Source code for xorbits._mars.tensor.arithmetic.isinf
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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
@arithmetic_operand(sparse_mode="unary")
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)