copulas/univariate/base.py
def _constant_percent_point(self, X):
        """Percent point for the degenerate case of constant distribution.

        Note that the output of this method will be an array whose unique values are `np.nan`
        and self.constant_value.
        More information can be found here: https://en.wikipedia.org/wiki/Degenerate_distribution

        Args:
            X(numpy.ndarray): Percentiles.

        Returns:
            numpy.ndarray:

        """
        return np.full(X.shape, self.constant_value)
Percent point for the degenerate case of constant distribution.

        Note that the output of this method will be an array whose unique values are `np.nan`
        and self.constant_value.
        More information can be found here: https://en.wikipedia.org/wiki/Degenerate_distribution

        Args:
            X(numpy.ndarray): Percentiles.

        Returns:
            numpy.ndarray:

        
Percent point for the degenerate case of constant distribution.
Note that the output of this method will be an array whose unique values are `np.nan`
and self.constant_value.
Percent point for the degenerate case of constant distribution . Note that the output of this method will be an array whose unique values are ` np . nan ` and self . constant_value .
def _constant_percent_point(self, X):
        return np.full(X.shape, self.constant_value)
def _constant_percent_point ( self , X ) : return np . full ( X . shape , self . constant_value )
Percent point for the degenerate case of constant distribution.
Percent point for the degenerate case of constant distribution .
"""Percent point for the degenerate case of constant distribution.

        Note that the output of this method will be an array whose unique values are `np.nan`
        and self.constant_value.
        More information can be found here: https://en.wikipedia.org/wiki/Degenerate_distribution

        Args:
            X(numpy.ndarray): Percentiles.

        Returns:
            numpy.ndarray:

        """
None
numpy.ndarray
self
X
None