scipy.special.ndtri#
- scipy.special.ndtri(y, out=None) = <ufunc 'ndtri'>#
- Inverse of - ndtrvs x- Returns the argument x for which the area under the standard normal probability density function (integrated from minus infinity to x) is equal to y. - Parameters:
- parray_like
- Probability 
- outndarray, optional
- Optional output array for the function results 
 
- Returns:
- xscalar or ndarray
- Value of x such that - ndtr(x) == p.
 
 - Notes - ndtrihas 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=1and 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 - ndtriis the percentile function of the standard normal distribution. This means it returns the inverse of the cumulative density- ndtr. First, let us compute a cumulative density value.- >>> import numpy as np >>> from scipy.special import ndtri, ndtr >>> cdf_val = ndtr(2) >>> cdf_val 0.9772498680518208 - Verify that - ndtriyields the original value for x up to floating point errors.- >>> ndtri(cdf_val) 2.0000000000000004 - Plot the function. For that purpose, we provide a NumPy array as argument. - >>> import matplotlib.pyplot as plt >>> x = np.linspace(0.01, 1, 200) >>> fig, ax = plt.subplots() >>> ax.plot(x, ndtri(x)) >>> ax.set_title("Standard normal percentile function") >>> plt.show() 