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-rw-r--r--numpy/__init__.py11
-rw-r--r--numpy/_import_tools.py351
-rw-r--r--numpy/core/_add_newdocs.py56
-rw-r--r--numpy/core/_internal.py115
-rw-r--r--numpy/core/code_generators/generate_numpy_api.py4
-rw-r--r--numpy/core/code_generators/generate_ufunc_api.py5
-rw-r--r--numpy/core/code_generators/generate_umath.py2
-rw-r--r--numpy/core/einsumfunc.py4
-rw-r--r--numpy/core/function_base.py5
-rw-r--r--numpy/core/multiarray.py34
-rw-r--r--numpy/core/numeric.py10
-rw-r--r--numpy/core/records.py4
-rw-r--r--numpy/core/setup.py138
-rw-r--r--numpy/core/src/common/array_assign.c (renamed from numpy/core/src/multiarray/array_assign.c)0
-rw-r--r--numpy/core/src/common/array_assign.h (renamed from numpy/core/src/multiarray/array_assign.h)0
-rw-r--r--numpy/core/src/common/binop_override.h (renamed from numpy/core/src/private/binop_override.h)0
-rw-r--r--numpy/core/src/common/cblasfuncs.c (renamed from numpy/core/src/multiarray/cblasfuncs.c)0
-rw-r--r--numpy/core/src/common/cblasfuncs.h (renamed from numpy/core/src/multiarray/cblasfuncs.h)0
-rw-r--r--numpy/core/src/common/get_attr_string.h (renamed from numpy/core/src/private/get_attr_string.h)0
-rw-r--r--numpy/core/src/common/lowlevel_strided_loops.h (renamed from numpy/core/src/private/lowlevel_strided_loops.h)0
-rw-r--r--numpy/core/src/common/mem_overlap.c (renamed from numpy/core/src/private/mem_overlap.c)0
-rw-r--r--numpy/core/src/common/mem_overlap.h (renamed from numpy/core/src/private/mem_overlap.h)0
-rw-r--r--numpy/core/src/common/npy_binsearch.h.src (renamed from numpy/core/src/private/npy_binsearch.h.src)0
-rw-r--r--numpy/core/src/common/npy_cblas.h (renamed from numpy/core/src/private/npy_cblas.h)0
-rw-r--r--numpy/core/src/common/npy_config.h (renamed from numpy/core/src/private/npy_config.h)0
-rw-r--r--numpy/core/src/common/npy_extint128.h (renamed from numpy/core/src/private/npy_extint128.h)0
-rw-r--r--numpy/core/src/common/npy_fpmath.h (renamed from numpy/core/src/private/npy_fpmath.h)0
-rw-r--r--numpy/core/src/common/npy_import.h (renamed from numpy/core/src/private/npy_import.h)0
-rw-r--r--numpy/core/src/common/npy_longdouble.c (renamed from numpy/core/src/private/npy_longdouble.c)0
-rw-r--r--numpy/core/src/common/npy_longdouble.h (renamed from numpy/core/src/private/npy_longdouble.h)0
-rw-r--r--numpy/core/src/common/npy_partition.h.src (renamed from numpy/core/src/private/npy_partition.h.src)0
-rw-r--r--numpy/core/src/common/npy_pycompat.h (renamed from numpy/core/src/private/npy_pycompat.h)0
-rw-r--r--numpy/core/src/common/npy_sort.h (renamed from numpy/core/src/private/npy_sort.h)0
-rw-r--r--numpy/core/src/common/python_xerbla.c (renamed from numpy/core/src/multiarray/python_xerbla.c)0
-rw-r--r--numpy/core/src/common/templ_common.h.src (renamed from numpy/core/src/private/templ_common.h.src)0
-rw-r--r--numpy/core/src/common/ucsnarrow.c (renamed from numpy/core/src/multiarray/ucsnarrow.c)0
-rw-r--r--numpy/core/src/common/ucsnarrow.h (renamed from numpy/core/src/multiarray/ucsnarrow.h)0
-rw-r--r--numpy/core/src/common/ufunc_override.c (renamed from numpy/core/src/private/ufunc_override.c)0
-rw-r--r--numpy/core/src/common/ufunc_override.h (renamed from numpy/core/src/private/ufunc_override.h)0
-rw-r--r--numpy/core/src/common/umathmodule.h8
-rw-r--r--numpy/core/src/multiarray/arraytypes.c.src2
-rw-r--r--numpy/core/src/multiarray/buffer.c56
-rw-r--r--numpy/core/src/multiarray/calculation.c33
-rw-r--r--numpy/core/src/multiarray/ctors.c9
-rw-r--r--numpy/core/src/multiarray/descriptor.c2
-rw-r--r--numpy/core/src/multiarray/dragon4.c51
-rw-r--r--numpy/core/src/multiarray/dragon4.h7
-rw-r--r--numpy/core/src/multiarray/mapping.c28
-rw-r--r--numpy/core/src/multiarray/methods.c2
-rw-r--r--numpy/core/src/multiarray/multiarraymodule.c63
-rw-r--r--numpy/core/src/multiarray/scalartypes.c.src33
-rw-r--r--numpy/core/src/umath/cpuid.c4
-rw-r--r--numpy/core/src/umath/extobj.c4
-rw-r--r--numpy/core/src/umath/loops.c.src12
-rw-r--r--numpy/core/src/umath/reduction.c4
-rw-r--r--numpy/core/src/umath/scalarmath.c.src4
-rw-r--r--numpy/core/src/umath/ufunc_object.c4
-rw-r--r--numpy/core/src/umath/ufunc_object.h2
-rw-r--r--numpy/core/src/umath/ufunc_type_resolution.c4
-rw-r--r--numpy/core/src/umath/umathmodule.c117
-rw-r--r--numpy/core/tests/test_arrayprint.py10
-rw-r--r--numpy/core/tests/test_datetime.py5
-rw-r--r--numpy/core/tests/test_deprecations.py5
-rw-r--r--numpy/core/tests/test_einsum.py1
-rw-r--r--numpy/core/tests/test_indexing.py1
-rw-r--r--numpy/core/tests/test_multiarray.py127
-rw-r--r--numpy/core/tests/test_nditer.py1
-rw-r--r--numpy/core/tests/test_numeric.py21
-rw-r--r--numpy/core/tests/test_regression.py8
-rw-r--r--numpy/core/tests/test_scalarbuffer.py27
-rw-r--r--numpy/core/tests/test_umath.py7
-rw-r--r--numpy/core/umath.py32
-rw-r--r--numpy/doc/broadcasting.py9
-rw-r--r--numpy/f2py/__main__.py25
-rwxr-xr-xnumpy/f2py/crackfortran.py2
-rwxr-xr-xnumpy/f2py/f2py2e.py24
-rw-r--r--numpy/f2py/setup.py50
-rw-r--r--numpy/lib/__init__.py2
-rw-r--r--numpy/lib/_datasource.py8
-rw-r--r--numpy/lib/arraysetops.py43
-rw-r--r--numpy/lib/function_base.py29
-rw-r--r--numpy/lib/histograms.py32
-rw-r--r--numpy/lib/nanfunctions.py16
-rw-r--r--numpy/lib/polynomial.py6
-rw-r--r--numpy/lib/shape_base.py4
-rw-r--r--numpy/lib/stride_tricks.py2
-rw-r--r--numpy/lib/tests/test__datasource.py27
-rw-r--r--numpy/lib/tests/test_arraysetops.py92
-rw-r--r--numpy/lib/tests/test_histograms.py14
-rw-r--r--numpy/lib/tests/test_index_tricks.py1
-rw-r--r--numpy/lib/tests/test_io.py2
-rw-r--r--numpy/lib/tests/test_shape_base.py14
-rw-r--r--numpy/lib/tests/test_stride_tricks.py14
-rw-r--r--numpy/linalg/linalg.py35
-rw-r--r--numpy/linalg/tests/test_linalg.py163
-rw-r--r--numpy/ma/core.py41
-rw-r--r--numpy/ma/tests/test_core.py29
-rw-r--r--numpy/polynomial/_polybase.py100
-rw-r--r--numpy/polynomial/chebyshev.py23
-rw-r--r--numpy/polynomial/hermite.py18
-rw-r--r--numpy/polynomial/hermite_e.py14
-rw-r--r--numpy/polynomial/laguerre.py18
-rw-r--r--numpy/polynomial/legendre.py25
-rw-r--r--numpy/polynomial/polynomial.py32
-rw-r--r--numpy/polynomial/tests/test_chebyshev.py11
-rw-r--r--numpy/polynomial/tests/test_classes.py50
-rw-r--r--numpy/polynomial/tests/test_hermite.py11
-rw-r--r--numpy/polynomial/tests/test_hermite_e.py11
-rw-r--r--numpy/polynomial/tests/test_laguerre.py11
-rw-r--r--numpy/polynomial/tests/test_legendre.py11
-rw-r--r--numpy/polynomial/tests/test_polynomial.py11
-rw-r--r--numpy/random/__init__.py62
-rw-r--r--numpy/random/info.py138
-rw-r--r--numpy/random/mtrand/mtrand.pyx10
-rw-r--r--numpy/random/tests/test_random.py1
-rw-r--r--numpy/testing/_private/nosetester.py20
-rw-r--r--numpy/testing/_private/utils.py21
-rw-r--r--numpy/testing/tests/test_decorators.py1
-rw-r--r--numpy/testing/tests/test_utils.py2
-rw-r--r--numpy/tests/test_ctypeslib.py28
-rw-r--r--numpy/tests/test_scripts.py45
121 files changed, 1487 insertions, 1304 deletions
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)