# 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:
    x ndarray

      The ndarray to apply logit to element-wise.

    out ndarray, 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

  `expit`

  Notes

  As a ufunc logit takes a number of optional keyword arguments. For more information see ufuncs

  New in version 0.10.0.

  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])

  `expit` is 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()