"""

Load validation data from .npy files.

"""

X = np.load(os.path.join(DATA_DIR, 'pre-X-validate.npy'))

m = np.load(os.path.join(DATA_DIR, 'pre-m-validate.npy'))

ids = m[:, 0].astype(int)

# let's take mm2

mult = m[:, 1]

# let's take mm3

# mult = m[:, 2]

X = X.astype(np.float32)

X /= 255

"""

Accumulate results per study (because one study has many SAX slices),

so the averaged CDF for all slices is returned.

"""

sum_result = {}

cnt_result = {}

size = prob.shape[0]

for i in range(size):

study_id = ids[i]

idx = int(study_id)

if idx not in cnt_result:

cnt_result[idx] = 0.

sum_result[idx] = np.zeros((1, prob.shape[1]), dtype=np.float32)

cnt_result[idx] += 1

sum_result[idx] += prob[i, :]

for i in cnt_result.keys():

sum_result[i][:] /= cnt_result[i]

model_systole = get_model()

model_diastole = get_model()

print('Loading models weights...')

model_systole.load_weights(config.systole_weights)

model_diastole.load_weights(config.diastole_weights)

# load val losses to use as sigmas for CDF

with open(config.val_loss_systole, 'r') as f:

val_loss_systole = float(f.readline())

with open(config.val_loss_diastole, 'r') as f:

val_loss_diastole = float(f.readline())

print('Loading validation data...')

X, ids, mult = load_validation_data()

batch_size = 32

print('Predicting on validation data...')

pred_normed_systole = model_systole.predict(X, batch_size=batch_size, verbose=1)

pred_normed_diastole = model_diastole.predict(X, batch_size=batch_size, verbose=1)

print('Normed_systole:', pred_normed_systole.shape)

print('Normed_diastole:', pred_normed_diastole.shape)

print('mult:', mult.shape)

pred_systole = pred_normed_systole[:,0] * mult

pred_diastole = pred_normed_diastole[:,0] * mult

print('systole:', pred_systole.shape)

print('diastole:', pred_diastole.shape)

# real predictions to CDF

cdf_pred_systole = real_to_cdf(pred_systole, val_loss_systole)

cdf_pred_diastole = real_to_cdf(pred_diastole, val_loss_diastole)

print('Accumulating results...')

sub_systole = accumulate_study_results(ids, cdf_pred_systole)

sub_diastole = accumulate_study_results(ids, cdf_pred_diastole)

# write to submission file

print('Writing submission to file...')

fi = csv.reader(open('/data/sample_submission_validate.csv'))

f = open(config.submission, 'w')

fo = csv.writer(f, lineterminator='\n')

fo.writerow(next(fi))

for line in fi:

idx = line[0]

key, target = idx.split('_')

key = int(key)

out = [idx]

if key in sub_systole:

if target == 'Diastole':

out.extend(list(sub_diastole[key][0]))

else:

out.extend(list(sub_systole[key][0]))

else:

print('Miss {0}'.format(idx))

fo.writerow(out)

f.close()