def derivativeX(self, x, y):
    '\n        Evaluates the partial derivative of interpolated function with respect\n        to x (the first argument) at the given input.\n\n        Parameters\n        ----------\n        x : np.array or float\n            Real values to be evaluated in the interpolated function.\n        y : np.array or float\n            Real values to be evaluated in the interpolated function; must be\n            the same size as x.\n\n        Returns\n        -------\n        dfdx : np.array or float\n            The derivative of the interpolated function with respect to x, eval-\n            uated at x,y: dfdx = f_x(x,y), with the same shape as x and y.\n        '
    xa = np.asarray(x)
    ya = np.asarray(y)
    return self._derX(xa.flatten(), ya.flatten()).reshape(xa.shape)
Evaluates the partial derivative of interpolated function with respect
to x (the first argument) at the given input.

Parameters
----------
x : np.array or float
    Real values to be evaluated in the interpolated function.
y : np.array or float
    Real values to be evaluated in the interpolated function; must be
    the same size as x.

Returns
-------
dfdx : np.array or float
    The derivative of the interpolated function with respect to x, eval-
    uated at x,y: dfdx = f_x(x,y), with the same shape as x and y.
def derivativeX(self, x, y):
    '\n        Evaluates the partial derivative of interpolated function with respect\n        to x (the first argument) at the given input.\n\n        Parameters\n        ----------\n        x : np.array or float\n            Real values to be evaluated in the interpolated function.\n        y : np.array or float\n            Real values to be evaluated in the interpolated function; must be\n            the same size as x.\n\n        Returns\n        -------\n        dfdx : np.array or float\n            The derivative of the interpolated function with respect to x, eval-\n            uated at x,y: dfdx = f_x(x,y), with the same shape as x and y.\n        '
    xa = np.asarray(x)
    ya = np.asarray(y)
    return self._derX(xa.flatten(), ya.flatten()).reshape(xa.shape)