You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: dtd_covariance_1d_data2fit.m
    path of file: ./repos/md-dmri/methods/dtd_covariance
    
    the code of the file until where you have to start completion: function [m,cond,n_rank] = dtd_covariance_1d_data2fit(signal, xps, opt, ind)

    
function [m,cond,n_rank] = dtd_covariance_1d_data2fit(signal, xps, opt, ind)
% function [m,cond,n_rank] = dtd_covariance_1d_data2fit(signal, xps, opt, ind)
%
% Diffusion tensor distribution (DTD) modeling using cumulant expansion:
% This function calculates the first two terms of the cumulant expansion
% from Q-space trajectory (QTI) data.
%
% In the cumulant expansion
% - The first term corresponds to the mean of the tensor distribution, a second order
%   tensor, which is closely realted to the diffusion tensor in DTI
% - The second term is the covariance of the tensor distribution, a fourth order tensor
%
% The output from this function will be a model parameter vector of
% dimension 1 + 6 + 21 = 28
%
% The second output is the condition number of the matrix used in the
% inversion
%
% For details, see Westin et al (2016) NeuroImage 135

if (nargin < 3), opt = dtd_covariance_opt; end