def testLocalDtFillTimesDailyOneTz(self):
key = (2016, 5, 3)
test_section_list = []
test_section_list.append(
self._createTestSection(
arrow.Arrow(2016, 5, 3, 6, tzinfo=tz.gettz(PST)), PST))
test_section_list.append(
self._createTestSection(
arrow.Arrow(2016, 5, 3, 10, tzinfo=tz.gettz(PST)), PST))
test_section_list.append(
self._createTestSection(
arrow.Arrow(2016, 5, 3, 23, tzinfo=tz.gettz(PST)), PST))
section_group_df = self.ts.to_data_df(
eac.get_section_key_for_analysis_results(), test_section_list)
logging.debug("First row of section_group_df = %s" %
section_group_df.iloc[0])
self.assertEqual(earmt._get_tz(section_group_df), PST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
self.assertEqual(ms.ts, 1462258800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, PST)
def testLocalDtFillTimesDailyOneTz(self):
key = (2016, 5, 3)
test_section_list = []
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,6, tzinfo=tz.gettz(PST)),
PST))
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,10, tzinfo=tz.gettz(PST)),
PST))
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,23, tzinfo=tz.gettz(PST)),
PST))
section_group_df = self.ts.to_data_df(esda.CLEANED_SECTION_KEY,
test_section_list)
logging.debug("First row of section_group_df = %s" % section_group_df.iloc[0])
self.assertEqual(earmt._get_tz(section_group_df), PST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
self.assertEqual(ms.ts, 1462258800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, PST)
def testLocalDtFillTimesDailyMultiTzGoingEast(self):
key = (2016, 5, 3)
test_section_list = []
# This is perhaps an extreme use case, but it is actually a fairly
# common one with air travel
# Step 1: user leaves SFO at 1am on the 3rd for JFK on a cross-country flight
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,1, tzinfo=tz.gettz(PST)),
PST))
# cross-country takes 8 hours, so she arrives in New York at 9:00 IST = 12:00am EDT
# (taking into account the time difference)
test_section_list[0]['data'] = self._fillDates(test_section_list[0].data, "end_",
arrow.Arrow(2016,5,3,9,tzinfo=tz.gettz(PST)),
EST)
# Step 2: user leaves JFK for LHR at 1pm EST.
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,13, tzinfo=tz.gettz(EST)),
EST))
# cross-atlantic flight takes 7 hours, so she arrives at LHR at 8:00pm EDT
# = 2am on the 4th local time
test_section_list[1]['data'] = self._fillDates(test_section_list[1].data, "end_",
arrow.Arrow(2016,5,3,21,tzinfo=tz.gettz(EST)),
BST)
# Then, she catches the train from the airport to her hotel in London
# at 3am local time = 9:00pm EST
# So as per local time, this is a new trip
#
# This clearly indicates why we need to use the timezone of the end of
# last section to generate the timestamp for the range. If we use the
# timezone of the beginning of the trip, we will say that the range ends
# at midnight EST. But then it should include the next_day_first_trip,
# which starts at 9pm EST, but it does not.
# So we should use midnight BST instead. Note that midnight BST was
# actually during the trip, but then it is no different from a regular
# trip (in one timezone) where the trip spans the date change
next_day_first_trip = self._createTestSection(
arrow.Arrow(2016,5,4,3, tzinfo=tz.gettz(BST)),
BST)
section_group_df = self.ts.to_data_df(esda.CLEANED_SECTION_KEY, test_section_list)
logging.debug("first row is %s" % section_group_df.loc[0])
# Timestamps are monotonically increasing
self.assertEqual(section_group_df.start_ts.tolist(),
[1462262400, 1462294800])
# The timezone for the end time is PST since that's where we started
# the first trip from
self.assertEqual(earmt._get_tz(section_group_df), PST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
self.assertEqual(ms.ts, 1462258800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, PST)
# This test fails if it is not BST
self.assertGreater(next_day_first_trip.data.start_ts, ms.ts)
def testLocalDtFillTimesDailyMultiTzGoingWest(self):
key = (2016, 5, 3)
test_section_list = []
# This is perhaps an extreme use case, but it is actually a fairly
# common one with air travel
# Step 1: user leaves Delhi at 1am on the 3rd for JFK on the non-stop
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,1, tzinfo=tz.gettz(IST)),
IST))
# non-stop takes 15 hours, so she arrives in New York at 16:00 IST = 6:30am EDT
# (taking into account the time difference)
# Step 2: user leaves JFK for SFO at 7am EST on a non-stop
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,7, tzinfo=tz.gettz(EST)),
EST))
# cross-country flight takes 8 hours, so she arrives in SFO at 15:00 EDT
# = 12:00 PDT
test_section_list[1]['data'] = self._fillDates(test_section_list[1].data, "end_",
arrow.Arrow(2016,5,3,15,tzinfo=tz.gettz(EST)),
PST)
# Step 2: user starts a trip out of SFO a midnight of the 4th PST
# (earliest possible trip)
# for our timestamp algo to be correct, this has to be after the
# timestamp for the range
next_day_first_trip = self._createTestSection(
arrow.Arrow(2016,5,4,0, tzinfo=tz.gettz(PST)),
PST)
section_group_df = self.ts.to_data_df(esda.CLEANED_SECTION_KEY,
test_section_list)
# Timestamps are monotonically increasing
self.assertEqual(section_group_df.start_ts.tolist(),
[1462217400, 1462273200])
self.assertEqual(next_day_first_trip.data.start_ts, 1462345200)
# The timezone for the end time is IST since that's where we started
# the first trip
self.assertEqual(earmt._get_tz(section_group_df), IST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
# The end of the period is the end of the day in PST. So that we can
# capture trip home from the airport, etc.
# The next trip must start from the same timezone
# if a trip straddles two timezones, we need to decide how the metrics
# are split. A similar issue occurs when the trip straddles two days.
# We have arbitrarily decided to bucket by start_time, so we follow the
# same logic and bucket by the timezone of the start time.
#
# So the bucket for this day ends at the end of the day in EDT.
# If we included any trips after noon in SF, e.g. going home from the
# aiport, then it would extend to midnight PDT.
#
# The main argument that I'm trying to articulate is that we need to
# come up with a notion of when the bucket ended. To some extent, we can
# set this arbitrarily between the end of the last trip on the 3rd and the
# and the start of the first trip on the 4th.
#
# Picking midnight on the timezone of the last trip on the 3rd is
# reasonable since we know that no trips have started since the last
# trip on the 3rd to the midnight of the 3rd EST.
# So the worry here is that the first trip on the next day may be on
# next day in the end timezone of the trip but on the same day in the
# start timezone of the trip
# e.g. reverse trip
# maybe using the end of the section is best after all
self.assertEqual(ms.ts, 1462213800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, IST)
self.assertGreater(next_day_first_trip.data.start_ts, ms.ts)
def testLocalDtFillTimesDailyMultiTzGoingEast(self):
key = (2016, 5, 3)
test_section_list = []
# This is perhaps an extreme use case, but it is actually a fairly
# common one with air travel
# Step 1: user leaves SFO at 1am on the 3rd for JFK on a cross-country flight
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,1, tzinfo=tz.gettz(PST)),
PST))
# cross-country takes 8 hours, so she arrives in New York at 9:00 IST = 12:00am EDT
# (taking into account the time difference)
test_section_list[0]['data'] = self._fillDates(test_section_list[0].data, "end_",
arrow.Arrow(2016,5,3,9,tzinfo=tz.gettz(PST)),
EST)
# Step 2: user leaves JFK for LHR at 1pm EST.
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,13, tzinfo=tz.gettz(EST)),
EST))
# cross-atlantic flight takes 7 hours, so she arrives at LHR at 8:00pm EDT
# = 2am on the 4th local time
test_section_list[1]['data'] = self._fillDates(test_section_list[1].data, "end_",
arrow.Arrow(2016,5,3,21,tzinfo=tz.gettz(EST)),
BST)
# Then, she catches the train from the airport to her hotel in London
# at 3am local time = 9:00pm EST
# So as per local time, this is a new trip
#
# This clearly indicates why we need to use the timezone of the end of
# last section to generate the timestamp for the range. If we use the
# timezone of the beginning of the trip, we will say that the range ends
# at midnight EST. But then it should include the next_day_first_trip,
# which starts at 9pm EST, but it does not.
# So we should use midnight BST instead. Note that midnight BST was
# actually during the trip, but then it is no different from a regular
# trip (in one timezone) where the trip spans the date change
next_day_first_trip = self._createTestSection(
arrow.Arrow(2016,5,4,3, tzinfo=tz.gettz(BST)),
BST)
section_group_df = pd.DataFrame(
[self.ts._to_df_entry(s) for s in test_section_list])
logging.debug("first row is %s" % section_group_df.loc[0])
# Timestamps are monotonically increasing
self.assertEqual(section_group_df.start_ts.tolist(),
[1462262400, 1462294800])
# The timezone for the end time is PST since that's where we started
# the first trip from
self.assertEqual(earmt._get_tz(section_group_df), PST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
self.assertEqual(ms.ts, 1462258800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, PST)
# This test fails if it is not BST
self.assertGreater(next_day_first_trip.data.start_ts, ms.ts)
def testLocalDtFillTimesDailyMultiTzGoingWest(self):
key = (2016, 5, 3)
test_section_list = []
# This is perhaps an extreme use case, but it is actually a fairly
# common one with air travel
# Step 1: user leaves Delhi at 1am on the 3rd for JFK on the non-stop
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,1, tzinfo=tz.gettz(IST)),
IST))
# non-stop takes 15 hours, so she arrives in New York at 16:00 IST = 6:30am EDT
# (taking into account the time difference)
# Step 2: user leaves JFK for SFO at 7am EST on a non-stop
test_section_list.append(
self._createTestSection(arrow.Arrow(2016,5,3,7, tzinfo=tz.gettz(EST)),
EST))
# cross-country flight takes 8 hours, so she arrives in SFO at 15:00 EDT
# = 12:00 PDT
test_section_list[1]['data'] = self._fillDates(test_section_list[1].data, "end_",
arrow.Arrow(2016,5,3,15,tzinfo=tz.gettz(EST)),
PST)
# Step 2: user starts a trip out of SFO a midnight of the 4th PST
# (earliest possible trip)
# for our timestamp algo to be correct, this has to be after the
# timestamp for the range
next_day_first_trip = self._createTestSection(
arrow.Arrow(2016,5,4,0, tzinfo=tz.gettz(PST)),
PST)
section_group_df = pd.DataFrame(
[self.ts._to_df_entry(s) for s in test_section_list])
# Timestamps are monotonically increasing
self.assertEqual(section_group_df.start_ts.tolist(),
[1462217400, 1462273200])
self.assertEqual(next_day_first_trip.data.start_ts, 1462345200)
# The timezone for the end time is IST since that's where we started
# the first trip
self.assertEqual(earmt._get_tz(section_group_df), IST)
ms = ecwms.ModeStatTimeSummary()
earmt.local_dt_fill_times_daily(key, section_group_df, ms)
logging.debug("before starting checks, ms = %s" % ms)
# The end of the period is the end of the day in PST. So that we can
# capture trip home from the airport, etc.
# The next trip must start from the same timezone
# if a trip straddles two timezones, we need to decide how the metrics
# are split. A similar issue occurs when the trip straddles two days.
# We have arbitrarily decided to bucket by start_time, so we follow the
# same logic and bucket by the timezone of the start time.
#
# So the bucket for this day ends at the end of the day in EDT.
# If we included any trips after noon in SF, e.g. going home from the
# aiport, then it would extend to midnight PDT.
#
# The main argument that I'm trying to articulate is that we need to
# come up with a notion of when the bucket ended. To some extent, we can
# set this arbitrarily between the end of the last trip on the 3rd and the
# and the start of the first trip on the 4th.
#
# Picking midnight on the timezone of the last trip on the 3rd is
# reasonable since we know that no trips have started since the last
# trip on the 3rd to the midnight of the 3rd EST.
# So the worry here is that the first trip on the next day may be on
# next day in the end timezone of the trip but on the same day in the
# start timezone of the trip
# e.g. reverse trip
# maybe using the end of the section is best after all
self.assertEqual(ms.ts, 1462213800)
self.assertEqual(ms.local_dt.day, 3)
self.assertEqual(ms.local_dt.timezone, IST)
self.assertGreater(next_day_first_trip.data.start_ts, ms.ts)
