Python DataExtractor.users_ids_list Exemples

Exemple #1

'''
for each user, outputs statistics that tests the consistency of the locations extracted:
	-show the distribution of frequencies of the clusters
	-show the distribution of the most frequent locations by hour of the day
'''

#!/usr/bin/env python
import sys
import pprint as pp
import os.path

sys.path.insert(0, "/home/dehajjik/workspace/src/utils")
from location_distribution_per_hour_one_user import location_distribution_per_hour_one_user as ldphou
from location_visits_distribution_one_user import location_visits_distribution_one_user as lvdou
from categorized_data_utils import DataExtractor
from plot_lib_utils import *


for user_id in DataExtractor.users_ids_list():
	for option in ["week_end", "week_days", "all"]:
		ldphou(user_id,option)
	lvdou(user_id)
	print("user "+str(user_id)+" extracted")
	
PlotlibDrawer.show()

Exemple #2

Fichier : location_accuracy_stat_all_users.py Projet : wsgan001/discovering_user_habbits_from_smartphone_logs

import os.path
import matplotlib.pyplot as plt

sys.path.insert(0, "/home/dehajjik/workspace/src/utils")
from location_time_coverage_one_user import location_time_coverage_one_user as tc_categorized

sys.path.insert(0, "/home/dehajjik/workspace/src/clean_data_exploration")
from location_time_coverage_one_user_clean import location_time_coverage_one_user_clean as tc_clean

from plot_lib_utils import *
from numpy_utils import *

from categorized_data_utils import DataExtractor
from plot_lib_utils import *

coverage_cat = np.zeros(len(DataExtractor.users_ids_list()))
coverage_clean = np.zeros(len(DataExtractor.users_ids_list()))

i = 0
for user_id in DataExtractor.users_ids_list():
    coverage_cat[i] = tc_categorized(user_id)
    coverage_clean[i] = tc_clean(user_id)

    i += 1

    print("user " + str(user_id) + " extracted")

print coverage_cat
print coverage_clean
fig, ax = plt.subplots()

Exemple #3

Fichier : location_accuracy_stat_all_users.py Projet : khajji/master_thesis_report

sys.path.insert(0, "/home/dehajjik/workspace/src/utils")
from location_time_coverage_one_user import location_time_coverage_one_user as tc_categorized

sys.path.insert(0, "/home/dehajjik/workspace/src/clean_data_exploration")
from location_time_coverage_one_user_clean import location_time_coverage_one_user_clean as tc_clean


from plot_lib_utils import *
from numpy_utils import *

from categorized_data_utils import DataExtractor
from plot_lib_utils import *


coverage_cat = np.zeros(len(DataExtractor.users_ids_list()))
coverage_clean = np.zeros(len(DataExtractor.users_ids_list()))



i = 0
for user_id in DataExtractor.users_ids_list():
	coverage_cat[i] = tc_categorized(user_id)
	coverage_clean[i] = tc_clean(user_id)
	
	i+=1

	print("user "+str(user_id)+" extracted")

print coverage_cat
print coverage_clean