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from __future__ import annotations from ._dtypes import _floating_dtypes, _numeric_dtypes from ._manipulation_functions import reshape from ._array_object import Array from ..core.numeric import normalize_axis_tuple from typing import TYPE_CHECKING from typing import NamedTuple import numpy.linalg import numpy as np _...
null
170,016
from __future__ import annotations from ._dtypes import _floating_dtypes, _numeric_dtypes from ._manipulation_functions import reshape from ._array_object import Array from ..core.numeric import normalize_axis_tuple from typing import TYPE_CHECKING from typing import NamedTuple import numpy.linalg import numpy as np _...
Array API compatible wrapper for :py:func:`np.trace <numpy.trace>`. See its docstring for more information.
170,017
from __future__ import annotations from ._dtypes import _floating_dtypes, _numeric_dtypes from ._manipulation_functions import reshape from ._array_object import Array from ..core.numeric import normalize_axis_tuple from typing import TYPE_CHECKING from typing import NamedTuple import numpy.linalg import numpy as np _...
null
170,018
from __future__ import annotations from ._dtypes import _floating_dtypes, _numeric_dtypes from ._manipulation_functions import reshape from ._array_object import Array from ..core.numeric import normalize_axis_tuple from typing import TYPE_CHECKING from typing import NamedTuple import numpy.linalg import numpy as np _...
Array API compatible wrapper for :py:func:`np.linalg.norm <numpy.linalg.norm>`. See its docstring for more information.
170,019
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.abs <numpy.abs>`. See its docstring for more information.
170,020
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arccos <numpy.arccos>`. See its docstring for more information.
170,021
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arccosh <numpy.arccosh>`. See its docstring for more information.
170,022
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.add <numpy.add>`. See its docstring for more information.
170,023
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arcsin <numpy.arcsin>`. See its docstring for more information.
170,024
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arcsinh <numpy.arcsinh>`. See its docstring for more information.
170,025
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arctan <numpy.arctan>`. See its docstring for more information.
170,026
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) def _result_type(type1, type2...
Array API compatible wrapper for :py:func:`np.arctan2 <numpy.arctan2>`. See its docstring for more information.
170,027
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.arctanh <numpy.arctanh>`. See its docstring for more information.
170,028
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_or_boolean_dtypes = ( bool, int8, int16, int32,...
Array API compatible wrapper for :py:func:`np.bitwise_and <numpy.bitwise_and>`. See its docstring for more information.
170,029
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uin...
Array API compatible wrapper for :py:func:`np.left_shift <numpy.left_shift>`. See its docstring for more information.
170,030
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_or_boolean_dtypes = ( bool, int8, int16, int32,...
Array API compatible wrapper for :py:func:`np.invert <numpy.invert>`. See its docstring for more information.
170,031
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_or_boolean_dtypes = ( bool, int8, int16, int32,...
Array API compatible wrapper for :py:func:`np.bitwise_or <numpy.bitwise_or>`. See its docstring for more information.
170,032
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uin...
Array API compatible wrapper for :py:func:`np.right_shift <numpy.right_shift>`. See its docstring for more information.
170,033
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_or_boolean_dtypes = ( bool, int8, int16, int32,...
Array API compatible wrapper for :py:func:`np.bitwise_xor <numpy.bitwise_xor>`. See its docstring for more information.
170,034
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uin...
Array API compatible wrapper for :py:func:`np.ceil <numpy.ceil>`. See its docstring for more information.
170,035
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.cos <numpy.cos>`. See its docstring for more information.
170,036
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.cosh <numpy.cosh>`. See its docstring for more information.
170,037
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) def _result_type(type1, type2...
Array API compatible wrapper for :py:func:`np.divide <numpy.divide>`. See its docstring for more information.
170,038
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np def _result_type(type1, type2): if (type1, type2) in _promotion_tabl...
Array API compatible wrapper for :py:func:`np.equal <numpy.equal>`. See its docstring for more information.
170,039
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.exp <numpy.exp>`. See its docstring for more information.
170,040
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.expm1 <numpy.expm1>`. See its docstring for more information.
170,041
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uin...
Array API compatible wrapper for :py:func:`np.floor <numpy.floor>`. See its docstring for more information.
170,042
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.floor_divide <numpy.floor_divide>`. See its docstring for more information.
170,043
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.greater <numpy.greater>`. See its docstring for more information.
170,044
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.greater_equal <numpy.greater_equal>`. See its docstring for more information.
170,045
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.isfinite <numpy.isfinite>`. See its docstring for more information.
170,046
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.isinf <numpy.isinf>`. See its docstring for more information.
170,047
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.isnan <numpy.isnan>`. See its docstring for more information.
170,048
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.less <numpy.less>`. See its docstring for more information.
170,049
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.less_equal <numpy.less_equal>`. See its docstring for more information.
170,050
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.log <numpy.log>`. See its docstring for more information.
170,051
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.log1p <numpy.log1p>`. See its docstring for more information.
170,052
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.log2 <numpy.log2>`. See its docstring for more information.
170,053
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.log10 <numpy.log10>`. See its docstring for more information.
170,054
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) def _result_type(type1, type2...
Array API compatible wrapper for :py:func:`np.logaddexp <numpy.logaddexp>`. See its docstring for more information.
170,055
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _boolean_dtypes = (bool,) def _result_type(type1, type2): if (t...
Array API compatible wrapper for :py:func:`np.logical_and <numpy.logical_and>`. See its docstring for more information.
170,056
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _boolean_dtypes = (bool,) class Array: """ n-d array object for...
Array API compatible wrapper for :py:func:`np.logical_not <numpy.logical_not>`. See its docstring for more information.
170,057
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _boolean_dtypes = (bool,) def _result_type(type1, type2): if (t...
Array API compatible wrapper for :py:func:`np.logical_or <numpy.logical_or>`. See its docstring for more information.
170,058
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _boolean_dtypes = (bool,) def _result_type(type1, type2): if (t...
Array API compatible wrapper for :py:func:`np.logical_xor <numpy.logical_xor>`. See its docstring for more information.
170,059
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.multiply <numpy.multiply>`. See its docstring for more information.
170,060
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.negative <numpy.negative>`. See its docstring for more information.
170,061
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np def _result_type(type1, type2): if (type1, type2) in _promotion_tabl...
Array API compatible wrapper for :py:func:`np.not_equal <numpy.not_equal>`. See its docstring for more information.
170,062
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.positive <numpy.positive>`. See its docstring for more information.
170,063
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.power <numpy.power>`. See its docstring for more information.
170,064
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.remainder <numpy.remainder>`. See its docstring for more information.
170,065
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.round <numpy.round>`. See its docstring for more information.
170,066
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.sign <numpy.sign>`. See its docstring for more information.
170,067
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.sin <numpy.sin>`. See its docstring for more information.
170,068
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.sinh <numpy.sinh>`. See its docstring for more information.
170,069
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.square <numpy.square>`. See its docstring for more information.
170,070
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.sqrt <numpy.sqrt>`. See its docstring for more information.
170,071
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _numeric_dtypes = ( float32, float64, int8, int16, i...
Array API compatible wrapper for :py:func:`np.subtract <numpy.subtract>`. See its docstring for more information.
170,072
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.tan <numpy.tan>`. See its docstring for more information.
170,073
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _floating_dtypes = (float32, float64) class Array: """ n-d arra...
Array API compatible wrapper for :py:func:`np.tanh <numpy.tanh>`. See its docstring for more information.
170,074
from __future__ import annotations from ._dtypes import ( _boolean_dtypes, _floating_dtypes, _integer_dtypes, _integer_or_boolean_dtypes, _numeric_dtypes, _result_type, ) from ._array_object import Array import numpy as np _integer_dtypes = (int8, int16, int32, int64, uint8, uint16, uint32, uin...
Array API compatible wrapper for :py:func:`np.trunc <numpy.trunc>`. See its docstring for more information.
170,075
from __future__ import annotations from ._array_object import Array from typing import Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more information. This is a wrapper around ...
Array API compatible wrapper for :py:func:`np.all <numpy.all>`. See its docstring for more information.
170,076
from __future__ import annotations from ._array_object import Array from typing import Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more information. This is a wrapper around ...
Array API compatible wrapper for :py:func:`np.any <numpy.any>`. See its docstring for more information.
170,077
from __future__ import annotations from ._array_object import Array import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more information. This is a wrapper around numpy.ndarray that restricts the usage to ...
Array API compatible wrapper for :py:func:`np.argsort <numpy.argsort>`. See its docstring for more information.
170,078
from __future__ import annotations from ._array_object import Array import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for more information. This is a wrapper around numpy.ndarray that restricts the usage to ...
Array API compatible wrapper for :py:func:`np.sort <numpy.sort>`. See its docstring for more information.
170,079
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.concatenate <numpy.concatenate>`. See its docstring for more information.
170,080
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.expand_dims <numpy.expand_dims>`. See its docstring for more information.
170,081
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.flip <numpy.flip>`. See its docstring for more information.
170,082
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.transpose <numpy.transpose>`. See its docstring for more information.
170,083
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.roll <numpy.roll>`. See its docstring for more information.
170,084
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.squeeze <numpy.squeeze>`. See its docstring for more information.
170,085
from __future__ import annotations from ._array_object import Array from ._data_type_functions import result_type from typing import List, Optional, Tuple, Union import numpy as np class Array: """ n-d array object for the array API namespace. See the docstring of :py:obj:`np.ndarray <numpy.ndarray>` for ...
Array API compatible wrapper for :py:func:`np.stack <numpy.stack>`. See its docstring for more information.
170,086
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Adds a Notes section to an existing docstring.
170,087
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Get the signature from obj
170,088
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Return the minimum value that can be represented by the dtype of an object. This function is useful for calculating a fill value suitable for taking the maximum of an array with a given dtype. Parameters ---------- obj : ndarray, dtype or scalar An object that can be queried for it's numeric type. Returns ------- val :...
170,089
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Private function validating the given `fill_value` for the given dtype. If fill_value is None, it is set to the default corresponding to the dtype. If fill_value is not None, its value is forced to the given dtype. The result is always a 0d array.
170,090
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Set the filling value of a, if a is a masked array. This function changes the fill value of the masked array `a` in place. If `a` is not a masked array, the function returns silently, without doing anything. Parameters ---------- a : array_like Input array. fill_value : dtype Filling value. A consistency test is perfor...
170,091
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Return the common filling value of two masked arrays, if any. If ``a.fill_value == b.fill_value``, return the fill value, otherwise return None. Parameters ---------- a, b : MaskedArray The masked arrays for which to compare fill values. Returns ------- fill_value : scalar or None The common fill value, or None. Exampl...
170,092
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Return input with invalid data masked and replaced by a fill value. Invalid data means values of `nan`, `inf`, etc. Parameters ---------- a : array_like Input array, a (subclass of) ndarray. mask : sequence, optional Mask. Must be convertible to an array of booleans with the same shape as `data`. True indicates a maske...
170,093
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
null
170,094
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Returns a completely flattened version of the mask, where nested fields are collapsed. Parameters ---------- mask : array_like Input array, which will be interpreted as booleans. Returns ------- flattened_mask : ndarray of bools The flattened input. Examples -------- >>> mask = np.array([0, 0, 1]) >>> np.ma.flatten_mas...
170,095
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Check whether there are masked values along the given axis
170,096
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where greater than a given value. This function is a shortcut to ``masked_where``, with `condition` = (x > value). See Also -------- masked_where : Mask where a condition is met. Examples -------- >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_greater(a, 2) masked_a...
170,097
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where greater than or equal to a given value. This function is a shortcut to ``masked_where``, with `condition` = (x >= value). See Also -------- masked_where : Mask where a condition is met. Examples -------- >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_greater_e...
170,098
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where less than a given value. This function is a shortcut to ``masked_where``, with `condition` = (x < value). See Also -------- masked_where : Mask where a condition is met. Examples -------- >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_less(a, 2) masked_array(d...
170,099
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where less than or equal to a given value. This function is a shortcut to ``masked_where``, with `condition` = (x <= value). See Also -------- masked_where : Mask where a condition is met. Examples -------- >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_less_equal(a...
170,100
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where `not` equal to a given value. This function is a shortcut to ``masked_where``, with `condition` = (x != value). See Also -------- masked_where : Mask where a condition is met. Examples -------- >>> import numpy.ma as ma >>> a = np.arange(4) >>> a array([0, 1, 2, 3]) >>> ma.masked_not_equal(a, 2) mas...
170,101
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where equal to a given value. Return a MaskedArray, masked where the data in array `x` are equal to `value`. The fill_value of the returned MaskedArray is set to `value`. For floating point arrays, consider using ``masked_values(x, value)``. See Also -------- masked_where : Mask where a condition is met. ...
170,102
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array inside a given interval. Shortcut to ``masked_where``, where `condition` is True for `x` inside the interval [v1,v2] (v1 <= x <= v2). The boundaries `v1` and `v2` can be given in either order. See Also -------- masked_where : Mask where a condition is met. Notes ----- The array `x` is prefilled with its f...
170,103
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array outside a given interval. Shortcut to ``masked_where``, where `condition` is True for `x` outside the interval [v1,v2] (x < v1)|(x > v2). The boundaries `v1` and `v2` can be given in either order. See Also -------- masked_where : Mask where a condition is met. Notes ----- The array `x` is prefilled with i...
170,104
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask the array `x` where the data are exactly equal to value. This function is similar to `masked_values`, but only suitable for object arrays: for floating point, use `masked_values` instead. Parameters ---------- x : array_like Array to mask value : object Comparison value copy : {True, False}, optional Whether to re...
170,105
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask using floating point equality. Return a MaskedArray, masked where the data in array `x` are approximately equal to `value`, determined using `isclose`. The default tolerances for `masked_values` are the same as those for `isclose`. For integer types, exact equality is used, in the same way as `masked_equal`. The f...
170,106
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Mask an array where invalid values occur (NaNs or infs). This function is a shortcut to ``masked_where``, with `condition` = ~(np.isfinite(a)). Any pre-existing mask is conserved. Only applies to arrays with a dtype where NaNs or infs make sense (i.e. floating point types), but accepts any array_like object. See Also -...
170,107
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Puts printoptions in result where mask is True. Private function allowing for recursion
170,108
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Recursively fill `a` with `fill_value`.
170,109
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Flatten a structured array. The data type of the output is chosen such that it can represent all of the (nested) fields. Parameters ---------- a : structured array Returns ------- output : masked array or ndarray A flattened masked array if the input is a masked array, otherwise a standard ndarray. Examples -------- >>...
170,110
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Return a class method wrapper around a basic array method. Creates a class method which returns a masked array, where the new ``_data`` array is the output of the corresponding basic method called on the original ``_data``. If `onmask` is True, the new mask is the output of the method called on the initial mask. Otherw...
170,111
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Internal function that builds a new MaskedArray from the information stored in a pickle.
170,112
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
null
170,113
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Returns element-wise base array raised to power from second array. This is the masked array version of `numpy.power`. For details see `numpy.power`. See Also -------- numpy.power Notes ----- The *out* argument to `numpy.power` is not supported, `third` has to be None. Examples -------- >>> import numpy.ma as ma >>> x =...
170,114
import builtins import inspect import operator import warnings import textwrap import re from functools import reduce import numpy as np import numpy.core.umath as umath import numpy.core.numerictypes as ntypes from numpy.core import multiarray as mu from numpy import ndarray, amax, amin, iscomplexobj, bool_, _NoValue ...
Shift the bits of an integer to the left. This is the masked array version of `numpy.left_shift`, for details see that function. See Also -------- numpy.left_shift