numpy · charris · Nov 15, 2018 · Nov 13, 2018 · Nov 14, 2018 · Nov 14, 2018
diff --git a/numpy/_globals.py b/numpy/_globals.py
@@ -17,7 +17,6 @@ def foo(arg=np._NoValue):
 """
 from __future__ import division, absolute_import, print_function
 
-
 __ALL__ = [
     'ModuleDeprecationWarning', 'VisibleDeprecationWarning', '_NoValue'
     ]
@@ -39,7 +38,9 @@ class ModuleDeprecationWarning(DeprecationWarning):
     nose tester will let pass without making tests fail.
 
     """
-    pass
+
+
+ModuleDeprecationWarning.__module__ = 'numpy'
 
 
 class VisibleDeprecationWarning(UserWarning):
@@ -50,7 +51,10 @@ class VisibleDeprecationWarning(UserWarning):
     the usage is most likely a user bug.
 
     """
-    pass
+
+
+VisibleDeprecationWarning.__module__ = 'numpy'
+
 
 class _NoValueType(object):
     """Special keyword value.
@@ -73,4 +77,5 @@ def __reduce__(self):
     def __repr__(self):
         return "<no value>"
 
+
 _NoValue = _NoValueType()
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py
@@ -4552,184 +4552,6 @@ def luf(lamdaexpr, *args, **kwargs):
 #
 ##############################################################################
 
-add_newdoc('numpy.core.multiarray', 'bincount',
-    """
-    bincount(x, weights=None, minlength=0)
-
-    Count number of occurrences of each value in array of non-negative ints.
-
-    The number of bins (of size 1) is one larger than the largest value in
-    `x`. If `minlength` is specified, there will be at least this number
-    of bins in the output array (though it will be longer if necessary,
-    depending on the contents of `x`).
-    Each bin gives the number of occurrences of its index value in `x`.
-    If `weights` is specified the input array is weighted by it, i.e. if a
-    value ``n`` is found at position ``i``, ``out[n] += weight[i]`` instead
-    of ``out[n] += 1``.
-
-    Parameters
-    ----------
-    x : array_like, 1 dimension, nonnegative ints
-        Input array.
-    weights : array_like, optional
-        Weights, array of the same shape as `x`.
-    minlength : int, optional
-        A minimum number of bins for the output array.
-
-        .. versionadded:: 1.6.0
-
-    Returns
-    -------
-    out : ndarray of ints
-        The result of binning the input array.
-        The length of `out` is equal to ``np.amax(x)+1``.
-
-    Raises
-    ------
-    ValueError
-        If the input is not 1-dimensional, or contains elements with negative
-        values, or if `minlength` is negative.
-    TypeError
-        If the type of the input is float or complex.
-
-    See Also
-    --------
-    histogram, digitize, unique
-
-    Examples
-    --------
-    >>> np.bincount(np.arange(5))
-    array([1, 1, 1, 1, 1])
-    >>> np.bincount(np.array([0, 1, 1, 3, 2, 1, 7]))
-    array([1, 3, 1, 1, 0, 0, 0, 1])
-
-    >>> x = np.array([0, 1, 1, 3, 2, 1, 7, 23])
-    >>> np.bincount(x).size == np.amax(x)+1
-    True
-
-    The input array needs to be of integer dtype, otherwise a
-    TypeError is raised:
-
-    >>> np.bincount(np.arange(5, dtype=float))
-    Traceback (most recent call last):
-      File "<stdin>", line 1, in <module>
-    TypeError: array cannot be safely cast to required type
-
-    A possible use of ``bincount`` is to perform sums over
-    variable-size chunks of an array, using the ``weights`` keyword.
-
-    >>> w = np.array([0.3, 0.5, 0.2, 0.7, 1., -0.6]) # weights
-    >>> x = np.array([0, 1, 1, 2, 2, 2])
-    >>> np.bincount(x,  weights=w)
-    array([ 0.3,  0.7,  1.1])
-
-    """)
-
-add_newdoc('numpy.core.multiarray', 'ravel_multi_index',
-    """
-    ravel_multi_index(multi_index, dims, mode='raise', order='C')
-
-    Converts a tuple of index arrays into an array of flat
-    indices, applying boundary modes to the multi-index.
-
-    Parameters
-    ----------
-    multi_index : tuple of array_like
-        A tuple of integer arrays, one array for each dimension.
-    dims : tuple of ints
-        The shape of array into which the indices from ``multi_index`` apply.
-    mode : {'raise', 'wrap', 'clip'}, optional
-        Specifies how out-of-bounds indices are handled.  Can specify
-        either one mode or a tuple of modes, one mode per index.
-
-        * 'raise' -- raise an error (default)
-        * 'wrap' -- wrap around
-        * 'clip' -- clip to the range
-
-        In 'clip' mode, a negative index which would normally
-        wrap will clip to 0 instead.
-    order : {'C', 'F'}, optional
-        Determines whether the multi-index should be viewed as
-        indexing in row-major (C-style) or column-major
-        (Fortran-style) order.
-
-    Returns
-    -------
-    raveled_indices : ndarray
-        An array of indices into the flattened version of an array
-        of dimensions ``dims``.
-
-    See Also
-    --------
-    unravel_index
-
-    Notes
-    -----
-    .. versionadded:: 1.6.0
-
-    Examples
-    --------
-    >>> arr = np.array([[3,6,6],[4,5,1]])
-    >>> np.ravel_multi_index(arr, (7,6))
-    array([22, 41, 37])
-    >>> np.ravel_multi_index(arr, (7,6), order='F')
-    array([31, 41, 13])
-    >>> np.ravel_multi_index(arr, (4,6), mode='clip')
-    array([22, 23, 19])
-    >>> np.ravel_multi_index(arr, (4,4), mode=('clip','wrap'))
-    array([12, 13, 13])
-
-    >>> np.ravel_multi_index((3,1,4,1), (6,7,8,9))
-    1621
-    """)
-
-add_newdoc('numpy.core.multiarray', 'unravel_index',
-    """
-    unravel_index(indices, shape, order='C')
-
-    Converts a flat index or array of flat indices into a tuple
-    of coordinate arrays.
-
-    Parameters
-    ----------
-    indices : array_like
-        An integer array whose elements are indices into the flattened
-        version of an array of dimensions ``shape``. Before version 1.6.0,
-        this function accepted just one index value.
-    shape : tuple of ints
-        The shape of the array to use for unraveling ``indices``.
-
-        .. versionchanged:: 1.16.0
-            Renamed from ``dims`` to ``shape``.
-
-    order : {'C', 'F'}, optional
-        Determines whether the indices should be viewed as indexing in
-        row-major (C-style) or column-major (Fortran-style) order.
-
-        .. versionadded:: 1.6.0
-
-    Returns
-    -------
-    unraveled_coords : tuple of ndarray
-        Each array in the tuple has the same shape as the ``indices``
-        array.
-
-    See Also
-    --------
-    ravel_multi_index
-
-    Examples
-    --------
-    >>> np.unravel_index([22, 41, 37], (7,6))
-    (array([3, 6, 6]), array([4, 5, 1]))
-    >>> np.unravel_index([31, 41, 13], (7,6), order='F')
-    (array([3, 6, 6]), array([4, 5, 1]))
-
-    >>> np.unravel_index(1621, (6,7,8,9))
-    (3, 1, 4, 1)
-
-    """)
-
 add_newdoc('numpy.core.multiarray', 'add_docstring',
     """
     add_docstring(obj, docstring)

diff --git a/numpy/core/_internal.py b/numpy/core/_internal.py
@@ -10,6 +10,7 @@
 import sys
 
 from numpy.compat import unicode
+from numpy.core.overrides import set_module
 from .multiarray import dtype, array, ndarray
 try:
     import ctypes
@@ -718,9 +719,11 @@ def _lcm(a, b):
     return a // _gcd(a, b) * b
 
 # Exception used in shares_memory()
+@set_module('numpy')
 class TooHardError(RuntimeError):
     pass
 
+@set_module('numpy')
 class AxisError(ValueError, IndexError):
     """ Axis supplied was invalid. """
     def __init__(self, axis, ndim=None, msg_prefix=None):

diff --git a/numpy/core/arrayprint.py b/numpy/core/arrayprint.py
@@ -48,7 +48,7 @@
 from .numeric import concatenate, asarray, errstate
 from .numerictypes import (longlong, intc, int_, float_, complex_, bool_,
                            flexible)
-from .overrides import array_function_dispatch
+from .overrides import array_function_dispatch, set_module
 import warnings
 import contextlib
 
@@ -89,6 +89,8 @@ def _make_options_dict(precision=None, threshold=None, edgeitems=None,
 
     return options
 
+
+@set_module('numpy')
 def set_printoptions(precision=None, threshold=None, edgeitems=None,
                      linewidth=None, suppress=None, nanstr=None, infstr=None,
                      formatter=None, sign=None, floatmode=None, **kwarg):
@@ -250,6 +252,7 @@ def set_printoptions(precision=None, threshold=None, edgeitems=None,
         set_legacy_print_mode(0)
 
 
+@set_module('numpy')
 def get_printoptions():
     """
     Return the current print options.
@@ -279,6 +282,7 @@ def get_printoptions():
     return _format_options.copy()
 
 
+@set_module('numpy')
 @contextlib.contextmanager
 def printoptions(*args, **kwargs):
     """Context manager for setting print options.
@@ -976,6 +980,8 @@ def __init__(self, *args, **kwargs):
                       DeprecationWarning, stacklevel=2)
         super(LongFloatFormat, self).__init__(*args, **kwargs)
 
+
+@set_module('numpy')
 def format_float_scientific(x, precision=None, unique=True, trim='k',
                             sign=False, pad_left=None, exp_digits=None):
     """
@@ -1043,6 +1049,8 @@ def format_float_scientific(x, precision=None, unique=True, trim='k',
                               trim=trim, sign=sign, pad_left=pad_left,
                               exp_digits=exp_digits)
 
+
+@set_module('numpy')
 def format_float_positional(x, precision=None, unique=True,
                             fractional=True, trim='k', sign=False,
                             pad_left=None, pad_right=None):

diff --git a/numpy/core/defchararray.py b/numpy/core/defchararray.py
@@ -23,6 +23,7 @@
 from .numeric import ndarray, compare_chararrays
 from .numeric import array as narray
 from numpy.core.multiarray import _vec_string
+from numpy.core.overrides import set_module
 from numpy.core import overrides
 from numpy.compat import asbytes, long
 import numpy
@@ -1820,6 +1821,7 @@ def isdecimal(a):
     return _vec_string(a, bool_, 'isdecimal')
 
 
+@set_module('numpy')
 class chararray(ndarray):
     """
     chararray(shape, itemsize=1, unicode=False, buffer=None, offset=0,

diff --git a/numpy/core/function_base.py b/numpy/core/function_base.py
@@ -7,6 +7,7 @@
 from .numeric import (result_type, NaN, shares_memory, MAY_SHARE_BOUNDS,
                       TooHardError,asanyarray)
 from numpy.core.multiarray import add_docstring
+from numpy.core.overrides import set_module
 
 __all__ = ['logspace', 'linspace', 'geomspace']
 
@@ -23,6 +24,7 @@ def _index_deprecate(i, stacklevel=2):
     return i
 
 
+@set_module('numpy')
 def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None):
     """
     Return evenly spaced numbers over a specified interval.
@@ -154,6 +156,7 @@ def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None):
         return y.astype(dtype, copy=False)
 
 
+@set_module('numpy')
 def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None):
     """
     Return numbers spaced evenly on a log scale.
@@ -238,6 +241,7 @@ def logspace(start, stop, num=50, endpoint=True, base=10.0, dtype=None):
     return _nx.power(base, y).astype(dtype)
 
 
+@set_module('numpy')
 def geomspace(start, stop, num=50, endpoint=True, dtype=None):
     """
     Return numbers spaced evenly on a log scale (a geometric progression).

diff --git a/numpy/core/getlimits.py b/numpy/core/getlimits.py
@@ -8,6 +8,7 @@
 import warnings
 
 from .machar import MachAr
+from .overrides import set_module
 from . import numeric
 from . import numerictypes as ntypes
 from .numeric import array, inf
@@ -289,6 +290,7 @@ def _discovered_machar(ftype):
                   params['title'])
 
 
+@set_module('numpy')
 class finfo(object):
     """
     finfo(dtype)
@@ -439,6 +441,7 @@ def __repr__(self):
                  " max=%(_str_max)s, dtype=%(dtype)s)") % d)
 
 
+@set_module('numpy')
 class iinfo(object):
     """
     iinfo(type)

diff --git a/numpy/core/machar.py b/numpy/core/machar.py
@@ -11,9 +11,11 @@
 
 from numpy.core.fromnumeric import any
 from numpy.core.numeric import errstate
+from numpy.core.overrides import set_module
 
 # Need to speed this up...especially for longfloat
 
+@set_module('numpy')
 class MachAr(object):
     """
     Diagnosing machine parameters.

diff --git a/numpy/core/memmap.py b/numpy/core/memmap.py
@@ -5,6 +5,7 @@
 from numpy.compat import (
     long, basestring, os_fspath, contextlib_nullcontext, is_pathlib_path
 )
+from numpy.core.overrides import set_module
 
 __all__ = ['memmap']
 
@@ -19,6 +20,8 @@
     "write":"w+"
     }
 
+
+@set_module('numpy')
 class memmap(ndarray):
     """Create a memory-map to an array stored in a *binary* file on disk.