Current File : //opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/array_api/_elementwise_functions.py
from __future__ import annotations
from ._dtypes import (
_boolean_dtypes,
_floating_dtypes,
_real_floating_dtypes,
_complex_floating_dtypes,
_integer_dtypes,
_integer_or_boolean_dtypes,
_real_numeric_dtypes,
_numeric_dtypes,
_result_type,
)
from ._array_object import Array
import numpy as np
def abs(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.abs <numpy.abs>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in abs")
return Array._new(np.abs(x._array))
# Note: the function name is different here
def acos(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arccos <numpy.arccos>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in acos")
return Array._new(np.arccos(x._array))
# Note: the function name is different here
def acosh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arccosh <numpy.arccosh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in acosh")
return Array._new(np.arccosh(x._array))
def add(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.add <numpy.add>`.
See its docstring for more information.
"""
if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in add")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.add(x1._array, x2._array))
# Note: the function name is different here
def asin(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arcsin <numpy.arcsin>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in asin")
return Array._new(np.arcsin(x._array))
# Note: the function name is different here
def asinh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arcsinh <numpy.arcsinh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in asinh")
return Array._new(np.arcsinh(x._array))
# Note: the function name is different here
def atan(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arctan <numpy.arctan>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in atan")
return Array._new(np.arctan(x._array))
# Note: the function name is different here
def atan2(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arctan2 <numpy.arctan2>`.
See its docstring for more information.
"""
if x1.dtype not in _real_floating_dtypes or x2.dtype not in _real_floating_dtypes:
raise TypeError("Only real floating-point dtypes are allowed in atan2")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.arctan2(x1._array, x2._array))
# Note: the function name is different here
def atanh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.arctanh <numpy.arctanh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in atanh")
return Array._new(np.arctanh(x._array))
def bitwise_and(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.bitwise_and <numpy.bitwise_and>`.
See its docstring for more information.
"""
if (
x1.dtype not in _integer_or_boolean_dtypes
or x2.dtype not in _integer_or_boolean_dtypes
):
raise TypeError("Only integer or boolean dtypes are allowed in bitwise_and")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.bitwise_and(x1._array, x2._array))
# Note: the function name is different here
def bitwise_left_shift(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.left_shift <numpy.left_shift>`.
See its docstring for more information.
"""
if x1.dtype not in _integer_dtypes or x2.dtype not in _integer_dtypes:
raise TypeError("Only integer dtypes are allowed in bitwise_left_shift")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
# Note: bitwise_left_shift is only defined for x2 nonnegative.
if np.any(x2._array < 0):
raise ValueError("bitwise_left_shift(x1, x2) is only defined for x2 >= 0")
return Array._new(np.left_shift(x1._array, x2._array))
# Note: the function name is different here
def bitwise_invert(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.invert <numpy.invert>`.
See its docstring for more information.
"""
if x.dtype not in _integer_or_boolean_dtypes:
raise TypeError("Only integer or boolean dtypes are allowed in bitwise_invert")
return Array._new(np.invert(x._array))
def bitwise_or(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.bitwise_or <numpy.bitwise_or>`.
See its docstring for more information.
"""
if (
x1.dtype not in _integer_or_boolean_dtypes
or x2.dtype not in _integer_or_boolean_dtypes
):
raise TypeError("Only integer or boolean dtypes are allowed in bitwise_or")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.bitwise_or(x1._array, x2._array))
# Note: the function name is different here
def bitwise_right_shift(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.right_shift <numpy.right_shift>`.
See its docstring for more information.
"""
if x1.dtype not in _integer_dtypes or x2.dtype not in _integer_dtypes:
raise TypeError("Only integer dtypes are allowed in bitwise_right_shift")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
# Note: bitwise_right_shift is only defined for x2 nonnegative.
if np.any(x2._array < 0):
raise ValueError("bitwise_right_shift(x1, x2) is only defined for x2 >= 0")
return Array._new(np.right_shift(x1._array, x2._array))
def bitwise_xor(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.bitwise_xor <numpy.bitwise_xor>`.
See its docstring for more information.
"""
if (
x1.dtype not in _integer_or_boolean_dtypes
or x2.dtype not in _integer_or_boolean_dtypes
):
raise TypeError("Only integer or boolean dtypes are allowed in bitwise_xor")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.bitwise_xor(x1._array, x2._array))
def ceil(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.ceil <numpy.ceil>`.
See its docstring for more information.
"""
if x.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in ceil")
if x.dtype in _integer_dtypes:
# Note: The return dtype of ceil is the same as the input
return x
return Array._new(np.ceil(x._array))
def conj(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.conj <numpy.conj>`.
See its docstring for more information.
"""
if x.dtype not in _complex_floating_dtypes:
raise TypeError("Only complex floating-point dtypes are allowed in conj")
return Array._new(np.conj(x))
def cos(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.cos <numpy.cos>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in cos")
return Array._new(np.cos(x._array))
def cosh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.cosh <numpy.cosh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in cosh")
return Array._new(np.cosh(x._array))
def divide(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.divide <numpy.divide>`.
See its docstring for more information.
"""
if x1.dtype not in _floating_dtypes or x2.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in divide")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.divide(x1._array, x2._array))
def equal(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.equal <numpy.equal>`.
See its docstring for more information.
"""
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.equal(x1._array, x2._array))
def exp(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.exp <numpy.exp>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in exp")
return Array._new(np.exp(x._array))
def expm1(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.expm1 <numpy.expm1>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in expm1")
return Array._new(np.expm1(x._array))
def floor(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.floor <numpy.floor>`.
See its docstring for more information.
"""
if x.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in floor")
if x.dtype in _integer_dtypes:
# Note: The return dtype of floor is the same as the input
return x
return Array._new(np.floor(x._array))
def floor_divide(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.floor_divide <numpy.floor_divide>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in floor_divide")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.floor_divide(x1._array, x2._array))
def greater(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.greater <numpy.greater>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in greater")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.greater(x1._array, x2._array))
def greater_equal(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.greater_equal <numpy.greater_equal>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in greater_equal")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.greater_equal(x1._array, x2._array))
def imag(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.imag <numpy.imag>`.
See its docstring for more information.
"""
if x.dtype not in _complex_floating_dtypes:
raise TypeError("Only complex floating-point dtypes are allowed in imag")
return Array._new(np.imag(x))
def isfinite(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.isfinite <numpy.isfinite>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in isfinite")
return Array._new(np.isfinite(x._array))
def isinf(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.isinf <numpy.isinf>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in isinf")
return Array._new(np.isinf(x._array))
def isnan(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.isnan <numpy.isnan>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in isnan")
return Array._new(np.isnan(x._array))
def less(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.less <numpy.less>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in less")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.less(x1._array, x2._array))
def less_equal(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.less_equal <numpy.less_equal>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in less_equal")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.less_equal(x1._array, x2._array))
def log(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.log <numpy.log>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in log")
return Array._new(np.log(x._array))
def log1p(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.log1p <numpy.log1p>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in log1p")
return Array._new(np.log1p(x._array))
def log2(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.log2 <numpy.log2>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in log2")
return Array._new(np.log2(x._array))
def log10(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.log10 <numpy.log10>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in log10")
return Array._new(np.log10(x._array))
def logaddexp(x1: Array, x2: Array) -> Array:
"""
Array API compatible wrapper for :py:func:`np.logaddexp <numpy.logaddexp>`.
See its docstring for more information.
"""
if x1.dtype not in _real_floating_dtypes or x2.dtype not in _real_floating_dtypes:
raise TypeError("Only real floating-point dtypes are allowed in logaddexp")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.logaddexp(x1._array, x2._array))
def logical_and(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.logical_and <numpy.logical_and>`.
See its docstring for more information.
"""
if x1.dtype not in _boolean_dtypes or x2.dtype not in _boolean_dtypes:
raise TypeError("Only boolean dtypes are allowed in logical_and")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.logical_and(x1._array, x2._array))
def logical_not(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.logical_not <numpy.logical_not>`.
See its docstring for more information.
"""
if x.dtype not in _boolean_dtypes:
raise TypeError("Only boolean dtypes are allowed in logical_not")
return Array._new(np.logical_not(x._array))
def logical_or(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.logical_or <numpy.logical_or>`.
See its docstring for more information.
"""
if x1.dtype not in _boolean_dtypes or x2.dtype not in _boolean_dtypes:
raise TypeError("Only boolean dtypes are allowed in logical_or")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.logical_or(x1._array, x2._array))
def logical_xor(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.logical_xor <numpy.logical_xor>`.
See its docstring for more information.
"""
if x1.dtype not in _boolean_dtypes or x2.dtype not in _boolean_dtypes:
raise TypeError("Only boolean dtypes are allowed in logical_xor")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.logical_xor(x1._array, x2._array))
def multiply(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.multiply <numpy.multiply>`.
See its docstring for more information.
"""
if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in multiply")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.multiply(x1._array, x2._array))
def negative(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.negative <numpy.negative>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in negative")
return Array._new(np.negative(x._array))
def not_equal(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.not_equal <numpy.not_equal>`.
See its docstring for more information.
"""
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.not_equal(x1._array, x2._array))
def positive(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.positive <numpy.positive>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in positive")
return Array._new(np.positive(x._array))
# Note: the function name is different here
def pow(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.power <numpy.power>`.
See its docstring for more information.
"""
if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in pow")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.power(x1._array, x2._array))
def real(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.real <numpy.real>`.
See its docstring for more information.
"""
if x.dtype not in _complex_floating_dtypes:
raise TypeError("Only complex floating-point dtypes are allowed in real")
return Array._new(np.real(x))
def remainder(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.remainder <numpy.remainder>`.
See its docstring for more information.
"""
if x1.dtype not in _real_numeric_dtypes or x2.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in remainder")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.remainder(x1._array, x2._array))
def round(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.round <numpy.round>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in round")
return Array._new(np.round(x._array))
def sign(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.sign <numpy.sign>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in sign")
return Array._new(np.sign(x._array))
def sin(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.sin <numpy.sin>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in sin")
return Array._new(np.sin(x._array))
def sinh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.sinh <numpy.sinh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in sinh")
return Array._new(np.sinh(x._array))
def square(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.square <numpy.square>`.
See its docstring for more information.
"""
if x.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in square")
return Array._new(np.square(x._array))
def sqrt(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.sqrt <numpy.sqrt>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in sqrt")
return Array._new(np.sqrt(x._array))
def subtract(x1: Array, x2: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.subtract <numpy.subtract>`.
See its docstring for more information.
"""
if x1.dtype not in _numeric_dtypes or x2.dtype not in _numeric_dtypes:
raise TypeError("Only numeric dtypes are allowed in subtract")
# Call result type here just to raise on disallowed type combinations
_result_type(x1.dtype, x2.dtype)
x1, x2 = Array._normalize_two_args(x1, x2)
return Array._new(np.subtract(x1._array, x2._array))
def tan(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.tan <numpy.tan>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in tan")
return Array._new(np.tan(x._array))
def tanh(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.tanh <numpy.tanh>`.
See its docstring for more information.
"""
if x.dtype not in _floating_dtypes:
raise TypeError("Only floating-point dtypes are allowed in tanh")
return Array._new(np.tanh(x._array))
def trunc(x: Array, /) -> Array:
"""
Array API compatible wrapper for :py:func:`np.trunc <numpy.trunc>`.
See its docstring for more information.
"""
if x.dtype not in _real_numeric_dtypes:
raise TypeError("Only real numeric dtypes are allowed in trunc")
if x.dtype in _integer_dtypes:
# Note: The return dtype of trunc is the same as the input
return x
return Array._new(np.trunc(x._array))
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