diff options
151 files changed, 2219 insertions, 1568 deletions
diff --git a/.codecov.yml b/.codecov.yml index 5e5890588..448ddf1e9 100644 --- a/.codecov.yml +++ b/.codecov.yml @@ -8,3 +8,6 @@ coverage: # Require 1% coverage, i.e., always succeed target: 1 comment: off + +ignore: + - "**/setup.py" diff --git a/.lgtm.yml b/.lgtm.yml new file mode 100644 index 000000000..c0a9cf59a --- /dev/null +++ b/.lgtm.yml @@ -0,0 +1,9 @@ +path_classifiers: + library: + - tools + generated: + # The exports defined in __init__.py are defined in the Cython module + # np.random.mtrand. By excluding this file we suppress a number of + # "undefined export" alerts + - numpy/random/__init__.py + diff --git a/.travis.yml b/.travis.yml index 904094d47..5c1f8ab1f 100644 --- a/.travis.yml +++ b/.travis.yml @@ -1,7 +1,7 @@ # After changing this file, check it on: # http://lint.travis-ci.org/ language: python - +group: travis_latest # Run jobs on container-based infrastructure, can be overridden per job sudo: false diff --git a/MANIFEST.in b/MANIFEST.in index eff19e20a..918e59e85 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -14,8 +14,8 @@ recursive-include numpy/_build_utils * recursive-include numpy/linalg/lapack_lite *.c *.h include tox.ini # Add sdist files whose use depends on local configuration. -include numpy/core/src/multiarray/cblasfuncs.c -include numpy/core/src/multiarray/python_xerbla.c +include numpy/core/src/common/cblasfuncs.c +include numpy/core/src/common/python_xerbla.c # Adding scons build related files not found by distutils recursive-include numpy/core/code_generators *.py *.txt recursive-include numpy/core *.in *.h @@ -20,8 +20,8 @@ It provides: Testing: -- NumPy versions >= 1.15 require ``pytest`` -- NumPy versions < 1.15 require ``nose`` +- NumPy versions ≥ 1.15 require `pytest` +- NumPy versions < 1.15 require `nose` Tests can then be run after installation with: diff --git a/benchmarks/benchmarks/bench_io.py b/benchmarks/benchmarks/bench_io.py index 782d4ab30..ce30c4345 100644 --- a/benchmarks/benchmarks/bench_io.py +++ b/benchmarks/benchmarks/bench_io.py @@ -3,6 +3,7 @@ from __future__ import absolute_import, division, print_function from .common import Benchmark, get_squares import numpy as np +from io import StringIO class Copy(Benchmark): @@ -62,3 +63,179 @@ class Savez(Benchmark): def time_vb_savez_squares(self): np.savez('tmp.npz', self.squares) + +class LoadtxtCSVComments(Benchmark): + # benchmarks for np.loadtxt comment handling + # when reading in CSV files + + params = [10, int(1e2), int(1e4), int(1e5)] + param_names = ['num_lines'] + + def setup(self, num_lines): + data = [u'1,2,3 # comment'] * num_lines + # unfortunately, timeit will only run setup() + # between repeat events, but not for iterations + # within repeats, so the StringIO object + # will have to be rewinded in the benchmark proper + self.data_comments = StringIO(u'\n'.join(data)) + + def time_comment_loadtxt_csv(self, num_lines): + # benchmark handling of lines with comments + # when loading in from csv files + + # inspired by similar benchmark in pandas + # for read_csv + + # need to rewind StringIO object (unfortunately + # confounding timing result somewhat) for every + # call to timing test proper + np.loadtxt(self.data_comments, + delimiter=u',') + self.data_comments.seek(0) + +class LoadtxtCSVdtypes(Benchmark): + # benchmarks for np.loadtxt operating with + # different dtypes parsed / cast from CSV files + + params = (['float32', 'float64', 'int32', 'int64', + 'complex128', 'str', 'object'], + [10, int(1e2), int(1e4), int(1e5)]) + param_names = ['dtype', 'num_lines'] + + def setup(self, dtype, num_lines): + data = [u'5, 7, 888'] * num_lines + self.csv_data = StringIO(u'\n'.join(data)) + + def time_loadtxt_dtypes_csv(self, dtype, num_lines): + # benchmark loading arrays of various dtypes + # from csv files + + # state-dependent timing benchmark requires + # rewind of StringIO object + + np.loadtxt(self.csv_data, + delimiter=u',', + dtype=dtype) + self.csv_data.seek(0) + +class LoadtxtCSVStructured(Benchmark): + # benchmarks for np.loadtxt operating with + # a structured data type & CSV file + + def setup(self): + num_lines = 50000 + data = [u"M, 21, 72, X, 155"] * num_lines + self.csv_data = StringIO(u'\n'.join(data)) + + def time_loadtxt_csv_struct_dtype(self): + # obligate rewind of StringIO object + # between iterations of a repeat: + + np.loadtxt(self.csv_data, + delimiter=u',', + dtype=[('category_1', 'S1'), + ('category_2', 'i4'), + ('category_3', 'f8'), + ('category_4', 'S1'), + ('category_5', 'f8')]) + self.csv_data.seek(0) + + +class LoadtxtCSVSkipRows(Benchmark): + # benchmarks for loadtxt row skipping when + # reading in csv file data; a similar benchmark + # is present in the pandas asv suite + + params = [0, 500, 10000] + param_names = ['skiprows'] + + def setup(self, skiprows): + np.random.seed(123) + test_array = np.random.rand(100000, 3) + self.fname = 'test_array.csv' + np.savetxt(fname=self.fname, + X=test_array, + delimiter=',') + + def time_skiprows_csv(self, skiprows): + np.loadtxt(self.fname, + delimiter=',', + skiprows=skiprows) + +class LoadtxtReadUint64Integers(Benchmark): + # pandas has a similar CSV reading benchmark + # modified to suit np.loadtxt + + params = [550, 1000, 10000] + param_names = ['size'] + + def setup(self, size): + arr = np.arange(size).astype('uint64') + 2**63 + self.data1 = StringIO(u'\n'.join(arr.astype(str).tolist())) + arr = arr.astype(object) + arr[500] = -1 + self.data2 = StringIO(u'\n'.join(arr.astype(str).tolist())) + + def time_read_uint64(self, size): + # mandatory rewind of StringIO object + # between iterations of a repeat: + np.loadtxt(self.data1) + self.data1.seek(0) + + def time_read_uint64_neg_values(self, size): + # mandatory rewind of StringIO object + # between iterations of a repeat: + np.loadtxt(self.data2) + self.data2.seek(0) + +class LoadtxtUseColsCSV(Benchmark): + # benchmark selective column reading from CSV files + # using np.loadtxt + + params = [2, [1, 3], [1, 3, 5, 7]] + param_names = ['usecols'] + + def setup(self, usecols): + num_lines = 5000 + data = [u'0, 1, 2, 3, 4, 5, 6, 7, 8, 9'] * num_lines + self.csv_data = StringIO(u'\n'.join(data)) + + def time_loadtxt_usecols_csv(self, usecols): + # must rewind StringIO because of state + # dependence of file reading + np.loadtxt(self.csv_data, + delimiter=u',', + usecols=usecols) + self.csv_data.seek(0) + +class LoadtxtCSVDateTime(Benchmark): + # benchmarks for np.loadtxt operating with + # datetime data in a CSV file + + params = [20, 200, 2000, 20000] + param_names = ['num_lines'] + + def setup(self, num_lines): + # create the equivalent of a two-column CSV file + # with date strings in the first column and random + # floating point data in the second column + dates = np.arange('today', 20, dtype=np.datetime64) + np.random.seed(123) + values = np.random.rand(20) + date_line = u'' + + for date, value in zip(dates, values): + date_line += (str(date) + ',' + str(value) + '\n') + + # expand data to specified number of lines + data = date_line * (num_lines // 20) + self.csv_data = StringIO(data) + + def time_loadtxt_csv_datetime(self, num_lines): + # rewind StringIO object -- the timing iterations + # are state-dependent + X = np.loadtxt(self.csv_data, + delimiter=u',', + dtype=([('dates', 'M8[us]'), + ('values', 'float64')])) + self.csv_data.seek(0) diff --git a/doc/RELEASE_WALKTHROUGH.rst.txt b/doc/RELEASE_WALKTHROUGH.rst.txt index 260e0c1b7..c3400194c 100644 --- a/doc/RELEASE_WALKTHROUGH.rst.txt +++ b/doc/RELEASE_WALKTHROUGH.rst.txt @@ -2,15 +2,18 @@ This file contains a walkthrough of the NumPy 1.14.5 release on Linux. The commands can be copied into the command line, but be sure to replace 1.14.5 by the correct version. + Release Walkthrough ==================== + Backport Pull Requests ---------------------- Changes that have been marked for this release must be backported to the maintenance/1.14.x branch. + Update Release documentation ---------------------------- @@ -21,17 +24,19 @@ the final list of changes and contributors. This text can be generated by:: where ``GITHUB`` contains your github access token. This text may also be appended to ``doc/release/1.14.5-notes.rst`` for release updates, though not -for new releases like ``1.14.0``, as the changelogs for latter tend to be +for new releases like ``1.14.0``, as the changelogs for ``*.0`` releases tend to be excessively long. The ``doc/source/release.rst`` file should also be updated with a link to the new release notes. These changes should be committed to the maintenance branch, and later will be forward ported to master. + Finish the Release Note ----------------------- Fill out the release note ``doc/release/1.14.5-notes.rst`` calling out significant changes. + Prepare the release commit -------------------------- @@ -60,6 +65,7 @@ requires write permission to the numpy repository:: As an example, see the 1.14.3 REL commit: `<https://github.com/numpy/numpy/commit/73299826729be58cec179b52c656adfcaefada93>`_. + Build source releases --------------------- @@ -70,6 +76,7 @@ source releases in the latter. :: $ cython --version # check that you have the correct cython version $ paver sdist # sdist will do a git clean -xdf, so we omit that + Build wheels ------------ @@ -102,6 +109,7 @@ need to restart them. .. example_: https://github.com/MacPython/numpy-wheels/commit/fed9c04629c155e7804282eb803d81097244598d + Download wheels --------------- @@ -121,8 +129,16 @@ upload later using ``twine``:: $ ./wheel-uploader -u $CDN_URL -n -v -w $NPY_WHLS -t macosx numpy 1.14.5 If you do this often, consider making CDN_URL and NPY_WHLS part of your default -environment. Note that we need local copies of the files in order to generate -hashes to include in the README files generated later. +environment. + +Generate the README files +------------------------- + +This needs to be done after all installers are present, but before the pavement +file is updated for continued development. + + $ paver write_release_and_log + Tag the release --------------- @@ -144,6 +160,7 @@ push the tag upstream:: We wait until this point to push the tag because it is very difficult to change the tag after it has been pushed. + Reset the maintenance branch into a development state ----------------------------------------------------- @@ -172,13 +189,10 @@ avoid synchronization problems if pip users access the files while this is in process. Note that PyPI only allows a single source distribution, here we have chosen the zip archive. + Upload files to github ---------------------- -Generate the ``release/README.*`` files:: - - $ paver write_release_and_log - Go to `<https://github.com/numpy/numpy/releases>`_, there should be a ``v1.14.5 tag``, click on it and hit the edit button for that tag. There are two ways to add files, using an editable text window and as binary uploads. @@ -230,6 +244,7 @@ This assumes that you have forked `<https://github.com/scipy/scipy.org>`_:: Now go to your fork and make a pull request for the branch. + Announce to mailing lists ------------------------- @@ -238,9 +253,10 @@ scipy-user, and python-announce-list mailing lists. Look at previous announcements for the basic template. The contributor and PR lists are the same as generated for the release notes above. + Post-Release Tasks ------------------ Forward port the documentation changes ``doc/release/1.14.5-notes.rst``, -``doc/changelog/1.14.5-changelog.rst`` and add the release note to +``doc/changelog/1.14.5-changelog.rst`` and add the release note to ``doc/source/release.rst``. diff --git a/doc/changelog/1.15.1-changelog.rst b/doc/changelog/1.15.1-changelog.rst new file mode 100644 index 000000000..42ba67c2b --- /dev/null +++ b/doc/changelog/1.15.1-changelog.rst @@ -0,0 +1,44 @@ + +Contributors +============ + +A total of 7 people contributed to this release. People with a "+" by their +names contributed a patch for the first time. + +* Charles Harris +* Chris Billington +* Elliott Sales de Andrade + +* Eric Wieser +* Jeremy Manning + +* Matti Picus +* Ralf Gommers + +Pull requests merged +==================== + +A total of 24 pull requests were merged for this release. + +* `#11647 <https://github.com/numpy/numpy/pull/11647>`__: MAINT: Filter Cython warnings in ``__init__.py`` +* `#11648 <https://github.com/numpy/numpy/pull/11648>`__: BUG: Fix doc source links to unwrap decorators +* `#11657 <https://github.com/numpy/numpy/pull/11657>`__: BUG: Ensure singleton dimensions are not dropped when converting... +* `#11661 <https://github.com/numpy/numpy/pull/11661>`__: BUG: Warn on Nan in minimum,maximum for scalars +* `#11665 <https://github.com/numpy/numpy/pull/11665>`__: BUG: cython sometimes emits invalid gcc attribute +* `#11682 <https://github.com/numpy/numpy/pull/11682>`__: BUG: Fix regression in void_getitem +* `#11698 <https://github.com/numpy/numpy/pull/11698>`__: BUG: Make matrix_power again work for object arrays. +* `#11700 <https://github.com/numpy/numpy/pull/11700>`__: BUG: Add missing PyErr_NoMemory after failing malloc +* `#11719 <https://github.com/numpy/numpy/pull/11719>`__: BUG: Fix undefined functions on big-endian systems. +* `#11720 <https://github.com/numpy/numpy/pull/11720>`__: MAINT: Make einsum optimize default to False. +* `#11746 <https://github.com/numpy/numpy/pull/11746>`__: BUG: Fix regression in loadtxt for bz2 text files in Python 2. +* `#11757 <https://github.com/numpy/numpy/pull/11757>`__: BUG: Revert use of `console_scripts`. +* `#11758 <https://github.com/numpy/numpy/pull/11758>`__: BUG: Fix Fortran kind detection for aarch64 & s390x. +* `#11759 <https://github.com/numpy/numpy/pull/11759>`__: BUG: Fix printing of longdouble on ppc64le. +* `#11760 <https://github.com/numpy/numpy/pull/11760>`__: BUG: Fixes for unicode field names in Python 2 +* `#11761 <https://github.com/numpy/numpy/pull/11761>`__: BUG: Increase required cython version on python 3.7 +* `#11763 <https://github.com/numpy/numpy/pull/11763>`__: BUG: check return value of _buffer_format_string +* `#11775 <https://github.com/numpy/numpy/pull/11775>`__: MAINT: Make assert_array_compare more generic. +* `#11776 <https://github.com/numpy/numpy/pull/11776>`__: TST: Fix urlopen stubbing. +* `#11777 <https://github.com/numpy/numpy/pull/11777>`__: BUG: Fix regression in intersect1d. +* `#11779 <https://github.com/numpy/numpy/pull/11779>`__: BUG: Fix test sensitive to platform byte order. +* `#11781 <https://github.com/numpy/numpy/pull/11781>`__: BUG: Avoid signed overflow in histogram +* `#11785 <https://github.com/numpy/numpy/pull/11785>`__: BUG: Fix pickle and memoryview for datetime64, timedelta64 scalars +* `#11786 <https://github.com/numpy/numpy/pull/11786>`__: BUG: Deprecation triggers segfault diff --git a/doc/neps/index.rst.tmpl b/doc/neps/index.rst.tmpl index 6cbad8eb2..e7b8fedba 100644 --- a/doc/neps/index.rst.tmpl +++ b/doc/neps/index.rst.tmpl @@ -1,12 +1,21 @@ -=========================== -NumPy Enhancement Proposals -=========================== - -NumPy Enhancement Proposals (NEPs) describe proposed changes to NumPy. -NEPs are modeled on Python Enhancement Proposals (PEPs), and are typically -written up when large changes to NumPy are proposed. +===================================== +Roadmap & NumPy Enhancement Proposals +===================================== + +This page provides an overview of development priorities for NumPy. +Specifically, it contains a roadmap with a higher-level overview, as +well as NumPy Enhancement Proposals (NEPs)—suggested changes +to the library—in various stages of discussion or completion (see `NEP +0 <nep-0000>`__). + +Roadmap +------- +.. toctree:: + :maxdepth: 1 -This page provides an overview of all NEPs. + The Scope of NumPy <scope> + Current roadmap <roadmap> + Wish list <https://github.com/numpy/numpy/issues?q=is%3Aopen+is%3Aissue+label%3A%2223+-+Wish+List%22> Meta-NEPs (NEPs about NEPs or Processes) ---------------------------------------- diff --git a/doc/neps/roadmap.rst b/doc/neps/roadmap.rst new file mode 100644 index 000000000..a45423711 --- /dev/null +++ b/doc/neps/roadmap.rst @@ -0,0 +1,115 @@ +============= +NumPy Roadmap +============= + +This is a live snapshot of tasks and features we will be investing resources +in. It may be used to encourage and inspire developers and to search for +funding. + +Interoperability protocols & duck typing +---------------------------------------- + +- `__array_function__` + + See `NEP 18`_ and a sample implementation_ + +- Array Duck-Typing + + `NEP 22`_ `np.asduckarray()` + +- Mixins like `NDArrayOperatorsMixin`: + + - for mutable arrays + - for reduction methods implemented as ufuncs + +Better dtypes +------------- + +- Easier custom dtypes + - Simplify and/or wrap the current C-API + - More consistent support for dtype metadata + - Support for writing a dtype in Python +- New string dtype(s): + - Encoded strings with fixed-width storage (utf8, latin1, ...) and/or + - Variable length strings (could share implementation with dtype=object, but are explicitly type-checked) + - One of these should probably be the default for text data. The current behavior on Python 3 is neither efficient nor user friendly. +- `np.int` should not be platform dependent +- better coercion for string + number + +Random number generation policy & rewrite +----------------------------------------- + +`NEP 19`_ and a `reference implementation`_ + +Indexing +-------- + +vindex/oindex `NEP 21`_ + +Infrastructure +-------------- + +NumPy is much more than just the code base itself, we also maintain +docs, CI, benchmarks, etc. + +- Rewrite numpy.org +- Benchmarking: improve the extent of the existing suite, and run & render + the results as part of the docs or website. + + - Hardware: find a machine that can reliably run serial benchmarks + - ASV produces graphs, could we set up a site? Currently at + https://pv.github.io/numpy-bench/, should that become a community resource? + +Functionality outside core +-------------------------- + +Some things inside NumPy do not actually match the `Scope of NumPy`. + +- A backend system for `numpy.fft` (so that e.g. `fft-mkl` doesn't need to monkeypatch numpy) + +- Rewrite masked arrays to not be a ndarray subclass -- maybe in a separate project? +- MaskedArray as a duck-array type, and/or +- dtypes that support missing values + +- Write a strategy on how to deal with overlap between numpy and scipy for `linalg` and `fft` (and implement it). + +- Deprecate `np.matrix` + +Continuous Integration +---------------------- + +We depend on CI to discover problems as we continue to develop NumPy before the +code reaches downstream users. + +- CI for more exotic platforms (e.g. ARM is now available from + http://www.shippable.com/, but it is not free). +- Multi-package testing +- Add an official channel for numpy dev builds for CI usage by other projects so + they may confirm new builds do not break their package. + +Typing +------ + +Python type annotation syntax should support ndarrays and dtypes. + +- Type annotations for NumPy: github.com/numpy/numpy-stubs +- Support for typing shape and dtype in multi-dimensional arrays in Python more generally + +NumPy scalars +------------- + +Numpy has both scalars and zero-dimensional arrays. + +- The current implementation adds a large maintenance burden -- can we remove + scalars and/or simplify it internally? +- Zero dimensional arrays get converted into scalars by most NumPy + functions (i.e., output of `np.sin(x)` depends on whether `x` is + zero-dimensional or not). This inconsistency should be addressed, + so that one could, e.g., write sane type annotations. + +.. _`NEP 19`: https://www.numpy.org/neps/nep-0019-rng-policy.html +.. _`NEP 22`: http://www.numpy.org/neps/nep-0022-ndarray-duck-typing-overview.html +.. _`NEP 18`: https://www.numpy.org/neps/nep-0018-array-function-protocol.html +.. _implementation: https://gist.github.com/shoyer/1f0a308a06cd96df20879a1ddb8f0006 +.. _`reference implementation`: https://github.com/bashtage/randomgen +.. _`NEP 21`: https://www.numpy.org/neps/nep-0021-advanced-indexing.html diff --git a/doc/neps/scope.rst b/doc/neps/scope.rst new file mode 100644 index 000000000..a675b8c96 --- /dev/null +++ b/doc/neps/scope.rst @@ -0,0 +1,46 @@ +============== +Scope of NumPy +============== + +Here, we describe aspects of N-d array computation that are within scope for NumPy development. This is *not* an aspirational definition of where NumPy should aim, but instead captures the status quo—areas which we have decided to continue supporting, at least for the time being. + +- **In-memory, N-dimensional, homogeneously typed (single pointer + strided) arrays on CPUs** + + - Support for a wide range of data types + - Not specialized hardware such as GPUs + - But, do support wide range of CPUs (e.g. ARM, PowerX) + +- **Higher level APIs for N-dimensional arrays** + + - NumPy is a *de facto* standard for array APIs in Python + - Indexing and fast iteration over elements (ufunc) + - Interoperability protocols with other data container implementations (like `__array_ufunc__`). + +- **Python API and a C API** to the ndarray's methods and attributes. + +- Other **specialized types or uses of N-dimensional arrays**: + + - Masked arrays + - Structured arrays (informally known as record arrays) + - Memory mapped arrays + +- Historically, NumPy has included the following **basic functionality + in support of scientific computation**. We intend to keep supporting + (but not to expand) what is currently included: + + - Linear algebra + - Fast Fourier transforms and windowing + - Pseudo-random number generators + - Polynomial fitting + +- NumPy provides some **infrastructure for other packages in the scientific Python ecosystem**: + + - numpy.distutils (build support for C++, Fortran, BLAS/LAPACK, and other relevant libraries for scientific computing + - f2py (generating bindings for Fortran code) + - testing utilities + +- **Speed**: we take performance concerns seriously and aim to execute + operations on large arrays with similar performance as native C + code. That said, where conflict arises, maintenance and portability take + precedence over performance. We aim to prevent regressions where + possible (e.g., through asv). diff --git a/doc/release/1.13.0-notes.rst b/doc/release/1.13.0-notes.rst index 4554e53ea..3b719db09 100644 --- a/doc/release/1.13.0-notes.rst +++ b/doc/release/1.13.0-notes.rst @@ -183,11 +183,11 @@ override the behavior of NumPy's ufuncs. This works quite similarly to Python's ``__mul__`` and other binary operation routines. See the documentation for a more detailed description of the implementation and behavior of this new option. The API is provisional, we do not yet guarantee backward compatibility -as modifications may be made pending feedback. See the NEP_ and +as modifications may be made pending feedback. See `NEP 13`_ and documentation_ for more details. -.. _NEP: https://github.com/numpy/numpy/blob/master/doc/neps/ufunc-overrides.rst -.. _documentation: https://github.com/charris/numpy/blob/master/doc/source/reference/arrays.classes.rst +.. _`NEP 13`: http://www.numpy.org/neps/nep-0013-ufunc-overrides.html +.. _documentation: https://github.com/numpy/numpy/blob/master/doc/source/reference/arrays.classes.rst New ``positive`` ufunc ---------------------- diff --git a/doc/release/1.13.1-notes.rst b/doc/release/1.13.1-notes.rst index 807296a85..88a4bc3dd 100644 --- a/doc/release/1.13.1-notes.rst +++ b/doc/release/1.13.1-notes.rst @@ -13,7 +13,7 @@ used with 3.6.0 due to Python bug 29943_. NumPy 1.13.2 will be released shortly after Python 3.6.2 is out to fix that problem. If you are using 3.6.0 the workaround is to upgrade to 3.6.1 or use an earlier Python version. -.. _#29943: https://bugs.python.org/issue29943 +.. _29943: https://bugs.python.org/issue29943 Pull requests merged @@ -21,7 +21,7 @@ Pull requests merged A total of 19 pull requests were merged for this release. * #9240 DOC: BLD: fix lots of Sphinx warnings/errors. -* #9255 Revert "DEP: Raise TypeError for subtract(bool_, bool_)." +* #9255 Revert "DEP: Raise TypeError for subtract(bool, bool)." * #9261 BUG: don't elide into readonly and updateifcopy temporaries for... * #9262 BUG: fix missing keyword rename for common block in numpy.f2py * #9263 BUG: handle resize of 0d array diff --git a/doc/release/1.14.0-notes.rst b/doc/release/1.14.0-notes.rst index 0f14f7703..462631de6 100644 --- a/doc/release/1.14.0-notes.rst +++ b/doc/release/1.14.0-notes.rst @@ -14,11 +14,11 @@ dropping Python 2.7 support in the runup to 2020. The decision has been made to support 2.7 for all releases made in 2018, with the last release being designated a long term release with support for bug fixes extending through 2019. In 2019 support for 2.7 will be dropped in all new releases. More details -can be found in the relevant NEP_. +can be found in `NEP 12`_. This release supports Python 2.7 and 3.4 - 3.6. -.. _NEP: https://github.com/numpy/numpy/blob/master/doc/neps/dropping-python2.7-proposal.rst +.. _`NEP 12`: http://www.numpy.org/neps/nep-0014-dropping-python2.7-proposal.html Highlights @@ -134,8 +134,8 @@ are marked readonly. In the past, it was possible to get away with:: var_arr = np.asarray(val) val_arr += 1 # now errors, previously changed np.ma.masked.data -``np.ma`` functions producing ``fill_value``s have changed ----------------------------------------------------------- +``np.ma`` functions producing ``fill_value`` s have changed +----------------------------------------------------------- Previously, ``np.ma.default_fill_value`` would return a 0d array, but ``np.ma.minimum_fill_value`` and ``np.ma.maximum_fill_value`` would return a tuple of the fields. Instead, all three methods return a structured ``np.void`` diff --git a/doc/release/1.14.1-notes.rst b/doc/release/1.14.1-notes.rst index 2ed4c3e14..7b95c2e28 100644 --- a/doc/release/1.14.1-notes.rst +++ b/doc/release/1.14.1-notes.rst @@ -67,7 +67,7 @@ A total of 36 pull requests were merged for this release. * `#10431 <https://github.com/numpy/numpy/pull/10431>`__: REL: Add 1.14.1 release notes template * `#10435 <https://github.com/numpy/numpy/pull/10435>`__: MAINT: Use ValueError for duplicate field names in lookup (backport) * `#10534 <https://github.com/numpy/numpy/pull/10534>`__: BUG: Provide a better error message for out-of-order fields -* `#10536 <https://github.com/numpy/numpy/pull/10536>`__: BUG: Resize bytes_ columns in genfromtxt (backport of #10401) +* `#10536 <https://github.com/numpy/numpy/pull/10536>`__: BUG: Resize bytes columns in genfromtxt (backport of #10401) * `#10537 <https://github.com/numpy/numpy/pull/10537>`__: BUG: multifield-indexing adds padding bytes: revert for 1.14.1 * `#10539 <https://github.com/numpy/numpy/pull/10539>`__: BUG: fix np.save issue with python 2.7.5 * `#10540 <https://github.com/numpy/numpy/pull/10540>`__: BUG: Add missing DECREF in Py2 int() cast diff --git a/doc/release/1.15.0-notes.rst b/doc/release/1.15.0-notes.rst index 0e3d2a525..7235ca915 100644 --- a/doc/release/1.15.0-notes.rst +++ b/doc/release/1.15.0-notes.rst @@ -99,7 +99,7 @@ Deprecations * Users of ``nditer`` should use the nditer object as a context manager anytime one of the iterator operands is writeable, so that numpy can manage writeback semantics, or should call ``it.close()``. A - `RuntimeWarning` may be emitted otherwise in these cases. + `RuntimeWarning` may be emitted otherwise in these cases. * The ``normed`` argument of ``np.histogram``, deprecated long ago in 1.6.0, now emits a ``DeprecationWarning``. @@ -227,13 +227,6 @@ Changes to ``PyArray_GetDTypeTransferFunction`` significant performance hit, consider implementing ``copyswapn`` to reflect the implementation of ``PyArray_GetStridedCopyFn``. See `#10898 <https://github.com/numpy/numpy/pull/10898>`__. -* Functions ``npy_get_floatstatus_barrier`` and ``npy_clear_floatstatus_barrier`` - have been added and should be used in place of the ``npy_get_floatstatus``and - ``npy_clear_status`` functions. Optimizing compilers like GCC 8.1 and Clang - were rearranging the order of operations when the previous functions were - used in the ufunc SIMD functions, resulting in the floatstatus flags being ' - checked before the operation whose status we wanted to check was run. - See `#10339 <https://github.com/numpy/numpy/issues/10370>`__. New Features diff --git a/doc/release/1.15.1-notes.rst b/doc/release/1.15.1-notes.rst new file mode 100644 index 000000000..ddb83303c --- /dev/null +++ b/doc/release/1.15.1-notes.rst @@ -0,0 +1,74 @@ +========================== +NumPy 1.15.1 Release Notes +========================== + +This is a bugfix release for bugs and regressions reported following the 1.15.0 +release. + +* The annoying but harmless RuntimeWarning that "numpy.dtype size changed" has + been suppressed. The long standing suppression was lost in the transition to + pytest. +* The update to Cython 0.28.3 exposed a problematic use of a gcc attribute used + to prefer code size over speed in module initialization, possibly resulting in + incorrect compiled code. This has been fixed in latest Cython but has been + disabled here for safety. +* Support for big-endian and ARMv8 architectures has been improved. + +The Python versions supported by this release are 2.7, 3.4-3.7. The wheels are +linked with OpenBLAS v0.3.0, which should fix some of the linalg problems +reported for NumPy 1.14. + + +Compatibility Note +================== + +The NumPy 1.15.x OS X wheels released on PyPI no longer contain 32-bit +binaries. That will also be the case in future releases. See +`#11625 <https://github.com/numpy/numpy/issues/11625>`__ for the related +discussion. Those needing 32-bit support should look elsewhere or build +from source. + + +Contributors +============ + +A total of 7 people contributed to this release. People with a "+" by their +names contributed a patch for the first time. + +* Charles Harris +* Chris Billington +* Elliott Sales de Andrade + +* Eric Wieser +* Jeremy Manning + +* Matti Picus +* Ralf Gommers + +Pull requests merged +==================== + +A total of 24 pull requests were merged for this release. + +* `#11647 <https://github.com/numpy/numpy/pull/11647>`__: MAINT: Filter Cython warnings in ``__init__.py`` +* `#11648 <https://github.com/numpy/numpy/pull/11648>`__: BUG: Fix doc source links to unwrap decorators +* `#11657 <https://github.com/numpy/numpy/pull/11657>`__: BUG: Ensure singleton dimensions are not dropped when converting... +* `#11661 <https://github.com/numpy/numpy/pull/11661>`__: BUG: Warn on Nan in minimum,maximum for scalars +* `#11665 <https://github.com/numpy/numpy/pull/11665>`__: BUG: cython sometimes emits invalid gcc attribute +* `#11682 <https://github.com/numpy/numpy/pull/11682>`__: BUG: Fix regression in void_getitem +* `#11698 <https://github.com/numpy/numpy/pull/11698>`__: BUG: Make matrix_power again work for object arrays. +* `#11700 <https://github.com/numpy/numpy/pull/11700>`__: BUG: Add missing PyErr_NoMemory after failing malloc +* `#11719 <https://github.com/numpy/numpy/pull/11719>`__: BUG: Fix undefined functions on big-endian systems. +* `#11720 <https://github.com/numpy/numpy/pull/11720>`__: MAINT: Make einsum optimize default to False. +* `#11746 <https://github.com/numpy/numpy/pull/11746>`__: BUG: Fix regression in loadtxt for bz2 text files in Python 2. +* `#11757 <https://github.com/numpy/numpy/pull/11757>`__: BUG: Revert use of `console_scripts`. +* `#11758 <https://github.com/numpy/numpy/pull/11758>`__: BUG: Fix Fortran kind detection for aarch64 & s390x. +* `#11759 <https://github.com/numpy/numpy/pull/11759>`__: BUG: Fix printing of longdouble on ppc64le. +* `#11760 <https://github.com/numpy/numpy/pull/11760>`__: BUG: Fixes for unicode field names in Python 2 +* `#11761 <https://github.com/numpy/numpy/pull/11761>`__: BUG: Increase required cython version on python 3.7 +* `#11763 <https://github.com/numpy/numpy/pull/11763>`__: BUG: check return value of _buffer_format_string +* `#11775 <https://github.com/numpy/numpy/pull/11775>`__: MAINT: Make assert_array_compare more generic. +* `#11776 <https://github.com/numpy/numpy/pull/11776>`__: TST: Fix urlopen stubbing. +* `#11777 <https://github.com/numpy/numpy/pull/11777>`__: BUG: Fix regression in intersect1d. +* `#11779 <https://github.com/numpy/numpy/pull/11779>`__: BUG: Fix test sensitive to platform byte order. +* `#11781 <https://github.com/numpy/numpy/pull/11781>`__: BUG: Avoid signed overflow in histogram +* `#11785 <https://github.com/numpy/numpy/pull/11785>`__: BUG: Fix pickle and memoryview for datetime64, timedelta64 scalars +* `#11786 <https://github.com/numpy/numpy/pull/11786>`__: BUG: Deprecation triggers segfault diff --git a/doc/release/1.16.0-notes.rst b/doc/release/1.16.0-notes.rst index 98d3baba6..378b96b3b 100644 --- a/doc/release/1.16.0-notes.rst +++ b/doc/release/1.16.0-notes.rst @@ -15,12 +15,18 @@ Deprecations ============ `typeNA` and `sctypeNA` have been deprecated -------------------------------------------- +-------------------------------------------- The type dictionaries `numpy.core.typeNA` and `numpy.core.sctypeNA` were buggy -and not documented. They will be removed in the 1.18 release. Use +and not documented. They will be removed in the 1.18 release. Use `numpy.sctypeDict` instead. + +``np.PackageLoader`` and ``np.pkgload`` have been removed +--------------------------------------------------------- +These were deprecated in 1.10, had no tests, and seem to no longer work in +1.15 anyway. + Future Changes ============== @@ -28,6 +34,14 @@ Future Changes Compatibility notes =================== +f2py script on Windows +---------------------- +On Windows, the installed script for running f2py is now an ``.exe`` file +rather than a ``*.py`` file and should be run from the command line as ``f2py`` +whenever the ``Scripts`` directory is in the path. Folks needing compatibility +with earler versions of Numpy should run ``f2py`` as a module: ``python -m +numpy.f2py [...]``. + C API changes ============= @@ -40,18 +54,25 @@ New Features Improvements ============ +`np.polynomial.Polynomial` classes render in LaTeX in Jupyter notebooks +----------------------------------------------------------------------- + +When used in a front-end that supports it, `Polynomial` instances are now +rendered through LaTeX. The current format is experimental, and is subject to +change. + ``randint`` and ``choice`` now work on empty distributions -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +---------------------------------------------------------- Even when no elements needed to be drawn, ``np.random.randint`` and ``np.random.choice`` raised an error when the arguments described an empty distribution. This has been fixed so that e.g. ``np.random.choice([], 0) == np.array([], dtype=float64)``. -``linalg.qr`` now works with empty matrices -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Previously, a ``LinAlgError`` would be raised when empty matrix -(with zero rows and/or columns) is passed in. This has been fixed -so that outputs of appropriate shapes are returned for the various modes. +``linalg.lstsq`` and ``linalg.qr`` now work with empty matrices +--------------------------------------------------------------- +Previously, a ``LinAlgError`` would be raised when an empty matrix/empty +matrices (with zero rows and/or columns) is/are passed in. Now outputs of +appropriate shapes are returned. ARM support updated ------------------- @@ -68,12 +89,17 @@ behavior will be appending. This applied to: `LDFLAGS`, `F77FLAGS`, `F90FLAGS`, `FREEFLAGS`, `FOPT`, `FDEBUG`, and `FFLAGS`. See gh-11525 for more details. +``np.clip`` and the ``clip`` method check for memory overlap +------------------------------------------------------------ +The ``out`` argument to these functions is now always tested for memory overlap +to avoid corrupted results when memory overlap occurs. + + Changes ======= Comparison ufuncs will now error rather than return NotImplemented ------------------------------------------------------------------ - Previously, comparison ufuncs such as ``np.equal`` would return `NotImplemented` if their arguments had structured dtypes, to help comparison operators such as ``__eq__`` deal with those. This is no longer needed, as the @@ -95,3 +121,13 @@ Previously only ``float32`` and ``float64`` set invalid float status (by default emitting a `RuntimeWarning`) when a Nan is encountered in `numpy.maximum` and `numpy.minimum`. Now ``float16``, ``complex64``, ``complex128`` and ``complex256`` will do so as well. + +Umath and multiarray c-extension modules merged into a single module +-------------------------------------------------------------------- +The two modules were merged, according to the first step in `NEP 15`_. +Previously `np.core.umath` and `np.core.multiarray` were the 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/f2py/compile_session.dat b/doc/source/f2py/compile_session.dat index 0d8408198..5c42742be 100644 --- a/doc/source/f2py/compile_session.dat +++ b/doc/source/f2py/compile_session.dat @@ -1,10 +1,10 @@ ->>> import f2py2e +>>> import numpy.f2py >>> fsource = ''' ... subroutine foo ... print*, "Hello world!" ... end ... ''' ->>> f2py2e.compile(fsource,modulename='hello',verbose=0) +>>> numpy.f2py.compile(fsource, modulename='hello', verbose=0) 0 >>> import hello >>> hello.foo() diff --git a/doc/source/f2py/getting-started.rst b/doc/source/f2py/getting-started.rst index fffd61c45..3d8ea24e4 100644 --- a/doc/source/f2py/getting-started.rst +++ b/doc/source/f2py/getting-started.rst @@ -45,9 +45,9 @@ to run :: - f2py -c fib1.f -m fib1 + python -m numpy.f2py -c fib1.f -m fib1 -This command builds (see ``-c`` flag, execute ``f2py`` without +This command builds (see ``-c`` flag, execute ``python -m numpy.f2py`` without arguments to see the explanation of command line options) an extension module ``fib1.so`` (see ``-m`` flag) to the current directory. Now, in Python the Fortran subroutine ``FIB`` is accessible via ``fib1.fib``:: @@ -162,7 +162,7 @@ one. :: - f2py fib1.f -m fib2 -h fib1.pyf + python -m numpy.f2py fib1.f -m fib2 -h fib1.pyf The signature file is saved to ``fib1.pyf`` (see ``-h`` flag) and its contents is shown below. @@ -188,7 +188,7 @@ one. :: - f2py -c fib2.pyf fib1.f + python -m numpy.f2py -c fib2.pyf fib1.f In Python:: @@ -243,7 +243,7 @@ __ fib3.f Building the extension module can be now carried out in one command:: - f2py -c -m fib3 fib3.f + python -m numpy.f2py -c -m fib3 fib3.f Notice that the resulting wrapper to ``FIB`` is as "smart" as in previous case:: diff --git a/doc/source/f2py/run_main_session.dat b/doc/source/f2py/run_main_session.dat index 29ecc3dfe..b9a7e1b0d 100644 --- a/doc/source/f2py/run_main_session.dat +++ b/doc/source/f2py/run_main_session.dat @@ -1,14 +1,14 @@ ->>> import f2py2e ->>> r=f2py2e.run_main(['-m','scalar','docs/usersguide/scalar.f']) +>>> import numpy.f2py +>>> r = numpy.f2py.run_main(['-m','scalar','doc/source/f2py/scalar.f']) Reading fortran codes... - Reading file 'docs/usersguide/scalar.f' + Reading file 'doc/source/f2py/scalar.f' (format:fix,strict) Post-processing... Block: scalar Block: FOO Building modules... Building module "scalar"... Wrote C/API module "scalar" to file "./scalarmodule.c" ->>> print r -{'scalar': {'h': ['/home/users/pearu/src_cvs/f2py2e/src/fortranobject.h'], +>>> printr(r) +{'scalar': {'h': ['/home/users/pearu/src_cvs/f2py/src/fortranobject.h'], 'csrc': ['./scalarmodule.c', - '/home/users/pearu/src_cvs/f2py2e/src/fortranobject.c']}} + '/home/users/pearu/src_cvs/f2py/src/fortranobject.c']}} diff --git a/doc/source/f2py/usage.rst b/doc/source/f2py/usage.rst index a6f093154..0f5068e0e 100644 --- a/doc/source/f2py/usage.rst +++ b/doc/source/f2py/usage.rst @@ -3,7 +3,19 @@ Using F2PY =========== F2PY can be used either as a command line tool ``f2py`` or as a Python -module ``f2py2e``. +module ``numpy.f2py``. While we try to install the command line tool as part +of the numpy setup, some platforms like Windows make it difficult to +reliably put the executable on the ``PATH``. We will refer to ``f2py`` +in this document but you may have to run it as a module + +``` +python -m numpy.f2py +``` + +If you run ``f2py`` with no arguments, and the line ``numpy Version`` at the +end matches the NumPy version printed from ``python -m numpy.f2py``, then you +can use the shorter version. If not, or if you cannot run ``f2py``, you should +replace all calls to ``f2py`` here with the longer version. Command ``f2py`` ================= @@ -194,15 +206,15 @@ Other options: Execute ``f2py`` without any options to get an up-to-date list of available options. -Python module ``f2py2e`` -========================= +Python module ``numpy.f2py`` +============================ .. warning:: - The current Python interface to ``f2py2e`` module is not mature and - may change in future depending on users needs. + The current Python interface to the ``f2py`` module is not mature and + may change in the future. -The following functions are provided by the ``f2py2e`` module: +The following functions are provided by the ``numpy.f2py`` module: ``run_main(<list>)`` Equivalent to running:: diff --git a/doc/source/reference/c-api.ufunc.rst b/doc/source/reference/c-api.ufunc.rst index 8c2554a9e..07c7b0c80 100644 --- a/doc/source/reference/c-api.ufunc.rst +++ b/doc/source/reference/c-api.ufunc.rst @@ -85,12 +85,61 @@ Functions Must to an array of length *ntypes* containing :c:type:`PyUFuncGenericFunction` items. These items are pointers to functions that actually implement the underlying - (element-by-element) function :math:`N` times. + (element-by-element) function :math:`N` times with the following + signature: + + .. c:function:: void loopfunc( + char** args, npy_intp* dimensions, npy_intp* steps, void* data) + + *args* + + An array of pointers to the actual data for the input and output + arrays. The input arguments are given first followed by the output + arguments. + + *dimensions* + + A pointer to the size of the dimension over which this function is + looping. + + *steps* + + A pointer to the number of bytes to jump to get to the + next element in this dimension for each of the input and + output arguments. + + *data* + + Arbitrary data (extra arguments, function names, *etc.* ) + that can be stored with the ufunc and will be passed in + when it is called. + + This is an example of a func specialized for addition of doubles + returning doubles. + + .. code-block:: c + + static void + double_add(char **args, npy_intp *dimensions, npy_intp *steps, + void *extra) + { + npy_intp i; + npy_intp is1 = steps[0], is2 = steps[1]; + npy_intp os = steps[2], n = dimensions[0]; + char *i1 = args[0], *i2 = args[1], *op = args[2]; + for (i = 0; i < n; i++) { + *((double *)op) = *((double *)i1) + + *((double *)i2); + i1 += is1; + i2 += is2; + op += os; + } + } :param data: Should be ``NULL`` or a pointer to an array of size *ntypes* . This array may contain arbitrary extra-data to be passed to - the corresponding 1-d loop function in the func array. + the corresponding loop function in the func array. :param types: Length ``(nin + nout) * ntypes`` array of ``char`` encoding the @@ -102,6 +151,9 @@ Functions be ``(char[]) {5, 5, 0, 7, 7, 0}`` since ``NPY_INT32`` is 5, ``NPY_INT64`` is 7, and ``NPY_BOOL`` is 0. + The bit-width names can also be used (e.g. :c:data:`NPY_INT32`, + :c:data:`NPY_COMPLEX128` ) if desired. + :ref:`ufuncs.casting` will be used at runtime to find the first ``func`` callable by the input/output provided. @@ -114,14 +166,19 @@ Functions :param nout: The number of outputs + :param identity: + + Either :c:data:`PyUFunc_One`, :c:data:`PyUFunc_Zero`, + :c:data:`PyUFunc_None`. This specifies what should be returned when + an empty array is passed to the reduce method of the ufunc. + :param name: - The name for the ufunc. Specifying a name of 'add' or - 'multiply' enables a special behavior for integer-typed - reductions when no dtype is given. If the input type is an - integer (or boolean) data type smaller than the size of the - `numpy.int_` data type, it will be internally upcast to the - `numpy.int_` (or `numpy.uint`) - data type. + The name for the ufunc as a ``NULL`` terminated string. Specifying + a name of 'add' or 'multiply' enables a special behavior for + integer-typed reductions when no dtype is given. If the input type is an + integer (or boolean) data type smaller than the size of the `numpy.int_` + data type, it will be internally upcast to the `numpy.int_` (or + `numpy.uint`) data type. :param doc: Allows passing in a documentation string to be stored with the diff --git a/doc/source/reference/routines.polynomials.classes.rst b/doc/source/reference/routines.polynomials.classes.rst index f44ddd46c..da0394305 100644 --- a/doc/source/reference/routines.polynomials.classes.rst +++ b/doc/source/reference/routines.polynomials.classes.rst @@ -35,11 +35,11 @@ degree :math:`n`, but could just as easily be the basis functions of any of the other classes. The convention for all the classes is that the coefficient :math:`c[i]` goes with the basis function of degree i. -All of the classes have the same methods, and especially they implement the -Python numeric operators +, -, \*, //, %, divmod, \*\*, ==, -and !=. The last two can be a bit problematic due to floating point -roundoff errors. We now give a quick demonstration of the various -operations using NumPy version 1.7.0. +All of the classes are immutable and have the same methods, and +especially they implement the Python numeric operators +, -, \*, //, %, +divmod, \*\*, ==, and !=. The last two can be a bit problematic due to +floating point roundoff errors. We now give a quick demonstration of the +various operations using NumPy version 1.7.0. Basics ------ @@ -187,6 +187,11 @@ Which gives the polynomial `p` in Chebyshev form. This works because the original polynomial. However, all the multiplications and divisions will be done using Chebyshev series, hence the type of the result. +It is intended that all polynomial instances are immutable, therefore +augmented operations (``+=``, ``-=``, etc.) and any other functionality that +would violate the immutablity of a polynomial instance are intentionally +unimplemented. + Calculus -------- diff --git a/doc/source/release.rst b/doc/source/release.rst index e7166a454..935d397e3 100644 --- a/doc/source/release.rst +++ b/doc/source/release.rst @@ -3,6 +3,7 @@ Release Notes ************* .. include:: ../release/1.16.0-notes.rst +.. include:: ../release/1.15.1-notes.rst .. include:: ../release/1.15.0-notes.rst .. include:: ../release/1.14.5-notes.rst .. include:: ../release/1.14.4-notes.rst diff --git a/doc/source/user/c-info.beyond-basics.rst b/doc/source/user/c-info.beyond-basics.rst index aee68f6e7..d4d941a5e 100644 --- a/doc/source/user/c-info.beyond-basics.rst +++ b/doc/source/user/c-info.beyond-basics.rst @@ -358,38 +358,6 @@ previously created. Then you call :c:func:`PyUFunc_RegisterLoopForType` this function is ``0`` if the process was successful and ``-1`` with an error condition set if it was not successful. -.. c:function:: int PyUFunc_RegisterLoopForType( \ - PyUFuncObject* ufunc, int usertype, PyUFuncGenericFunction function, \ - int* arg_types, void* data) - - *ufunc* - - The ufunc to attach this loop to. - - *usertype* - - The user-defined type this loop should be indexed under. This number - must be a user-defined type or an error occurs. - - *function* - - The ufunc inner 1-d loop. This function must have the signature as - explained in Section `3 <#sec-creating-a-new>`__ . - - *arg_types* - - (optional) If given, this should contain an array of integers of at - least size ufunc.nargs containing the data-types expected by the loop - function. The data will be copied into a NumPy-managed structure so - the memory for this argument should be deleted after calling this - function. If this is NULL, then it will be assumed that all data-types - are of type usertype. - - *data* - - (optional) Specify any optional data needed by the function which will - be passed when the function is called. - .. index:: pair: dtype; adding new diff --git a/doc/source/user/c-info.ufunc-tutorial.rst b/doc/source/user/c-info.ufunc-tutorial.rst index 788a3429f..96a73f9a6 100644 --- a/doc/source/user/c-info.ufunc-tutorial.rst +++ b/doc/source/user/c-info.ufunc-tutorial.rst @@ -893,9 +893,9 @@ Example NumPy ufunc with structured array dtype arguments This example shows how to create a ufunc for a structured array dtype. For the example we show a trivial ufunc for adding two arrays with dtype 'u8,u8,u8'. The process is a bit different from the other examples since -a call to PyUFunc_FromFuncAndData doesn't fully register ufuncs for +a call to :c:func:`PyUFunc_FromFuncAndData` doesn't fully register ufuncs for custom dtypes and structured array dtypes. We need to also call -PyUFunc_RegisterLoopForDescr to finish setting up the ufunc. +:c:func:`PyUFunc_RegisterLoopForDescr` to finish setting up the ufunc. We only give the C code as the setup.py file is exactly the same as the setup.py file in `Example NumPy ufunc for one dtype`_, except that @@ -1048,133 +1048,6 @@ The C file is given below. #endif } - -.. _`sec:PyUFunc-spec`: - -PyUFunc_FromFuncAndData Specification -===================================== - -What follows is the full specification of PyUFunc_FromFuncAndData, which -automatically generates a ufunc from a C function with the correct signature. - -.. seealso:: :c:func:`PyUFunc_FromFuncAndDataAndSignature` - -.. c:function:: PyObject *PyUFunc_FromFuncAndData( \ - PyUFuncGenericFunction* func, void** data, char* types, int ntypes, \ - int nin, int nout, int identity, char* name, char* doc, int unused) - - *func* - - A pointer to an array of 1-d functions to use. This array must be at - least ntypes long. Each entry in the array must be a - ``PyUFuncGenericFunction`` function. This function has the following - signature. An example of a valid 1d loop function is also given. - - .. c:function:: void loop1d( \ - char** args, npy_intp* dimensions, npy_intp* steps, void* data) - - *args* - - An array of pointers to the actual data for the input and output - arrays. The input arguments are given first followed by the output - arguments. - - *dimensions* - - A pointer to the size of the dimension over which this function is - looping. - - *steps* - - A pointer to the number of bytes to jump to get to the - next element in this dimension for each of the input and - output arguments. - - *data* - - Arbitrary data (extra arguments, function names, *etc.* ) - that can be stored with the ufunc and will be passed in - when it is called. - - .. code-block:: c - - static void - double_add(char **args, npy_intp *dimensions, npy_intp *steps, - void *extra) - { - npy_intp i; - npy_intp is1 = steps[0], is2 = steps[1]; - npy_intp os = steps[2], n = dimensions[0]; - char *i1 = args[0], *i2 = args[1], *op = args[2]; - for (i = 0; i < n; i++) { - *((double *)op) = *((double *)i1) + - *((double *)i2); - i1 += is1; - i2 += is2; - op += os; - } - } - - *data* - - An array of data. There should be ntypes entries (or NULL) --- one for - every loop function defined for this ufunc. This data will be passed - in to the 1-d loop. One common use of this data variable is to pass in - an actual function to call to compute the result when a generic 1-d - loop (e.g. :c:func:`PyUFunc_d_d`) is being used. - - *types* - - An array of type-number signatures (type ``char`` ). This - array should be of size (nin+nout)*ntypes and contain the - data-types for the corresponding 1-d loop. The inputs should - be first followed by the outputs. For example, suppose I have - a ufunc that supports 1 integer and 1 double 1-d loop - (length-2 func and data arrays) that takes 2 inputs and - returns 1 output that is always a complex double, then the - types array would be - - .. code-block:: c - - static char types[3] = {NPY_INT, NPY_DOUBLE, NPY_CDOUBLE} - - The bit-width names can also be used (e.g. :c:data:`NPY_INT32`, - :c:data:`NPY_COMPLEX128` ) if desired. - - *ntypes* - - The number of data-types supported. This is equal to the number of 1-d - loops provided. - - *nin* - - The number of input arguments. - - *nout* - - The number of output arguments. - - *identity* - - Either :c:data:`PyUFunc_One`, :c:data:`PyUFunc_Zero`, - :c:data:`PyUFunc_None`. This specifies what should be returned when - an empty array is passed to the reduce method of the ufunc. - - *name* - - A ``NULL`` -terminated string providing the name of this ufunc - (should be the Python name it will be called). - - *doc* - - A documentation string for this ufunc (will be used in generating the - response to ``{ufunc_name}.__doc__``). Do not include the function - signature or the name as this is generated automatically. - - *unused* - - Unused; kept for compatibility. Just set it to zero. - .. index:: pair: ufunc; adding new diff --git a/numpy/__init__.py b/numpy/__init__.py index 2b8d41798..e1df236bb 100644 --- a/numpy/__init__.py +++ b/numpy/__init__.py @@ -133,17 +133,9 @@ else: from .version import git_revision as __git_revision__ from .version import version as __version__ - from ._import_tools import PackageLoader - - def pkgload(*packages, **options): - loader = PackageLoader(infunc=True) - return loader(*packages, **options) - __all__ = ['ModuleDeprecationWarning', 'VisibleDeprecationWarning'] - pkgload.__doc__ = PackageLoader.__call__.__doc__ - # Allow distributors to run custom init code from . import _distributor_init @@ -172,8 +164,7 @@ else: from .core import round, abs, max, min - __all__.extend(['__version__', 'pkgload', 'PackageLoader', - 'show_config']) + __all__.extend(['__version__', 'show_config']) __all__.extend(core.__all__) __all__.extend(_mat.__all__) __all__.extend(lib.__all__) diff --git a/numpy/_import_tools.py b/numpy/_import_tools.py deleted file mode 100644 index cb8bc477c..000000000 --- a/numpy/_import_tools.py +++ /dev/null @@ -1,351 +0,0 @@ -from __future__ import division, absolute_import, print_function - -import os -import sys -import warnings - -__all__ = ['PackageLoader'] - -class PackageLoader(object): - def __init__(self, verbose=False, infunc=False): - """ Manages loading packages. - """ - - if infunc: - _level = 2 - else: - _level = 1 - self.parent_frame = frame = sys._getframe(_level) - self.parent_name = eval('__name__', frame.f_globals, frame.f_locals) - parent_path = eval('__path__', frame.f_globals, frame.f_locals) - if isinstance(parent_path, str): - parent_path = [parent_path] - self.parent_path = parent_path - if '__all__' not in frame.f_locals: - exec('__all__ = []', frame.f_globals, frame.f_locals) - self.parent_export_names = eval('__all__', frame.f_globals, frame.f_locals) - - self.info_modules = {} - self.imported_packages = [] - self.verbose = None - - def _get_info_files(self, package_dir, parent_path, parent_package=None): - """ Return list of (package name,info.py file) from parent_path subdirectories. - """ - from glob import glob - files = glob(os.path.join(parent_path, package_dir, 'info.py')) - for info_file in glob(os.path.join(parent_path, package_dir, 'info.pyc')): - if info_file[:-1] not in files: - files.append(info_file) - info_files = [] - for info_file in files: - package_name = os.path.dirname(info_file[len(parent_path)+1:])\ - .replace(os.sep, '.') - if parent_package: - package_name = parent_package + '.' + package_name - info_files.append((package_name, info_file)) - info_files.extend(self._get_info_files('*', - os.path.dirname(info_file), - package_name)) - return info_files - - def _init_info_modules(self, packages=None): - """Initialize info_modules = {<package_name>: <package info.py module>}. - """ - from numpy.compat import npy_load_module - info_files = [] - info_modules = self.info_modules - - if packages is None: - for path in self.parent_path: - info_files.extend(self._get_info_files('*', path)) - else: - for package_name in packages: - package_dir = os.path.join(*package_name.split('.')) - for path in self.parent_path: - names_files = self._get_info_files(package_dir, path) - if names_files: - info_files.extend(names_files) - break - else: - try: - exec('import %s.info as info' % (package_name)) - info_modules[package_name] = info - except ImportError as msg: - self.warn('No scipy-style subpackage %r found in %s. '\ - 'Ignoring: %s'\ - % (package_name, ':'.join(self.parent_path), msg)) - - for package_name, info_file in info_files: - if package_name in info_modules: - continue - fullname = self.parent_name +'.'+ package_name - if info_file[-1]=='c': - filedescriptor = ('.pyc', 'rb', 2) - else: - filedescriptor = ('.py', 'U', 1) - - try: - info_module = npy_load_module(fullname + '.info', - info_file, - filedescriptor) - except Exception as msg: - self.error(msg) - info_module = None - - if info_module is None or getattr(info_module, 'ignore', False): - info_modules.pop(package_name, None) - else: - self._init_info_modules(getattr(info_module, 'depends', [])) - info_modules[package_name] = info_module - - return - - def _get_sorted_names(self): - """ Return package names sorted in the order as they should be - imported due to dependence relations between packages. - """ - - depend_dict = {} - for name, info_module in self.info_modules.items(): - depend_dict[name] = getattr(info_module, 'depends', []) - package_names = [] - - for name in list(depend_dict.keys()): - if not depend_dict[name]: - package_names.append(name) - del depend_dict[name] - - while depend_dict: - for name, lst in list(depend_dict.items()): - new_lst = [n for n in lst if n in depend_dict] - if not new_lst: - package_names.append(name) - del depend_dict[name] - else: - depend_dict[name] = new_lst - - return package_names - - def __call__(self,*packages, **options): - """Load one or more packages into parent package top-level namespace. - - This function is intended to shorten the need to import many - subpackages, say of scipy, constantly with statements such as - - import scipy.linalg, scipy.fftpack, scipy.etc... - - Instead, you can say: - - import scipy - scipy.pkgload('linalg','fftpack',...) - - or - - scipy.pkgload() - - to load all of them in one call. - - If a name which doesn't exist in scipy's namespace is - given, a warning is shown. - - Parameters - ---------- - *packages : arg-tuple - the names (one or more strings) of all the modules one - wishes to load into the top-level namespace. - verbose= : integer - verbosity level [default: -1]. - verbose=-1 will suspend also warnings. - force= : bool - when True, force reloading loaded packages [default: False]. - postpone= : bool - when True, don't load packages [default: False] - - """ - # 2014-10-29, 1.10 - warnings.warn('pkgload and PackageLoader are obsolete ' - 'and will be removed in a future version of numpy', - DeprecationWarning, stacklevel=2) - frame = self.parent_frame - self.info_modules = {} - if options.get('force', False): - self.imported_packages = [] - self.verbose = verbose = options.get('verbose', -1) - postpone = options.get('postpone', None) - self._init_info_modules(packages or None) - - self.log('Imports to %r namespace\n----------------------------'\ - % self.parent_name) - - for package_name in self._get_sorted_names(): - if package_name in self.imported_packages: - continue - info_module = self.info_modules[package_name] - global_symbols = getattr(info_module, 'global_symbols', []) - postpone_import = getattr(info_module, 'postpone_import', False) - if (postpone and not global_symbols) \ - or (postpone_import and postpone is not None): - continue - - old_object = frame.f_locals.get(package_name, None) - - cmdstr = 'import '+package_name - if self._execcmd(cmdstr): - continue - self.imported_packages.append(package_name) - - if verbose!=-1: - new_object = frame.f_locals.get(package_name) - if old_object is not None and old_object is not new_object: - self.warn('Overwriting %s=%s (was %s)' \ - % (package_name, self._obj2repr(new_object), - self._obj2repr(old_object))) - - if '.' not in package_name: - self.parent_export_names.append(package_name) - - for symbol in global_symbols: - if symbol=='*': - symbols = eval('getattr(%s,"__all__",None)'\ - % (package_name), - frame.f_globals, frame.f_locals) - if symbols is None: - symbols = eval('dir(%s)' % (package_name), - frame.f_globals, frame.f_locals) - symbols = [s for s in symbols if not s.startswith('_')] - else: - symbols = [symbol] - - if verbose!=-1: - old_objects = {} - for s in symbols: - if s in frame.f_locals: - old_objects[s] = frame.f_locals[s] - - cmdstr = 'from '+package_name+' import '+symbol - if self._execcmd(cmdstr): - continue - - if verbose!=-1: - for s, old_object in old_objects.items(): - new_object = frame.f_locals[s] - if new_object is not old_object: - self.warn('Overwriting %s=%s (was %s)' \ - % (s, self._obj2repr(new_object), - self._obj2repr(old_object))) - - if symbol=='*': - self.parent_export_names.extend(symbols) - else: - self.parent_export_names.append(symbol) - - return - - def _execcmd(self, cmdstr): - """ Execute command in parent_frame.""" - frame = self.parent_frame - try: - exec (cmdstr, frame.f_globals, frame.f_locals) - except Exception as msg: - self.error('%s -> failed: %s' % (cmdstr, msg)) - return True - else: - self.log('%s -> success' % (cmdstr)) - return - - def _obj2repr(self, obj): - """ Return repr(obj) with""" - module = getattr(obj, '__module__', None) - file = getattr(obj, '__file__', None) - if module is not None: - return repr(obj) + ' from ' + module - if file is not None: - return repr(obj) + ' from ' + file - return repr(obj) - - def log(self, mess): - if self.verbose>1: - print(str(mess), file=sys.stderr) - def warn(self, mess): - if self.verbose>=0: - print(str(mess), file=sys.stderr) - def error(self, mess): - if self.verbose!=-1: - print(str(mess), file=sys.stderr) - - def _get_doc_title(self, info_module): - """ Get the title from a package info.py file. - """ - title = getattr(info_module, '__doc_title__', None) - if title is not None: - return title - title = getattr(info_module, '__doc__', None) - if title is not None: - title = title.lstrip().split('\n', 1)[0] - return title - return '* Not Available *' - - def _format_titles(self,titles,colsep='---'): - display_window_width = 70 # How to determine the correct value in runtime?? - lengths = [len(name)-name.find('.')-1 for (name, title) in titles]+[0] - max_length = max(lengths) - lines = [] - for (name, title) in titles: - name = name[name.find('.')+1:] - w = max_length - len(name) - words = title.split() - line = '%s%s %s' % (name, w*' ', colsep) - tab = len(line) * ' ' - while words: - word = words.pop(0) - if len(line)+len(word)>display_window_width: - lines.append(line) - line = tab - line += ' ' + word - lines.append(line) - return '\n'.join(lines) - - def get_pkgdocs(self): - """ Return documentation summary of subpackages. - """ - import sys - self.info_modules = {} - self._init_info_modules(None) - - titles = [] - symbols = [] - for package_name, info_module in self.info_modules.items(): - global_symbols = getattr(info_module, 'global_symbols', []) - fullname = self.parent_name +'.'+ package_name - note = '' - if fullname not in sys.modules: - note = ' [*]' - titles.append((fullname, self._get_doc_title(info_module) + note)) - if global_symbols: - symbols.append((package_name, ', '.join(global_symbols))) - - retstr = self._format_titles(titles) +\ - '\n [*] - using a package requires explicit import (see pkgload)' - - - if symbols: - retstr += """\n\nGlobal symbols from subpackages"""\ - """\n-------------------------------\n""" +\ - self._format_titles(symbols, '-->') - - return retstr - -class PackageLoaderDebug(PackageLoader): - def _execcmd(self, cmdstr): - """ Execute command in parent_frame.""" - frame = self.parent_frame - print('Executing', repr(cmdstr), '...', end=' ') - sys.stdout.flush() - exec (cmdstr, frame.f_globals, frame.f_locals) - print('ok') - sys.stdout.flush() - return - -if int(os.environ.get('NUMPY_IMPORT_DEBUG', '0')): - PackageLoader = PackageLoaderDebug diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index b65920fde..9ebd12cbd 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -1454,11 +1454,10 @@ add_newdoc('numpy.core.multiarray', 'arange', Values are generated within the half-open interval ``[start, stop)`` (in other words, the interval including `start` but excluding `stop`). For integer arguments the function is equivalent to the Python built-in - `range <https://docs.python.org/library/functions.html#func-range>`_ function, - but returns an ndarray rather than a list. + `range` function, but returns an ndarray rather than a list. When using a non-integer step, such as 0.1, the results will often not - be consistent. It is better to use ``linspace`` for these cases. + be consistent. It is better to use `numpy.linspace` for these cases. Parameters ---------- @@ -2843,40 +2842,19 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('ctypes', ----- Below are the public attributes of this object which were documented in "Guide to NumPy" (we have omitted undocumented public attributes, - as well as documented private attributes): - - * data: A pointer to the memory area of the array as a Python integer. - This memory area may contain data that is not aligned, or not in correct - byte-order. The memory area may not even be writeable. The array - flags and data-type of this array should be respected when passing this - attribute to arbitrary C-code to avoid trouble that can include Python - crashing. User Beware! The value of this attribute is exactly the same - as self._array_interface_['data'][0]. - - * shape (c_intp*self.ndim): A ctypes array of length self.ndim where - the basetype is the C-integer corresponding to dtype('p') on this - platform. This base-type could be c_int, c_long, or c_longlong - depending on the platform. The c_intp type is defined accordingly in - numpy.ctypeslib. The ctypes array contains the shape of the underlying - array. - - * strides (c_intp*self.ndim): A ctypes array of length self.ndim where - the basetype is the same as for the shape attribute. This ctypes array - contains the strides information from the underlying array. This strides - information is important for showing how many bytes must be jumped to - get to the next element in the array. - - * data_as(obj): Return the data pointer cast to a particular c-types object. - For example, calling self._as_parameter_ is equivalent to - self.data_as(ctypes.c_void_p). Perhaps you want to use the data as a - pointer to a ctypes array of floating-point data: - self.data_as(ctypes.POINTER(ctypes.c_double)). - - * shape_as(obj): Return the shape tuple as an array of some other c-types - type. For example: self.shape_as(ctypes.c_short). - - * strides_as(obj): Return the strides tuple as an array of some other - c-types type. For example: self.strides_as(ctypes.c_longlong). + as well as documented private attributes): + + .. autoattribute:: numpy.core._internal._ctypes.data + + .. autoattribute:: numpy.core._internal._ctypes.shape + + .. autoattribute:: numpy.core._internal._ctypes.strides + + .. automethod:: numpy.core._internal._ctypes.data_as + + .. automethod:: numpy.core._internal._ctypes.shape_as + + .. automethod:: numpy.core._internal._ctypes.strides_as Be careful using the ctypes attribute - especially on temporary arrays or arrays constructed on the fly. For example, calling @@ -7158,10 +7136,10 @@ add_newdoc('numpy.core.multiarray', 'datetime_data', array(250, dtype='timedelta64[s]') The result can be used to construct a datetime that uses the same units - as a timedelta:: + as a timedelta >>> np.datetime64('2010', np.datetime_data(dt_25s)) - numpy.datetime64('2010-01-01T00:00:00','25s') + numpy.datetime64('2010-01-01T00:00:00', '25s') """) diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py index 9990bacf0..48ede14d0 100644 --- a/numpy/core/_internal.py +++ b/numpy/core/_internal.py @@ -9,7 +9,7 @@ from __future__ import division, absolute_import, print_function import re import sys -from numpy.compat import basestring +from numpy.compat import basestring, unicode from .multiarray import dtype, array, ndarray try: import ctypes @@ -257,33 +257,72 @@ class _ctypes(object): self._zerod = False def data_as(self, obj): + """ + Return the data pointer cast to a particular c-types object. + For example, calling ``self._as_parameter_`` is equivalent to + ``self.data_as(ctypes.c_void_p)``. Perhaps you want to use the data as a + pointer to a ctypes array of floating-point data: + ``self.data_as(ctypes.POINTER(ctypes.c_double))``. + """ return self._ctypes.cast(self._data, obj) def shape_as(self, obj): + """ + Return the shape tuple as an array of some other c-types + type. For example: ``self.shape_as(ctypes.c_short)``. + """ if self._zerod: return None return (obj*self._arr.ndim)(*self._arr.shape) def strides_as(self, obj): + """ + Return the strides tuple as an array of some other + c-types type. For example: ``self.strides_as(ctypes.c_longlong)``. + """ if self._zerod: return None return (obj*self._arr.ndim)(*self._arr.strides) def get_data(self): + """ + A pointer to the memory area of the array as a Python integer. + This memory area may contain data that is not aligned, or not in correct + byte-order. The memory area may not even be writeable. The array + flags and data-type of this array should be respected when passing this + attribute to arbitrary C-code to avoid trouble that can include Python + crashing. User Beware! The value of this attribute is exactly the same + as ``self._array_interface_['data'][0]``. + """ return self._data def get_shape(self): + """ + (c_intp*self.ndim): A ctypes array of length self.ndim where + the basetype is the C-integer corresponding to ``dtype('p')`` on this + platform. This base-type could be `ctypes.c_int`, `ctypes.c_long`, or + `ctypes.c_longlong` depending on the platform. + The c_intp type is defined accordingly in `numpy.ctypeslib`. + The ctypes array contains the shape of the underlying array. + """ return self.shape_as(_getintp_ctype()) def get_strides(self): + """ + (c_intp*self.ndim): A ctypes array of length self.ndim where + the basetype is the same as for the shape attribute. This ctypes array + contains the strides information from the underlying array. This strides + information is important for showing how many bytes must be jumped to + get to the next element in the array. + """ return self.strides_as(_getintp_ctype()) def get_as_parameter(self): return self._ctypes.c_void_p(self._data) - data = property(get_data, None, doc="c-types data") - shape = property(get_shape, None, doc="c-types shape") - strides = property(get_strides, None, doc="c-types strides") + data = property(get_data) + shape = property(get_shape) + strides = property(get_strides) _as_parameter_ = property(get_as_parameter, None, doc="_as parameter_") @@ -294,7 +333,7 @@ def _newnames(datatype, order): """ oldnames = datatype.names nameslist = list(oldnames) - if isinstance(order, str): + if isinstance(order, (str, unicode)): order = [order] seen = set() if isinstance(order, (list, tuple)): @@ -444,46 +483,46 @@ _pep3118_standard_map = { } _pep3118_standard_typechars = ''.join(_pep3118_standard_map.keys()) -def _dtype_from_pep3118(spec): - class Stream(object): - def __init__(self, s): - self.s = s - self.byteorder = '@' +class _Stream(object): + def __init__(self, s): + self.s = s + self.byteorder = '@' - def advance(self, n): - res = self.s[:n] - self.s = self.s[n:] - return res + def advance(self, n): + res = self.s[:n] + self.s = self.s[n:] + return res - def consume(self, c): - if self.s[:len(c)] == c: - self.advance(len(c)) - return True - return False - - def consume_until(self, c): - if callable(c): - i = 0 - while i < len(self.s) and not c(self.s[i]): - i = i + 1 - return self.advance(i) - else: - i = self.s.index(c) - res = self.advance(i) - self.advance(len(c)) - return res + def consume(self, c): + if self.s[:len(c)] == c: + self.advance(len(c)) + return True + return False - @property - def next(self): - return self.s[0] + def consume_until(self, c): + if callable(c): + i = 0 + while i < len(self.s) and not c(self.s[i]): + i = i + 1 + return self.advance(i) + else: + i = self.s.index(c) + res = self.advance(i) + self.advance(len(c)) + return res - def __bool__(self): - return bool(self.s) - __nonzero__ = __bool__ + @property + def next(self): + return self.s[0] - stream = Stream(spec) + def __bool__(self): + return bool(self.s) + __nonzero__ = __bool__ + +def _dtype_from_pep3118(spec): + stream = _Stream(spec) dtype, align = __dtype_from_pep3118(stream, is_subdtype=False) return dtype diff --git a/numpy/core/code_generators/generate_numpy_api.py b/numpy/core/code_generators/generate_numpy_api.py index b4aeaa277..7f2541667 100644 --- a/numpy/core/code_generators/generate_numpy_api.py +++ b/numpy/core/code_generators/generate_numpy_api.py @@ -46,11 +46,11 @@ static int _import_array(void) { int st; - PyObject *numpy = PyImport_ImportModule("numpy.core.multiarray"); + PyObject *numpy = PyImport_ImportModule("numpy.core._multiarray_umath"); PyObject *c_api = NULL; if (numpy == NULL) { - PyErr_SetString(PyExc_ImportError, "numpy.core.multiarray failed to import"); + PyErr_SetString(PyExc_ImportError, "numpy.core._multiarray_umath failed to import"); return -1; } c_api = PyObject_GetAttrString(numpy, "_ARRAY_API"); diff --git a/numpy/core/code_generators/generate_ufunc_api.py b/numpy/core/code_generators/generate_ufunc_api.py index 3bcf137f7..1b0143e88 100644 --- a/numpy/core/code_generators/generate_ufunc_api.py +++ b/numpy/core/code_generators/generate_ufunc_api.py @@ -36,11 +36,12 @@ static void **PyUFunc_API=NULL; static NPY_INLINE int _import_umath(void) { - PyObject *numpy = PyImport_ImportModule("numpy.core.umath"); + PyObject *numpy = PyImport_ImportModule("numpy.core._multiarray_umath"); PyObject *c_api = NULL; if (numpy == NULL) { - PyErr_SetString(PyExc_ImportError, "numpy.core.umath failed to import"); + PyErr_SetString(PyExc_ImportError, + "numpy.core._multiarray_umath failed to import"); return -1; } c_api = PyObject_GetAttrString(numpy, "_UFUNC_API"); diff --git a/numpy/core/code_generators/generate_umath.py b/numpy/core/code_generators/generate_umath.py index 632bcb41f..6dc01877b 100644 --- a/numpy/core/code_generators/generate_umath.py +++ b/numpy/core/code_generators/generate_umath.py @@ -1080,6 +1080,8 @@ def make_code(funcdict, filename): Please make changes to the code generator program (%s) **/ #include "cpuid.h" + #include "ufunc_object.h" + #include "ufunc_type_resolution.h" %s static int diff --git a/numpy/core/einsumfunc.py b/numpy/core/einsumfunc.py index 163f125c2..5b8689235 100644 --- a/numpy/core/einsumfunc.py +++ b/numpy/core/einsumfunc.py @@ -1319,8 +1319,8 @@ def einsum(*operands, **kwargs): """ - # Grab non-einsum kwargs; never optimize 2-argument case. - optimize_arg = kwargs.pop('optimize', len(operands) > 3) + # Grab non-einsum kwargs; do not optimize by default. + optimize_arg = kwargs.pop('optimize', False) # If no optimization, run pure einsum if optimize_arg is False: diff --git a/numpy/core/function_base.py b/numpy/core/function_base.py index fb72bada5..799b1418d 100644 --- a/numpy/core/function_base.py +++ b/numpy/core/function_base.py @@ -71,7 +71,10 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None): -------- arange : Similar to `linspace`, but uses a step size (instead of the number of samples). - logspace : Samples uniformly distributed in log space. + geomspace : Similar to `linspace`, but with numbers spaced evenly on a log + scale (a geometric progression). + logspace : Similar to `geomspace`, but with the end points specified as + logarithms. Examples -------- diff --git a/numpy/core/multiarray.py b/numpy/core/multiarray.py new file mode 100644 index 000000000..8b07bccf2 --- /dev/null +++ b/numpy/core/multiarray.py @@ -0,0 +1,34 @@ +""" +Create the numpy.core.multiarray namespace for backward compatibility. In v1.16 +the multiarray and umath c-extension modules were merged into a single +_multiarray_umath extension module. So we replicate the old namespace +by importing from the extension module. +""" + +from . import _multiarray_umath +from numpy.core._multiarray_umath import * +from numpy.core._multiarray_umath import (_fastCopyAndTranspose, _flagdict, _insert, + _reconstruct, _vec_string, _ARRAY_API, _monotonicity) + +__all__ = ['_ARRAY_API', 'ALLOW_THREADS', 'BUFSIZE', 'CLIP', 'DATETIMEUNITS', + 'ITEM_HASOBJECT', 'ITEM_IS_POINTER', 'LIST_PICKLE', 'MAXDIMS', + 'MAY_SHARE_BOUNDS', 'MAY_SHARE_EXACT', 'NEEDS_INIT', 'NEEDS_PYAPI', + 'RAISE', 'USE_GETITEM', 'USE_SETITEM', 'WRAP', + '_fastCopyAndTranspose', '_flagdict', '_insert', '_reconstruct', + '_vec_string', '_monotonicity', + 'add_docstring', 'arange', 'array', 'bincount', 'broadcast', 'busday_count', + 'busday_offset', 'busdaycalendar', 'can_cast', 'compare_chararrays', + 'concatenate', 'copyto', 'correlate', 'correlate2', 'count_nonzero', + 'c_einsum', 'datetime_as_string', 'datetime_data', 'digitize', 'dot', + 'dragon4_positional', 'dragon4_scientific', 'dtype', 'empty', 'empty_like', + 'error', 'flagsobj', 'flatiter', 'format_longfloat', 'frombuffer', + 'fromfile', 'fromiter', 'fromstring', 'getbuffer', 'inner', 'int_asbuffer', + 'interp', 'interp_complex', 'is_busday', 'lexsort', 'matmul', + 'may_share_memory', 'min_scalar_type', 'ndarray', 'nditer', 'nested_iters', + 'newbuffer', 'normalize_axis_index', 'packbits', 'promote_types', + 'putmask', 'ravel_multi_index', 'result_type', 'scalar', + 'set_datetimeparse_function', 'set_legacy_print_mode', 'set_numeric_ops', + 'set_string_function', 'set_typeDict', 'shares_memory', 'test_interrupt', + 'tracemalloc_domain', 'typeinfo', 'unpackbits', 'unravel_index', 'vdot', + 'where', 'zeros'] + diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py index e5570791a..1b4818b76 100644 --- a/numpy/core/numeric.py +++ b/numpy/core/numeric.py @@ -2850,16 +2850,11 @@ class errstate(object): Notes ----- - The ``with`` statement was introduced in Python 2.5, and can only be used - there by importing it: ``from __future__ import with_statement``. In - earlier Python versions the ``with`` statement is not available. - For complete documentation of the types of floating-point exceptions and treatment options, see `seterr`. Examples -------- - >>> from __future__ import with_statement # use 'with' in Python 2.5 >>> olderr = np.seterr(all='ignore') # Set error handling to known state. >>> np.arange(3) / 0. @@ -2919,10 +2914,7 @@ True_ = bool_(True) def extend_all(module): existing = set(__all__) - try: - mall = getattr(module, '__all__') - except AttributeError: - mall = [k for k in module.__dict__.keys() if not k.startswith('_')] + mall = getattr(module, '__all__') for a in mall: if a not in existing: __all__.append(a) diff --git a/numpy/core/records.py b/numpy/core/records.py index 612d39322..a483871ba 100644 --- a/numpy/core/records.py +++ b/numpy/core/records.py @@ -42,7 +42,7 @@ import warnings from . import numeric as sb from . import numerictypes as nt -from numpy.compat import isfileobj, bytes, long +from numpy.compat import isfileobj, bytes, long, unicode from .arrayprint import get_printoptions # All of the functions allow formats to be a dtype @@ -174,7 +174,7 @@ class format_parser(object): if (names): if (type(names) in [list, tuple]): pass - elif isinstance(names, str): + elif isinstance(names, (str, unicode)): names = names.split(',') else: raise NameError("illegal input names %s" % repr(names)) diff --git a/numpy/core/setup.py b/numpy/core/setup.py index f826b278f..b306aa4e8 100644 --- a/numpy/core/setup.py +++ b/numpy/core/setup.py @@ -514,9 +514,9 @@ def configuration(parent_package='',top_path=None): def generate_numpyconfig_h(ext, build_dir): """Depends on config.h: generate_config_h has to be called before !""" - # put private include directory in build_dir on search path + # put common include directory in build_dir on search path # allows using code generation in headers headers - config.add_include_dirs(join(build_dir, "src", "private")) + config.add_include_dirs(join(build_dir, "src", "common")) config.add_include_dirs(join(build_dir, "src", "npymath")) target = join(build_dir, header_dir, '_numpyconfig.h') @@ -603,7 +603,7 @@ def configuration(parent_package='',top_path=None): generate_numpy_api = generate_api_func('generate_numpy_api') generate_ufunc_api = generate_api_func('generate_ufunc_api') - config.add_include_dirs(join(local_dir, "src", "private")) + config.add_include_dirs(join(local_dir, "src", "common")) config.add_include_dirs(join(local_dir, "src")) config.add_include_dirs(join(local_dir)) @@ -700,9 +700,9 @@ def configuration(parent_package='',top_path=None): npysort_sources = [join('src', 'npysort', 'quicksort.c.src'), join('src', 'npysort', 'mergesort.c.src'), join('src', 'npysort', 'heapsort.c.src'), - join('src', 'private', 'npy_partition.h.src'), + join('src', 'common', 'npy_partition.h.src'), join('src', 'npysort', 'selection.c.src'), - join('src', 'private', 'npy_binsearch.h.src'), + join('src', 'common', 'npy_binsearch.h.src'), join('src', 'npysort', 'binsearch.c.src'), ] config.add_library('npysort', @@ -710,16 +710,55 @@ def configuration(parent_package='',top_path=None): include_dirs=[]) ####################################################################### - # multiarray module # + # _multiarray_umath module - common part # + ####################################################################### + + common_deps = [ + join('src', 'common', 'array_assign.h'), + join('src', 'common', 'binop_override.h'), + join('src', 'common', 'cblasfuncs.h'), + join('src', 'common', 'lowlevel_strided_loops.h'), + join('src', 'common', 'mem_overlap.h'), + join('src', 'common', 'npy_config.h'), + join('src', 'common', 'npy_extint128.h'), + join('src', 'common', 'npy_longdouble.h'), + join('src', 'common', 'templ_common.h.src'), + join('src', 'common', 'ucsnarrow.h'), + join('src', 'common', 'ufunc_override.h'), + join('src', 'common', 'umathmodule.h'), + ] + + common_src = [ + join('src', 'common', 'array_assign.c'), + join('src', 'common', 'mem_overlap.c'), + join('src', 'common', 'npy_longdouble.c'), + join('src', 'common', 'templ_common.h.src'), + join('src', 'common', 'ucsnarrow.c'), + join('src', 'common', 'ufunc_override.c'), + ] + + blas_info = get_info('blas_opt', 0) + if blas_info and ('HAVE_CBLAS', None) in blas_info.get('define_macros', []): + extra_info = blas_info + # These files are also in MANIFEST.in so that they are always in + # the source distribution independently of HAVE_CBLAS. + common_src.extend([join('src', 'common', 'cblasfuncs.c'), + join('src', 'common', 'python_xerbla.c'), + ]) + if uses_accelerate_framework(blas_info): + common_src.extend(get_sgemv_fix()) + else: + extra_info = {} + + ####################################################################### + # _multiarray_umath module - multiarray part # ####################################################################### multiarray_deps = [ join('src', 'multiarray', 'arrayobject.h'), join('src', 'multiarray', 'arraytypes.h'), - join('src', 'multiarray', 'array_assign.h'), join('src', 'multiarray', 'buffer.h'), join('src', 'multiarray', 'calculation.h'), - join('src', 'multiarray', 'cblasfuncs.h'), join('src', 'multiarray', 'common.h'), join('src', 'multiarray', 'convert_datatype.h'), join('src', 'multiarray', 'convert.h'), @@ -742,17 +781,8 @@ def configuration(parent_package='',top_path=None): join('src', 'multiarray', 'shape.h'), join('src', 'multiarray', 'strfuncs.h'), join('src', 'multiarray', 'typeinfo.h'), - join('src', 'multiarray', 'ucsnarrow.h'), join('src', 'multiarray', 'usertypes.h'), join('src', 'multiarray', 'vdot.h'), - join('src', 'private', 'npy_config.h'), - join('src', 'private', 'templ_common.h.src'), - join('src', 'private', 'lowlevel_strided_loops.h'), - join('src', 'private', 'mem_overlap.h'), - join('src', 'private', 'npy_longdouble.h'), - join('src', 'private', 'ufunc_override.h'), - join('src', 'private', 'binop_override.h'), - join('src', 'private', 'npy_extint128.h'), join('include', 'numpy', 'arrayobject.h'), join('include', 'numpy', '_neighborhood_iterator_imp.h'), join('include', 'numpy', 'npy_endian.h'), @@ -778,7 +808,6 @@ def configuration(parent_package='',top_path=None): join('src', 'multiarray', 'alloc.c'), join('src', 'multiarray', 'arrayobject.c'), join('src', 'multiarray', 'arraytypes.c.src'), - join('src', 'multiarray', 'array_assign.c'), join('src', 'multiarray', 'array_assign_scalar.c'), join('src', 'multiarray', 'array_assign_array.c'), join('src', 'multiarray', 'buffer.c'), @@ -821,40 +850,11 @@ def configuration(parent_package='',top_path=None): join('src', 'multiarray', 'temp_elide.c'), join('src', 'multiarray', 'typeinfo.c'), join('src', 'multiarray', 'usertypes.c'), - join('src', 'multiarray', 'ucsnarrow.c'), join('src', 'multiarray', 'vdot.c'), - join('src', 'private', 'templ_common.h.src'), - join('src', 'private', 'mem_overlap.c'), - join('src', 'private', 'npy_longdouble.c'), - join('src', 'private', 'ufunc_override.c'), ] - blas_info = get_info('blas_opt', 0) - if blas_info and ('HAVE_CBLAS', None) in blas_info.get('define_macros', []): - extra_info = blas_info - # These files are also in MANIFEST.in so that they are always in - # the source distribution independently of HAVE_CBLAS. - multiarray_src.extend([join('src', 'multiarray', 'cblasfuncs.c'), - join('src', 'multiarray', 'python_xerbla.c'), - ]) - if uses_accelerate_framework(blas_info): - multiarray_src.extend(get_sgemv_fix()) - else: - extra_info = {} - - config.add_extension('multiarray', - sources=multiarray_src + - [generate_config_h, - generate_numpyconfig_h, - generate_numpy_api, - join(codegen_dir, 'generate_numpy_api.py'), - join('*.py')], - depends=deps + multiarray_deps, - libraries=['npymath', 'npysort'], - extra_info=extra_info) - ####################################################################### - # umath module # + # _multiarray_umath module - umath part # ####################################################################### def generate_umath_c(ext, build_dir): @@ -883,34 +883,34 @@ def configuration(parent_package='',top_path=None): join('src', 'umath', 'scalarmath.c.src'), join('src', 'umath', 'ufunc_type_resolution.c'), join('src', 'umath', 'override.c'), - join('src', 'private', 'mem_overlap.c'), - join('src', 'private', 'npy_longdouble.c'), - join('src', 'private', 'ufunc_override.c')] + ] umath_deps = [ generate_umath_py, join('include', 'numpy', 'npy_math.h'), join('include', 'numpy', 'halffloat.h'), join('src', 'multiarray', 'common.h'), - join('src', 'private', 'templ_common.h.src'), + join('src', 'common', 'templ_common.h.src'), join('src', 'umath', 'simd.inc.src'), join('src', 'umath', 'override.h'), join(codegen_dir, 'generate_ufunc_api.py'), - join('src', 'private', 'lowlevel_strided_loops.h'), - join('src', 'private', 'mem_overlap.h'), - join('src', 'private', 'npy_longdouble.h'), - join('src', 'private', 'ufunc_override.h'), - join('src', 'private', 'binop_override.h')] + npymath_sources - - config.add_extension('umath', - sources=umath_src + + ] + + config.add_extension('_multiarray_umath', + sources=multiarray_src + umath_src + + npymath_sources + common_src + [generate_config_h, - generate_numpyconfig_h, - generate_umath_c, - generate_ufunc_api], - depends=deps + umath_deps, - libraries=['npymath'], - ) + generate_numpyconfig_h, + generate_numpy_api, + join(codegen_dir, 'generate_numpy_api.py'), + join('*.py'), + generate_umath_c, + generate_ufunc_api, + ], + depends=deps + multiarray_deps + umath_deps + + common_deps, + libraries=['npymath', 'npysort'], + extra_info=extra_info) ####################################################################### # umath_tests module # @@ -939,9 +939,9 @@ def configuration(parent_package='',top_path=None): config.add_extension('_multiarray_tests', sources=[join('src', 'multiarray', '_multiarray_tests.c.src'), - join('src', 'private', 'mem_overlap.c')], - depends=[join('src', 'private', 'mem_overlap.h'), - join('src', 'private', 'npy_extint128.h')], + join('src', 'common', 'mem_overlap.c')], + depends=[join('src', 'common', 'mem_overlap.h'), + join('src', 'common', 'npy_extint128.h')], libraries=['npymath']) ####################################################################### diff --git a/numpy/core/src/multiarray/array_assign.c b/numpy/core/src/common/array_assign.c index a48e245d8..a48e245d8 100644 --- a/numpy/core/src/multiarray/array_assign.c +++ b/numpy/core/src/common/array_assign.c diff --git a/numpy/core/src/multiarray/array_assign.h b/numpy/core/src/common/array_assign.h index 3fecff007..3fecff007 100644 --- a/numpy/core/src/multiarray/array_assign.h +++ b/numpy/core/src/common/array_assign.h diff --git a/numpy/core/src/private/binop_override.h b/numpy/core/src/common/binop_override.h index 47df63e38..47df63e38 100644 --- a/numpy/core/src/private/binop_override.h +++ b/numpy/core/src/common/binop_override.h diff --git a/numpy/core/src/multiarray/cblasfuncs.c b/numpy/core/src/common/cblasfuncs.c index 6460c5db1..6460c5db1 100644 --- a/numpy/core/src/multiarray/cblasfuncs.c +++ b/numpy/core/src/common/cblasfuncs.c diff --git a/numpy/core/src/multiarray/cblasfuncs.h b/numpy/core/src/common/cblasfuncs.h index 66ce4ca5b..66ce4ca5b 100644 --- a/numpy/core/src/multiarray/cblasfuncs.h +++ b/numpy/core/src/common/cblasfuncs.h diff --git a/numpy/core/src/private/get_attr_string.h b/numpy/core/src/common/get_attr_string.h index bec87c5ed..bec87c5ed 100644 --- a/numpy/core/src/private/get_attr_string.h +++ b/numpy/core/src/common/get_attr_string.h diff --git a/numpy/core/src/private/lowlevel_strided_loops.h b/numpy/core/src/common/lowlevel_strided_loops.h index f9c671f77..f9c671f77 100644 --- a/numpy/core/src/private/lowlevel_strided_loops.h +++ b/numpy/core/src/common/lowlevel_strided_loops.h diff --git a/numpy/core/src/private/mem_overlap.c b/numpy/core/src/common/mem_overlap.c index 21db1893b..21db1893b 100644 --- a/numpy/core/src/private/mem_overlap.c +++ b/numpy/core/src/common/mem_overlap.c diff --git a/numpy/core/src/private/mem_overlap.h b/numpy/core/src/common/mem_overlap.h index 8044f1663..8044f1663 100644 --- a/numpy/core/src/private/mem_overlap.h +++ b/numpy/core/src/common/mem_overlap.h diff --git a/numpy/core/src/private/npy_binsearch.h.src b/numpy/core/src/common/npy_binsearch.h.src index ce3b34b0e..ce3b34b0e 100644 --- a/numpy/core/src/private/npy_binsearch.h.src +++ b/numpy/core/src/common/npy_binsearch.h.src diff --git a/numpy/core/src/private/npy_cblas.h b/numpy/core/src/common/npy_cblas.h index a083f3bcc..a083f3bcc 100644 --- a/numpy/core/src/private/npy_cblas.h +++ b/numpy/core/src/common/npy_cblas.h diff --git a/numpy/core/src/private/npy_config.h b/numpy/core/src/common/npy_config.h index 8143e7719..8143e7719 100644 --- a/numpy/core/src/private/npy_config.h +++ b/numpy/core/src/common/npy_config.h diff --git a/numpy/core/src/private/npy_extint128.h b/numpy/core/src/common/npy_extint128.h index a887ff317..a887ff317 100644 --- a/numpy/core/src/private/npy_extint128.h +++ b/numpy/core/src/common/npy_extint128.h diff --git a/numpy/core/src/private/npy_fpmath.h b/numpy/core/src/common/npy_fpmath.h index dbb3fb23d..dbb3fb23d 100644 --- a/numpy/core/src/private/npy_fpmath.h +++ b/numpy/core/src/common/npy_fpmath.h diff --git a/numpy/core/src/private/npy_import.h b/numpy/core/src/common/npy_import.h index 221e1e645..221e1e645 100644 --- a/numpy/core/src/private/npy_import.h +++ b/numpy/core/src/common/npy_import.h diff --git a/numpy/core/src/private/npy_longdouble.c b/numpy/core/src/common/npy_longdouble.c index 508fbceac..508fbceac 100644 --- a/numpy/core/src/private/npy_longdouble.c +++ b/numpy/core/src/common/npy_longdouble.c diff --git a/numpy/core/src/private/npy_longdouble.h b/numpy/core/src/common/npy_longdouble.h index 036b53070..036b53070 100644 --- a/numpy/core/src/private/npy_longdouble.h +++ b/numpy/core/src/common/npy_longdouble.h diff --git a/numpy/core/src/private/npy_partition.h.src b/numpy/core/src/common/npy_partition.h.src index a22cf911c..a22cf911c 100644 --- a/numpy/core/src/private/npy_partition.h.src +++ b/numpy/core/src/common/npy_partition.h.src diff --git a/numpy/core/src/private/npy_pycompat.h b/numpy/core/src/common/npy_pycompat.h index aa0b5c122..aa0b5c122 100644 --- a/numpy/core/src/private/npy_pycompat.h +++ b/numpy/core/src/common/npy_pycompat.h diff --git a/numpy/core/src/private/npy_sort.h b/numpy/core/src/common/npy_sort.h index 8c6f05623..8c6f05623 100644 --- a/numpy/core/src/private/npy_sort.h +++ b/numpy/core/src/common/npy_sort.h diff --git a/numpy/core/src/multiarray/python_xerbla.c b/numpy/core/src/common/python_xerbla.c index bdf0b9058..bdf0b9058 100644 --- a/numpy/core/src/multiarray/python_xerbla.c +++ b/numpy/core/src/common/python_xerbla.c diff --git a/numpy/core/src/private/templ_common.h.src b/numpy/core/src/common/templ_common.h.src index a65a00758..a65a00758 100644 --- a/numpy/core/src/private/templ_common.h.src +++ b/numpy/core/src/common/templ_common.h.src diff --git a/numpy/core/src/multiarray/ucsnarrow.c b/numpy/core/src/common/ucsnarrow.c index 8e293e9f2..8e293e9f2 100644 --- a/numpy/core/src/multiarray/ucsnarrow.c +++ b/numpy/core/src/common/ucsnarrow.c diff --git a/numpy/core/src/multiarray/ucsnarrow.h b/numpy/core/src/common/ucsnarrow.h index fe31a5e25..fe31a5e25 100644 --- a/numpy/core/src/multiarray/ucsnarrow.h +++ b/numpy/core/src/common/ucsnarrow.h diff --git a/numpy/core/src/private/ufunc_override.c b/numpy/core/src/common/ufunc_override.c index 33b54c665..33b54c665 100644 --- a/numpy/core/src/private/ufunc_override.c +++ b/numpy/core/src/common/ufunc_override.c diff --git a/numpy/core/src/private/ufunc_override.h b/numpy/core/src/common/ufunc_override.h index 5b269d270..5b269d270 100644 --- a/numpy/core/src/private/ufunc_override.h +++ b/numpy/core/src/common/ufunc_override.h diff --git a/numpy/core/src/common/umathmodule.h b/numpy/core/src/common/umathmodule.h new file mode 100644 index 000000000..6998596ee --- /dev/null +++ b/numpy/core/src/common/umathmodule.h @@ -0,0 +1,8 @@ +#include "__umath_generated.c" +#include "__ufunc_api.c" + +PyObject * add_newdoc_ufunc(PyObject *NPY_UNUSED(dummy), PyObject *args); +PyObject * ufunc_frompyfunc(PyObject *NPY_UNUSED(dummy), PyObject *args, PyObject *NPY_UNUSED(kwds)); +int initumath(PyObject *m); + + diff --git a/numpy/core/src/multiarray/arraytypes.c.src b/numpy/core/src/multiarray/arraytypes.c.src index b4158ec8e..d622effe6 100644 --- a/numpy/core/src/multiarray/arraytypes.c.src +++ b/numpy/core/src/multiarray/arraytypes.c.src @@ -733,7 +733,7 @@ VOID_getitem(void *input, void *vap) return (PyObject *)ret; } - return PyBytes_FromStringAndSize(PyArray_DATA(ap), descr->elsize); + return PyBytes_FromStringAndSize(ip, descr->elsize); } diff --git a/numpy/core/src/multiarray/buffer.c b/numpy/core/src/multiarray/buffer.c index 21dbdefd6..c8e3da8bc 100644 --- a/numpy/core/src/multiarray/buffer.c +++ b/numpy/core/src/multiarray/buffer.c @@ -175,6 +175,14 @@ _is_natively_aligned_at(PyArray_Descr *descr, return 1; } +/* + * Fill in str with an appropriate PEP 3118 format string, based on + * descr. For structured dtypes, calls itself recursively. Each call extends + * str at offset then updates offset, and uses descr->byteorder, (and + * possibly the byte order in obj) to determine the byte-order char. + * + * Returns 0 for success, -1 for failure + */ static int _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str, PyObject* obj, Py_ssize_t *offset, @@ -195,8 +203,8 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str, PyObject *item, *subarray_tuple; Py_ssize_t total_count = 1; Py_ssize_t dim_size; + Py_ssize_t old_offset; char buf[128]; - int old_offset; int ret; if (PyTuple_Check(descr->subarray->shape)) { @@ -230,15 +238,15 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str, return ret; } else if (PyDataType_HASFIELDS(descr)) { - int base_offset = *offset; + Py_ssize_t base_offset = *offset; _append_str(str, "T{"); for (k = 0; k < PyTuple_GET_SIZE(descr->names); ++k) { PyObject *name, *item, *offset_obj, *tmp; PyArray_Descr *child; char *p; - Py_ssize_t len; - int new_offset; + Py_ssize_t len, new_offset; + int ret; name = PyTuple_GET_ITEM(descr->names, k); item = PyDict_GetItem(descr->fields, name); @@ -266,8 +274,11 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str, } /* Insert child item */ - _buffer_format_string(child, str, obj, offset, + ret = _buffer_format_string(child, str, obj, offset, active_byteorder); + if (ret < 0) { + return -1; + } /* Insert field name */ #if defined(NPY_PY3K) @@ -393,8 +404,8 @@ _buffer_format_string(PyArray_Descr *descr, _tmp_string_t *str, case NPY_CFLOAT: if (_append_str(str, "Zf")) return -1; break; case NPY_CDOUBLE: if (_append_str(str, "Zd")) return -1; break; case NPY_CLONGDOUBLE: if (_append_str(str, "Zg")) return -1; break; - /* XXX: datetime */ - /* XXX: timedelta */ + /* XXX NPY_DATETIME */ + /* XXX NPY_TIMEDELTA */ case NPY_OBJECT: if (_append_char(str, 'O')) return -1; break; case NPY_STRING: { char buf[128]; @@ -468,10 +479,33 @@ _buffer_info_new(PyObject *obj) info = malloc(sizeof(_buffer_info_t)); if (info == NULL) { + PyErr_NoMemory(); goto fail; } - if (PyArray_IsScalar(obj, Generic)) { + if (PyArray_IsScalar(obj, Datetime) || PyArray_IsScalar(obj, Timedelta)) { + /* + * Special case datetime64 scalars to remain backward compatible. + * This will change in a future version. + * Note arrays of datetime64 and strutured arrays with datetime64 + * fields will not hit this code path and are currently unsupported + * in _buffer_format_string. + */ + _append_char(&fmt, 'B'); + _append_char(&fmt, '\0'); + info->ndim = 1; + info->shape = malloc(sizeof(Py_ssize_t) * 2); + if (info->shape == NULL) { + PyErr_NoMemory(); + goto fail; + } + info->strides = info->shape + info->ndim; + info->shape[0] = 8; + info->strides[0] = 1; + info->format = fmt.s; + return info; + } + else if (PyArray_IsScalar(obj, Generic)) { descr = PyArray_DescrFromScalar(obj); if (descr == NULL) { goto fail; @@ -493,6 +527,7 @@ _buffer_info_new(PyObject *obj) else { info->shape = malloc(sizeof(Py_ssize_t) * PyArray_NDIM(arr) * 2 + 1); if (info->shape == NULL) { + PyErr_NoMemory(); goto fail; } info->strides = info->shape + PyArray_NDIM(arr); @@ -796,8 +831,6 @@ gentype_getbuffer(PyObject *self, Py_buffer *view, int flags) /* Fill in information */ info = _buffer_get_info(self); if (info == NULL) { - PyErr_SetString(PyExc_BufferError, - "could not get scalar buffer information"); goto fail; } @@ -820,6 +853,9 @@ gentype_getbuffer(PyObject *self, Py_buffer *view, int flags) } #endif view->len = elsize; + if (PyArray_IsScalar(self, Datetime) || PyArray_IsScalar(self, Timedelta)) { + elsize = 1; /* descr->elsize,char is 8,'M', but we return 1,'B' */ + } view->itemsize = elsize; Py_DECREF(descr); diff --git a/numpy/core/src/multiarray/calculation.c b/numpy/core/src/multiarray/calculation.c index e47dd81b9..90ee2c5b2 100644 --- a/numpy/core/src/multiarray/calculation.c +++ b/numpy/core/src/multiarray/calculation.c @@ -5,6 +5,7 @@ #define NPY_NO_DEPRECATED_API NPY_API_VERSION #define _MULTIARRAYMODULE #include "numpy/arrayobject.h" +#include "lowlevel_strided_loops.h" #include "npy_config.h" @@ -1102,7 +1103,18 @@ PyArray_Clip(PyArrayObject *self, PyObject *min, PyObject *max, PyArrayObject *o if (out == newin) { outgood = 1; } - if (!outgood && PyArray_ISONESEGMENT(out) && + + + /* make sure the shape of the output array is the same */ + if (!PyArray_SAMESHAPE(newin, out)) { + PyErr_SetString(PyExc_ValueError, "clip: Output array must have the" + "same shape as the input."); + goto fail; + } + + if (!outgood && PyArray_EQUIVALENTLY_ITERABLE( + self, out, PyArray_TRIVIALLY_ITERABLE_OP_READ, + PyArray_TRIVIALLY_ITERABLE_OP_NOREAD) && PyArray_CHKFLAGS(out, NPY_ARRAY_ALIGNED) && PyArray_ISNOTSWAPPED(out) && PyArray_EquivTypes(PyArray_DESCR(out), indescr)) { @@ -1111,15 +1123,19 @@ PyArray_Clip(PyArrayObject *self, PyObject *min, PyObject *max, PyArrayObject *o /* * Do we still not have a suitable output array? - * Create one, now + * Create one, now. No matter why the array is not suitable a copy has + * to be made. This may be just to avoid memory overlap though. */ if (!outgood) { int oflags; - if (PyArray_ISFORTRAN(out)) + if (PyArray_ISFORTRAN(self)) { oflags = NPY_ARRAY_FARRAY; - else + } + else { oflags = NPY_ARRAY_CARRAY; - oflags |= NPY_ARRAY_WRITEBACKIFCOPY | NPY_ARRAY_FORCECAST; + } + oflags |= (NPY_ARRAY_WRITEBACKIFCOPY | NPY_ARRAY_FORCECAST | + NPY_ARRAY_ENSURECOPY); Py_INCREF(indescr); newout = (PyArrayObject*)PyArray_FromArray(out, indescr, oflags); if (newout == NULL) { @@ -1131,13 +1147,6 @@ PyArray_Clip(PyArrayObject *self, PyObject *min, PyObject *max, PyArrayObject *o Py_INCREF(newout); } - /* make sure the shape of the output array is the same */ - if (!PyArray_SAMESHAPE(newin, newout)) { - PyErr_SetString(PyExc_ValueError, "clip: Output array must have the" - "same shape as the input."); - goto fail; - } - /* Now we can call the fast-clip function */ min_data = max_data = NULL; if (mina != NULL) { diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c index 938850997..f1b8a0209 100644 --- a/numpy/core/src/multiarray/ctors.c +++ b/numpy/core/src/multiarray/ctors.c @@ -92,6 +92,7 @@ swab_separator(const char *sep) s = start = malloc(strlen(sep)+3); if (s == NULL) { + PyErr_NoMemory(); return NULL; } /* add space to front if there isn't one */ @@ -1390,10 +1391,12 @@ _array_from_buffer_3118(PyObject *memoryview) if (!is_ctypes) { /* This object has no excuse for a broken PEP3118 buffer */ - PyErr_SetString( + PyErr_Format( PyExc_RuntimeError, - "Item size computed from the PEP 3118 buffer format " - "string does not match the actual item size."); + "Item size %zd for PEP 3118 buffer format " + "string %s does not match the dtype %c item size %d.", + view->itemsize, view->format, descr->type, + descr->elsize); Py_DECREF(descr); return NULL; } diff --git a/numpy/core/src/multiarray/descriptor.c b/numpy/core/src/multiarray/descriptor.c index a0dc98f0e..1d44cf8be 100644 --- a/numpy/core/src/multiarray/descriptor.c +++ b/numpy/core/src/multiarray/descriptor.c @@ -2401,7 +2401,7 @@ arraydescr_reduce(PyArray_Descr *self, PyObject *NPY_UNUSED(args)) if (ret == NULL) { return NULL; } - mod = PyImport_ImportModule("numpy.core.multiarray"); + mod = PyImport_ImportModule("numpy.core._multiarray_umath"); if (mod == NULL) { Py_DECREF(ret); return NULL; diff --git a/numpy/core/src/multiarray/dragon4.c b/numpy/core/src/multiarray/dragon4.c index abbf05220..14dfa71c2 100644 --- a/numpy/core/src/multiarray/dragon4.c +++ b/numpy/core/src/multiarray/dragon4.c @@ -114,7 +114,7 @@ LogBase2_64(npy_uint64 val) return LogBase2_32((npy_uint32)val); } -#if defined(HAVE_LDOUBLE_IEEE_QUAD_LE) +#if defined(HAVE_LDOUBLE_IEEE_QUAD_LE) || defined(HAVE_LDOUBLE_IEEE_QUAD_BE) static npy_uint32 LogBase2_128(npy_uint64 hi, npy_uint64 lo) { @@ -217,7 +217,8 @@ BigInt_Set_uint64(BigInt *i, npy_uint64 val) #if (defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE) || \ defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE) || \ - defined(HAVE_LDOUBLE_IEEE_QUAD_LE)) + defined(HAVE_LDOUBLE_IEEE_QUAD_LE) || \ + defined(HAVE_LDOUBLE_IEEE_QUAD_BE)) static void BigInt_Set_2x_uint64(BigInt *i, npy_uint64 hi, npy_uint64 lo) { @@ -2845,7 +2846,7 @@ Dragon4_PrintFloat_IEEE_binary128_be( #if (defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE) || \ defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE)) /* - * IBM extended precision 128-bit floating-point format, aka IBM double-dobule + * IBM extended precision 128-bit floating-point format, aka IBM double-double * * IBM's double-double type is a pair of IEEE binary64 values, which you add * together to get a total value. The exponents are arranged so that the lower @@ -2882,12 +2883,15 @@ Dragon4_PrintFloat_IEEE_binary128_be( */ static npy_uint32 Dragon4_PrintFloat_IBM_double_double( - Dragon4_Scratch *scratch, FloatVal128 val128, Dragon4_Options *opt) + Dragon4_Scratch *scratch, npy_float128 *value, Dragon4_Options *opt) { char *buffer = scratch->repr; npy_uint32 bufferSize = sizeof(scratch->repr); BigInt *bigints = scratch->bigints; + FloatVal128 val128; + FloatUnion128 buf128; + npy_uint32 floatExponent1, floatExponent2; npy_uint64 floatMantissa1, floatMantissa2; npy_uint32 floatSign1, floatSign2; @@ -2908,6 +2912,12 @@ Dragon4_PrintFloat_IBM_double_double( return 0; } + /* The high part always comes before the low part, regardless of the + * endianness of the system. */ + buf128.floatingPoint = *value; + val128.hi = buf128.integer.a; + val128.lo = buf128.integer.b; + /* deconstruct the floating point values */ floatMantissa1 = val128.hi & bitmask_u64(52); floatExponent1 = (val128.hi >> 52) & bitmask_u32(11); @@ -3052,39 +3062,6 @@ Dragon4_PrintFloat_IBM_double_double( signbit, mantissaBit, hasUnequalMargins, opt); } -#if defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE) -static npy_uint32 -Dragon4_PrintFloat_IBM_double_double_le( - Dragon4_Scratch *scratch, npy_float128 *value, Dragon4_Options *opt) -{ - FloatVal128 val128; - FloatUnion128 buf128; - - buf128.floatingPoint = *value; - val128.lo = buf128.integer.a; - val128.hi = buf128.integer.b; - - return Dragon4_PrintFloat_IBM_double_double(scratch, val128, opt); -} -#endif /* HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE */ - -#if defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE) -static npy_uint32 -Dragon4_PrintFloat_IBM_double_double_be( - Dragon4_Scratch *scratch, npy_float128 *value, Dragon4_Options *opt) -{ - FloatVal128 val128; - FloatUnion128 buf128; - - buf128.floatingPoint = *value; - val128.hi = buf128.integer.a; - val128.lo = buf128.integer.b; - - return Dragon4_PrintFloat_IBM_double_double(scratch, val128, opt); -} - -#endif /* HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE */ - #endif /* HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE | HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE */ #endif /* NPY_FLOAT128 */ diff --git a/numpy/core/src/multiarray/dragon4.h b/numpy/core/src/multiarray/dragon4.h index 383a0949d..2b8b4cef4 100644 --- a/numpy/core/src/multiarray/dragon4.h +++ b/numpy/core/src/multiarray/dragon4.h @@ -75,10 +75,9 @@ #define NPY_LONGDOUBLE_BINFMT_NAME Intel_extended128 #elif defined(HAVE_LDOUBLE_MOTOROLA_EXTENDED_12_BYTES_BE) #define NPY_LONGDOUBLE_BINFMT_NAME Motorola_extended96 -#elif defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE) - #define NPY_LONGDOUBLE_BINFMT_NAME IBM_double_double_le -#elif defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE) - #define NPY_LONGDOUBLE_BINFMT_NAME IBM_double_double_be +#elif (defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_LE) || \ + defined(HAVE_LDOUBLE_IBM_DOUBLE_DOUBLE_BE)) + #define NPY_LONGDOUBLE_BINFMT_NAME IBM_double_double #else #error No long double representation defined #endif diff --git a/numpy/core/src/multiarray/mapping.c b/numpy/core/src/multiarray/mapping.c index f338226c2..2fdb3ebf6 100644 --- a/numpy/core/src/multiarray/mapping.c +++ b/numpy/core/src/multiarray/mapping.c @@ -2915,20 +2915,20 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type, Py_INCREF(extra_op_dtype); mit->extra_op_dtype = extra_op_dtype; - /* Create an iterator, just to broadcast the arrays?! */ - tmp_iter = NpyIter_MultiNew(mit->numiter, index_arrays, - NPY_ITER_ZEROSIZE_OK | - NPY_ITER_REFS_OK | - NPY_ITER_MULTI_INDEX | - NPY_ITER_DONT_NEGATE_STRIDES, - NPY_KEEPORDER, - NPY_UNSAFE_CASTING, - tmp_op_flags, NULL); - if (tmp_iter == NULL) { - goto fail; - } - if (PyArray_SIZE(subspace) == 1) { + /* Create an iterator, just to broadcast the arrays?! */ + tmp_iter = NpyIter_MultiNew(mit->numiter, index_arrays, + NPY_ITER_ZEROSIZE_OK | + NPY_ITER_REFS_OK | + NPY_ITER_MULTI_INDEX | + NPY_ITER_DONT_NEGATE_STRIDES, + NPY_KEEPORDER, + NPY_UNSAFE_CASTING, + tmp_op_flags, NULL); + if (tmp_iter == NULL) { + goto fail; + } + /* * nditer allows itemsize with npy_intp type, so it works * here, but it would *not* work directly, since elsize @@ -2941,6 +2941,7 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type, "internal error: failed to find output array strides"); goto fail; } + NpyIter_Deallocate(tmp_iter); } else { /* Just use C-order strides (TODO: allow also F-order) */ @@ -2950,7 +2951,6 @@ PyArray_MapIterNew(npy_index_info *indices , int index_num, int index_type, stride *= mit->dimensions[i]; } } - NpyIter_Deallocate(tmp_iter); /* shape is set, and strides is set up to mit->nd, set rest */ PyArray_CreateSortedStridePerm(PyArray_NDIM(subspace), diff --git a/numpy/core/src/multiarray/methods.c b/numpy/core/src/multiarray/methods.c index 2e836d1d0..3d2cce5e1 100644 --- a/numpy/core/src/multiarray/methods.c +++ b/numpy/core/src/multiarray/methods.c @@ -1566,7 +1566,7 @@ array_reduce(PyArrayObject *self, PyObject *NPY_UNUSED(args)) if (ret == NULL) { return NULL; } - mod = PyImport_ImportModule("numpy.core.multiarray"); + mod = PyImport_ImportModule("numpy.core._multiarray_umath"); if (mod == NULL) { Py_DECREF(ret); return NULL; diff --git a/numpy/core/src/multiarray/multiarraymodule.c b/numpy/core/src/multiarray/multiarraymodule.c index 6e57f1d6d..8f782cff6 100644 --- a/numpy/core/src/multiarray/multiarraymodule.c +++ b/numpy/core/src/multiarray/multiarraymodule.c @@ -19,6 +19,7 @@ #include "structmember.h" #define NPY_NO_DEPRECATED_API NPY_API_VERSION +#define _UMATHMODULE #define _MULTIARRAYMODULE #include <numpy/npy_common.h> #include "numpy/arrayobject.h" @@ -54,7 +55,6 @@ NPY_NO_EXPORT int NPY_NUMUSERTYPES = 0; #include "ctors.h" #include "array_assign.h" #include "common.h" -#include "ufunc_override.h" #include "multiarraymodule.h" #include "cblasfuncs.h" #include "vdot.h" @@ -67,6 +67,17 @@ NPY_NO_EXPORT int NPY_NUMUSERTYPES = 0; #include "get_attr_string.h" /* + ***************************************************************************** + ** INCLUDE GENERATED CODE ** + ***************************************************************************** + */ +#include "funcs.inc" +#include "loops.h" +#include "umathmodule.h" + +NPY_NO_EXPORT int initscalarmath(PyObject *); + +/* * global variable to determine if legacy printing is enabled, accessible from * C. For simplicity the mode is encoded as an integer where '0' means no * legacy mode, and '113' means 1.13 legacy mode. We can upgrade this if we @@ -2020,7 +2031,7 @@ array_fromstring(PyObject *NPY_UNUSED(ignored), PyObject *args, PyObject *keywds if (DEPRECATE( "The binary mode of fromstring is deprecated, as it behaves " "surprisingly on unicode inputs. Use frombuffer instead") < 0) { - Py_DECREF(descr); + Py_XDECREF(descr); return NULL; } } @@ -4365,6 +4376,18 @@ static struct PyMethodDef array_module_methods[] = { METH_VARARGS | METH_KEYWORDS, NULL}, {"set_legacy_print_mode", (PyCFunction)set_legacy_print_mode, METH_VARARGS, NULL}, + /* from umath */ + {"frompyfunc", + (PyCFunction) ufunc_frompyfunc, + METH_VARARGS | METH_KEYWORDS, NULL}, + {"seterrobj", + (PyCFunction) ufunc_seterr, + METH_VARARGS, NULL}, + {"geterrobj", + (PyCFunction) ufunc_geterr, + METH_VARARGS, NULL}, + {"_add_newdoc_ufunc", (PyCFunction)add_newdoc_ufunc, + METH_VARARGS, NULL}, {NULL, NULL, 0, NULL} /* sentinel */ }; @@ -4382,9 +4405,6 @@ static struct PyMethodDef array_module_methods[] = { static int setup_scalartypes(PyObject *NPY_UNUSED(dict)) { - initialize_casting_tables(); - initialize_numeric_types(); - if (PyType_Ready(&PyBool_Type) < 0) { return -1; } @@ -4624,7 +4644,7 @@ intern_strings(void) #if defined(NPY_PY3K) static struct PyModuleDef moduledef = { PyModuleDef_HEAD_INIT, - "multiarray", + "_multiarray_umath", NULL, -1, array_module_methods, @@ -4638,10 +4658,10 @@ static struct PyModuleDef moduledef = { /* Initialization function for the module */ #if defined(NPY_PY3K) #define RETVAL(x) x -PyMODINIT_FUNC PyInit_multiarray(void) { +PyMODINIT_FUNC PyInit__multiarray_umath(void) { #else #define RETVAL(x) -PyMODINIT_FUNC initmultiarray(void) { +PyMODINIT_FUNC init_multiarray_umath(void) { #endif PyObject *m, *d, *s; PyObject *c_api; @@ -4650,7 +4670,7 @@ PyMODINIT_FUNC initmultiarray(void) { #if defined(NPY_PY3K) m = PyModule_Create(&moduledef); #else - m = Py_InitModule("multiarray", array_module_methods); + m = Py_InitModule("_multiarray_umath", array_module_methods); #endif if (!m) { goto err; @@ -4684,6 +4704,17 @@ PyMODINIT_FUNC initmultiarray(void) { * static structure slots with functions from the Python C_API. */ PyArray_Type.tp_hash = PyObject_HashNotImplemented; + + /* Load the ufunc operators into the array module's namespace */ + if (InitOperators(d) < 0) { + goto err; + } + + initialize_casting_tables(); + initialize_numeric_types(); + if(initscalarmath(m) < 0) + goto err; + if (PyType_Ready(&PyArray_Type) < 0) { goto err; } @@ -4730,6 +4761,16 @@ PyMODINIT_FUNC initmultiarray(void) { PyDict_SetItemString(d, "_ARRAY_API", c_api); Py_DECREF(c_api); + c_api = NpyCapsule_FromVoidPtr((void *)PyUFunc_API, NULL); + if (c_api == NULL) { + goto err; + } + PyDict_SetItemString(d, "_UFUNC_API", c_api); + Py_DECREF(c_api); + if (PyErr_Occurred()) { + goto err; + } + /* * PyExc_Exception should catch all the standard errors that are * now raised instead of the string exception "multiarray.error" @@ -4806,7 +4847,9 @@ PyMODINIT_FUNC initmultiarray(void) { if (set_typeinfo(d) != 0) { goto err; } - + if (initumath(m) != 0) { + goto err; + } return RETVAL(m); err: diff --git a/numpy/core/src/multiarray/scalartypes.c.src b/numpy/core/src/multiarray/scalartypes.c.src index a32aa47ab..fdd4d7878 100644 --- a/numpy/core/src/multiarray/scalartypes.c.src +++ b/numpy/core/src/multiarray/scalartypes.c.src @@ -538,19 +538,22 @@ _void_to_hex(const char* argbuf, const Py_ssize_t arglen, } static PyObject * +_void_scalar_repr(PyObject *obj) { + static PyObject *reprfunc = NULL; + npy_cache_import("numpy.core.arrayprint", + "_void_scalar_repr", &reprfunc); + if (reprfunc == NULL) { + return NULL; + } + return PyObject_CallFunction(reprfunc, "O", obj); +} + +static PyObject * voidtype_repr(PyObject *self) { PyVoidScalarObject *s = (PyVoidScalarObject*) self; if (PyDataType_HASFIELDS(s->descr)) { - static PyObject *reprfunc = NULL; - - npy_cache_import("numpy.core.arrayprint", - "_void_scalar_repr", &reprfunc); - if (reprfunc == NULL) { - return NULL; - } - - return PyObject_CallFunction(reprfunc, "O", self); + return _void_scalar_repr(self); } return _void_to_hex(s->obval, s->descr->elsize, "void(b'", "\\x", "')"); } @@ -560,15 +563,7 @@ voidtype_str(PyObject *self) { PyVoidScalarObject *s = (PyVoidScalarObject*) self; if (PyDataType_HASFIELDS(s->descr)) { - static PyObject *reprfunc = NULL; - - npy_cache_import("numpy.core.arrayprint", - "_void_scalar_repr", &reprfunc); - if (reprfunc == NULL) { - return NULL; - } - - return PyObject_CallFunction(reprfunc, "O", self); + return _void_scalar_repr(self); } return _void_to_hex(s->obval, s->descr->elsize, "b'", "\\x", "'"); } @@ -1875,7 +1870,7 @@ gentype_reduce(PyObject *self, PyObject *NPY_UNUSED(args)) } #endif - mod = PyImport_ImportModule("numpy.core.multiarray"); + mod = PyImport_ImportModule("numpy.core._multiarray_umath"); if (mod == NULL) { return NULL; } diff --git a/numpy/core/src/umath/cpuid.c b/numpy/core/src/umath/cpuid.c index 912d51eeb..6744ceb05 100644 --- a/numpy/core/src/umath/cpuid.c +++ b/numpy/core/src/umath/cpuid.c @@ -1,13 +1,11 @@ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include <Python.h> #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "cpuid.h" #define XCR_XFEATURE_ENABLED_MASK 0x0 diff --git a/numpy/core/src/umath/extobj.c b/numpy/core/src/umath/extobj.c index 188054e22..aea1815e8 100644 --- a/numpy/core/src/umath/extobj.c +++ b/numpy/core/src/umath/extobj.c @@ -1,13 +1,11 @@ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include <Python.h> #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "npy_pycompat.h" #include "extobj.h" diff --git a/numpy/core/src/umath/loops.c.src b/numpy/core/src/umath/loops.c.src index e988792a2..66b69f555 100644 --- a/numpy/core/src/umath/loops.c.src +++ b/numpy/core/src/umath/loops.c.src @@ -1,14 +1,12 @@ /* -*- c -*- */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include "Python.h" #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "numpy/npy_common.h" #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" @@ -1874,9 +1872,13 @@ NPY_NO_EXPORT void } else { BINARY_LOOP { - const @type@ in1 = *(@type@ *)ip1; + @type@ in1 = *(@type@ *)ip1; const @type@ in2 = *(@type@ *)ip2; - *((@type@ *)op1) = (in1 @OP@ in2 || npy_isnan(in1)) ? in1 : in2; + in1 = (in1 @OP@ in2 || npy_isnan(in1)) ? in1 : in2; + if (npy_isnan(in1)) { + npy_set_floatstatus_invalid(); + } + *((@type@ *)op1) = in1; } } } diff --git a/numpy/core/src/umath/reduction.c b/numpy/core/src/umath/reduction.c index 8136d7b3f..6d04ce372 100644 --- a/numpy/core/src/umath/reduction.c +++ b/numpy/core/src/umath/reduction.c @@ -7,15 +7,13 @@ * See LICENSE.txt for the license. */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #define PY_SSIZE_T_CLEAN #include <Python.h> #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include <numpy/arrayobject.h> #include "npy_config.h" diff --git a/numpy/core/src/umath/scalarmath.c.src b/numpy/core/src/umath/scalarmath.c.src index 3e29c4b4e..e98d9f865 100644 --- a/numpy/core/src/umath/scalarmath.c.src +++ b/numpy/core/src/umath/scalarmath.c.src @@ -7,13 +7,11 @@ */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include "Python.h" #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" #include "numpy/arrayscalars.h" diff --git a/numpy/core/src/umath/ufunc_object.c b/numpy/core/src/umath/ufunc_object.c index 20c448d8b..459b0a594 100644 --- a/numpy/core/src/umath/ufunc_object.c +++ b/numpy/core/src/umath/ufunc_object.c @@ -24,15 +24,13 @@ * */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include "Python.h" #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "npy_pycompat.h" #include "numpy/arrayobject.h" diff --git a/numpy/core/src/umath/ufunc_object.h b/numpy/core/src/umath/ufunc_object.h index 5438270f1..f5de9f9b7 100644 --- a/numpy/core/src/umath/ufunc_object.h +++ b/numpy/core/src/umath/ufunc_object.h @@ -1,6 +1,8 @@ #ifndef _NPY_UMATH_UFUNC_OBJECT_H_ #define _NPY_UMATH_UFUNC_OBJECT_H_ +#include <numpy/ufuncobject.h> + NPY_NO_EXPORT PyObject * ufunc_geterr(PyObject *NPY_UNUSED(dummy), PyObject *args); diff --git a/numpy/core/src/umath/ufunc_type_resolution.c b/numpy/core/src/umath/ufunc_type_resolution.c index 1766ba564..807b03512 100644 --- a/numpy/core/src/umath/ufunc_type_resolution.c +++ b/numpy/core/src/umath/ufunc_type_resolution.c @@ -9,14 +9,12 @@ * See LICENSE.txt for the license. */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include "Python.h" #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API -#define NO_IMPORT_ARRAY - #include "npy_pycompat.h" #include "numpy/ufuncobject.h" diff --git a/numpy/core/src/umath/umathmodule.c b/numpy/core/src/umath/umathmodule.c index 9291a5138..20bd2b0a8 100644 --- a/numpy/core/src/umath/umathmodule.c +++ b/numpy/core/src/umath/umathmodule.c @@ -16,12 +16,12 @@ * __ufunc_api.c */ #define _UMATHMODULE +#define _MULTIARRAYMODULE #define NPY_NO_DEPRECATED_API NPY_API_VERSION #include "Python.h" #include "npy_config.h" -#define PY_ARRAY_UNIQUE_SYMBOL _npy_umathmodule_ARRAY_API #include "numpy/arrayobject.h" #include "numpy/ufuncobject.h" @@ -30,20 +30,6 @@ #include "numpy/npy_math.h" -/* - ***************************************************************************** - ** INCLUDE GENERATED CODE ** - ***************************************************************************** - */ -#include "funcs.inc" -#include "loops.h" -#include "ufunc_object.h" -#include "ufunc_type_resolution.h" -#include "__umath_generated.c" -#include "__ufunc_api.c" - -NPY_NO_EXPORT int initscalarmath(PyObject *); - static PyUFuncGenericFunction pyfunc_functions[] = {PyUFunc_On_Om}; static int @@ -82,7 +68,7 @@ object_ufunc_loop_selector(PyUFuncObject *ufunc, return 0; } -static PyObject * +PyObject * ufunc_frompyfunc(PyObject *NPY_UNUSED(dummy), PyObject *args, PyObject *NPY_UNUSED(kwds)) { /* Keywords are ignored for now */ @@ -179,7 +165,7 @@ ufunc_frompyfunc(PyObject *NPY_UNUSED(dummy), PyObject *args, PyObject *NPY_UNUS } /* docstring in numpy.add_newdocs.py */ -static PyObject * +PyObject * add_newdoc_ufunc(PyObject *NPY_UNUSED(dummy), PyObject *args) { PyUFuncObject *ufunc; @@ -270,97 +256,24 @@ intern_strings(void) npy_um_str_array_wrap && npy_um_str_array_finalize && npy_um_str_ufunc; } -/* Setup the umath module */ -/* Remove for time being, it is declared in __ufunc_api.h */ -/*static PyTypeObject PyUFunc_Type;*/ - -static struct PyMethodDef methods[] = { - {"frompyfunc", - (PyCFunction) ufunc_frompyfunc, - METH_VARARGS | METH_KEYWORDS, NULL}, - {"seterrobj", - (PyCFunction) ufunc_seterr, - METH_VARARGS, NULL}, - {"geterrobj", - (PyCFunction) ufunc_geterr, - METH_VARARGS, NULL}, - {"_add_newdoc_ufunc", (PyCFunction)add_newdoc_ufunc, - METH_VARARGS, NULL}, - {NULL, NULL, 0, NULL} /* sentinel */ -}; - - -#if defined(NPY_PY3K) -static struct PyModuleDef moduledef = { - PyModuleDef_HEAD_INIT, - "umath", - NULL, - -1, - methods, - NULL, - NULL, - NULL, - NULL -}; -#endif - -#include <stdio.h> +/* Setup the umath part of the module */ -#if defined(NPY_PY3K) -#define RETVAL(x) x -PyMODINIT_FUNC PyInit_umath(void) -#else -#define RETVAL(x) -PyMODINIT_FUNC initumath(void) -#endif +int initumath(PyObject *m) { - PyObject *m, *d, *s, *s2, *c_api; + PyObject *d, *s, *s2; int UFUNC_FLOATING_POINT_SUPPORT = 1; #ifdef NO_UFUNC_FLOATING_POINT_SUPPORT UFUNC_FLOATING_POINT_SUPPORT = 0; #endif - /* Create the module and add the functions */ -#if defined(NPY_PY3K) - m = PyModule_Create(&moduledef); -#else - m = Py_InitModule("umath", methods); -#endif - if (!m) { - goto err; - } - - /* Import the array */ - if (_import_array() < 0) { - if (!PyErr_Occurred()) { - PyErr_SetString(PyExc_ImportError, - "umath failed: Could not import array core."); - } - goto err; - } /* Initialize the types */ if (PyType_Ready(&PyUFunc_Type) < 0) - goto err; + return -1; /* Add some symbolic constants to the module */ d = PyModule_GetDict(m); - c_api = NpyCapsule_FromVoidPtr((void *)PyUFunc_API, NULL); - if (PyErr_Occurred()) { - goto err; - } - PyDict_SetItemString(d, "_UFUNC_API", c_api); - Py_DECREF(c_api); - if (PyErr_Occurred()) { - goto err; - } - - /* Load the ufunc operators into the array module's namespace */ - if (InitOperators(d) < 0) { - goto err; - } - PyDict_SetItemString(d, "pi", s = PyFloat_FromDouble(NPY_PI)); Py_DECREF(s); PyDict_SetItemString(d, "e", s = PyFloat_FromDouble(NPY_E)); @@ -417,19 +330,11 @@ PyMODINIT_FUNC initumath(void) PyDict_SetItemString(d, "conj", s); PyDict_SetItemString(d, "mod", s2); - initscalarmath(m); - if (!intern_strings()) { - goto err; - } - - return RETVAL(m); - - err: - /* Check for errors */ - if (!PyErr_Occurred()) { PyErr_SetString(PyExc_RuntimeError, - "cannot load umath module."); + "cannot intern umath strings while initializing _multiarray_umath."); + return -1; } - return RETVAL(NULL); + + return 0; } diff --git a/numpy/core/tests/test_arrayprint.py b/numpy/core/tests/test_arrayprint.py index 6214e325c..6522c6e8a 100644 --- a/numpy/core/tests/test_arrayprint.py +++ b/numpy/core/tests/test_arrayprint.py @@ -8,6 +8,7 @@ import pytest import numpy as np from numpy.testing import ( assert_, assert_equal, assert_raises, assert_warns, HAS_REFCOUNT, + assert_raises_regex, ) import textwrap @@ -210,6 +211,15 @@ class TestArray2String(object): assert_(np.array2string(a, max_line_width=4, legacy='1.13') == '[0 1\n 2]') assert_(np.array2string(a, max_line_width=4) == '[0\n 1\n 2]') + def test_unexpected_kwarg(self): + # ensure than an appropriate TypeError + # is raised when array2string receives + # an unexpected kwarg + + with assert_raises_regex(TypeError, 'nonsense'): + np.array2string(np.array([1, 2, 3]), + nonsense=None) + def test_format_function(self): """Test custom format function for each element in array.""" def _format_function(x): diff --git a/numpy/core/tests/test_datetime.py b/numpy/core/tests/test_datetime.py index 942554cae..8e058d5fb 100644 --- a/numpy/core/tests/test_datetime.py +++ b/numpy/core/tests/test_datetime.py @@ -620,6 +620,10 @@ class TestDateTime(object): assert_equal(pickle.loads(pickle.dumps(dt)), dt) dt = np.dtype('M8[W]') assert_equal(pickle.loads(pickle.dumps(dt)), dt) + scalar = np.datetime64('2016-01-01T00:00:00.000000000') + assert_equal(pickle.loads(pickle.dumps(scalar)), scalar) + delta = scalar - np.datetime64('2015-01-01T00:00:00.000000000') + assert_equal(pickle.loads(pickle.dumps(delta)), delta) # Check that loading pickles from 1.6 works pkl = b"cnumpy\ndtype\np0\n(S'M8'\np1\nI0\nI1\ntp2\nRp3\n" + \ @@ -1698,7 +1702,6 @@ class TestDateTime(object): assert_equal(np.busday_offset(np.datetime64('NaT'), 1, roll='preceding'), np.datetime64('NaT')) - def test_datetime_busdaycalendar(self): # Check that it removes NaT, duplicates, and weekends # and sorts the result. diff --git a/numpy/core/tests/test_deprecations.py b/numpy/core/tests/test_deprecations.py index 5d66d963f..10ef16800 100644 --- a/numpy/core/tests/test_deprecations.py +++ b/numpy/core/tests/test_deprecations.py @@ -518,3 +518,8 @@ class TestPositiveOnNonNumerical(_DeprecationTestCase): # 2018-06-28, 1.16.0 def test_positive_on_non_number(self): self.assert_deprecated(operator.pos, args=(np.array('foo'),)) + +class TestFromstring(_DeprecationTestCase): + # 2017-10-19, 1.14 + def test_fromstring(self): + self.assert_deprecated(np.fromstring, args=('\x00'*80,)) diff --git a/numpy/core/tests/test_einsum.py b/numpy/core/tests/test_einsum.py index 8ce374a75..6b5b9c06e 100644 --- a/numpy/core/tests/test_einsum.py +++ b/numpy/core/tests/test_einsum.py @@ -965,7 +965,6 @@ class TestEinsumPath(object): path, path_str = np.einsum_path(*edge_test4, optimize='optimal') self.assert_path_equal(path, ['einsum_path', (0, 1), (0, 1, 2, 3, 4, 5)]) - def test_path_type_input(self): # Test explicit path handeling path_test = self.build_operands('dcc,fce,ea,dbf->ab') diff --git a/numpy/core/tests/test_indexing.py b/numpy/core/tests/test_indexing.py index 276cd9f93..1934d542a 100644 --- a/numpy/core/tests/test_indexing.py +++ b/numpy/core/tests/test_indexing.py @@ -194,7 +194,6 @@ class TestIndexing(object): assert_raises(IndexError, arr.__getitem__, (slice(None), index)) - def test_boolean_indexing_onedim(self): # Indexing a 2-dimensional array with # boolean array of length one diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py index 1511f5b6b..1c59abaa7 100644 --- a/numpy/core/tests/test_multiarray.py +++ b/numpy/core/tests/test_multiarray.py @@ -108,7 +108,6 @@ class TestFlags(object): assert_equal(self.a.flags['X'], False) assert_equal(self.a.flags['WRITEBACKIFCOPY'], False) - def test_string_align(self): a = np.zeros(4, dtype=np.dtype('|S4')) assert_(a.flags.aligned) @@ -2729,7 +2728,6 @@ class TestMethods(object): # Order of axis argument doesn't matter: assert_equal(b.diagonal(0, 2, 1), [[0, 3], [4, 7]]) - def test_diagonal_view_notwriteable(self): # this test is only for 1.9, the diagonal view will be # writeable in 1.10. @@ -4386,7 +4384,6 @@ class TestIO(object): d.tofile(f) assert_equal(os.path.getsize(self.filename), d.nbytes * 2) - def test_io_open_buffered_fromfile(self): # gh-6632 self.x.tofile(self.filename) @@ -4748,55 +4745,72 @@ class TestRecord(object): # Error raised when multiple fields have the same name assert_raises(ValueError, test_assign) - if sys.version_info[0] >= 3: - def test_bytes_fields(self): - # Bytes are not allowed in field names and not recognized in titles - # on Py3 - assert_raises(TypeError, np.dtype, [(b'a', int)]) - assert_raises(TypeError, np.dtype, [(('b', b'a'), int)]) - - dt = np.dtype([((b'a', 'b'), int)]) - assert_raises(TypeError, dt.__getitem__, b'a') - - x = np.array([(1,), (2,), (3,)], dtype=dt) - assert_raises(IndexError, x.__getitem__, b'a') - - y = x[0] - assert_raises(IndexError, y.__getitem__, b'a') - - def test_multiple_field_name_unicode(self): - def test_assign_unicode(): - dt = np.dtype([("\u20B9", "f8"), - ("B", "f8"), - ("\u20B9", "f8")]) - - # Error raised when multiple fields have the same name(unicode included) - assert_raises(ValueError, test_assign_unicode) - - else: - def test_unicode_field_titles(self): - # Unicode field titles are added to field dict on Py2 - title = u'b' - dt = np.dtype([((title, 'a'), int)]) - dt[title] - dt['a'] - x = np.array([(1,), (2,), (3,)], dtype=dt) - x[title] - x['a'] - y = x[0] - y[title] - y['a'] - - def test_unicode_field_names(self): - # Unicode field names are converted to ascii on Python 2: - encodable_name = u'b' - assert_equal(np.dtype([(encodable_name, int)]).names[0], b'b') - assert_equal(np.dtype([(('a', encodable_name), int)]).names[0], b'b') - - # But raises UnicodeEncodeError if it can't be encoded: - nonencodable_name = u'\uc3bc' - assert_raises(UnicodeEncodeError, np.dtype, [(nonencodable_name, int)]) - assert_raises(UnicodeEncodeError, np.dtype, [(('a', nonencodable_name), int)]) + @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3") + def test_bytes_fields(self): + # Bytes are not allowed in field names and not recognized in titles + # on Py3 + assert_raises(TypeError, np.dtype, [(b'a', int)]) + assert_raises(TypeError, np.dtype, [(('b', b'a'), int)]) + + dt = np.dtype([((b'a', 'b'), int)]) + assert_raises(TypeError, dt.__getitem__, b'a') + + x = np.array([(1,), (2,), (3,)], dtype=dt) + assert_raises(IndexError, x.__getitem__, b'a') + + y = x[0] + assert_raises(IndexError, y.__getitem__, b'a') + + @pytest.mark.skipif(sys.version_info[0] < 3, reason="Not Python 3") + def test_multiple_field_name_unicode(self): + def test_assign_unicode(): + dt = np.dtype([("\u20B9", "f8"), + ("B", "f8"), + ("\u20B9", "f8")]) + + # Error raised when multiple fields have the same name(unicode included) + assert_raises(ValueError, test_assign_unicode) + + @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2") + def test_unicode_field_titles(self): + # Unicode field titles are added to field dict on Py2 + title = u'b' + dt = np.dtype([((title, 'a'), int)]) + dt[title] + dt['a'] + x = np.array([(1,), (2,), (3,)], dtype=dt) + x[title] + x['a'] + y = x[0] + y[title] + y['a'] + + @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Not Python 2") + def test_unicode_field_names(self): + # Unicode field names are converted to ascii on Python 2: + encodable_name = u'b' + assert_equal(np.dtype([(encodable_name, int)]).names[0], b'b') + assert_equal(np.dtype([(('a', encodable_name), int)]).names[0], b'b') + + # But raises UnicodeEncodeError if it can't be encoded: + nonencodable_name = u'\uc3bc' + assert_raises(UnicodeEncodeError, np.dtype, [(nonencodable_name, int)]) + assert_raises(UnicodeEncodeError, np.dtype, [(('a', nonencodable_name), int)]) + + def test_fromarrays_unicode(self): + # A single name string provided to fromarrays() is allowed to be unicode + # on both Python 2 and 3: + x = np.core.records.fromarrays([[0], [1]], names=u'a,b', formats=u'i4,i4') + assert_equal(x['a'][0], 0) + assert_equal(x['b'][0], 1) + + def test_unicode_order(self): + # Test that we can sort with order as a unicode field name in both Python 2 and + # 3: + name = u'b' + x = np.array([1, 3, 2], dtype=[(name, int)]) + x.sort(order=name) + assert_equal(x[u'b'], np.array([1, 2, 3])) def test_field_names(self): # Test unicode and 8-bit / byte strings can be used @@ -4909,7 +4923,6 @@ class TestRecord(object): assert_equal(collect_warnings(c[['f0', 'f2']].view, 'i8,i8'), [FutureWarning]) - def test_record_hash(self): a = np.array([(1, 2), (1, 2)], dtype='i1,i2') a.flags.writeable = False @@ -6470,6 +6483,14 @@ class TestNewBufferProtocol(object): # Issue #4015. self._check_roundtrip(0) + def test_invalid_buffer_format(self): + # datetime64 cannot be used fully in a buffer yet + # Should be fixed in the next Numpy major release + dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')]) + a = np.empty(3, dt) + assert_raises((ValueError, BufferError), memoryview, a) + assert_raises((ValueError, BufferError), memoryview, np.array((3), 'M8[D]')) + def test_export_simple_1d(self): x = np.array([1, 2, 3, 4, 5], dtype='i') y = memoryview(x) diff --git a/numpy/core/tests/test_nditer.py b/numpy/core/tests/test_nditer.py index 13bc6b34a..5e8165bc5 100644 --- a/numpy/core/tests/test_nditer.py +++ b/numpy/core/tests/test_nditer.py @@ -2358,7 +2358,6 @@ class TestIterNested(object): j.close() assert_equal(a, [[1, 2, 3], [4, 5, 6]]) - def test_dtype_buffered(self): # Test nested iteration with buffering to change dtype diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py index 53486dc51..e7181736f 100644 --- a/numpy/core/tests/test_numeric.py +++ b/numpy/core/tests/test_numeric.py @@ -1275,7 +1275,6 @@ class TestArrayComparisons(object): assert_equal(a == None, [False, False, False]) assert_equal(a != None, [True, True, True]) - def test_array_equiv(self): res = np.array_equiv(np.array([1, 2]), np.array([1, 2])) assert_(res) @@ -1530,7 +1529,7 @@ class TestClip(object): m = -0.5 M = 0.6 self.fastclip(a, m, M, a) - self.clip(a, m, M, ac) + self.clip(ac, m, M, ac) assert_array_strict_equal(a, ac) def test_noncontig_inplace(self): @@ -1543,7 +1542,7 @@ class TestClip(object): m = -0.5 M = 0.6 self.fastclip(a, m, M, a) - self.clip(a, m, M, ac) + self.clip(ac, m, M, ac) assert_array_equal(a, ac) def test_type_cast_01(self): @@ -1722,6 +1721,22 @@ class TestClip(object): self.clip(a, m, M, act) assert_array_strict_equal(ac, act) + def test_clip_with_out_transposed(self): + # Test that the out argument works when tranposed + a = np.arange(16).reshape(4, 4) + out = np.empty_like(a).T + a.clip(4, 10, out=out) + expected = self.clip(a, 4, 10) + assert_array_equal(out, expected) + + def test_clip_with_out_memory_overlap(self): + # Test that the out argument works when it has memory overlap + a = np.arange(16).reshape(4, 4) + ac = a.copy() + a[:-1].clip(4, 10, out=a[1:]) + expected = self.clip(ac[:-1], 4, 10) + assert_array_equal(a[1:], expected) + def test_clip_inplace_array(self): # Test native double input with array min/max a = self._generate_data(self.nr, self.nc) diff --git a/numpy/core/tests/test_regression.py b/numpy/core/tests/test_regression.py index f8e297736..c38625dac 100644 --- a/numpy/core/tests/test_regression.py +++ b/numpy/core/tests/test_regression.py @@ -1831,7 +1831,6 @@ class TestRegression(object): assert_equal(oct(a), oct(0)) assert_equal(hex(a), hex(0)) - def test_object_array_self_copy(self): # An object array being copied into itself DECREF'ed before INCREF'ing # causing segmentation faults (gh-3787) @@ -2371,6 +2370,13 @@ class TestRegression(object): del va assert_equal(x, b'\x00\x00\x00\x00') + def test_void_getitem(self): + # Test fix for gh-11668. + assert_(np.array([b'a'], 'V1').astype('O') == b'a') + assert_(np.array([b'ab'], 'V2').astype('O') == b'ab') + assert_(np.array([b'abc'], 'V3').astype('O') == b'abc') + assert_(np.array([b'abcd'], 'V4').astype('O') == b'abcd') + def test_structarray_title(self): # The following used to segfault on pypy, due to NPY_TITLE_KEY # not working properly and resulting to double-decref of the diff --git a/numpy/core/tests/test_scalarbuffer.py b/numpy/core/tests/test_scalarbuffer.py index 6d57a5014..cb6c521e1 100644 --- a/numpy/core/tests/test_scalarbuffer.py +++ b/numpy/core/tests/test_scalarbuffer.py @@ -5,7 +5,7 @@ import sys import numpy as np import pytest -from numpy.testing import assert_, assert_equal +from numpy.testing import assert_, assert_equal, assert_raises # PEP3118 format strings for native (standard alignment and byteorder) types scalars_and_codes = [ @@ -77,3 +77,28 @@ class TestScalarPEP3118(object): mv_a = memoryview(a) assert_equal(mv_x.itemsize, mv_a.itemsize) assert_equal(mv_x.format, mv_a.format) + + def test_datetime_memoryview(self): + # gh-11656 + # Values verified with v1.13.3, shape is not () as in test_scalar_dim + def as_dict(m): + return dict(strides=m.strides, shape=m.shape, itemsize=m.itemsize, + ndim=m.ndim, format=m.format) + + dt1 = np.datetime64('2016-01-01') + dt2 = np.datetime64('2017-01-01') + expected = {'strides': (1,), 'itemsize': 1, 'ndim': 1, + 'shape': (8,), 'format': 'B'} + v = memoryview(dt1) + res = as_dict(v) + assert_equal(res, expected) + + v = memoryview(dt2 - dt1) + res = as_dict(v) + assert_equal(res, expected) + + dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')]) + a = np.empty(1, dt) + # Fails to create a PEP 3118 valid buffer + assert_raises((ValueError, BufferError), memoryview, a[0]) + diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py index 7679a2b85..c15ce83f6 100644 --- a/numpy/core/tests/test_umath.py +++ b/numpy/core/tests/test_umath.py @@ -14,7 +14,7 @@ from numpy.testing import ( assert_, assert_equal, assert_raises, assert_raises_regex, assert_array_equal, assert_almost_equal, assert_array_almost_equal, assert_allclose, assert_no_warnings, suppress_warnings, - _gen_alignment_data, + _gen_alignment_data, assert_warns ) @@ -1173,7 +1173,6 @@ class TestBitwiseUFuncs(object): assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg) assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg) - def test_identity(self): assert_(np.bitwise_or.identity == 0, 'bitwise_or') assert_(np.bitwise_xor.identity == 0, 'bitwise_xor') @@ -1340,6 +1339,10 @@ class TestMinMax(object): assert_equal(np.min(r), np.nan) assert_equal(len(sup.log), n) + def test_minimize_warns(self): + # gh 11589 + assert_warns(RuntimeWarning, np.minimum, np.nan, 1) + class TestAbsoluteNegative(object): def test_abs_neg_blocked(self): diff --git a/numpy/core/umath.py b/numpy/core/umath.py new file mode 100644 index 000000000..efa213b1a --- /dev/null +++ b/numpy/core/umath.py @@ -0,0 +1,32 @@ +""" +Create the numpy.core.umath namespace for backward compatibility. In v1.16 +the multiarray and umath c-extension modules were merged into a single +_multiarray_umath extension module. So we replicate the old namespace +by importing from the extension module. +""" + +from . import _multiarray_umath +from numpy.core._multiarray_umath import * +from numpy.core._multiarray_umath import _add_newdoc_ufunc, _arg + +__all__ = ['ERR_CALL', 'ERR_DEFAULT', 'ERR_IGNORE', 'ERR_LOG', 'ERR_PRINT', + 'ERR_RAISE', 'ERR_WARN', 'FLOATING_POINT_SUPPORT', 'FPE_DIVIDEBYZERO', + 'FPE_INVALID', 'FPE_OVERFLOW', 'FPE_UNDERFLOW', 'NAN', 'NINF', 'NZERO', + 'PINF', 'PZERO', 'SHIFT_DIVIDEBYZERO', 'SHIFT_INVALID', 'SHIFT_OVERFLOW', + 'SHIFT_UNDERFLOW', 'UFUNC_BUFSIZE_DEFAULT', 'UFUNC_PYVALS_NAME', + '_add_newdoc_ufunc', '_arg', + 'absolute', 'add', 'arccos', 'arccosh', 'arcsin', 'arcsinh', 'arctan', + 'arctan2', 'arctanh', 'bitwise_and', 'bitwise_or', 'bitwise_xor', 'cbrt', + 'ceil', 'conj', 'conjugate', 'copysign', 'cos', 'cosh', 'deg2rad', + 'degrees', 'divide', 'divmod', 'e', 'equal', 'euler_gamma', 'exp', 'exp2', + 'expm1', 'fabs', 'floor', 'floor_divide', 'float_power', 'fmax', 'fmin', + 'fmod', 'frexp', 'frompyfunc', 'gcd', 'geterrobj', 'greater', + 'greater_equal', 'heaviside', 'hypot', 'invert', 'isfinite', 'isinf', + 'isnan', 'isnat', 'lcm', 'ldexp', 'left_shift', 'less', 'less_equal', + 'log', 'log10', 'log1p', 'log2', 'logaddexp', 'logaddexp2', 'logical_and', + 'logical_not', 'logical_or', 'logical_xor', 'maximum', 'minimum', 'mod', + 'modf', 'multiply', 'negative', 'nextafter', 'not_equal', 'pi', 'positive', + 'power', 'rad2deg', 'radians', 'reciprocal', 'remainder', 'right_shift', + 'rint', 'seterrobj', 'sign', 'signbit', 'sin', 'sinh', 'spacing', 'sqrt', + 'square', 'subtract', 'tan', 'tanh', 'true_divide', 'trunc'] + diff --git a/numpy/doc/broadcasting.py b/numpy/doc/broadcasting.py index 1dc4f60bf..6c3a4bc75 100644 --- a/numpy/doc/broadcasting.py +++ b/numpy/doc/broadcasting.py @@ -53,9 +53,10 @@ dimensions are compatible when 2) one of them is 1 If these conditions are not met, a -``ValueError: frames are not aligned`` exception is thrown, indicating that -the arrays have incompatible shapes. The size of the resulting array -is the maximum size along each dimension of the input arrays. +``ValueError: operands could not be broadcast together`` exception is +thrown, indicating that the arrays have incompatible shapes. The size of +the resulting array is the maximum size along each dimension of the input +arrays. Arrays do not need to have the same *number* of dimensions. For example, if you have a ``256x256x3`` array of RGB values, and you want to scale @@ -124,7 +125,7 @@ An example of broadcasting in practice:: (5,) >>> x + y - <type 'exceptions.ValueError'>: shape mismatch: objects cannot be broadcast to a single shape + ValueError: operands could not be broadcast together with shapes (4,) (5,) >>> xx.shape (4, 1) diff --git a/numpy/f2py/__main__.py b/numpy/f2py/__main__.py index cb8f261c1..6eff41099 100644 --- a/numpy/f2py/__main__.py +++ b/numpy/f2py/__main__.py @@ -1,27 +1,6 @@ # See http://cens.ioc.ee/projects/f2py2e/ from __future__ import division, print_function -import os -import sys -for mode in ["g3-numpy", "2e-numeric", "2e-numarray", "2e-numpy"]: - try: - i = sys.argv.index("--" + mode) - del sys.argv[i] - break - except ValueError: - pass -os.environ["NO_SCIPY_IMPORT"] = "f2py" -if mode == "g3-numpy": - sys.stderr.write("G3 f2py support is not implemented, yet.\\n") - sys.exit(1) -elif mode == "2e-numeric": - from f2py2e import main -elif mode == "2e-numarray": - sys.argv.append("-DNUMARRAY") - from f2py2e import main -elif mode == "2e-numpy": - from numpy.f2py import main -else: - sys.stderr.write("Unknown mode: " + repr(mode) + "\\n") - sys.exit(1) +from f2py2e import main + main() diff --git a/numpy/f2py/crackfortran.py b/numpy/f2py/crackfortran.py index 19ce8c145..99ff030e3 100755 --- a/numpy/f2py/crackfortran.py +++ b/numpy/f2py/crackfortran.py @@ -2403,7 +2403,7 @@ def _selected_real_kind_func(p, r=0, radix=0): if p < 16: return 8 machine = platform.machine().lower() - if machine.startswith('power') or machine.startswith('ppc64'): + if machine.startswith(('aarch64', 'power', 'ppc64', 's390x')): if p <= 20: return 16 else: diff --git a/numpy/f2py/f2py2e.py b/numpy/f2py/f2py2e.py index 254f99966..8750ed0b3 100755 --- a/numpy/f2py/f2py2e.py +++ b/numpy/f2py/f2py2e.py @@ -644,13 +644,25 @@ def main(): from numpy.distutils.system_info import show_all show_all() return + + # Probably outdated options that were not working before 1.16 + if '--g3-numpy' in sys.argv[1:]: + sys.stderr.write("G3 f2py support is not implemented, yet.\\n") + sys.exit(1) + elif '--2e-numeric' in sys.argv[1:]: + sys.argv.remove('--2e-numeric') + elif '--2e-numarray' in sys.argv[1:]: + # Note that this errors becaust the -DNUMARRAY argument is + # not recognized. Just here for back compatibility and the + # error message. + sys.argv.append("-DNUMARRAY") + sys.argv.remove('--2e-numarray') + elif '--2e-numpy' in sys.argv[1:]: + sys.argv.remove('--2e-numpy') + else: + pass + if '-c' in sys.argv[1:]: run_compile() else: run_main(sys.argv[1:]) - -# if __name__ == "__main__": -# main() - - -# EOF diff --git a/numpy/f2py/setup.py b/numpy/f2py/setup.py index 73cb3b8bf..e95b9584f 100644 --- a/numpy/f2py/setup.py +++ b/numpy/f2py/setup.py @@ -18,8 +18,6 @@ Pearu Peterson """ from __future__ import division, print_function -__version__ = "$Id: setup.py,v 1.32 2005/01/30 17:22:14 pearu Exp $" - import os import sys from distutils.dep_util import newer @@ -27,60 +25,22 @@ from numpy.distutils import log from numpy.distutils.core import setup from numpy.distutils.misc_util import Configuration -from __version__ import version - - -def _get_f2py_shebang(): - """ Return shebang line for f2py script - If we are building a binary distribution format, then the shebang line - should be ``#!python`` rather than ``#!`` followed by the contents of - ``sys.executable``. - """ - if set(('bdist_wheel', 'bdist_egg', 'bdist_wininst', - 'bdist_rpm')).intersection(sys.argv): - return '#!python' - return '#!' + sys.executable +from __version__ import version def configuration(parent_package='', top_path=None): config = Configuration('f2py', parent_package, top_path) - config.add_data_dir('tests') - - config.add_data_files('src/fortranobject.c', - 'src/fortranobject.h', - ) - - config.make_svn_version_py() - - def generate_f2py_py(build_dir): - f2py_exe = 'f2py' + os.path.basename(sys.executable)[6:] - if f2py_exe[-4:] == '.exe': - f2py_exe = f2py_exe[:-4] + '.py' - if 'bdist_wininst' in sys.argv and f2py_exe[-3:] != '.py': - f2py_exe = f2py_exe + '.py' - target = os.path.join(build_dir, f2py_exe) - if newer(__file__, target): - log.info('Creating %s', target) - f = open(target, 'w') - f.write(_get_f2py_shebang() + '\n') - mainloc = os.path.join(os.path.dirname(__file__), "__main__.py") - with open(mainloc) as mf: - f.write(mf.read()) - f.close() - return target - - config.add_scripts(generate_f2py_py) - - log.info('F2PY Version %s', config.get_version()) - + config.add_data_files( + 'src/fortranobject.c', + 'src/fortranobject.h') return config + if __name__ == "__main__": config = configuration(top_path='') - print('F2PY Version', version) config = config.todict() config['download_url'] = "http://cens.ioc.ee/projects/f2py2e/2.x"\ diff --git a/numpy/lib/__init__.py b/numpy/lib/__init__.py index dc40ac67b..c1757150e 100644 --- a/numpy/lib/__init__.py +++ b/numpy/lib/__init__.py @@ -26,7 +26,7 @@ from .financial import * from .arrayterator import Arrayterator from .arraypad import * from ._version import * -from numpy.core.multiarray import tracemalloc_domain +from numpy.core._multiarray_umath import tracemalloc_domain __all__ = ['emath', 'math', 'tracemalloc_domain'] __all__ += type_check.__all__ diff --git a/numpy/lib/_datasource.py b/numpy/lib/_datasource.py index 6f1295f09..ab00b1444 100644 --- a/numpy/lib/_datasource.py +++ b/numpy/lib/_datasource.py @@ -37,6 +37,7 @@ from __future__ import division, absolute_import, print_function import os import sys +import warnings import shutil import io @@ -85,9 +86,10 @@ def _python2_bz2open(fn, mode, encoding, newline): if "t" in mode: # BZ2File is missing necessary functions for TextIOWrapper - raise ValueError("bz2 text files not supported in python2") - else: - return bz2.BZ2File(fn, mode) + warnings.warn("Assuming latin1 encoding for bz2 text file in Python2", + RuntimeWarning, stacklevel=5) + mode = mode.replace("t", "") + return bz2.BZ2File(fn, mode) def _python2_gzipopen(fn, mode, encoding, newline): """ Wrapper to open gzip in text mode. diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py index 5880ea154..62e9b6d50 100644 --- a/numpy/lib/arraysetops.py +++ b/numpy/lib/arraysetops.py @@ -82,6 +82,11 @@ def ediff1d(ary, to_end=None, to_begin=None): # force a 1d array ary = np.asanyarray(ary).ravel() + # we have unit tests enforcing + # propagation of the dtype of input + # ary to returned result + dtype_req = ary.dtype + # fast track default case if to_begin is None and to_end is None: return ary[1:] - ary[:-1] @@ -89,13 +94,23 @@ def ediff1d(ary, to_end=None, to_begin=None): if to_begin is None: l_begin = 0 else: - to_begin = np.asanyarray(to_begin).ravel() + to_begin = np.asanyarray(to_begin) + if not np.can_cast(to_begin, dtype_req): + raise TypeError("dtype of to_begin must be compatible " + "with input ary") + + to_begin = to_begin.ravel() l_begin = len(to_begin) if to_end is None: l_end = 0 else: - to_end = np.asanyarray(to_end).ravel() + to_end = np.asanyarray(to_end) + if not np.can_cast(to_end, dtype_req): + raise TypeError("dtype of to_end must be compatible " + "with input ary") + + to_end = to_end.ravel() l_end = len(to_end) # do the calculation in place and copy to_begin and to_end @@ -312,12 +327,12 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): If True, the input arrays are both assumed to be unique, which can speed up the calculation. Default is False. return_indices : bool - If True, the indices which correspond to the intersection of the - two arrays are returned. The first instance of a value is used - if there are multiple. Default is False. - - .. versionadded:: 1.15.0 - + If True, the indices which correspond to the intersection of the two + arrays are returned. The first instance of a value is used if there are + multiple. Default is False. + + .. versionadded:: 1.15.0 + Returns ------- intersect1d : ndarray @@ -326,7 +341,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): The indices of the first occurrences of the common values in `ar1`. Only provided if `return_indices` is True. comm2 : ndarray - The indices of the first occurrences of the common values in `ar2`. + The indices of the first occurrences of the common values in `ar2`. Only provided if `return_indices` is True. @@ -345,7 +360,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): >>> from functools import reduce >>> reduce(np.intersect1d, ([1, 3, 4, 3], [3, 1, 2, 1], [6, 3, 4, 2])) array([3]) - + To return the indices of the values common to the input arrays along with the intersected values: >>> x = np.array([1, 1, 2, 3, 4]) @@ -355,8 +370,11 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): (array([0, 2, 4]), array([1, 0, 2])) >>> xy, x[x_ind], y[y_ind] (array([1, 2, 4]), array([1, 2, 4]), array([1, 2, 4])) - + """ + ar1 = np.asanyarray(ar1) + ar2 = np.asanyarray(ar2) + if not assume_unique: if return_indices: ar1, ind1 = unique(ar1, return_index=True) @@ -367,7 +385,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): else: ar1 = ar1.ravel() ar2 = ar2.ravel() - + aux = np.concatenate((ar1, ar2)) if return_indices: aux_sort_indices = np.argsort(aux, kind='mergesort') @@ -389,6 +407,7 @@ def intersect1d(ar1, ar2, assume_unique=False, return_indices=False): else: return int1d + def setxor1d(ar1, ar2, assume_unique=False): """ Find the set exclusive-or of two arrays. diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 75a39beaa..2992e92bb 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -305,12 +305,17 @@ def average(a, axis=None, weights=None, returned=False): Returns ------- - average, [sum_of_weights] : array_type or double - Return the average along the specified axis. When returned is `True`, + retval, [sum_of_weights] : array_type or double + Return the average along the specified axis. When `returned` is `True`, return a tuple with the average as the first element and the sum - of the weights as the second element. The return type is `Float` - if `a` is of integer type, otherwise it is of the same type as `a`. - `sum_of_weights` is of the same type as `average`. + of the weights as the second element. `sum_of_weights` is of the + same type as `retval`. The result dtype follows a genereal pattern. + If `weights` is None, the result dtype will be that of `a` , or ``float64`` + if `a` is integral. Otherwise, if `weights` is not None and `a` is non- + integral, the result type will be the type of lowest precision capable of + representing values of both `a` and `weights`. If `a` happens to be + integral, the previous rules still applies but the result dtype will + at least be ``float64``. Raises ------ @@ -327,6 +332,8 @@ def average(a, axis=None, weights=None, returned=False): ma.average : average for masked arrays -- useful if your data contains "missing" values + numpy.result_type : Returns the type that results from applying the + numpy type promotion rules to the arguments. Examples -------- @@ -346,10 +353,16 @@ def average(a, axis=None, weights=None, returned=False): >>> np.average(data, axis=1, weights=[1./4, 3./4]) array([ 0.75, 2.75, 4.75]) >>> np.average(data, weights=[1./4, 3./4]) + Traceback (most recent call last): ... TypeError: Axis must be specified when shapes of a and weights differ. - + + >>> a = np.ones(5, dtype=np.float128) + >>> w = np.ones(5, dtype=np.complex64) + >>> avg = np.average(a, weights=w) + >>> print(avg.dtype) + complex256 """ a = np.asanyarray(a) @@ -1769,8 +1782,8 @@ class vectorize(object): Generalized function class. Define a vectorized function which takes a nested sequence of objects or - numpy arrays as inputs and returns an single or tuple of numpy array as - output. The vectorized function evaluates `pyfunc` over successive tuples + numpy arrays as inputs and returns a single numpy array or a tuple of numpy + arrays. The vectorized function evaluates `pyfunc` over successive tuples of the input arrays like the python map function, except it uses the broadcasting rules of numpy. diff --git a/numpy/lib/histograms.py b/numpy/lib/histograms.py index 422b356f7..f03f30fb0 100644 --- a/numpy/lib/histograms.py +++ b/numpy/lib/histograms.py @@ -260,6 +260,32 @@ def _get_outer_edges(a, range): return first_edge, last_edge +def _unsigned_subtract(a, b): + """ + Subtract two values where a >= b, and produce an unsigned result + + This is needed when finding the difference between the upper and lower + bound of an int16 histogram + """ + # coerce to a single type + signed_to_unsigned = { + np.byte: np.ubyte, + np.short: np.ushort, + np.intc: np.uintc, + np.int_: np.uint, + np.longlong: np.ulonglong + } + dt = np.result_type(a, b) + try: + dt = signed_to_unsigned[dt.type] + except KeyError: + return np.subtract(a, b, dtype=dt) + else: + # we know the inputs are integers, and we are deliberately casting + # signed to unsigned + return np.subtract(a, b, casting='unsafe', dtype=dt) + + def _get_bin_edges(a, bins, range, weights): """ Computes the bins used internally by `histogram`. @@ -311,7 +337,7 @@ def _get_bin_edges(a, bins, range, weights): # Do not call selectors on empty arrays width = _hist_bin_selectors[bin_name](a) if width: - n_equal_bins = int(np.ceil((last_edge - first_edge) / width)) + n_equal_bins = int(np.ceil(_unsigned_subtract(last_edge, first_edge) / width)) else: # Width can be zero for some estimators, e.g. FD when # the IQR of the data is zero. @@ -703,7 +729,7 @@ def histogram(a, bins=10, range=None, normed=None, weights=None, n = np.zeros(n_equal_bins, ntype) # Pre-compute histogram scaling factor - norm = n_equal_bins / (last_edge - first_edge) + norm = n_equal_bins / _unsigned_subtract(last_edge, first_edge) # We iterate over blocks here for two reasons: the first is that for # large arrays, it is actually faster (for example for a 10^8 array it @@ -731,7 +757,7 @@ def histogram(a, bins=10, range=None, normed=None, weights=None, # Compute the bin indices, and for values that lie exactly on # last_edge we need to subtract one - f_indices = (tmp_a - first_edge) * norm + f_indices = _unsigned_subtract(tmp_a, first_edge) * norm indices = f_indices.astype(np.intp) indices[indices == n_equal_bins] -= 1 diff --git a/numpy/lib/nanfunctions.py b/numpy/lib/nanfunctions.py index abd2da1a2..8d6b0f139 100644 --- a/numpy/lib/nanfunctions.py +++ b/numpy/lib/nanfunctions.py @@ -1178,13 +1178,15 @@ def nanquantile(a, q, axis=None, out=None, overwrite_input=False, This optional parameter specifies the interpolation method to use when the desired quantile lies between two data points ``i < j``: - * linear: ``i + (j - i) * fraction``, where ``fraction`` - is the fractional part of the index surrounded by ``i`` - and ``j``. - * lower: ``i``. - * higher: ``j``. - * nearest: ``i`` or ``j``, whichever is nearest. - * midpoint: ``(i + j) / 2``. + + * linear: ``i + (j - i) * fraction``, where ``fraction`` + is the fractional part of the index surrounded by ``i`` + and ``j``. + * lower: ``i``. + * higher: ``j``. + * nearest: ``i`` or ``j``, whichever is nearest. + * midpoint: ``(i + j) / 2``. + keepdims : bool, optional If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py index 0e691f56e..9f3b84732 100644 --- a/numpy/lib/polynomial.py +++ b/numpy/lib/polynomial.py @@ -396,7 +396,11 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False): Fit a polynomial ``p(x) = p[0] * x**deg + ... + p[deg]`` of degree `deg` to points `(x, y)`. Returns a vector of coefficients `p` that minimises - the squared error. + the squared error in the order `deg`, `deg-1`, ... `0`. + + The `Polynomial.fit <numpy.polynomial.polynomial.Polynomial.fit>` class + method is recommended for new code as it is more stable numerically. See + the documentation of the method for more information. Parameters ---------- diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index d31d8a939..66f534734 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -688,7 +688,7 @@ def array_split(ary, indices_or_sections, axis=0): except AttributeError: Ntotal = len(ary) try: - # handle scalar case. + # handle array case. Nsections = len(indices_or_sections) + 1 div_points = [0] + list(indices_or_sections) + [Ntotal] except TypeError: @@ -700,7 +700,7 @@ def array_split(ary, indices_or_sections, axis=0): section_sizes = ([0] + extras * [Neach_section+1] + (Nsections-extras) * [Neach_section]) - div_points = _nx.array(section_sizes).cumsum() + div_points = _nx.array(section_sizes, dtype=_nx.intp).cumsum() sub_arys = [] sary = _nx.swapaxes(ary, axis, 0) diff --git a/numpy/lib/stride_tricks.py b/numpy/lib/stride_tricks.py index bc5993802..ca13738c1 100644 --- a/numpy/lib/stride_tricks.py +++ b/numpy/lib/stride_tricks.py @@ -242,7 +242,7 @@ def broadcast_arrays(*args, **kwargs): subok = kwargs.pop('subok', False) if kwargs: raise TypeError('broadcast_arrays() got an unexpected keyword ' - 'argument {!r}'.format(kwargs.keys()[0])) + 'argument {!r}'.format(list(kwargs.keys())[0])) args = [np.array(_m, copy=False, subok=subok) for _m in args] shape = _broadcast_shape(*args) diff --git a/numpy/lib/tests/test__datasource.py b/numpy/lib/tests/test__datasource.py index 32812990c..85788941c 100644 --- a/numpy/lib/tests/test__datasource.py +++ b/numpy/lib/tests/test__datasource.py @@ -2,11 +2,14 @@ from __future__ import division, absolute_import, print_function import os import sys +import pytest from tempfile import mkdtemp, mkstemp, NamedTemporaryFile from shutil import rmtree -from numpy.testing import assert_, assert_equal, assert_raises, SkipTest import numpy.lib._datasource as datasource +from numpy.testing import ( + assert_, assert_equal, assert_raises, assert_warns, SkipTest + ) if sys.version_info[0] >= 3: import urllib.request as urllib_request @@ -30,14 +33,14 @@ def urlopen_stub(url, data=None): old_urlopen = None -def setup(): +def setup_module(): global old_urlopen old_urlopen = urllib_request.urlopen urllib_request.urlopen = urlopen_stub -def teardown(): +def teardown_module(): urllib_request.urlopen = old_urlopen # A valid website for more robust testing @@ -161,6 +164,24 @@ class TestDataSourceOpen(object): fp.close() assert_equal(magic_line, result) + @pytest.mark.skipif(sys.version_info[0] >= 3, reason="Python 2 only") + def test_Bz2File_text_mode_warning(self): + try: + import bz2 + except ImportError: + # We don't have the bz2 capabilities to test. + raise SkipTest + # Test datasource's internal file_opener for BZip2 files. + filepath = os.path.join(self.tmpdir, 'foobar.txt.bz2') + fp = bz2.BZ2File(filepath, 'w') + fp.write(magic_line) + fp.close() + with assert_warns(RuntimeWarning): + fp = self.ds.open(filepath, 'rt') + result = fp.readline() + fp.close() + assert_equal(magic_line, result) + class TestDataSourceExists(object): def setup(self): diff --git a/numpy/lib/tests/test_arraysetops.py b/numpy/lib/tests/test_arraysetops.py index dace5ade8..4b61726d2 100644 --- a/numpy/lib/tests/test_arraysetops.py +++ b/numpy/lib/tests/test_arraysetops.py @@ -6,10 +6,13 @@ from __future__ import division, absolute_import, print_function import numpy as np import sys -from numpy.testing import assert_array_equal, assert_equal, assert_raises +from numpy.testing import (assert_array_equal, assert_equal, + assert_raises, assert_raises_regex) from numpy.lib.arraysetops import ( ediff1d, intersect1d, setxor1d, union1d, setdiff1d, unique, in1d, isin ) +import pytest + class TestSetOps(object): @@ -30,19 +33,30 @@ class TestSetOps(object): ed = np.array([1, 2, 5]) c = intersect1d(a, b) assert_array_equal(c, ed) - assert_array_equal([], intersect1d([], [])) - + + def test_intersect1d_array_like(self): + # See gh-11772 + class Test(object): + def __array__(self): + return np.arange(3) + + a = Test() + res = intersect1d(a, a) + assert_array_equal(res, a) + res = intersect1d([1, 2, 3], [1, 2, 3]) + assert_array_equal(res, [1, 2, 3]) + def test_intersect1d_indices(self): # unique inputs - a = np.array([1, 2, 3, 4]) + a = np.array([1, 2, 3, 4]) b = np.array([2, 1, 4, 6]) c, i1, i2 = intersect1d(a, b, assume_unique=True, return_indices=True) ee = np.array([1, 2, 4]) assert_array_equal(c, ee) assert_array_equal(a[i1], ee) assert_array_equal(b[i2], ee) - + # non-unique inputs a = np.array([1, 2, 2, 3, 4, 3, 2]) b = np.array([1, 8, 4, 2, 2, 3, 2, 3]) @@ -51,7 +65,7 @@ class TestSetOps(object): assert_array_equal(c, ef) assert_array_equal(a[i1], ef) assert_array_equal(b[i2], ef) - + # non1d, unique inputs a = np.array([[2, 4, 5, 6], [7, 8, 1, 15]]) b = np.array([[3, 2, 7, 6], [10, 12, 8, 9]]) @@ -61,7 +75,7 @@ class TestSetOps(object): ea = np.array([2, 6, 7, 8]) assert_array_equal(ea, a[ui1]) assert_array_equal(ea, b[ui2]) - + # non1d, not assumed to be uniqueinputs a = np.array([[2, 4, 5, 6, 6], [4, 7, 8, 7, 2]]) b = np.array([[3, 2, 7, 7], [10, 12, 8, 7]]) @@ -71,7 +85,7 @@ class TestSetOps(object): ea = np.array([2, 7, 8]) assert_array_equal(ea, a[ui1]) assert_array_equal(ea, b[ui2]) - + def test_setxor1d(self): a = np.array([5, 7, 1, 2]) b = np.array([2, 4, 3, 1, 5]) @@ -114,6 +128,68 @@ class TestSetOps(object): assert_array_equal([7,1], ediff1d(two_elem, to_begin=7)) assert_array_equal([5,6,1], ediff1d(two_elem, to_begin=[5,6])) + @pytest.mark.parametrize("ary, prepend, append", [ + # should fail because trying to cast + # np.nan standard floating point value + # into an integer array: + (np.array([1, 2, 3], dtype=np.int64), + None, + np.nan), + # should fail because attempting + # to downcast to smaller int type: + (np.array([1, 2, 3], dtype=np.int32), + np.array([5, 7, 2], dtype=np.int64), + None), + # should fail because attempting to cast + # two special floating point values + # to integers (on both sides of ary): + (np.array([1., 3., 9.], dtype=np.int8), + np.nan, + np.nan), + ]) + def test_ediff1d_forbidden_type_casts(self, ary, prepend, append): + # verify resolution of gh-11490 + + # specifically, raise an appropriate + # Exception when attempting to append or + # prepend with an incompatible type + msg = 'must be compatible' + with assert_raises_regex(TypeError, msg): + ediff1d(ary=ary, + to_end=append, + to_begin=prepend) + + @pytest.mark.parametrize("ary," + "prepend," + "append," + "expected", [ + (np.array([1, 2, 3], dtype=np.int16), + 0, + None, + np.array([0, 1, 1], dtype=np.int16)), + (np.array([1, 2, 3], dtype=np.int32), + 0, + 0, + np.array([0, 1, 1, 0], dtype=np.int32)), + (np.array([1, 2, 3], dtype=np.int64), + 3, + -9, + np.array([3, 1, 1, -9], dtype=np.int64)), + ]) + def test_ediff1d_scalar_handling(self, + ary, + prepend, + append, + expected): + # maintain backwards-compatibility + # of scalar prepend / append behavior + # in ediff1d following fix for gh-11490 + actual = np.ediff1d(ary=ary, + to_end=append, + to_begin=prepend) + assert_equal(actual, expected) + + def test_isin(self): # the tests for in1d cover most of isin's behavior # if in1d is removed, would need to change those tests to test diff --git a/numpy/lib/tests/test_histograms.py b/numpy/lib/tests/test_histograms.py index f136b5c81..561f5f938 100644 --- a/numpy/lib/tests/test_histograms.py +++ b/numpy/lib/tests/test_histograms.py @@ -310,6 +310,20 @@ class TestHistogram(object): assert_equal(d_edge.dtype, dates.dtype) assert_equal(t_edge.dtype, td) + def do_signed_overflow_bounds(self, dtype): + exponent = 8 * np.dtype(dtype).itemsize - 1 + arr = np.array([-2**exponent + 4, 2**exponent - 4], dtype=dtype) + hist, e = histogram(arr, bins=2) + assert_equal(e, [-2**exponent + 4, 0, 2**exponent - 4]) + assert_equal(hist, [1, 1]) + + def test_signed_overflow_bounds(self): + self.do_signed_overflow_bounds(np.byte) + self.do_signed_overflow_bounds(np.short) + self.do_signed_overflow_bounds(np.intc) + self.do_signed_overflow_bounds(np.int_) + self.do_signed_overflow_bounds(np.longlong) + def do_precision_lower_bound(self, float_small, float_large): eps = np.finfo(float_large).eps diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py index 315251daa..7e9c026e4 100644 --- a/numpy/lib/tests/test_index_tricks.py +++ b/numpy/lib/tests/test_index_tricks.py @@ -113,7 +113,6 @@ class TestRavelUnravelIndex(object): assert_(x.flags.writeable) assert_(y.flags.writeable) - def test_0d(self): # gh-580 x = np.unravel_index(0, ()) diff --git a/numpy/lib/tests/test_io.py b/numpy/lib/tests/test_io.py index f58c9e33d..1f3664d92 100644 --- a/numpy/lib/tests/test_io.py +++ b/numpy/lib/tests/test_io.py @@ -348,7 +348,6 @@ class TestSaveTxt(object): assert_raises(ValueError, np.savetxt, c, np.array(1)) assert_raises(ValueError, np.savetxt, c, np.array([[[1], [2]]])) - def test_record(self): a = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')]) c = BytesIO() @@ -2025,7 +2024,6 @@ M 33 21.99 assert_equal(test['f0'], 0) assert_equal(test['f1'], "testNonethe" + utf8.decode("UTF-8")) - def test_utf8_file_nodtype_unicode(self): # bytes encoding with non-latin1 -> unicode upcast utf8 = u'\u03d6' diff --git a/numpy/lib/tests/test_shape_base.py b/numpy/lib/tests/test_shape_base.py index 6d24dd624..6e4cd225d 100644 --- a/numpy/lib/tests/test_shape_base.py +++ b/numpy/lib/tests/test_shape_base.py @@ -3,6 +3,8 @@ from __future__ import division, absolute_import, print_function import numpy as np import warnings import functools +import sys +import pytest from numpy.lib.shape_base import ( apply_along_axis, apply_over_axes, array_split, split, hsplit, dsplit, @@ -14,6 +16,9 @@ from numpy.testing import ( ) +IS_64BIT = sys.maxsize > 2**32 + + def _add_keepdims(func): """ hack in keepdims behavior into a function taking an axis """ @functools.wraps(func) @@ -403,6 +408,15 @@ class TestArraySplit(object): assert_(a.dtype.type is res[-1].dtype.type) # perhaps should check higher dimensions + @pytest.mark.skipif(not IS_64BIT, reason="Needs 64bit platform") + def test_integer_split_2D_rows_greater_max_int32(self): + a = np.broadcast_to([0], (1 << 32, 2)) + res = array_split(a, 4) + chunk = np.broadcast_to([0], (1 << 30, 2)) + tgt = [chunk] * 4 + for i in range(len(tgt)): + assert_equal(res[i].shape, tgt[i].shape) + def test_index_split_simple(self): a = np.arange(10) indices = [1, 5, 7] diff --git a/numpy/lib/tests/test_stride_tricks.py b/numpy/lib/tests/test_stride_tricks.py index 3c2ca8b87..b2bd7da3e 100644 --- a/numpy/lib/tests/test_stride_tricks.py +++ b/numpy/lib/tests/test_stride_tricks.py @@ -3,7 +3,8 @@ from __future__ import division, absolute_import, print_function import numpy as np from numpy.core._rational_tests import rational from numpy.testing import ( - assert_equal, assert_array_equal, assert_raises, assert_ + assert_equal, assert_array_equal, assert_raises, assert_, + assert_raises_regex ) from numpy.lib.stride_tricks import ( as_strided, broadcast_arrays, _broadcast_shape, broadcast_to @@ -57,6 +58,17 @@ def test_same(): assert_array_equal(x, bx) assert_array_equal(y, by) +def test_broadcast_kwargs(): + # ensure that a TypeError is appropriately raised when + # np.broadcast_arrays() is called with any keyword + # argument other than 'subok' + x = np.arange(10) + y = np.arange(10) + + with assert_raises_regex(TypeError, + r'broadcast_arrays\(\) got an unexpected keyword*'): + broadcast_arrays(x, y, dtype='float64') + def test_one_off(): x = np.array([[1, 2, 3]]) diff --git a/numpy/linalg/linalg.py b/numpy/linalg/linalg.py index c3b76ada7..ccc437663 100644 --- a/numpy/linalg/linalg.py +++ b/numpy/linalg/linalg.py @@ -133,11 +133,6 @@ def _linalgRealType(t): """Cast the type t to either double or cdouble.""" return double -_complex_types_map = {single : csingle, - double : cdouble, - csingle : csingle, - cdouble : cdouble} - def _commonType(*arrays): # in lite version, use higher precision (always double or cdouble) result_type = single @@ -542,6 +537,8 @@ def matrix_power(a, n): of the same shape as M is returned. If ``n < 0``, the inverse is computed and then raised to the ``abs(n)``. + .. note:: Stacks of object matrices are not currently supported. + Parameters ---------- a : (..., M, M) array_like @@ -604,6 +601,16 @@ def matrix_power(a, n): except TypeError: raise TypeError("exponent must be an integer") + # Fall back on dot for object arrays. Object arrays are not supported by + # the current implementation of matmul using einsum + if a.dtype != object: + fmatmul = matmul + elif a.ndim == 2: + fmatmul = dot + else: + raise NotImplementedError( + "matrix_power not supported for stacks of object arrays") + if n == 0: a = empty_like(a) a[...] = eye(a.shape[-2], dtype=a.dtype) @@ -618,20 +625,20 @@ def matrix_power(a, n): return a elif n == 2: - return matmul(a, a) + return fmatmul(a, a) elif n == 3: - return matmul(matmul(a, a), a) + return fmatmul(fmatmul(a, a), a) # Use binary decomposition to reduce the number of matrix multiplications. # Here, we iterate over the bits of n, from LSB to MSB, raise `a` to # increasing powers of 2, and multiply into the result as needed. z = result = None while n > 0: - z = a if z is None else matmul(z, z) + z = a if z is None else fmatmul(z, z) n, bit = divmod(n, 2) if bit: - result = z if result is None else matmul(result, z) + result = z if result is None else fmatmul(result, z) return result @@ -2115,7 +2122,6 @@ def lstsq(a, b, rcond="warn"): if is_1d: b = b[:, newaxis] _assertRank2(a, b) - _assertNoEmpty2d(a, b) # TODO: relax this constraint m, n = a.shape[-2:] m2, n_rhs = b.shape[-2:] if m != m2: @@ -2146,7 +2152,16 @@ def lstsq(a, b, rcond="warn"): signature = 'DDd->Ddid' if isComplexType(t) else 'ddd->ddid' extobj = get_linalg_error_extobj(_raise_linalgerror_lstsq) + if n_rhs == 0: + # lapack can't handle n_rhs = 0 - so allocate the array one larger in that axis + b = zeros(b.shape[:-2] + (m, n_rhs + 1), dtype=b.dtype) x, resids, rank, s = gufunc(a, b, rcond, signature=signature, extobj=extobj) + if m == 0: + x[...] = 0 + if n_rhs == 0: + # remove the item we added + x = x[..., :n_rhs] + resids = resids[..., :n_rhs] # remove the axis we added if is_1d: diff --git a/numpy/linalg/tests/test_linalg.py b/numpy/linalg/tests/test_linalg.py index 0df673884..98a77d8f5 100644 --- a/numpy/linalg/tests/test_linalg.py +++ b/numpy/linalg/tests/test_linalg.py @@ -875,14 +875,12 @@ class TestDet(DetCases): class LstsqCases(LinalgSquareTestCase, LinalgNonsquareTestCase): def do(self, a, b, tags): - if 'size-0' in tags: - assert_raises(LinAlgError, linalg.lstsq, a, b) - return - arr = np.asarray(a) m, n = arr.shape u, s, vt = linalg.svd(a, 0) x, residuals, rank, sv = linalg.lstsq(a, b, rcond=-1) + if m == 0: + assert_((x == 0).all()) if m <= n: assert_almost_equal(b, dot(a, x)) assert_equal(rank, m) @@ -923,78 +921,117 @@ class TestLstsq(LstsqCases): # Warning should be raised exactly once (first command) assert_(len(w) == 1) - + @pytest.mark.parametrize(["m", "n", "n_rhs"], [ + (4, 2, 2), + (0, 4, 1), + (0, 4, 2), + (4, 0, 1), + (4, 0, 2), + (4, 2, 0), + (0, 0, 0) + ]) + def test_empty_a_b(self, m, n, n_rhs): + a = np.arange(m * n).reshape(m, n) + b = np.ones((m, n_rhs)) + x, residuals, rank, s = linalg.lstsq(a, b, rcond=None) + if m == 0: + assert_((x == 0).all()) + assert_equal(x.shape, (n, n_rhs)) + assert_equal(residuals.shape, ((n_rhs,) if m > n else (0,))) + if m > n and n_rhs > 0: + # residuals are exactly the squared norms of b's columns + r = b - np.dot(a, x) + assert_almost_equal(residuals, (r * r).sum(axis=-2)) + assert_equal(rank, min(m, n)) + assert_equal(s.shape, (min(m, n),)) + + +@pytest.mark.parametrize('dt', [np.dtype(c) for c in '?bBhHiIqQefdgFDGO']) class TestMatrixPower(object): - R90 = array([[0, 1], [-1, 0]]) - Arb22 = array([[4, -7], [-2, 10]]) - noninv = array([[1, 0], [0, 0]]) - arbfloat = array([[[0.1, 3.2], [1.2, 0.7]], - [[0.2, 6.4], [2.4, 1.4]]]) - large = identity(10) - t = large[1, :].copy() - large[1, :] = large[0, :] - large[0, :] = t + rshft_0 = np.eye(4) + rshft_1 = rshft_0[[3, 0, 1, 2]] + rshft_2 = rshft_0[[2, 3, 0, 1]] + rshft_3 = rshft_0[[1, 2, 3, 0]] + rshft_all = [rshft_0, rshft_1, rshft_2, rshft_3] + noninv = array([[1, 0], [0, 0]]) + stacked = np.block([[[rshft_0]]]*2) + #FIXME the 'e' dtype might work in future + dtnoinv = [object, np.dtype('e'), np.dtype('g'), np.dtype('G')] - def test_large_power(self): + def test_large_power(self, dt): + power = matrix_power + rshft = self.rshft_1.astype(dt) assert_equal( - matrix_power(self.R90, 2 ** 100 + 2 ** 10 + 2 ** 5 + 1), self.R90) + matrix_power(rshft, 2**100 + 2**10 + 2**5 + 0), self.rshft_0) assert_equal( - matrix_power(self.R90, 2 ** 100 + 2 ** 10 + 1), self.R90) + matrix_power(rshft, 2**100 + 2**10 + 2**5 + 1), self.rshft_1) assert_equal( - matrix_power(self.R90, 2 ** 100 + 2 + 1), -self.R90) - - def test_large_power_trailing_zero(self): + matrix_power(rshft, 2**100 + 2**10 + 2**5 + 2), self.rshft_2) assert_equal( - matrix_power(self.R90, 2 ** 100 + 2 ** 10 + 2 ** 5), identity(2)) + matrix_power(rshft, 2**100 + 2**10 + 2**5 + 3), self.rshft_3) - def testip_zero(self): + def test_power_is_zero(self, dt): def tz(M): mz = matrix_power(M, 0) assert_equal(mz, identity_like_generalized(M)) assert_equal(mz.dtype, M.dtype) - for M in [self.Arb22, self.arbfloat, self.large]: - tz(M) - - def testip_one(self): - def tz(M): - mz = matrix_power(M, 1) - assert_equal(mz, M) - assert_equal(mz.dtype, M.dtype) - for M in [self.Arb22, self.arbfloat, self.large]: - tz(M) - - def testip_two(self): - def tz(M): - mz = matrix_power(M, 2) - assert_equal(mz, matmul(M, M)) - assert_equal(mz.dtype, M.dtype) - for M in [self.Arb22, self.arbfloat, self.large]: - tz(M) - - def testip_invert(self): - def tz(M): - mz = matrix_power(M, -1) - assert_almost_equal(matmul(mz, M), identity_like_generalized(M)) - for M in [self.R90, self.Arb22, self.arbfloat, self.large]: - tz(M) - - def test_invert_noninvertible(self): - assert_raises(LinAlgError, matrix_power, self.noninv, -1) - - def test_invalid(self): - assert_raises(TypeError, matrix_power, self.R90, 1.5) - assert_raises(TypeError, matrix_power, self.R90, [1]) - assert_raises(LinAlgError, matrix_power, np.array([1]), 1) - assert_raises(LinAlgError, matrix_power, np.array([[1], [2]]), 1) - assert_raises(LinAlgError, matrix_power, np.ones((4, 3, 2)), 1) - - -class TestBoolPower(object): + + for mat in self.rshft_all: + tz(mat.astype(dt)) + if dt != object: + tz(self.stacked.astype(dt)) + + def test_power_is_one(self, dt): + def tz(mat): + mz = matrix_power(mat, 1) + assert_equal(mz, mat) + assert_equal(mz.dtype, mat.dtype) + + for mat in self.rshft_all: + tz(mat.astype(dt)) + if dt != object: + tz(self.stacked.astype(dt)) + + def test_power_is_two(self, dt): + def tz(mat): + mz = matrix_power(mat, 2) + mmul = matmul if mat.dtype != object else dot + assert_equal(mz, mmul(mat, mat)) + assert_equal(mz.dtype, mat.dtype) + + for mat in self.rshft_all: + tz(mat.astype(dt)) + if dt != object: + tz(self.stacked.astype(dt)) + + def test_power_is_minus_one(self, dt): + def tz(mat): + invmat = matrix_power(mat, -1) + mmul = matmul if mat.dtype != object else dot + assert_almost_equal( + mmul(invmat, mat), identity_like_generalized(mat)) + + for mat in self.rshft_all: + if dt not in self.dtnoinv: + tz(mat.astype(dt)) + + def test_exceptions_bad_power(self, dt): + mat = self.rshft_0.astype(dt) + assert_raises(TypeError, matrix_power, mat, 1.5) + assert_raises(TypeError, matrix_power, mat, [1]) + + def test_exceptions_non_square(self, dt): + assert_raises(LinAlgError, matrix_power, np.array([1], dt), 1) + assert_raises(LinAlgError, matrix_power, np.array([[1], [2]], dt), 1) + assert_raises(LinAlgError, matrix_power, np.ones((4, 3, 2), dt), 1) + + def test_exceptions_not_invertible(self, dt): + if dt in self.dtnoinv: + return + mat = self.noninv.astype(dt) + assert_raises(LinAlgError, matrix_power, mat, -1) - def test_square(self): - A = array([[True, False], [True, True]]) - assert_equal(matrix_power(A, 2), A) class TestEigvalshCases(HermitianTestCase, HermitianGeneralizedTestCase): diff --git a/numpy/ma/core.py b/numpy/ma/core.py index 74edeb274..65ce967ae 100644 --- a/numpy/ma/core.py +++ b/numpy/ma/core.py @@ -215,7 +215,7 @@ def _recursive_fill_value(dtype, f): """ Recursively produce a fill value for `dtype`, calling f on scalar dtypes """ - if dtype.names: + if dtype.names is not None: vals = tuple(_recursive_fill_value(dtype[name], f) for name in dtype.names) return np.array(vals, dtype=dtype)[()] # decay to void scalar from 0d elif dtype.subdtype: @@ -433,7 +433,7 @@ def _recursive_set_fill_value(fillvalue, dt): if cdtype.subdtype: cdtype = cdtype.subdtype[0] - if cdtype.names: + if cdtype.names is not None: output_value.append(tuple(_recursive_set_fill_value(fval, cdtype))) else: output_value.append(np.array(fval, dtype=cdtype).item()) @@ -1282,7 +1282,7 @@ def _replace_dtype_fields_recursive(dtype, primitive_dtype): _recurse = _replace_dtype_fields_recursive # Do we have some name fields ? - if dtype.names: + if dtype.names is not None: descr = [] for name in dtype.names: field = dtype.fields[name] @@ -1547,7 +1547,7 @@ def _shrink_mask(m): """ Shrink a mask to nomask if possible """ - if not m.dtype.names and not m.any(): + if m.dtype.names is None and not m.any(): return nomask else: return m @@ -1733,7 +1733,7 @@ def mask_or(m1, m2, copy=False, shrink=True): names = m1.dtype.names for name in names: current1 = m1[name] - if current1.dtype.names: + if current1.dtype.names is not None: _recursive_mask_or(current1, m2[name], newmask[name]) else: umath.logical_or(current1, m2[name], newmask[name]) @@ -1750,7 +1750,7 @@ def mask_or(m1, m2, copy=False, shrink=True): (dtype1, dtype2) = (getattr(m1, 'dtype', None), getattr(m2, 'dtype', None)) if (dtype1 != dtype2): raise ValueError("Incompatible dtypes '%s'<>'%s'" % (dtype1, dtype2)) - if dtype1.names: + if dtype1.names is not None: # Allocate an output mask array with the properly broadcast shape. newmask = np.empty(np.broadcast(m1, m2).shape, dtype1) _recursive_mask_or(m1, m2, newmask) @@ -1793,7 +1793,7 @@ def flatten_mask(mask): def _flatmask(mask): "Flatten the mask and returns a (maybe nested) sequence of booleans." mnames = mask.dtype.names - if mnames: + if mnames is not None: return [flatten_mask(mask[name]) for name in mnames] else: return mask @@ -2431,7 +2431,7 @@ def _recursive_printoption(result, mask, printopt): """ names = result.dtype.names - if names: + if names is not None: for name in names: curdata = result[name] curmask = mask[name] @@ -2483,7 +2483,7 @@ def _recursive_filled(a, mask, fill_value): names = a.dtype.names for name in names: current = a[name] - if current.dtype.names: + if current.dtype.names is not None: _recursive_filled(current, mask[name], fill_value[name]) else: np.copyto(current, fill_value[name], where=mask[name]) @@ -2870,12 +2870,12 @@ class MaskedArray(ndarray): _data._mask = mask _data._sharedmask = not copy else: - if _data.dtype.names: + if _data.dtype.names is not None: def _recursive_or(a, b): "do a|=b on each field of a, recursively" for name in a.dtype.names: (af, bf) = (a[name], b[name]) - if af.dtype.names: + if af.dtype.names is not None: _recursive_or(af, bf) else: af |= bf @@ -2962,7 +2962,7 @@ class MaskedArray(ndarray): if isinstance(obj, ndarray): # XX: This looks like a bug -- shouldn't it check self.dtype # instead? - if obj.dtype.names: + if obj.dtype.names is not None: _mask = getmaskarray(obj) else: _mask = getmask(obj) @@ -3011,7 +3011,7 @@ class MaskedArray(ndarray): # When _mask.shape is not writable (because it's a void) pass # Finalize the fill_value for structured arrays - if self.dtype.names: + if self.dtype.names is not None: if self._fill_value is None: self._fill_value = _check_fill_value(None, self.dtype) return @@ -3295,15 +3295,14 @@ class MaskedArray(ndarray): return _dtype = _data.dtype - nbfields = len(_dtype.names or ()) if value is masked: # The mask wasn't set: create a full version. if _mask is nomask: _mask = self._mask = make_mask_none(self.shape, _dtype) # Now, set the mask to its value. - if nbfields: - _mask[indx] = tuple([True] * nbfields) + if _dtype.names is not None: + _mask[indx] = tuple([True] * len(_dtype.names)) else: _mask[indx] = True return @@ -3312,8 +3311,8 @@ class MaskedArray(ndarray): dval = getattr(value, '_data', value) # Get the _mask part of the new value mval = getmask(value) - if nbfields and mval is nomask: - mval = tuple([False] * nbfields) + if _dtype.names is not None and mval is nomask: + mval = tuple([False] * len(_dtype.names)) if _mask is nomask: # Set the data, then the mask _data[indx] = dval @@ -3328,7 +3327,7 @@ class MaskedArray(ndarray): indx = indx * umath.logical_not(_mask) _data[indx] = dval else: - if nbfields: + if _dtype.names is not None: err_msg = "Flexible 'hard' masks are not yet supported." raise NotImplementedError(err_msg) mindx = mask_or(_mask[indx], mval, copy=True) @@ -3709,7 +3708,7 @@ class MaskedArray(ndarray): if self is masked_singleton: return np.asanyarray(fill_value) - if m.dtype.names: + if m.dtype.names is not None: result = self._data.copy('K') _recursive_filled(result, self._mask, fill_value) elif not m.any(): @@ -3979,7 +3978,7 @@ class MaskedArray(ndarray): mask = mask_or(smask, omask, copy=True) odata = getdata(other) - if mask.dtype.names: + if mask.dtype.names is not None: # For possibly masked structured arrays we need to be careful, # since the standard structured array comparison will use all # fields, masked or not. To avoid masked fields influencing the diff --git a/numpy/ma/tests/test_core.py b/numpy/ma/tests/test_core.py index 67a9186a8..a08a0d956 100644 --- a/numpy/ma/tests/test_core.py +++ b/numpy/ma/tests/test_core.py @@ -514,8 +514,6 @@ class TestMaskedArray(object): fill_value=999999)''') ) - - def test_str_repr_legacy(self): oldopts = np.get_printoptions() np.set_printoptions(legacy='1.13') @@ -788,7 +786,6 @@ class TestMaskedArray(object): control = "(0, [[--, 0.0, --], [0.0, 0.0, --]], 0.0)" assert_equal(str(t_2d0), control) - def test_flatten_structured_array(self): # Test flatten_structured_array on arrays # On ndarray @@ -3174,18 +3171,13 @@ class TestMaskedArrayMethods(object): assert_equal(test.mask, mask_first.mask) # Test sort on dtype with subarray (gh-8069) + # Just check that the sort does not error, structured array subarrays + # are treated as byte strings and that leads to differing behavior + # depending on endianess and `endwith`. dt = np.dtype([('v', int, 2)]) a = a.view(dt) - mask_last = mask_last.view(dt) - mask_first = mask_first.view(dt) - test = sort(a) - assert_equal(test, mask_last) - assert_equal(test.mask, mask_last.mask) - test = sort(a, endwith=False) - assert_equal(test, mask_first) - assert_equal(test.mask, mask_first.mask) def test_argsort(self): # Test argsort @@ -5022,3 +5014,18 @@ def test_astype(): x_f2 = np.array(x, dtype=x.dtype, order='F', subok=True) assert_(x_f2.flags.f_contiguous) assert_(x_f2.mask.flags.f_contiguous) + + +def test_fieldless_void(): + dt = np.dtype([]) # a void dtype with no fields + x = np.empty(4, dt) + + # these arrays contain no values, so there's little to test - but this + # shouldn't crash + mx = np.ma.array(x) + assert_equal(mx.dtype, x.dtype) + assert_equal(mx.shape, x.shape) + + mx = np.ma.array(x, mask=x) + assert_equal(mx.dtype, x.dtype) + assert_equal(mx.shape, x.shape) diff --git a/numpy/polynomial/_polybase.py b/numpy/polynomial/_polybase.py index 78392d2a2..dc72e7661 100644 --- a/numpy/polynomial/_polybase.py +++ b/numpy/polynomial/_polybase.py @@ -9,7 +9,7 @@ abc module from the stdlib, hence it is only available for Python >= 2.6. from __future__ import division, absolute_import, print_function from abc import ABCMeta, abstractmethod, abstractproperty -from numbers import Number +import numbers import numpy as np from . import polyutils as pu @@ -17,7 +17,7 @@ from . import polyutils as pu __all__ = ['ABCPolyBase'] class ABCPolyBase(object): - """An abstract base class for series classes. + """An abstract base class for immutable series classes. ABCPolyBase provides the standard Python numerical methods '+', '-', '*', '//', '%', 'divmod', '**', and '()' along with the @@ -82,6 +82,10 @@ class ABCPolyBase(object): def nickname(self): pass + @abstractproperty + def basis_name(self): + pass + @abstractmethod def _add(self): pass @@ -273,6 +277,89 @@ class ABCPolyBase(object): name = self.nickname return format % (name, coef) + @classmethod + def _repr_latex_term(cls, i, arg_str, needs_parens): + if cls.basis_name is None: + raise NotImplementedError( + "Subclasses must define either a basis name, or override " + "_repr_latex_term(i, arg_str, needs_parens)") + # since we always add parens, we don't care if the expression needs them + return "{{{basis}}}_{{{i}}}({arg_str})".format( + basis=cls.basis_name, i=i, arg_str=arg_str + ) + + @staticmethod + def _repr_latex_scalar(x): + # TODO: we're stuck with disabling math formatting until we handle + # exponents in this function + return r'\text{{{}}}'.format(x) + + def _repr_latex_(self): + # get the scaled argument string to the basis functions + off, scale = self.mapparms() + if off == 0 and scale == 1: + term = 'x' + needs_parens = False + elif scale == 1: + term = '{} + x'.format( + self._repr_latex_scalar(off) + ) + needs_parens = True + elif off == 0: + term = '{}x'.format( + self._repr_latex_scalar(scale) + ) + needs_parens = True + else: + term = '{} + {}x'.format( + self._repr_latex_scalar(off), + self._repr_latex_scalar(scale) + ) + needs_parens = True + + # filter out uninteresting coefficients + filtered_coeffs = [ + (i, c) + for i, c in enumerate(self.coef) + # if not (c == 0) # handle NaN + ] + + mute = r"\color{{LightGray}}{{{}}}".format + + parts = [] + for i, c in enumerate(self.coef): + # prevent duplication of + and - signs + if i == 0: + coef_str = '{}'.format(self._repr_latex_scalar(c)) + elif not isinstance(c, numbers.Real): + coef_str = ' + ({})'.format(self._repr_latex_scalar(c)) + elif not np.signbit(c): + coef_str = ' + {}'.format(self._repr_latex_scalar(c)) + else: + coef_str = ' - {}'.format(self._repr_latex_scalar(-c)) + + # produce the string for the term + term_str = self._repr_latex_term(i, term, needs_parens) + if term_str == '1': + part = coef_str + else: + part = r'{}\,{}'.format(coef_str, term_str) + + if c == 0: + part = mute(part) + + parts.append(part) + + if parts: + body = ''.join(parts) + else: + # in case somehow there are no coefficients at all + body = '0' + + return r'$x \mapsto {}$'.format(body) + + + # Pickle and copy def __getstate__(self): @@ -338,7 +425,7 @@ class ABCPolyBase(object): # there is no true divide if the rhs is not a Number, although it # could return the first n elements of an infinite series. # It is hard to see where n would come from, though. - if not isinstance(other, Number) or isinstance(other, bool): + if not isinstance(other, numbers.Number) or isinstance(other, bool): form = "unsupported types for true division: '%s', '%s'" raise TypeError(form % (type(self), type(other))) return self.__floordiv__(other) @@ -425,9 +512,6 @@ class ABCPolyBase(object): rem = self.__class__(rem, self.domain, self.window) return quo, rem - # Enhance me - # some augmented arithmetic operations could be added here - def __eq__(self, other): res = (isinstance(other, self.__class__) and np.all(self.domain == other.domain) and @@ -773,7 +857,9 @@ class ABCPolyBase(object): ------- new_series : series A series that represents the least squares fit to the data and - has the domain specified in the call. + has the domain and window specified in the call. If the + coefficients for the unscaled and unshifted basis polynomials are + of interest, do ``new_series.convert().coef``. [resid, rank, sv, rcond] : list These values are only returned if `full` = True diff --git a/numpy/polynomial/chebyshev.py b/numpy/polynomial/chebyshev.py index 310c711ef..f14ed988d 100644 --- a/numpy/polynomial/chebyshev.py +++ b/numpy/polynomial/chebyshev.py @@ -21,9 +21,10 @@ Arithmetic ---------- - `chebadd` -- add two Chebyshev series. - `chebsub` -- subtract one Chebyshev series from another. +- `chebmulx` -- multiply a Chebyshev series in ``P_i(x)`` by ``x``. - `chebmul` -- multiply two Chebyshev series. - `chebdiv` -- divide one Chebyshev series by another. -- `chebpow` -- raise a Chebyshev series to an positive integer power +- `chebpow` -- raise a Chebyshev series to a positive integer power. - `chebval` -- evaluate a Chebyshev series at given points. - `chebval2d` -- evaluate a 2D Chebyshev series at given points. - `chebval3d` -- evaluate a 3D Chebyshev series at given points. @@ -579,7 +580,7 @@ def chebadd(c1, c2): See Also -------- - chebsub, chebmul, chebdiv, chebpow + chebsub, chebmulx, chebmul, chebdiv, chebpow Notes ----- @@ -629,7 +630,7 @@ def chebsub(c1, c2): See Also -------- - chebadd, chebmul, chebdiv, chebpow + chebadd, chebmulx, chebmul, chebdiv, chebpow Notes ----- @@ -684,6 +685,12 @@ def chebmulx(c): .. versionadded:: 1.5.0 + Examples + -------- + >>> from numpy.polynomial import chebyshev as C + >>> C.chebmulx([1,2,3]) + array([ 1., 2.5, 3., 1.5, 2.]) + """ # c is a trimmed copy [c] = pu.as_series([c]) @@ -722,7 +729,7 @@ def chebmul(c1, c2): See Also -------- - chebadd, chebsub, chebdiv, chebpow + chebadd, chebsub, chebmulx, chebdiv, chebpow Notes ----- @@ -773,7 +780,7 @@ def chebdiv(c1, c2): See Also -------- - chebadd, chebsub, chebmul, chebpow + chebadd, chebsub, chemulx, chebmul, chebpow Notes ----- @@ -841,10 +848,13 @@ def chebpow(c, pow, maxpower=16): See Also -------- - chebadd, chebsub, chebmul, chebdiv + chebadd, chebsub, chebmulx, chebmul, chebdiv Examples -------- + >>> from numpy.polynomial import chebyshev as C + >>> C.chebpow([1, 2, 3, 4], 2) + array([15.5, 22. , 16. , 14. , 12.5, 12. , 8. ]) """ # c is a trimmed copy @@ -2188,3 +2198,4 @@ class Chebyshev(ABCPolyBase): nickname = 'cheb' domain = np.array(chebdomain) window = np.array(chebdomain) + basis_name = 'T' diff --git a/numpy/polynomial/hermite.py b/numpy/polynomial/hermite.py index 75c7e6832..2aed4b34f 100644 --- a/numpy/polynomial/hermite.py +++ b/numpy/polynomial/hermite.py @@ -16,11 +16,12 @@ Constants Arithmetic ---------- -- `hermmulx` -- multiply a Hermite series in ``P_i(x)`` by ``x``. - `hermadd` -- add two Hermite series. - `hermsub` -- subtract one Hermite series from another. +- `hermmulx` -- multiply a Hermite series in ``P_i(x)`` by ``x``. - `hermmul` -- multiply two Hermite series. - `hermdiv` -- divide one Hermite series by another. +- `hermpow` -- raise a Hermite series to a positive integer power. - `hermval` -- evaluate a Hermite series at given points. - `hermval2d` -- evaluate a 2D Hermite series at given points. - `hermval3d` -- evaluate a 3D Hermite series at given points. @@ -323,7 +324,7 @@ def hermadd(c1, c2): See Also -------- - hermsub, hermmul, hermdiv, hermpow + hermsub, hermmulx, hermmul, hermdiv, hermpow Notes ----- @@ -371,7 +372,7 @@ def hermsub(c1, c2): See Also -------- - hermadd, hermmul, hermdiv, hermpow + hermadd, hermmulx, hermmul, hermdiv, hermpow Notes ----- @@ -417,6 +418,10 @@ def hermmulx(c): out : ndarray Array representing the result of the multiplication. + See Also + -------- + hermadd, hermsub, hermmul, hermdiv, hermpow + Notes ----- The multiplication uses the recursion relationship for Hermite @@ -469,7 +474,7 @@ def hermmul(c1, c2): See Also -------- - hermadd, hermsub, hermdiv, hermpow + hermadd, hermsub, hermmulx, hermdiv, hermpow Notes ----- @@ -537,7 +542,7 @@ def hermdiv(c1, c2): See Also -------- - hermadd, hermsub, hermmul, hermpow + hermadd, hermsub, hermmulx, hermmul, hermpow Notes ----- @@ -606,7 +611,7 @@ def hermpow(c, pow, maxpower=16): See Also -------- - hermadd, hermsub, hermmul, hermdiv + hermadd, hermsub, hermmulx, hermmul, hermdiv Examples -------- @@ -1851,3 +1856,4 @@ class Hermite(ABCPolyBase): nickname = 'herm' domain = np.array(hermdomain) window = np.array(hermdomain) + basis_name = 'H' diff --git a/numpy/polynomial/hermite_e.py b/numpy/polynomial/hermite_e.py index 125364a11..d4520ad6c 100644 --- a/numpy/polynomial/hermite_e.py +++ b/numpy/polynomial/hermite_e.py @@ -16,11 +16,12 @@ Constants Arithmetic ---------- -- `hermemulx` -- multiply a Hermite_e series in ``P_i(x)`` by ``x``. - `hermeadd` -- add two Hermite_e series. - `hermesub` -- subtract one Hermite_e series from another. +- `hermemulx` -- multiply a Hermite_e series in ``P_i(x)`` by ``x``. - `hermemul` -- multiply two Hermite_e series. - `hermediv` -- divide one Hermite_e series by another. +- `hermepow` -- raise a Hermite_e series to a positive integer power. - `hermeval` -- evaluate a Hermite_e series at given points. - `hermeval2d` -- evaluate a 2D Hermite_e series at given points. - `hermeval3d` -- evaluate a 3D Hermite_e series at given points. @@ -324,7 +325,7 @@ def hermeadd(c1, c2): See Also -------- - hermesub, hermemul, hermediv, hermepow + hermesub, hermemulx, hermemul, hermediv, hermepow Notes ----- @@ -372,7 +373,7 @@ def hermesub(c1, c2): See Also -------- - hermeadd, hermemul, hermediv, hermepow + hermeadd, hermemulx, hermemul, hermediv, hermepow Notes ----- @@ -470,7 +471,7 @@ def hermemul(c1, c2): See Also -------- - hermeadd, hermesub, hermediv, hermepow + hermeadd, hermesub, hermemulx, hermediv, hermepow Notes ----- @@ -538,7 +539,7 @@ def hermediv(c1, c2): See Also -------- - hermeadd, hermesub, hermemul, hermepow + hermeadd, hermesub, hermemulx, hermemul, hermepow Notes ----- @@ -605,7 +606,7 @@ def hermepow(c, pow, maxpower=16): See Also -------- - hermeadd, hermesub, hermemul, hermediv + hermeadd, hermesub, hermemulx, hermemul, hermediv Examples -------- @@ -1848,3 +1849,4 @@ class HermiteE(ABCPolyBase): nickname = 'herme' domain = np.array(hermedomain) window = np.array(hermedomain) + basis_name = 'He' diff --git a/numpy/polynomial/laguerre.py b/numpy/polynomial/laguerre.py index 2b9757ab8..a116d20a7 100644 --- a/numpy/polynomial/laguerre.py +++ b/numpy/polynomial/laguerre.py @@ -16,11 +16,12 @@ Constants Arithmetic ---------- -- `lagmulx` -- multiply a Laguerre series in ``P_i(x)`` by ``x``. - `lagadd` -- add two Laguerre series. - `lagsub` -- subtract one Laguerre series from another. +- `lagmulx` -- multiply a Laguerre series in ``P_i(x)`` by ``x``. - `lagmul` -- multiply two Laguerre series. - `lagdiv` -- divide one Laguerre series by another. +- `lagpow` -- raise a Laguerre series to a positive integer power. - `lagval` -- evaluate a Laguerre series at given points. - `lagval2d` -- evaluate a 2D Laguerre series at given points. - `lagval3d` -- evaluate a 3D Laguerre series at given points. @@ -320,7 +321,7 @@ def lagadd(c1, c2): See Also -------- - lagsub, lagmul, lagdiv, lagpow + lagsub, lagmulx, lagmul, lagdiv, lagpow Notes ----- @@ -369,7 +370,7 @@ def lagsub(c1, c2): See Also -------- - lagadd, lagmul, lagdiv, lagpow + lagadd, lagmulx, lagmul, lagdiv, lagpow Notes ----- @@ -415,6 +416,10 @@ def lagmulx(c): out : ndarray Array representing the result of the multiplication. + See Also + -------- + lagadd, lagsub, lagmul, lagdiv, lagpow + Notes ----- The multiplication uses the recursion relationship for Laguerre @@ -468,7 +473,7 @@ def lagmul(c1, c2): See Also -------- - lagadd, lagsub, lagdiv, lagpow + lagadd, lagsub, lagmulx, lagdiv, lagpow Notes ----- @@ -536,7 +541,7 @@ def lagdiv(c1, c2): See Also -------- - lagadd, lagsub, lagmul, lagpow + lagadd, lagsub, lagmulx, lagmul, lagpow Notes ----- @@ -603,7 +608,7 @@ def lagpow(c, pow, maxpower=16): See Also -------- - lagadd, lagsub, lagmul, lagdiv + lagadd, lagsub, lagmulx, lagmul, lagdiv Examples -------- @@ -1801,3 +1806,4 @@ class Laguerre(ABCPolyBase): nickname = 'lag' domain = np.array(lagdomain) window = np.array(lagdomain) + basis_name = 'L' diff --git a/numpy/polynomial/legendre.py b/numpy/polynomial/legendre.py index a83c5735f..e9c24594b 100644 --- a/numpy/polynomial/legendre.py +++ b/numpy/polynomial/legendre.py @@ -27,12 +27,12 @@ Arithmetic .. autosummary:: :toctree: generated/ - legmulx multiply a Legendre series in P_i(x) by x. legadd add two Legendre series. legsub subtract one Legendre series from another. + legmulx multiply a Legendre series in ``P_i(x)`` by ``x``. legmul multiply two Legendre series. legdiv divide one Legendre series by another. - legpow raise a Legendre series to an positive integer power + legpow raise a Legendre series to a positive integer power. legval evaluate a Legendre series at given points. legval2d evaluate a 2D Legendre series at given points. legval3d evaluate a 3D Legendre series at given points. @@ -351,7 +351,7 @@ def legadd(c1, c2): See Also -------- - legsub, legmul, legdiv, legpow + legsub, legmulx, legmul, legdiv, legpow Notes ----- @@ -401,7 +401,7 @@ def legsub(c1, c2): See Also -------- - legadd, legmul, legdiv, legpow + legadd, legmulx, legmul, legdiv, legpow Notes ----- @@ -451,6 +451,10 @@ def legmulx(c): out : ndarray Array representing the result of the multiplication. + See Also + -------- + legadd, legmul, legmul, legdiv, legpow + Notes ----- The multiplication uses the recursion relationship for Legendre @@ -460,6 +464,12 @@ def legmulx(c): xP_i(x) = ((i + 1)*P_{i + 1}(x) + i*P_{i - 1}(x))/(2i + 1) + Examples + -------- + >>> from numpy.polynomial import legendre as L + >>> L.legmulx([1,2,3]) + array([ 0.66666667, 2.2, 1.33333333, 1.8]) + """ # c is a trimmed copy [c] = pu.as_series([c]) @@ -500,7 +510,7 @@ def legmul(c1, c2): See Also -------- - legadd, legsub, legdiv, legpow + legadd, legsub, legmulx, legdiv, legpow Notes ----- @@ -570,7 +580,7 @@ def legdiv(c1, c2): See Also -------- - legadd, legsub, legmul, legpow + legadd, legsub, legmulx, legmul, legpow Notes ----- @@ -640,7 +650,7 @@ def legpow(c, pow, maxpower=16): See Also -------- - legadd, legsub, legmul, legdiv + legadd, legsub, legmulx, legmul, legdiv Examples -------- @@ -1831,3 +1841,4 @@ class Legendre(ABCPolyBase): nickname = 'leg' domain = np.array(legdomain) window = np.array(legdomain) + basis_name = 'P' diff --git a/numpy/polynomial/polynomial.py b/numpy/polynomial/polynomial.py index adbf30234..259cd31f5 100644 --- a/numpy/polynomial/polynomial.py +++ b/numpy/polynomial/polynomial.py @@ -18,9 +18,10 @@ Arithmetic ---------- - `polyadd` -- add two polynomials. - `polysub` -- subtract one polynomial from another. +- `polymulx` -- multiply a polynomial in ``P_i(x)`` by ``x``. - `polymul` -- multiply two polynomials. - `polydiv` -- divide one polynomial by another. -- `polypow` -- raise a polynomial to an positive integer power +- `polypow` -- raise a polynomial to a positive integer power. - `polyval` -- evaluate a polynomial at given points. - `polyval2d` -- evaluate a 2D polynomial at given points. - `polyval3d` -- evaluate a 3D polynomial at given points. @@ -224,7 +225,7 @@ def polyadd(c1, c2): See Also -------- - polysub, polymul, polydiv, polypow + polysub, polymulx, polymul, polydiv, polypow Examples -------- @@ -269,7 +270,7 @@ def polysub(c1, c2): See Also -------- - polyadd, polymul, polydiv, polypow + polyadd, polymulx, polymul, polydiv, polypow Examples -------- @@ -312,6 +313,10 @@ def polymulx(c): out : ndarray Array representing the result of the multiplication. + See Also + -------- + polyadd, polysub, polymul, polydiv, polypow + Notes ----- @@ -351,7 +356,7 @@ def polymul(c1, c2): See Also -------- - polyadd, polysub, polydiv, polypow + polyadd, polysub, polymulx, polydiv, polypow Examples -------- @@ -388,7 +393,7 @@ def polydiv(c1, c2): See Also -------- - polyadd, polysub, polymul, polypow + polyadd, polysub, polymulx, polymul, polypow Examples -------- @@ -450,10 +455,13 @@ def polypow(c, pow, maxpower=None): See Also -------- - polyadd, polysub, polymul, polydiv + polyadd, polysub, polymulx, polymul, polydiv Examples -------- + >>> from numpy.polynomial import polynomial as P + >>> P.polypow([1,2,3], 2) + array([ 1., 4., 10., 12., 9.]) """ # c is a trimmed copy @@ -1643,3 +1651,15 @@ class Polynomial(ABCPolyBase): nickname = 'poly' domain = np.array(polydomain) window = np.array(polydomain) + basis_name = None + + @staticmethod + def _repr_latex_term(i, arg_str, needs_parens): + if needs_parens: + arg_str = r'\left({}\right)'.format(arg_str) + if i == 0: + return '1' + elif i == 1: + return arg_str + else: + return '{}^{{{}}}'.format(arg_str, i) diff --git a/numpy/polynomial/tests/test_chebyshev.py b/numpy/polynomial/tests/test_chebyshev.py index 439dfa08d..7fb7492c6 100644 --- a/numpy/polynomial/tests/test_chebyshev.py +++ b/numpy/polynomial/tests/test_chebyshev.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.chebyshev as cheb from numpy.polynomial.polynomial import polyval @@ -111,6 +113,15 @@ class TestArithmetic(object): res = cheb.chebadd(cheb.chebmul(quo, ci), rem) assert_equal(trim(res), trim(tgt), err_msg=msg) + def test_chebpow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(cheb.chebmul, [c]*j, np.array([1])) + res = cheb.chebpow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/polynomial/tests/test_classes.py b/numpy/polynomial/tests/test_classes.py index 738741668..15e24f92b 100644 --- a/numpy/polynomial/tests/test_classes.py +++ b/numpy/polynomial/tests/test_classes.py @@ -562,6 +562,56 @@ def test_ufunc_override(Poly): assert_raises(TypeError, np.add, x, p) + +class TestLatexRepr(object): + """Test the latex repr used by ipython """ + + def as_latex(self, obj): + # right now we ignore the formatting of scalars in our tests, since + # it makes them too verbose. Ideally, the formatting of scalars will + # be fixed such that tests below continue to pass + obj._repr_latex_scalar = lambda x: str(x) + try: + return obj._repr_latex_() + finally: + del obj._repr_latex_scalar + + def test_simple_polynomial(self): + # default input + p = Polynomial([1, 2, 3]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0 + 2.0\,x + 3.0\,x^{2}$') + + # translated input + p = Polynomial([1, 2, 3], domain=[-2, 0]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0 + 2.0\,\left(1.0 + x\right) + 3.0\,\left(1.0 + x\right)^{2}$') + + # scaled input + p = Polynomial([1, 2, 3], domain=[-0.5, 0.5]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0 + 2.0\,\left(2.0x\right) + 3.0\,\left(2.0x\right)^{2}$') + + # affine input + p = Polynomial([1, 2, 3], domain=[-1, 0]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0 + 2.0\,\left(1.0 + 2.0x\right) + 3.0\,\left(1.0 + 2.0x\right)^{2}$') + + def test_basis_func(self): + p = Chebyshev([1, 2, 3]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0\,{T}_{0}(x) + 2.0\,{T}_{1}(x) + 3.0\,{T}_{2}(x)$') + # affine input - check no surplus parens are added + p = Chebyshev([1, 2, 3], domain=[-1, 0]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0\,{T}_{0}(1.0 + 2.0x) + 2.0\,{T}_{1}(1.0 + 2.0x) + 3.0\,{T}_{2}(1.0 + 2.0x)$') + + def test_multichar_basis_func(self): + p = HermiteE([1, 2, 3]) + assert_equal(self.as_latex(p), + r'$x \mapsto 1.0\,{He}_{0}(x) + 2.0\,{He}_{1}(x) + 3.0\,{He}_{2}(x)$') + + # # Test class method that only exists for some classes # diff --git a/numpy/polynomial/tests/test_hermite.py b/numpy/polynomial/tests/test_hermite.py index 18c26af8f..1287ef3fe 100644 --- a/numpy/polynomial/tests/test_hermite.py +++ b/numpy/polynomial/tests/test_hermite.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.hermite as herm from numpy.polynomial.polynomial import polyval @@ -99,6 +101,15 @@ class TestArithmetic(object): res = herm.hermadd(herm.hermmul(quo, ci), rem) assert_equal(trim(res), trim(tgt), err_msg=msg) + def test_hermpow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(herm.hermmul, [c]*j, np.array([1])) + res = herm.hermpow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/polynomial/tests/test_hermite_e.py b/numpy/polynomial/tests/test_hermite_e.py index 58d74dae9..ccb44ad73 100644 --- a/numpy/polynomial/tests/test_hermite_e.py +++ b/numpy/polynomial/tests/test_hermite_e.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.hermite_e as herme from numpy.polynomial.polynomial import polyval @@ -99,6 +101,15 @@ class TestArithmetic(object): res = herme.hermeadd(herme.hermemul(quo, ci), rem) assert_equal(trim(res), trim(tgt), err_msg=msg) + def test_hermepow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(herme.hermemul, [c]*j, np.array([1])) + res = herme.hermepow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/polynomial/tests/test_laguerre.py b/numpy/polynomial/tests/test_laguerre.py index 3cb630e46..3ababec5e 100644 --- a/numpy/polynomial/tests/test_laguerre.py +++ b/numpy/polynomial/tests/test_laguerre.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.laguerre as lag from numpy.polynomial.polynomial import polyval @@ -96,6 +98,15 @@ class TestArithmetic(object): res = lag.lagadd(lag.lagmul(quo, ci), rem) assert_almost_equal(trim(res), trim(tgt), err_msg=msg) + def test_lagpow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(lag.lagmul, [c]*j, np.array([1])) + res = lag.lagpow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/polynomial/tests/test_legendre.py b/numpy/polynomial/tests/test_legendre.py index aeecd8775..a23086d59 100644 --- a/numpy/polynomial/tests/test_legendre.py +++ b/numpy/polynomial/tests/test_legendre.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.legendre as leg from numpy.polynomial.polynomial import polyval @@ -100,6 +102,15 @@ class TestArithmetic(object): res = leg.legadd(leg.legmul(quo, ci), rem) assert_equal(trim(res), trim(tgt), err_msg=msg) + def test_legpow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(leg.legmul, [c]*j, np.array([1])) + res = leg.legpow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/polynomial/tests/test_polynomial.py b/numpy/polynomial/tests/test_polynomial.py index 67728e35e..0c93be278 100644 --- a/numpy/polynomial/tests/test_polynomial.py +++ b/numpy/polynomial/tests/test_polynomial.py @@ -3,6 +3,8 @@ """ from __future__ import division, absolute_import, print_function +from functools import reduce + import numpy as np import numpy.polynomial.polynomial as poly from numpy.testing import ( @@ -102,6 +104,15 @@ class TestArithmetic(object): res = poly.polyadd(poly.polymul(quo, ci), rem) assert_equal(res, tgt, err_msg=msg) + def test_polypow(self): + for i in range(5): + for j in range(5): + msg = "At i=%d, j=%d" % (i, j) + c = np.arange(i + 1) + tgt = reduce(poly.polymul, [c]*j, np.array([1])) + res = poly.polypow(c, j) + assert_equal(trim(res), trim(tgt), err_msg=msg) + class TestEvaluation(object): # coefficients of 1 + 2*x + 3*x**2 diff --git a/numpy/random/__init__.py b/numpy/random/__init__.py index 82aefce5f..965ab5ea9 100644 --- a/numpy/random/__init__.py +++ b/numpy/random/__init__.py @@ -6,17 +6,15 @@ Random Number Generation ==================== ========================================================= Utility functions ============================================================================== -random Uniformly distributed values of a given shape. +random_sample Uniformly distributed floats over ``[0, 1)``. +random Alias for `random_sample`. bytes Uniformly distributed random bytes. random_integers Uniformly distributed integers in a given range. -random_sample Uniformly distributed floats in a given range. -random Alias for random_sample -ranf Alias for random_sample -sample Alias for random_sample -choice Generate a weighted random sample from a given array-like permutation Randomly permute a sequence / generate a random sequence. shuffle Randomly permute a sequence in place. seed Seed the random number generator. +choice Random sample from 1-D array. + ==================== ========================================================= ==================== ========================================================= @@ -90,9 +88,55 @@ from __future__ import division, absolute_import, print_function import warnings -# To get sub-modules -from .info import __doc__, __all__ - +__all__ = [ + '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_integers', + 'random_sample', + 'rayleigh', + 'seed', + 'set_state', + 'shuffle', + 'standard_cauchy', + 'standard_exponential', + 'standard_gamma', + 'standard_normal', + 'standard_t', + 'triangular', + 'uniform', + 'vonmises', + 'wald', + 'weibull', + 'zipf' +] with warnings.catch_warnings(): warnings.filterwarnings("ignore", message="numpy.ndarray size changed") diff --git a/numpy/random/info.py b/numpy/random/info.py index be9c8d9bd..b9fd7f26a 100644 --- a/numpy/random/info.py +++ b/numpy/random/info.py @@ -1,139 +1,5 @@ -""" -======================== -Random Number Generation -======================== - -==================== ========================================================= -Utility functions -============================================================================== -random_sample Uniformly distributed floats over ``[0, 1)``. -random Alias for `random_sample`. -bytes Uniformly distributed random bytes. -random_integers Uniformly distributed integers in a given range. -permutation Randomly permute a sequence / generate a random sequence. -shuffle Randomly permute a sequence in place. -seed Seed the random number generator. -choice Random sample from 1-D array. - -==================== ========================================================= - -==================== ========================================================= -Compatibility functions -============================================================================== -rand Uniformly distributed values. -randn Normally distributed values. -ranf Uniformly distributed floating point numbers. -randint Uniformly distributed integers in a given range. -==================== ========================================================= - -==================== ========================================================= -Univariate distributions -============================================================================== -beta Beta distribution over ``[0, 1]``. -binomial Binomial distribution. -chisquare :math:`\\chi^2` distribution. -exponential Exponential distribution. -f F (Fisher-Snedecor) distribution. -gamma Gamma distribution. -geometric Geometric distribution. -gumbel Gumbel distribution. -hypergeometric Hypergeometric distribution. -laplace Laplace distribution. -logistic Logistic distribution. -lognormal Log-normal distribution. -logseries Logarithmic series distribution. -negative_binomial Negative binomial distribution. -noncentral_chisquare Non-central chi-square distribution. -noncentral_f Non-central F distribution. -normal Normal / Gaussian distribution. -pareto Pareto distribution. -poisson Poisson distribution. -power Power distribution. -rayleigh Rayleigh distribution. -triangular Triangular distribution. -uniform Uniform distribution. -vonmises Von Mises circular distribution. -wald Wald (inverse Gaussian) distribution. -weibull Weibull distribution. -zipf Zipf's distribution over ranked data. -==================== ========================================================= - -==================== ========================================================= -Multivariate distributions -============================================================================== -dirichlet Multivariate generalization of Beta distribution. -multinomial Multivariate generalization of the binomial distribution. -multivariate_normal Multivariate generalization of the normal distribution. -==================== ========================================================= - -==================== ========================================================= -Standard distributions -============================================================================== -standard_cauchy Standard Cauchy-Lorentz distribution. -standard_exponential Standard exponential distribution. -standard_gamma Standard Gamma distribution. -standard_normal Standard normal distribution. -standard_t Standard Student's t-distribution. -==================== ========================================================= - -==================== ========================================================= -Internal functions -============================================================================== -get_state Get tuple representing internal state of generator. -set_state Set state of generator. -==================== ========================================================= - -""" from __future__ import division, absolute_import, print_function -depends = ['core'] +from .. import __doc__ -__all__ = [ - '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_integers', - 'random_sample', - 'rayleigh', - 'seed', - 'set_state', - 'shuffle', - 'standard_cauchy', - 'standard_exponential', - 'standard_gamma', - 'standard_normal', - 'standard_t', - 'triangular', - 'uniform', - 'vonmises', - 'wald', - 'weibull', - 'zipf' -] +depends = ['core'] diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx index ec759fdfb..5097ad88f 100644 --- a/numpy/random/mtrand/mtrand.pyx +++ b/numpy/random/mtrand/mtrand.pyx @@ -2505,7 +2505,7 @@ cdef class RandomState: Examples -------- From Dalgaard page 83 [1]_, suppose the daily energy intake for 11 - women in Kj is: + women in kilojoules (kJ) is: >>> intake = np.array([5260., 5470, 5640, 6180, 6390, 6515, 6805, 7515, \\ ... 7515, 8230, 8770]) @@ -4198,12 +4198,12 @@ cdef class RandomState: ----- The probability density for the Hypergeometric distribution is - .. math:: P(x) = \\frac{\\binom{m}{n}\\binom{N-m}{n-x}}{\\binom{N}{n}}, + .. math:: P(x) = \\frac{\\binom{g}{x}\\binom{b}{n-x}}{\\binom{g+b}{n}}, - where :math:`0 \\le x \\le m` and :math:`n+m-N \\le x \\le n` + where :math:`0 \\le x \\le n` and :math:`n-b \\le x \\le g` - for P(x) the probability of x successes, n = ngood, m = nbad, and - N = number of samples. + for P(x) the probability of x successes, g = ngood, b = nbad, and + n = number of samples. Consider an urn with black and white marbles in it, ngood of them black and nbad are white. If you draw nsample balls without diff --git a/numpy/random/tests/test_random.py b/numpy/random/tests/test_random.py index 2e0885024..8328c69c0 100644 --- a/numpy/random/tests/test_random.py +++ b/numpy/random/tests/test_random.py @@ -1454,7 +1454,6 @@ class TestBroadcast(object): assert_raises(ValueError, zipf, np.nan) assert_raises(ValueError, zipf, [0, 0, np.nan]) - def test_geometric(self): p = [0.5] bad_p_one = [-1] diff --git a/numpy/testing/_private/nosetester.py b/numpy/testing/_private/nosetester.py index c2cf58377..1728d9d1f 100644 --- a/numpy/testing/_private/nosetester.py +++ b/numpy/testing/_private/nosetester.py @@ -338,12 +338,14 @@ class NoseTester(object): Identifies the tests to run. This can be a string to pass to the nosetests executable with the '-A' option, or one of several special values. Special values are: + * 'fast' - the default - which corresponds to the ``nosetests -A`` option of 'not slow'. * 'full' - fast (as above) and slow tests as in the 'no -A' option to nosetests - this is the same as ''. * None or '' - run all tests. - attribute_identifier - string passed directly to nosetests as '-A'. + * attribute_identifier - string passed directly to nosetests as '-A'. + verbose : int, optional Verbosity value for test outputs, in the range 1-10. Default is 1. extra_argv : list, optional @@ -352,16 +354,14 @@ class NoseTester(object): If True, run doctests in module. Default is False. coverage : bool, optional If True, report coverage of NumPy code. Default is False. - (This requires the `coverage module: - <http://nedbatchelder.com/code/modules/coverage.html>`_). + (This requires the + `coverage module <https://nedbatchelder.com/code/modules/coveragehtml>`_). raise_warnings : None, str or sequence of warnings, optional This specifies which warnings to configure as 'raise' instead - of being shown once during the test execution. Valid strings are: - - - "develop" : equals ``(Warning,)`` - - "release" : equals ``()``, don't raise on any warnings. + of being shown once during the test execution. Valid strings are: - The default is to use the class initialization value. + * "develop" : equals ``(Warning,)`` + * "release" : equals ``()``, do not raise on any warnings. timer : bool or int, optional Timing of individual tests with ``nose-timer`` (which needs to be installed). If True, time tests and report on all of them. @@ -489,12 +489,14 @@ class NoseTester(object): Identifies the benchmarks to run. This can be a string to pass to the nosetests executable with the '-A' option, or one of several special values. Special values are: + * 'fast' - the default - which corresponds to the ``nosetests -A`` option of 'not slow'. * 'full' - fast (as above) and slow benchmarks as in the 'no -A' option to nosetests - this is the same as ''. * None or '' - run all tests. - attribute_identifier - string passed directly to nosetests as '-A'. + * attribute_identifier - string passed directly to nosetests as '-A'. + verbose : int, optional Verbosity value for benchmark outputs, in the range 1-10. Default is 1. extra_argv : list, optional diff --git a/numpy/testing/_private/utils.py b/numpy/testing/_private/utils.py index 0e2f8ba91..a3832fcde 100644 --- a/numpy/testing/_private/utils.py +++ b/numpy/testing/_private/utils.py @@ -687,6 +687,8 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True, equal_inf=True): __tracebackhide__ = True # Hide traceback for py.test from numpy.core import array, isnan, inf, bool_ + from numpy.core.fromnumeric import all as npall + x = array(x, copy=False, subok=True) y = array(y, copy=False, subok=True) @@ -697,14 +699,21 @@ def assert_array_compare(comparison, x, y, err_msg='', verbose=True, return x.dtype.char in "Mm" def func_assert_same_pos(x, y, func=isnan, hasval='nan'): - """Handling nan/inf: combine results of running func on x and y, - checking that they are True at the same locations.""" - # Both the != True comparison here and the cast to bool_ at - # the end are done to deal with `masked`, which cannot be - # compared usefully, and for which .all() yields masked. + """Handling nan/inf. + + Combine results of running func on x and y, checking that they are True + at the same locations. + + """ + # Both the != True comparison here and the cast to bool_ at the end are + # done to deal with `masked`, which cannot be compared usefully, and + # for which np.all yields masked. The use of the function np.all is + # for back compatibility with ndarray subclasses that changed the + # return values of the all method. We are not committed to supporting + # such subclasses, but some used to work. x_id = func(x) y_id = func(y) - if (x_id == y_id).all() != True: + if npall(x_id == y_id) != True: msg = build_err_msg([x, y], err_msg + '\nx and y %s location mismatch:' % (hasval), verbose=verbose, header=header, diff --git a/numpy/testing/tests/test_decorators.py b/numpy/testing/tests/test_decorators.py index ea684140d..d00820b80 100644 --- a/numpy/testing/tests/test_decorators.py +++ b/numpy/testing/tests/test_decorators.py @@ -53,7 +53,6 @@ class TestNoseDecorators(object): assert_(f_istest.__test__) assert_(not f_isnottest.__test__) - def test_skip_functions_hardcoded(self): @dec.skipif(True) def f1(x): diff --git a/numpy/testing/tests/test_utils.py b/numpy/testing/tests/test_utils.py index 84d310992..2c60e2867 100644 --- a/numpy/testing/tests/test_utils.py +++ b/numpy/testing/tests/test_utils.py @@ -1391,7 +1391,6 @@ class TestAssertNoGcCycles(object): assert_no_gc_cycles(no_cycle) - def test_asserts(self): def make_cycle(): a = [] @@ -1406,7 +1405,6 @@ class TestAssertNoGcCycles(object): with assert_raises(AssertionError): assert_no_gc_cycles(make_cycle) - def test_fails(self): """ Test that in cases where the garbage cannot be collected, we raise an diff --git a/numpy/tests/test_ctypeslib.py b/numpy/tests/test_ctypeslib.py index 75ce9c8ca..675f8d242 100644 --- a/numpy/tests/test_ctypeslib.py +++ b/numpy/tests/test_ctypeslib.py @@ -12,11 +12,11 @@ try: cdll = None if hasattr(sys, 'gettotalrefcount'): try: - cdll = load_library('multiarray_d', np.core.multiarray.__file__) + cdll = load_library('_multiarray_umath_d', np.core._multiarray_umath.__file__) except OSError: pass if cdll is None: - cdll = load_library('multiarray', np.core.multiarray.__file__) + cdll = load_library('_multiarray_umath', np.core._multiarray_umath.__file__) _HAS_CTYPE = True except ImportError: _HAS_CTYPE = False @@ -30,7 +30,7 @@ class TestLoadLibrary(object): def test_basic(self): try: # Should succeed - load_library('multiarray', np.core.multiarray.__file__) + load_library('_multiarray_umath', np.core._multiarray_umath.__file__) except ImportError as e: msg = ("ctypes is not available on this python: skipping the test" " (import error was: %s)" % str(e)) @@ -43,7 +43,7 @@ class TestLoadLibrary(object): try: so = get_shared_lib_extension(is_python_ext=True) # Should succeed - load_library('multiarray%s' % so, np.core.multiarray.__file__) + load_library('_multiarray_umath%s' % so, np.core._multiarray_umath.__file__) except ImportError: print("No distutils available, skipping test.") except ImportError as e: @@ -170,3 +170,23 @@ class TestAsArray(object): check(as_array(pointer(c_array), shape=())) check(as_array(pointer(c_array[0]), shape=(2,))) check(as_array(pointer(c_array[0][0]), shape=(2, 3))) + + def test_reference_cycles(self): + # related to gh-6511 + import ctypes + + # create array to work with + # don't use int/long to avoid running into bpo-10746 + N = 100 + a = np.arange(N, dtype=np.short) + + # get pointer to array + pnt = np.ctypeslib.as_ctypes(a) + + with np.testing.assert_no_gc_cycles(): + # decay the array above to a pointer to its first element + newpnt = ctypes.cast(pnt, ctypes.POINTER(ctypes.c_short)) + # and construct an array using this data + b = np.ctypeslib.as_array(newpnt, (N,)) + # now delete both, which should cleanup both objects + del newpnt, b diff --git a/numpy/tests/test_scripts.py b/numpy/tests/test_scripts.py index ee09390c7..26e3ea745 100644 --- a/numpy/tests/test_scripts.py +++ b/numpy/tests/test_scripts.py @@ -62,32 +62,37 @@ def run_command(cmd, check_code=True): @pytest.mark.skipif(is_inplace, reason="Cannot test f2py command inplace") def test_f2py(): # test that we can run f2py script + + def try_f2py_commands(cmds): + success = 0 + for f2py_cmd in cmds: + try: + code, stdout, stderr = run_command([f2py_cmd, '-v']) + assert_equal(stdout.strip(), b'2') + success += 1 + except Exception: + pass + return success + if sys.platform == 'win32': + # Only the single 'f2py' script is installed in windows. exe_dir = dirname(sys.executable) - if exe_dir.endswith('Scripts'): # virtualenv - f2py_cmd = r"%s\f2py.py" % exe_dir + f2py_cmds = [os.path.join(exe_dir, 'f2py')] else: - f2py_cmd = r"%s\Scripts\f2py.py" % exe_dir - - code, stdout, stderr = run_command([sys.executable, f2py_cmd, '-v']) - success = stdout.strip() == b'2' - assert_(success, "Warning: f2py not found in path") + f2py_cmds = [os.path.join(exe_dir, "Scripts", 'f2py')] + success = try_f2py_commands(f2py_cmds) + msg = "Warning: f2py not found in path" + assert_(success == 1, msg) else: + # Three scripts are installed in Unix-like systems: + # 'f2py', 'f2py{major}', and 'f2py{major.minor}'. For example, + # if installed with python3.7 the scripts would be named + # 'f2py', 'f2py3', and 'f2py3.7'. version = sys.version_info major = str(version.major) minor = str(version.minor) - f2py_cmds = ('f2py', 'f2py' + major, 'f2py' + major + '.' + minor) - success = False - - for f2py_cmd in f2py_cmds: - try: - code, stdout, stderr = run_command([f2py_cmd, '-v']) - assert_equal(stdout.strip(), b'2') - success = True - break - except Exception: - pass - msg = "Warning: neither %s nor %s nor %s found in path" % f2py_cmds - assert_(success, msg) + success = try_f2py_commands(f2py_cmds) + msg = "Warning: not all of %s, %s, and %s are found in path" % f2py_cmds + assert_(success == 3, msg) diff --git a/runtests.py b/runtests.py index 388b911a1..81c7c103f 100755 --- a/runtests.py +++ b/runtests.py @@ -328,9 +328,10 @@ def build_project(args): # Always use ccache, if installed env['PATH'] = os.pathsep.join(EXTRA_PATH + env.get('PATH', '').split(os.pathsep)) cvars = distutils.sysconfig.get_config_vars() - if 'gcc' in cvars.get('CC', ''): + compiler = env.get('CC') or cvars.get('CC', '') + if 'gcc' in compiler: # Check that this isn't clang masquerading as gcc. - if sys.platform != 'darwin' or 'gnu-gcc' in cvars.get('CC', ''): + if sys.platform != 'darwin' or 'gnu-gcc' in compiler: # add flags used as werrors warnings_as_errors = ' '.join([ # from tools/travis-test.sh @@ -1,23 +1,20 @@ #!/usr/bin/env python -"""NumPy: array processing for numbers, strings, records, and objects. +""" NumPy is the fundamental package for array computing with Python. -NumPy is a general-purpose array-processing package designed to -efficiently manipulate large multi-dimensional arrays of arbitrary -records without sacrificing too much speed for small multi-dimensional -arrays. NumPy is built on the Numeric code base and adds features -introduced by numarray as well as an extended C-API and the ability to -create arrays of arbitrary type which also makes NumPy suitable for -interfacing with general-purpose data-base applications. +It provides: -There are also basic facilities for discrete fourier transform, -basic linear algebra and random number generation. +- a powerful N-dimensional array object +- sophisticated (broadcasting) functions +- tools for integrating C/C++ and Fortran code +- useful linear algebra, Fourier transform, and random number capabilities +- and much more -All numpy wheels distributed from pypi are BSD licensed. +Besides its obvious scientific uses, NumPy can also be used as an efficient +multi-dimensional container of generic data. Arbitrary data-types can be +defined. This allows NumPy to seamlessly and speedily integrate with a wide +variety of databases. -Windows wheels are linked against the ATLAS BLAS / LAPACK library, restricted -to SSE2 instructions, so may not give optimal linear algebra performance for -your machine. See https://docs.scipy.org/doc/numpy/user/install.html for -alternatives. +All NumPy wheels distributed on PyPI are BSD licensed. """ from __future__ import division, print_function @@ -352,6 +349,18 @@ def setup_package(): # Rewrite the version file everytime write_version_py() + # The f2py scripts that will be installed + if sys.platform == 'win32': + f2py_cmds = [ + 'f2py = numpy.f2py.f2py2e:main', + ] + else: + f2py_cmds = [ + 'f2py = numpy.f2py.f2py2e:main', + 'f2py%s = numpy.f2py.f2py2e:main' % sys.version_info[:1], + 'f2py%s.%s = numpy.f2py.f2py2e:main' % sys.version_info[:2], + ] + metadata = dict( name = 'numpy', maintainer = "NumPy Developers", @@ -369,11 +378,7 @@ def setup_package(): python_requires='>=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*', zip_safe=False, entry_points={ - 'console_scripts': [ - 'f2py = numpy.f2py.__main__:main', - 'conv-template = numpy.distutils.conv_template:main', - 'from-template = numpy.distutils.from_template:main', - ] + 'console_scripts': f2py_cmds }, ) diff --git a/tools/travis-test.sh b/tools/travis-test.sh index 11863b5fe..97b192813 100755 --- a/tools/travis-test.sh +++ b/tools/travis-test.sh @@ -125,6 +125,22 @@ run_test() fi if [ -n "$RUN_COVERAGE" ]; then + # move back up to the source dir because we want to execute + # gcov on the source files after the tests have gone through + # the code paths + cd .. + + # execute gcov on source files + find . -name '*.gcno' -type f -exec gcov -pb {} + + + # move the C line coverage report files to the same path + # as the Python report data + mv *.gcov empty + + # move back to the previous path for good measure + # as the Python coverage data is there + cd empty + # Upload coverage files to codecov bash <(curl -s https://codecov.io/bash) -X gcov -X coveragepy fi @@ -153,6 +169,14 @@ if [ -n "$USE_WHEEL" ] && [ $# -eq 0 ]; then $PIP install -U virtualenv # ensure some warnings are not issued export CFLAGS=$CFLAGS" -Wno-sign-compare -Wno-unused-result" + # adjust gcc flags if C coverage requested + if [ -n "$RUN_COVERAGE" ]; then + export NPY_DISTUTILS_APPEND_FLAGS=1 + export CC='gcc --coverage' + export F77='gfortran --coverage' + export F90='gfortran --coverage' + export LDFLAGS='--coverage' + fi $PYTHON setup.py bdist_wheel # Make another virtualenv to install into virtualenv --python=`which $PYTHON` venv-for-wheel |