def test_calc_minute_of_day():
time1 = datetime.time(hour=0, minute=1, second=1)
time2 = datetime.time(hour=1, minute=0, second=1)
time3 = datetime.time(hour=0, minute=0, second=0)
time4 = datetime.time(hour=23, minute=59, second=59)
value1 = support.calc_minute_of_day(time1)
value2 = support.calc_minute_of_day(time2)
value3 = support.calc_minute_of_day(time3)
value4 = support.calc_minute_of_day(time4)
run_tests.compare_answer(value1, 1, "minute of day = 1")
run_tests.compare_answer(value2, 60, "minute of day = 2")
run_tests.compare_answer(value3, 0, "minute of day = 3")
run_tests.compare_answer(value4, 1439, "minute of day = 4")
def find_the_gaps_user_info_to_mp_fetched(dbcc, user_id, start_date,
start_time, end_date, end_time,
user_info_list):
start_unix_minutes = support.date_time_to_unix_minutes_timestamp(
datetime.datetime.combine(start_date, start_time))
end_unix_minutes = support.date_time_to_unix_minutes_timestamp(
datetime.datetime.combine(end_date, end_time))
missing_ranges_unix_minutes = support.reduce_to_missing_ranges(
user_info_list, lambda x: support.date_time_to_unix_minutes_timestamp(
datetime.datetime.combine(x.date, x.time)), 1, start_unix_minutes,
end_unix_minutes)
mp_fetched = []
for missing_range_unix_minutes in missing_ranges_unix_minutes:
progression = missing_range_unix_minutes.get_progression()
for missing_unix_minute in progression:
date_time = support.unix_minutes_timestamp_to_date_time(
missing_unix_minute)
time = date_time.time()
date = date_time.date()
minute_of_day = support.calc_minute_of_day(time)
day = support.calc_day(date)
cell_id = 0
new_mp_fetched = db_layout.MPFetched.new(dbcc, user_id,
minute_of_day, date, day,
cell_id)
mp_fetched.append(new_mp_fetched)
return mp_fetched
def find_the_gaps_user_info_to_mp_fetched(dbcc, user_id, start_date, start_time, end_date, end_time, user_info_list):
start_unix_minutes = support.date_time_to_unix_minutes_timestamp(datetime.datetime.combine(start_date, start_time))
end_unix_minutes = support.date_time_to_unix_minutes_timestamp(datetime.datetime.combine(end_date, end_time))
missing_ranges_unix_minutes = support.reduce_to_missing_ranges(
user_info_list,
lambda x: support.date_time_to_unix_minutes_timestamp(datetime.datetime.combine(x.date, x.time)),
1,
start_unix_minutes,
end_unix_minutes,
)
mp_fetched = []
for missing_range_unix_minutes in missing_ranges_unix_minutes:
progression = missing_range_unix_minutes.get_progression()
for missing_unix_minute in progression:
date_time = support.unix_minutes_timestamp_to_date_time(missing_unix_minute)
time = date_time.time()
date = date_time.date()
minute_of_day = support.calc_minute_of_day(time)
day = support.calc_day(date)
cell_id = 0
new_mp_fetched = db_layout.MPFetched.new(dbcc, user_id, minute_of_day, date, day, cell_id)
mp_fetched.append(new_mp_fetched)
return mp_fetched
def clear_user_information_maas_message(dbcc, msg):
user_id = msg.user_id
db_user_mobility_information_list = []
#Save it in mean database and convert to db layout object
for movement in msg.user_information:
db_user_mobility_information = db_layout.UserMobilityInformation.new(
dbcc, user_id, movement.time, movement.date, movement.cell_id)
db_user_mobility_information_list.append(db_user_mobility_information)
db_layout.UserMobilityInformation.save_many(
dbcc, db_user_mobility_information_list)
mp_fetched_list = []
#Clear the data and save it in the fetched database
for db_user_mobility_information in db_user_mobility_information_list:
minute_of_day = support.calc_minute_of_day(
db_user_mobility_information.time)
day = support.calc_day(db_user_mobility_information.date)
mp_fetched = db_layout.MPFetched.new(
dbcc, user_id, minute_of_day, db_user_mobility_information.date,
day, db_user_mobility_information.cell_id)
mp_fetched_list.append(mp_fetched)
#Fill in gaps
end_date_time = datetime.datetime.combine(
msg.start_date,
msg.start_time) + datetime.timedelta(seconds=msg.time_span)
gaps_mp_fetched = find_the_gaps_user_info_to_mp_fetched(
dbcc, msg.user_id,
msg.start_date, msg.start_time, end_date_time.date(),
end_date_time.time(), db_user_mobility_information_list)
mp_fetched_list.extend(gaps_mp_fetched)
db_layout.MPFetched.save_many(dbcc, mp_fetched_list)
err.log_error(
err.INFO, "Cleared " + str(len(msg.user_information)) +
" rows user information data")
err.log_error(
err.INFO, "Filled in " + str(len(gaps_mp_fetched)) +
" holes with mp fetched data")
return sr.SuppliedUserInfo.from_maas_user_info_message_to_supplied_info(
msg)
def mobility_prediction(pykov_chain, current_cell_id, current_date, current_time, predicted_date, predicted_time):
initial_minute_of_day = support.calc_minute_of_day(current_time)
initial_day = support.calc_day(current_date)
initial_key = UserEntry(initial_day, initial_minute_of_day, current_cell_id).to_pykov_key()
initial_pykov_vector = pykov.Vector({initial_key: 1})
difference_in_seconds = (
datetime.datetime.combine(predicted_date, predicted_time)
- datetime.datetime.combine(current_date, current_time)
).total_seconds()
difference_in_minutes = int(difference_in_seconds / 60)
distribution_dict = pykov_chain.pow(initial_pykov_vector, difference_in_minutes)
print "eeeeeee", distribution_dict
return distribution_dict
def clear_user_information_maas_message(dbcc, msg):
user_id = msg.user_id
db_user_mobility_information_list = []
# Save it in mean database and convert to db layout object
for movement in msg.user_information:
db_user_mobility_information = db_layout.UserMobilityInformation.new(
dbcc, user_id, movement.time, movement.date, movement.cell_id
)
db_user_mobility_information_list.append(db_user_mobility_information)
db_layout.UserMobilityInformation.save_many(dbcc, db_user_mobility_information_list)
mp_fetched_list = []
# Clear the data and save it in the fetched database
for db_user_mobility_information in db_user_mobility_information_list:
minute_of_day = support.calc_minute_of_day(db_user_mobility_information.time)
day = support.calc_day(db_user_mobility_information.date)
mp_fetched = db_layout.MPFetched.new(
dbcc, user_id, minute_of_day, db_user_mobility_information.date, day, db_user_mobility_information.cell_id
)
mp_fetched_list.append(mp_fetched)
# Fill in gaps
end_date_time = datetime.datetime.combine(msg.start_date, msg.start_time) + datetime.timedelta(
seconds=msg.time_span
)
gaps_mp_fetched = find_the_gaps_user_info_to_mp_fetched(
dbcc,
msg.user_id,
msg.start_date,
msg.start_time,
end_date_time.date(),
end_date_time.time(),
db_user_mobility_information_list,
)
mp_fetched_list.extend(gaps_mp_fetched)
db_layout.MPFetched.save_many(dbcc, mp_fetched_list)
err.log_error(err.INFO, "Cleared " + str(len(msg.user_information)) + " rows user information data")
err.log_error(err.INFO, "Filled in " + str(len(gaps_mp_fetched)) + " holes with mp fetched data")
return sr.SuppliedUserInfo.from_maas_user_info_message_to_supplied_info(msg)
def mobility_prediction(pykov_chain, current_cell_id, current_date,
current_time, predicted_date, predicted_time):
initial_minute_of_day = support.calc_minute_of_day(current_time)
initial_day = support.calc_day(current_date)
initial_key = UserEntry(initial_day, initial_minute_of_day,
current_cell_id).to_pykov_key()
initial_pykov_vector = pykov.Vector({initial_key: 1})
difference_in_seconds = (
datetime.datetime.combine(predicted_date, predicted_time) -
datetime.datetime.combine(current_date, current_time)).total_seconds()
difference_in_minutes = int(difference_in_seconds / 60)
distribution_dict = pykov_chain.pow(initial_pykov_vector,
difference_in_minutes)
print 'eeeeeee', distribution_dict
return distribution_dict