Restructured the code and added the code to load the data.

IOHelper.py

+from config import general_params as params
+from config import CNN_params as CNN_params
+import numpy as np
+import scipy.io as sio
+import os
+# import torch as torch
+
+train_data_path = params['train_data_path']
+
+def get_data(verbose=True):
+    """
+        Load the data for training.
+        :param datapath: matlab data directory
+        :param variable: variable of the matlab file
+        :return: the data as numpy array / Tensor?
+    """
+    train_data = torch_training_data(train_data_path, verbose)
+    return train_data
+
+def torch_training_data(train_data_path, verbose=True):
+    """
+    Extract training data from the file.
+    :param train_data_path: name of the file to open.
+    :param verbose: boolean; if true, it prints information about
+    the status of the program.
+    :return: a numpy array of shape ...?
+    """
+    if verbose: print("Loading data... ")
+    if verbose: print("Extracting trials...")
+    trials = extract_trials()
+    if verbose: print(len(trials), " trials found.")
+
+    full_data = []
+    for i in range(5):
+        next_trial = load_matlab_trial(datapath=train_data_path, trial=trials[i], filename=CNN_params['filename'], variable=CNN_params['data_variable'])
+        full_data.append(next_trial.tolist()[0][0])
+
+    if verbose: print("data loaded.")
+    print(np.shape(full_data))
+    if verbose: print("Tensoring data..")
+    if verbose: print("not implemented yet")
+    return full_data
+
+def load_matlab_trial(datapath, trial, filename, variable):
+    """
+    Load the data from Matlab
+    :param datapath: matlab data directory
+    :param filename: name of the file from which the data must be loaded
+    :param variable: variable of the matlab file
+    :return: the data as numpy array
+    """
+    data = sio.loadmat(datapath + trial + "/" + filename)[filename][variable]
+    return data
+
+def extract_trials():
+    """
+        Extracts the trials from the root directory
+    """
+    my_list = os.listdir(train_data_path)
+    trials = [name for name in my_list if len(name) == 3]
+    return trials
\ No newline at end of file

config.py

+# configuration used by the training and evaluation methods
+# let's keep it here to have a clean code on other methods that we try
+general_params = {}
+CNN_params = {}
+
+"""
+Models:
+
+CNN-1: First try: CNN to predict movement towards left or right (prosaccade) with 1 second data.
+RNN? Transformers, Attention, etc etc
+"""
+
+# general parameters
+general_params['model'] = "CNN-1"
+general_params['train_data_path'] = "/Volumes/methlab/ETH_AS/preprocessed2/"
+
+# CNN - 1
+CNN_params['data_variable'] = "data"
+CNN_params['filename'] = "EEGprocue"

main.py

+from config import general_params as params
+from IOHelper import get_data
+import time
+
+def main():
+    start_time = time.time()
+    if params['model'] == 'CNN-1':
+        print("Started running CNN-1. If you want to run other methods please choose another model in the config.py file.")
+        get_data()
+    else:
+        raise Exception('Please choose one of the following models in the config.py file')
+
+    print("--- Runtime: %s seconds ---" % (time.time() - start_time))
+
+if __name__=='__main__':
+    main()