def calculate_jacobian(Ih_table):
"""Calculate the jacobian matrix, size Ih_table.size by len(self.apm.x)."""
gsq = np.square(Ih_table.inverse_scale_factors) * Ih_table.weights
sumgsq = Ih_table.sum_in_groups(gsq)
dIh = (Ih_table.intensities -
(Ih_table.Ih_values * 2.0 *
Ih_table.inverse_scale_factors)) * Ih_table.weights
jacobian = calc_jacobian(
Ih_table.derivatives.transpose(),
Ih_table.h_index_matrix,
flumpy.from_numpy(Ih_table.Ih_values),
flumpy.from_numpy(Ih_table.inverse_scale_factors),
flumpy.from_numpy(dIh),
flumpy.from_numpy(sumgsq),
)
return jacobian
def calculate_jacobian(Ih_table):
"""Calculate the jacobian matrix, size Ih_table.size by len(self.apm.x)."""
gsq = Ih_table.inverse_scale_factors**2 * Ih_table.weights
sumgsq = gsq * Ih_table.h_index_matrix
dIh = (Ih_table.intensities -
(Ih_table.Ih_values * 2.0 *
Ih_table.inverse_scale_factors)) * Ih_table.weights
jacobian = calc_jacobian(
Ih_table.derivatives.transpose(),
Ih_table.h_index_matrix,
Ih_table.Ih_values,
Ih_table.inverse_scale_factors,
dIh,
sumgsq,
)
return jacobian