Source code for mars.tensor.arithmetic.isfinite

#!/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 TensorIsFinite(TensorUnaryOp):
    _op_type_ = OperandDef.ISFINITE
    _func_name = "isfinite"

[docs]@inject_dtype(np.bool_) def isfinite(x, out=None, where=None, **kwargs): """ Test element-wise for finiteness (not infinity or not Not a Number). The result is returned as a boolean tensor. 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 : Tensor, bool For scalar input, the result is a new boolean with value True if the input is finite; otherwise the value is False (input is either positive infinity, negative infinity or Not a Number). For array input, the result is a boolean array with the same dimensions as the input and the values are True if the corresponding element of the input is finite; otherwise the values are False (element is either positive infinity, negative infinity or Not a Number). See Also -------- isinf, isneginf, isposinf, isnan Notes ----- Not a Number, positive infinity and negative infinity are considered to be non-finite. Mars uses the IEEE Standard for Binary Floating-Point for Arithmetic (IEEE 754). This means that Not a Number is not equivalent to infinity. Also that positive infinity is not equivalent to negative infinity. But infinity is equivalent to positive infinity. Errors result if the second argument is also supplied when `x` is a scalar input, or if first and second arguments have different shapes. Examples -------- >>> import mars.tensor as mt >>> mt.isfinite(1).execute() True >>> mt.isfinite(0).execute() True >>> mt.isfinite(mt.nan).execute() False >>> mt.isfinite(mt.inf).execute() False >>> mt.isfinite(mt.NINF).execute() False >>> mt.isfinite([mt.log(-1.).execute(),1.,mt.log(0).execute()]).execute() array([False, True, False]) >>> x = mt.array([-mt.inf, 0., mt.inf]) >>> y = mt.array([2, 2, 2]) >>> mt.isfinite(x, y).execute() array([0, 1, 0]) >>> y.execute() array([0, 1, 0]) """ op = TensorIsFinite(**kwargs) return op(x, out=out, where=where)