ -3206,6 +3403,10 @@ cdef class RandomState: parameters, `n` successes and `p` probability of success where `n` is > 0 and `p` is in the interval [0, 1]. + .. note:: + New code should use the ``negative_binomial`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- n : float or array_like of floats @@ -3225,6 +3426,10 @@ cdef class RandomState: where each sample is equal to N, the number of failures that occurred before a total of n successes was reached. + See Also + -------- + Generator.negative_binomial: which should be used for new code. + Notes ----- The probability mass function of the negative binomial distribution is @@ -3283,6 +3488,10 @@ cdef class RandomState: The Poisson distribution is the limit of the binomial distribution for large N. + .. note:: + New code should use the ``poisson`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- lam : float or array_like of floats @@ -3299,6 +3508,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Poisson distribution. + See Also + -------- + Generator.poisson: which should be used for new code. + Notes ----- The Poisson distribution @@ -3361,6 +3574,10 @@ cdef class RandomState: frequency of an item is inversely proportional to its rank in a frequency table. + .. note:: + New code should use the ``zipf`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- a : float or array_like of floats @@ -3380,6 +3597,7 @@ cdef class RandomState: -------- scipy.stats.zipf : probability density function, distribution, or cumulative density function, etc. + Generator.zipf: which should be used for new code. Notes ----- @@ -3446,6 +3664,10 @@ cdef class RandomState: where `p` is the probability of success of an individual trial. + .. note:: + New code should use the ``geometric`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- p : float or array_like of floats @@ -3461,6 +3683,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized geometric distribution. + See Also + -------- + Generator.geometric: which should be used for new code. + Examples -------- Draw ten thousand values from the geometric distribution, @@ -3492,6 +3718,10 @@ cdef class RandomState: a bad selection), and `nsample` (number of items sampled, which is less than or equal to the sum ``ngood + nbad``). + .. note:: + New code should use the ``hypergeometric`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- ngood : int or array_like of ints @@ -3519,6 +3749,7 @@ cdef class RandomState: -------- scipy.stats.hypergeom : probability density function, distribution or cumulative density function, etc. + Generator.hypergeometric: which should be used for new code. Notes ----- @@ -3618,6 +3849,10 @@ cdef class RandomState: Samples are drawn from a log series distribution with specified shape parameter, 0 < ``p`` < 1. + .. note:: + New code should use the ``logseries`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- p : float or array_like of floats @@ -3637,6 +3872,7 @@ cdef class RandomState: -------- scipy.stats.logser : probability density function, distribution or cumulative density function, etc. + Generator.logseries: which should be used for new code. Notes ----- @@ -3706,6 +3942,10 @@ cdef class RandomState: (average or "center") and variance (standard deviation, or "width," squared) of the one-dimensional normal distribution. + .. note:: + New code should use the ``multivariate_normal`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- mean : 1-D array_like, of length N @@ -3733,6 +3973,10 @@ cdef class RandomState: In other words, each entry ``out[i,j,...,:]`` is an N-dimensional value drawn from the distribution. + See Also + -------- + Generator.multivariate_normal: which should be used for new code. + Notes ----- The mean is a coordinate in N-dimensional space, which represents the @@ -3872,6 +4116,10 @@ cdef class RandomState: ``X_i = [X_0, X_1, ..., X_p]``, represent the number of times the outcome was ``i``. + .. note:: + New code should use the ``multinomial`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- n : int @@ -3895,6 +4143,10 @@ cdef class RandomState: In other words, each entry ``out[i,j,...,:]`` is an N-dimensional value drawn from the distribution. + See Also + -------- + Generator.multinomial: which should be used for new code. + Examples -------- Throw a dice 20 times: @@ -3982,6 +4234,10 @@ cdef class RandomState: is a conjugate prior of a multinomial distribution in Bayesian inference. + .. note:: + New code should use the ``dirichlet`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- alpha : array @@ -4002,6 +4258,10 @@ cdef class RandomState: ValueError If any value in alpha is less than or equal to zero + See Also + -------- + Generator.dirichlet: which should be used for new code. + Notes ----- The Dirichlet distribution is a distribution over vectors @@ -4119,6 +4379,10 @@ cdef class RandomState: multi-dimensional array. The order of sub-arrays is changed but their contents remains the same. + .. note:: + New code should use the ``shuffle`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- x : array_like @@ -4128,6 +4392,10 @@ cdef class RandomState: ------- None + See Also + -------- + Generator.shuffle: which should be used for new code. + Examples -------- >>> arr = np.arange(10) @@ -4206,6 +4474,10 @@ cdef class RandomState: If `x` is a multi-dimensional array, it is only shuffled along its first index. + .. note:: + New code should use the ``permutation`` method of a ``default_rng()`` + instance instead; see `random-quick-start`. + Parameters ---------- x : int or array_like @@ -4218,6 +4490,9 @@ cdef class RandomState: out : ndarray Permuted sequence or array range. + See Also + -------- + Generator.permutation: which should be used for new code. Examples -------- diff --git a/numpy/random/setup.py b/numpy/random/setup.py index f9059d7d7..1b093d6d3 100644 --- a/numpy/random/setup.py +++ b/numpy/random/setup.py @@ -34,6 +34,7 @@ def configuration(parent_package='', top_path=None): defs.append(('NPY_NO_DEPRECATED_API', 0)) config.add_data_dir('tests') + config.add_data_dir('_examples') EXTRA_LINK_ARGS = [] # Math lib @@ -77,8 +78,8 @@ def configuration(parent_package='', top_path=None): libraries=EXTRA_LIBRARIES, extra_compile_args=EXTRA_COMPILE_ARGS, extra_link_args=EXTRA_LINK_ARGS, - depends=['_%s.pyx' % gen, 'bit_generator.pyx', - 'bit_generator.pxd'], + depends=['_%s.pyx' % gen, '_bit_generator.pyx', + '_bit_generator.pxd'], define_macros=_defs, ) for gen in ['_common', '_bit_generator']: @@ -92,6 +93,7 @@ def configuration(parent_package='', top_path=None): depends=['%s.pyx' % gen, '%s.pxd' % gen,], define_macros=defs, ) + config.add_data_files('{0}.pxd'.format(gen)) other_srcs = [ 'src/distributions/logfactorial.c', 'src/distributions/distributions.c', @@ -110,6 +112,7 @@ def configuration(parent_package='', top_path=None): depends=['%s.pyx' % gen], define_macros=defs, ) + config.add_data_files('_bounded_integers.pxd') config.add_extension('mtrand', sources=['mtrand.c', 'src/legacy/legacy-distributions.c', @@ -122,6 +125,7 @@ def configuration(parent_package='', top_path=None): depends=['mtrand.pyx'], define_macros=defs + LEGACY_DEFS, ) + config.add_data_files('__init__.pxd') return config diff --git a/numpy/random/src/distributions/distributions.c b/numpy/random/src/distributions/distributions.c index ab8de8bcb..0b46dc6d8 100644 --- a/numpy/random/src/distributions/distributions.c +++ b/numpy/random/src/distributions/distributions.c @@ -1,4 +1,4 @@ -#include "include/distributions.h" +#include "numpy/random/distributions.h" #include "ziggurat_constants.h" #include "logfactorial.h" @@ -41,19 +41,7 @@ void random_standard_uniform_fill_f(bitgen_t *bitgen_state, npy_intp cnt, float } } -double random_standard_exponential(bitgen_t *bitgen_state) { - return -log(1.0 - next_double(bitgen_state)); -} - -void random_standard_exponential_fill(bitgen_t * bitgen_state, npy_intp cnt, double * out) -{ - npy_intp i; - for (i = 0; i < cnt; i++) { - out[i] = random_standard_exponential(bitgen_state); - } -} - -static double standard_exponential_zig_unlikely(bitgen_t *bitgen_state, +static double standard_exponential_unlikely(bitgen_t *bitgen_state, uint8_t idx, double x) { if (idx == 0) { /* Switch to 1.0 - U to avoid log(0.0), see GH 13361 */ @@ -63,11 +51,11 @@ static double standard_exponential_zig_unlikely(bitgen_t *bitgen_state, exp(-x)) { return x; } else { - return random_standard_exponential_zig(bitgen_state); + return random_standard_exponential(bitgen_state); } } -double random_standard_exponential_zig(bitgen_t *bitgen_state) { +double random_standard_exponential(bitgen_t *bitgen_state) { uint64_t ri; uint8_t idx; double x; @@ -79,30 +67,18 @@ double random_standard_exponential_zig(bitgen_t *bitgen_state) { if (ri < ke_double[idx]) { return x; /* 98.9% of the time we return here 1st try */ } - return standard_exponential_zig_unlikely(bitgen_state, idx, x); -} - -void random_standard_exponential_zig_fill(bitgen_t * bitgen_state, npy_intp cnt, double * out) -{ - npy_intp i; - for (i = 0; i < cnt; i++) { - out[i] = random_standard_exponential_zig(bitgen_state); - } -} - -float random_standard_exponential_f(bitgen_t *bitgen_state) { - return -logf(1.0f - next_float(bitgen_state)); + return standard_exponential_unlikely(bitgen_state, idx, x); } -void random_standard_exponential_fill_f(bitgen_t * bitgen_state, npy_intp cnt, float * out) +void random_standard_exponential_fill(bitgen_t * bitgen_state, npy_intp cnt, double * out) { npy_intp i; for (i = 0; i < cnt; i++) { - out[i] = random_standard_exponential_f(bitgen_state); + out[i] = random_standard_exponential(bitgen_state); } } -static float standard_exponential_zig_unlikely_f(bitgen_t *bitgen_state, +static float standard_exponential_unlikely_f(bitgen_t *bitgen_state, uint8_t idx, float x) { if (idx == 0) { /* Switch to 1.0 - U to avoid log(0.0), see GH 13361 */ @@ -112,11 +88,11 @@ static float standard_exponential_zig_unlikely_f(bitgen_t *bitgen_state, expf(-x)) { return x; } else { - return random_standard_exponential_zig_f(bitgen_state); + return random_standard_exponential_f(bitgen_state); } } -float random_standard_exponential_zig_f(bitgen_t *bitgen_state) { +float random_standard_exponential_f(bitgen_t *bitgen_state) { uint32_t ri; uint8_t idx; float x; @@ -128,17 +104,34 @@ float random_standard_exponential_zig_f(bitgen_t *bitgen_state) { if (ri < ke_float[idx]) { return x; /* 98.9% of the time we return here 1st try */ } - return standard_exponential_zig_unlikely_f(bitgen_state, idx, x); + return standard_exponential_unlikely_f(bitgen_state, idx, x); +} + +void random_standard_exponential_fill_f(bitgen_t * bitgen_state, npy_intp cnt, float * out) +{ + npy_intp i; + for (i = 0; i < cnt; i++) { + out[i] = random_standard_exponential_f(bitgen_state); + } +} + +void random_standard_exponential_inv_fill(bitgen_t * bitgen_state, npy_intp cnt, double * out) +{ + npy_intp i; + for (i = 0; i < cnt; i++) { + out[i] = -log(1.0 - next_double(bitgen_state)); + } } -void random_standard_exponential_zig_fill_f(bitgen_t * bitgen_state, npy_intp cnt, float * out) +void random_standard_exponential_inv_fill_f(bitgen_t * bitgen_state, npy_intp cnt, float * out) { npy_intp i; for (i = 0; i < cnt; i++) { - out[i] = random_standard_exponential_zig_f(bitgen_state); + out[i] = -log(1.0 - next_float(bitgen_state)); } } + double random_standard_normal(bitgen_t *bitgen_state) { uint64_t r; int sign; @@ -228,13 +221,13 @@ double random_standard_gamma(bitgen_t *bitgen_state, double U, V, X, Y; if (shape == 1.0) { - return random_standard_exponential_zig(bitgen_state); + return random_standard_exponential(bitgen_state); } else if (shape == 0.0) { return 0.0; } else if (shape < 1.0) { for (;;) { U = next_double(bitgen_state); - V = random_standard_exponential_zig(bitgen_state); + V = random_standard_exponential(bitgen_state); if (U <= 1.0 - shape) { X = pow(U, 1. / shape); if (X <= V) { @@ -274,13 +267,13 @@ float random_standard_gamma_f(bitgen_t *bitgen_state, float U, V, X, Y; if (shape == 1.0f) { - return random_standard_exponential_zig_f(bitgen_state); + return random_standard_exponential_f(bitgen_state); } else if (shape == 0.0) { return 0.0; } else if (shape < 1.0f) { for (;;) { U = next_float(bitgen_state); - V = random_standard_exponential_zig_f(bitgen_state); + V = random_standard_exponential_f(bitgen_state); if (U <= 1.0f - shape) { X = powf(U, 1.0f / shape); if (X <= V) { @@ -391,7 +384,7 @@ double random_normal(bitgen_t *bitgen_state, double loc, double scale) { } double random_exponential(bitgen_t *bitgen_state, double scale) { - return scale * random_standard_exponential_zig(bitgen_state); + return scale * random_standard_exponential(bitgen_state); } double random_uniform(bitgen_t *bitgen_state, double lower, double range) { @@ -455,18 +448,18 @@ double random_standard_cauchy(bitgen_t *bitgen_state) { } double random_pareto(bitgen_t *bitgen_state, double a) { - return exp(random_standard_exponential_zig(bitgen_state) / a) - 1; + return exp(random_standard_exponential(bitgen_state) / a) - 1; } double random_weibull(bitgen_t *bitgen_state, double a) { if (a == 0.0) { return 0.0; } - return pow(random_standard_exponential_zig(bitgen_state), 1. / a); + return pow(random_standard_exponential(bitgen_state), 1. / a); } double random_power(bitgen_t *bitgen_state, double a) { - return pow(1 - exp(-random_standard_exponential_zig(bitgen_state)), 1. / a); + return pow(1 - exp(-random_standard_exponential(bitgen_state)), 1. / a); } double random_laplace(bitgen_t *bitgen_state, double loc, double scale) { diff --git a/numpy/random/src/distributions/random_hypergeometric.c b/numpy/random/src/distributions/random_hypergeometric.c index da5ea9c68..0da49bd62 100644 --- a/numpy/random/src/distributions/random_hypergeometric.c +++ b/numpy/random/src/distributions/random_hypergeometric.c @@ -1,4 +1,4 @@ -#include "include/distributions.h" +#include "numpy/random/distributions.h" #include "logfactorial.h" #include <stdint.h> diff --git a/numpy/random/src/distributions/random_mvhg_count.c b/numpy/random/src/distributions/random_mvhg_count.c index 9c0cc045d..7cbed1f9e 100644 --- a/numpy/random/src/distributions/random_mvhg_count.c +++ b/numpy/random/src/distributions/random_mvhg_count.c @@ -2,10 +2,10 @@ #include <stdlib.h> #include <stdbool.h> -#include "include/distributions.h" +#include "numpy/random/distributions.h" /* - * random_mvhg_count + * random_multivariate_hypergeometric_count * * Draw variates from the multivariate hypergeometric distribution-- * the "count" algorithm. @@ -57,7 +57,7 @@ * * the product num_variates * num_colors does not overflow */ -int random_mvhg_count(bitgen_t *bitgen_state, +int random_multivariate_hypergeometric_count(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, diff --git a/numpy/random/src/distributions/random_mvhg_marginals.c b/numpy/random/src/distributions/random_mvhg_marginals.c index 301a4acad..809d129de 100644 --- a/numpy/random/src/distributions/random_mvhg_marginals.c +++ b/numpy/random/src/distributions/random_mvhg_marginals.c @@ -3,12 +3,12 @@ #include <stdbool.h> #include <math.h> -#include "include/distributions.h" +#include "numpy/random/distributions.h" #include "logfactorial.h" /* - * random_mvhg_marginals + * random_multivariate_hypergeometric_marginals * * Draw samples from the multivariate hypergeometric distribution-- * the "marginals" algorithm. @@ -95,7 +95,7 @@ * * the product num_variates * num_colors does not overflow */ -void random_mvhg_marginals(bitgen_t *bitgen_state, +void random_multivariate_hypergeometric_marginals(bitgen_t *bitgen_state, int64_t total, size_t num_colors, int64_t *colors, int64_t nsample, diff --git a/numpy/random/tests/test_direct.py b/numpy/random/tests/test_direct.py index 34d7bd278..9f77f0ad2 100644 --- a/numpy/random/tests/test_direct.py +++ b/numpy/random/tests/test_direct.py @@ -1,5 +1,6 @@ import os from os.path import join +import sys import numpy as np from numpy.testing import (assert_equal, assert_allclose, assert_array_equal, @@ -26,6 +27,12 @@ try: except ImportError: MISSING_CTYPES = False +if sys.flags.optimize > 1: + # no docstrings present to inspect when PYTHONOPTIMIZE/Py_OptimizeFlag > 1 + # cffi cannot succeed + MISSING_CFFI = True + + pwd = os.path.dirname(os.path.abspath(__file__)) diff --git a/numpy/random/tests/test_extending.py b/numpy/random/tests/test_extending.py new file mode 100644 index 000000000..807de1a25 --- /dev/null +++ b/numpy/random/tests/test_extending.py @@ -0,0 +1,51 @@ +import os, sys +import pytest +import warnings + +try: + import cffi +except ImportError: + cffi = None + +if sys.flags.optimize > 1: + # no docstrings present to inspect when PYTHONOPTIMIZE/Py_OptimizeFlag > 1 + # cffi cannot succeed + cffi = None + +try: + with warnings.catch_warnings(record=True) as w: + # numba issue gh-4733 + warnings.filterwarnings('always', '', DeprecationWarning) + import numba +except ImportError: + numba = None + +try: + import cython +except ImportError: + cython = None + +@pytest.mark.skipif(cython is None, reason="requires cython") +def test_cython(): + curdir = os.getcwd() + argv = sys.argv + examples = (os.path.dirname(__file__), '..', '_examples') + try: + os.chdir(os.path.join(*examples)) + sys.argv = argv[:1] + ['build'] + with warnings.catch_warnings(record=True) as w: + # setuptools issue gh-1885 + warnings.filterwarnings('always', '', DeprecationWarning) + from numpy.random._examples.cython import setup + finally: + sys.argv = argv + os.chdir(curdir) + +@pytest.mark.skipif(numba is None or cffi is None, + reason="requires numba and cffi") +def test_numba(): + from numpy.random._examples.numba import extending + +@pytest.mark.skipif(cffi is None, reason="requires cffi") +def test_cffi(): + from numpy.random._examples.cffi import extending diff --git a/numpy/testing/_private/utils.py b/numpy/testing/_private/utils.py index 8a31fcf15..8599222d3 100644 --- a/numpy/testing/_private/utils.py +++ b/numpy/testing/_private/utils.py @@ -21,6 +21,7 @@ import pprint from numpy.core import( intp, float32, empty, arange, array_repr, ndarray, isnat, array) +import numpy.__config__ if sys.version_info[0] >= 3: from io import StringIO @@ -39,7 +40,7 @@ __all__ = [ 'SkipTest', 'KnownFailureException', 'temppath', 'tempdir', 'IS_PYPY', 'HAS_REFCOUNT', 'suppress_warnings', 'assert_array_compare', '_assert_valid_refcount', '_gen_alignment_data', 'assert_no_gc_cycles', - 'break_cycles', + 'break_cycles', 'HAS_LAPACK64' ] @@ -53,6 +54,7 @@ verbose = 0 IS_PYPY = platform.python_implementation() == 'PyPy' HAS_REFCOUNT = getattr(sys, 'getrefcount', None) is not None +HAS_LAPACK64 = hasattr(numpy.__config__, 'lapack64__opt_info') def import_nose(): @@ -284,6 +286,10 @@ def assert_equal(actual, desired, err_msg='', verbose=True): check that all elements of these objects are equal. An exception is raised at the first conflicting values. + When one of `actual` and `desired` is a scalar and the other is array_like, + the function checks that each element of the array_like object is equal to + the scalar. + This function handles NaN comparisons as if NaN was a "normal" number. That is, no assertion is raised if both objects have NaNs in the same positions. This is in contrast to the IEEE standard on NaNs, which says @@ -374,21 +380,6 @@ def assert_equal(actual, desired, err_msg='', verbose=True): if isscalar(desired) != isscalar(actual): raise AssertionError(msg) - # Inf/nan/negative zero handling - try: - isdesnan = gisnan(desired) - isactnan = gisnan(actual) - if isdesnan and isactnan: - return # both nan, so equal - - # handle signed zero specially for floats - if desired == 0 and actual == 0: - if not signbit(desired) == signbit(actual): - raise AssertionError(msg) - - except (TypeError, ValueError, NotImplementedError): - pass - try: isdesnat = isnat(desired) isactnat = isnat(actual) @@ -404,6 +395,33 @@ def assert_equal(actual, desired, err_msg='', verbose=True): except (TypeError, ValueError, NotImplementedError): pass + # Inf/nan/negative zero handling + try: + isdesnan = gisnan(desired) + isactnan = gisnan(actual) + if isdesnan and isactnan: + return # both nan, so equal + + # handle signed zero specially for floats + array_actual = array(actual) + array_desired = array(desired) + if (array_actual.dtype.char in 'Mm' or + array_desired.dtype.char in 'Mm'): + # version 1.18 + # until this version, gisnan failed for datetime64 and timedelta64. + # Now it succeeds but comparison to scalar with a different type + # emits a DeprecationWarning. + # Avoid that by skipping the next check + raise NotImplementedError('cannot compare to a scalar ' + 'with a different type') + + if desired == 0 and actual == 0: + if not signbit(desired) == signbit(actual): + raise AssertionError(msg) + + except (TypeError, ValueError, NotImplementedError): + pass + try: # Explicitly use __eq__ for comparison, gh-2552 if not (desired == actual): @@ -841,10 +859,11 @@ def assert_array_equal(x, y, err_msg='', verbose=True): Raises an AssertionError if two array_like objects are not equal. Given two array_like objects, check that the shape is equal and all - elements of these objects are equal. An exception is raised at - shape mismatch or conflicting values. In contrast to the standard usage - in numpy, NaNs are compared like numbers, no assertion is raised if - both objects have NaNs in the same positions. + elements of these objects are equal (but see the Notes for the special + handling of a scalar). An exception is raised at shape mismatch or + conflicting values. In contrast to the standard usage in numpy, NaNs + are compared like numbers, no assertion is raised if both objects have + NaNs in the same positions. The usual caution for verifying equality with floating point numbers is advised. @@ -871,6 +890,12 @@ def assert_array_equal(x, y, err_msg='', verbose=True): relative and/or absolute precision. assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal + Notes + ----- + When one of `x` and `y` is a scalar and the other is array_like, the + function checks that each element of the array_like object is equal to + the scalar. + Examples -------- The first assert does not raise an exception: @@ -878,7 +903,7 @@ def assert_array_equal(x, y, err_msg='', verbose=True): >>> np.testing.assert_array_equal([1.0,2.33333,np.nan], ... [np.exp(0),2.33333, np.nan]) - Assert fails with numerical inprecision with floats: + Assert fails with numerical imprecision with floats: >>> np.testing.assert_array_equal([1.0,np.pi,np.nan], ... [1, np.sqrt(np.pi)**2, np.nan]) @@ -899,6 +924,12 @@ def assert_array_equal(x, y, err_msg='', verbose=True): ... [1, np.sqrt(np.pi)**2, np.nan], ... rtol=1e-10, atol=0) + As mentioned in the Notes section, `assert_array_equal` has special + handling for scalars. Here the test checks that each value in `x` is 3: + + >>> x = np.full((2, 5), fill_value=3) + >>> np.testing.assert_array_equal(x, 3) + """ __tracebackhide__ = True # Hide traceback for py.test assert_array_compare(operator.__eq__, x, y, err_msg=err_msg, @@ -2351,3 +2382,97 @@ def break_cycles(): gc.collect() # one more, just to make sure gc.collect() + + +def requires_memory(free_bytes): + """Decorator to skip a test if not enough memory is available""" + import pytest + + def decorator(func): + @wraps(func) + def wrapper(*a, **kw): + msg = check_free_memory(free_bytes) + if msg is not None: + pytest.skip(msg) + + try: + return func(*a, **kw) + except MemoryError: + # Probably ran out of memory regardless: don't regard as failure + pytest.xfail("MemoryError raised") + + return wrapper + + return decorator + + +def check_free_memory(free_bytes): + """ + Check whether `free_bytes` amount of memory is currently free. + Returns: None if enough memory available, otherwise error message + """ + env_var = 'NPY_AVAILABLE_MEM' + env_value = os.environ.get(env_var) + if env_value is not None: + try: + mem_free = _parse_size(env_value) + except ValueError as exc: + raise ValueError('Invalid environment variable {}: {!s}'.format( + env_var, exc)) + + msg = ('{0} GB memory required, but environment variable ' + 'NPY_AVAILABLE_MEM={1} set'.format( + free_bytes/1e9, env_value)) + else: + mem_free = _get_mem_available() + + if mem_free is None: + msg = ("Could not determine available memory; set NPY_AVAILABLE_MEM " + "environment variable (e.g. NPY_AVAILABLE_MEM=16GB) to run " + "the test.") + mem_free = -1 + else: + msg = '{0} GB memory required, but {1} GB available'.format( + free_bytes/1e9, mem_free/1e9) + + return msg if mem_free < free_bytes else None + + +def _parse_size(size_str): + """Convert memory size strings ('12 GB' etc.) to float""" + suffixes = {'': 1, 'b': 1, + 'k': 1000, 'm': 1000**2, 'g': 1000**3, 't': 1000**4, + 'kb': 1000, 'mb': 1000**2, 'gb': 1000**3, 'tb': 1000**4, + 'kib': 1024, 'mib': 1024**2, 'gib': 1024**3, 'tib': 1024**4} + + size_re = re.compile(r'^\s*(\d+|\d+\.\d+)\s*({0})\s*$'.format( + '|'.join(suffixes.keys())), re.I) + + m = size_re.match(size_str.lower()) + if not m or m.group(2) not in suffixes: + raise ValueError("value {!r} not a valid size".format(size_str)) + return int(float(m.group(1)) * suffixes[m.group(2)]) + + +def _get_mem_available(): + """Return available memory in bytes, or None if unknown.""" + try: + import psutil + return psutil.virtual_memory().available + except (ImportError, AttributeError): + pass + + if sys.platform.startswith('linux'): + info = {} + with open('/proc/meminfo', 'r') as f: + for line in f: + p = line.split() + info[p[0].strip(':').lower()] = int(p[1]) * 1024 + + if 'memavailable' in info: + # Linux >= 3.14 + return info['memavailable'] + else: + return info['memfree'] + info['cached'] + + return None diff --git a/numpy/tests/test_public_api.py b/numpy/tests/test_public_api.py index c71d03432..0484bb8cd 100644 --- a/numpy/tests/test_public_api.py +++ b/numpy/tests/test_public_api.py @@ -386,7 +386,7 @@ SKIP_LIST_2 = [ 'numpy.matlib.fft', 'numpy.matlib.random', 'numpy.matlib.ctypeslib', - 'numpy.matlib.ma' + 'numpy.matlib.ma', ] @@ -27,8 +27,8 @@ import subprocess import textwrap -if sys.version_info[:2] < (3, 5): - raise RuntimeError("Python version >= 3.5 required.") +if sys.version_info[:2] < (3, 6): + raise RuntimeError("Python version >= 3.6 required.") import builtins @@ -41,7 +41,6 @@ License :: OSI Approved Programming Language :: C Programming Language :: Python Programming Language :: Python :: 3 -Programming Language :: Python :: 3.5 Programming Language :: Python :: 3.6 Programming Language :: Python :: 3.7 Programming Language :: Python :: 3.8 @@ -56,7 +55,7 @@ Operating System :: MacOS """ MAJOR = 1 -MINOR = 18 +MINOR = 19 MICRO = 0 ISRELEASED = False VERSION = '%d.%d.%d' % (MAJOR, MINOR, MICRO) diff --git a/site.cfg.example b/site.cfg.example index b6b0175d6..a58039df3 100644 --- a/site.cfg.example +++ b/site.cfg.example @@ -132,6 +132,26 @@ # include_dirs = /opt/OpenBLAS/include # runtime_library_dirs = /opt/OpenBLAS/lib +# OpenBLAS (64-bit with suffix) +# ----------------------------- +# OpenBLAS can be compiled with 64-bit integer size and symbol suffix '64_' +# (INTERFACE64=1 SYMBOLSUFFIX=64_). OpenBLAS built with this setting are also +# provided by some Linux distributions (e.g. Fedora's 64-bit openblas packages). +# This is an emerging "standard" for 64-bit BLAS/LAPACK, avoiding symbol clashes +# with 32-bit BLAS/LAPACK. +# +# To build Numpy with such 64-bit BLAS/LAPACK, set environment variable +# NPY_USE_BLAS64_=1 at build time. +# +# See: +# https://github.com/xianyi/OpenBLAS/issues/646 +# +# [openblas64_] +# libraries = openblas64_ +# library_dirs = /opt/OpenBLAS/lib +# include_dirs = /opt/OpenBLAS/include +# runtime_library_dirs = /opt/OpenBLAS/lib + # BLIS # ---- # BLIS (https://github.com/flame/blis) also provides a BLAS interface. It's a diff --git a/test_requirements.txt b/test_requirements.txt index 32b95897a..627150673 100644 --- a/test_requirements.txt +++ b/test_requirements.txt @@ -1,7 +1,9 @@ cython==0.29.14 -pytest==5.2.2 +pytest==5.3.1 pytz==2019.3 pytest-cov==2.8.1 pickle5; python_version == '3.7' pickle5; python_version == '3.6' and platform_python_implementation != 'PyPy' nose +# for numpy.random.test.test_extending +cffi diff --git a/tools/refguide_check.py b/tools/refguide_check.py index c20807267..ba045cebf 100644 --- a/tools/refguide_check.py +++ b/tools/refguide_check.py @@ -2,8 +2,10 @@ """ refguide_check.py [OPTIONS] [-- ARGS] -Check for a NumPy submodule whether the objects in its __all__ dict -correspond to the objects included in the reference guide. +- Check for a NumPy submodule whether the objects in its __all__ dict + correspond to the objects included in the reference guide. +- Check docstring examples +- Check example blocks in RST files Example of usage:: @@ -15,12 +17,13 @@ objects are left out of the refguide for a good reason (it's an alias of another function, or deprecated, or ...) Another use of this helper script is to check validity of code samples -in docstrings. This is different from doctesting [we do not aim to have -numpy docstrings doctestable!], this is just to make sure that code in -docstrings is valid python:: +in docstrings:: - $ python refguide_check.py --doctests optimize + $ python refguide_check.py --doctests ma +or in RST-based documentations:: + + $ python refguide_check.py --rst docs """ from __future__ import print_function @@ -47,9 +50,11 @@ import numpy as np sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'doc', 'sphinxext')) from numpydoc.docscrape_sphinx import get_doc_object +SKIPBLOCK = doctest.register_optionflag('SKIPBLOCK') + if parse_version(sphinx.__version__) >= parse_version('1.5'): # Enable specific Sphinx directives - from sphinx.directives import SeeAlso, Only + from sphinx.directives.other import SeeAlso, Only directives.register_directive('seealso', SeeAlso) directives.register_directive('only', Only) else: @@ -102,6 +107,21 @@ DOCTEST_SKIPLIST = set([ 'numpy.lib.Repository', ]) +# Skip non-numpy RST files, historical release notes +# Any single-directory exact match will skip the directory and all subdirs. +# Any exact match (like 'doc/release') will scan subdirs but skip files in +# the matched directory. +# Any filename will skip that file +RST_SKIPLIST = [ + 'scipy-sphinx-theme', + 'sphinxext', + 'neps', + 'changelog', + 'doc/release', + 'doc/source/release', + 'c-info.ufunc-tutorial.rst', +] + # these names are not required to be present in ALL despite being in # autosummary:: listing REFGUIDE_ALL_SKIPLIST = [ @@ -132,6 +152,17 @@ HAVE_MATPLOTLIB = False def short_path(path, cwd=None): """ Return relative or absolute path name, whichever is shortest. + + Parameters + ---------- + path: str or None + + cwd: str or None + + Returns + ------- + str + Relative path or absolute path based on current working directory """ if not isinstance(path, str): return path @@ -145,17 +176,32 @@ def short_path(path, cwd=None): def find_names(module, names_dict): - # Refguide entries: - # - # - 3 spaces followed by function name, and maybe some spaces, some - # dashes, and an explanation; only function names listed in - # refguide are formatted like this (mostly, there may be some false - # positives) - # - # - special directives, such as data and function - # - # - (scipy.constants only): quoted list - # + """ + Finds the occurrences of function names, special directives like data + and functions and scipy constants in the docstrings of `module`. The + following patterns are searched for: + + * 3 spaces followed by function name, and maybe some spaces, some + dashes, and an explanation; only function names listed in + refguide are formatted like this (mostly, there may be some false + positives + * special directives, such as data and function + * (scipy.constants only): quoted list + + The `names_dict` is updated by reference and accessible in calling method + + Parameters + ---------- + module : ModuleType + The module, whose docstrings is to be searched + names_dict : dict + Dictionary which contains module name as key and a set of found + function names and directives as value + + Returns + ------- + None + """ patterns = [ r"^\s\s\s([a-z_0-9A-Z]+)(\s+-+.*)?$", r"^\.\. (?:data|function)::\s*([a-z_0-9A-Z]+)\s*$" @@ -183,7 +229,23 @@ def find_names(module, names_dict): def get_all_dict(module): - """Return a copy of the __all__ dict with irrelevant items removed.""" + """ + Return a copy of the __all__ dict with irrelevant items removed. + + Parameters + ---------- + module : ModuleType + The module whose __all__ dict has to be processed + + Returns + ------- + deprecated : list + List of callable and deprecated sub modules + not_deprecated : list + List of non callable or non deprecated sub modules + others : list + List of remaining types of sub modules + """ if hasattr(module, "__all__"): all_dict = copy.deepcopy(module.__all__) else: @@ -219,7 +281,30 @@ def get_all_dict(module): def compare(all_dict, others, names, module_name): - """Return sets of objects only in __all__, refguide, or completely missing.""" + """ + Return sets of objects from all_dict. + Will return three sets: + {in module_name.__all__}, + {in REFGUIDE*}, + and {missing from others} + + Parameters + ---------- + all_dict : list + List of non deprecated sub modules for module_name + others : list + List of sub modules for module_name + names : set + Set of function names or special directives present in + docstring of module_name + module_name : ModuleType + + Returns + ------- + only_all : set + only_ref : set + missing : set + """ only_all = set() for name in all_dict: if name not in names: @@ -243,7 +328,19 @@ def compare(all_dict, others, names, module_name): return only_all, only_ref, missing + def is_deprecated(f): + """ + Check if module `f` is deprecated + + Parameter + --------- + f : ModuleType + + Returns + ------- + bool + """ with warnings.catch_warnings(record=True) as w: warnings.simplefilter("error") try: @@ -254,7 +351,32 @@ def is_deprecated(f): pass return False + def check_items(all_dict, names, deprecated, others, module_name, dots=True): + """ + Check that `all_dict` is consistent with the `names` in `module_name` + For instance, that there are no deprecated or extra objects. + + Parameters + ---------- + all_dict : list + + names : set + + deprecated : list + + others : list + + module_name : ModuleType + + dots : bool + Whether to print a dot for each check + + Returns + ------- + list + List of [(name, success_flag, output)...] + """ num_all = len(all_dict) num_ref = len(names) @@ -305,6 +427,21 @@ def check_items(all_dict, names, deprecated, others, module_name, dots=True): def validate_rst_syntax(text, name, dots=True): + """ + Validates the doc string in a snippet of documentation + `text` from file `name` + Parameters + ---------- + text : str + Docstring text + name : str + File name for which the doc string is to be validated + dots : bool + Whether to print a dot symbol for each check + Returns + ------- + (bool, str) + """ if text is None: if dots: output_dot('E') @@ -381,7 +518,16 @@ def check_rest(module, names, dots=True): """ Check reStructuredText formatting of docstrings - Returns: [(name, success_flag, output), ...] + Parameters + ---------- + module : ModuleType + + names : set + + Returns + ------- + result : list + List of [(module_name, success_flag, output),...] """ try: @@ -450,6 +596,7 @@ DEFAULT_NAMESPACE = {'np': np} # the namespace to do checks in CHECK_NAMESPACE = { 'np': np, + 'numpy': np, 'assert_allclose': np.testing.assert_allclose, 'assert_equal': np.testing.assert_equal, # recognize numpy repr's @@ -465,10 +612,15 @@ CHECK_NAMESPACE = { 'nan': np.nan, 'NaN': np.nan, 'inf': np.inf, - 'Inf': np.inf,} + 'Inf': np.inf, + 'StringIO': io.StringIO, +} class DTRunner(doctest.DocTestRunner): + """ + The doctest runner + """ DIVIDER = "\n" def __init__(self, item_name, checker=None, verbose=None, optionflags=0): @@ -502,6 +654,9 @@ class DTRunner(doctest.DocTestRunner): example, got) class Checker(doctest.OutputChecker): + """ + Check the docstrings + """ obj_pattern = re.compile('at 0x[0-9a-fA-F]+>') int_pattern = re.compile('^[0-9]+L?$') vanilla = doctest.OutputChecker() @@ -517,7 +672,7 @@ class Checker(doctest.OutputChecker): self.parse_namedtuples = parse_namedtuples self.atol, self.rtol = atol, rtol if ns is None: - self.ns = dict(CHECK_NAMESPACE) + self.ns = CHECK_NAMESPACE else: self.ns = ns @@ -581,9 +736,9 @@ class Checker(doctest.OutputChecker): # and then compare the tuples. try: num = len(a_want) - regex = ('[\w\d_]+\(' + - ', '.join(['[\w\d_]+=(.+)']*num) + - '\)') + regex = (r'[\w\d_]+\(' + + ', '.join([r'[\w\d_]+=(.+)']*num) + + r'\)') grp = re.findall(regex, got.replace('\n', ' ')) if len(grp) > 1: # no more than one for now return False @@ -615,9 +770,23 @@ class Checker(doctest.OutputChecker): def _run_doctests(tests, full_name, verbose, doctest_warnings): - """Run modified doctests for the set of `tests`. + """ + Run modified doctests for the set of `tests`. + + Parameters + ---------- + tests: list + + full_name : str - Returns: list of [(success_flag, output), ...] + verbose : bool + + doctest_warning : bool + + Returns + ------- + tuple(bool, list) + Tuple of (success, output) """ flags = NORMALIZE_WHITESPACE | ELLIPSIS | IGNORE_EXCEPTION_DETAIL runner = DTRunner(full_name, checker=Checker(), optionflags=flags, @@ -629,7 +798,9 @@ def _run_doctests(tests, full_name, verbose, doctest_warnings): output.append(msg) class MyStderr(object): - """Redirect stderr to the current stdout""" + """ + Redirect stderr to the current stdout + """ def write(self, msg): if doctest_warnings: sys.stdout.write(msg) @@ -655,11 +826,21 @@ def _run_doctests(tests, full_name, verbose, doctest_warnings): # try to ensure random seed is NOT reproducible np.random.seed(None) + ns = {} for t in tests: + # We broke the tests up into chunks to try to avoid PSEUDOCODE + # This has the unfortunate side effect of restarting the global + # namespace for each test chunk, so variables will be "lost" after + # a chunk. Chain the globals to avoid this + t.globs.update(ns) t.filename = short_path(t.filename, cwd) - fails, successes = runner.run(t, out=out) + # Process our options + if any([SKIPBLOCK in ex.options for ex in t.examples]): + continue + fails, successes = runner.run(t, out=out, clear_globs=False) if fails > 0: success = False + ns = t.globs finally: sys.stderr = old_stderr os.chdir(cwd) @@ -672,9 +853,25 @@ def _run_doctests(tests, full_name, verbose, doctest_warnings): def check_doctests(module, verbose, ns=None, dots=True, doctest_warnings=False): - """Check code in docstrings of the module's public symbols. - - Returns: list of [(item_name, success_flag, output), ...] + """ + Check code in docstrings of the module's public symbols. + + Parameters + ---------- + module : ModuleType + Name of module + verbose : bool + Should the result be verbose + ns : dict + Name space of module + dots : bool + + doctest_warnings : bool + + Returns + ------- + results : list + List of [(item_name, success_flag, output), ...] """ if ns is None: ns = dict(DEFAULT_NAMESPACE) @@ -724,13 +921,30 @@ def check_doctests(module, verbose, ns=None, def check_doctests_testfile(fname, verbose, ns=None, dots=True, doctest_warnings=False): - """Check code in a text file. + """ + Check code in a text file. Mimic `check_doctests` above, differing mostly in test discovery. (which is borrowed from stdlib's doctest.testfile here, https://github.com/python-git/python/blob/master/Lib/doctest.py) - Returns: list of [(item_name, success_flag, output), ...] + Parameters + ---------- + fname : str + File name + verbose : bool + + ns : dict + Name space + + dots : bool + + doctest_warnings : bool + + Returns + ------- + list + List of [(item_name, success_flag, output), ...] Notes ----- @@ -757,10 +971,9 @@ def check_doctests_testfile(fname, verbose, ns=None, 5 """ - results = [] - if ns is None: - ns = dict(DEFAULT_NAMESPACE) + ns = CHECK_NAMESPACE + results = [] _, short_name = os.path.split(fname) if short_name in DOCTEST_SKIPLIST: @@ -782,20 +995,32 @@ def check_doctests_testfile(fname, verbose, ns=None, # split the text into "blocks" and try to detect and omit pseudocode blocks. parser = doctest.DocTestParser() good_parts = [] + base_line_no = 0 for part in text.split('\n\n'): - tests = parser.get_doctest(part, ns, fname, fname, 0) + try: + tests = parser.get_doctest(part, ns, fname, fname, base_line_no) + except ValueError as e: + if e.args[0].startswith('line '): + # fix line number since `parser.get_doctest` does not increment + # the reported line number by base_line_no in the error message + parts = e.args[0].split() + parts[1] = str(int(parts[1]) + base_line_no) + e.args = (' '.join(parts),) + e.args[1:] + raise if any(word in ex.source for word in PSEUDOCODE for ex in tests.examples): # omit it pass else: # `part` looks like a good code, let's doctest it - good_parts += [part] + good_parts.append((part, base_line_no)) + base_line_no += part.count('\n') + 2 # Reassemble the good bits and doctest them: - good_text = '\n\n'.join(good_parts) - tests = parser.get_doctest(good_text, ns, fname, fname, 0) - success, output = _run_doctests([tests], full_name, verbose, + tests = [] + for good_text, line_no in good_parts: + tests.append(parser.get_doctest(good_text, ns, fname, fname, line_no)) + success, output = _run_doctests(tests, full_name, verbose, doctest_warnings) if dots: @@ -810,7 +1035,76 @@ def check_doctests_testfile(fname, verbose, ns=None, return results +def iter_included_files(base_path, verbose=0, suffixes=('.rst',)): + """ + Generator function to walk `base_path` and its subdirectories, skipping + files or directories in RST_SKIPLIST, and yield each file with a suffix in + `suffixes` + + Parameters + ---------- + base_path : str + Base path of the directory to be processed + verbose : int + + suffixes : tuple + + Yields + ------ + path + Path of the directory and it's sub directories + """ + if os.path.exists(base_path) and os.path.isfile(base_path): + yield base_path + for dir_name, subdirs, files in os.walk(base_path, topdown=True): + if dir_name in RST_SKIPLIST: + if verbose > 0: + sys.stderr.write('skipping files in %s' % dir_name) + files = [] + for p in RST_SKIPLIST: + if p in subdirs: + if verbose > 0: + sys.stderr.write('skipping %s and subdirs' % p) + subdirs.remove(p) + for f in files: + if (os.path.splitext(f)[1] in suffixes and + f not in RST_SKIPLIST): + yield os.path.join(dir_name, f) + + +def check_documentation(base_path, results, args, dots): + """ + Check examples in any *.rst located inside `base_path`. + Add the output to `results`. + + See Also + -------- + check_doctests_testfile + """ + for filename in iter_included_files(base_path, args.verbose): + if dots: + sys.stderr.write(filename + ' ') + sys.stderr.flush() + + tut_results = check_doctests_testfile( + filename, + (args.verbose >= 2), dots=dots, + doctest_warnings=args.doctest_warnings) + + # stub out a "module" which is needed when reporting the result + def scratch(): + pass + scratch.__name__ = filename + results.append((scratch, tut_results)) + if dots: + sys.stderr.write('\n') + sys.stderr.flush() + + def init_matplotlib(): + """ + Check feasibility of matplotlib initialization. + """ global HAVE_MATPLOTLIB try: @@ -822,34 +1116,48 @@ def init_matplotlib(): def main(argv): + """ + Validates the docstrings of all the pre decided set of + modules for errors and docstring standards. + """ parser = ArgumentParser(usage=__doc__.lstrip()) parser.add_argument("module_names", metavar="SUBMODULES", default=[], nargs='*', help="Submodules to check (default: all public)") - parser.add_argument("--doctests", action="store_true", help="Run also doctests") + parser.add_argument("--doctests", action="store_true", + help="Run also doctests on ") parser.add_argument("-v", "--verbose", action="count", default=0) parser.add_argument("--doctest-warnings", action="store_true", help="Enforce warning checking for doctests") - parser.add_argument("--skip-tutorial", action="store_true", - help="Skip running doctests in the tutorial.") + parser.add_argument("--rst", nargs='?', const='doc', default=None, + help=("Run also examples from *rst files " + "discovered walking the directory(s) specified, " + "defaults to 'doc'")) args = parser.parse_args(argv) modules = [] names_dict = {} - if args.module_names: - args.skip_tutorial = True - else: + if not args.module_names: args.module_names = list(PUBLIC_SUBMODULES) os.environ['SCIPY_PIL_IMAGE_VIEWER'] = 'true' module_names = list(args.module_names) - for name in list(module_names): + for name in module_names: if name in OTHER_MODULE_DOCS: name = OTHER_MODULE_DOCS[name] if name not in module_names: module_names.append(name) + dots = True + success = True + results = [] + errormsgs = [] + + + if args.doctests or args.rst: + init_matplotlib() + for submodule_name in module_names: module_name = BASE_MODULE + '.' + submodule_name __import__(module_name) @@ -861,69 +1169,55 @@ def main(argv): if submodule_name in args.module_names: modules.append(module) - dots = True - success = True - results = [] - - print("Running checks for %d modules:" % (len(modules),)) - - if args.doctests or not args.skip_tutorial: - init_matplotlib() - - for module in modules: - if dots: - if module is not modules[0]: - sys.stderr.write(' ') - sys.stderr.write(module.__name__ + ' ') - sys.stderr.flush() - all_dict, deprecated, others = get_all_dict(module) - names = names_dict.get(module.__name__, set()) + if args.doctests or not args.rst: + print("Running checks for %d modules:" % (len(modules),)) + for module in modules: + if dots: + sys.stderr.write(module.__name__ + ' ') + sys.stderr.flush() - mod_results = [] - mod_results += check_items(all_dict, names, deprecated, others, module.__name__) - mod_results += check_rest(module, set(names).difference(deprecated), - dots=dots) - if args.doctests: - mod_results += check_doctests(module, (args.verbose >= 2), dots=dots, - doctest_warnings=args.doctest_warnings) + all_dict, deprecated, others = get_all_dict(module) + names = names_dict.get(module.__name__, set()) - for v in mod_results: - assert isinstance(v, tuple), v + mod_results = [] + mod_results += check_items(all_dict, names, deprecated, others, + module.__name__) + mod_results += check_rest(module, set(names).difference(deprecated), + dots=dots) + if args.doctests: + mod_results += check_doctests(module, (args.verbose >= 2), dots=dots, + doctest_warnings=args.doctest_warnings) - results.append((module, mod_results)) + for v in mod_results: + assert isinstance(v, tuple), v - if dots: - sys.stderr.write("\n") - sys.stderr.flush() + results.append((module, mod_results)) - if not args.skip_tutorial: - base_dir = os.path.join(os.path.abspath(os.path.dirname(__file__)), '..') - tut_path = os.path.join(base_dir, 'doc', 'source', 'tutorial', '*.rst') - print('\nChecking tutorial files at %s:' % os.path.relpath(tut_path, os.getcwd())) - for filename in sorted(glob.glob(tut_path)): if dots: sys.stderr.write('\n') - sys.stderr.write(os.path.split(filename)[1] + ' ') sys.stderr.flush() - tut_results = check_doctests_testfile(filename, (args.verbose >= 2), - dots=dots, doctest_warnings=args.doctest_warnings) - - def scratch(): pass # stub out a "module", see below - scratch.__name__ = filename - results.append((scratch, tut_results)) + all_dict, deprecated, others = get_all_dict(module) + if args.rst: + base_dir = os.path.join(os.path.abspath(os.path.dirname(__file__)), '..') + rst_path = os.path.relpath(os.path.join(base_dir, args.rst)) + if os.path.exists(rst_path): + print('\nChecking files in %s:' % rst_path) + check_documentation(rst_path, results, args, dots) + else: + sys.stderr.write(f'\ninvalid --rst argument "{args.rst}"') + errormsgs.append('invalid directory argument to --rst') if dots: sys.stderr.write("\n") sys.stderr.flush() # Report results - all_success = True - for module, mod_results in results: success = all(x[1] for x in mod_results) - all_success = all_success and success + if not success: + errormsgs.append(f'failed checking {module.__name__}') if success and args.verbose == 0: continue @@ -946,11 +1240,11 @@ def main(argv): print(output.strip()) print("") - if all_success: - print("\nOK: refguide and doctests checks passed!") + if len(errormsgs) == 0: + print("\nOK: all checks passed!") sys.exit(0) else: - print("\nERROR: refguide or doctests have errors") + print('\nERROR: ', '\n '.join(errormsgs)) sys.exit(1) diff --git a/tools/travis-test.sh b/tools/travis-test.sh index 549a2d570..241b9d913 100755 --- a/tools/travis-test.sh +++ b/tools/travis-test.sh @@ -66,10 +66,18 @@ setup_base() run_test() { $PIP install -r test_requirements.txt + if [ -n "$USE_DEBUG" ]; then export PYTHONPATH=$PWD fi + # pytest aborts when running --durations with python3.6-dbg, so only enable + # it for non-debug tests. That is a cPython bug fixed in later versions of + # python3.7 but python3.7-dbg is not currently available on travisCI. + if [ -z "$USE_DEBUG" ]; then + DURATIONS_FLAG="--durations 10" + fi + if [ -n "$RUN_COVERAGE" ]; then COVERAGE_FLAG=--coverage fi @@ -82,17 +90,15 @@ run_test() "import os; import numpy; print(os.path.dirname(numpy.__file__))") export PYTHONWARNINGS=default - if [ -n "$PPC64_LE" ]; then + if [ -n "$CHECK_BLAS" ]; then $PYTHON ../tools/openblas_support.py --check_version $OpenBLAS_version fi if [ -n "$RUN_FULL_TESTS" ]; then export PYTHONWARNINGS="ignore::DeprecationWarning:virtualenv" - $PYTHON -b ../runtests.py -n -v --durations 10 --mode=full $COVERAGE_FLAG + $PYTHON -b ../runtests.py -n -v --mode=full $DURATIONS_FLAG $COVERAGE_FLAG else - # disable --durations temporarily, pytest currently aborts - # when that is used with python3.6-dbg - $PYTHON ../runtests.py -n -v # --durations 10 + $PYTHON ../runtests.py -n -v $DURATIONS_FLAG fi if [ -n "$RUN_COVERAGE" ]; then |