Source code for xorbits._mars.tensor.arithmetic.expm1

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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)