In Matlab (R2021b) I am using some given function, which reads time-dependent values of several variables and returns them in a combined matrix together with a time vector. In the data matrix each column represents one vector of time-dependent values for one variable.
[data,time] = function_reading_data_of_several_values('filename');
For readability of the following code where the variables are further processed, I would like to store these columns in separate vector variables. I am doing it like that:
MomentX = data(1,:);
MomentY = data(2,:);
MomentZ = data(3,:);
ForceX = data(4,:);
ForceY = data(5,:);
ForceZ = data(6,:);
That is working. But is there some simpler (or shorter) way of assigning the column of the matrix to individual vectors? I am asking because in real program I have more than the 6 columns as in the example. Code is getting quite long. I was thinking of something similar to the line below, but that does not work:
[MomentX,MomentY,MomentZ,ForceX,ForceY,ForceZ] = data; %does not work
Do you have any idea? Thanks for help!
Update:
Thanks to the hint here in the group to use tables, a solution could be like this:
...
[data,time] = function_reading_data_of_several_values('filename');
% data in matrix. Each column representing a stime dependent variable
varNames = {'MomentX', 'MomentX',...}; % Names of columns
T=array2table(data','VariableNames',varNames); % Transform to Table
Stress = T.MomentX/W + T.ForceY/A %accesing table columns
...
This seems to work fine and readable to me.
Solution 1: In industrial solutions like dSpace, it is very common to do it in struct arrays:
mydata.X(1).time = [0.01 0.02 0.03 0.04];
mydata.Y(1).name = 'MomentX';
mydata.Y(1).data = [1 2 3 4];
mydata.Y(2).name = 'MomentY';
mydata.Y(2).data = [2 3 4 5];
Solution 2: It is also very common to create tables
See: https://de.mathworks.com/help/matlab/ref/table.html
As already commented, it is probably better to use a table instead of separate variables may not be a good idea. But if you want to, it can be done this way:
A = magic(6): % example 6-column matrix
A_cell = num2cell(A, 1); % separate columns in cells
[MomentX, MomentY, MomentZ, ForceX, ForceY, ForceZ] = A_cell{:};
This is almost the same as your
[MomentX,MomentY,MomentZ,ForceX,ForceY,ForceZ] = data; %does not work
except that the right-hand side needs to be a comma-separated list, which in this case is obtained from a cell array.
Related
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 have a matrix of structs. I'm trying to extract from that matrix a matrix the same size
with only one of the fields as values.
I've been trying to use struct2cell and similar functions without success.
How can this be done?
If I understand you correctly, you have an array of struct like e.g this
s(1:2,1:3) = struct('a',1,'b',2);
Now you want a different struct that only has the field b
[newS(1:2,1:3).b] = deal(s.b);
edit
If all you need is the output (and if the field values are scalar), you can do the following:
out = zeros(size(s));
out(:) = cat(1,s.b)
I'll borrow Jonas' example. You can use the [] to gather a particular field.
% Create structure array
s(1:2,1:3) = struct('a',1,'b',2);
% Change values
for idx = 1:prod(size(s))
s(idx).a = idx;
s(idx).b = idx^2;
end
% Gather a specific field and reshape it to the size of the original matrix
A = reshape([s.a],size(s));
B = reshape([s.b],size(s));
I have a similar problem, but the contents of the field in my structure array are varying length strings that I use to tag my data, so when I extract the contents of the field, I want a cell of varying length strings.
This code using getfield and arrayfun does the job, but I think it is more complicated than it needs to be.
sa = struct('name', {'ben' 'frank', 'betty', 'cybil', 'jack'}, 'value', {1 1 2 3 5})
names = arrayfun(#(x) getfield(x, 'name'), sa, 'UniformOutput', false)
Can anyone suggest cleaner alternative? extractfield in the mapping toolbox seems to do the job, but it is not part of the base MATLAB system.
Update: I have answered my own embedded question.
names = {sa.name}
I have several data named ET1_A_C1_l1, ET1_A_C2_l1, ET1_A_C3_l1, ..., ET1_A_C63_l1 in Workspace. Besides that,I also have another sets of data named ET1_H_C1_l1, ET1_H_C2_l1, ..., ET1_A_C63_l1
Now I need to combine 2 set of data into one named Total_data.mat; For example,
Total_data=[ET1_A_C1_l1 ET1_A_C2_l1 ET1_A_C3_l1 ..... ET1_A_63_l1;ET1_H_C1_l1 ET1_H_C2_l1 ....ET1_H_C63_l1]
and need to take a huge of time to type the code one by one. Is there any idea using the loop to do this??
Thanks.
Rather than jumping on my wagon straight away, I'll start with the solution (which has been set up with an example):
%# State the size of each matrix
T = 6; N = 2;
%# State the number of matrices in category A and H (63 in your case - but 2 in my example)
K = 2;
%# Set up some example matrices
ET1_A_C1_l1 = rand(T, N); ET1_A_C2_l1 = 1 + rand(T, N);
ET1_H_C1_l1 = 2 + rand(T, N); ET1_H_C2_l1 = 3 + rand(T, N);
%# Preallocate a matrix to hold the output
M = NaN(2 * T, K * N);
%# Loop over the variables and add them to the matrix using the evil eval
for k = 1:K
M(1:T, (k*N)-1:k*N) = eval(['ET1_A_C', num2str(k), '_l1']);
M(T+1:2*T, (k*N)-1:k*N) = eval(['ET1_H_C', num2str(k), '_l1']);
end
%# Save to a mat file
save('Total_Data.mat', 'M');
Now, wagon time: If you've been given the data in the form that you have it now, and there was nothing you could do about it, and you realize what a terrible situation it is to be in, then you can stop reading now.
But, if you were responsible for creating all those E_blah variables in the first place, then you need to take a look at the answer of #jerad and start thinking about different ways of storing data. A cell array or a structure is one way to go about it. Or start with one big matrix in the first place. But remember the following two general rules:
1) If you have more than 20 variables in your workspace, then you're probably doing it wrong.
2) If you find yourself frequently using the evil function eval then you're almost definitely doing it wrong.
Having this kind of problem suggests to me that you're not yet comfortable with the other data structures available in matlab... like cell arrays and structures. You could easily solve this problem by storing your data in a less arrays and then indexing them properly when needed.
Read about structures (this tutorial is excellent) in the matlab documentation and then try to use one to store all of your data. I think that will solve this problem and many others you didn't know you had.
You should be using something like the following.
ET = struct;
ET.A.C(1) = ET1_A_C1;
ET.A.C(2) = ET1_A_C2;
...
ET.A.C(N) = ET1_A_CN;
ET.H.C(1) = ET1_H_C1;
ET.H.C(2) = ET1_H_C2;
...
ET.H.C(N) = ET1_H_CN;
Now every thing is one variable which you can save without typing anything extra.
filename=Total_data.mat;
for i=1:63
J(i,1)=ET1_A_C{i};
J(i,2)=ET1_H_C{i};
end
save(filename,'J(1:63,1)','J(1:63,2)');
What is the best way to do random sample with replacement from dataset? I am using 316 * 34 as my dataset. I want to segment the data into three buckets but with replacement. Should I use the randperm because I need to make sure I keep the index intact where that index would be handy in identifying the label data. I am new to matlab I saw there are couple of random sample methods but they didn't look like its doing what I am looking for, its strange to think that something like doesn't exist in matlab, but I did the follwoing:
My issue is when I do this row_idx = round(rand(1)*316) sometimes I get zero, that leads to two questions
what should I do to avoid zeor?
What is the best way to do the random sample with replacement.
shuffle_X = X(randperm(size(X,1)),:);
lengthOf_shuffle_X = length(shuffle_X)
number_of_rows_per_bucket = round(lengthOf_shuffle_X / 3)
bucket_cell = cell(3,1)
bag_matrix = []
for k = 1:length(bucket_cell)
for i = 1:number_of_rows_per_bucket
row_idx = round(rand(1)*316)
bag_matrix(i,:) = shuffle_X(row_idx,:)
end
bucket_cell{k} = bag_matrix
end
I could do following:
if row_idx == 0
row_idx = round(rand(1)*316)
assuming random number will never give two zeros values in two consecutive rounds.
randi is a good way to get integer indices for sampling with replacement. Assuming you want to fill three buckets with an equal number of samples, then you can write
data = rand(316,34); %# create some dummy data
number_of_data = size(data,1);
number_of_rows_per_bucket = 50;
bucket_cell = cell(1,3);
idx = randi([1,number_of_data],[number_of_rows_per_bucket,3]);
for iBucket = 1:3
bucket_cell{iBucket} = data(idx(:,iBucket),:);
end
To the question: if you use randperm it will give you a draw order without replacement, since you can draw any item once.
If you use randi it draws you with replacement, that is you draw an item possibly many times.
If you want to "segment" a dataset, that usually means you split the dataset into three distinct sets. For that you use draw without replacement (you don't put the items back; use randperm). If you'd do it with replacement (using randi), it will be incredibly slow, since after some time the chance that you draw an item which you have not before is very low.
(Details in coupon collector ).
If you need a segmentation that is a split, you can just go over the elements and independently decide where to put it. (That is you choose a bucket for each item with replacement -- that is you put any chosen bucket back into the game.)
For that:
% if your data items are vectors say data = [1 1; 2 2; 3 3; 4 4]
num_data = length(data);
bucket_labels = randi(3,[1,num_data]); % draw a bucket label for each item, independently.
for i=1:3
bucket{i} = data(bucket_labels==i,:);
end
%if your data items are scalars say data = [1 2 3 4 5]
num_data = length(data);
bucket_labels = randi(3,[1,num_data]);
for i=1:3
bucket{i} = data(bucket_labels==i);
end
there we go.
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