def derivativeX(self, x, y, z):
    '\n        Evaluate the first derivative with respect to x of the function at given\n        state space points.\n\n        Parameters\n        ----------\n        x : np.array\n             First input values.\n        y : np.array\n             Second input values; should be of same shape as x.\n        z : np.array\n             Third input values; should be of same shape as x.\n\n        Returns\n        -------\n        dfdx_out : np.array\n            First derivative of function with respect to the first input,\n            evaluated at (x,y,z), of same shape as inputs.\n        '
    xShift = self.lowerBound(y)
    dfdx_out = self.func.derivativeX((x - xShift), y, z)
    return dfdx_out
Evaluate the first derivative with respect to x of the function at given
state space points.

Parameters
----------
x : np.array
     First input values.
y : np.array
     Second input values; should be of same shape as x.
z : np.array
     Third input values; should be of same shape as x.

Returns
-------
dfdx_out : np.array
    First derivative of function with respect to the first input,
    evaluated at (x,y,z), of same shape as inputs.
def derivativeX(self, x, y, z):
    '\n        Evaluate the first derivative with respect to x of the function at given\n        state space points.\n\n        Parameters\n        ----------\n        x : np.array\n             First input values.\n        y : np.array\n             Second input values; should be of same shape as x.\n        z : np.array\n             Third input values; should be of same shape as x.\n\n        Returns\n        -------\n        dfdx_out : np.array\n            First derivative of function with respect to the first input,\n            evaluated at (x,y,z), of same shape as inputs.\n        '
    xShift = self.lowerBound(y)
    dfdx_out = self.func.derivativeX((x - xShift), y, z)
    return dfdx_out