# Source code for mars.tensor.arithmetic.logical_not

#!/usr/bin/env python
# -*- coding: utf-8 -*-
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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import numpy as np
from ... import opcodes as OperandDef
from ..utils import infer_dtype
from .core import TensorUnaryOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode="unary")
class TensorNot(TensorUnaryOp):
_op_type_ = OperandDef.NOT
_func_name = "logical_not"
[docs]@infer_dtype(np.logical_not)
def logical_not(x, out=None, where=None, **kwargs):
"""
Compute the truth value of NOT x element-wise.
Parameters
----------
x : array_like
Logical NOT is applied to the elements of `x`.
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 or Tensor of bool
Boolean result with the same shape as `x` of the NOT operation
on elements of `x`.
See Also
--------
logical_and, logical_or, logical_xor
Examples
--------
>>> import mars.tensor as mt
>>> mt.logical_not(3).execute()
False
>>> mt.logical_not([True, False, 0, 1]).execute()
array([False, True, True, False])
>>> x = mt.arange(5)
>>> mt.logical_not(x<3).execute()
array([False, False, False, True, True])
"""
op = TensorNot(**kwargs)
return op(x, out=out, where=where)