classobj Levenberg_marquardt

Instance Methods

__init__(self, chi2_func, dchi2_func, dfunc, errors, args, x0, func_tol, grad_tol, maxiter, full_output, print_flag, print_prefix)
Class for Levenberg-Marquardt minimisation specific functions.

create_lm_matrix(self)
Function to create the Levenberg-Marquardt matrix.

new_param_func(self)
Find the new parameter vector self.xk_new.

test_mod(self, fk_new, fk, dfk_new)
Modified convergence test.

update(self)
Update function

Inherited from base_classes.Min: double_test, func_test, grad_test, hessian_type_and_mod, minimise, setup_conv_tests

Method Details

__init__(self, chi2_func, dchi2_func, dfunc, errors, args, x0, func_tol, grad_tol, maxiter, full_output, print_flag, print_prefix)
(Constructor)

Class for Levenberg-Marquardt minimisation specific functions.

Unless you know what you are doing, you should call the function 'levenberg_marquardt' rather than using this class.

Overrides: base_classes.Min.__init__

create_lm_matrix(self)

Function to create the Levenberg-Marquardt matrix.

The matrix is:

                  _n_
                  \   /     1        d y(xi)   d y(xi)                \ 
   LM_matrix_jk =  >  | ---------- . ------- . ------- . (1 + lambda) |
                  /__ \ sigma_i**2     dj        dk                   /
                  i=1

where j == k is one of the function parameters, and:

                  _n_
                  \   /     1        d y(xi)   d y(xi) \ 
   LM_matrix_jk =  >  | ---------- . ------- . ------- |
                  /__ \ sigma_i**2     dj        dk    /
                  i=1

where j != k are function parameters.

test_mod(self, fk_new, fk, dfk_new)

Modified convergence test.

This is needed to prevent the Levenberg-Marquardt minimiser from terminating if there is no movement during an iteration due to an uphill step being encountered.

update(self)

Update function

Update the chi-squared value, chi-squared gradient vector, and derivative function matrix.

Overrides: base_classes.Min.update