diff --git a/gamma_bomb_2/GammaBomb_2_UserGuide.pdf b/gamma_bomb_2/GammaBomb_2_UserGuide.pdf
deleted file mode 100644
index d49ad9a..0000000
Binary files a/gamma_bomb_2/GammaBomb_2_UserGuide.pdf and /dev/null differ
diff --git a/gamma_bomb_2/code/Repair_LST_HDR.m b/gamma_bomb_2/code/Repair_LST_HDR.m
deleted file mode 100644
index be80a48..0000000
--- a/gamma_bomb_2/code/Repair_LST_HDR.m
+++ /dev/null
@@ -1,77 +0,0 @@
-function Repair_LST_HDR(lst_files)
-%% Function To Repair Lst mode header files if missing
-%% Written by Daniel Chonde
-%% Req: cell of list file names
-%% Output: *.lst.hdr files when missing
-%% Written: 3/31/2011 Updated: 11/14/2011
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%This function repairs missing .lst.hdr files which are necessary for
-%gettting the timing information for reconstruction.
-%%
-
-
-%%Repair LST.HDR files
-if size(dir('*.lst'),1)~=size(dir('*.lst.hdr'),1)
-    disp('It appears that some LST header files are missing we will attempt to approximate them');
-    for m=1:size(lst_files,1)
-        lst_hdr_files(m,:)=strcat(lst_files(m),'.hdr');
-    end
-    clear m
-    
-    for m=1:size(lst_hdr_files,1)
-        if exist(lst_hdr_files{m,:},'file')==0
-            if exist(regexprep(strtrim(lst_hdr_files{m,:}),'.lst',''),'file')
-                disp([regexprep(strtrim(lst_hdr_files{m,:}),'.lst','') ' found...ask Larry to make .lst.hdr files again...'])
-                copyfile(regexprep(strtrim(lst_hdr_files{m,:}),'.lst',''),lst_hdr_files{m,:})
-            else
-                disp([lst_hdr_files{m,:} ' is missing...approximating...'])
-                %figure out creation time of log file and subtract 58 seconds
-                no_ext_name=regexp(lst_hdr_files{m,:},'.lst.hdr','split');
-                %no_ext_name=regexp(lst_hdr_files{m-1,:},'.lst.hdr','split');
-                log_file=strcat(no_ext_name{1},'.lst');
-                log=dir(log_file);
-                log_date=log.date;
-                log_creation_date_time=regexp(log_date,' ','split');
-                log_h_m_s=regexp(cell2mat(log_creation_date_time(1,2)),':','split');
-                log_file_creation_time=str2double(log_h_m_s{1,1})*3600+str2double(log_h_m_s{1,2})*60+str2double(log_h_m_s{1,3});
-                %lst_file_creation_time=log_file_creation_time-58;
-                start=calc_lst_duration(log_file);
-                lst_file_creation_time=log_file_creation_time-start;
-                new_hdr_hh=num2str(floor(lst_file_creation_time/3600));
-                if size(new_hdr_hh,2)==1
-                    new_hdr_hh=strcat('0',new_hdr_hh);
-                end
-                new_hdr_mm=num2str(floor(lst_file_creation_time/60-floor((lst_file_creation_time/3600))*60));
-                if size(new_hdr_mm,2)==1
-                    new_hdr_mm=strcat('0',new_hdr_mm);
-                end
-                new_hdr_ss=num2str(lst_file_creation_time-str2num(new_hdr_mm)*60-str2num(new_hdr_hh)*3600);
-                if size(new_hdr_ss,2)==1
-                    new_hdr_ss=strcat('0',new_hdr_ss);
-                end
-                
-                if m==1
-                    copyfile(fullfile('D:\Users\Dan\Codes\matlab\externals','template.lst.hdr'),lst_hdr_files{m,:});
-                else
-                    copyfile(lst_hdr_files{m-1,:},lst_hdr_files{m,:});
-                end
-                fileattrib(lst_hdr_files{m,:},'+w');
-                %fid=fopen(lst_hdr_files{m-1,:});
-                fid=fopen(lst_hdr_files{m,:});
-                F = fread(fid, '*char')';
-                fclose(fid);
-                C=regexp(F(1,:),'\(hh:mm:ss)\s:=','split');
-                F((size(C{1},2)+15):(size(C{1},2)+16))=new_hdr_hh;
-                F((size(C{1},2)+18):(size(C{1},2)+19))=new_hdr_mm;
-                F((size(C{1},2)+21):(size(C{1},2)+22))=new_hdr_ss;
-                fid2=fopen(lst_hdr_files{m,:},'w');
-                fwrite(fid2,F);
-                fclose(fid2);
-                fileattrib(lst_hdr_files{m,:},'-w');
-            end
-        end
-        clear C F fid fid2 log log_creation_date_time log_date log_file log_file_creation_time log_h_m_s lst_file_creation_time new_hdr_hh new_hdr_mm new_hdr_ss no_ext_name
-    end
-    clear m lst_hdr_files
-end
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/TAC_process_data.m b/gamma_bomb_2/code/TAC_process_data.m
deleted file mode 100644
index 99ab3f7..0000000
--- a/gamma_bomb_2/code/TAC_process_data.m
+++ /dev/null
@@ -1,18 +0,0 @@
-function TAC_process_data(Sum_Output_name)
-if ~exist(fullfile(pwd,'TAC_process_data.bat'),'file')
-    copyfile('D:\Users\Dan\Codes\bat\TAC_process_data.bat')
-end
-if ~exist(fullfile(pwd,'TAC_process_data_cleanup.bat'),'file')
-    copyfile('D:\Users\Dan\Codes\bat\TAC_process_data_cleanup.bat')
-end
-
-dos(['hist_PET -l ' Sum_Output_name '.lst -s ' Sum_Output_name '.s -L ' Sum_Output_name '.lor -A c:\bin\lorlookup_p256.dat -C 19,128']);
-copyfile(strcat(Sum_Output_name,'.s.hc'),strcat(Sum_Output_name,'_hp.s.hc'),'f');
-delete(strcat(Sum_Output_name,'_p.lor*'),strcat(Sum_Output_name,'_d.lor*'),strcat(Sum_Output_name,'.s*'),strcat(Sum_Output_name,'_*r*.s*'),strcat(Sum_Output_name,'.*map'))
-process_data_command_line=['TAC_process_data ' Sum_Output_name];
-dos_ex(process_data_command_line);
-process_data_cleanup_command_line=['TAC_process_data_cleanup ' Sum_Output_name];
-dos(process_data_cleanup_command_line);
-convertshc(strcat(Sum_Output_name,'.s.hc'),strcat(Sum_Output_name,'_hp.s.hc'))
-copyfile(strcat(Sum_Output_name,'.s.hc'),strcat(Sum_Output_name,'_head_curve.s.hc'),'f');
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/TAC_sort_lst_mode.m b/gamma_bomb_2/code/TAC_sort_lst_mode.m
deleted file mode 100644
index 0dc2045..0000000
--- a/gamma_bomb_2/code/TAC_sort_lst_mode.m
+++ /dev/null
@@ -1,122 +0,0 @@
-function [Scanner_Duration, Series_Duration, frame_start_time, frame_stop_time, acquisition_start, lst_files, lst_files_whole]=TAC_sort_lst_mode(refpath,calc_t_rez)
-
-if nargin<2, calc_t_rez=1000;end
-
-cd(refpath)
-lst_files=dir('*.lst');
-lst_files_whole=dir('*.lst');
-%order Frames
-for m=1:size(lst_files,1)
-    File{m,1}=lst_files(m).name;
-end
-clear m
-for p=1:size(File,1)
-    order(p,:)=regexp(cell2mat(File(p)),'.lst','split');
-    order1(p,:)=mat2cell(order{p,1},size(order{p,1},1),size(order{p,1},2));
-    order2(p,:)=regexp(order1{p,1},'Frame','split');
-    if size(order2,2)==2
-        order3(p,:)=[str2double(order2{p,2}) p];
-    else
-        order3(p,:)=[str2double(order2{p,1}) p];
-    end
-end
-File_unsor=File;
-clear File
-sortorder=sortrows(order3,1);
-File=File_unsor(sortorder(:,2));
-lst_files_whole=lst_files_whole(sortorder(:,2));
-clear p
-clear File_unsor
-lst_files=File;
-clear File
-
-%% Determine end time from file time information
-%%%%%This code is the old way of determining time information, from reading
-%%%%%frame time information and hdr file.  A faster implementation is to
-%%%%%just read the first frame time information and then the time marks.
-% for m=1:size(lst_files_whole,1)
-% frame_date{m,1}=lst_files_whole(m).date;
-% frame_end_date_time(m,:)=regexp(cell2mat(frame_date(m)),' ','split');
-% h_m_s(m,:)=regexp(cell2mat(frame_end_date_time(m,2)),':','split');
-% frame_stop_time(m,1)=str2double(h_m_s{m,1})*3600+str2double(h_m_s{m,2})*60+str2double(h_m_s{m,3});
-% end
-% clear m
-% 
-% %%Determine start time from lst.hdr information
- Repair_LST_HDR(lst_files)
-% for m=1:size(lst_files_whole,1)
-% fid = fopen(strcat(lst_files_whole(m).name,'.hdr'), 'r'); %Open file for reading
-% for k=1:15
-%     tline=fgetl(fid);
-%     if k==5
-%         strscantime=textscan(tline,'%s %s %s %s %s');
-%         H_M_S=regexp(cell2mat(strscantime{5}),':','split');
-%         frame_start_time(m,1)=str2double(H_M_S(1))*3600+str2double(H_M_S(2))*60+str2double(H_M_S(3));
-%     else
-%     end
-%     clear tline
-% end
-% fclose(fid);
-% clear k
-% end
-% clear m
-for m=1:size(lst_files_whole,1)
-    if m==1
-        fid = fopen(strcat(lst_files_whole(m).name,'.hdr'), 'r'); %Open file for reading
-        for k=1:15
-            tline=fgetl(fid);
-            if k==5
-                strscantime=textscan(tline,'%s %s %s %s %s');
-                H_M_S=regexp(cell2mat(strscantime{5}),':','split');
-                world_clock=str2double(H_M_S(1))*3600+str2double(H_M_S(2))*60+str2double(H_M_S(3));
-            else
-            end
-            clear tline
-        end
-        fclose(fid);
-    end
-    [duration,ids]=calc_lst_duration(lst_files_whole(m).name,calc_t_rez);
-    frame_start_time(m,1)=ids(1);
-    frame_stop_time(m,1)=ids(2);
-end
-tdiff=frame_start_time(1,1)-world_clock;
-frame_start_time=floor(frame_start_time-tdiff);
-frame_stop_time=floor(frame_stop_time-tdiff);
-acquisition_start=frame_start_time(1,1);
-
-%%Set start time and stop time relative to Series Start Time
-frame_start_time_true=frame_start_time;
-frame_stop_time_true=frame_stop_time;
-frame_start_time=frame_start_time_true-frame_start_time_true(1,1);
-frame_stop_time=frame_stop_time_true-frame_start_time_true(1,1);
-
-%%Build Time Line (1 if data was collect during that second, 0 if no data
-%%was present)
-Scanner_Duration((frame_start_time(1)+1):(frame_stop_time(size(frame_stop_time,1))))=0;
-for m=1:(size(frame_start_time,1))
-    Scanner_Duration((frame_start_time(m)+1):(frame_stop_time(m)))=1;
-end
-clear m
-%Remove short breaks due to framing data
-Series_Duration=Scanner_Duration;
-System_off=find(Series_Duration==0)';
-for m=1:size(System_off,1)
-    if Scanner_Duration(System_off(m))==0 && Series_Duration(System_off(m))==0
-        if Series_Duration(System_off(m)-1)==1 && Series_Duration(System_off(m)+10)==1
-            Series_Duration(System_off(m):System_off(m)+10)=1;
-        end
-    else
-    end
-end
-% for m=1:size(System_off,1)
-%     if sum(Series_Duration((System_off(m)-5):(System_off(m))))~=0 && sum(Series_Duration((System_off(m)):(System_off(m)+5)))~=0
-%         Series_Duration(System_off(m))=1;
-%     else
-%     end
-% end
-clear m
-
-end
-%important variables
-%%Scanner_Duration Series_Duration frame_start_time frame_stop_time
-%%lst_files lst_files_whole
\ No newline at end of file
diff --git a/gamma_bomb_2/code/calc_lst_duration.m b/gamma_bomb_2/code/calc_lst_duration.m
deleted file mode 100644
index 3ffa625..0000000
--- a/gamma_bomb_2/code/calc_lst_duration.m
+++ /dev/null
@@ -1,101 +0,0 @@
-%six bytes ber given event
-function [total_time,ids,last_gc]=calc_lst_duration(lst_ffile,t_mks)
-
-fid = fopen(lst_ffile, 'r', 'l'); %Open file for reading
-
-if nargin<2, t_mks=1000;end
-
-%% Find first x-time marks
-index=0;
-test={};
-t=0;
-while 1
-    fseek(fid, 6*index, 'bof');
-    %start_event=reshape(flipud(dec2hex(fread(fid,6,'uint8')))',1,12);
-    start_event=reshape(flipud(dec2hex(fread(fid,6,'uint8'),2))',1,12);
-    if (strcmp(start_event(1,2),'A') && strcmp(start_event(1,3),'0')) || feof(fid)
-        t=t+1;
-        test{end+1,1}=start_event;
-        if t==t_mks || feof(fid)
-            break
-        else
-            index=index+1;
-        end
-    else
-        index=index+1;
-    end
-end
-
-time={};
-for m=1:size(test,1)
-    time{end+1,1}=hex2dec(test{m,1}(1,4:end));
-end
-errtest=[1;cell2mat(time(2:end))-cell2mat(time(1:end-1))];
-if ~isempty(find(errtest>1))
-    start_event=test{test{1}};
-    stop_event=test{find(errtest>1)-1};
-    start_time=hex2dec(start_event(1,4:end));
-    stop_time=hex2dec(stop_event(1,4:end));
-    extra_time=floor((stop_time-start_time)*200*10^(-6));
-    
-    start_event=test{find(errtest>1)};
-else
-    start_event=test{1};
-    extra_time=0;
-end
-
-
-%% Find last x-time marks
-index=1;
-test2={};
-t=0;
-while 1
-    fseek(fid, -6*index, 'eof');
-    %stop_event=reshape(flipud(dec2hex(fread(fid,6,'uint8')))',1,12);
-    stop_event=reshape(flipud(dec2hex(fread(fid,6,'uint8'),2))',1,12);
-    if index==1 %get last_gc
-        last_gc=stop_event(1,1);
-    end
-    if (strcmp(stop_event(1,2),'A') && strcmp(stop_event(1,3),'0')) || ~ftell(fid)
-        t=t+1;
-        test2{end+1,1}=stop_event;
-        if t==t_mks || ~ftell(fid)
-            break
-        else
-            index=index+1;
-        end
-    else
-        index=index+1;
-    end
-end
-
-% %% Error correction for frame end (added 05/06/2013)
-% time={};
-% for m=1:size(test2,1)
-%     time{end+1,1}=hex2dec(test2{m,1}(1,4:end));
-% end
-% errtest2=[1;cell2mat(time(2:end))-cell2mat(time(1:end-1))];
-% if ~isempty(find(errtest2~=-1))
-%     estart_event=test2{test2{1}};
-%     estop_event=test2{find(errtest2~=-1,1,'last')-1};
-%     estart_time=hex2dec(estart_event(1,4:end));
-%     estop_time=hex2dec(estop_event(1,4:end));
-%     extra_time=extra_time+floor((estart_time-estop_time)*200*10^(-6));
-%     
-%     stop_event=test2{find(errtest2~=-1,1,'last')};
-% else
-%     stop_event=test2{1};
-%     extra_time=extra_time;
-% end
-
-stop_event=test2{1};
-
-start_time=hex2dec(start_event(1,4:end));
-stop_time=hex2dec(stop_event(1,4:end));
-
-total_time=floor((stop_time-start_time)*200*10^(-6))+extra_time;
-
-fclose(fid);
-
-ids=[start_time;stop_time]*200*10^(-6);
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/check_decreasing.m b/gamma_bomb_2/code/check_decreasing.m
deleted file mode 100644
index d76e516..0000000
--- a/gamma_bomb_2/code/check_decreasing.m
+++ /dev/null
@@ -1,84 +0,0 @@
-function [num_deleted, adjusted_data] = check_decreasing(data)
-% Check that data is monatonically decreasing after initial hill
-% If data prematurely approaches zero, omit these points from analysis
-
-tail_avg = 0;
-temp = zeros(0,2); % Temporary matrix
-cutoff_min = 60; % Program starts looking for bad points here
-cutoff_max = 200;
-
-% Calculate the average of all measurements taken after 60 seconds
-for m=1:size(data)
-    if data(m,1) > cutoff_min
-        temp(end+1,:) = data(m,:);
-        tail_avg = mean(temp);
-    end
-end
-clear temp;
-approx_zero = min(tail_avg(1,2)./2, data(end,2)); % Cutoff for what is considered to be "near zero"
-
-% Add a third column to the data table (1 = keep the point, 0 = delete it)
-% Default: keep all points
-for m=1:size(data)
-    data(m,3) = 1;
-end
-
-% Determine the minima within the range of analysis (between time at cutoff_min &
-% time at cutoff_max)
-for m=2:size(data)-1
-    if(data(m,2)<data(m+1,2) && data(m,2)<data(m-1,2))
-        data(m,3) = 0;
-    end
-    if(data(m,1)<cutoff_min || data(m,1)>cutoff_max)
-        data(m,3) = 1;
-    end
-    if(data(m,2)>approx_zero)
-        data(m,3) = 1;
-    end
-end
-
-% Delete points adjacent to the minima found above when necessary
-larger = 0;
-for m=2:size(data)-1
-    if(data(m,3) == 0)
-        larger = max(data(m+1,2), data(m-1,2));
-    end
-end
-for m=2:size(data)-1
-    for m=2:size(data)-1
-        if data(m,2) < larger && (data(m+1,3)==0 || data(m-1,3)==0)
-            data(m,3) = 0;
-        end
-    end
-end
-        
-
-% Store points we'll keep for further analyses in 'adjusted_data'
-% Store all deleted points in deleted_points
-adjusted_data = zeros(0,2);
-deleted_points = zeros(0,2);
-for m=1:size(data)
-    if data(m,3) == 1
-        adjusted_data(end+1,:) = data(m,1:2);
-    else
-        deleted_points(end+1,:) = data(m,1:2);
-    end
-end
-%adjusted_data(end+1,:) = data(end,1:2); % Add final data point to adjusted_data
-[num_deleted,~] = size(deleted_points);
-
-%% Plot to Debug
-% figure
-% hold on;
-% plot(data(:,1),data(:,2), '.r');
-% set(gca, 'XScale', 'log');
-% title('Before');
-% plot(adjusted_data(:,1),adjusted_data(:,2), '.');
-% set(gca, 'XScale', 'log');
-% refline(0, approx_zero);
-% refline(Inf, cutoff_min);
-% refline(Inf, cutoff_max);
-% title('Adjusting for Points that Prematurely Approach Zero');
-% hold off;
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/convertshc.m b/gamma_bomb_2/code/convertshc.m
deleted file mode 100644
index 1e5fa8a..0000000
--- a/gamma_bomb_2/code/convertshc.m
+++ /dev/null
@@ -1,40 +0,0 @@
-function convertshc(hc_file,hp_hc)
-
-fid=fopen(hc_file);
-t_hc_line=[];
-while 1
-    hc_line=fgetl(fid);
-    if hc_line==-1,break;end %EOF
-    if strcmpi(hc_line(1:10), 'Head Curve')
-        t_hc_line(end+1,:)=sscanf(hc_line,'Head Curve %i %i %i %i %i %i %i %i %i %i %i ET=%f gcerrors=%i')';
-    end
-end
-fclose(fid);
-
-
-if nargin>1
-    t_hc_line2=csvread(hp_hc, 1, 0);
-    %%make sure HistPET is always increasing
-    for m=2:size(t_hc_line2,1);
-        if t_hc_line2(m,1)<t_hc_line2(m-1,1)
-           t_hc_line2(m,1)=t_hc_line2(m-1,1)+1000; 
-        end
-    end
-    if size(t_hc_line,1)>size(t_hc_line2,1) %% HistPET version has fewer times...lets just assume they increase by 1 sec as one might assume.
-        offset=size(t_hc_line,1)-size(t_hc_line2,1);
-        t_hc_line2=[t_hc_line2;[[1:offset]'*1000,zeros(offset,12)]];
-    end    
-    t_hc_line(:,1)=t_hc_line2(1:size(t_hc_line,1),1);
-end
-
-
-if ~isempty(t_hc_line)
-    fid1=fopen(hc_file, 'wt');
-    fprintf(fid1,'Time(msec),CFD,StoredXY,QualEvent,RIO_Singles,Delays,RIO_Delay,Prompts,RIO_Prompt,ERS_Prompt,ERS_Delays,ERS_Singles,SyncErrCnt\n\r');
-    for m=1:size(t_hc_line,1)
-        fprintf(fid1,[sprintf('%i,%i,%i,%i,%i,%i,%i,%i,%i,%i,%i,%i,%i',t_hc_line(m,:)) '\n\r']);
-    end
-    fclose(fid1);
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/dos_ex.m b/gamma_bomb_2/code/dos_ex.m
deleted file mode 100644
index b315f1f..0000000
--- a/gamma_bomb_2/code/dos_ex.m
+++ /dev/null
@@ -1,9 +0,0 @@
-function dos_ex(dos_string)
-%%I'm not sure why, but the dos/system function crashes when it is using
-%%lmsort, but seems to be okay with !.  Let's make an easy function to do
-%%this
-
-
-evalin('base',[strcat('!',dos_string)])
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/feng_fit3.m b/gamma_bomb_2/code/feng_fit3.m
deleted file mode 100644
index bee139d..0000000
--- a/gamma_bomb_2/code/feng_fit3.m
+++ /dev/null
@@ -1,246 +0,0 @@
-function [fitobject, fit_metric, models]=feng_fit3(bld_ffile,endtime,met_fit,exclude_from,sf,options)
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%% SCRIPT TO FIT BLOOD DATA WITH FENG & L3 MODELS
-%% Written by Daniel Chonde
-%% Req:blood file (*.bld)
-%% Output: blood file (*_feng.bld)
-%% Written: 08/12/2012 Updated:
-% Will also now return statistical gof data (goodness of fit)
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% This script reads in a .bld file and fits Feng's model to the blood data.
-%
-% example:
-% feng_fit(bld_ffile,endtime)
-%   bld_ffile=path to a .bld file
-%   endtime=time to interpolate model to in seconds
-%   sf=number of decimal places to write to file
-%
-% feng_fit(bld_ffile) fits the model and interpolates the data to the
-% last timepoint in the bld file
-%
-% feng_fit(bld_ffile,endtime) fit the model and interpolate the data to
-% an arbitrary timepoint given by endtime, where endtime is in seconds.
-%
-fit_metric = zeros(0,1);
-
-if nargin<4, exclude_from='';end
-
-A=dlmread(bld_ffile,'\t',1,0);
-if A(1,1)~=0, A=[0 0;A];end %add t=0 activity=0, if not already present
-
-if exclude_from
-    A(find(A(:,1)>exclude_from,1,'first'):end,:)=[];
-end
-
-if nargin<5 || isempty(sf) %%Figure out how many decmal places are used
-    %fid=fopen(bld_ffile,'r')
-    %test=textscan(fid,'%s')
-    %fclose(fid)
-    teststr=num2str(A(end,2));
-    splits=regexp(teststr,'\.','split');
-    sf=size(splits{2},2);
-end
-names=textread(bld_ffile,'%s',1,'delimiter','\n');
-hdrnames=regexp(names,'\t','split');
-
-time=A(:,1);plasma=A(:,2);
-num_points = length(time);
-assignin('base','num_points',num_points);
-if nargin<2, endtime=max(time);end
-if nargin<3, met_fit=fit([1:10]',ones(1,10)','poly1');end % if not met data, construct a straight line
-%% Remove points after 5 minutes that go up greater than 5%
-cutofft=find(time>300,1,'first');
-iter=1;
-num_outliers = 0;
-while 1
-    kvals=[zeros(cutofft-1,1);(plasma(cutofft:end).*met_fit(time(cutofft:end))-plasma(cutofft-1:end-1).*met_fit(time(cutofft-1:end-1)))./(plasma(cutofft-1:end-1).*met_fit(time(cutofft-1:end-1)))>0.05];
-    if iter==1
-        ktime=time(find(kvals));
-        kplasma=plasma(find(kvals));
-    else
-        ktime=[ktime;time(find(kvals))];
-        kplasma=[kplasma;plasma(find(kvals))];
-    end
-    num_outliers = length(kvals);
-    time(find(kvals))=[];
-    plasma(find(kvals))=[];
-    iter=iter+1;
-    if ~any(kvals)
-        num_outliers = 0;
-        break;
-    end
-end
-assignin('base', 'num_outliers', num_outliers);
-
-%%Quick Linear interpolation so we can have that file (used by Jean Logan)
-plasma_linear=interp1(time,plasma,time(1):endtime,'linear','extrap');
-plasma_linear(plasma_linear<0)=0;
-
-
-%% Fit Models
-models={'feng_model_aif(a,b,c,d,e,f,g,x)','Feng'
-    'lin_3exp_model_aif(a,b,c,d,e,f,g,h,jj,x)','L3Exp'};
-
-%Check if there is an options.Choice--this is my workaround to allow you to
-%select a single fit model
-if exist('options','var') && isfield(options,'Choice'),models(:,~cellfun(@(x) strcmpi(options.Choice,x),models(:,2)))=[];end
-
-for ppp=1:size(models,1)
-    ffun=fittype(models{ppp,1});
-    if nargin<6
-        options=fitoptions(ffun);
-        options.MaxIter=1000;
-        options.MaxFunEvals=1000;
-        switch models{ppp,2}
-            case 'Feng'
-                options.Lower=[0 -1 0 -1 0 -1 0];
-                options.Upper=[500 0 500 0 500 0 time(find(plasma==max(plasma)))+30];
-                %options.Weights=sqrt(plasma)/sum(sqrt(plasma));
-            case 'L3Exp'
-                options.MaxFunEvals=1000;options.Lower=[0 0 0 0 0 0 0 0 0 ];
-                options.Upper=[1000 1 1000 1 1000 1 30 time(find(plasma==max(plasma))) 30]; 
-        end
-    end
-    
-    for m=1:2
-        if m==1
-            switch models{ppp,2}
-                case 'Feng'
-                    if isempty(options.StartPoint),options.StartPoint=[251/60,-2.1/60,5.8,-0.0104/60,1.879,-0.219/60,time(find(plasma==max(plasma)))-20];end
-                case 'L3Exp'
-                    if isempty(options.StartPoint),object.StartPoint=[60 .1 90 11 138 .02 10 1 1];end
-            end
-        else
-            switch models{ppp,2}
-                case 'Feng'            
-            options.StartPoint=[fitobject.a,fitobject.b,fitobject.c,fitobject.d,fitobject.e,fitobject.f,fitobject.g];
-                case 'L3Exp'
-            options.StartPoint=[fitobject.a,fitobject.b,fitobject.c,fitobject.d,fitobject.e,fitobject.f,fitobject.g,fitobject.h,fitobject.jj];        
-            end
-        end
-        
-        [fitobject,gof]=fit(time,plasma,ffun,options);
-        display(['Iteration ' num2str(m)])
-        display(gof)
-        display(fitobject)
-    end
-    
-    fplasma=fitobject(time(1):endtime); 
-    
-    
-    
-    % ***SUBPLOT #1*** Plot data on Log Scale x-axis
-    assignin('base', 'kplasma', kplasma);
-    figure; subplot(2,2,1);
-    if(size(kplasma)>0)
-        plot(time,plasma,'xb');hold on;plot(ktime,kplasma,'*g');fplot(fitobject,[time(1) endtime],0.0001,'r');set(gca,'XScale','log');
-        legend('Data','Outliers','Fitted Curve');
-        legend off;
-    else
-        plot(time,plasma,'xb');hold on;plot(ktime,kplasma,'*g');plot(fitobject);title(strcat(models{ppp,2},' Model Fit'));
-    end
-    title(strcat(models{ppp,2},' Model Fit (Log Scale)'));
-    xlabel('Time (s)','FontSize',7);ylabel('kBq/ml','FontSize',7);
-    
-    
-    
-    % ***SUBPLOT #2*** Plot data on regular x-axis
-    subplot(2,2,2);
-    if ~isempty(kplasma)
-        plot(time,plasma,'xb');hold on;plot(ktime,kplasma,'*g');plot(fitobject);title(strcat(models{ppp,2},' Model Fit'))
-        legend('Data','Outliers','Fitted Curve');
-    else
-        plot(time,plasma,'xb');hold on;plot(fitobject);
-        legend('Data', 'Fitted Curve', 'Location', 'best');
-    end
-    xlabel('Time (s)','FontSize',7);ylabel('kBq/ml','FontSize',7);
-    
-    
-
-    % Calculate integral for raw data (Crude approximation on graph)
-    int_of_raw = zeros(length(time),1);
-    raw_data = cat(2, time, plasma);
-    for m=1:length(int_of_raw)
-        if m==1
-            int_of_raw(m,1) = (raw_data(m,1)).*(raw_data(m,2));
-        else
-            int_of_raw(m,1) = ((raw_data(m,1)-raw_data(m-1,1)).*(raw_data(m,2))) + int_of_raw(m-1,1);
-        end
-        assignin('base', 'int_of_raw', int_of_raw);
-%         int_of_raw(m,1) = trapz(raw_data(1:m,2));
-    end
-    % Calculate integral for fitted data
-    fit_data = zeros(length(fplasma),2);
-    for m=0:length(fplasma)-1
-        fit_data(m+1,1) = m;
-        fit_data(m+1,2) = fplasma(m+1,1);
-    end
-    int_of_fit = zeros(length(fplasma),1);
-    for m=1:length(int_of_fit)
-        int_of_fit(m,1) = trapz(fit_data(1:m,2));
-    end
-    
-    
-    % ***SUBPLOT #3*** Plot the integral of the fit compared to the 
-    % integral of the raw data
-    subplot(2,2,3);
-    hold on;
-    plot(fit_data(:,1),int_of_fit(:,1),'r');
-    plot(time,int_of_raw,'b');
-    % Adjust Plot Format
-    title('Integral of Fit vs. Crude Approximation', 'FontSize', 9, 'FontWeight', 'bold');
-    %legend('Integral of Fit', 'Crude Approximation', 'Location', 'best');
-    xlabel('Time (s)', 'FontSize', 7); ylabel('Integral', 'FontSize', 7);
-    set(gca, 'FontSize', 7, 'XScale', 'log');
-    
-    
-    
-    % ***SUBPLOT #4*** Integrals on linear x-scale
-    subplot(2,2,4);
-    plot(fit_data(:,1),int_of_fit(:,1),'r');
-    hold on;
-    plot(time,int_of_raw,'b');
-    title('Integral of Fit vs. Crude Approximation', 'FontSize', 9, 'FontWeight', 'bold');
-    legend('Integral of Fit', 'Crude Approximation', 'Location', 'SouthEast');
-    xlabel('Time (s)', 'FontSize', 7); ylabel('Integral', 'FontSize', 7);
-    set(gca, 'FontSize', 7);
-    
-    fit_metric(end+1) = evaluate_fit(int_of_fit,int_of_raw);
-    
-    
-    
-    
-    % Create textbox to display "fit metric"
-    annotation(gcf,'textbox',...
-        [0.841619718309864 0.00418410041840576 0.147112676056338 0.0719487425300029],...
-        'String',{'Fit Metric: ' num2str(fit_metric(1, ppp))},...
-        'FontWeight','bold',...
-        'FitBoxToText','on',...
-        'BackgroundColor',[1 1 1]);
-    
-    % Save the graph as an image
-    drawnow;
-    set(gcf, 'Position', [50 50 840 630]);
-    saveas(gcf,fullfile(pwd,regexprep(bld_ffile,'\.bld',['_' models{ppp,2} '.bmp'])))
-
-    % Save the BLD files
-    [bldpath,bldname,bldext]=fileparts(bld_ffile);
-    print_list(hdrnames{:},[[time(1):endtime]', fplasma],fullfile(bldpath,strcat(bldname,['_' models{ppp,2}],bldext)),sf);
-end
-    print_list(hdrnames{:},[[time(1):endtime]', plasma_linear'],fullfile(bldpath,strcat(bldname,'_linear',bldext)),sf);
-    disp(fit_metric);
-end
-    
-    
-    
-function fit_metric = evaluate_fit(int_of_fit,int_of_raw)
-fit_metric = nan;
-% Compares the integral of the fit data and the integral of the raw data to
-% determine goodness of fit.
-% Returns a "fit metric"
-
-% Calculate integral for the fit data
-fit_metric = log10(abs(int_of_raw(end,1) - int_of_fit(end,1)));
-disp 'FIT METRIC';
-disp(fit_metric);
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/feng_model_aif.m b/gamma_bomb_2/code/feng_model_aif.m
deleted file mode 100644
index 7651984..0000000
--- a/gamma_bomb_2/code/feng_model_aif.m
+++ /dev/null
@@ -1,22 +0,0 @@
-function aif=feng_model_aif(A1,L1,A2,L2,A3,L3,tau,t)
-%%Model of AIF bolus based on Feng et al. Int J Biomed Comput (1993)
-%   Y(t)=0,                                                    t<tau
-%   Y(t)=(A1*(t-tau)-A2-A3).*exp(L1*(t-tau))+...
-%           A2*exp(L2*(t-tau))+A3*exp(L3*(t-tau));             t>=tau
-%
-%   [A1]=uCi/ml/sec
-%   [A2]=[A3]=uCi/ml
-%   [t]=sec
-%   [tau]=sec
-%   [L1]=[L1]=[L1]=1/sec
-
-aif=zeros(size(t));
-
-pre= t<tau;
-post= t>=tau;
-
-aif(pre)=0;
-aif(post)=(A1*(t(post)-tau)-A2-A3).*exp(L1*(t(post)-tau))+...
-    A2*exp(L2*(t(post)-tau))+A3*exp(L3*(t(post)-tau));
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/final_report.m b/gamma_bomb_2/code/final_report.m
deleted file mode 100644
index 07d61c5..0000000
--- a/gamma_bomb_2/code/final_report.m
+++ /dev/null
@@ -1,180 +0,0 @@
-%% Gamma Bomb! 2.0 Blood Data Report
-%% Participant Information
-% This section displays important demographic information about the 
-% participant and gives some generic information about the present study.
-%%
-[~,~,chart] = xlsread(dose_info);
-assignin('base', 'chart', chart);
-name = '';
-start=regexp(participant, ligand, 'start');
-for m=start(1,1):(start(1,1)+11) 
-    name = strcat(name, participant(m));
-end
-disp(strcat('Participant #:.......',name));
-disp(strcat('Dose Info Sheet:.....',dose_info));
-hour = floor(toi_time./3600);
-minute = floor(mod(toi_time,3600) ./ 60);
-second = floor(mod(mod(toi_time,3600),60));
-t_hour = num2str(hour);
-t_minute = num2str(minute);
-t_second = num2str(second);
-if hour < 10
-    t_hour = strcat('0',num2str(hour));
-end
-if minute < 10
-    t_minute = strcat('0',num2str(minute));
-end
-if second < 10
-    t_second = strcat('0',num2str(second));
-end
-disp(' ');
-disp(strcat('TOI:.........................',t_hour,':',t_minute,':',t_second));
-disp(strcat('BAT Offset...................', num2str(batoffset), ' sec'));
-if isnan(chart{16,3})
-    radiotracer = tracer;
-else
-    radiotracer = chart{16,3};
-end
-disp(['Radioligand:.................' radiotracer '- ' ligand]);
-disp(' ');
-if isnan(chart{2,10})
-    weight = 'Unavailable';
-else
-    weight = [num2str(chart{2,10}) ' lbs'];
-end
-disp(strcat('Participant Weight...........', weight));
-if isnan(chart{5,10})
-    height = 'Unavailable';
-else
-    height = [num2str(chart{5,10}) ' in'];
-end
-disp(strcat('Participant Height...........', height));
-if isnan(chart{8,10})
-    sex = 'Unavailable';
-else
-    sex = upper(chart{8,10});
-end
-disp(strcat('Participant Sex..............', sex));
-if isnan(chart{11,10})
-    byear = 'Unavailable';
-else
-    byear = num2str(chart{11,10});
-end
-disp(strcat('Participant Birth Year.......', byear));
-disp(' ');
-
-best = min(abs(models_gof));
-best_model_i = nan;
-for m=1:length(models_gof)
-    if models_gof(m) == best
-        best_model_i = m;
-    end
-end
-best_model = models(best_model_i, 2);
-disp(strcat('Best TAC Model...............', best_model));
-best_fit_i = nan;
-best = max(abs(GOF_TABLE(:,1)));
-for m=1:length(GOF_TABLE)
-    if GOF_TABLE(m) == best
-        best_fit_i = m;
-    end
-end
-best_fit = upper(pf_fits(best_fit_i,1));
-disp(strcat('Best Parent Fraction Fit.....', best_fit));
-%% 
-% --------------------------------------------------------------------------------------------------------------------------
-%% Blood Time Activity Curve (TAC) Fits
-% _Current analysis uses two kinetic models to interpolate the Time Activity
-% Curve:_ 
-%
-% # Feng Fit 
-% # Linear to 3-Exponential (L3Exp) Fit
-%
-% _During this analysis, outliers were removed prior to curve-fitting.  Outliers are
-% classified as any point after 5 minutes that increased greater than 5
-% percent OR as any point that prematurely approaches zero._
-%
-%%
-disp(['Number of Outliers: ' num2str(num_outliers+num_deleted)]);
-disp(['Number of Points Used in Analysis: ' num2str(num_points)]);
-for m=1:3
-    disp(' ');
-end
-%%
-%
-% *Goodness of Fit*
-%
-% The table below summarizes the goodness of fit of the two TAC Models.
-% The fit metric represents the space between the fitted curve and the raw
-% data.  It is calculated according to the equation:
-%
-%%
-%
-% $M = \log ( |\int_{0}^{t} x dx - \int_{0}^{t} x' dx |)$
-%
-% _where:_ 
-%
-% * $M$ = _goodness of fit_
-% * $t$ = _duration of the blood data (s)_
-% * $x$ = _raw data points_ 
-% * $x'$ = _fitted data_
-%
-% _According to the metric, a perfect fit would yeild M = 0.  The "best fit"
-% will have a value M closest to 0._
-%
-%%
-hdrs = '';
-types = models(:,2);
-for m=1:size(types)
-    if m==1
-        hdrs = [types(1)];
-    else
-        hdrs = [hdrs ' ' types(m)];
-    end
-end
-printmat(models_gof, 'Model Goodness of Fit', 'Fit_Metric', 'Feng_Fit L3Exp_Fit');
-disp(' ');
-disp(['Best TAC Model: ' best_model]);
-
-%%
-% *Feng Model*
-%
-% <<plasma_art_Feng.bmp>>
-%
-% *L3Exp Model*
-%
-% <<plasma_art_L3Exp.bmp>>
-%
-%% 
-% --------------------------------------------------------------------------------------------------------------------------
-%% Summary of Parent Fraction Fit Statistics
-% _The Parent Fraction has been fitted to four different curves:_
-% Hill Fit, Linear to Exponential Fit (Lin2Exp), Exponential Fit (Exp), and
-% Power Fit.
-%
-%%
-printmat(GOF_TABLE, 'Parent Fraction Fit Stats', 'Hill_Fit Lin2Exp_Fit Exponential_Fit Power_Fit',...
- 'Rsquare Adj_RSquare DFE');
-disp(' ');
-disp(['Best Parent Fraction Fit: ' best_fit]);
-cd (csv_path);
-%% Parent Fraction Fits
-%
-% <<parentfraction_fits.bmp>>
-%
-%% Histograms for Parent Fraction Data Points
-% _Each histogram below represents the blood data for single the Parent
-% Fraction Data Point indicated by the graph's title.  Red bars show
-% metabolite data and blue bars show the parent data._
-%
-% <<histograms_1.bmp>>
-%
-% <<histograms_2.bmp>>
-%
-%%
-if population_bool
-    disp('Parent Fraction calculated from Population data.  Histograms unavailable.');
-end
-
-%%
-% GammaBomb! 2.0 - Developed at the Hooker Research Group - MGH Martinos Center - Boston, MA
\ No newline at end of file
diff --git a/gamma_bomb_2/code/find_BAT.m b/gamma_bomb_2/code/find_BAT.m
deleted file mode 100644
index 127388e..0000000
--- a/gamma_bomb_2/code/find_BAT.m
+++ /dev/null
@@ -1,89 +0,0 @@
-function InjectionStart=find_BAT(head_curve1,crop_counts,save_img)
-if nargin<2
-    %crop_counts=300;
-    crop_counts=300;
-end
-if nargin<3,save_img=1;end
-if length(head_curve1)>crop_counts
-head_curve=head_curve1(1:crop_counts);
-else
-    head_curve=head_curve1;
-end
-%% Clean up the head curve so we can estimate the injection time
-signoise=nanmean(head_curve(1:5));
-if isnan(signoise), signoise=0;end
-head_curve=head_curve-signoise; %consider the first 5 points as noise
-head_curve(head_curve<0)=NaN;
-head_curve=pchip(1:size(head_curve,1),head_curve,[1:size(head_curve,1)]');
-%Quick moving average filter to remove the noise
-b=ones(1,16)/16;
-a=1;
-filteredData=filter(b,a,head_curve);
-dtest=(filteredData(2:end)-filteredData(1:end-1))./(filteredData(2:end)+filteredData(1:end-1));
-fdtest=filter(ones(1,5)/5,a,dtest);
-sfdtest=fdtest;sfdtest(filteredData<1000)=0;
-[~,I]=max(sfdtest);
-assignin('base', 'a', a);
-assignin('base', 'b', b);
-%g=@(a,b,c,d,e,x) model_aif(a,b,c,d,e,x);
-%ffun=fittype(g);
-ffun=fittype('model_aif(a,b,c,d,e,x)');
-
-assignin('base', 'a_after', a);
-assignin('base', 'ffun', ffun);
-
-options=fitoptions(ffun);
-
-assignin('base', 'options', options);
-
-%options.StartPoint=[1,30,min(head_curve(head_curve>0)),(max(head_curve(head_curve>0 &head_curve<Inf))-min(head_curve(head_curve>0)))/10,(head_curve(ceil(length(head_curve)*1/2))-head_curve(end))/length(head_curve)];
-x_val=[0:size(head_curve,1)-1]';
-x_val_fit=x_val(head_curve>=0 &head_curve<Inf);
-head_curve_fit=head_curve(head_curve>=0 &head_curve<Inf);
-%options.StartPoint=[1,70,min(head_curve_fit),(max(head_curve_fit)-min(head_curve_fit))/10,(head_curve_fit(end)-head_curve_fit(find(x_val_fit<ceil(x_val_fit(end)*1/2),1,'last')))/x_val_fit(end)];
-options.StartPoint=[I,10,min(head_curve_fit),(max(head_curve_fit)-min(head_curve_fit))/10,(head_curve_fit(end)-head_curve_fit(find(x_val_fit<ceil(x_val_fit(end)*1/2),1,'last')))/x_val_fit(end)];
-options.MaxIter=1000;
-options.MaxFunEvals=1000;
-%options.Lower=[0 0 -Inf -Inf -Inf];
-options.Lower=[0 0 0 -(max(head_curve_fit)-min(head_curve_fit)) -(max(head_curve_fit)-min(head_curve_fit))];
-%options.Upper=[length(head_curve) length(head_curve) Inf Inf Inf];
-options.Upper=[300 300 max(head_curve_fit) (max(head_curve_fit)-min(head_curve_fit)) (max(head_curve_fit)-min(head_curve_fit))];
-options.Robust='LAR';
-%% Force start time to be point where trues>1000
-%options.Lower=[x_val_fit(find(head_curve_fit>=100,1,'first'))-.1 0 min(head_curve_fit) -(max(head_curve_fit)-min(head_curve_fit)) -(max(head_curve_fit)-min(head_curve_fit))];
-%options.Upper=[x_val_fit(find(head_curve_fit>=100,1,'first')) 300 max(head_curve_fit) (max(head_curve_fit)-min(head_curve_fit)) (max(head_curve_fit)-min(head_curve_fit))];
-
-%%
-[fitobject,gof]=fit(x_val_fit,head_curve_fit,ffun,options);
-
-assignin('base', 'head_curve_fit', head_curve_fit);
-assignin('base', 'x_val_fit', x_val_fit);
-assignin('base', 'fitobject', fitobject);
-assignin('base', 'a_fitobject', fitobject.a);
-
-if fitobject.a>0 && fitobject.d>0
-InjectionStart=ceil(fitobject.a);
-else
-InjectionStart=0;    
-end
-if save_img
-figure('Position',[680   558   560*2   420]);%figure;
-for gg=1:2
-subplot(1,2,gg);plot(0:length(head_curve)-1,head_curve);
-hold on
-fplot(fitobject,[0,length(head_curve)-1],'r');
-set(get(gca,'XLabel'),'String','Time (sec)')
-set(get(gca,'YLabel'),'String','Counts')
-set(get(gca,'Title'),'String',['Bolus Arrival Time Pick-off T=' num2str(InjectionStart)])
-if fitobject.a>0 && fitobject.d>0 && gg==1
-xlim([0,300])
-else
-    xlim([0,20+fitobject.a])
-end
-end
-legend('head curve','fit','Location','NorthWest');
-%saveas(gcf,'BAT.pdf');
-set(gcf,'PaperPositionMode','auto','PaperOrientation','landscape');print(gcf,'-dpdf','BAT.pdf')
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/gamma_bomb.m b/gamma_bomb_2/code/gamma_bomb.m
deleted file mode 100644
index 35e1c04..0000000
--- a/gamma_bomb_2/code/gamma_bomb.m
+++ /dev/null
@@ -1,605 +0,0 @@
-%  patient_AIF_gamma_read.m
-%  Author: Spencer Bowen
-%  Lab Group: Catana
-%  Date: 09-06-12
-%  Read automatic gamma counter data for AIF arterial and venous whole blood and plasma samples and
-%  sort into a readable format.
-%  inputs:   template_file = name of csv file with automatic gamma counter sample information
-%	     csv_file      = name, including directory, of the csv file with the first set of
-%			     sample measurements (assumes csv files numeric with sequential values)
-%	     csv_out       = name of the csv file to write the compiled data to
-%
-%
-%  Modified By Tom Morin 
-%  5/01/15 - Modified to print results to a single html/PDF file
-%  5/20/15 - Added Power, Exponential, & Hill Fits to Parent Fraciton Data
-%  5/21/15 - Now displays BAT Offset (Bolus Arrival Time) in final report
-%               and accounts for BAT in .bld output files
-%  5/22/15 - More aesthetically pleasing final reports
-%  5/27/15 - Delete points that prematurely approach zero in TAC
-%  6/2/15  - Added histograms to show origin of parent fraction data
-%  6/3/15  - Display integrals with Fit/L3Exp Fits & calculate custom metric
-%  6/4/15  - State which fits/models are best in the final report.
-
-function  gamma_bomb(template_file, csv_path, tracer, met_correct, dose_info, report_format, population_pf, bk_cps_value)
-%% Check to see if a Final Report has already been created
-exit_gamma_bomb = 0;
-exit_gamma_bomb = check_overwrite(csv_path, population_pf);
-if(exit_gamma_bomb == 1)
-    disp('Exiting Gamma Bomb 2.0');
-    return;
-end
-
-assignin('base', 'population_bool', population_pf);
-assignin('base', 'tracer', tracer);
-
-%% Define Constants
-switch lower(tracer)
-    case {'f-18'} %F-18
-        half_life=60*120;
-    case {'c-11'} %c-11
-        half_life=20.38*60;
-    otherwise
-        error('unknown tracer.  Contact Ciprian')
-end
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% define constants
-% number of positions in the gamma counter racks
-pos_num = 10;
-max_samp= 10000;
-csv_dat_str = '%d%s%s%d%d%d%d%d%f%s%f%f%f%s';
-pa_col  = 1;
-wa_col  = 2;
-pv_col  = 3;
-wv_col  = 4;
-out_str = '%d,%d,%d,%s,%f,%d';
-num_out_col = 6;
-% strings describing output columns
-out_hdr_str = {'Run ID','Rack','Pos','Measurement Time',...
-    'Duration (sec)','F-18 350-600 keV Counts'};
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% load parameters
-current_dir = pwd;cd(csv_path);
-
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%% Read in Template File
-h = waitbar(0, 'Reading in Template Files - 0%');
-[~,tube_code_mx,~]=xlsread(template_file,1);
-[col_time_mx,~,~]=xlsread(template_file,2);
-[tube_vol_mx,~,~]=xlsread(template_file,3);
-[TOI,~,~]=xlsread(template_file,4);
-toi_vec=datevec(TOI);
-assignin('base', 'TOI', TOI);
-toi_time=toi_vec(4)*3600+toi_vec(5)*60+toi_vec(6);
-%assignin('base', 'toi_vec', toi_vec);
-assignin('base', 'toi_time', toi_time);
-InjectionStart=0;
-update_waitbar(0.05, h, 'Calculating BAT (This may take a few minutes.)');
-if exist(fullfile(home_dir,'PET','Frame1.lst.hdr'),'file')
-    if exist(fullfile(home_dir,'PET','Sum','TAC_workspace.mat'),'file')
-        display('using TAC to determine the start time and align the data to the PET')
-        load(fullfile(home_dir,'PET','Sum','TAC_workspace.mat'),'InjectionStart');
-        load(fullfile(home_dir,'PET','Sum','TAC_workspace.mat'),'Series_Duration');
-    else
-        display('No TAC workspace found--Reconstrucing Frame1.lst to get injection Start')
-        c_dir=pwd;
-        cd(fullfile(home_dir,'PET'));
-        [Scanner_Duration, Series_Duration, frame_start_time, ...
-            frame_stop_time, acquisition_start, lst_files, ...
-            lst_files_whole]=TAC_sort_lst_mode(fullfile(home_dir,'PET'));
-        TAC_process_data('Frame1');
-        update_waitbar(0.1, h, 'Generating Head Curve...');
-        file=fullfile(pwd, strcat('Frame1','_head_curve.s.hc')); %build fullfile name
-        [head_curve,head_curve_trues]=generate_head_curve(file,Series_Duration);
-        update_waitbar(0.2, h, 'Determining Injection Start Time');
-        
-        assignin('base', 'head_curve_trues', head_curve_trues);
-        
-        InjectionStart=find_BAT(head_curve_trues);
-        update_waitbar(0.22, h, 'Deleting Frames');
-        delete('Frame1*.lor*','Frame1*.s*')
-        update_waitbar(0.24, h,'Changing Directory');
-        cd(c_dir)
-    end
-    update_waitbar(0.26, h, 'Dipslaying Injection Start & Series Duration');
-    display(['Injection Start: ' num2str(InjectionStart)]);
-    display(['Series Duration: ' num2str(length(Series_Duration))]);
-    update_waitbar(0.28, h, 'Determining extrap_time');
-    extrap_time=length(Series_Duration);
-    update_waitbar(0.3, h, 'Crunching some more numbers...');
-    lst_hdr=read_i_hdr(fullfile(home_dir,'PET','Frame1.lst.hdr'));
-    lst_startvec=datevec(lst_hdr.StudyTimeHhMmSs);
-    lst_start=lst_startvec(4)*3600+lst_startvec(5)*60+lst_startvec(6);
-    batoffset=(lst_start+InjectionStart)-toi_time;
-    toi_time=toi_time+batoffset;
-    assignin('base','InjectionStart', InjectionStart);
-    assignin('base', 'lst_start', lst_start);
-    assignin('base', 'batoffset', batoffset);
-    assignin('base', 'toi_time', toi_time);
-end
-col_time_mx(1,:)=[];
-tube_vol_mx(1,:)=[];
-tot_samps=size(unique(find(~strcmpi(tube_code_mx,'E'))),1); %total number of non E
-datev=datevec(col_time_mx);
-secv=datev(1:end,4)*3600+datev(1:end,5)*60+datev(1:end,6);
-col_time_mx=reshape(secv,size(col_time_mx))-toi_time;
-%%
-
-csv_files=ls(fullfile(csv_path,'*.csv'));
-[~,csv_name,~]=fileparts(csv_files(1,:));
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% open and read in csv files (filenames should end in consecutive numbers)
-update_waitbar(0.35, h, 'Reading in CSV files');
-csv_tot       = 0;
-csv_start_num = str2num(csv_name);
-csv_samp_tot  = 0;
-fail=0;
-readon = 1;
-while readon
-    csv_cur= fullfile(csv_path,[num2str(csv_start_num+csv_tot,'%06.0f') '.csv']);
-    
-    if ~exist(csv_cur,'file');
-        fail=fail+1;
-        if fail==2;
-            break
-        end
-    else
-        
-        fid_in = fopen(csv_cur,'r');
-        csv_dat= textscan(fid_in,csv_dat_str,'delimiter',',','HeaderLines',1,'EndOfLine','\n');
-        fclose(fid_in);
-        csv_samp_tot = csv_samp_tot + length(csv_dat{1});
-        if csv_tot==0
-            csv_comp_dat = csv_dat;
-        else
-            rack_offset=csv_comp_dat{6}(end);
-            for cnti=1:14
-                if cnti==6
-                    csv_comp_dat{cnti} = [csv_comp_dat{cnti}; csv_dat{cnti}+rack_offset];
-                else
-                    csv_comp_dat{cnti} = [csv_comp_dat{cnti}; csv_dat{cnti}];
-                end
-            end
-        end
-    end
-    
-    if csv_samp_tot>=tot_samps
-        readon=0;
-    else
-        csv_tot= csv_tot+1;
-    end
-    
-end
-assignin('base', 'csv_comp_dat', csv_comp_dat);
-
-%% Construct other necessary matrices 
-%(Take csv data and format it to tables that are the same dimensions as the one in the template file)
-%Rack=row
-%Pos=col
-update_waitbar(0.4, h, 'Constructing matrices');
-count_time_mx=zeros(size(tube_code_mx));
-count_dur_mx=zeros(size(tube_code_mx));
-t_counts_mx=zeros(size(tube_code_mx));
-dev_cpm_mx=zeros(size(tube_code_mx));
-t_counts_error_mx=zeros(size(tube_code_mx));
-
-for m=1:size(csv_comp_dat{1},1)
-    dv=datevec(csv_comp_dat{3}(m));
-    count_time_mx(csv_comp_dat{6}(m),csv_comp_dat{8}(m))=dv(4)*3600+dv(5)*60+dv(6);
-    count_dur_mx(csv_comp_dat{6}(m),csv_comp_dat{8}(m))=csv_comp_dat{9}(m);
-    t_counts_mx(csv_comp_dat{6}(m),csv_comp_dat{8}(m))=csv_comp_dat{11}(m);
-    dev_cpm_mx(csv_comp_dat{6}(m),csv_comp_dat{8}(m))=csv_comp_dat{12}(m);
-    t_counts_error_mx(csv_comp_dat{6}(m),csv_comp_dat{8}(m))=csv_comp_dat{13}(m);
-end
-
-%% Construct blank scan matrix
-Bpos=find(strcmpi(tube_code_mx','B'));
-display(nargin)
-if nargin==8
-    bk_mx=ones(size(count_time_mx))*bk_cps_value;
-elseif ~isempty(Bpos)
-    blanks=zeros(size(tube_code_mx))';
-    start_pos=1;
-    t_counts_mx_p=(t_counts_mx./count_dur_mx)';
-    for m=1:length(Bpos)
-        blanks(start_pos:Bpos(m))=t_counts_mx_p(Bpos(m));
-        start_pos=Bpos(m)+1;
-    end
-    %finish rest of positions
-    blanks(blanks==0)=t_counts_mx_p(Bpos(end));
-    bk_mx=blanks';
-else
-    bk_mx=zeros(size(count_time_mx));
-end
-
-%% Decay Correct Data
-update_waitbar(0.45, h, 'Decaying Data');
-elapsed_t_mx=count_time_mx-toi_time;
-cps_dkc_mx=(t_counts_mx./count_dur_mx-bk_mx).*exp(log(2).*elapsed_t_mx/half_life);
-kbq_ml_dkc_mx=cps_dkc_mx./tube_vol_mx*60/40;
-%% Breakdown for Metabolite Correction
-%
-final_labels={};
-file_name={};
-if ~met_correct
-    [tube_struct,t_labels]=sort_tube_codes(tube_code_mx,col_time_mx,kbq_ml_dkc_mx);
-else
-    kbq_ml_dkc_met_mx=kbq_ml_dkc_mx;
-    kbq_ml_dkc_met_mx(find(strcmpi(tube_code_mx,'M')|strcmpi(tube_code_mx,'P')))=kbq_ml_dkc_mx(strcmpi(tube_code_mx,'M')|strcmpi(tube_code_mx,'P')).*tube_vol_mx(strcmpi(tube_code_mx,'M')|strcmpi(tube_code_mx,'P'));
-    [tube_struct,t_labels]=sort_tube_codes(tube_code_mx,col_time_mx,kbq_ml_dkc_met_mx);
-    % Metabolite Correction
-    u_times=unique(tube_struct.M(:,1));
-    for m=1:size(u_times,1)
-        mets(m,1)=sum(tube_struct.M(find(tube_struct.M(:,1)==u_times(m)),2));
-        parent(m,1)=sum(tube_struct.P(find(tube_struct.P(:,1)==u_times(m)),2));
-        if isfield(tube_struct,'PA')
-            plasma(m,1)=tube_struct.PA(find(tube_struct.PA(:,1)==u_times(m)),2);
-        elseif isfield(tube_struct,'PV')
-            plasma(m,1)=tube_struct.PV(find(tube_struct.PV(:,1)==u_times(m)),2);
-        else
-            error('For Metabolite correction either arterial or venous samples must be drawn. Contact Ciprian');
-        end
-    end
-    total=mets+parent;
-    met_ratio=parent./total;
-    tube_struct.M=[0 1;u_times met_ratio];
-    tube_struct=rmfield(tube_struct,'P');
-    t_labels(cellfun(@(x) strcmpi(x,'P'),t_labels))=[];
-end
-
-update_waitbar(0.5, h, 'Generating TAC Data...');
-for m=1:size(t_labels,1)
-    switch lower(t_labels{m})
-        case 'pa'
-            final_labels=[final_labels,{'sample-time[seconds]';'plasma[kBq/cc]'}];
-            file_name=[file_name,{'plasma_art.bld'}];
-        case 'pv'
-            final_labels=[final_labels,{'sample-time[seconds]';'plasma[kBq/cc]'}];
-            file_name=[file_name,{'plasma_ven.bld'}];
-        case 'wa'
-            final_labels=[final_labels,{'sample-time[seconds]';'whole-blood[kBq/cc]'}];
-            file_name=[file_name,{'whole-blood_art.bld'}];
-        case 'wv'
-            final_labels=[final_labels,{'sample-time[seconds]';'whole-blood[kBq/cc]'}];
-            file_name=[file_name,{'whole-blood_ven.bld'}];
-        case 'm'
-            final_labels=[final_labels,{'sample-time[seconds]';'parent-fraction[1/1]'}];
-            file_name=[file_name,{'parentfraction.bld'}];
-        otherwise
-    end
-end
-
-if (exist(fullfile(pwd,'parentfraction.bld'),'file') || ~met_correct) && (exist(fullfile(pwd,'whole-blood_ven.bld'),'file') || exist(fullfile(pwd,'whole-blood_art.bld'),'file') || exist(fullfile(pwd,'plasma_ven.bld'),'file') || exist(fullfile(pwd,'plasma_art.bld'),'file'))
-    qans=questdlg('Parent-Fraction and Blood .bld files present. Overwrite?','Blood GUI','Yes','No','No');
-else
-    qans='yes';
-end
-
-if strcmpi(qans,'yes')
-    % Delete points that approach zero prematurely
-    [num_deleted, temp] = check_decreasing(tube_struct.PA);
-    tube_struct.PA = [];
-    tube_struct.PA = temp;
-    % Print Preliminary Data to BLD files
-    for m=1:size(t_labels,1)
-        if ~(population_pf && strcmp(file_name{m},'parentfraction.bld'))    % Check to see if Population Parent Fraction has already been created
-            print_list(final_labels(:,m), tube_struct.(t_labels{m}), fullfile(pwd,file_name{m}), 4);
-            figure;
-            if ~strcmpi(t_labels{m},'m') && tube_struct.(t_labels{m})(1,1)~=0 && tube_struct.(t_labels{m})(1,2)~=0
-                tube_struct.(t_labels{m})=[0 0;tube_struct.(t_labels{m})];
-            end
-            
-            % PCHIP Fit of Parent Fraction Data
-            p_cfit=fit(tube_struct.(t_labels{m})(:,1),tube_struct.(t_labels{m})(:,2),'pchipinterp');
-            subplot(2,1,1);
-            plot(tube_struct.(t_labels{m})(:,1),tube_struct.(t_labels{m})(:,2),'r*');
-            hold on;
-            fplot(p_cfit,xlim,.00001);
-            title(['PCHIP-interp of ' regexprep(file_name{m},'_','\\_')]);
-            legend('data','interpolant');
-            
-            subplot(2,1,2);
-            plot(tube_struct.(t_labels{m})(:,1),tube_struct.(t_labels{m})(:,2),'r*');
-            plot(p_cfit,'integral');
-            title(['Integral of ' regexprep(file_name{m},'_','\\_')])
-        end
-    end
-else
-end
-assignin('base', 'u_times', u_times);
-assignin('base', 'kbq_ml_dkc_mx', kbq_ml_dkc_mx);
-assignin('base', 'tube_code_mx', tube_code_mx);
-
-%% Construct Histograms for extra analysis
-if (~population_pf)
-    make_histograms(u_times, kbq_ml_dkc_mx, tube_code_mx);
-end
-
-%% Fit data
-pos_wksp_file=ls(fullfile(home_dir,'PET','Sum','*_workspace.mat'));
-if ~isempty(pos_wksp_file) && exist(fullfile(home_dir,'PET','Frame1.lst.hdr'),'file')
-    wkspfil=fullfile(home_dir,'PET','Sum',deblank(pos_wksp_file(1,:)));
-    load(deblank(wkspfil(1,:)),'Series_Duration');
-    if length(Series_Duration)>tube_struct.(t_labels{m})(end,1);
-        extrap_time=length(Series_Duration);
-    else
-        extrap_time=tube_struct.(t_labels{m})(end,1);
-    end
-else
-    extrap_time=tube_struct.(t_labels{m})(end,1);
-end
-
-% Fit Parent Fraction according to four different models
-[met_fit, GOF_TABLE, fits] = pf_fit('parentfraction.bld','',extrap_time, 4);
-assignin('base', 'GOF_TABLE', GOF_TABLE);
-assignin('base', 'pf_fits', fits);
-set(gcf, 'Position', [50 50 840 630]);
-saveas(gcf, 'parentfraction_fits.bmp');
-
-% Fit the raw data
-update_waitbar(0.7, h, 'Fitting Raw Data (This may take a minute.)');
-raw_bld_file={'plasma_art.bld','plasma_ven.bld','whole-blood_art.bld','whole-blood_ven.bld'};
-for m=1:4
-    if exist(fullfile(pwd,raw_bld_file{m}),'file'),
-        test=dlmread(raw_bld_file{m},'\t',1,0);
-        if test(1,1)<200 %test(1,1)<60 %only fit data that looks like the peak was captured.
-            if exist(fullfile(pwd,'parentfraction.bld'),'file')
-            % feng_fit3 fits data according to Feng & L3Exp models
-            [bld_fit, models_gof, models]=feng_fit3(raw_bld_file{m},extrap_time,met_fit);  
-            else
-            [bld_fit, models_gof, models]=feng_fit3(raw_bld_file{m},extrap_time);
-            end
-            if exist(fullfile(pwd,'parentfraction_fit.bld'),'file') %%metabolite correction
-                corr_bld_crv=met_fit.*bld_fit;
-            end
-        end
-    end
-end
-assignin('base', 'models_gof', models_gof);
-
-update_waitbar(0.8, h, 'Generating Additional Figures');
-% Use Parent Fraction Fit to apply Met correction (if metcor was selected)
-disp 'FENG & LIN3EXP FITS via Lin2Exp Met Correction';
-if exist(fullfile(pwd,'parentfraction_lin2exp.bld'),'file')
-    bld_fls=cellstr(ls('*.bld'));
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'parentfraction','match')))=[];
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'plasma_art.bld','match')))=[];
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'plasma_ven.bld','match')))=[];
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'whole-blood_art.bld','match')))=[];
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'whole-blood_ven.bld','match')))=[];
-    bld_fls(cellfun(@(x) ~isempty(x),regexp(bld_fls,'_metcor','match')))=[];
-
- PFfit_fls=cellstr(ls('*.bld'));
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'Feng','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'L3','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'parentfraction.bld','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'plasma_art.bld','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'plasma_ven.bld','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'whole-blood_art.bld','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'whole-blood_ven.bld','match')))=[];
-    PFfit_fls(cellfun(@(x) ~isempty(x),regexp(PFfit_fls,'linear','match')))=[];
-    
-    iteration = 1;
-    if ~isempty(bld_fls)
-        for m=1:size(bld_fls,1)
-            for i=1:size(PFfit_fls,1)
-                switch PFfit_fls{i}
-                    case {'parentfraction_hill.bld'}
-                        fname = 'hill';
-                    case {'parentfraction_exp.bld'}
-                        fname = 'exp';
-                    case {'parentfraction_power.bld'}
-                        fname = 'power';
-                    case {'parentfraction_lin2exp.bld'}
-                        fname = 'lin2exp';
-                    otherwise
-                        error ('Fit model not known to this program.')
-                end
-                %iteration = (((m.*size(PFfit_fls,1)) + i) - size(PFfit_fls,1));
-                type = metcor_bld2(bld_fls{m},PFfit_fls{i},fname,batoffset,iteration,(size(bld_fls,1)),(size(PFfit_fls,1)));
-                %metcor_bld3(bld_fls{m},PFfit_fls{i},fname,batoffset);
-                %metcor_bld4(bld_fls{m},PFfit_fls{i},fname,batoffset);end
-                if iteration < size(PFfit_fls,1)
-                    iteration = iteration + 1;
-                else
-                    iteration = 1;
-                    saveas(gcf, fullfile(pwd,strcat('metcor_graphs_',type,'.bmp')));
-                end
-            end
-        end
-    end
-end
-
-%% Write header
-fid1=fopen(fullfile(csv_path,'blood.hdr'), 'w');
-fprintf(fid1,['TemplateFile:=' regexprep(template_file,'\\','\\\\'), '\r']);
-fprintf(fid1,['CSVPath:=' regexprep(csv_path,'\\','\\\\'), '\r']);
-fprintf(fid1,['Injection Start:=' num2str(InjectionStart), '\r']);
-fprintf(fid1,['BAT Offset:=' num2str(batoffset), '\r']);
-fprintf(fid1,['Tracer:=' num2str(tracer), '\r']);
-fprintf(fid1,['MetCorrection:=' num2str(met_correct), '\r']);
-fprintf(fid1,['Duration:=' num2str(extrap_time), '\r']);
-fprintf(fid1,['Reconstruction Date:=' datestr(now), '\r']);
-fclose(fid1);
-
-update_waitbar(0.9, h, 'Creating the Final Report');
-%% Create Final Report (final_report.pdf)
-% Assign necessary variables to workspace
-assignin('base', 'participant', template_file);
-assignin('base', 'dose_info', dose_info);
-assignin('base', 'csv_path', csv_path);
-assignin('base', 'batoffset', batoffset);
-assignin('base', 'num_deleted', num_deleted);
-assignin('base', 'models', models);
-
-if strcmp(report_format, 'pdf')
-    publish('final_report.m', 'showCode', false, 'maxHeight', 100, 'maxWidth', 100 ...
-        , 'imageFormat', 'jpg', 'format', 'pdf', 'outputDir', csv_path);
-elseif strcmp(report_format, 'html')
-    publish('final_report.m', 'showCode', false, 'maxHeight', 100, 'maxWidth', 100 ...
-        , 'imageFormat', 'jpg', 'format', 'html', 'outputDir', csv_path);
-elseif strcmp(report_format, 'both')
-    publish('final_report.m', 'showCode', false, 'maxHeight', 100, 'maxWidth', 100 ...
-        , 'imageFormat', 'jpg', 'format', 'html', 'outputDir', csv_path);
-    publish('final_report.m', 'showCode', false, 'maxHeight', 100, 'maxWidth', 100 ...
-        , 'imageFormat', 'jpg', 'format', 'pdf', 'outputDir', csv_path);
-end
-
-%% Clean Up
-update_waitbar(0.95, h, 'Cleaning Up');
-% Put HTML report, BMP Images, & PNG Images into a separate folder
-mkdir 'images_and_html';
-if strcmp(report_format, 'html') || strcmp(report_format, 'both')
-    copyfile('final_report.html', 'images_and_html');
-    delete('final_report.html');
-end
-bmps = ls('*.bmp');
-for m=1:size(bmps)
-    file = regexprep(bmps(m,:), ' ', '');
-    %disp( [file, '.']);
-    copyfile(file, 'images_and_html');
-    delete(file);
-end
-pngs = ls('*.png');
-for m=1:size(pngs)
-    file = regexprep(pngs(m,:), ' ', '');
-    %disp( [file, '.']);
-    copyfile(file, 'images_and_html');
-    delete(file);
-end
-addpath('images_and_html');
-
-% Put BLD files into a separate folder
-mkdir 'bld_files';
-blds = ls('*.bld');
-for m=1:size(blds)
-    file = regexprep(blds(m,:), ' ', '');
-    %disp( [file, '.']);
-    copyfile(file, 'bld_files');
-    delete(file);
-end
-addpath('bld_files');
-
-update_waitbar(1, h, 'Analysis Complete!');
-
-% Clear Workspace Variables
-clear;
-
-disp ' *****ANALYSIS COMPLETE***** ';
-close all;
-end
-
-
-
-%% =======================================================================
-function [tube_struct,t_labels]=sort_tube_codes(tube_code_mx,col_time_mx,kbq_ml_dkc_mx)
-% count_time_mx
-% count_dur_mx
-% t_counts_mx
-% dev_cpm_mx
-% t_counts_error_mx
-% counts_dkc_mx
-%% First, sort tubes by label then time
-t_labels=unique(tube_code_mx(:));
-t_labels(cellfun(@(x) any(strcmpi(x,{'B','E','K'})),t_labels))=[]; %remove B and E
-tube_struct=struct;
-for m=1:size(t_labels,1)
-    lab_pos=find(strcmpi(tube_code_mx,t_labels{m}));
-    [time,lab_pos_ind]=sort(col_time_mx(lab_pos));
-    ordered_data=kbq_ml_dkc_mx(lab_pos(lab_pos_ind));
-    tube_struct.(t_labels{m})=[time, ordered_data];
-    tube_struct.(t_labels{m})(tube_struct.(t_labels{m})(:,1)<0,:)=[]; %remove negative times
-    tube_struct.(t_labels{m})(tube_struct.(t_labels{m})(:,2)<0,:)=[]; %remove negative numbers
-end
-end
-
-
-
-%% =======================================================================
-function exit_gamma_bomb = check_overwrite(csv_path, population_pf)
-% Input: the directory of csv_files
-% Output: Checks to make sure a final report has not already been generated 
-% for this data.  If a final report is found:
-%   - Delete existing final report
-%   - Delete any exisiting image files/graphs that were generated before
-%   - Delete any existing bld files that were generated beforeif (exist(fullfile(csv_path,'final_report.html'),'file'))
-    images=ls(fullfile(csv_path,'*.bmp'));
-    disp(images);
-    [num_imgs,~] = size(images);
-    
-    overwrite_warning = 'Empty';
-    if ( exist([csv_path '\final_report.pdf'], 'file') || exist([csv_path '\final_report.html'], 'file') || (num_imgs>0) ||...
-           exist([csv_path '\bld_files'], 'dir') || exist([csv_path '\images_and_html'], 'dir') )
-        overwrite_warning = questdlg(...
-        'Final Report or images already generated for this participant. Overwrite? (All existing final reports, bld files, and bitmap images will be deleted.)'...
-        ,'Overwrite Warning','Yes','No','No');
-    end
-    if strcmp(overwrite_warning, 'No')
-        disp 'Program Terminated.';
-        exit_gamma_bomb = 1;
-    elseif strcmp(overwrite_warning, 'Empty')
-        exit_gamma_bomb = 0;
-        return;
-    else
-        if exist(fullfile(csv_path,'final_report.html'),'file')
-            delete(fullfile(csv_path,'final_report.html'),'file');
-        end
-        if exist(fullfile(csv_path,'final_report.pdf'),'file')
-            delete(fullfile(csv_path,'final_report.pdf'),'file');
-        end
-        if exist([csv_path '\bld_files'], 'dir')
-            rmdir('bld_files', 's');
-        end
-        if exist([csv_path '\images_and_html'], 'dir')
-            rmdir('images_and_html', 's');
-        end
-        images=ls(fullfile(csv_path,'*.bmp'));
-        pngs = ls(fullfile(csv_path,'*.png'));
-        images = cat(1, images, pngs);
-        [num_img,~] = size(images);
-        disp(num_img);
-        if (num_img > 0)
-            for m=1:num_img
-                delete(strcat(csv_path,'\',images(m,:)));
-            end
-        end
-        
-        % Don't delete bld files if you're using a population parent
-        % fraction!
-        if (~population_pf)
-            builds=ls(fullfile(csv_path,'*.bld'));
-        
-            [num_bld,~] = size(builds);
-            disp(num_bld);
-            if (num_bld > 0)
-                for m=1:num_bld
-                    delete(strcat(csv_path,'\',builds(m,:)));
-                end
-            end
-        end
-        
-        
-        clear images builds
-        exit_gamma_bomb = 0;
-        %delete(images);
-        %delete(builds);
-    end
-end
-
-
-%% ========================================================================
-function update_waitbar(val, h, message)
-% Updates the waitbar to show program's progress
-if val == 0
-    h = waitbar(0, [message, ' - ', num2str(val*100), '%']);
-elseif val > 1
-    return;
-elseif val == 1
-    close(h);
-else
-    waitbar(val, h, [message, ' - ', num2str(val*100), '%']);
-end  
-end
-
diff --git a/gamma_bomb_2/code/gamma_bomb_gui.fig b/gamma_bomb_2/code/gamma_bomb_gui.fig
deleted file mode 100644
index 29ac3f0..0000000
Binary files a/gamma_bomb_2/code/gamma_bomb_gui.fig and /dev/null differ
diff --git a/gamma_bomb_2/code/gamma_bomb_gui.m b/gamma_bomb_2/code/gamma_bomb_gui.m
deleted file mode 100644
index ce18b27..0000000
--- a/gamma_bomb_2/code/gamma_bomb_gui.m
+++ /dev/null
@@ -1,373 +0,0 @@
-function varargout = gamma_bomb_gui(varargin)
-% GAMMA_BOMB_GUI MATLAB code for gamma_bomb_gui.fig
-%      GAMMA_BOMB_GUI, by itself, creates a new GAMMA_BOMB_GUI or raises the existing
-%      singleton*.
-%
-%      H = GAMMA_BOMB_GUI returns the handle to a new GAMMA_BOMB_GUI or the handle to
-%      the existing singleton*.
-%
-%      GAMMA_BOMB_GUI('CALLBACK',hObject,eventData,handles,...) calls the local
-%      function named CALLBACK in GAMMA_BOMB_GUI.M with the given input arguments.
-%
-%      GAMMA_BOMB_GUI('Property','Value',...) creates a new GAMMA_BOMB_GUI or raises the
-%      existing singleton*.  Starting from the left, property value pairs are
-%      applied to the GUI before gamma_bomb_gui_OpeningFcn gets called.  An
-%      unrecognized property name or invalid value makes property application
-%      stop.  All inputs are passed to gamma_bomb_gui_OpeningFcn via varargin.
-%
-%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
-%      instance to run (singleton)".
-%
-% See also: GUIDE, GUIDATA, GUIHANDLES
-
-% Edit the above text to modify the response to help gamma_bomb_gui
-
-% Last Modified by GUIDE v2.5 03-Jun-2015 15:19:03
-
-% Begin initialization code - DO NOT EDIT
-gui_Singleton = 1;
-gui_State = struct('gui_Name',       mfilename, ...
-                   'gui_Singleton',  gui_Singleton, ...
-                   'gui_OpeningFcn', @gamma_bomb_gui_OpeningFcn, ...
-                   'gui_OutputFcn',  @gamma_bomb_gui_OutputFcn, ...
-                   'gui_LayoutFcn',  [] , ...
-                   'gui_Callback',   []);
-if nargin && ischar(varargin{1})
-    gui_State.gui_Callback = str2func(varargin{1});
-end
-
-if nargout
-    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
-else
-    gui_mainfcn(gui_State, varargin{:});
-end
-% End initialization code - DO NOT EDIT
-
-
-% --- Executes just before gamma_bomb_gui is made visible.
-function gamma_bomb_gui_OpeningFcn(hObject, eventdata, handles, varargin)
-% This function has no output args, see OutputFcn.
-% hObject    handle to figure
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-% varargin   command line arguments to gamma_bomb_gui (see VARARGIN)
-
-% Choose default command line output for gamma_bomb_gui
-handles.output = hObject;
-
-% Update handles structure
-guidata(hObject, handles);
-
-% UIWAIT makes gamma_bomb_gui wait for user response (see UIRESUME)
-% uiwait(handles.gamma_gui);
-
-
-% --- Outputs from this function are returned to the command line.
-function varargout = gamma_bomb_gui_OutputFcn(hObject, eventdata, handles) 
-% varargout  cell array for returning output args (see VARARGOUT);
-% hObject    handle to figure
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Get default command line output from handles structure
-varargout{1} = handles.output;
-
-
-
-function xls_ffile_Callback(hObject, eventdata, handles)
-% hObject    handle to xls_ffile (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of xls_ffile as text
-%        str2double(get(hObject,'String')) returns contents of xls_ffile as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function xls_ffile_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to xls_ffile (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in get_xls_ffile.
-function get_xls_ffile_Callback(hObject, eventdata, handles)
-% hObject    handle to get_xls_ffile (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-[filename,filepath,~]=uigetfile(fullfile(pwd,'*.xls;*xlsx'),'Pick Template File');
-cd(filepath)
-set(handles.xls_ffile,'String',fullfile(filepath,filename))
-guidata(hObject, handles);
-
-
-function csv_dir_Callback(hObject, eventdata, handles)
-% hObject    handle to csv_dir (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of csv_dir as text
-%        str2double(get(hObject,'String')) returns contents of csv_dir as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function csv_dir_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to csv_dir (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in get_csv_dir.
-function get_csv_dir_Callback(hObject, eventdata, handles)
-% hObject    handle to get_csv_dir (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-set(handles.csv_dir,'String',uigetdir(pwd))
-guidata(hObject, handles);
-
-% --- Executes on selection change in tracer.
-function tracer_Callback(hObject, eventdata, handles)
-% hObject    handle to tracer (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: contents = cellstr(get(hObject,'String')) returns tracer contents as cell array
-%        contents{get(hObject,'Value')} returns selected item from tracer
-
-
-% --- Executes during object creation, after setting all properties.
-function tracer_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to tracer (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: popupmenu controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in allons_y.
-function allons_y_Callback(hObject, eventdata, handles)
-% hObject    handle to allons_y (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-assignin('base','ligand',get(handles.ligand,'String'));
-cd(get(handles.csv_dir,'String'));
-
-% Quickly check data to make sure all the times make sense
-dlg={'***Template***'};
-template_TOI=datestr(xlsread(get(handles.xls_ffile,'String'),4),'HH:MM:SS');
-dlg(end+1)={['Template TOI = ' template_TOI]};
-col_mx=xlsread(get(handles.xls_ffile,'String'),2);
-first_sample_t=datestr(col_mx(2,1),'HH:MM:SS');
-dlg(end+1)={['First Draw Time = ' first_sample_t]};
-
-% First csv file
-dlg(end+1)={'***CSV***'};
-csv_files=ls(get(handles.csv_dir,'String'));
-fid_in = fopen(fullfile(get(handles.csv_dir,'String'),csv_files(3,:)),'r');
-csv_dat_str = '%d%s%s%d%d%d%d%d%f%s%f%f%f%s';
-csv_dat= textscan(fid_in,csv_dat_str,'delimiter',',','HeaderLines',1,'EndOfLine','\n');
-csv_read_t=datestr(csv_dat{3}{1},'HH:MM:SS');
-dlg(end+1)={['First Read Time = ' csv_read_t]};
-
-% Bay 6 Dose info and Frame1.hdr
-hd=home_dir(get(handles.xls_ffile,'String'));
-if exist(fullfile(hd,'PET','Dose_info.xls'),'file')
-    dlg(end+1)={'***Dose Info***'};
-    di=xlsread(fullfile(hd,'PET','Dose_info.xls'),1);
-    dose_calib_t=datestr(di(3,7),'HH:MM:SS');
-    dlg(end+1)={['Dose Calib. Time = ' dose_calib_t]};
-    Series_t=datestr(di(3,1),'HH:MM:SS');
-    dlg(end+1)={['Series Time = ' Series_t]};
-    Acq_t=datestr(di(3,1),'HH:MM:SS');
-    dlg(end+1)={['Acq Time = ' Acq_t]};
-end
-dlg(end+1)={'***Frame 1***'};
-if exist(fullfile(hd,'PET','Frame1.lst.hdr'),'file')
-    pd=read_i_hdr(fullfile(hd,'PET','Frame1.lst.hdr'));
-    PET_start_t=pd.StudyTimeHhMmSs;
-elseif exist(fullfile(hd,'PET','Frame1.hdr'),'file')
-    pd=read_i_hdr(fullfile(hd,'PET','Frame1.hdr'));
-    PET_start_t=pd.StudyTimeHhMmSs;
-else
-    PET_start_t='';
-end
-dlg(end+1)={['Frame1.lst.hdr Start Time = ' PET_start_t]};
-dlg(end+1)={''};
-dlg(end+1)={'Do these times make sense?'};
-button=questdlg(dlg);
-
-% Was a population curve generated for the parent fraction?
-population_bool = false;
-if (strcmp(get(handles.pop_gen_button, 'String'), 'Parent Fraction Ready!'))
-    population_bool = true;
-end
-
-% Begin Data Analysis if times make sense
-switch button
-    case 'Yes'
-contents = cellstr(get(handles.tracer,'String'));
-format = cellstr(get(handles.report_format,'String'));
-    display(get(handles.xls_ffile,'String'))
-    display(get(handles.csv_dir,'String'))
-    display(contents{get(handles.tracer,'Value')})
-    display(str2num(get(handles.bkgnd,'String')))
-if isempty(get(handles.bkgnd,'String'))
-gamma_bomb(get(handles.xls_ffile,'String'),get(handles.csv_dir,'String'),...
-    contents{get(handles.tracer,'Value')},get(handles.met_cor,'Value'),...
-    get(handles.dose_info_ffile, 'String'), format{get(handles.report_format, 'Value')},population_bool)
-else
-    display('Static Background Entered...')
-gamma_bomb(get(handles.xls_ffile,'String'),get(handles.csv_dir,'String'),...
-    contents{get(handles.tracer,'Value')},get(handles.met_cor,'Value'),...
-    get(handles.dose_info_ffile, 'String'), format{get(handles.report_format, 'Value')},population_bool,str2num(get(handles.bkgnd,'String')))    
-end
-otherwise
-end
-
-function bkgnd_Callback(hObject, eventdata, handles)
-% hObject    handle to bkgnd (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of bkgnd as text
-%        str2double(get(hObject,'String')) returns contents of bkgnd as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function bkgnd_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to bkgnd (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in met_cor.
-function met_cor_Callback(hObject, eventdata, handles)
-% hObject    handle to met_cor (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hint: get(hObject,'Value') returns toggle state of met_cor
-
-
-% --- Executes on button press in adj_csv.
-function adj_csv_Callback(~, eventdata, handles)
-% hObject    handle to adj_csv (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-time_inc_GUI
-
-
-% --- Executes on button press in dose_info.
-function dose_info_Callback(hObject, eventdata, handles)
-% hObject    handle to dose_info (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-[filename,filepath,~]=uigetfile(fullfile(pwd,'*.xls;*xlsx'),'Pick Dose Info File');
-cd(filepath)
-set(handles.dose_info_ffile,'String',fullfile(filepath,filename))
-guidata(hObject, handles);
-
-
-
-function dose_info_ffile_Callback(hObject, eventdata, handles)
-% hObject    handle to dose_info_ffile (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of dose_info_ffile as text
-%        str2double(get(hObject,'String')) returns contents of dose_info_ffile as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function dose_info_ffile_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to dose_info_ffile (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on selection change in report_format.
-function report_format_Callback(hObject, eventdata, handles)
-% hObject    handle to report_format (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: contents = cellstr(get(hObject,'String')) returns report_format contents as cell array
-%        contents{get(hObject,'Value')} returns selected item from report_format
-
-
-% --- Executes during object creation, after setting all properties.
-function report_format_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to report_format (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: popupmenu controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in pop_gen_button.
-function pop_gen_button_Callback(hObject, eventdata, handles)
-% hObject    handle to pop_gen_button (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-if (strcmp(get(handles.csv_dir,'String'),'Edit Text'))
-    warndlg('Please choose a CSV dir before continuing.', 'Must Select CSV Directory');
-else
-   pop_gen_gui();
-   %set(handles.pop_gen_button, 'Enable', 'off', 'String', 'Parent Fraction Ready!');
-end
-
-
-
-function ligand_Callback(hObject, eventdata, handles)
-% hObject    handle to ligand (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of ligand as text
-%        str2double(get(hObject,'String')) returns contents of ligand as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function ligand_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to ligand (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-    
-end
diff --git a/gamma_bomb_2/code/generate_head_curve.m b/gamma_bomb_2/code/generate_head_curve.m
deleted file mode 100644
index b662a5e..0000000
--- a/gamma_bomb_2/code/generate_head_curve.m
+++ /dev/null
@@ -1,56 +0,0 @@
-function [head_curve,head_curve_trues]=generate_head_curve(file,Series_Duration)
-
-acq_timing_error=0;
-
-head_curve_full = csvread(file, 1, 0);
-if head_curve_full(1,1)~=1000
-    warndlg(sprintf('Head curve file was found to start at a time~=1 sec. \n I''m going to attempt to fix this.'));
-    time_offset=head_curve_full(1,1);
-    head_curve_full(:,1)=head_curve_full(:,1)-head_curve_full(1,1)+1000;
-    acq_timing_error=1;
-end
-
-if nargin<2, Series_Duration(1,1:size(head_curve_full,1))=1;end
-
-head_curve_reduced=head_curve_full(:,1:2);
-head_curve_reduced(:,1)=floor(head_curve_reduced(:,1)/1000);
-
-% compute trues as ERS_prompts - ERS_delays
-head_curve_true_reduced=[head_curve_full(:,1) head_curve_full(:,10)-head_curve_full(:,11)];
-head_curve_true_reduced(head_curve_true_reduced<0)=NaN;
-
-head_curve_true_reduced(:,1)=floor(head_curve_true_reduced(:,1)/1000);
-head_curve=Series_Duration';
-head_curve_trues=Series_Duration';
-
-%%align Head Curve to Number Line
-for m=1:size(head_curve_reduced,1);
-    if head_curve_reduced(m,1)<size(head_curve,1) && (head_curve(head_curve_reduced(m,1),1)==1 || head_curve(head_curve_reduced(m,1),1)==0) ;
-        head_curve(head_curve_reduced(m,1),1)=head_curve_reduced(m,2).*head_curve(head_curve_reduced(m,1),1);
-    else
-    end
-end
-clear m
-
-%%align Treus to Number Line
-for m=1:size(head_curve_true_reduced,1);
-    if head_curve_true_reduced(m,1)<size(head_curve_trues,1) && (head_curve_trues(head_curve_true_reduced(m,1),1)==1 || head_curve_trues(head_curve_true_reduced(m,1),1)==0) ;
-        head_curve_trues(head_curve_true_reduced(m,1),1)=head_curve_true_reduced(m,2).*head_curve_trues(head_curve_true_reduced(m,1),1);
-    else
-    end
-end
-clear m
-
-%%Head Curve Correction for Error Flags
-if sum(head_curve_full(:,13))~=0
-    %fprintf('%d Error Flags Spotted in Head Curve...correcting.\n', max(head_curve_full(:,13)));
-    fprintf('%d Error Flags Spotted in Head Curve...correcting.\n', length(unique(head_curve_full(:,13)))-1);
-    head_curve_uncorr=head_curve;
-    error_index=find(head_curve==1);
-    for m=1:size(error_index,1)
-        head_curve(error_index(m,1),1)=head_curve(error_index(m,1)-1,1);
-    end
-    clear m
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/home_dir.m b/gamma_bomb_2/code/home_dir.m
deleted file mode 100644
index 558e439..0000000
--- a/gamma_bomb_2/code/home_dir.m
+++ /dev/null
@@ -1,23 +0,0 @@
-function homedir=home_dir(s_path)
-
-if nargin<1
-twig=strcat(pwd,'\');
-s_path=pwd;
-else
-    if ~strcmp(s_path(end),'\')
-    twig=strcat(s_path,'\');
-    else
-    twig=s_path;    
-    end
-end
-
-test=regexpi(twig,{'\\PET\\','\\MR_PET\\','\\MR\\','\\BLOOD\\'},'match');
-n=find([isempty(test{1}) isempty(test{2}) isempty(test{3}) isempty(test{4})]==0);
-if isempty(n)
-  homedir=strcat(s_path,'\'); %you're in the home dir.  
-else
-split_limb=regexpi(twig,['\' cell2mat(test{n}) '\'],'split');
-homedir=strcat(split_limb{1:end-1});
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/lin_3exp_model_aif.m b/gamma_bomb_2/code/lin_3exp_model_aif.m
deleted file mode 100644
index 7fae4be..0000000
--- a/gamma_bomb_2/code/lin_3exp_model_aif.m
+++ /dev/null
@@ -1,24 +0,0 @@
-function aif=lin_3exp_model_aif(A1,L1,A2,L2,A3,L3,C,ts,tp,t)
-%%Model of AIF bolus based on Feng et al. Int J Biomed Comput (1993)
-%   Y(t)=0,                                                    t<ts
-%   Y(t)=A1*(t-ts)                                             t>=ts & t<ts+tp
-%   Y(t)=(A1*tp-A2-A3)*exp(-L1*(t-tp))+A2*exp(-L2*(t-tp))+A3*exp(-L3*(t-tp))
-%
-%   [A1]=uCi/ml/sec
-%   [A2]=[A3]=uCi/ml
-%   [t]=sec
-%   [tau]=sec
-%   [L1]=[L1]=[L1]=1/sec
-
-aif=zeros(size(t));
-
-pre= t<ts;
-inc= t>=ts & t<ts+tp;
-post= t>=ts+tp;
-
-aif(pre)=0;
-aif(inc)=A1*(t(inc)-ts);
-aif(post)=(A1*(tp)+A2+A3-C)/3*exp(-L1*(t(post)-(ts+tp)))+(A1*(tp)-A2-C)/3*exp(-L2*(t(post)-(ts+tp)))+(A1*(tp)-A3-C)/3*exp(-L3*(t(post)-(ts+tp)))+C;
-
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/linear_2exp_model.m b/gamma_bomb_2/code/linear_2exp_model.m
deleted file mode 100644
index 3cbc980..0000000
--- a/gamma_bomb_2/code/linear_2exp_model.m
+++ /dev/null
@@ -1,15 +0,0 @@
-function aif=linear_2exp_model(A1,A2,A3,tau,lambda1,lambda2,t)
-%%
-%Y(t)=A1*t+A2                                    0<t<tau
-%Y(t)=(A1*tau+A2+A3)/2*exp(-lambda1*(t-tau))+(A1*tau+A2-A3)/2*exp(-lambda2*(t-tau)) ;            t<tau
-
-
-aif=zeros(size(t));
-
-pre= t<tau;
-post= t>=tau;
-
-aif(pre)=A1*t(pre)+A2;
-aif(post)=(A1*tau+A2+A3)/2*exp(-lambda1*(t(post)-tau))+(A1*tau+A2-A3)/2*exp(-lambda2*(t(post)-tau)) ;
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/make_histograms.m b/gamma_bomb_2/code/make_histograms.m
deleted file mode 100644
index 785b9f3..0000000
--- a/gamma_bomb_2/code/make_histograms.m
+++ /dev/null
@@ -1,92 +0,0 @@
-function make_histograms(times, kbq_ml_dkc_mx, t_codes)
-% Creates a 9-bar histogram for each time point in the parent fraction data
-% times = Titles (each histogram represents one time)
-% kbq_ml_dkc_mx = y-data
-% t_codes = matrix of data types (same dimensions as kbq_ml_dkc_mx) ('M =
-% Metabolite', 'P = Parent', etc...)
-
-% Get dimensions of input matrices
-[rows, cols] = size(t_codes);
-
-% Figure out how many subplots (num_graphs) will be needed and which row of
-% the kbq_ml_dkc matrix will be graphed as the first subplot (first)
-first = rows;
-num_graphs = 0;
-for r=1:rows
-    will_graph = false;
-    for c=1:cols
-        if strcmp(t_codes(r,c),'M') || strcmp(t_codes(r,c),'P')
-            if r < first
-                first = r-1;
-            end
-            will_graph = true;
-        end
-    end
-    if will_graph
-        num_graphs = num_graphs + 1;
-    end
-end
-
-% Plot the data
-for iter=1:2
-    figure;
-    hold on;
-    for r=1:rows
-        sub = false;
-        for c=1:cols
-            if strcmp(t_codes(r,c),'M') || strcmp(t_codes(r,c),'P')
-                sub = true;
-            end
-        end
-        if sub
-            subplot(1,num_graphs,r-first);
-            met = zeros(1,0);
-            parent = zeros(1,0);
-            num_m_bars = 0;
-            num_p_bars = 0;
-            for c=1:cols
-                if strcmp(t_codes(r,c),'M')
-                    met(end+1)=kbq_ml_dkc_mx(r,c);
-                    num_m_bars = num_m_bars + 1;
-                elseif strcmp(t_codes(r,c), 'P')
-                    parent(end+1)=kbq_ml_dkc_mx(r,c);
-                    num_p_bars = num_p_bars+1;
-                end
-            end
-            % Put the parent & met data into different columns to allow for
-            % different colors
-            data = zeros(num_m_bars+num_p_bars,2);
-            data(1:num_m_bars,1) = met';
-            data(num_m_bars+1:end,2) = parent';
-            h = bar(data,3);
-            set(h(1),'FaceColor','r');
-            set(h(2),'FaceColor',[.2, 0, 0.8]);
-            if iter == 1
-                ylim([0 1]);            
-                xlabel('Tube #');
-                ylabel('kBq/mL');
-            else
-                ylim('auto');
-                xlabel('Tube #');
-                ylabel('kBq/mL');
-            end
-            if (r-first == 1)
-                legend('Metabolite', 'Parent', 'Location', 'NorthWestOutside');
-            else
-                legend 'off';
-            end
-            title_str = [num2str(round(times(r-first)./60)) ' Min.'];
-            title(title_str, 'FontSize', 10, 'FontWeight', 'bold');
-
-            set(gca, 'FontSize', 7);
-        end
-    end
-
-% Save Histograms as a BMP image
-set(gcf, 'Position', [519 711 1250 270]);
-disp(iter)
-filename = ['histograms_' num2str(iter)];
-saveas(gcf, filename, 'bmp');
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/metcor_bld2.m b/gamma_bomb_2/code/metcor_bld2.m
deleted file mode 100644
index e2481b7..0000000
--- a/gamma_bomb_2/code/metcor_bld2.m
+++ /dev/null
@@ -1,99 +0,0 @@
-%% MODIFIED by Tom Morin (05/01/2015) from script by Daniel Chonde
-
-function type = metcor_bld2(blood_ffile,met_ffile,fit_source,batoffset,iteration,figrows,figcols)
-    % This creates the various metabolite correction bld files & BAT
-    % correction bld files.
-    % INPUT:
-    % - blood_ffile = File containing fitted TAC blood data (i.e plasma_art_Feng.bld)
-    % - met_ffile = File containing Parent Fraction data (i.e. parent_fraction_hill.bld)
-    % - fit_source = name of the Parent Fraction fit (i.e. hill, exp, etc.)
-    % - batoffset = Bolus Arrival Time offset in seconds (calculated previously)
-    % - Iteration, figrows, & figcols, were all used to organize the
-    % aesthetics of the subplots/figures.  These are no longer needed in
-    % the final report, so they are no longer produced.
-    % OUTPUT:
-    % - bld files for the met correction & BAT correction of each model fit
-    % - type = A name describing the model fit & its met correciton (i.e. Feng_Hill, L3Exp_Power, etc.)
-    
-    
-    % Read in data & create necessary matrices
-    raw_data=dlmread('plasma_art.bld','\t',1,0);
-    plasma_art=dlmread(blood_ffile,'\t',1,0);
-    parentfraction=dlmread(met_ffile,'\t',1,0);
-    
-    %This method for finding sigfigs doesn't work when the last value is a
-    %whole number
-%     teststr=num2str(plasma_art(find(plasma_art(:,2)>0,1,'last'),2));
-%     splits=regexp(teststr,'\.','split');
-%     sf=size(splits{2},2);
-    fid=fopen(blood_ffile,'r');
-    fgetl(fid);
-    teststr=fgetl(fid);
-    splits=regexp(teststr,'\.','split');
-    sf=length(splits{end});
-    fclose(fid);
-
-    if length(plasma_art(:,1))==length(parentfraction(:,1))
-        plasma_art_metcor(:,1)=plasma_art(:,1);
-        plasma_art_metcor(:,2)=plasma_art(:,2).*parentfraction(:,2);
-    else 
-        error('Dimensions do not match');
-    end
-    
-    % Set file name
-    name = regexprep(blood_ffile, '.bld', '_metcor');
-    name = strcat(name, '_', fit_source);
-    type = regexprep(name, 'plasma_art_', '');
-    type = regexprep(type, strcat('_metcor_', fit_source), '');
-    
-% * * The Plots generated below are no longer used in the final report. * *
-% =========================================================================
-%     % Plot some shit
-%     if iteration == 1
-%         figure
-%     end
-%     subplot(figrows.*2,figcols./2,((iteration.*2)-1));plot(plasma_art(:,1),plasma_art(:,2));hold on;
-%     plot(plasma_art_metcor(:,1),plasma_art_metcor(:,2),'r');
-%     %plot(raw_data(:,1),raw_data(:,2),'xk');
-%     set(gca,'XScale','log', 'FontSize', 7);
-%     
-%     ylabel('kBq/ml', 'FontSize', 7);
-%     if iteration == 1
-%         legend({'uncorrected','met corrected'}, 'Location', 'NorthEast', 'FontSize', 6, 'Orientation', 'vertical')
-%         title(strcat(type, ' Fits'), 'FontSize', 12, 'FontWeight', 'bold')
-%     else
-%         legend('off');
-%     end
-%     subplot(figrows.*2,figcols./2,(iteration.*2));plot(parentfraction(:,1),parentfraction(:,2), 'm')
-%     title(strcat(upper(fit_source), ' Fit Parent-Fraction'), 'FontSize', 9, 'FontWeight', 'bold');
-%     ylabel('Fraction', 'FontSize', 7);
-%     xlabel('Time (s)', 'FontSize', 7);
-%     set(gca, 'FontSize', 7);
-%     %hold off;
-%     
-%     set(gcf, 'Position', [50 50 750 800]);
-% =========================================================================
-% * * The Plots generated above are no longer used in the final report. * *
-
-    % Save JPG image of graph
-    % saveas(gcf,fullfile(pwd,strcat(name, '.bmp')));
-    % set(gca,'XScale','log');
-    
-    % Save BLD file with fit data
-    names=textread(blood_ffile,'%s',1,'delimiter','\n');
-    hdrnames=regexp(names,'\t','split');
-    print_list(hdrnames{:},plasma_art_metcor,strcat(name, '.bld'),sf);
-    
-    % Apply BAT Offset & Save BLD file
-    A=zeros(batoffset,2);
-    [len,~]=size(A);
-    for m=1:len-1
-        A(m,1) = m;
-    end
-    for m=1:length(plasma_art_metcor)
-        plasma_art_metcor(m,1) = plasma_art_metcor(m,1) + batoffset;
-    end
-    bat_cor = cat(1, A, plasma_art_metcor);
-    print_list(hdrnames{:},bat_cor,strcat(name, '_BATcor.bld'),sf);
-end
-
diff --git a/gamma_bomb_2/code/model_aif.m b/gamma_bomb_2/code/model_aif.m
deleted file mode 100644
index dcd02d1..0000000
--- a/gamma_bomb_2/code/model_aif.m
+++ /dev/null
@@ -1,20 +0,0 @@
-function mu=model_aif(a,b,c,b1,b2,t)
-%%Model of AIF bolus for extraction of bolus arrival time (BAT)
-%   MU=c,                   t<a
-%   MU=c+b1(t-a)            a<=t<=a+b
-%   MU=c+b1(b)+b2(t-b-a)    t>a+b
-%% at some point I need to come back to this and change the equation so b is the amount of time where the first line is used
-%since b must always be greater than a.  This can be enforced by writing
-%the equation such that a<=t<=a+b, or essentially replacing b by (b+a)
-
-mu=zeros(size(t));
-
-pre= a>=t;
-low_side= (a<t) & (t <= (a+b));
-high_side= ((a+b)<t);
-
-mu(pre)=c;
-mu(low_side)=(t(low_side)-a)*b1+c;
-mu(high_side)=(t(high_side)-b-a)*b2+c+b1*(b);
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/pf_fit.m b/gamma_bomb_2/code/pf_fit.m
deleted file mode 100644
index 088ef65..0000000
--- a/gamma_bomb_2/code/pf_fit.m
+++ /dev/null
@@ -1,144 +0,0 @@
-function [best_fit, GOF_TABLE, fits] = pf_fit(met_ffile,end_lin_time,extrap_time,sf)
-%% Written by Tom Morin
-% Fit Parent Fraction data according to four models: hill, lin2exp, exp, &
-% power
-
-% INPUT: 
-% met_ffile: a bld file containing parent fraction data
-% end_lin_time: the time where the curve switches from lin to exp in the
-%               lin2exp model
-% extrap_time: the end time for the data
-% sf: # significant figures to report in the output bld files
-% fit_type: the type of model used to fit the PF data
-
-% OUTPUT:
-% - 4 plots for containing the four separate fits
-% - 4 bld files with fit data
-% - A table summarizing the goodness of fit
-
-%% DEFINED CONSTANTS
-std_cutoff = 1.5; % Outliers are classified as any point outside of std_cutoff standard deviations from the fit
-
-%% Read in the data file & create x,y matrix of data (time = x, met = y)
-A=dlmread(met_ffile,'\t',1,0);
-if nargin<2 || isempty(end_lin_time)
-    end_lin_time=A(2,1); % This is the time at which the curve will switch from linear to expontential
-end
-
-if nargin<4 %Figure out how many decimal places are used
-    teststr=num2str(A(2,2));
-    splits=regexp(teststr,'\.','split');
-    sf=size(splits{2},2);
-end
-names=textread(met_ffile,'%s',1,'delimiter','\n');
-hdrnames=regexp(names,'\t','split');
-
-time=A(:,1);met=A(:,2);
-
-if nargin<3 || isempty(extrap_time)
-extrap_time=time(end);
-end
-
-%% Plot the Data, Fit the Curve, Denote GOF, & Save Output BLD file
-figure('Name', 'Parent Fraction Fits');
-fits = {'hill'; 'lin2exp'; 'exp'; 'power'};
-for m=1:size(fits)
-    fit_type = fits{m};
-    % Set options depending on fit_type
-    switch fit_type
-        case 'hill'
-            final_read = A(end, 2);
-            c = 1 - final_read;
-            equation = strcat('1 - ((', num2str(c), '*(x^a))/(b+(x^a)))');
-            ffun = fittype(equation);
-            
-            options = fitoptions( ffun );
-            options.Display = 'Off';
-            options.Lower = [1 0];
-            options.StartPoint = [0.64306354724818 0.506030011368413];
-            iter = 1;
-        case 'lin2exp'
-            %Y(t)=A1*t+A2                                    0<t<tau
-            %Y(t)=(A1*tau+A2+A3)/2*exp(-lambda1*(t-tau))+(A1*tau+A2-A3)/2*exp(-lambda2*(t-tau)) ;            t<tau
-            ffun=fittype(['linear_2exp_model(A1,1,A3,' num2str(end_lin_time) ',lambda1,lambda2,x)']);
-            
-            options=fitoptions(ffun);
-            options.StartPoint=[(0.5486-1)/589 0 0.007367 0.0003396];
-            options.MaxIter=1000;
-            options.MaxFunEvals=1000;
-            options.Lower=[-Inf 0 0 0];
-            options.Upper=[0 Inf Inf Inf];
-            iter = 2;
-        case 'exp'
-            equation = '(a.*exp(b.*x))+((1-a).*exp(d.*x))';
-            ffun = fittype(equation);
-            
-            options = fitoptions( ffun );
-            options.Display = 'Off';
-            options.Lower = [0 -Inf -Inf];
-            options.StartPoint = [0 0 0];
-            options.Upper = [Inf Inf Inf];
-            iter = 3;
-        case 'power'
-            ffun = fittype( '1./((1+(a.*(x.^b))).^c)' );
-            options = fitoptions( ffun );
-            options.Display = 'Off';
-            options.Lower = [0 0 0];
-            options.StartPoint = [0.228976968716819 0.91333736150167 0.152378018969223];
-            options.Upper = [Inf Inf Inf];
-            iter = 4;
-    end
-    
-    % Fit the data
-    [fit1,gof1]=fit(time,met,ffun,options);
-    
-    % Adjust for Outliers (data outside 1.5 stdevs of the fitted curve)
-    fdata = feval(fit1,time);
-    I = abs(fdata - met) > std_cutoff*std(met);
-    outliers = excludedata(time,met,'indices',I);
-    options.Exclude=outliers;
-    [fit2,gof2] = fit(time,met,ffun,options);
-    
-    % Plot the data
-    subplot(2,2,iter);
-    if sum(outliers) > 0
-        plot(fit2,'r-', time, met, '.b',outliers,'r*');
-    else
-        plot(fit2, 'r-', time, met, '.b');
-    end
-    hold on;
-    %plot(fit1, 'b:');  % This is the original fit, before outliers deleted
-    
-    % Set up Legend
-    if iter == 1 && sum(outliers) > 0
-        legend('Data', 'Oultiers', 'Fit', 'Location', 'NorthEast' );
-    elseif iter == 1
-        legend('Data', 'Fit', 'Location', 'NorthEast');
-    else
-        legend 'off';
-    end
-    
-    % Label axes
-    xlabel('Time (s)', 'FontSize', 7);
-    ylabel('Parent Fraction', 'FontSize', 7');
-    set(gca, 'FontSize', 7);
-    title([upper(fit_type) ' Fit of Parent Fraction'], 'FontSize', 10, 'FontWeight', 'bold');
-    
-    % Denote Goodness of Fit Data
-    GOF_TABLE(iter,1) = gof2.rsquare;
-    GOF_TABLE(iter,2) = gof2.adjrsquare;
-    GOF_TABLE(iter,3) = gof2.dfe;
-    
-    % Determine Best Fit & Pass it back for met correction
-    if iter == 1
-        best_fit = fit2;
-    elseif abs(GOF_TABLE(iter,1)-1) < abs(GOF_TABLE(iter-1,1)-1)
-        best_fit = fit2;
-    end
-    
-    % Save the fitted data to a bld file
-    fmet=fit2(time(1):extrap_time);
-    [metpath,metname,metext]=fileparts(met_ffile);
-    print_list(hdrnames{:},[[time(1):extrap_time]', fmet],fullfile(metpath,strcat(metname,'_',fit_type,metext)),sf);
-end
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/pop_gen_gui.fig b/gamma_bomb_2/code/pop_gen_gui.fig
deleted file mode 100644
index c6494d6..0000000
Binary files a/gamma_bomb_2/code/pop_gen_gui.fig and /dev/null differ
diff --git a/gamma_bomb_2/code/pop_gen_gui.m b/gamma_bomb_2/code/pop_gen_gui.m
deleted file mode 100644
index 66b60fd..0000000
--- a/gamma_bomb_2/code/pop_gen_gui.m
+++ /dev/null
@@ -1,341 +0,0 @@
-function varargout = pop_gen_gui(varargin)
-% POP_GEN_GUI MATLAB code for pop_gen_gui.fig
-%      POP_GEN_GUI, by itself, creates a new POP_GEN_GUI or raises the existing
-%      singleton*.
-%
-%      H = POP_GEN_GUI returns the handle to a new POP_GEN_GUI or the handle to
-%      the existing singleton*.
-%
-%      POP_GEN_GUI('CALLBACK',hObject,eventData,handles,...) calls the local
-%      function named CALLBACK in POP_GEN_GUI.M with the given input arguments.
-%
-%      POP_GEN_GUI('Property','Value',...) creates a new POP_GEN_GUI or raises the
-%      existing singleton*.  Starting from the left, property value pairs are
-%      applied to the GUI before pop_gen_gui_OpeningFcn gets called.  An
-%      unrecognized property name or invalid value makes property application
-%      stop.  All inputs are passed to pop_gen_gui_OpeningFcn via varargin.
-%
-%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
-%      instance to run (singleton)".
-%
-% See also: GUIDE, GUIDATA, GUIHANDLES
-
-% Edit the above text to modify the response to help pop_gen_gui
-
-% Last Modified by GUIDE v2.5 29-May-2015 14:33:13
-
-% Begin initialization code - DO NOT EDIT
-gui_Singleton = 1;
-gui_State = struct('gui_Name',       mfilename, ...
-                   'gui_Singleton',  gui_Singleton, ...
-                   'gui_OpeningFcn', @pop_gen_gui_OpeningFcn, ...
-                   'gui_OutputFcn',  @pop_gen_gui_OutputFcn, ...
-                   'gui_LayoutFcn',  [] , ...
-                   'gui_Callback',   []);
-if nargin && ischar(varargin{1})
-    gui_State.gui_Callback = str2func(varargin{1});
-end
-
-if nargout
-    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
-else
-    gui_mainfcn(gui_State, varargin{:});
-end
-% End initialization code - DO NOT EDIT
-
-
-% --- Executes just before pop_gen_gui is made visible.
-function pop_gen_gui_OpeningFcn(hObject, eventdata, handles, varargin)
-% This function has no output args, see OutputFcn.
-% hObject    handle to figure
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-% varargin   command line arguments to pop_gen_gui (see VARARGIN)
-
-% Choose default command line output for pop_gen_gui
-handles.output = hObject;
-
-% Update handles structure
-guidata(hObject, handles);
-
-h = findobj('Tag', 'gamma_gui');
-gamma_bomb_data = guidata(h);
-directory = get(gamma_bomb_data.csv_dir, 'String');
-set(handles.place,'String', directory);
-% UIWAIT makes pop_gen_gui wait for user response (see UIRESUME)
-% uiwait(handles.population_generation);
-
-
-% --- Outputs from this function are returned to the command line.
-function varargout = pop_gen_gui_OutputFcn(hObject, eventdata, handles) 
-% varargout  cell array for returning output args (see VARARGOUT);
-% hObject    handle to figure
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Get default command line output from handles structure
-varargout{1} = handles.output;
-
-
-
-% --- Executes during object creation, after setting all properties.
-function listbox1_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to listbox1 (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: listbox controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on selection change in popupmenu1.
-function popupmenu1_Callback(hObject, eventdata, handles)
-% hObject    handle to popupmenu1 (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: contents = cellstr(get(hObject,'String')) returns popupmenu1 contents as cell array
-%        contents{get(hObject,'Value')} returns selected item from popupmenu1
-
-
-% --- Executes during object creation, after setting all properties.
-function popupmenu1_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to popupmenu1 (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: popupmenu controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on selection change in list.
-function list_Callback(hObject, eventdata, handles)
-% hObject    handle to list (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: contents = cellstr(get(hObject,'String')) returns list contents as cell array
-%        contents{get(hObject,'Value')} returns selected item from list
-
-
-% --- Executes during object creation, after setting all properties.
-function list_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to list (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: listbox controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in browse.
-function browse_Callback(hObject, eventdata, handles)
-% hObject    handle to browse (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-[filename,filepath,~]=uigetfile(fullfile(pwd,'*.bld'),'Pick Data File');
-cd(filepath)
-set(handles.cur_file,'String',fullfile(filepath,filename))
-guidata(hObject, handles);
-
-
-% --- Executes on button press in add.
-function add_Callback(hObject, eventdata, handles)
-% hObject    handle to add (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Add a selected file to the population list
-entries = get(handles.list,'String');
-value = get(handles.list,'Value');
-newEntryName  = { get(handles.cur_file,'String') };
-
-if ~strcmp(newEntryName,'Filename')
-    on_list = false;
-    for m=1:length(entries)
-        if strcmp(entries(m),newEntryName)
-            on_list = true;
-        end
-    end
-    if ~on_list
-        if value > 0 && strcmp(entries(1,:),'List of bld Data Files')
-            entries = newEntryName;
-            value = 1;
-        else
-            entries = [entries; newEntryName];
-            value = value+1;
-        end
-        if value > 0
-            set(handles.remove, 'Enable', 'on');
-        end
-        set(handles.list,'String',entries,'Value',value);
-    else
-        warndlg('This file has already been added to the list.');
-    end
-end
-
-
-% --- Executes on button press in remove.
-function remove_Callback(hObject, eventdata, handles)
-% hObject    handle to remove (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Remove a selected file from the population list
-entries = get(handles.list, 'String');
-value = get(handles.list, 'Value');
-
-entries(value) = [];
-nentries = length(entries);
-
-if value > nentries
-    value = value-1;
-end
-
-set(handles.list,'Value',value,'String',entries)
-
-if nentries == 0
-    set(handles.remove,'Enable','off')
-end
-
-
-function cur_file_Callback(hObject, eventdata, handles)
-% hObject    handle to cur_file (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of cur_file as text
-%        str2double(get(hObject,'String')) returns contents of cur_file as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function cur_file_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to cur_file (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in analyze.
-function analyze_Callback(hObject, eventdata, handles)
-% hObject    handle to analyze (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Produce Parent Fraction Data from the selected population and continue on
-% to analyze the rest of the data (returns to Gamma_Bomb_GUI
-complete = false;
-if strcmp(get(handles.list,'String'),'List of bld Data Files')
-    warndlg('Please add at least one bld file to the list of data files.', 'File List Empty');
-else
-complete = pop_parent_fraction(get(handles.list,'String'), get(handles.place,'String'));
-end
-if complete
-    h = findobj('Tag', 'gamma_gui');
-    gamma_bomb_data = guidata(h);
-    set(gamma_bomb_data.pop_gen_button, 'Enable', 'off', 'String', 'Parent Fraction Ready!');
-    close(pop_gen_gui);
-    return;
-end
-
-
-
-function place_Callback(hObject, eventdata, handles)
-% hObject    handle to place (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Hints: get(hObject,'String') returns contents of place as text
-%        str2double(get(hObject,'String')) returns contents of place as a double
-
-
-% --- Executes during object creation, after setting all properties.
-function place_CreateFcn(hObject, eventdata, handles)
-% hObject    handle to place (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    empty - handles not created until after all CreateFcns called
-
-% Hint: edit controls usually have a white background on Windows.
-%       See ISPC and COMPUTER.
-if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
-    set(hObject,'BackgroundColor','white');
-end
-
-
-% --- Executes on button press in open_pop.
-function open_pop_Callback(hObject, eventdata, handles)
-% hObject    handle to open_pop (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-
-% Read in the imported population
-entries = get(handles.list, 'String');
-value = get(handles.list, 'Value');
-[list_len,~] = size(entries);
-[filename,filepath,~]=uigetfile(fullfile(pwd,'*.bld'),'Import Existing Population');
-fID = fopen(fullfile(filepath,filename),'r');
-list = textscan(fID,'%s\n');
-fclose(fID);
-new_entries = list{1};
-
-% Account for Empty List
-if list_len == 0 || (list_len == 1 && strcmp(entries(1,:),'List of bld Data Files'))
-    for m=1:size(new_entries)
-        if m == 1
-            entries = [new_entries{m}];
-        else
-            entries = [entries; new_entries{m}];
-        end
-    end
-    value = length(new_entries);
-% Ensure that duplicate data files are not added
-else
-    for m=1:size(new_entries)
-        on_list = false;
-        for n=1:size(entries)
-            if strcmp(entries(n,:),new_entries{m})
-                on_list = true;
-            end
-        end
-        if ~on_list
-            entries = [entries; new_entries{m}];
-            value = value+1;
-        end
-    end
-end
-
-set(handles.list,'String',entries,'Value',value);
-
-
-
-% --- Executes on button press in save_pop.
-function save_pop_Callback(hObject, eventdata, handles)
-% hObject    handle to save_pop (see GCBO)
-% eventdata  reserved - to be defined in a future version of MATLAB
-% handles    structure with handles and user data (see GUIDATA)
-%
-% Save the current list of files to be used again later (bld file)
-value = get(handles.list, 'Value');
-entries = get(handles.list, 'String');
-if value < 2
-    warndlg('Cannot save populations with fewer than 2 data files.  Please add more data files to the list.', 'Populatin Too Small');
-else
-    [filename,filepath] = uiputfile('population.bld', 'Save Population As');
-    fID = fopen(fullfile(filepath,filename),'w');
-    fprintf(fID,'%s\n',entries{:});
-    fclose(fID);
-end
diff --git a/gamma_bomb_2/code/pop_parent_fraction.m b/gamma_bomb_2/code/pop_parent_fraction.m
deleted file mode 100644
index 78009d8..0000000
--- a/gamma_bomb_2/code/pop_parent_fraction.m
+++ /dev/null
@@ -1,52 +0,0 @@
-% Created by: Tom Morin
-% Date: 5/28/15
-
-function complete = pop_parent_fraction(files, directory)
-% Generate a parent fraction curve from data from a population of several 
-% participants
-% INPUT: files = bld files containing parent fraction data points
-
-% Read in data files, create matrices, and plot all matrices on one graph
-complete = false;
-cat_data = zeros(0,2);
-[num_files,~] = size(files);
-figure
-for m=1:num_files
-    disp(files{m});
-    A = dlmread(files{m}, '\t', 1, 0);
-    cat_data = cat(1, cat_data, A);
-    hold on;
-    %plot(A(:,1),A(:,2),'*r');    
-end
-title('Parent Fraction from Population Data','FontSize', 10,'FontWeight', 'bold');
-xlabel('Time (s)', 'FontSize', 7);
-ylabel('Parent Fraction', 'FontSize', 7);
-cat_data = sortrows(cat_data);
-
-pop_pf_mx = handle_repeated_data(cat_data);
-plot(pop_pf_mx(:,1),pop_pf_mx(:,2),'*b');
-
-% Write final Parent Fraction data file to csv_dir from gamma bomb gui
-print_list({'sample-time[seconds]';'parent-fraction[1/1]'}, pop_pf_mx, fullfile(directory,'parentfraction.bld'),4);
-complete = true;
-end
-
-
-function pop_pf_mx = handle_repeated_data(cat_data)
-% Prepare the data points for curve fitting by ensuring that the data is a
-% one-to-one function (one y-value for each x-value)
-% If there are multiple y-values for one x-value, average them together
-
-pop_pf_mx(1,:) = cat_data(1,:);
-num_repeats = 0;
-for m=2:length(cat_data)-1
-    if pop_pf_mx(end,1) ~= cat_data(m,1)
-        num_repeats = 0;
-        pop_pf_mx(end+1,:) = cat_data(m,:);
-    else
-        num_repeats = num_repeats + 1;
-        pop_pf_mx(end,2) = (pop_pf_mx(end,2).*num_repeats) + cat_data(m,2);
-        pop_pf_mx(end,2) = pop_pf_mx(end,2) ./ (num_repeats+1);
-    end
-end
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/print_list.m b/gamma_bomb_2/code/print_list.m
deleted file mode 100644
index 5f980d4..0000000
--- a/gamma_bomb_2/code/print_list.m
+++ /dev/null
@@ -1,55 +0,0 @@
-function print_list(hdr,M,ffile,sf)
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-%% SCRIPT TO PRINT PMOD READABLE TEXT-FILES 
-%% Written by Daniel Chonde
-%% Req: dynamic pet data (*.i files)
-%% Output: Patlak i file (brain.i)
-%% Written: 03/16/2012 Updated:
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% This script prints out data to a pmod readable tab delimited file.  It is
-% called by gammareader, the function used to automatically convert blood
-% data to single files.
-% hdr = the headings on the final output file
-% M = a matrix of data
-% ffile = the desired name of the output file
-% sf = the desired significant figures for data in output file
-%
-% example:
-% print_list({'sample-time[seconds]';plasma[kBq/cc]},data,'sampledata.bld')
-%
-%
-
-%% Set output number format
-if nargin<4, sf=1;end
-pformat=['%.' num2str(sf) 'f'];
-
-%% Load Row Data
-if iscolumn(hdr),hdr=hdr';end
-if size(M,2)~=size(hdr,2), error('data and data header are different lengths.');end
-
-%% Sort rows to make sure they are in ascending order
-M=sortrows(M,1);
-
-%% Write Format Strings
-hdr_str='';
-mat_str='';
-for m=1:size(hdr,2)
-hdr_str=[hdr_str '%s'];
-mat_str=[mat_str pformat];
-if m~=size(hdr,2), 
-    hdr_str=[hdr_str '\t'];
-    mat_str=[mat_str '\t'];
-else
-    hdr_str=[hdr_str '\n'];
-    mat_str=[mat_str '\n'];
-end
-end
-
-%% Print Data to file
-fid=fopen(ffile,'w');
-fprintf(fid,hdr_str,hdr{:});
-fprintf(fid,mat_str,M');
-fclose(fid);
-
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/code/read_i_hdr.m b/gamma_bomb_2/code/read_i_hdr.m
deleted file mode 100644
index c474ce2..0000000
--- a/gamma_bomb_2/code/read_i_hdr.m
+++ /dev/null
@@ -1,51 +0,0 @@
-function V=read_i_hdr(fullf)
-
-
-if nargin<1
-[file,path,~]=uigetfile('*.i.hdr', 'Pick one of the DICOM files');
-fullf=fullfile(path,file);
-end
-
-[path,filename,ext]=fileparts(fullf);
-switch ext
-    case '.i'
-file=strcat(filename,ext,'.hdr');
-    case '.hdr'
-file=strcat(filename,ext);
-%     case ''
-% file=strcat(filename,'i.hdr');
-    otherwise
-error('File does not have .i or .i.hdr')        
-end
-if isempty(path)
-    path=pwd;
-end
-
-fid = fopen(fullfile(path,file), 'r'); %Open file for reading
-m=1;
-while 1
-tline=fgetl(fid);
-if tline==-1;break;end
-oldhdr{m,1} = tline;
-clear tline
-m=m+1;
-end
-fclose(fid);
-clear m
-
-V=struct;
-spoldhdr=cell(1);
-for m=1:size(oldhdr,1)
-    if size(regexp(oldhdr{m},':=','split'),2)>size(spoldhdr,2); spoldhdr{:,end+1}='';end
-    spoldhdr(m,:)=regexp(oldhdr{m},':=','split');
-    spoldhdr{m,1}=strtrim(regexprep(spoldhdr{m,1},'(\<[a-z])','${upper($1)}'));
-    spoldhdr{m,1}=regexprep(spoldhdr{m,1},' ','');
-    spoldhdr{m,1}=regexprep(spoldhdr{m,1},'[\!,[,],/,(,),\%,:]','');
-end
-clear m
-
-for m=1:size(spoldhdr,1)
-    V.(spoldhdr{m,1})=strtrim(spoldhdr{m,2});
-end
-
-end
\ No newline at end of file
diff --git a/gamma_bomb_2/final_report.pdf b/gamma_bomb_2/final_report.pdf
deleted file mode 100644
index f54d9e1..0000000
Binary files a/gamma_bomb_2/final_report.pdf and /dev/null differ