This repo has 3 files

batched_analysis.m

Analyses the data using a batched approach, where the data is segmented using the retun_batch.m function.

Batches are defined by the user and subsampling frequencies are set in the file get_variables.m

Right now, it appends the new batches, which may be potentially slow

TODO: Precalculate the size of the spectrogram to generate a nameholder matrix to populate

Parallelize the computation of the batches to further speed up the calculations.

read_data.m

This file reads the full set of data and plots the coefficients in a heatmap without any batching. Since it reads the whole set of data from file, it can run into very large delays, and may not be able to calculate the full spectrogram either.

findNearest.m

This function matches the indexes of the original value and the samples generated by the spectrogram function

labelize.m

This functions accepts a threshold and float array and creates 0s and 1s labels

return_batch.m

Using the variables concerning the original sampling rate and the data file, it returns specific batches of data the user can specify the batch of data as well as the size The function is debugged for the case when the batches are large than the data, and for the case where the last batched may be incomplete

get_variables.m

Function to consolidate all the variables of interest from all the programs, so there are no coding mistakes