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TST: expand tests
DOC: add comment to workaround line
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@@ -6,6 +6,7 @@ import itertools
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from itertools import product
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import blaze as bz
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from nose_parameterized import parameterized
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import numpy as np
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import pandas as pd
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from pandas.util.testing import assert_series_equal
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@@ -462,31 +463,44 @@ class BlazeEventsLoaderTestCase(EventsLoaderTestCase):
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class EventLoaderUtilsTestCase(ZiplineTestCase):
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dates = [pd.Timestamp('2013-01-04 3:00:00'), pd.Timestamp('2013-01-24'),
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pd.Timestamp('2013-04-04'), pd.Timestamp('2013-04-21')]
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combos = list(itertools.permutations(dates))
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def test_normalize_to_query_time(self):
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# Order matters in pandas 18.0.2. Prior to that, using tz_convert on
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# a DatetimeIndex with DST/EST timestamps mixed resulted in some of
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# them being an hour off (1 hour past midnight).
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expected = pd.Series(
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[pd.Timestamp('2013-01-04'),
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dates = [pd.Timestamp('2013-01-04 3:00:00'),
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pd.Timestamp('2013-01-24'),
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pd.Timestamp('2013-01-31 20:00:00'),
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pd.Timestamp('2013-04-04'),
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pd.Timestamp('2013-04-21')]
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).reset_index(drop=True)
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combos = list(itertools.permutations(dates))
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expected_us = pd.Series(
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[pd.Timestamp('2013-01-04'),
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pd.Timestamp('2013-01-24'),
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pd.Timestamp('2013-02-01'),
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pd.Timestamp('2013-04-04'),
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pd.Timestamp('2013-04-21')]
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)
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# Russia's TZ offset is +3
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expected_russia = pd.Series(
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[pd.Timestamp('2013-01-04'),
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pd.Timestamp('2013-01-24'),
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pd.Timestamp('2013-01-31'),
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pd.Timestamp('2013-04-04'),
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pd.Timestamp('2013-04-21')]
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)
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# Test with timezones on either side of the meridian
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@parameterized.expand([(expected_us, 'US/Eastern', time(8, 45)),
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(expected_russia, 'Europe/Moscow', time(16, 45))])
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def test_normalize_to_query_time(self, expected, tz, query_time):
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# Order matters in pandas 0.18.2. Prior to that, using tz_convert on
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# a DatetimeIndex with DST/EST timestamps mixed resulted in some of
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# them being an hour off (1 hour past midnight).
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for combo in self.combos:
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df = pd.DataFrame({"timestamp": combo})
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tz = 'US/Eastern'
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query_time = time(8, 45)
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result = normalize_timestamp_to_query_time(df,
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query_time,
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tz,
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inplace=False,
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ts_field='timestamp')
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result = result.sort("timestamp").reset_index(drop=True)
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assert_series_equal(result['timestamp'], expected)
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assert_series_equal(result['timestamp'], expected,
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check_names=False)
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@@ -237,12 +237,15 @@ def normalize_timestamp_to_query_time(df,
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_midnight,
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include_end=False,
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)
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# for all of the times that are greater than our query time add 1
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# day and truncate to the date
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# For all of the times that are greater than our query time add 1
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# day and truncate to the date.
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# We normalize twice here because of a bug in pandas 0.16.1 that causes
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# tz_localize() to shift some timestamps by an hour if they are not grouped
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# together by DST/EST.
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df.loc[to_roll_forward, ts_field] = (
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dtidx_local_time[to_roll_forward] + datetime.timedelta(days=1)
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).normalize().tz_localize(None).tz_localize('utc').normalize() # cast
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# back to utc
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).normalize().tz_localize(None).tz_localize('utc').normalize()
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df.loc[~to_roll_forward, ts_field] = dtidx[~to_roll_forward].normalize()
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return df
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