copulas/univariate/gaussian.py
def percent_point(self, U):
        """Given a cumulated distribution value, returns a value in original space.

        Arguments:
            U: `np.ndarray` of shape (n, 1) and values in [0,1]

        Returns:
            `np.ndarray`: Estimated values in original space.
        """
        self.check_fit()
        return norm.ppf(U, loc=self.mean, scale=self.std)
Given a cumulated distribution value, returns a value in original space.

        Arguments:
            U: `np.ndarray` of shape (n, 1) and values in [0,1]

        Returns:
            `np.ndarray`: Estimated values in original space.
        
Given a cumulated distribution value, returns a value in original space.
Given a cumulated distribution value returns a value in original space .
def percent_point(self, U):
        self.check_fit()
        return norm.ppf(U, loc=self.mean, scale=self.std)
def percent_point ( self , U ) : self . check_fit ( ) return norm . ppf ( U , loc = self . mean , scale = self . std )
Given a cumulated distribution value, returns a value in original space.
Given a cumulated distribution value returns a value in original space .
"""Given a cumulated distribution value, returns a value in original space.

        Arguments:
            U: `np.ndarray` of shape (n, 1) and values in [0,1]

        Returns:
            `np.ndarray`: Estimated values in original space.
        """
Estimated values in original space.
Estimated values in original space .
`np.ndarray`
self
U
`np.ndarray` of shape (n, 1) and values in [0,1]
` np . ndarray ` of shape ( n 1 ) and values in [ 0 1 ]