I need to calculate the mean, standard deviation, and other values for a number of variables and I was wondering how to use a loop to my advantage. I have 5 electrodes of data. So to calculate the mean of each I do this:
mean_ch1 = mean(ch1);
mean_ch2 = mean(ch2);
mean_ch3 = mean(ch3);
mean_ch4 = mean(ch4);
mean_ch5 = mean(ch5);
What I want is to be able to condense that code into a line or so. The code I tried does not work:
for i = 1:5
mean_ch(i) = mean(ch(i));
end
I know this code is wrong but it conveys the idea of what I'm trying to accomplish. I want to end up with 5 separate variables that are named by the loop or a cell array with all 5 variables within it allowing for easy recall. I know there must be a way to write this code I'm just not sure how to accomplish it.
You have a few options for how you can do this:
You can put all your channel data into one large matrix first, then compute the mean of the rows or columns using the function MEAN. For example, if each chX variable is an N-by-1 array, you can do the following:
chArray = [ch1 ch2 ch3 ch4 ch5]; %# Make an N-by-5 matrix
meanArray = mean(chArray); %# Take the mean of each column
You can put all your channel data into a cell array first, then compute the mean of each cell using the function CELLFUN:
meanArray = cellfun(#mean,{ch1,ch2,ch3,ch4,ch5});
This would work even if each chX array is a different length from one another.
You can use EVAL to generate the separate variables for each channel mean:
for iChannel = 1:5
varName = ['ch' int2str(iChannel)]; %# Create the name string
eval(['mean_' varName ' = mean(' varName ');']);
end
If it's always exactly 5 channels, you can do
ch = {ch1, ch2, ch3, ch4, ch5}
for j = 1:5
mean_ch(j) = mean(ch{j});
end
A more complicated way would be
for j = 1:nchannels
mean_ch(j) = eval(['mean(ch' num2str(j) ')']);
end
Apart from gnovice's answer. You could use structures and dynamic field names to accomplish your task. First I assume that your channel data variables are all in the format ch* and are the only variables in your MATLAB workspace. The you could do something like the following
%# Move the channel data into a structure with fields ch1, ch2, ....
%# This could be done by saving and reloading the workspace
save('channelData.mat','ch*');
chanData = load('channelData.mat');
%# Next you can then loop through the structure calculating the mean for each channel
flds = fieldnames(chanData); %# get the fieldnames stored in the structure
for i=1:length(flds)
mean_ch(i) = mean(chanData.(flds{i});
end
Related
I would like to name variable (type double) in the following way:
k0 = D(1,1);
k1 = D(2,2);
k2 = D(3,3);
k3 = D(4,4);
k4 = D(5,5);
k5 = D(6,6);
k6 = D(7,7);
k7 = D(8,8);
...
up to k99 automatically using for loop. So I see that I should use array or cell instead of double variable using eval as it is slow. But if I should use array or cell instead of double variable, I have to start at k{1} or k(1), which loses the meaning as I want exactly that k0 refers to D(1,1), i.e. the number in my variable is 1 less. How do I create meaningful cell name like k{0}?
Also, say I have an array A. There are also some times i need meaningful variable name, such as
c111 = A(1)*A(1)*A(1)
c222 = A(2)*A(2)*A(2)
c333 = A(3)*A(3)*A(3)
How can I create c{111} efficiently using for loop?
Use structures:
D = rand(21);
c = 1;
for k = -10:10
if k<0
s.(['k_' num2str(abs(k))]) = D(c,c);
else
s.(['k' num2str(k)]) = D(c,c);
end
c = c+1;
end
This will give you a structure like:
s =
k_10: 0.51785
k_9: 0.90121
k_8: 0.40746
k_7: 0.092989
.
.
k_1: 0.75522
k0: 0.55257
k1: 0.28708
.
.
k9: 0.94182
k10: 0.2124
and don't use eval...
Answer to 1st Question:-
D=randn(100); % A matrix of random elements of size 8x8
for m=0:99
assignin('base', ['k' num2str(m)], D(m+1,m+1))
end
Answer to 2nd Question:-
A=randn(1,3); % An array of 3 random elements
for n=1:3
assignin('base', ['c' num2str(111*n)], A(n)^3)
end
Comments:-
You've stated that you need variables like k0,k1,k2,... and c111,c222,c333 but you're asking how to create k{0}, k{1},k{2},... and c{111},c{222},c{333}. As far as your need is concerned, I have given answer to it. Regarding the latter, k{0} is never possible and c{111},c{222},c{333},... don't make good sense without using any of the first 0:100 values and then 112:221 values and so on. Although you can do it using:
A=rand(1,3); % An array of 3 random elements
c{333} = 0 ; % Pre-allocation
for p=1:3 % Since you want to use a 'for loop'
c{111*p} = A(p)^3;
end
And regarding the requirement that you made in the comment in these words "I also have some variable using negative index", you can never have variables in the negative index. If you mean you want to create variables with names like k-1, k-2,... etc, it is not possible. An alternate way is to use k_1, k_2,... etc but then as you said in the question "k0 refers to D(1,1), i.e. the number in my variable is 1 less". It means k_1 will refer to D(0,0) and so on which is again an invalid thing for MATLAB.
Recommendation:-
You really need to modify your code.
I have a huge table data= {1000 x 1000} of binary data.
They table's variable names are encoded for eg D1,D2,...,DA2,DA3,... with their real labels given in a .txt file.
The .txt file also consists of some text for eg:
D1: Age
Mean age: 33
Median :
.
.
.
D2: weight
I would just like to pick out these names from the text file and create a table with the real variable names.
Any suggestions?
If there is a specific number of lines between each of those labels, then you can extract them by reading in the file, and looping over the relevant lines. For each label, it simple to extract the label with strsplit()
e.g. Let's say there's 5 lines between each label
uselessLines = 5;
% imports as a vertical matrix with each line from the file.
dataLabelsFile = importdata(filename);
% get the total number of lines
numLines = size(dataLabelsFile);
% pre-allocate array for labels, a cell is used for a string
dataLabels = cell(ceil(numLines/(uselessLines+1)));
% use a seperate counting variable
m = 1;
% now, for each label, we add it to the dataLabels matrix
for i=1:(uselessLines+1):numLines
line = strsplit(dataLabelsFile{i}); % by default splits on whitespace
dataLabels(m) = line(2);
m = m + 1;
end
By the end of that loop you should have a variable called dataLabels that holds all of the labels. Now, you can actually very easily work out which label goes with which set of data
provided they are still in the same order. The indexes will be the same for the label to the data.
This is a method you could try if the labels are evenly spaced.
However, if the labels are a random number of lines, then you probably want to do a check with a regular expression like the person below me has suggested. Then you just replace the last two lines of the loop with something like this.
...
if (regular expression matched)
dataLabels(m) = line(2);
m = m + 1;
end
...
That being said, while regular expressions are flexible, if you can get away with replacing it with literally one function call, it's usually better to do that. Regex efficiencies are determined by the skill of the programmer, while in-built functions have generally been tested by some of the better programmers in the world. Additionally, Regex's are harder to understand if you ever want to go back and change it.
Of course there are times when Regex's are amazing, I'm just not convinced this is one of those times.
An implemention of the approach in my earlier comment:
fid = fopen(filename);
varNames = cell(0);
proceed = true;
while proceed
line = fgetl(fid);
if ischar(line)
startIdx = regexp(line,'(?<=^[A-Z]*\d*:)\s');
if ~isempty(startIdx)
varNames{end+1} = strtrim(line(startIdx:end)); %#ok<SAGROW>
end
else
proceed = false;
end
end
fclose(fid);
I cant put the resulting varNames in a table for you, since I have a version of Matlab that does not support tables.
I have the following piece of code:
for query = queryFiles
queryImage = imread(strcat('Queries/', query));
queryImage = im2single(rgb2gray(queryImage));
[qf,qd] = vl_covdet(queryImage, opts{:}) ;
for databaseEntry = databaseFiles
entryImage = imread(databaseEntry.name);
entryImage = im2single(rgb2gray(entryImage));
[df,dd] = vl_covdet(entryImage, opts{:}) ;
[matches, H] = matchFeatures(qf,qf,df,dd) ;
result = [result; query, databaseEntry, length(matches)];
end
end
It is my understanding that it should work as a Java/C++ for(query:queryFiles), however the query appears to be a copy of the queryFiles. How do I iterate through this vector normally?
I managed to sort the problem out. It was mainly to my MATLAB ignorance. I wasn't aware of cell arrays and that's the reason I had this problem. That and the required transposition.
From your code it appears that queryFiles is a numeric vector. Maybe it's a column vector? In that case you should convert it into a row:
for query = queryFiles.'
This is because the for loop in Matlab picks a column at each iteration. If your vector is a single column, it picks the whole vector in just one iteration.
In MATLAB, the for construct expects a row vector as input:
for ii = 1:5
will work (loops 5 times with ii = 1, 2, ...)
x = 1:5;
for ii = x
works the same way
However, when you have something other than a row vector, you would simply get a copy (or a column of data at a time).
To help you better, you need to tell us what the data type of queryFiles is. I am guessing it might be a cell array of strings since you are concatenating with a file path (look at fullfile function for the "right" way to do this). If so, then a "safe" approach is:
for ii = 1:numel(queryFiles)
query = queryFiles{ii}; % or queryFiles(ii)
It is often helpful to know what loop number you are in, and in this case ii provides that count for you. This approach is robust even when you don't know ahead of time what the shape of queryFiles is.
Here is how you can loop over all elements in queryFiles, this works for scalars, row vectors, column vectors and even high dimensional matrices:
for query = queryFiles(:)'
% Do stuff
end
Is queryFiles a cell array? The safest way to do this is to use an index:
for i = 1:numel(queryFiles)
query = queryFiles{i};
...
end
I am refering to an example like this
I have a function to analize the elements of a vector, 'input'. If these elements have a special property I store their values in a vector, 'output'.
The problem is that at the begging I don´t know the number of elements it will need to store in 'output'so I don´t know its size.
I have a loop, inside I go around the vector, 'input' through an index. When I consider special some element of this vector capture the values of 'input' and It be stored in a vector 'ouput' through a sentence like this:
For i=1:N %Where N denotes the number of elements of 'input'
...
output(j) = input(i);
...
end
The problem is that I get an Error if I don´t previously "declare" 'output'. I don´t like to "declare" 'output' before reach the loop as output = input, because it store values from input in which I am not interested and I should think some way to remove all values I stored it that don´t are relevant to me.
Does anyone illuminate me about this issue?
Thank you.
How complicated is the logic in the for loop?
If it's simple, something like this would work:
output = input ( logic==true )
Alternatively, if the logic is complicated and you're dealing with big vectors, I would preallocate a vector that stores whether to save an element or not. Here is some example code:
N = length(input); %Where N denotes the number of elements of 'input'
saveInput = zeros(1,N); % create a vector of 0s
for i=1:N
...
if (input meets criteria)
saveInput(i) = 1;
end
end
output = input( saveInput==1 ); %only save elements worth saving
The trivial solution is:
% if input(i) meets your conditions
output = [output; input(i)]
Though I don't know if this has good performance or not
If N is not too big so that it would cause you memory problems, you can pre-assign output to a vector of the same size as input, and remove all useless elements at the end of the loop.
output = NaN(N,1);
for i=1:N
...
output(i) = input(i);
...
end
output(isnan(output)) = [];
There are two alternatives
If output would be too big if it was assigned the size of N, or if you didn't know the upper limit of the size of output, you can do the following
lengthOutput = 100;
output = NaN(lengthOutput,1);
counter = 1;
for i=1:N
...
output(counter) = input(i);
counter = counter + 1;
if counter > lengthOutput
%# append output if necessary by doubling its size
output = [output;NaN(lengthOutput,1)];
lengthOutput = length(output);
end
end
%# remove unused entries
output(counter:end) = [];
Finally, if N is small, it is perfectly fine to call
output = [];
for i=1:N
...
output = [output;input(i)];
...
end
Note that performance degrades dramatically if N becomes large (say >1000).
I am trying to deal with a very large dataset. I have k = ~4200 matrices (varying sizes) which must be compared combinatorially, skipping non-unique and self comparisons. Each of k(k-1)/2 comparisons produces a matrix, which must be indexed against its parents (i.e. can find out where it came from). The convenient way to do this is to (triangularly) fill a k-by-k cell array with the result of each comparison. These are ~100 X ~100 matrices, on average. Using single precision floats, it works out to 400 GB overall.
I need to 1) generate the cell array or pieces of it without trying to place the whole thing in memory and 2) access its elements (and their elements) in like fashion. My attempts have been inefficient due to reliance on MATLAB's eval() as well as save and clear occurring in loops.
for i=1:k
[~,m] = size(data{i});
cur_var = ['H' int2str(i)];
%# if i == 1; save('FileName'); end; %# If using a single MAT file and need to create it.
eval([cur_var ' = cell(1,k-i);']);
for j=i+1:k
[~,n] = size(data{j});
eval([cur_var '{i,j} = zeros(m,n,''single'');']);
eval([cur_var '{i,j} = compare(data{i},data{j});']);
end
save(cur_var,cur_var); %# Add '-append' when using a single MAT file.
clear(cur_var);
end
The other thing I have done is to perform the split when mod((i+j-1)/2,max(factor(k(k-1)/2))) == 0. This divides the result into the largest number of same-size pieces, which seems logical. The indexing is a little more complicated, but not too bad because a linear index could be used.
Does anyone know/see a better way?
Here's a version that combines going fast with using minimal memory.
I use fwrite/fread so that you still can use parfor (and this time, I made sure it works :) )
%# assume data is loaded an k is known
%# find the index pairs for comparisons. This could be done more elegantly, I guess.
%# I'm constructing a lower triangular array, i.e. an array that has ones wherever
%# we want to compare i (row) and j (col). Then I use find to get i and j
[iIdx,jIdx] = find(tril(ones(k,k),-1));
%# create a directory to store the comparisons
mkdir('H_matrix_elements')
savePath = fullfile(pwd,'H_matrix_elements');
%# loop through all comparisons in parallel. This way there may be a bit more overhead from
%# the individual function calls. However, parfor is most efficient if there are
%# a lot of relatively similarly fast iterations.
parfor ct = 1:length(iIdx)
%# make the comparison - do double b/c there shouldn't be a memory issue
currentComparison = compare(data{iIdx(ct)},data{jIdx{ct});
%# create save-name as H_i_j, e.g. H_104_23
saveName = fullfile(savePath,sprintf('H_%i_%i',iIdx(ct),jIdx(ct)));
%# save. Since 'save' is not allowed, use fwrite to write the data to disk
fid = fopen(saveName,'w');
%# for simplicity: save data as vector, add two elements to the beginning
%# to store the size of the array
fwrite(fid,[size(currentComparison)';currentComparison(:)]); % ' #SO formatting
%# close file
fclose(fid)
end
%# to read e.g. comparison H_104_23
fid = fopen(fullfile(savePath,'H_104_23'),'r');
tmp = fread(fid);
fclose(fid);
%# reshape into 2D array.
data = reshape(tmp(3:end),tmp(1),tmp(2));
You can get rid of the eval and clear calls by assigning the filename separately.
for i=1:k
[~,m] = size(data{i});
file_name = ['H' int2str(i)];
cur_var = cell(1, k-i);
for j=i+1:k
[~,n] = size(data{j});
cur_var{i,j} = zeros(m, n, 'single');
cur_var{i,j} = compare(data{i}, data{j});
end
save(file_name, cur_var);
end
If you need the saved variables to take different names, use the -struct option to save.
str.(file_name);
save(file_name, '-struct', str);