# Source code for mars.tensor.arithmetic.cosh

#!/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 TensorCosh(TensorUnaryOp):
_op_type_ = OperandDef.COSH
_func_name = "cosh"
[docs]@infer_dtype(np.cosh)
def cosh(x, out=None, where=None, **kwargs):
"""
Hyperbolic cosine, element-wise.
Equivalent to ``1/2 * (mt.exp(x) + mt.exp(-x))`` and ``mt.cos(1j*x)``.
Parameters
----------
x : array_like
Input tensor.
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
-------
out : Tensor
Output array of same shape as `x`.
Examples
--------
>>> import mars.tensor as mt
>>> mt.cosh(0).execute()
1.0
The hyperbolic cosine describes the shape of a hanging cable:
>>> import matplotlib.pyplot as plt
>>> x = mt.linspace(-4, 4, 1000)
>>> plt.plot(x.execute(), mt.cosh(x).execute())
>>> plt.show()
"""
op = TensorCosh(**kwargs)
return op(x, out=out, where=where)