scipy.special.logit#
- scipy.special.logit(x, out=None) = <ufunc 'logit'>#
- Logit ufunc for ndarrays. - The logit function is defined as logit(p) = log(p/(1-p)). Note that logit(0) = -inf, logit(1) = inf, and logit(p) for p<0 or p>1 yields nan. - Parameters:
- xndarray
- The ndarray to apply logit to element-wise. 
- outndarray, optional
- Optional output array for the function results 
 
- Returns:
- scalar or ndarray
- An ndarray of the same shape as x. Its entries are logit of the corresponding entry of x. 
 
 - See also - Notes - As a ufunc logit takes a number of optional keyword arguments. For more information see ufuncs - Added in version 0.10.0. - logithas 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 - >>> import numpy as np >>> from scipy.special import logit, expit - >>> logit([0, 0.25, 0.5, 0.75, 1]) array([ -inf, -1.09861229, 0. , 1.09861229, inf]) - expitis the inverse of- logit:- >>> expit(logit([0.1, 0.75, 0.999])) array([ 0.1 , 0.75 , 0.999]) - Plot logit(x) for x in [0, 1]: - >>> import matplotlib.pyplot as plt >>> x = np.linspace(0, 1, 501) >>> y = logit(x) >>> plt.plot(x, y) >>> plt.grid() >>> plt.ylim(-6, 6) >>> plt.xlabel('x') >>> plt.title('logit(x)') >>> plt.show() 