| 
  | levenberg_marquardt(chi2_func=None,
        dchi2_func=None,
        dfunc=None,
        errors=None,
        args=(),
        x0=None,
        func_tol=1e-25,
        grad_tol=None,
        maxiter=1000000.0,
        print_flag=0,
        print_prefix='',
        full_output=False) | source code |  Levenberg-Marquardt minimisation. 
    Parameters:
        chi2_func- User supplied chi-squared function which is run with the function
          parameters and args as options.chi2_func- funcdchi2_func- User supplied chi-squared gradient function which is run with the
          function parameters and args as options.dchi2_func- funcdfunc- User supplied function which should return a vector of partial 
          derivatives of the function which back calculates values for the 
          chi-squared function.dfunc- funcerrors- The experimental errors.errors- numpy rank-1 arrayargs- A tuple containing the arguments to send to chi2_func and 
          dchi2_func.args- tuplex0- The initial function parameter values.x0- numpy rank-1 arrayfunc_tol(float) - The function tolerance value.  Once the function value between 
          iterations decreases below this value, minimisation is 
          terminated.grad_tol(float) - The gradient tolerance value.maxiter- The maximum number of iterations.maxiter- intprint_flag(int) - A flag specifying how much information should be printed to 
          standard output during minimisation.  0 means no output, 1 means 
          minimal output, and values above 1 increase the amount of output 
          printed.print_prefix(str) - The text to add out to the front of all printouts.full_output- A flag specifying what should be returned.  If full_output is 
          False, the parameter values and chi-squared value are returned as
          a tuple.  If full_output is True, the parameter values, 
          chi-squared value, number of iterations, and the warning flag are
          returned as a tuple.full_output- bool |