This is the entire code if that provides any more help..
clear
clc
% first we load the file of interest
% contains 496-12 columns ( 484)
% directory where the data is
main_dir = '/Users/alexisekim/Desktop/Terry_Stuff/Luo_Research/Cloud_Data/';
seadays = [20130812, 20130821, 20130823, 20130902, 20130904, 20130911, 20130918];
% start and end utc time (seconds) for area of interest for each day in
% order
% NonConvective Hours
utcStarts = [48009, 52467, 54128, 54591, 45001, 55587, 56714];
utcEnds = [66799, 61999, 59999, 57999, 45002, 74999, 61499];
%NonConvective Hours
utcStarts = [730001, 72001, 74001, 80001, 45003, 82001, 68001];
utcEnds = [77659, 80271, 80894, 86181, 74428, 87252, 78116];
%preloading a really large array to store data
bigDATA = nan(16, 100000);
bigGPS = bigDATA;
bigDATAstart = 1;
bigGPSstart = 1;
for jj = 1:7 % each day...
if jj== 5 % not interested in this day anymore
continue
end
disp(jj)
filename = [main_dir, 'SEAC4RS-mrg01-dc8_merge_', num2str(seadays(jj)), '_R3.ict'];
delimiterIn = ',';
headerlinesIn = 526;
data = importdata(filename,delimiterIn, headerlinesIn);
utcTime = data.data(:,1);
zGPS = data.data(:,8);
%%the value of ii will be the corresponding column number of the var of interest
%aerosol ext (dry)... OA... SO4... NO3... NH4... aerosol volume... etc
% making the values less than 0 be NaN
zGPS(zGPS<0) = NaN;
goodPoints = find((utcTime >= utcStarts(jj)) &( utcTime <utcEnds(jj)));
meaning_of_var = {'Aerosol Extinction (dry)', 'OA(ug/m^3)', 'SO4 (ug/m^3)', 'NO3 (ug/m^3) ', 'NH4 (ug/m^3)', ...
'Aerosol Volume', 'CO', 'Isoprene (ppbv)', 'RH', 'Black Carbon Mass (nm)', ...
'SO2', 'CO2', 'CH2O (ppbv)', 'O3', 'lat', 'lon', 'Sample Volume (L)', 'Particle Conc. (#/L)', 'Total Count(#)', ...
'Water Soluble Organic Carbon (ugC/m^3)'};
%these are the column numbers for the corresponding variables above
ii_array = [198 139 81 80 84 238 63 353 43 159 92 62 66 73 6 7 238 239 246 156];
for ii = 1:length(ii_array)
a = data.data(:,ii_array(ii));
a (a<0) = NaN;
bigDATA(ii, bigDATAstart:(bigDATAstart - 1 +length(goodPoints))) = a(goodPoints);
bigGPS(ii, bigGPSstart:(bigGPSstart - 1 +length(goodPoints))) = zGPS(goodPoints);
% this section will plot the figures for the individual days
% figure
%
%
% boxplot(a(goodPoints), ceil(zGPS(goodPoints)), 'orientation', 'horizontal')
% ylabel('Altitude (km)')
% xlabel(meaning_of_var(ii))
% title(meaning_of_var(ii))
%
end %ii
bigDATAstart = bigDATAstart + length(goodPoints);
bigGPSstart = bigGPSstart + length(goodPoints);
end %%jj
% adjusting the final size of the really large array to what it actually is
finalDATA = bigDATA(:,1:bigDATAstart-1);
finalGPS = bigGPS(:, 1:bigGPSstart-1);
%%--------------------------------------------------------------------
% This section plots cumulatively all of the data collected for all the
% days sampled.
%%--------------------------------------------------------------------
% kk = is the 'meaning of var' in increasing order
for kk = 1:length(ii_array)
%these variables were skipped and not plotted (RH, CO2, Lat, Lon)
if( (kk ==9)|| (kk==12) || (kk==15) || (kk==16) )
continue
end
boxplot(finalDATA(kk,:), ceil(finalGPS(kk,:)), 'orientation', 'horizontal')
%adjustments that to remove noisey plots
if kk == 1
axis ([0 300 0 14])
elseif kk == 2
axis ([0 25 0 14])
elseif kk == 4
axis([0 1 0 14])
elseif kk == 7
axis ([0 250 0 14])
elseif kk == 8
axis([0 5 0 14])
end
ylabel('Altitude (km)')
xlabel(meaning_of_var(kk))
title(meaning_of_var(kk))
%file name will be uniquely named based off kk which has a meaning
%(see meaning of var for the meaning of each)
fileName = ['sample_ALL_',num2str(kk),'.jpeg'];
print ('-djpeg99', fileName)
close
%
end %%kk