from loaders import DataLoader import matplotlib.pyplot as plt loader = DataLoader() datasets_dict = { 'ERN': loader.get_ern, 'SMR': lambda validation=False, subject=2: loader.get_smr( subject, validation), # noqa 'BMNIST': loader.get_bmnist11, # 'BMNIST_2': loader.get_bmnist2, 'SEED': loader.get_seed, # 'ThoughtViz': loader.get_thoughtviz, } datasets = [[k, datasets_dict[k]] for k in datasets_dict] k = 'A' for dname, ldr in datasets: fig, axes = plt.subplots(1, 1) p = ldr(validation=True) data = p['data'][0][-10, :, 0].reshape(-1, ) loader.topoplot(p['name'], data) axes.set_title('({}) Topoplot for {}'.format(k, p['name'])) fig.savefig('./topoplot_new/{}_topoplot_new.png'.format(dname)) k = chr(ord(k) + 1) print('Done {}, {}'.format(dname, p['name']))
{'num_gru': [32,150],#2**i for i in range(5,7)], 'pool1D': [True, False], 'has2D': [True], 'pool2D': [True,False], 'poolAvg': [True, False]} ] loader = DataLoader() list_splits = [] X = [] X_t = [] Y = [] Y_t = [] train_size = 0 for i in range(1): d = loader.get_smr(subject=i, return_idx=True) data = d['data'] X.append(data[0]) X_t.append(data[2]) Y.append(data[1]) Y_t.append(data[3]) list_splits.append(d['data_idx']) train_size+=data[0].shape[0] list_splits = [[i[0], i[1] + train_size] for i in list_splits] list_splits = [[np.append(i[0], i[1], axis=0), i[1]] for i in list_splits] X = np.concatenate(X, axis=0) X_t = np.concatenate(X_t, axis=0) X = np.append(X, X_t, axis=0) Y = np.concatenate(Y, axis=0)