def transform_to_categorized_data_one_user(user_id):
out_path_prefix = "/speech/dbwork/mul/students/dehajjik/categorized_data/"
data_key = "data"
metadata_key = "metadata"
print "loading data for user "+str(user_id)
nontransformed_data = DataExtractor.load_json_data(user_id)
#nontransformed_data = JsonUtils.load_json_data("/home/dehajjik/workspace/resources/sample_data_for_location_categorization_test.json")
#the transfomers responsible for the features of the data categorization
feature_transformers = {LocationTransformer.transformed_feature_name: LocationTransformer(nontransformed_data),
NotificationTransformer.transformed_feature_name : NotificationTransformer(nontransformed_data),
ApplaunchTransformer.transformed_feature_name : ApplaunchTransformer(nontransformed_data),
BatteryTransformer.transformed_feature_name: BatteryTransformer(nontransformed_data),
HeadsetTransformer.transformed_feature_name: HeadsetTransformer(nontransformed_data),
BluetoothPairedTransformer.transformed_feature_name: BluetoothPairedTransformer(nontransformed_data),
BluetoothSeenTransformer.transformed_feature_name: BluetoothSeenTransformer(nontransformed_data),
ActivityTransformer.transformed_feature_name : ActivityTransformer(nontransformed_data)}
#the features that we want to transform
selected_features = [LocationTransformer.transformed_feature_name,
NotificationTransformer.transformed_feature_name,
ApplaunchTransformer.transformed_feature_name,
#BatteryTransformer.transformed_feature_name,
#HeadsetTransformer.transformed_feature_name,
BluetoothPairedTransformer.transformed_feature_name,
#BluetoothSeenTransformer.transformed_feature_name,
ActivityTransformer.transformed_feature_name]
#selected_features = [ActivityTransformer.transformed_feature_name]
categorized_data = {}
categorized_data[data_key]={}
categorized_data[metadata_key]={}
for feature in selected_features:
feature_transformers[feature].transform()
if feature_transformers[feature].transformed_feature_data != {None:None} and feature_transformers[feature].transformed_feature_metadata != {None:None}:
categorized_data[data_key][feature]= feature_transformers[feature].transformed_feature_data
categorized_data[metadata_key][feature] = feature_transformers[feature].transformed_feature_metadata
JsonUtils.save_json_data(out_path_prefix+str(DataExtractor.user_long_ids[user_id])+"/all/all_in_one_validated_log", categorized_data)
return categorized_data
def nb_realizations_by_feature_one_user(user_id):
data = DataExtractor.load_json_data(user_id)
observation_period = [300.0, 231.0, 89.0, 249.0, 229.0,224.0]
realizations_by_feature = {}
realization_per_day_by_feature = {}
for feature in data:
realizations_by_feature[feature]=len(data[feature])
realization_per_day_by_feature[feature]= len(data[feature])/observation_period[user_id-1]
str_res = ('user '+str(user_id)+'('+str(DataExtractor.user_long_ids[user_id])+': \nnumber of realizations by feature:\n'+pformat(realizations_by_feature)+'\n average number of realizations per day per feature:\n'+pformat(realization_per_day_by_feature)+'\n\n')
return str_res
def nb_realizations_by_feature_one_user(user_id):
data = DataExtractor.load_json_data(user_id)
observation_period = [300.0, 231.0, 89.0, 249.0, 229.0, 224.0]
realizations_by_feature = {}
realization_per_day_by_feature = {}
for feature in data:
realizations_by_feature[feature] = len(data[feature])
realization_per_day_by_feature[feature] = len(
data[feature]) / observation_period[user_id - 1]
str_res = ('user ' + str(user_id) + '(' +
str(DataExtractor.user_long_ids[user_id]) +
': \nnumber of realizations by feature:\n' +
pformat(realizations_by_feature) +
'\n average number of realizations per day per feature:\n' +
pformat(realization_per_day_by_feature) + '\n\n')
return str_res
#!/usr/bin/env python
import sys
sys.path.insert(0, "/home/dehajjik/workspace/src/utils")
from transform_to_categorized_data_one_user import transform_to_categorized_data_one_user as ttcdou
from clean_data_utils import DataExtractor
'''
make the categorized data transformation for all the users
'''
for user_id in DataExtractor.users_ids_list():
ttcdou(user_id)
print("user "+str(user_id)+" extracted")
#!/usr/bin/env python
import sys
sys.path.insert(0, "/home/dehajjik/workspace/src/utils")
from transform_to_categorized_data_one_user import transform_to_categorized_data_one_user as ttcdou
from clean_data_utils import DataExtractor
'''
make the categorized data transformation for all the users
'''
for user_id in DataExtractor.users_ids_list():
ttcdou(user_id)
print("user " + str(user_id) + " extracted")