With the simulation tools of FID-A-master I created simulated spectra of triglycerides observed with PRESS. A Matlab function Sim_UFATG_PRESS.m creates the spin systems for all protons of (poly)(un)saturated fatty acids of variable chain lengths and glycerol to simulate biological triglycerides.
In the package I included a function for plotting simulation output as single spectra or as a stacked plot and a spin system of triglyceride. It also includes a function to sum the outputs of simulations so we can build biological fats or oils with various amounts of unsaturated or saturated fatty acids by summing the simulation outputs.
Unfortunately I can’t attach the software in a .zip format (as per instructions on https://mrshub.org/software_contribute/) because only jpg, jpeg, png, gif, txt, md, pdf are authorized extentions. I hope to learn how I can upload the zip file soon.
Thank you, that is an awesome submission! I’ve received your e-mail, uploaded your code to the MRSHub GitHub repository, and created an entry in the Software & Code section of the MRSHub.
My sincere apologies that you weren’t able to upload .zip files as attachment to your post - this was a restriction of the forum software that I have now fixed… so please don’t hesitate to try again with your next submission
Thanks again!
Best wishes,
Georg (on behalf of the MRSHub Team)
Hi,
Sorry for this omission. gausmult.m is simply applying a Gaussian line broadening to the signals. See Code below
Ronald
function gsdata = gausmult(data, width, SW, tbegin )
%============================================================================
% function gsdata = gausmult(data, width, SW, tbegin);
% INPUT:
% data = complex time domain data in columns
% [m,n] = size(data) then m is the number of time points and n is the
% number of signals
% width : line broadening in Hz (default 2 Hz)
% SW is spectral width Hz ( default 1500)
% tbegin, tste begin time and step time on s ( default 0 and 1e-3 )
%==========================================================================
[m,n] = size(data);
if nargin < 2
width = 2;
end
if nargin < 3
SW = 1500;
end
if nargin < 4
tbegin = 0;
end
tstep = 1/SW;
% Fourier transform of a Gaussian
% FTexp( -ax^2) = sqrt( pi/a)* exp( -pi^2k^2/a)
% half height in freq domain is when exp( -pi^2k^2/a) = 0.5
% so ln( 2 ) = pi^2k^2/a, or aln(2)/pi^2 = k^2
% Substittute the desired line width lw for k
% ( lw/2 )^2 = -a*ln(2)/pi^2
% Now a = ( lw/2 pi )^2 /ln(2)
widthsq = (piwidth/2)^2/log(2);
time = (tbegin+(0:m-1)’*tstep);
if n ==1
timesq = time.^2;
gsdata = data.exp(-timesqwidthsq);
else
time = time( :, ones(1,n) );
timesq = time.^2;
gsdata = data.exp(-timesqwidthsq);
end
