Merge branch 'main' into deprecate-find-common-type

1 files changed, 33 insertions, 62 deletions

diff --git a/numpy/core/numeric.py b/numpy/core/numeric.py
index 5b92972d1..91ac3f860 100644
--- a/numpy/core/numeric.py
+++ b/numpy/core/numeric.py
@@ -4,6 +4,7 @@ import operator
 import sys
 import warnings
 import numbers
+import builtins
 
 import numpy as np
 from . import multiarray
@@ -17,7 +18,8 @@ from .multiarray import (
     fromstring, inner, lexsort, matmul, may_share_memory,
     min_scalar_type, ndarray, nditer, nested_iters, promote_types,
     putmask, result_type, set_numeric_ops, shares_memory, vdot, where,
-    zeros, normalize_axis_index, _get_promotion_state, _set_promotion_state)
+    zeros, normalize_axis_index, _get_promotion_state, _set_promotion_state,
+    _using_numpy2_behavior)
 
 from . import overrides
 from . import umath
@@ -26,7 +28,7 @@ from .overrides import set_array_function_like_doc, set_module
 from .umath import (multiply, invert, sin, PINF, NAN)
 from . import numerictypes
 from .numerictypes import longlong, intc, int_, float_, complex_, bool_
-from ._exceptions import TooHardError, AxisError
+from ..exceptions import ComplexWarning, TooHardError, AxisError
 from ._ufunc_config import errstate, _no_nep50_warning
 
 bitwise_not = invert
@@ -52,22 +54,10 @@ __all__ = [
     'identity', 'allclose', 'compare_chararrays', 'putmask',
     'flatnonzero', 'Inf', 'inf', 'infty', 'Infinity', 'nan', 'NaN',
     'False_', 'True_', 'bitwise_not', 'CLIP', 'RAISE', 'WRAP', 'MAXDIMS',
-    'BUFSIZE', 'ALLOW_THREADS', 'ComplexWarning', 'full', 'full_like',
+    'BUFSIZE', 'ALLOW_THREADS', 'full', 'full_like',
     'matmul', 'shares_memory', 'may_share_memory', 'MAY_SHARE_BOUNDS',
-    'MAY_SHARE_EXACT', 'TooHardError', 'AxisError',
-    '_get_promotion_state', '_set_promotion_state']
-
-
-@set_module('numpy')
-class ComplexWarning(RuntimeWarning):
-    """
-    The warning raised when casting a complex dtype to a real dtype.
-
-    As implemented, casting a complex number to a real discards its imaginary
-    part, but this behavior may not be what the user actually wants.
-
-    """
-    pass
+    'MAY_SHARE_EXACT', '_get_promotion_state', '_set_promotion_state',
+    '_using_numpy2_behavior']
 
 
 def _zeros_like_dispatcher(a, dtype=None, order=None, subok=None, shape=None):
@@ -143,10 +133,6 @@ def zeros_like(a, dtype=None, order='K', subok=True, shape=None):
     return res
 
 
-def _ones_dispatcher(shape, dtype=None, order=None, *, like=None):
-    return(like,)
-
-
 @set_array_function_like_doc
 @set_module('numpy')
 def ones(shape, dtype=None, order='C', *, like=None):
@@ -200,16 +186,14 @@ def ones(shape, dtype=None, order='C', *, like=None):
 
     """
     if like is not None:
-        return _ones_with_like(shape, dtype=dtype, order=order, like=like)
+        return _ones_with_like(like, shape, dtype=dtype, order=order)
 
     a = empty(shape, dtype, order)
     multiarray.copyto(a, 1, casting='unsafe')
     return a
 
 
-_ones_with_like = array_function_dispatch(
-    _ones_dispatcher
-)(ones)
+_ones_with_like = array_function_dispatch()(ones)
 
 
 def _ones_like_dispatcher(a, dtype=None, order=None, subok=None, shape=None):
@@ -336,7 +320,8 @@ def full(shape, fill_value, dtype=None, order='C', *, like=None):
 
     """
     if like is not None:
-        return _full_with_like(shape, fill_value, dtype=dtype, order=order, like=like)
+        return _full_with_like(
+                like, shape, fill_value, dtype=dtype, order=order)
 
     if dtype is None:
         fill_value = asarray(fill_value)
@@ -346,9 +331,7 @@ def full(shape, fill_value, dtype=None, order='C', *, like=None):
     return a
 
 
-_full_with_like = array_function_dispatch(
-    _full_dispatcher
-)(full)
+_full_with_like = array_function_dispatch()(full)
 
 
 def _full_like_dispatcher(a, fill_value, dtype=None, order=None, subok=None, shape=None):
@@ -707,7 +690,7 @@ def correlate(a, v, mode='valid'):
     --------
     convolve : Discrete, linear convolution of two one-dimensional sequences.
     multiarray.correlate : Old, no conjugate, version of correlate.
-    scipy.signal.correlate : uses FFT which has superior performance on large arrays. 
+    scipy.signal.correlate : uses FFT which has superior performance on large arrays.
 
     Notes
     -----
@@ -721,7 +704,7 @@ def correlate(a, v, mode='valid'):
     `numpy.correlate` may perform slowly in large arrays (i.e. n = 1e5) because it does
     not use the FFT to compute the convolution; in that case, `scipy.signal.correlate` might
     be preferable.
-    
+
 
     Examples
     --------
@@ -738,7 +721,7 @@ def correlate(a, v, mode='valid'):
     array([ 0.5-0.5j,  1.0+0.j ,  1.5-1.5j,  3.0-1.j ,  0.0+0.j ])
 
     Note that you get the time reversed, complex conjugated result
-    (:math:`\overline{c_{-k}}`) when the two input sequences a and v change 
+    (:math:`\overline{c_{-k}}`) when the two input sequences a and v change
     places:
 
     >>> np.correlate([0, 1, 0.5j], [1+1j, 2, 3-1j], 'full')
@@ -860,14 +843,13 @@ def outer(a, b, out=None):
     """
     Compute the outer product of two vectors.
 
-    Given two vectors, ``a = [a0, a1, ..., aM]`` and
-    ``b = [b0, b1, ..., bN]``,
+    Given two vectors `a` and `b` of length ``M`` and ``N``, repsectively,
     the outer product [1]_ is::
 
-      [[a0*b0  a0*b1 ... a0*bN ]
-       [a1*b0    .
+      [[a_0*b_0  a_0*b_1 ... a_0*b_{N-1} ]
+       [a_1*b_0    .
        [ ...          .
-       [aM*b0            aM*bN ]]
+       [a_{M-1}*b_0            a_{M-1}*b_{N-1} ]]
 
     Parameters
     ----------
@@ -899,9 +881,9 @@ def outer(a, b, out=None):
 
     References
     ----------
-    .. [1] : G. H. Golub and C. F. Van Loan, *Matrix Computations*, 3rd
-             ed., Baltimore, MD, Johns Hopkins University Press, 1996,
-             pg. 8.
+    .. [1] G. H. Golub and C. F. Van Loan, *Matrix Computations*, 3rd
+           ed., Baltimore, MD, Johns Hopkins University Press, 1996,
+           pg. 8.
 
     Examples
     --------
@@ -1300,7 +1282,7 @@ def rollaxis(a, axis, start=0):
            +-------------------+----------------------+
            | ``arr.ndim + 1``  | raise ``AxisError``  |
            +-------------------+----------------------+
-           
+
         .. |vdots|   unicode:: U+22EE .. Vertical Ellipsis
 
     Returns
@@ -1791,10 +1773,6 @@ def indices(dimensions, dtype=int, sparse=False):
     return res
 
 
-def _fromfunction_dispatcher(function, shape, *, dtype=None, like=None, **kwargs):
-    return (like,)
-
-
 @set_array_function_like_doc
 @set_module('numpy')
 def fromfunction(function, shape, *, dtype=float, like=None, **kwargs):
@@ -1843,11 +1821,11 @@ def fromfunction(function, shape, *, dtype=float, like=None, **kwargs):
     >>> np.fromfunction(lambda i, j: i, (2, 2), dtype=float)
     array([[0., 0.],
            [1., 1.]])
-           
-    >>> np.fromfunction(lambda i, j: j, (2, 2), dtype=float)    
+
+    >>> np.fromfunction(lambda i, j: j, (2, 2), dtype=float)
     array([[0., 1.],
            [0., 1.]])
-           
+
     >>> np.fromfunction(lambda i, j: i == j, (3, 3), dtype=int)
     array([[ True, False, False],
            [False,  True, False],
@@ -1860,15 +1838,14 @@ def fromfunction(function, shape, *, dtype=float, like=None, **kwargs):
 
     """
     if like is not None:
-        return _fromfunction_with_like(function, shape, dtype=dtype, like=like, **kwargs)
+        return _fromfunction_with_like(
+                like, function, shape, dtype=dtype, **kwargs)
 
     args = indices(shape, dtype=dtype)
     return function(*args, **kwargs)
 
 
-_fromfunction_with_like = array_function_dispatch(
-    _fromfunction_dispatcher
-)(fromfunction)
+_fromfunction_with_like = array_function_dispatch()(fromfunction)
 
 
 def _frombuffer(buf, dtype, shape, order):
@@ -2046,7 +2023,7 @@ def binary_repr(num, width=None):
         binary = bin(num)[2:]
         binwidth = len(binary)
         outwidth = (binwidth if width is None
-                    else max(binwidth, width))
+                    else builtins.max(binwidth, width))
         warn_if_insufficient(width, binwidth)
         return binary.zfill(outwidth)
 
@@ -2066,7 +2043,7 @@ def binary_repr(num, width=None):
             binary = bin(twocomp)[2:]
             binwidth = len(binary)
 
-            outwidth = max(binwidth, width)
+            outwidth = builtins.max(binwidth, width)
             warn_if_insufficient(width, binwidth)
             return '1' * (outwidth - binwidth) + binary
 
@@ -2143,10 +2120,6 @@ def _maketup(descr, val):
         return tuple(res)
 
 
-def _identity_dispatcher(n, dtype=None, *, like=None):
-    return (like,)
-
-
 @set_array_function_like_doc
 @set_module('numpy')
 def identity(n, dtype=None, *, like=None):
@@ -2181,15 +2154,13 @@ def identity(n, dtype=None, *, like=None):
 
     """
     if like is not None:
-        return _identity_with_like(n, dtype=dtype, like=like)
+        return _identity_with_like(like, n, dtype=dtype)
 
     from numpy import eye
     return eye(n, dtype=dtype, like=like)
 
 
-_identity_with_like = array_function_dispatch(
-    _identity_dispatcher
-)(identity)
+_identity_with_like = array_function_dispatch()(identity)
 
 
 def _allclose_dispatcher(a, b, rtol=None, atol=None, equal_nan=None):