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    Metadata details:
    filename: dtr1r2d_dist2dps1d.m
    path of file: ./repos/md-dmri/methods/dtr1r2d
    
    the code of the file until where you have to start completion: function dps1d = dtr1r2d_dist2dps1d(dtr1r2d)

    
function dps1d = dtr1r2d_dist2dps1d(dtr1r2d)
% dps1d = dtr1r2d_dist2dps1d(dtr1r2d)
%
% Converts discrete diffusion tensor distribution to derived tensors and
% parameters. Equation numbers refer to definitions given in
% Topgaard. J. Magn. Reson. 275, 98 (2017).
% http://dx.doi.org/10.1016/j.jmr.2016.12.007
%
% Input arguments
% dtr1r2d: diffusion tensor distribution
%
% Output
% dps: derived parameters structure with fields
% s0: total amplitude = b0 signal
% miso: mean isotropic diffusivity, Eq (7.26)
% viso: variance of isotropic diffusivities, Eq (7.27)
% maniso: mean anisotropic diffusivity, Eq (7.28)
% vaniso: variance of anistropic diffusivities
% msqaniso: mean-square anisotropic diffusivity, Eq (7.29)
% vsqaniso: variance of squared anisotropic diffusivities
% t1x6: mean diffusion tensor in Voigt notation, 
% ct1x21: covariance tensor in Voigt-like notation, Eq (7.78)

dps1d.s0 = zeros([1 1]);
dps1d.t1x6 = zeros([1 6]);
dps1d.lambdazzvec = zeros([1 3]);
dps1d.lambdaxxvec = zeros([1 3]);
dps1d.lambdayyvec = zeros([1 3]);
dps1d.lambda11vec = zeros([1 3]);
dps1d.lambda22vec = zeros([1 3]);
dps1d.lambda33vec = zeros([1 3]);
dtiparam = {'trace','iso','lambda33','lambda22','lambda11','lambdazz','lambdaxx','lambdayy','vlambda',...
    'delta','eta','s','p','l','fa','cs','cl','cp','cm'};
param = {dtiparam{:},'miso','viso','maniso','vaniso','msqaniso','vsqaniso'};
for nparam = 1:numel(param)
    eval(['dps1d.' param{nparam} ' = zeros([1 1 1]);']);
end