Initial commit of existing script and example data

EPR_script.m

@@ -0,0 +1,139 @@
+% high-spin S=1 simulation
+% Go through the script line by line. Every "return" stops it.
+% When you have completed the task, comment out that "return"
+% so the script runs to the next "return"
+% An important part of your task is to understand the script.
+% I will be asking you about this in the exam.
+% This will be easier for those of you who attended the simulation session.
+
+clear all
+close all
+
+%% Baseline Correcting
+load '..\..\Messdaten\TR_EPR\EMX_Aufbau\HU_F2\HU_F2_435nm.mat' % check this matches the name of your data file
+
+whos % what variables have been loaded
+params % what information is contained in the structure called 'params'
+
+ % plot the raw data & check the number of points before the signal (pre-trigger)
+% plot(Data)
+% return
+
+ % substract the pre-trigger. Check how many points from the plot above
+signal_baseline_field = bsxfun(@minus, Data, mean(Data(1:1100,:)));
+% plot(signal_baseline_field) % plot the corrected data set
+% return
+
+ % plot the transpose and check the number of points to the lower and higher fields of the signal
+% plot(signal_baseline_field')
+% use the smaller value below
+% return
+
+ % BASLINE correction
+time_points = 140; % number of points from the plot above
+l1 = mean(signal_baseline_field(:,1:time_points),2); % calculate the mean on the left along the time axis
+l2 = mean(signal_baseline_field(:,end-time_points:end),2); %calculate the mean on the right along the time axis
+baseline_time = (l1 +l2)/2; %take the average
+
+signal_baseline_field_time = bsxfun(@minus, signal_baseline_field, baseline_time); % subtract the background in the time-domain 
+
+ % plot the corrected data set
+% plot(signal_baseline_field_time')
+% return
+
+ % plot the transpose to find the region of maximum signal. Use this below
+% plot(signal_baseline_field_time)
+% return
+
+ % contour plot: The index gives the number of contours
+% contourf(signal_baseline_field_time,6)
+% return
+
+%%
+figure(1)
+set(gcf,'PaperUnits','centimeters')
+set(gcf,'Position',[0,0,750, 750])
+set(gcf,'InvertHardcopy','off','Color',[1 1 1])
+set(0,'DefaultAxesFontSize', 14,'DefaultAxesLineWidth',2)
+
+ % contour plot: add the time and field axes
+subplot(2,1,2)
+contourf(0.1*params.Field_Vector, TimeBase*1e6 ,signal_baseline_field_time,'LineColor','none')
+
+ % contour plot: add the time and field axes
+% surf(0.1*params.Field_Vector, TimeBase*1e6 ,signal_baseline_field_time)
+% colormap default
+% shading interp
+
+xlabel('Magnetic Field / mT')
+ylabel('Time / \mus')
+% colorbar
+% print('TR_EPR_Chichibabin_80K_frozen_solution_532_01_3D' , '-dpng', '-r300')
+% return
+
+subplot(2,1,1)
+
+ % take the mean over the maxium region. You can decide how wide it is
+signal_baseline_field_time_mean = (mean(signal_baseline_field_time(1300:1390,:)));
+ % normalise the amplitude to 1
+signal_baseline_field_time_mean_norm = signal_baseline_field_time_mean/max(signal_baseline_field_time_mean);
+ % plot the spectrum
+plot(0.1*params.Field_Vector,signal_baseline_field_time_mean_norm,'LineWidth',2)
+
+xlabel('Magnetic Field / mT')
+
+axis('tight')
+box off
+return
+
+% print('TR_EPR_Chichibabin_80K_frozen_solution_570_01' , '-dpng', '-r300')
+return
+%% Simulation section. Use the "Run Section" button to avoid running the previous section every time
+
+Exp.mwFreq = params.mwFreq; % GHz
+Exp.nPoints = length(params.Field_Vector);
+Exp.CenterSweep = 0.1*[params.Field_Center params.Field_Sweep]; % mT (converted from Gauss)
+Exp.Harmonic = 0; % zeroth harmonic
+
+Exp.Temperature = [0 0.67 0.33]; % populations of the triplet sub-levels. These need to be varied manually to get the right shape
+
+Sys.S = 1; % Total Spin
+Sys.g = 1.9951; % needs to be optimised
+Sys.D = [2148.02 75.35]; % mT; The D and E values need to be optimised
+Sys.lw = [8.1034 0]; % mT; linewidth needs to be optimised
+
+Vary.g = 0.01; 
+Vary.D = [10 10];
+Vary.lw = [1 0];
+
+FitOpt.Method = 'simplex fcn';
+FitOpt.Scaling = 'lsq';
+
+ % When you have got a good fit by eye, use esfit to optimise
+% esfit('pepper',signal_baseline_field_time_mean_norm,Sys,Vary,Exp,[],FitOpt);%fitting route
+% return
+
+[bfield,spec] = pepper(Sys,Exp); % perform a simulation with the parameters above
+spec_norm = spec/max(spec); % normalize the simulation
+
+figure(2)
+set (gcf,'PaperUnits','centimeters')
+set (gcf,'Position',[-900,100,800,400]) % set the position, size and shape of the plot
+set (gcf,'InvertHardcopy','off','Color',[1 1 1])
+set(0,'DefaultAxesFontSize', 16,'DefaultAxesLineWidth',1.5)
+
+plot(0.1*params.Field_Vector,signal_baseline_field_time_mean_norm,'r', bfield,spec_norm,'b','LineWidth',1);
+axis('tight')
+
+legend('experimental','simulation')
+legend boxoff
+xlabel('Magnetic Field / mT')
+ylabel('EPR signal / A. U.')
+set(gca,'Box','Off','XMinorTick','On',...
+    'YMinorTick','On','TickDir','Out','YColor','k')
+return
+
+set(gcf,'Units','Inches');
+pos = get(gcf,'Position');
+set(gcf,'PaperPositionMode','Auto','PaperUnits','Inches','PaperSize',[pos(3), pos(4)]);
+print(gcf,'..\Abbildungen\Regression5','-dpdf','-r0');