How are you loading in the data? If you're currently using readtable(), I strongly encourage you to instead use textscan(). In doing so you will learn about format specifications for parsing text, which is incredibly useful, and will provide you with skills that generalize to other languages. Moreover, it is much faster when than readtable(). Mind you it's not a huge timecost if you're only dealing with a couple of files.
Here is a function you can use to batch-read in all of your data files. If you run it line-by-line as a script, you'll get a better idea as to what's going on. Generally, it is much easier to manipulate data when it is in matrix form (as opossed to tables), especially if you're only dealing with numeric data!
function out = getMyData(idx)
if nargin < 1 || ~exist('idx', 'var') || isempty(idx)
warning('No argument supplied for idx. Using default values.');
idx = 1:16;
end
if ~isnumeric(idx)
error('idx must be a numeric vector of integers from 1:16')
end
%% Use GUI for file lookup
[fileNames, fileDir]=uigetfile('MultiSelect','On','*.txt');
%% Get the file count
% Account for case of single trial selection
if ischar(fileNames)
fileNames = cellstr(fileNames);
end
FILEcount = numel(fileNames);
%% Determine number and name of headers
fid = fopen(fullfile(fileDir, fileNames{1}),'r');
headerNames = strsplit(fgetl(fid), ', ');
fclose(fid);
%% Specify formatSpec
formSpec = [repelem({'%*f'}, 1, numel(headerNames)), {'\r\n'}];
formSpec(idx) = {'%f'};
% Preallocate cell for data import
out = cell(FILEcount, 1);
% Loop to load in all files needed
for ii = 1:numel(fileNames)
try
fid = fopen(fullfile(fileDir, fileNames{ii}),'r');
out{ii} = single(cell2mat(textscan(fid,[formSpec{:}],...
'HeaderLines', 1, 'Delimiter',',')));
fclose(fid);
catch ME
warning('There was a problem loading file: %s', fileNames{ii});
end
end
end
The input argument, idx allows you to specify variables to be read-in by using the numeric index of the corresponding header, n. If you're finding it difficult to keep track of which variable is which, you can always modify the function to give you the headerNames variable in the output as well.
So, let's say I want to get the percentage ratio of AccelX from IMUREF.txt to the first m observations of AccelX in IMUDATA.txt.
% let's just to convert to matrix for demonstration purposes
% certainly possible to index into the cells, without much difficulty, however
% e.g. data{1}(:,2) for the AccelX column vector of IMUDATA.txt
a = data{1};
b = data{2};
cmpidxs = length(b);
my_X_accel_proportion = b(:,2) ./ a(1:cmpidxs,2)
my_X_accel_difference = b(:,2) - a(1:cmpidxs,2)
Most likely, you're going to want to get some functions together to streamline your analysis pipeline. Use what you can.
