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)
