dpnp.expm1

dpnp.expm1 = <DPNPUnaryFunc 'expm1'>

Computes the exponential minus 1 for each element \(x_i\) of input array x.

For full documentation refer to numpy.expm1.

Parameters:

x{dpnp.ndarray, usm_ndarray}

Input array, expected to have a floating-point data type.

out{None, dpnp.ndarray, usm_ndarray, tuple of ndarray}, optional

Output array to populate. Array must have the correct shape and the expected data type. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Default: None.

order{None, "C", "F", "A", "K"}, optional

Memory layout of the newly output array, if parameter out is None.

Default: "K".

Returns:

outdpnp.ndarray

An array containing containing the evaluated result for each element in x. The data type of the returned array is determined by the Type Promotion Rules.

Limitations

Parameters where and subok are supported with their default values. Keyword argument kwargs is currently unsupported. Otherwise NotImplementedError exception will be raised.

See also

dpnp.exp

Calculate \(e^x\), element-wise.

dpnp.exp2

Calculate \(2^x\), element-wise.

dpnp.log1p

Calculate \(\log(1 + x)\), element-wise, the inverse of dpnp.expm1.

Notes

This function provides greater precision than \(e^x - 1\) for small values of x.

Examples

>>> import dpnp as np
>>> x = np.arange(3.)
>>> np.expm1(x)
array([0.0, 1.718281828, 6.389056099])

>>> np.expm1(np.array(1e-10))
array(1.00000000005e-10)

>>> np.exp(np.array(1e-10)) - 1
array(1.000000082740371e-10)