How to generate dataset in one file instead of separate frams?
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I have a code below which save data on different frame but i want to save in one file because i need to convert them in HDF5 later on. the code is taken from link:
https://www.mathworks.com/help/deeplearning/ug/modulation-classification-with-deep-learning.html
dataDirectory = "E:\Thesis\SNR-dataset\new";
disp("Data file directory is " + dataDirectory)
%%
fileNameRoot = "frame";
% Check if data files exist
dataFilesExist = false;
if exist(dataDirectory,'dir')
files = dir(fullfile(dataDirectory,sprintf("%s*",fileNameRoot)));
if length(files) == numModulationTypes*numFramesPerModType
dataFilesExist = true;
end
end
if ~dataFilesExist
disp("Generating data and saving in data files...")
[success,msg,msgID] = mkdir(dataDirectory);
if ~success
error(msgID,msg)
end
for modType = 1:numModulationTypes
fprintf('%s - Generating %s frames\n', ...
datestr(toc/86400,'HH:MM:SS'), modulationTypes(modType))
label = modulationTypes(modType);
numSymbols = (numFramesPerModType / sps);
dataSrc = helperModClassGetSource(modulationTypes(modType), sps, 2*spf, fs);
modulator = helperModClassGetModulator(modulationTypes(modType), sps, fs);
if contains(char(modulationTypes(modType)), {'B-FM','DSB-AM','SSB-AM'})
% Analog modulation types use a center frequency of 100 MHz
channel.CenterFrequency = 100e6;
else
% Digital modulation types use a center frequency of 902 MHz
channel.CenterFrequency = 902e6;
end
for p=1:numFramesPerModType
% Generate random data
x = dataSrc();
%size(x)
% Modulate
y = modulator(x);
%size(y)
% Pass through independent channels
release(channel)
rxSamples = channel(y);
% Remove transients from the beginning, trim to size, and normalize
frame = helperModClassFrameGenerator(rxSamples, spf, spf, transDelay, sps);
% Save data file
fileName = fullfile(dataDirectory,...
sprintf("%s%s%03d",fileNameRoot,modulationTypes(modType),p));
save(fileName,"frame","label")
end
end
else
disp("Data files exist. Skip data generation.")
end%%
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