How to find strings in a very large array of data?
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Steven
el 20 de Nov. de 2019
Editada: per isakson
el 23 de Nov. de 2019
Hi
I have a csv file containing a large number of numbers and a few random strings like 'zgdf'. I need to find them and set them to zero. I cannot use 'csvread' (due to strings), so I use 'textscan' to read the file.
I then turn the data to digits using str2double. MATLAB then turns the string values to NaN which is fine for me, but it takes a long time, specially because this has to be done for many similar files.
Any faster method to sort this out?
This is how I read the data (original file has two columns and large number or rows):
fileID = fopen(filename);
C = textscan(fileID,'%s %s','Delimiter',',');
fclose(fileID);
for i = 1: length (C{1})
D(i) = str2double(C{1}{i});
end
Thanks
10 comentarios
Adam Danz
el 21 de Nov. de 2019
Editada: Adam Danz
el 21 de Nov. de 2019
Knowing your matlab relase is usually helpful which is why it's included as an optional field when you're forming a question in this forum.
I've confirmed that the loop method of str2double() is indeed faster than the direct application to the cell array. Sometimes loops are faster.
See method 3 in my answer which applies your sscanf idea and avoids the error you described.
See method 4 for a FEX function that is like str2double() but much faster.
Method 5 is very fast but requires r2019a.
Lastly, whenever you build a variable within a loop, always pre-allocate the variable. Not pre-allocating the variable will definitely slow down your code.
Ridwan Alam
el 21 de Nov. de 2019
Editada: Ridwan Alam
el 21 de Nov. de 2019
@Steven
I have updated my answer with the syntax for textscan with "TreatAsEmpty" option. It returns NaN in place of those known noisy chars. Using the ["EmptyValue",0] option will return 0 instead of NaN.
Not sure how much speed up will that do though :(
Respuesta aceptada
Adam Danz
el 20 de Nov. de 2019
Editada: Adam Danz
el 21 de Nov. de 2019
[This answer has been reorganized following the discussion in the comment section under the question]
Method 1
fid = fopen('myCSVfile.csv');
C = textscan(fid,'%s %s','Delimiter',',');
fclose(fid);
A = str2double(C{1}); % Faster than doing the same thing in a loop.
[update] the loop method below is actually faster
A = zeros(size(C{1})); % <--- always pre-allocate!
for i = 1:numel(C{1})
A = str2double(C{1}{i});
end
Method 2
Try this modification of the script produced by ImportData tool. Rather than importing your data and then converting it using str2double(), this imports the data as numeric and replaces non-numeric elements with NaN. I think it should be faster than your approach but I doubt it is much faster (or maybe it's not faster at all).
The only 2 variables you'll need to change to adapt to your data are
- file (the filename, or, preferably, the full path to your file)
- The NumerVariables value (number of columns of data)
%% Setup the Import Options and import the data
file = "C:\Users\name\Documents\MATLAB\myCSVfile.csv"; % Full path to your file (or just file name)
opts = delimitedTextImportOptions("NumVariables", 2); % Number of columns of data
opts.VariableTypes(:) = {'double'}; % read in all data as double (nan for strings)
opts.Delimiter = ",";
opts.ExtraColumnsRule = "ignore";
opts.EmptyLineRule = "read";
Data = readtable(file, opts); % Read in as table
Data = Data{:,:}; % Convert to matrix
Method 3
D = zeros(size(C{1})); % <--- pre-allocate!
for j = 1: length (C{1})
s = sscanf(C{1}{j},'%f');
if ~isempty(s)
D(j) = s;
end
end
This is 4.5x faster than method 1.
Method 4
This FEX function is designed to overcome the slow speed of str2double()
Method 5
A very fast solution is to read the data in using readmatrx() which automatically converts non-numeric elements to NaN but it requires r2019a.
file = 'myCSVfile.csv';
D = readmatrix(file); %that's it, just 2 lines
3 comentarios
Más respuestas (2)
Ridwan Alam
el 20 de Nov. de 2019
Editada: Ridwan Alam
el 21 de Nov. de 2019
Given, the list of noise is {'a', 'b', 'ee'}:
C = cell2mat(textscan(fileID,'%f %f','Delimiter',',','TreatAsEmpty',{'a','b','ee'},'EmptyValue',0));
Try this!!
%% Old Answer
Updated using Method 1 from Adam:
C = textscan(fileID,'%s %s','Delimiter',',');
C = [str2double(C{1}) str2double(C{2})];
C(isnan(C)) = 0;
9 comentarios
Ridwan Alam
el 21 de Nov. de 2019
Sure, Steven. Please vote up if you liked the conversation. Thanks!
per isakson
el 21 de Nov. de 2019
Editada: per isakson
el 23 de Nov. de 2019
"random strings like 'zgdf'" If that means letters of the US alphabet, this code is rather fast.
%%
chr = fileread('cssm.txt');
chr = regexprep( chr, '[A-Za-z]+', '0.0' );
cac = textscan( chr, '%f%f', 'Delimiter',',', 'CollectOutput',true );
num = cac{1};
result
>> num(1:10,:)
ans =
0.81472 0.15761
0 0.97059
0.12699 0.95717
0.91338 0.48538
0.63236 0.80028
0.09754 0.14189
0.2785 0
0.54688 0.91574
0 0.79221
0.96489 0.95949
Where cssm.txt contains
0.81472, 0.15761
abc , 0.97059
0.12699, 0.95717
0.91338, 0.48538
0.63236, 0.80028
0.09754, 0.14189
0.27850, def
0.54688, 0.91574
zgdf , 0.79221
0.96489, 0.95949
et cetera
In response to comments
See the caveat in the first line of my answer.
I fail to find a regular expression for "not a legal number" and if one exists it might not be that fast.
It's straight forward to add a few (many becomes impractical) characters, e.g. '^â', and make sure that the string is followed by comma or end of line.
>> chr = regexprep( '12.3, abc, g^â, 1.0e5, def ', '(?m)[A-Za-zâ^]+(?=\x20*\r?(,|$))', '0.0' )
chr =
'12.3, 0.0, 0.0, 1.0e5, 0.0 '
>>
Look ahead, e.g. '(?=\x20*\r?(,|$))', is reasonable fast, but look behind sometimes ruins the performance.
The above regex fails for 'def1', '1deg' and '10a'
fileread in combination with CRLF as newline character poses a problem when using regular expressions. The anchor $ doesn't recognise CRLF as newline. (Please tell me if I missed something.) The best way to avoid this problem is to replace fileread by a function that uses
[fid, msg] = fopen( filespec, 'rt' );
chr = fread( fid, inf, '*char' );
5 comentarios
per isakson
el 22 de Nov. de 2019
Editada: per isakson
el 22 de Nov. de 2019
I added a response to my answer.
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