scipy.special.ndtr#

scipy.special.ndtr(x, out=None) = <ufunc 'ndtr'>#

Cumulative distribution of the standard normal distribution.

Returns the area under the standard Gaussian probability density function, integrated from minus infinity to x

\[\frac{1}{\sqrt{2\pi}} \int_{-\infty}^x \exp(-t^2/2) dt\]
Parameters:
xarray_like, real or complex

Argument

outndarray, optional

Optional output array for the function results

Returns:
scalar or ndarray

The value of the normal CDF evaluated at x

See also

log_ndtr

Logarithm of ndtr

ndtri

Inverse of ndtr, standard normal percentile function

erf

Error function

erfc

1 - erf

scipy.stats.norm

Normal distribution

Notes

ndtr has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

Library

CPU

GPU

NumPy

n/a

CuPy

n/a

PyTorch

JAX

Dask

n/a

See Support for the array API standard for more information.

Examples

Evaluate ndtr at one point.

>>> import numpy as np
>>> from scipy.special import ndtr
>>> ndtr(0.5)
0.6914624612740131

Evaluate the function at several points by providing a NumPy array or list for x.

>>> ndtr([0, 0.5, 2])
array([0.5       , 0.69146246, 0.97724987])

Plot the function.

>>> import matplotlib.pyplot as plt
>>> x = np.linspace(-5, 5, 100)
>>> fig, ax = plt.subplots()
>>> ax.plot(x, ndtr(x))
>>> ax.set_title(r"Standard normal cumulative distribution function $\Phi$")
>>> plt.show()
../../_images/scipy-special-ndtr-1.png