epraya.LSquare1

LSquare1(Ham1, Expe, Vary, exper, maximal=1000, mode='p')

Fitting adjutsment of the experimental data using the scipy.optimize.least_squares method. This case is for simple systems.

Parameters:

• Ham1 (Class) – Container for the hamiltonian parameters.

• Expe (Class) – Container for the experimental conditions.

• Vary (Class) – Container for the range and parameters to vary.

• exper (np.array) – Experimental spectrum data to fit.

• maximal (int) – Max. number of evaluations of the function.

• mode (str) – Defines the sample type, ‘p’ for powder and ‘c’ for monocristal.

Returns:

spc (np.array) – Best adjusted spectrum using the Powder or Eresonant functions.