How do I average a matrix in steps but they are not all in equal steps

I have a matrix of 2214 by 8001, the absorbances were measured 5 times for each sample but some signals were were not good enough so they were removed during data cleaning. Now the matrix is left with 3, 4 or 5 signals per sample. They are no longer all 5 signals per sample. I need help with a code to create an average matrix.....xxx by 8001 since I cannot use reshape for this particular problem.

Thank You

[Radu Andrei Matei]

Hi, I think you should try to phrase your question more independently of your discipline, I don't know what an "absorbance" is for example. Could you try to explain what you need in more mathematical and/or programming terms?

[Image Analyst]

What do the rows and columns of your matrix represent? Do you have 3, 4, or 5 of those matrices?

If you have any more questions, then attach your data and code to read it in with the paperclip icon after you read this:

TUTORIAL: How to ask a question (on Answers) and get a fast answer

[NCA]

Apologies, if my question was not clear.

The matrix contains 2214 rows by 8001 coloums

Each sample measurement is repeated 5 times but I have removed some bad ones now I am left with some samples with only 3 or 4 runs. I need a code to average the samples. I cant use reshape because they are not in equal steps of 5 any longer.If it helps see below representation using 11 rows of imaginary samples

Sample 1

Sample 1

Sample1

Sample 2

Sample 2

Sample 2

Sample 2

Sample 2

Sample 3

Sample 3

Sample 3

Sample 3

etc etc

Answer 1

[Maneet Kaur Bagga]

Hi @NCA

As per my understanding of the question, when the data cleaning is being done and followed by this we want to do data labelling we can use the following approach:

• Create a table where each row is labelled to which sample it belongs
• Extract all the signal values related to a particular sample
• Then calculating the average of above we get the average signal value and store it in an array

You may refer to the below code for the understanding of above steps:

rng(0);
xdata = randi([0 10], 5,3);
sample_no = [1 1 2 2 2]'; 

% creating a table at the time of data cleaning. 
t = table(xdata,sample_no,'VariableNames',[ "Data", "SampleNo"]);
disp("table");
display(t)

unique_samples = unique(t.SampleNo); % Unique signals 

avgSignals = zeros(numel(unique_samples), 3); %to store the average signal values. 

for i = 1:numel(unique_samples) 
    data_for_sample_i = t{t.SampleNo == i, "Data"}; %extracting signal values that belong to sample i.
    average = mean(data_for_sample_i,1); %taking mean of the extracted signal values.
    avgSignals(i,:) = average;


end
disp("average signal values");
disp(avgSignals);

You may refer to the following documentation for better understanding

Table:

https://www.mathworks.com/help/matlab/tables.html

Data Cleaning and Calculations in Table:

https://www.mathworks.com/help/matlab/matlab_prog/computations-with-numeric-data-in-table-or-timetable.html

I hope this helps!

Thank You!

Maneet Bagga