def build_from_time(subject_id, valid_epochs):
# circadian_feature = TimeBasedFeatureService.build_circadian_model(subject_id, valid_epochs)
cosine_feature = TimeBasedFeatureService.build_cosine(valid_epochs)
time_feature = TimeBasedFeatureService.build_time(valid_epochs)
# TimeBasedFeatureService.write_circadian_model(subject_id, circadian_feature)
TimeBasedFeatureService.write_cosine(subject_id, cosine_feature)
TimeBasedFeatureService.write_time(subject_id, time_feature)
def build_from_time(subject_id, valid_epochs):
if Constants.INCLUDE_CIRCADIAN:
circadian_feature = TimeBasedFeatureService.build_circadian_model(
subject_id, valid_epochs)
TimeBasedFeatureService.write_circadian_model(
subject_id, circadian_feature)
cosine_feature = TimeBasedFeatureService.build_cosine(valid_epochs)
time_feature = TimeBasedFeatureService.build_time(valid_epochs)
TimeBasedFeatureService.write_cosine(subject_id, cosine_feature)
TimeBasedFeatureService.write_time(subject_id, time_feature)
def build(file_id):
if Constants.VERBOSE:
print('Building MESA subject ' + file_id + '...')
raw_labeled_sleep = MesaPSGService.load_raw(file_id)
heart_rate_collection = MesaHeartRateService.load_raw(file_id)
activity_count_collection = MesaActigraphyService.load_raw(file_id)
circadian_model = MesaTimeBasedService.load_circadian_model(file_id)
if activity_count_collection.data[0][0] != -1 and circadian_model is not None:
circadian_model = utils.remove_nans(circadian_model)
interval = Interval(start_time=0, end_time=np.shape(raw_labeled_sleep)[0])
activity_count_collection = ActivityCountService.crop(activity_count_collection, interval)
heart_rate_collection = HeartRateService.crop(heart_rate_collection, interval)
valid_epochs = []
for timestamp in range(interval.start_time, interval.end_time, Epoch.DURATION):
epoch = Epoch(timestamp=timestamp, index=len(valid_epochs))
activity_count_indices = ActivityCountFeatureService.get_window(activity_count_collection.timestamps,
epoch)
heart_rate_indices = HeartRateFeatureService.get_window(heart_rate_collection.timestamps, epoch)
if len(activity_count_indices) > 0 and 0 not in heart_rate_collection.values[heart_rate_indices]:
valid_epochs.append(epoch)
else:
pass
labeled_sleep = np.expand_dims(
MesaPSGService.crop(psg_labels=raw_labeled_sleep, valid_epochs=valid_epochs),
axis=1)
feature_count = ActivityCountFeatureService.build_from_collection(activity_count_collection,
valid_epochs)
feature_hr = HeartRateFeatureService.build_from_collection(heart_rate_collection, valid_epochs)
feature_time = np.expand_dims(TimeBasedFeatureService.build_time(valid_epochs), axis=1)
feature_cosine = np.expand_dims(TimeBasedFeatureService.build_cosine(valid_epochs), axis=1)
feature_circadian = TimeBasedFeatureService.build_circadian_model_from_raw(circadian_model,
valid_epochs)
feature_dictionary = {FeatureType.count: feature_count,
FeatureType.heart_rate: feature_hr,
FeatureType.time: feature_time,
FeatureType.circadian_model: feature_circadian,
FeatureType.cosine: feature_cosine}
subject = Subject(subject_id=file_id,
labeled_sleep=labeled_sleep,
feature_dictionary=feature_dictionary)
# Uncomment to save files for all subjects
# ax = plt.subplot(5, 1, 1)
# ax.plot(range(len(feature_hr)), feature_hr)
# ax = plt.subplot(5, 1, 2)
# ax.plot(range(len(feature_count)), feature_count)
# ax = plt.subplot(5, 1, 3)
# ax.plot(range(len(feature_cosine)), feature_cosine)
# ax = plt.subplot(5, 1, 4)
# ax.plot(range(len(feature_circadian)), feature_circadian)
# ax = plt.subplot(5, 1, 5)
# ax.plot(range(len(labeled_sleep)), labeled_sleep)
#
# plt.savefig(str(Constants.FIGURE_FILE_PATH.joinpath(file_id + '.png')))
# plt.close()
return subject