workflow_id = "periodic_meta_summaries"
if delete_existing_workflows:
hyperstream.workflow_manager.delete_workflow(workflow_id)
try:
w = hyperstream.workflow_manager.workflows[workflow_id]
except KeyError:
w = create_workflow_meta_summariser(hyperstream, safe=False)
hyperstream.workflow_manager.commit_workflow(workflow_id)
time_interval = TimeInterval.now_minus(days=2)
w.execute(time_interval)
M = hyperstream.channel_manager.memory
print('number of non_empty_streams: {}'.format(
len(hyperstream.channel_manager.memory.non_empty_streams)))
print 12345
if __name__ == '__main__':
import sys
from os import path
sys.path.insert(0, path.dirname(path.dirname(path.abspath(__file__))))
from sphere_plugins.sphere.utils import ArgumentParser
args = ArgumentParser.logging_parser(default_loglevel=logging.INFO)
run(delete_existing_workflows=True, loglevel=args.loglevel)
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
# DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
# OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE
# OR OTHER DEALINGS IN THE SOFTWARE.
import logging
import sys
from os import path
def run(house, loglevel=logging.INFO):
from hyperstream import HyperStream
from workflows.asset_splitter import split_sphere_assets
hyperstream = HyperStream(loglevel=loglevel, file_logger=None)
split_sphere_assets(hyperstream, house=house)
if __name__ == '__main__':
sys.path.insert(0, path.dirname(path.dirname(path.abspath(__file__))))
from sphere_plugins.sphere.utils import ArgumentParser
args = ArgumentParser.wearable_list_parser(default_loglevel=logging.INFO)
delete_existing_workflows = True
run(args.house, args.loglevel)
format(model_name))
for experiment_id in list(experiment_ids):
print("Experiment id: {}".format(experiment_id))
print("Time interval: {}".format(
reconstruct_interval(experiment_id)))
print("Accuracy: {}".format(
pformat(model['performance'][experiment_id]['accuracy'])))
print("Macro F1: {}".format(
pformat(
model['performance'][experiment_id]['f1_score_macro'])))
print("Micro F1: {}".format(
pformat(
model['performance'][experiment_id]['f1_score_micro'])))
print("Confusion Matrix:")
pprint(model['performance'][experiment_id]['confusion_matrix'])
print("")
return True
if __name__ == '__main__':
from os import path
sys.path.insert(0, path.dirname(path.dirname(path.abspath(__file__))))
from sphere_plugins.sphere.utils import ArgumentParser
args = ArgumentParser.technician_selection_parser(
default_loglevel=logging.INFO)
run(house=args.house,
selection=map(int, args.technicians_selection),
loglevel=args.loglevel)
# df = M.find_stream(name='experiments_dataframe', house=house).window().values()[0]
# if len(df) > 0:
if False:
# arrow.get(x).humanize()
# df['start'] = df['start'].map('{:%Y-%m-%d %H:%M:%S}'.format)
df['duration'] = df['end'] - df['start']
df['start'] = map(lambda x: '{:%Y-%m-%d %H:%M:%S}'.format(x), df['start'])
df['end'] = map(lambda x: '{:%Y-%m-%d %H:%M:%S}'.format(x), df['end'])
# df['duration'] = map(lambda x:'{:%Mmin %Ssec}'.format(x),df['duration'])
df['start_as_text'] = map(lambda x: arrow.get(x).humanize(), df['start'])
df['duration_as_text'] = map(lambda x: duration2str(x), df['duration'])
pd.set_option('display.width', 1000)
print(df[['id', 'start_as_text', 'duration_as_text', 'start', 'end', 'annotator']].to_string(index=False))
return True
else:
print("DataFrame is empty")
return False
if __name__ == '__main__':
import sys
from os import path
sys.path.insert(0, path.dirname(path.dirname(path.abspath(__file__))))
from sphere_plugins.sphere.utils import ArgumentParser
args = ArgumentParser.wearable_tap_sync_parser(default_loglevel=logging.INFO)
run(args.house, args.time, delete_existing_workflows=True, loglevel=args.loglevel)