I want to store efficiently some numbers as strings (with different lengths) into a table. This is my code:
% Table with numbers
n = 5;
m = 5;
T_numb = array2table((rand(n,m)));
% I create a table with empty cells (to store strings)
T_string = array2table(cell(n,m));
for i = 1:height(T_numb)
for ii = 1:width(T_numb)
T_string{i,ii} = cellstr(num2str(T_numb{i,ii}, '%.2f'));
end
end
What could I do to improve it? Thank you.
I don't have access to the function cell2table right now, but using the undocumented function sprintfc might work well here (check here for details).
For instance:
%// 2D array
a = magic(5)
b = sprintfc('%0.2f',a)
generates a cell array like this:
b =
'17.00' '24.00' '1.00' '8.00' '15.00'
'23.00' '5.00' '7.00' '14.00' '16.00'
'4.00' '6.00' '13.00' '20.00' '22.00'
'10.00' '12.00' '19.00' '21.00' '3.00'
'11.00' '18.00' '25.00' '2.00' '9.00'
which you can convert to a table using cell2table.
So in 1 line:
YourTable = cell2table(sprintfc('%0.2f',a))
This seems to be quite fast -
T_string = cell2table(reshape(strtrim(cellstr(num2str(A(:),'%.2f'))),size(A)))
Or with regexprep to replace strtrim -
cell2table(reshape(regexprep(cellstr(num2str(A(:),'%.2f')),'\s*',''),size(A)))
Here, A is the 2D input numeric array.
Related
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.
I am writing a code to do some very simple descriptive statistics, but I found myself being very repetitive with my syntax.
I know there's a way to shorten this code and make it more elegant and time efficient with something like a for-loop, but I am not quite keen enough in coding (yet) to know how to do this...
I have three variables, or groups (All data, condition 1, and condition 2). I also have 8 matlab functions that I need to perform on each of the three groups (e.g mean, median). I am saving all of the data in a table where each column corresponds to one of the functions (e.g. mean) and each row is that function performed on the correspnding group (e.g. (1,1) is mean of 'all data', (2,1) is mean of 'cond 1', and (3,1) is mean of 'cond 2'). It is important to preserve this structure as I am outputting to a csv file that I can open in excel. The columns, again, are labeled according the function, and the rows are ordered by 1) all data 2) cond 1, and 3) cond 2.
The data I am working with is in the second column of these matrices, by the way.
So here is the tedious way I am accomplishing this:
x = cell(3,8);
x{1,1} = mean(alldata(:,2));
x{2,1} = mean(cond1data(:,2));
x{3,1} = mean(cond2data(:,2));
x{1,2} = median(alldata(:,2));
x{2,2} = median(cond1data(:,2));
x{3,2} = median(cond2data(:,2));
x{1,3} = std(alldata(:,2));
x{2,3} = std(cond1data(:,2));
x{3,3} = std(cond2data(:,2));
x{1,4} = var(alldata(:,2)); % variance
x{2,4} = var(cond1data(:,2));
x{3,4} = var(cond2data(:,2));
x{1,5} = range(alldata(:,2));
x{2,5} = range(cond1data(:,2));
x{3,5} = range(cond2data(:,2));
x{1,6} = iqr(alldata(:,2)); % inter quartile range
x{2,6} = iqr(cond1data(:,2));
x{3,6} = iqr(cond2data(:,2));
x{1,7} = skewness(alldata(:,2));
x{2,7} = skewness(cond1data(:,2));
x{3,7} = skewness(cond2data(:,2));
x{1,8} = kurtosis(alldata(:,2));
x{2,8} = kurtosis(cond1data(:,2));
x{3,8} = kurtosis(cond2data(:,2));
% write output to .csv file using cell to table conversion
T = cell2table(x, 'VariableNames',{'mean', 'median', 'stddev', 'variance', 'range', 'IQR', 'skewness', 'kurtosis'});
writetable(T,'descriptivestats.csv')
I know there is a way to loop through this stuff and get the same output in a much shorter code. I tried to write a for-loop but I am just confusing myself and not sure how to do this. I'll include it anyway so maybe you can get an idea of what I'm trying to do.
x = cell(3,8);
data = [alldata, cond2data, cond2data];
dfunction = ['mean', 'median', 'std', 'var', 'range', 'iqr', 'skewness', 'kurtosis'];
for i = 1:8,
for y = 1:3
x{y,i} = dfucntion(i)(data(1)(:,2));
x{y+1,i} = dfunction(i)(data(2)(:,2));
x{y+2,i} = dfunction(i)(data(3)(:,2));
end
end
T = cell2table(x, 'VariableNames',{'mean', 'median', 'stddev', 'variance', 'range', 'IQR', 'skewness', 'kurtosis'});
writetable(T,'descriptivestats.csv')
Any ideas on how to make this work??
You want to use a cell array of function handles. The easiest way to do that is to use the # operator, as in
dfunctions = {#mean, #median, #std, #var, #range, #iqr, #skewness, #kurtosis};
Also, you want to combine your three data variables into one variable, to make it easier to iterate over them. There are two choices I can see. If your data variables are all M-by-2 in dimension, you could concatenate them into a M-by-2-by-3 three-dimensional array. You could do that with
data = cat(3, alldata, cond1data, cond2data);
The indexing expression into data that retrieves the values you want would be data(:, 2, y). That said, I think this approach would have to copy a lot of data around and probably isn't the best for performance. The other way to combine data together is in 1-by-3 cell array, like this:
data = {alldata, cond1data, cond2data};
The indexing expression into data that retrieves the values you want in this case would be data{y}(:, 2).
Since you are looping from y == 1 to y == 3, you only need one line in your inner loop body, not three.
for y = 1:3
x{y, i} = dfunctions{i}(data{y}(:,2));
end
Finally, to get the cell array of strings containing function names to pass to cell2table, you can use cellfun to apply func2str to each element of dfunctions:
funcnames = cellfun(#func2str, dfunctions, 'UniformOutput', false);
The final version looks like this:
dfunctions = {#mean, #median, #std, #var, #range, #iqr, #skewness, #kurtosis};
data = {alldata, cond1data, cond2data};
x = cell(length(data), length(dfunctions));
for i = 1:length(dfunctions)
for y = 1:length(data)
x{y, i} = dfunctions{i}(data{y}(:,2));
end
end
funcnames = cellfun(#func2str, dfunctions, 'UniformOutput', false);
T = cell2table(x, 'VariableNames', funcnames);
writetable(T,'descriptivestats.csv');
You can create a cell array of functions using str2func :
function_string = {'mean', 'median', 'std', 'var', 'range', 'iqr', 'skewness', 'kurtosis'};
dfunction = {};
for ii = 1:length(function_string)
fun{ii} = str2func(function_string{ii})
end
Then you can use it on your data as you'd like to :
for ii = 1:8,
for y = 1:3
x{y,i} = dfucntion{ii}(data(1)(:,2));
x{y+1,i} = dfunction{ii}(data(2)(:,2));
x{y+2,i} = dfunction{ii}(data(3)(:,2));
end
end
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 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