mars.tensor.expm1#

mars.tensor.expm1(x, out=None, where=None, **kwargs)[source]#

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 – Element-wise exponential minus one: out = exp(x) - 1.

Return type

Tensor

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