From d31e02d35fdb9e33b90355c635e2bcca32dd39fa Mon Sep 17 00:00:00 2001 From: Michael Schellenberger Costa Date: Mon, 21 Mar 2016 12:43:48 +0100 Subject: [PATCH] Removed old matlab files --- Test_Parameters.m | 174 ----------------------------------------------------- Test_Stimulation.m | 167 -------------------------------------------------- 2 files changed, 341 deletions(-) delete mode 100644 Test_Parameters.m delete mode 100644 Test_Stimulation.m diff --git a/Test_Parameters.m b/Test_Parameters.m deleted file mode 100644 index f556545..0000000 --- a/Test_Parameters.m +++ /dev/null @@ -1,174 +0,0 @@ -% mex command is given by: - -function Test_Parameters(type) -if nargin == 0 - type = 2; -end - - -mex CXXFLAGS="\$CXXFLAGS -std=c++11 -O3" TC_mex.cpp Cortical_Column.cpp Thalamic_Column.cpp - -% Path to fieltrip preprocessing function -if(isempty(strfind(path, '/nfshome/schellen/Documents/MATLAB/Tools/fieldtrip/preproc'))) - addpath('~/Documents/MATLAB/Tools/fieldtrip/preproc'); -end - -% Path to helper function -if(isempty(strfind(path, '/nfshome/schellen/Documents/MATLAB/Tools/boundedline'))) - addpath('~/Documents/MATLAB/Tools/boundedline'); -end - -if type == 1 - Param_Cortex = [4.7; % sigma_e - 1.33; % g_KNa - 120E-3]; % dphi - - Param_Thalamus = [0.051; % g_h - 0.024]; % g_LK - - fn_data = '/nfshome/schellen/Documents/MATLAB/TC_model/Data/SO_Average_N3'; - Model_Range_ERP = [-75, -45]; - Model_Range_FSP = [-0.25, 1.25]; - Data_Range_ERP = [-75, 35]; - Data_Range_FSP = [2, 5]; - xRange = -0.5:0.25:1.5; -else - Param_Cortex = [6; % sigma_e - 2.0; % g_KNa - 120E-3]; % dphi - - Param_Thalamus = [0.051; % g_h - 0.0205]; % g_LK - - fn_data = '/nfshome/schellen/Documents/MATLAB/TC_model/Data/SO_Average_N3'; - Model_Range_ERP = [-75, -45]; - Model_Range_FSP = [-0.25, 1.25]; - Data_Range_ERP = [-75, 35]; - Data_Range_FSP = [2, 5]; - xRange = -0.5:0.25:1.5; -end - -Connectivity = [ 2.5; % N_et - 2.5; % N_er - 15; % N_te - 15]; % N_ti - -load(fn_data); - -% stimulation parameters -% first number is the mode of stimulation -% 0 == none -% 1 == semi-periodic -% 2 == phase dependend - -var_stim = [ 0; % mode of stimulation - 40; % strength of the stimulus in Hz (spikes per second) - 100; % duration of the stimulus in ms - 5; % time between stimulation events in s (ISI) - 0; % range of ISI in s [ISI-range,ISI+range] - 3; % Number of stimuli per event - 1050; % time between stimuli within a event in ms - 450]; % time until stimuli after minimum in ms - -T = 300; % duration of the simulation - -[Ve, Vi, Vt, Vr] = TC_mex(T, Param_Cortex, Param_Thalamus, Connectivity, var_stim); -Fs = length(Ve)/T; - - -Ve_low = ft_preproc_bandpassfilter(Ve, Fs, [0.25,4], 513, 'fir') + mean(Ve); -Ve_FSP = ft_preproc_hilbert(ft_preproc_bandpassfilter(Ve, Fs, [12, 15], 513, 'fir'), 'abs').^2; - -% Search for peaks -[~, x_SO] = findpeaks(-Ve_low, 'MINPEAKHEIGHT', 68, 'MINPEAKDISTANCE', 0.2*Fs); - -% Remove those events, that are too close to begin/end -x_SO = x_SO(x_SO<(T-2)*Fs); -x_SO = x_SO(x_SO> 2*Fs); -x_SO = x_SO-3; % fix a different min position wrt data - -% Set the variables -N_Stim = length(x_SO); -Range_ERP = [-0.5, 1.5]; -time_event = linspace(Range_ERP(1), Range_ERP(2), (Range_ERP(2)-Range_ERP(1))*Fs); -Events = zeros(length(time_event), N_Stim); -Events_FSP = zeros(length(time_event), N_Stim); - -% Segmentation -for i=1:N_Stim - Events(:,i) = Ve ((x_SO(i)+Range_ERP(1)*Fs)+1:(x_SO(i)+Range_ERP(2)*Fs)); - Events_FSP(:,i) = Ve_FSP((x_SO(i)+Range_ERP(1)*Fs)+1:(x_SO(i)+Range_ERP(2)*Fs)); -end - -mean_ERP_model= mean(Events, 2); %#ok<*NASGU> -mean_FSP_model= mean(Events_FSP,2); -sd_ERP_model = std (Events, 0, 2); -sd_FSP_model = std (Events_FSP,0, 2); - -% Define handle for plotting -BL_model =@(y,x) boundedline(y,x(:,1), x(:,2), 'alpha', 'transparency', 0.1, 'r'); -BL_data =@(y,x) boundedline(y,x(:,1), x(:,2), 'alpha', 'transparency', 0.1, 'black'); - -% Option array for set -Option_Name = { 'ylim'; - 'ytick'; - 'yticklabel'; - 'ycolor'; - 'xtick'}'; - -Option_Model_ERP = {Model_Range_ERP; - linspace(Model_Range_ERP(1), Model_Range_ERP(2), 5); - linspace(Model_Range_ERP(1), Model_Range_ERP(2), 5); - 'black'; - xRange}'; %#ok<*NBRAK> - -Option_Data_ERP = {Data_Range_ERP; - linspace(Data_Range_ERP(1), Data_Range_ERP(2), 5); - linspace(Data_Range_ERP(1), Data_Range_ERP(2), 5); - 'black'; - xRange}'; - -Option_Model_FSP = {Model_Range_FSP; - linspace(Model_Range_FSP(1), Model_Range_FSP(2), 5); - linspace(Model_Range_FSP(1), Model_Range_FSP(2), 5); - 'black'; - xRange}'; - -Option_Data_FSP = {Data_Range_FSP; - linspace(Data_Range_FSP(1), Data_Range_FSP(2), 5); - linspace(Data_Range_FSP(1), Data_Range_FSP(2), 5); - 'black'; - xRange}'; - -figure(1) -subplot(411) -plot(linspace(0,30,3000),Ve(101:3100)); -title(['Ve with a mean of :',num2str(mean(Ve))]); -subplot(412) -plot(linspace(0,30,3000),Vi(101:3100)); -title(['Vi with a mean of :',num2str(mean(Vi))]); -subplot(413) -plot(linspace(0,30,3000),Vt(101:3100)); -title(['Vt with a mean of :',num2str(mean(Vt))]); -subplot(414) -plot(linspace(0,30,3000),Vr(101:3100)); -title(['Vr with a mean of :',num2str(mean(Vr))]); - -% Create figure -figure(2) -clf -subplot(211) -[AX1, ~, ~] = plotyy(time_events,[mean_SO_data, sem_SO_data],time_events,[mean_ERP_model, sd_ERP_model], BL_data, BL_model); -set(AX1(1), Option_Name, Option_Data_ERP); -set(AX1(2), Option_Name, Option_Model_ERP); -ylabel(AX1(1),'EEG [$\mu$V]'); -ylabel(AX1(2),'$V_{e}$ [mV]'); -title([num2str(N_Stim), ' Events']) -subplot(212) -[AX1, ~, ~] = plotyy(time_events,[mean_FSP_data, sem_FSP_data],time_events,[mean_FSP_model, sd_FSP_model], BL_data, BL_model); -set(AX1(1), Option_Name, Option_Data_FSP); -set(AX1(2), Option_Name, Option_Model_FSP); -ylabel(AX1(1),'FSP data [a.u.]'); -ylabel(AX1(2),'$FSP model$ [a.u.]'); -title([num2str(N_Stim), ' Events']) -end \ No newline at end of file diff --git a/Test_Stimulation.m b/Test_Stimulation.m deleted file mode 100644 index 6a5e38f..0000000 --- a/Test_Stimulation.m +++ /dev/null @@ -1,167 +0,0 @@ -% mex command is given by: - -function Test_Stimulation(type) -if nargin == 0 - type = 4; -end - - -mex CXXFLAGS="\$CXXFLAGS -std=c++11 -O3" TC_mex.cpp Cortical_Column.cpp Thalamic_Column.cpp - -% Path to fieltrip preprocessing function -if(isempty(strfind(path, '/nfshome/schellen/Documents/MATLAB/Tools/fieldtrip/preproc'))) - addpath('~/Documents/MATLAB/Tools/fieldtrip/preproc'); -end - -% Path to helper function -if(isempty(strfind(path, '/nfshome/schellen/Documents/MATLAB/Tools/boundedline'))) - addpath('~/Documents/MATLAB/Tools/boundedline'); -end - -Param_Cortex = [6; % sigma_e - 2.05; % g_KNa - 120E-3]; % dphi - -Param_Thalamus = [0.052; % g_h - 0.02]; % g_LK - -Connectivity = [ 2.6; % N_et - 2.6; % N_er - 5; % N_te - 10]; % N_ti - -% stimulation parameters -% first number is the mode of stimulation -% 0 == none -% 1 == semi-periodic -% 2 == phase dependend - -var_stim = [ 2; % mode of stimulation - 70; % strength of the stimulus in Hz (spikes per second) - 80; % duration of the stimulus in ms - 5; % time between stimulation events in s (ISI) - 0; % range of ISI in s [ISI-range,ISI+range] - 2; % Number of stimuli per event - 1075; % time between stimuli within a event in ms - 450]; % time until stimuli after minimum in ms - -T = 3600; % duration of the simulation - -load('/nfshome/schellen/Documents/MATLAB/TC_model/Data/ERP_Average_data'); - -Model_Range_ERP = [-75, -45]; -Data_Range_ERP = [-80, 50]; -Model_Range_FSP = [-0.25, 1.25]; -Data_Range_FSP = [2, 8]; -xRange = -1:0.5:3; - -% Option array for set -Option_Name = { 'ylim'; - 'ytick'; - 'yticklabel'; - 'ycolor'; - 'xtick'; - 'xlim'}'; - -Option_Model_ERP = {Model_Range_ERP; - -75:10:-40; - -75:10:-40; - 'black'; - xRange; - [xRange(1),xRange(end)]}'; %#ok<*NBRAK> - -Option_Data_ERP = {Data_Range_ERP; - -80:40:40; - -80:40:40; - 'black'; - xRange; - [xRange(1),xRange(end)]}'; - -Option_Model_FSP = {Model_Range_FSP; - linspace(Model_Range_FSP(1), Model_Range_FSP(2), 4); - linspace(Model_Range_FSP(1), Model_Range_FSP(2), 4); - 'black'; - xRange; - [xRange(1),xRange(end)]}'; - -Option_Data_FSP = {Data_Range_FSP; - linspace(Data_Range_FSP(1), Data_Range_FSP(2), 4); - linspace(Data_Range_FSP(1), Data_Range_FSP(2), 4); - 'black'; - xRange; - [xRange(1),xRange(end)]}'; - -[Ve, Vt, Ca, ah, Marker_Stim] = TC_mex(T, Param_Cortex, Param_Thalamus, Connectivity, var_stim); -Fs = length(Ve)/T; -Ve_FSP = ft_preproc_hilbert(ft_preproc_bandpassfilter(Ve, Fs, [12, 15], 513, 'fir'), 'abs').^2; -xRange = [-1, 3]; - -% Search for peaks -x_SO = Marker_Stim; - -% Remove those events, that are too close to begin/end -x_SO = x_SO(x_SO<(T-xRange(end))*Fs); -x_SO = x_SO(x_SO> -xRange(1)*Fs); - -% Set the variables -N_Stim = length(x_SO); -time_event = linspace(xRange(1), xRange(end), (xRange(end)-xRange(1))*Fs+1); -Events = zeros(length(time_event), N_Stim); -Events_FSP = zeros(length(time_event), N_Stim); - -% Segmentation -for i=1:N_Stim - Events(:,i) = Ve ((x_SO(i)+xRange(1)*Fs):(x_SO(i)+xRange(end)*Fs)); - Events_FSP(:,i) = Ve_FSP((x_SO(i)+xRange(1)*Fs):(x_SO(i)+xRange(end)*Fs)); -end - -mean_ERP_model= mean(Events, 2); %#ok<*NASGU> -mean_FSP_model= mean(Events_FSP,2); -sd_ERP_model = std (Events, 0, 2); -sd_FSP_model = std (Events_FSP,0, 2); - -% Define handle for plotting -BL_model =@(y,x) boundedline(y,x(:,1), x(:,2), 'alpha', 'transparency', 0.1, 'r'); -BL_data =@(y,x) boundedline(y,x(:,1), x(:,2), 'alpha', 'transparency', 0.1, 'black'); - -figure(1) -subplot(411) -plot(linspace(0,30,3000),Ve(101:3100)); -title(['Ve with a mean of :',num2str(mean(Ve))]); -subplot(412) -plot(linspace(0,30,3000),Vt(101:3100)); -title(['Vt with a mean of :',num2str(mean(Vt))]); -subplot(413) -plot(linspace(0,30,3000),Ca(101:3100)); -title(['Ca with a mean of :',num2str(mean(Ca))]); -subplot(414) -plot(linspace(0,30,3000),ah(101:3100)); -title(['ah with a mean of :',num2str(mean(ah))]); - -% Create figure -figure(2) -clf -subplot(211) -[AX1, ~, ~] = plotyy(time_events,[mean_ERP, sem_FSP],time_events,[mean_ERP_model, sd_ERP_model], BL_data, BL_model); -set(AX1(1),Option_Name, Option_Data_ERP, 'box', 'off'); -set(AX1(2),Option_Name, Option_Model_ERP); -ylabel(AX1(1),'EEG [$\mu$V]'); -ylabel(AX1(2),'V$_{p}$ [mV]'); - -subplot(212) -[AX2, ~, ~] = plotyy(time_events,[mean_FSP, sem_FSP],time_events,[mean_FSP_model, sd_FSP_model], BL_data, BL_model); -set(AX2(1),Option_Name, Option_Data_FSP); -set(AX2(2),Option_Name, Option_Model_FSP); -ylabel(AX2(1),'Spindle Power [$\mu$V$^{2}$]'); -ylabel(AX2(2),'Spindle Power [mV$^{2}$]'); -title([num2str(N_Stim), ' Events']) - -% Marker for stimulation -for i=1:2 - hx1 = graph2d.constantline((i-1)*1.05+0.125*(i-1)*(i-2)/2,'ydata', get(AX1(1),'ylim'), 'parent', AX1(1), 'color', 'black', 'LineStyle', ':'); - hx2 = graph2d.constantline((i-1)*1.05+0.125*(i-1)*(i-2)/2,'ydata', get(AX2(1),'ylim'), 'parent', AX2(1), 'color', 'black', 'LineStyle', ':'); - changedependvar(hx1,'x'); - changedependvar(hx2,'x'); -end - -end \ No newline at end of file