dpnp.scipy.special.erf

dpnp.scipy.special.erf = <DPNPUnaryFunc 'erf'>

Calculates the Gauss error function of a given input array.

It is defined as \(\frac{2}{\sqrt{\pi}} \int_{0}^{z} e^{-t^2} \, dt\).

For full documentation refer to scipy.special.erf.

Parameters:

x{dpnp.ndarray, usm_ndarray}

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

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

Optional output array for the function values. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.

Default: None.

Returns:

outdpnp.ndarray

The values of the error function at the given points x.

See also

dpnp.scipy.special.erfc

Complementary error function.

dpnp.scipy.special.erfinv

Inverse of the error function.

dpnp.scipy.special.erfcinv

Inverse of the complementary error function.

dpnp.scipy.special.erfcx

Scaled complementary error function.

dpnp.scipy.special.erfi

Imaginary error function.

Notes

The cumulative of the unit normal distribution is given by

\[\Phi(z) = \frac{1}{2} \left[ 1 + \operatorname{erf} \left( \frac{z}{\sqrt{2}} \right) \right]\]

Examples

>>> import dpnp as np
>>> x = np.linspace(-3, 3, num=5)
>>> np.scipy.special.erf(x)
array([[-0.99997791, -0.96610515,  0.        ,  0.96610515,  0.99997791])