(self, points)
return np.sum(weights[:, :, None] * parameter_vector, axis=1)
Return the function values.

        Parameters
        ----------
        points : ndarray
            The points at which to evaluate the function. One row for each
            data points.

        Returns
        -------
        values : ndarray
            The function values at the points.
Return the function values.
Return the function values .
def build_evaluation(self, points):
        """Return the function values.

        Parameters
        ----------
        points : ndarray
            The points at which to evaluate the function. One row for each
            data points.

        Returns
        -------
        values : ndarray
            The function values at the points.

        """
        points = np.atleast_2d(points)
        weights, simplices = self._get_weights(points)

        # Return function values
        parameter_vector = self.parameters[simplices]

        # Broadcast the weights along output dimensions
        return np.sum(weights[:, :, None] * parameter_vector, axis=1)
def build_evaluation ( self , points ) : points = np . atleast_2d ( points ) weights , simplices = self . _get_weights ( points ) # Return function values parameter_vector = self . parameters [ simplices ] # Broadcast the weights along output dimensions return np . sum ( weights [ : , : , None ] * parameter_vector , axis = 1 )