def process_kitchen(self):
# TODO: add sensor type as a column
activity = self.datasets['activity']
activity = localize_time(activity, ['start_date'])
doors = self.datasets['doors']
appliances = map_devices(self.datasets['appliances'],
self.datasets['device_types'])
doors = doors[(doors.location_name == 'fridge door')
& (doors.transition == 'opened>closed')]
activity = activity[activity.location_name.isin(['kitchen',
'dining room'])]
activity.insert(0, 'device_type', 'pir')
doors.insert(0, 'device_type', 'door')
appliances.value = appliances.value.astype(str)\
.replace({'microwave-use': 'oven-use',
'toaster-use': 'oven-use', 'iron-use': np.nan,
'multi-use socket-use': np.nan})
doors = doors[['patient_id', 'start_date', 'device_type','location_name']]\
.rename({'location_name': 'activity'}, axis=1)
activity = activity[['patient_id', 'start_date', 'device_type', 'location_name']]\
.rename({'location_name': 'activity'}, axis=1)
appliances = appliances[['patient_id', 'start_date', 'device_type', 'value']]\
.rename({'value': 'activity'}, axis=1)
kitchen = pd.concat([doors, activity, appliances.dropna()])
kitchen = kitchen[kitchen.patient_id != ''].sort_values(
['patient_id', 'start_date'])
kitchen = process_transition(kitchen, ['patient_id'], 'start_date',
'activity', ['device_type'])
return kitchen.reset_index(drop=True)
def process_doors(self):
groupby = ['patient_id', 'location_name']
datetime = 'start_date'
value = 'value'
covariates = ['location_name']
df = self.datasets['door']
df = localize_time(df, ['start_date'])
doors = process_transition(df, groupby, datetime, value, covariates)
return doors.drop('location_name', axis=1).reset_index()
def process_doors(self):
df = self.datasets['observation']
columns = ['subject', 'location', 'datetimeObserved', 'valueState', 'type']
df = (df[columns].query('type == "224751004"').dropna(
subset=['location']).drop(columns='type'))
df.columns = ['patient_id', 'location_name', 'start_date', 'value']
df.value = df.value.replace({'Close': 'closed', 'Open': 'opened'})
groupby = ['patient_id', 'location_name']
datetime = 'start_date'
value = 'value'
covariates = None
df = localize_time(df, ['start_date'])
doors = process_transition(df, groupby, datetime, value, covariates)
doors = doors.reset_index()
doors.location_name = doors.location_name.str.lower()
return doors
def process_transitions(self):
motion = self.datasets['motion']
motion = process_transition(motion, ['patient_id'], 'start_date',
'location_name')
return motion.reset_index()