from brain_matrix import BrainMatrix

from utils import Timer

import pandas as pd

#import seaborn as sns

if __name__ == '__main__':

features = ['language',

'music',

'navigation',

'spatial',

'reading',

'action',

'hippocampus',

'auditory',

'broca',

'gestures',

'hearing',

'learning',

'motor',

'movement',

'speech',

'syntactic',

'verbal',

'visuospatial']

folds = [features[a:b] for a, b in [(0,6), (6,12), (12,18)]]

data = []

with open('times.txt', 'w+') as log:

for fold_id, fold in enumerate(folds):

for ds in range(6,11):

with Timer('DOWNSAMPLED BY {ds}\n'.format_map(locals()),

print_func=log.write) as t:

matrix = BrainMatrix('emd', downsample=ds, name='validation')

matrix.compute_distances(fold)

inconsistency = matrix.plot_dendrogram()

stress = matrix.plot_mds(metric=False)

data.append([ds, fold_id, t.elapsed, inconsistency, stress])

df = pd.DataFrame(columns=['downsample', 'fold', 'time', 'inconsistency', 'stress'], data=data)

df.to_pickle('validation.pkl')

#f, ax = sns.plt.subplots(figsize=(7, 7))

#ax.set(yscale="log")

#sns.pointplot(x='features', y='time', hue='downsample', data=df)

#sns.plt.show()