function convert_stored_matrix
%takes the files processed data from the experimental files (created by create_storage_matrices, patchfile_analysis, and its calles) and presents it in useful formats
%this is the file to use for looking closely at an individual experiment
%called from command line
%calls stsd_simple_plotter_generic_converted,stsd_grid_plotter_generic,stsd_grid_plotter_irreg_spaced,stsd_grid_plotter_raw2,stsd_grid_plotter_raw2007,analyze_stored_controls,histogram_breakdown_dwn,...
%    stsd_grid_plotter_irreg_spaced_probabilities,stsd_grid_plotter_regularly_spaced_probabilities,sd_response_comparisons,concise_historian,stsd_statistics,stsd_spreadsheet_storer,multipeak_plotter,...
%    rectangles_with_error_bars, though some of these are archaic

clear all,close all,tic

[hy,files_to_analyze,presynaptic_side,postsynaptic_side,trials_to_remove,epoch_dividers,age_and_types,analyze_raw,raw_axis,excluding_failure_waveforms,detection_threshold,indivmode_raw,...
    raw_comparison_format,raw_movie_format,meanmode_raw,raw_include_SD,NLize_raw,analyze_extracted_grid,indiv_grid_plots,show_rectangular,analyze_extracted_simple,...
    indiv_simple_plots,analyze_first_pulse_only,minutes_per_trial,analyze_probabilities,NLize_extracted,analyze_controls,analyze_histograms,analyze_spontaneous,analyze_induction,analyze_statistics,...
    analyze_oa_ob_ab,activate_concise_historian,make_stsd_spreadsheets,analyze_fitted_curves,use_only_fitted_values,analyze_multipeaks,analyze_means_and_sems,show_raw_colorcode_bar,...
    extendedrawaxis_followinglastpulse,parameter_colors]=convert_stored_matrix_parametersfile;

samples_per_ms=10;
number_of_epochs=length(epoch_dividers)+1;
basic_pathname=('H:\extracted_values_modulebayHD\');
stimulated_recorded={{'pre-' 'post-'} {'pre' 'post'}};
synapse_in_question=strcat(stimulated_recorded{1}(presynaptic_side),stimulated_recorded{2}(postsynaptic_side));
stsd_parameters={'PSC','charge','latency','risetime','decaytime','asynchronous'};
epochal_colormaps={'jet','cool','flag','prism','hsv','autumn','hot'};

conjoined_filename='';
for j=1:length(files_to_analyze)
    conjoined_filename=strcat(conjoined_filename,files_to_analyze{j});
end

%setting some variables
if ~isempty(hy)
    if size(hy,1)==1
        permutations_of_IPIs=length(hy);    %this is for the stimphil 6 type stimuli being used now (feb/march 2006) with two IPIs, the first variable and the second fixed 
    else
        permutations_of_IPIs=hy(1,:)        %this is for stimphil 0 or 1 type stimuli
        max_length_raw=samples_per_ms*max(((hy(1,:)-1).*hy(3,:))+hy(2,:));
        min_length_raw=samples_per_ms*min(hy(2,:));
    end
else 
    permutations_of_IPIs=1;max_length_raw=1500;min_length_raw=1500;
end

%importing the raw (if indicated) and extracted matrices, as well as, possibly, matrices for some specialty variables
if analyze_raw
		plain_rawmatrix=[];
		for barbapapa=1:length(files_to_analyze)
            raw_pathname=strcat(basic_pathname,files_to_analyze{barbapapa},'____raw');
            temp_plain_rawmatrix=load(raw_pathname);
            if postsynaptic_side==1, temp_plain_rawmatrix=temp_plain_rawmatrix(:,1:2:end);else temp_plain_rawmatrix=temp_plain_rawmatrix(:,2:2:end);,end %removing the traces from the not-cared-about neuron
            if ~isempty(trials_to_remove{barbapapa})
                temp_plain_rawmatrix(:,trials_to_remove{barbapapa})=[];
            end
            plain_rawmatrix=[plain_rawmatrix temp_plain_rawmatrix];
		end
        number_of_trials=size(plain_rawmatrix,2)
        
        if isempty(hy)
            azaz_record=[];%ones(1,number_of_trials);
        elseif size(hy,1)==1
            azaz_record=plain_rawmatrix(1:2,:)'       %for stim_phil 6 type hy
        else        
            azaz_record=plain_rawmatrix(1:length(hy(1,:)),:)'; %for stim_phil 1 type hy
        end
        if find(~azaz_record),find(~azaz_record),error('azaz problems'),end
else
    azaz_record=[];
end

plain_extractedmatrix=[];
for barbamama=1:length(files_to_analyze)
    temp_plain_extractedmatrix=[];
	for barbarella=1:length(stsd_parameters)
        extracted_pathname=strcat(basic_pathname,files_to_analyze{barbamama},'__',synapse_in_question{1},stsd_parameters{barbarella});
        temp_plain_extractedmatrix(:,:,barbarella)=load(extracted_pathname);        
    end
    temp_plain_extractedmatrix(:,trials_to_remove{barbamama},:)=[];
    plain_extractedmatrix=[plain_extractedmatrix temp_plain_extractedmatrix];
end
if size(hy,1)==1,number_of_APs=size(plain_extractedmatrix,1)-2;else number_of_APs=size(hy,2)+1;end,number_of_IPIs=number_of_APs-1;number_of_trials=size(plain_extractedmatrix,2);
    
if NLize_extracted
    for cherry=1:size(plain_extractedmatrix,3)  %for each parameter
        orange=size(plain_extractedmatrix,1);   %the total number of rows
        for banana=1:(size(plain_extractedmatrix,1)-(size(hy,2)+1)) %for each row after the IPIs and the first row of values (the _o values)
            plain_extractedmatrix(orange,:,cherry)=plain_extractedmatrix(orange,:,cherry)./plain_extractedmatrix(size(hy,2)+1,:,cherry); %could add a correction to remove NaNs
            orange=orange-1;
        end
    end
end

if ~isempty(hy)
    if size(hy,1)==1
        azaz_record_extrac=plain_extractedmatrix(1:2,:,1)'; %as of march 7, 2006, taking the first *two* rows because now using a 3 pulse train (first IPI variable, second fixed at 50ms)
        if analyze_raw, if find(azaz_record_extrac~=azaz_record),error('mismatch between record of IPI durations from raw and from extracted files'),end,end
        for parameter=1:length(stsd_parameters)
            maxes_and_mins(1,parameter)=max(max(plain_extractedmatrix(3:end,:,parameter)));
            maxes_and_mins(2,parameter)=min(min(plain_extractedmatrix(3:end,:,parameter)));
            maxes_and_mins_naught(1,parameter)=max(max(plain_extractedmatrix(3,:,parameter)));
            maxes_and_mins_naught(2,parameter)=min(min(plain_extractedmatrix(3,:,parameter)));
            maxes_and_mins_nonnaught(1,parameter)=max(max(plain_extractedmatrix(4:end,:,parameter)));
            maxes_and_mins_nonnaught(2,parameter)=min(min(plain_extractedmatrix(4:end,:,parameter)));
        end
    else
        azaz_record=(plain_extractedmatrix(1:length(hy(1,:)),:,1))'    
        for parameter=1:length(stsd_parameters)
            maxes_and_mins(1,parameter)=max(max(plain_extractedmatrix(length(hy(1,:))+1:end,:,parameter)));
            maxes_and_mins(2,parameter)=min(min(plain_extractedmatrix(length(hy(1,:))+1:end,:,parameter)));
            maxes_and_mins_naught(1,parameter)=max(max(plain_extractedmatrix(length(hy(1,:))+1,:,parameter)));
            maxes_and_mins_naught(2,parameter)=min(min(plain_extractedmatrix(length(hy(1,:))+1,:,parameter)));
            maxes_and_mins_nonnaught(1,parameter)=max(max(plain_extractedmatrix(length(hy(1,:))+1:end,:,parameter)));  %need to clarify this -- what is added to hy?
            maxes_and_mins_nonnaught(2,parameter)=min(min(plain_extractedmatrix(length(hy(1,:))+1:end,:,parameter)));
		end
    end
else
    for parameter=1:length(stsd_parameters)
        maxes_and_mins(1,parameter)=max(max(plain_extractedmatrix(:,:,parameter)));
        maxes_and_mins(2,parameter)=min(min(plain_extractedmatrix(:,:,parameter)));
        maxes_and_mins_naught(1,parameter)=max(max(plain_extractedmatrix(1,:,parameter)));
        maxes_and_mins_naught(2,parameter)=min(min(plain_extractedmatrix(1,:,parameter)));
        maxes_and_mins_nonnaught(1,parameter)=max(max(plain_extractedmatrix(1,:,parameter)));  %need to clarify this -- what is added to hy?
        maxes_and_mins_nonnaught(2,parameter)=min(min(plain_extractedmatrix(1,:,parameter)));
    end
end

fit_array=[];           %will be passed empty if fitted cures are not analyzed
if analyze_fitted_curves
    for fit=1:length(files_to_analyze)
        temp_fit_array=load(strcat(basic_pathname,files_to_analyze{fit},'__fit_vals')); 
        temp_fit_array(:,trials_to_remove{fit})=[];
        fit_array=[fit_array temp_fit_array];
	end
    
    fit_extractedmatrix=plain_extractedmatrix;
    interval=size(fit_array,1)/number_of_APs;
    for i=1:size(plain_extractedmatrix,2)
        for j=1:size(azaz_record,2)+1
            fit_extractedmatrix(j+number_of_APs-1,i,1)=-1*(fit_array((j*interval)-4,i));  %PSC %MUST CHANGE to the proper value given that rise duration and decay duration will now be stored from iterative_curve_fit
            fit_extractedmatrix(j+number_of_APs-1,i,2)=-1*(fit_array((j*interval)-3,i));  %Q
            fit_extractedmatrix(j+number_of_APs-1,i,3)=.1*(fit_array((j*interval)-5,i));       %latency
            fit_extractedmatrix(j+number_of_APs-1,i,4)=fit_array((j*interval)-1,i);%/(-1*(fit_array((j*interval)-4,i)));%rise duration (?NLize to amplitude)
            fit_extractedmatrix(j+number_of_APs-1,i,5)=fit_array(j*interval,i)/(-1*(fit_array((j*interval)-4,i)));    %half decay duration (?NLize to amplitude)
            fit_extractedmatrix(j+number_of_APs-1,i,6)=nan;
        end
    end
    if use_only_fitted_values,plain_extractedmatrix=fit_extractedmatrix;end
end

if analyze_probabilities|analyze_extracted_grid
	detection_criterion_matrix=[];
    for dcz=1:length(files_to_analyze)
        temp_crit_array=load(strcat(basic_pathname,files_to_analyze{dcz},'__criterion_vals'));
        temp_crit_array(:,trials_to_remove{dcz})=[];
        detection_criterion_matrix=[detection_criterion_matrix temp_crit_array];
    end
    [latenciez,critz]=find_detection_crits_and_latencies_generalizedform(detection_criterion_matrix,detection_threshold,numberofAPs);
	plain_extractedmatrix(3:end,:,3)=latenciez/10;
    %'compressing' the compression matrix into the max in each segment
	% maxed_dcm=[];
	% dcmrows=size(detection_criterion_matrix,1)/3
	% maxed_dcm=max(detection_criterion_matrix(1:dcmrows,:));
	% maxed_dcm=[maxed_dcm;max(detection_criterion_matrix(dcmrows+1:2*dcmrows,:))];
	% maxed_dcm=[maxed_dcm;max(detection_criterion_matrix(2*dcmrows+1:end,:))];
	% maxed_dcm(maxed_dcm<1.5)=nan;    
	
	%removing failures, as designated by the criterion matrix threshold
	%for i=1:6,a=plain_extractedmatrix(3:end,:,i); a(isnan(maxed_dcm))=nan; plain_extractedmatrix(3:end,:,i)=a;end  
	% %figure(2),plot(plain_extractedmatrix(3,:,1),'ks'),hold on
	% plain_matrix=plain_extractedmatrix;
	
	% for i=1:6,a=plain_extractedmatrix(4,:,i); a(isnan(maxed_dcm(1,:)))=nan; plain_extractedmatrix(4,:,i)=a;end %removing _a if _o failed that trial
	% for i=1:6,a=plain_extractedmatrix(5,:,i); a(isnan(maxed_dcm(2,:)))=nan; plain_extractedmatrix(5,:,i)=a;end
	
	% plotting the relations of rise time, latency and size
	% clrz={'k' 'b' 'r'}
	% for i=1:3
	%     %subplot(1,3,1)
	%     %plot(plain_extractedmatrix(~isnan(plain_extractedmatrix(i+2,:,1))),plain_extractedmatrix(~isnan(plain_extractedmatrix(i+2,:,3))),'o','markerfacecolor',clrz{i},'markeredgecolor',clrz{i},'markersize',12), hold on, title('PSC v. latency','fontweight','bold','fontsize',20)
	%     %subplot(1,3,2)
	% %     normalizedrise=(plain_extractedmatrix(i+2,:,4))./(plain_extractedmatrix(i+2,:,1))
	%     plot(plain_extractedmatrix(i+2,:,1),plain_extractedmatrix(i+2,:,4),'o','markerfacecolor',clrz{i},'markeredgecolor',clrz{i},'markersize',12), hold on, title('PSC v. rise duration','fontweight','bold','fontsize',20)
	%     %subplot(1,3,3)
	%     %plot(plain_extractedmatrix(i+2,:,3),plain_extractedmatrix(i+2,:,4),'o','markerfacecolor',clrz{i},'markeredgecolor',clrz{i},'markersize',12), hold on, title('latency v. rise duration','fontweight','bold','fontsize',20)
	% end
end

if analyze_multipeaks
    multipeak_matrix=[];
	for multimer=1:length(files_to_analyze)
        multipeak_pathname=strcat(basic_pathname,files_to_analyze{multimer},'__multipeak_vals');
        temp_multipeakmatrix=load(multipeak_pathname);
        if ~isempty(trials_to_remove{multimer})
            temp_multipeakmatrix(:,trials_to_remove{multimer})=[];
        end
        if size(temp_multipeakmatrix,1)>size(multipeak_matrix,1)      %correcting size, bc the number of multipeaks can't be predicted in advance
            multipeak_matrix=cat(1,multipeak_matrix,repmat(nan,(size(temp_multipeakmatrix,1)-size(multipeak_matrix,1)),size(multipeak_matrix,2)));
        elseif size(multipeak_matrix,1)>size(temp_multipeakmatrix,1)
            temp_multipeakmatrix=cat(1,temp_multipeakmatrix,repmat(nan,(size(multipeak_matrix,1)-size(temp_multipeakmatrix,1)),size(temp_multipeakmatrix,2)));
        end
        multipeak_matrix=[multipeak_matrix temp_multipeakmatrix];
	end    
end

%analyzing
if analyze_extracted_simple
    stsd_simple_plotter_generic_converted(permutations_of_IPIs,number_of_APs,number_of_trials,conjoined_filename,hy,age_and_types,stsd_parameters,epoch_dividers,...
        indiv_simple_plots,NLize_extracted,plain_extractedmatrix,azaz_record,synapse_in_question{1},maxes_and_mins,number_of_IPIs,analyze_first_pulse_only,minutes_per_trial)
end
if analyze_extracted_grid
    if size(hy,1)~=1
        stsd_grid_plotter_generic(permutations_of_IPIs,azaz_record,number_of_APs,number_of_trials,conjoined_filename,hy,age_and_types,epoch_dividers,parameter_colors,...
            NLize_extracted,indiv_grid_plots,show_rectangular,stsd_parameters,synapse_in_question{1},maxes_and_mins_naught,maxes_and_mins_nonnaught,plain_extractedmatrix,...
            number_of_IPIs,epochal_colormaps)
	else
        stsd_grid_plotter_irreg_spaced(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs,detection_criterion_matrix,fit_array)
    end
end
if analyze_raw
    if size(hy,1)~=1
        stsd_grid_plotter_raw2(plain_rawmatrix,azaz_record,permutations_of_IPIs,number_of_APs,max_length_raw,number_of_trials,conjoined_filename,NLize_raw,postsynaptic_side,hy,...
            age_and_types,raw_axis,min_length_raw,meanmode_raw,raw_include_SD,indivmode_raw,raw_movie_format,raw_comparison_format,epoch_dividers,parameter_colors,...
            synapse_in_question{1},samples_per_ms,epochal_colormaps,fit_array,analyze_fitted_curves)
	else
       stsd_grid_plotter_raw_flat_hy(plain_rawmatrix,azaz_record,conjoined_filename,NLize_raw,hy,raw_axis,meanmode_raw,raw_include_SD,indivmode_raw,raw_movie_format,...
           raw_comparison_format,epoch_dividers,parameter_colors,samples_per_ms,epochal_colormaps,plain_extractedmatrix,excluding_failure_waveforms,fit_array,analyze_fitted_curves,...
           show_raw_colorcode_bar,extendedrawaxis_followinglastpulse)
	end
end
if analyze_controls, analyze_stored_controls(files_to_analyze,trials_to_remove,epoch_dividers,basic_pathname,parameter_colors,synapse_in_question,conjoined_filename),end %use a different color for each epoch

if analyze_histograms
    histogram_breakdown_dwn(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs,fit_array)   
end

if analyze_probabilities
    if size(hy,1)==1
        stsd_grid_plotter_irreg_spaced_probabilities(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs,detection_criterion_matrix)    
    else 
        stsd_grid_plotter_regularly_spaced_probabilities(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs) 
    end
end

if analyze_oa_ob_ab
    sd_response_comparisons(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs)
end

if activate_concise_historian
    concise_historian(plain_extractedmatrix,conjoined_filename,hy,epoch_dividers,parameter_colors,stsd_parameters,number_of_IPIs)    
end
    
if analyze_spontaneous,end %combine all the recorded spontaneous activity and calculate cumulative pdf for IEI for each epoch, plot epochs overlaying in diff colors, then same for event size
if analyze_induction,end %this may have to be done separately as the file names will be different etc.
if analyze_statistics, stsd_stats=stsd_statistics(plain_extractedmatrix, epoch_dividers, stsd_parameters,length(stsd_parameters),number_of_IPIs,number_of_trials,...
        conjoined_filename,parameter_colors), end
if make_stsd_spreadsheets, stsd_spreadsheet_storer(plain_extractedmatrix,azaz_record,synapse_in_question{1},number_of_IPIs,hy,permutations_of_IPIs,number_of_APs,number_of_trials,...
        conjoined_filename,stsd_parameters,epoch_dividers,files_to_analyze),end

if analyze_multipeaks
    multipeak_plotter(multipeak_matrix,azaz_record,epoch_dividers,hy,conjoined_filename,samples_per_ms)   
end
if analyze_means_and_sems
    rectangles_with_error_bars(azaz_record(:,2),epoch_dividers,critz,plain_extractedmatrix,hy)
end
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