diff options
Diffstat (limited to 'numpy/core/numeric.py')
| -rw-r--r-- | numpy/core/numeric.py | 95 |
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): |