Source code for mars.tensor.arithmetic.isinf

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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import numpy as np

from ... import opcodes as OperandDef
from ..utils import inject_dtype
from .core import TensorUnaryOp
from .utils import arithmetic_operand

class TensorIsInf(TensorUnaryOp):
    _op_type_ = OperandDef.ISINF
    _func_name = "isinf"

[docs]@inject_dtype(np.bool_) def isinf(x, out=None, where=None, **kwargs): """ Test element-wise for positive or negative infinity. Returns a boolean array of the same shape as `x`, True where ``x == +/-inf``, otherwise False. Parameters ---------- x : array_like Input values out : Tensor, None, or tuple of Tensor and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or `None`, a freshly-allocated tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs Returns ------- y : bool (scalar) or boolean Tensor For scalar input, the result is a new boolean with value True if the input is positive or negative infinity; otherwise the value is False. For tensor input, the result is a boolean tensor with the same shape as the input and the values are True where the corresponding element of the input is positive or negative infinity; elsewhere the values are False. If a second argument was supplied the result is stored there. If the type of that array is a numeric type the result is represented as zeros and ones, if the type is boolean then as False and True, respectively. The return value `y` is then a reference to that tensor. See Also -------- isneginf, isposinf, isnan, isfinite Notes ----- Mars uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). Errors result if the second argument is supplied when the first argument is a scalar, or if the first and second arguments have different shapes. Examples -------- >>> import mars.tensor as mt >>> mt.isinf(mt.inf).execute() True >>> mt.isinf(mt.nan).execute() False >>> mt.isinf(mt.NINF).execute() True >>> mt.isinf([mt.inf, -mt.inf, 1.0, mt.nan]).execute() array([ True, True, False, False]) >>> x = mt.array([-mt.inf, 0., mt.inf]) >>> y = mt.array([2, 2, 2]) >>> mt.isinf(x, y).execute() array([1, 0, 1]) >>> y.execute() array([1, 0, 1]) """ op = TensorIsInf(**kwargs) return op(x, out=out, where=where)