# Source code for mars.tensor.arithmetic.expm1

#!/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.
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#
# 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 TensorExpm1(TensorUnaryOp):
_op_type_ = OperandDef.EXPM1
_func_name = "expm1"
[docs]@infer_dtype(np.expm1)
def expm1(x, out=None, where=None, **kwargs):
"""
Calculate ``exp(x) - 1`` for all elements in the 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
-------
out : Tensor
Element-wise exponential minus one: ``out = exp(x) - 1``.
See Also
--------
log1p : ``log(1 + x)``, the inverse of expm1.
Notes
-----
This function provides greater precision than ``exp(x) - 1``
for small values of ``x``.
Examples
--------
The true value of ``exp(1e-10) - 1`` is ``1.00000000005e-10`` to
about 32 significant digits. This example shows the superiority of
expm1 in this case.
>>> import mars.tensor as mt
>>> mt.expm1(1e-10).execute()
1.00000000005e-10
>>> (mt.exp(1e-10) - 1).execute()
1.000000082740371e-10
"""
op = TensorExpm1(**kwargs)
return op(x, out=out, where=where)