Add files via upload

figures/Figure1/getAllFiles.m

@@ -0,0 +1,18 @@
+function fileList = getAllFiles(dirName)
+
+  dirData = dir(dirName);      %# Get the data for the current directory
+  dirIndex = [dirData.isdir];  %# Find the index for directories
+  fileList = {dirData(~dirIndex).name}';  %'# Get a list of the files
+  if ~isempty(fileList)
+    fileList = cellfun(@(x) fullfile(dirName,x),...  %# Prepend path to files
+                       fileList,'UniformOutput',false);
+  end
+  subDirs = {dirData(dirIndex).name};  %# Get a list of the subdirectories
+  validIndex = ~ismember(subDirs,{'.','..'});  %# Find index of subdirectories
+                                               %#   that are not '.' or '..'
+  for iDir = find(validIndex)                  %# Loop over valid subdirectories
+    nextDir = fullfile(dirName,subDirs{iDir});    %# Get the subdirectory path
+    fileList = [fileList; getAllFiles(nextDir)];  %# Recursively call getAllFiles
+  end
+
+end

figures/Figure3/PlotVoltageDistFig3.m

@@ -0,0 +1,143 @@
+% z=readtable('NMO_161366-voltageDistributionPreCosyne.csv'); % old one- on eLife folder
+% z= readtable('/Users/darshanr/Dropbox (HHMI)/VoltageWholeCellProject-2018/MultiCompProject/all_chart_output_v3.csv');
+
+ z= readtable('/Users/darshan/Dropbox/Work/VoltageWholeCellProject-2018/MultiCompProject/all_chart_output_v3_v1.csv');
+%z= readtable('/Users/darshan/Dropbox/Work/VoltageWholeCellProject-2018/MultiCompProject/NMO_161366_different_location.csv');
+
+
+
+%% Plot on-soma Vs distributed- summary
+Morphology='NMO_161366'; % L5 mouse
+% Morphology='NMO_130658'; % L4 FS mouse
+% Morphology='NMO_02484'; % L4 Spiny Stellate mouse
+
+% Morphology='JM072303'; % L4 Spiny Stellate mouse
+
+
+for kk=1:2
+
+    if kk==1
+        min_dist=-0.5; max_dist=0.001; condValue=2;
+    else
+        min_dist=0; max_dist=9e10; condValue=2;
+    end
+
+    z_morph=z;
+    zdis=z_morph(strcmp(z_morph.model_name,Morphology),:);
+    zdis=zdis((zdis.min_dist==min_dist)&(zdis.max_dist<max_dist),:);
+
+    cond_list=unique([zdis.cond_m]);
+    cond_m=cond_list(condValue) % The first, which is 0.5nanoSimense
+    zdis_cond=zdis(zdis.cond_m==cond_m,:);
+   % MODEL NAME ADD !!!!! NMO_161366
+    size(zdis_cond)
+    syn_n_list=unique([zdis_cond.syn_n]);
+
+    figure
+    % % % syn_n_list=[204 273 409 546 819 1023 2047];
+    % syn_n_list=[ 409 1023 2047 4095];
+
+    % syn_n_list=[ 468 937 2344 4688];
+    sig_vec=[];sdv_vec=[];totSim=[];
+    for ii=1:length(syn_n_list)
+        %     ii=5
+        v=zdis_cond.v_mean(zdis_cond.syn_n==syn_n_list(ii));
+        sig=zdis_cond.v_std(zdis_cond.syn_n==syn_n_list(ii));
+        plot(v,sig,'o')
+        hold on
+        sig_vec(ii)=mean(sig);sdv_vec(ii)=std(v);totSim(ii)=length(v);
+    end
+    figure(2)
+    subplot 211
+    semilogx(syn_n_list,sdv_vec,'o-')
+    hold on;axis square;box off;
+    xlim([450 10000])
+    ylabel('\Delta_v-  heteroginity voltage')
+    subplot 212
+    semilogx(syn_n_list,sig_vec,'o-')
+    hold on;axis square;box off;
+
+
+    xlim([450 10000]);ylim([0 6])
+    xlabel('num of conn.')
+    ylabel('std of voltage')
+    % legend('on-soma,g_s=0.01','uniform-dist,g_s=0.0025')
+    legend('on-soma,g_s=0.0025','uniform-dist,g_s=0.0025')
+end
+%% Plot on-soma Vs distributed- voltage distributions
+lineStyles = linspecer(100,'sequential');
+c=colormap(lineStyles);
+BIN_WIDTH = 1;
+BIN_MAX = -30;
+BIN_RANGE = -80:BIN_WIDTH:BIN_MAX;
+x_values = -90:0.01:BIN_MAX;
+c_vec=[1 100];
+for kk=1:2
+    if kk==1
+%         min_dist=-0.5; max_dist=0.001; condValue=1; numSyn=468;numSynIdx=4;
+
+% %             min_dist=-0.5; max_dist=0.001; condValue=1; numSyn=937;numSynIdx=5;
+%             min_dist=-0.5; max_dist=0.001; condValue=1; numSyn=4688;numSynIdx=7;
+%             min_dist=-0.5; max_dist=0.001; condValue=2; numSyn=2344;numSynIdx=6;
+
+
+                        min_dist=-0.5; max_dist=0.001; condValue=2; numSyn=2344;
+%                       min_dist=-0.5; max_dist=0.001; condValue=2; numSyn=7813;
+
+
+else
+%         min_dist=0; max_dist=9e10; condValue=1; numSyn=409;numSynIdx=5;
+
+%             min_dist=0; max_dist=9e10; condValue=1; numSyn=1023;numSynIdx=8;
+%             min_dist=0; max_dist=9e10; condValue=1; numSyn=2047;numSynIdx=10;
+
+%             min_dist=0; max_dist=9e10; condValue=1; numSyn=4095;numSynIdx=11;
+            min_dist=0; max_dist=9e10; condValue=2; numSyn=2047;
+%                min_dist=0; max_dist=9e10; condValue=2; numSyn=8190;
+
+    end
+
+%     zdis=z;
+    z_morph=z;
+    zdis=z_morph(strcmp(z_morph.model_name,Morphology),:);
+
+    zdis=zdis((zdis.min_dist==min_dist)&(zdis.max_dist<max_dist),:);
+
+    cond_list=unique([zdis.cond_m]);
+    cond_m=cond_list(condValue);
+    zdis_cond=zdis(zdis.cond_m==cond_m,:);
+    size(zdis_cond)
+    syn_n_list=unique([zdis_cond.syn_n])
+    numSynIdx=find(syn_n_list==numSyn);
+
+    figure(10)
+    v=zdis_cond.v_mean(zdis_cond.syn_n==syn_n_list(numSynIdx));
+    length(v)
+    x=v;
+    pd=fitdist(x,'Normal');
+    % Plot comparison of the histogram of the data, and the fit
+    % figure
+
+    % Empirical distribution
+    y_data=hist(x,BIN_RANGE);
+    % bar(BIN_RANGE,y_data./sum(y_data)/BIN_WIDTH,'facealpha',.5,'edgecolor','none')
+    bar(BIN_RANGE,y_data./sum(y_data)/BIN_WIDTH,'facealpha',.5,'edgecolor','none','facecolor',c(c_vec(kk),:))
+        hold on
+    % x_values = BIN_RANGE;
+    y = pdf(pd,x_values);
+    plot(x_values,y,'LineWidth',4,'Color',c(c_vec(kk),:))
+    % bar(BIN_RANGE,y_data./sum(y_data)/BIN_WIDTH,'b','facecolor','k','edgecolor','none')
+    hold on
+    pause
+    xlim([-70 -30])
+    axis square; box off;
+    hold on
+
+%     legend('on-soma,g_s=0.0025,#syn=937','uniform-dist,g_s=0.0025,#syn=1023','uniform-dist,g_s=0.0025,#syn=1023')
+    legend('on-soma,g_s=0.0005,#syn=2344','uniform-dist,g_s=0.0005,#syn=2047','uniform-dist,g_s=0.0025,#syn=1023')
+
+end
+
+
+
+