Filter data by flag columns

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Below I have some code which uses a for loop to call in each day of data from some radiometry data and processes it sequentially. Now I need to add some line of code so that I can apply the flags that are in the tables. I have attached an example day of data (labeled "Lw.mat", hopefully you're able to open it). At each time point there are two rows of data, this is because there were two instruments measuring, I need to at each time point pick one of these rows to use and omit the other based on the"flag" columns. I want to first apply the "flag light availability" and "flag light quality" so that only rows which pass both of these (has a 1 in both of these columns) are included. Then I want to use the "flag sunglint (Lw)" and "flag sunglint (Rrs)" columns so that if one row shows a 0 in either flag column then it should be excluded and the row with a 1 in at least one flag column should be used, if both rows have 1's in both flag columns then the row with the lowest value in column 13 should be used. If both rows show all 0s then both rows should be excluded.
Basically I'm very lost on how to do this so any help or guidence would be appreciated, I've looked at how to apply conditioning language and if it was just one condition I would probably be alright but trying to apply so many loses me and especially how to relate it to the pair of rows at each time point.
% Specify the folder where the files live.
myFolder = 'C:\Users\tbrob\MATLAB Drive\SO298-MATLAB\MATLAB\Lw';
% Check to make sure that folder actually exists. Warn user if it doesn't.
if ~isfolder(myFolder)
errorMessage = sprintf('Error: The following folder does not exist:\n%s', myFolder);
uiwait(warndlg(errorMessage));
return;
end
% Get a list of all files in the folder with the desired file name pattern.
filePattern = fullfile(myFolder, '*Lw.dat'); % The folder has 3 different file types; we only want the Es data from each day.
theFiles = dir(filePattern);
% Plotting setup
figure; % Create a new figure
subplot(2,1,1);
hold on; % Enable hold to overlay plots
subplot(2,1,2);
hold on; % Enable hold to overlay plots
% Process each file and plot the data
for k = 1 : length(theFiles)
baseFileName = theFiles(k).name;
fullFileName = fullfile(myFolder, baseFileName);
fprintf(1, 'Now reading %s\n', fullFileName);
% Read the data file
dataArray = readtable(fullFileName);
dataArray = table2array(dataArray);
%add code which at each timepoint, pics the first or second row based
%on if it passes first the sunlight flags and then the sunglint flags
% Extract relevant data for plotting
x = 320:2:950;
y = dataArray(2:end, 13:328);
L = y(1:2:end, :);
R = y(2:2:end, :);
% Plot the data
subplot(2, 1, 1);
plot(x, L);
subplot(2, 1, 2);
plot(x, R);
end

采纳的回答

Mathieu NOE
Mathieu NOE 2023-7-17
hello
this is my first attempt , I hope I didn't make any mistake in your requirements interpretation
still there is one case which is maybe not exactly treated as you wish : what are we suppose to do if we have for example one flag ("flag sunglint (Lw)") which has one 1 and the other flag ("flag sunglint (Rrs)") has two 1's ? for the time being my code keep both rows as valid . Only if both rows has both falgs having two 1's we do the min value search in the 13th column
this maybe needs a further improvement of the code
dataArray = Lw;
dataArray = table2array(dataArray);
%add code which at each timepoint, pics the first or second row based
%on if it passes first the sunlight flags and then the sunglint flags
[m,n] = size(dataArray);
out = []; % init
for k = 1:floor(m/2) % loop over 2 lines (rows) of data
r = (1:2)+(k-1)*2; % current 2 rows index
array = dataArray(r,:);
% I need to at each time point pick one of these rows to use and omit the other based on the"flag" columns.
% I want to first apply the "flag light availability" (C7) and "flag
% light quality" (C8) so that only rows which pass both of these (has a 1 in both of these columns)
% are included.
flag_light_availability = array(:,7); % 7th column
flag_light_quality = array(:,8); % 8th column
ind_rows1 = (flag_light_availability>0) & (flag_light_quality>0); % NB I prefer >0 instead of == 1 , it's more robust to round off / precision error
% keep the valid rows
array = array(ind_rows1,:);
% Then I want to use the "flag sunglint (Lw)" (C10) and "flag sunglint (Rrs)" (C11) columns
% the row with a 1 in at least one flag column should be used, if both rows have 1's in both flag columns
% then the row with the lowest value in column 13 should be used.
% If both rows show all 0s then both rows should be excluded.
flag_sunglint_Lw = array(:,10); % 10th column
flag_sunglint_Rrs = array(:,11); % 11th column
ind_rows2 = (flag_sunglint_Lw>0);
ind_rows3 = (flag_sunglint_Rrs>0);
% find if both rows have 1's in both flag columns
ind_rows_common = ind_rows2 & ind_rows3;
if all(ind_rows_common) % case 1 : both rows have 1's in both flag columns
% get corresponding values of column13
C13_data = array(ind_rows_common,13); % 13th column
% find which row has the lowest value in 13th col
[val,ind] = min(C13_data);
array = array(ind,:);
else % case 1 : we have only one flag == 1 => simply keep the data where one flag is == 1 (logical OR)
array = array(ind_rows2>0 | ind_rows3>0 ,:);
end
l(k) = size(array,1); % for debug only (shows how many of the 2 initial rows have been finally stored in the output)
out = [out; array]; % concat all valid data
end
% % Extract relevant data for plotting
% x = 320:2:950;
% y = dataArray(2:end, 13:328);
% L = y(1:2:end, :);
% R = y(2:2:end, :);
%
% % Plot the data
% subplot(2, 1, 1);
% plot(x, L);
% subplot(2, 1, 2);
% plot(x, R);
  2 个评论
Brandy
Brandy 2023-7-18
Hey thanks so much for the detailed explanation of how your code works, it really helps me to learn what is happening and how to apply it. For the case you talked about in which one row has Lw and Rrs flag =1 and the second row has flags = 0 and 1, I would like to select only the row with 1's.
I know it should be under that else statement and the else satement is saying if either flag =1 keep the row, but I'm not sure how to add if either flag=0 get rid of the row. Could I put something like
array(ind_rows2==0 | ind_rows3==0 ,:)=[];
Mathieu NOE
Mathieu NOE 2023-7-19
hello again
1) in fact I noticed that the code works fine too for this case as it will select the row whera we have a common 1's (case 2)
so for example (1 0) & (1 0) = (1 0) and we pick first row ,
same for (1 1) & (1 0) = (1 0)
or (1 0) & (1 1) = (1 0)
2) for the case "either flag=0 get rid of the row" there is nothing to do
my logic is to extract from the original array (dataArray) the valid data and store (concatenate) in array out
I am not deleting / removing rows in the original array (left untouched as you can check after running the code)
below I simply added a few more comments for case 2 so we keep track of that info, the code itself is the same as before :
dataArray = Lw;
dataArray = table2array(dataArray);
%add code which at each timepoint, pics the first or second row based
%on if it passes first the sunlight flags and then the sunglint flags
[m,n] = size(dataArray);
out = []; % init
for k = 1:floor(m/2) % loop over 2 lines (rows) of data
r = (1:2)+(k-1)*2; % current 2 rows index
array = dataArray(r,:);
% I need to at each time point pick one of these rows to use and omit the other based on the"flag" columns.
% I want to first apply the "flag light availability" (C7) and "flag
% light quality" (C8) so that only rows which pass both of these (has a 1 in both of these columns)
% are included.
flag_light_availability = array(:,7); % 7th column
flag_light_quality = array(:,8); % 8th column
ind_rows1 = (flag_light_availability>0) & (flag_light_quality>0); % NB I prefer >0 instead of == 1 , it's more robust to round off / precision error
% keep the valid rows
array = array(ind_rows1,:);
% Then I want to use the "flag sunglint (Lw)" (C10) and "flag sunglint (Rrs)" (C11) columns
% the row with a 1 in at least one flag column should be used, if both rows have 1's in both flag columns
% then the row with the lowest value in column 13 should be used.
% If both rows show all 0s then both rows should be excluded.
flag_sunglint_Lw = array(:,10); % 10th column
flag_sunglint_Rrs = array(:,11); % 11th column
ind_rows2 = (flag_sunglint_Lw>0);
ind_rows3 = (flag_sunglint_Rrs>0);
% find if both rows have 1's in both flag columns
ind_rows_common = ind_rows2 & ind_rows3;
if all(ind_rows_common) % case 1 : both rows have 1's in both flag columns
% get corresponding values of column13
C13_data = array(ind_rows_common,13); % 13th column
% find which row has the lowest value in 13th col
[val,ind] = min(C13_data);
array = array(ind,:);
else % case 2 : we have only one flag == 1 => simply keep the data where one flag is == 1 (logical OR)
% also if one row has both Lw and Rrs flag =1 and the second row has flags = 0 and 1, it will select only the common row with 1's.
array = array(ind_rows2>0 | ind_rows3>0 ,:);
end
% l(k) = size(array,1); % for debug only (shows how many of the 2 initial rows have been finally stored in the output)
out = [out; array]; % concat all valid data
end

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更多回答(1 个)

dpb
dpb 2023-7-17
load Lw
%whos Lw
Lw=addvars(Lw,datetime(Lw{:,1:6}),'NewVariableNames',{'Time'},'After',{'Second'});
Lw=removevars(Lw,[1:6]);
% shorten variable names to not be so much typing, stuff taking up space...
Lw.Properties.VariableNames=strrep(Lw.Properties.VariableNames,'Flag','');
Lw.Properties.VariableNames=strrep(Lw.Properties.VariableNames,'Sung','G');
Lw.Properties.VariableNames([2:3 5:6])=extractBefore(Lw.Properties.VariableNames([2:3 5:6]),7);
Lw=addvars(Lw,Lw.LightA & Lw.LightQ,'NewVariableNames',{'LightOK'},'After','Time'); % both available and quality
Lw=addvars(Lw,Lw.GlintL | Lw.GlintR,'NewVariableNames',{'GlintOK'},'After','LightOK'); % at least one or other OK
isMin=cell2mat(rowfun(@(v)v==min(v),Lw,'groupingvariables','Time','InputVariables','VarName13', ...
'OutputVariableName',{'isMin'},'OutputFormat','cell'));
Lw=addvars(Lw,isMin,'NewVariableNames',{'isMin'},'After','LightOK');
head(Lw,20)
Time LightOK isMin GlintOK LightA LightQ Weather GlintL GlintR minRrs VarName13 VarName14 VarName15 VarName16 VarName17 VarName18 VarName19 VarName20 VarName21 VarName22 VarName23 VarName24 VarName25 VarName26 VarName27 VarName28 VarName29 VarName30 VarName31 VarName32 VarName33 VarName34 VarName35 VarName36 VarName37 VarName38 VarName39 VarName40 VarName41 VarName42 VarName43 VarName44 VarName45 VarName46 VarName47 VarName48 VarName49 VarName50 VarName51 VarName52 VarName53 VarName54 VarName55 VarName56 VarName57 VarName58 VarName59 VarName60 VarName61 VarName62 VarName63 VarName64 VarName65 VarName66 VarName67 VarName68 VarName69 VarName70 VarName71 VarName72 VarName73 VarName74 VarName75 VarName76 VarName77 VarName78 VarName79 VarName80 VarName81 VarName82 VarName83 VarName84 VarName85 VarName86 VarName87 VarName88 VarName89 VarName90 VarName91 VarName92 VarName93 VarName94 VarName95 VarName96 VarName97 VarName98 VarName99 VarName100 VarName101 VarName102 VarName103 VarName104 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__________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ __________ 09-May-2023 00:00:00 true true true 1 1 3 1 1 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Now, the combination of
isBest=Lw.LightOK & Lw.GlintOK & Lw.isMin;
Those are the specific rows that match the conditions that both are ok as far as light, at least one is ok on the glint scale and if both are flagged on glint, then it deselects the one not the minimum V13 value.
  2 个评论
Brandy
Brandy 2023-7-18
Hey thanks so much for the answer, I had to adjust the code so that it would work in my original for loop but it works. But now I can't figure out where to put the line for plotting the new data. I just want to plot (x,y) for each file that gets brought in, and plot them ontop of eachother so "hold on", any idea where in the code it needs to go? When I put it inside the loop, after x= and y= then I get the error "vectors must be the same length".
myFolder = 'C:\Users\tbrob\MATLAB Drive\SO298-MATLAB\MATLAB\Lw';
% Check to make sure that folder actually exists. Warn user if it doesn't.
if ~isfolder(myFolder)
errorMessage = sprintf('Error: The following folder does not exist:\n%s', myFolder);
uiwait(warndlg(errorMessage));
return;
end
% Get a list of all files in the folder with the desired file name pattern.
filePattern = fullfile(myFolder, '*Lw.dat'); % The folder has 3 different file types; we only want the Es data from each day.
theFiles = dir(filePattern);
% Process each file and plot the data
for k = 1 : length(theFiles)
baseFileName = theFiles(k).name;
fullFileName = fullfile(myFolder, baseFileName);
fprintf(1, 'Now reading %s\n', fullFileName);
opts = delimitedTextImportOptions("NumVariables", 328);
% Specify range and delimiter
opts.DataLines = [51, Inf];
opts.Delimiter = "\t";
% Specify column names and types
opts.VariableNames = ["Year", "Month", "Day", "Hour", "Minute", "Second", "FlagLightAvailability", "FlagLightQuality", "FlagWeather", "FlagSunglintLw", "FlagSunglintRrs", "minRrs", "VarName13", "VarName14", "VarName15", "VarName16", "VarName17", "VarName18", "VarName19", "VarName20", "VarName21", "VarName22", "VarName23", "VarName24", "VarName25", "VarName26", "VarName27", "VarName28", "VarName29", "VarName30", "VarName31", "VarName32", "VarName33", "VarName34", "VarName35", "VarName36", "VarName37", "VarName38", "VarName39", "VarName40", "VarName41", "VarName42", "VarName43", "VarName44", "VarName45", "VarName46", "VarName47", "VarName48", "VarName49", "VarName50", "VarName51", "VarName52", "VarName53", "VarName54", "VarName55", "VarName56", "VarName57", "VarName58", "VarName59", "VarName60", "VarName61", "VarName62", "VarName63", "VarName64", "VarName65", "VarName66", "VarName67", "VarName68", "VarName69", "VarName70", "VarName71", "VarName72", "VarName73", "VarName74", "VarName75", "VarName76", "VarName77", "VarName78", "VarName79", "VarName80", "VarName81", "VarName82", "VarName83", "VarName84", "VarName85", "VarName86", "VarName87", "VarName88", "VarName89", "VarName90", "VarName91", "VarName92", "VarName93", "VarName94", "VarName95", "VarName96", "VarName97", "VarName98", "VarName99", "VarName100", "VarName101", "VarName102", "VarName103", "VarName104", "VarName105", "VarName106", "VarName107", "VarName108", "VarName109", "VarName110", "VarName111", "VarName112", "VarName113", "VarName114", "VarName115", "VarName116", "VarName117", "VarName118", "VarName119", "VarName120", "VarName121", "VarName122", "VarName123", "VarName124", "VarName125", "VarName126", "VarName127", "VarName128", "VarName129", "VarName130", "VarName131", "VarName132", "VarName133", "VarName134", "VarName135", "VarName136", "VarName137", "VarName138", "VarName139", "VarName140", "VarName141", "VarName142", "VarName143", "VarName144", "VarName145", "VarName146", "VarName147", "VarName148", "VarName149", "VarName150", "VarName151", "VarName152", "VarName153", "VarName154", "VarName155", "VarName156", "VarName157", "VarName158", "VarName159", "VarName160", "VarName161", "VarName162", "VarName163", "VarName164", "VarName165", "VarName166", "VarName167", "VarName168", "VarName169", "VarName170", "VarName171", "VarName172", "VarName173", "VarName174", "VarName175", "VarName176", "VarName177", "VarName178", "VarName179", "VarName180", "VarName181", "VarName182", "VarName183", "VarName184", "VarName185", "VarName186", "VarName187", "VarName188", "VarName189", "VarName190", "VarName191", "VarName192", "VarName193", "VarName194", "VarName195", "VarName196", "VarName197", "VarName198", "VarName199", "VarName200", "VarName201", "VarName202", "VarName203", "VarName204", "VarName205", "VarName206", "VarName207", "VarName208", "VarName209", "VarName210", "VarName211", "VarName212", "VarName213", "VarName214", "VarName215", "VarName216", "VarName217", "VarName218", "VarName219", "VarName220", "VarName221", "VarName222", "VarName223", "VarName224", "VarName225", "VarName226", "VarName227", "VarName228", "VarName229", "VarName230", "VarName231", "VarName232", "VarName233", "VarName234", "VarName235", "VarName236", "VarName237", "VarName238", "VarName239", "VarName240", "VarName241", "VarName242", "VarName243", "VarName244", "VarName245", "VarName246", "VarName247", "VarName248", "VarName249", "VarName250", "VarName251", "VarName252", "VarName253", "VarName254", "VarName255", "VarName256", "VarName257", "VarName258", "VarName259", "VarName260", "VarName261", "VarName262", "VarName263", "VarName264", "VarName265", "VarName266", "VarName267", "VarName268", "VarName269", "VarName270", "VarName271", "VarName272", "VarName273", "VarName274", "VarName275", "VarName276", "VarName277", "VarName278", "VarName279", "VarName280", "VarName281", "VarName282", "VarName283", "VarName284", "VarName285", "VarName286", "VarName287", "VarName288", "VarName289", "VarName290", "VarName291", "VarName292", "VarName293", "VarName294", "VarName295", "VarName296", "VarName297", "VarName298", "VarName299", "VarName300", "VarName301", "VarName302", "VarName303", "VarName304", "VarName305", "VarName306", "VarName307", "VarName308", "VarName309", "VarName310", "VarName311", "VarName312", "VarName313", "VarName314", "VarName315", "VarName316", "VarName317", "VarName318", "VarName319", "VarName320", "VarName321", "VarName322", "VarName323", "VarName324", "VarName325", "VarName326", "VarName327", "VarName328"];
opts.VariableTypes = ["double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double", "double"];
% Specify file level properties
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
% Specify variable properties
opts = setvaropts(opts, ["Year", "Month", "Day", "Hour", "Minute", "Second", "FlagLightAvailability", "FlagLightQuality", "FlagWeather", "FlagSunglintLw", "FlagSunglintRrs", "minRrs", "VarName13", "VarName14", "VarName15", "VarName16", "VarName17", "VarName18", "VarName19", "VarName20", "VarName21", "VarName22", "VarName23", "VarName24", "VarName25", "VarName26", "VarName27", "VarName28", "VarName29", "VarName30", "VarName31", "VarName32", "VarName33", "VarName34", "VarName35", "VarName36", "VarName37", "VarName38", "VarName39", "VarName40", "VarName41", "VarName42", "VarName43", "VarName44", "VarName45", "VarName46", "VarName47", "VarName48", "VarName49", "VarName50", "VarName51", "VarName52", "VarName53", "VarName54", "VarName55", "VarName56", "VarName57", "VarName58", "VarName59", "VarName60", "VarName61", "VarName62", "VarName63", "VarName64", "VarName65", "VarName66", "VarName67", "VarName68", "VarName69", "VarName70", "VarName71", "VarName72", "VarName73", "VarName74", "VarName75", "VarName76", "VarName77", "VarName78", "VarName79", "VarName80", "VarName81", "VarName82", "VarName83", "VarName84", "VarName85", "VarName86", "VarName87", "VarName88", "VarName89", "VarName90", "VarName91", "VarName92", "VarName93", "VarName94", "VarName95", "VarName96", "VarName97", "VarName98", "VarName99", "VarName100", "VarName101", "VarName102", "VarName103", "VarName104", "VarName105", "VarName106", "VarName107", "VarName108", "VarName109", "VarName110", "VarName111", "VarName112", "VarName113", "VarName114", "VarName115", "VarName116", "VarName117", "VarName118", "VarName119", "VarName120", "VarName121", "VarName122", "VarName123", "VarName124", "VarName125", "VarName126", "VarName127", "VarName128", "VarName129", "VarName130", "VarName131", "VarName132", "VarName133", "VarName134", "VarName135", "VarName136", "VarName137", "VarName138", "VarName139", "VarName140", "VarName141", "VarName142", "VarName143", "VarName144", "VarName145", "VarName146", "VarName147", "VarName148", "VarName149", "VarName150", "VarName151", "VarName152", "VarName153", "VarName154", "VarName155", "VarName156", "VarName157", "VarName158", "VarName159", "VarName160", "VarName161", "VarName162", "VarName163", "VarName164", "VarName165", "VarName166", "VarName167", "VarName168", "VarName169", "VarName170", "VarName171", "VarName172", "VarName173", "VarName174", "VarName175", "VarName176", "VarName177", "VarName178", "VarName179", "VarName180", "VarName181", "VarName182", "VarName183", "VarName184", "VarName185", "VarName186", "VarName187", "VarName188", "VarName189", "VarName190", "VarName191", "VarName192", "VarName193", "VarName194", "VarName195", "VarName196", "VarName197", "VarName198", "VarName199", "VarName200", "VarName201", "VarName202", "VarName203", "VarName204", "VarName205", "VarName206", "VarName207", "VarName208", "VarName209", "VarName210", "VarName211", "VarName212", "VarName213", "VarName214", "VarName215", "VarName216", "VarName217", "VarName218", "VarName219", "VarName220", "VarName221", "VarName222", "VarName223", "VarName224", "VarName225", "VarName226", "VarName227", "VarName228", "VarName229", "VarName230", "VarName231", "VarName232", "VarName233", "VarName234", "VarName235", "VarName236", "VarName237", "VarName238", "VarName239", "VarName240", "VarName241", "VarName242", "VarName243", "VarName244", "VarName245", "VarName246", "VarName247", "VarName248", "VarName249", "VarName250", "VarName251", "VarName252", "VarName253", "VarName254", "VarName255", "VarName256", "VarName257", "VarName258", "VarName259", "VarName260", "VarName261", "VarName262", "VarName263", "VarName264", "VarName265", "VarName266", "VarName267", "VarName268", "VarName269", "VarName270", "VarName271", "VarName272", "VarName273", "VarName274", "VarName275", "VarName276", "VarName277", "VarName278", "VarName279", "VarName280", "VarName281", "VarName282", "VarName283", "VarName284", "VarName285", "VarName286", "VarName287", "VarName288", "VarName289", "VarName290", "VarName291", "VarName292", "VarName293", "VarName294", "VarName295", "VarName296", "VarName297", "VarName298", "VarName299", "VarName300", "VarName301", "VarName302", "VarName303", "VarName304", "VarName305", "VarName306", "VarName307", "VarName308", "VarName309", "VarName310", "VarName311", "VarName312", "VarName313", "VarName314", "VarName315", "VarName316", "VarName317", "VarName318", "VarName319", "VarName320", "VarName321", "VarName322", "VarName323", "VarName324", "VarName325", "VarName326", "VarName327", "VarName328"], "ThousandsSeparator", ",");
% Import the data
Lw= readtable(fullFileName, opts);
clear opts
Lw=addvars(Lw,datetime(Lw{:,1:6}),'NewVariableNames',{'Time'},'After',{'Second'});
Lw=removevars(Lw,[1:6]);
% shorten variable names to not be so much typing, stuff taking up space...
Lw.Properties.VariableNames=strrep(Lw.Properties.VariableNames,'Flag','');
Lw.Properties.VariableNames=strrep(Lw.Properties.VariableNames,'Sung','G');
Lw.Properties.VariableNames([2:3 5:6])=extractBefore(Lw.Properties.VariableNames([2:3 5:6]),7);
Lw=addvars(Lw,Lw.LightA & Lw.LightQ,'NewVariableNames',{'LightOK'},'After','Time'); % both available and quality
Lw=addvars(Lw,Lw.GlintL | Lw.GlintR,'NewVariableNames',{'GlintOK'},'After','LightOK'); % at least one or other OK
isMin=cell2mat(rowfun(@(v)v==min(v),Lw,'groupingvariables','Time','InputVariables','VarName13', ...
'OutputVariableName',{'isMin'},'OutputFormat','cell'));
Lw=addvars(Lw,isMin,'NewVariableNames',{'isMin'},'After','LightOK');
head(Lw,20);
isBest=Lw.LightOK & Lw.GlintOK & Lw.isMin;
LwBest=Lw(isBest,:);
% Extract relevant data for plotting
x = 320:2:950;
y = LwBest(:, 11:326);
y=table2array(y);
end
dpb
dpb 2023-7-19
"I had to adjust the code so that it would work in my original for loop..."
That's part of the point was to illustrate vectorized use of MATLAB.
It wasn't/isn't clear to me precisely what the plots should be of; the thing where you introduce magic numbers to subscript is not anything that can be logically code; what's that all about and why those particular numbers? Must be some logic there, but it wasn't explained as to why/what it was to be able to do anything with/about...
"... I get the error "vectors must be the same length"."
There's an indexing issue with the selection of the arrays in that one goes from the first row while another starts at the second--that causes a mismatch in lengths. What was up with that? Although I noticed there was a negative value for one of the variables in that first row that maybe disqualified it? If that's the deal, that should also be handled logically.
You had a very good table to start with; use it or, if you don't want the table, then use readmatrix instead of readtable; switching back and forth just wastes code and perhaps memory; there's no real reason to use both storage formats for the same data/code.
"...and plot them on top of eachother so "hold on","
You can put hold first if you need to plot into the same axis sequentially, but plot is vectorized; it will plot multiple lines at one time; each column passed is considered a separate variable to be plotted against the corresponding x; the x values can be a vector while y is an array as long as the lengths are matching -- that's why you don't want to select different array sizes but use logic operations on the data. If some values aren't to be shown, then set them to NaN with the logical; they will be silently ignored by the plot routines.
Then, the whole thing is one call to plot for each file.

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