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Fix #13306: Hour overflow in tz-aware datetime conversions. #13313

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Fix #13306: Hour overflow in tz-aware datetime conversions. #13313

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a1ed5a5
Fix #13306: Hour overflow in tz-aware datetime conversions.
uwedeportivo May 28, 2016
82f263a
Use vectorized searchsorted and tests.
uwedeportivo May 28, 2016
1f5f7a5
Code Review jreback
uwedeportivo Jun 1, 2016
be3ed90
whatsnew entry for issue #13306
uwedeportivo Jun 1, 2016
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.18.2.txt
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Expand Up @@ -338,7 +338,7 @@ Bug Fixes
- Bug in ``.resample(..)`` with a ``PeriodIndex`` not changing its ``freq`` appropriately when empty (:issue:`13067`)
- Bug in ``.resample(..)`` with a ``PeriodIndex`` not retaining its type or name with an empty ``DataFrame``appropriately when empty (:issue:`13212`)
- Bug in ``groupby(..).resample(..)`` where passing some keywords would raise an exception (:issue:`13235`)

- Bug in ``.tz-convert`` tz-aware ``DateTimeIndex`` relies on index being sorted for correct results (:issue: `13306`)



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82 changes: 82 additions & 0 deletions pandas/tseries/tests/test_timezones.py
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Expand Up @@ -902,6 +902,88 @@ def test_utc_with_system_utc(self):
# check that the time hasn't changed.
self.assertEqual(ts, ts.tz_convert(dateutil.tz.tzutc()))

def test_tz_convert_hour_overflow_dst(self):
# Regression test for:
# https://github.com/pydata/pandas/issues/13306

# sorted case US/Eastern -> UTC
ts = ['2008-05-12 09:50:00',
'2008-12-12 09:50:35',
'2009-05-12 09:50:32']
tt = to_datetime(ts).tz_localize('US/Eastern')
ut = tt.tz_convert('UTC')
expected = np.array([13, 14, 13], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# sorted case UTC -> US/Eastern
ts = ['2008-05-12 13:50:00',
'2008-12-12 14:50:35',
'2009-05-12 13:50:32']
tt = to_datetime(ts).tz_localize('UTC')
ut = tt.tz_convert('US/Eastern')
expected = np.array([9, 9, 9], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# unsorted case US/Eastern -> UTC
ts = ['2008-05-12 09:50:00',
'2008-12-12 09:50:35',
'2008-05-12 09:50:32']
tt = to_datetime(ts).tz_localize('US/Eastern')
ut = tt.tz_convert('UTC')
expected = np.array([13, 14, 13], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# unsorted case UTC -> US/Eastern
ts = ['2008-05-12 13:50:00',
'2008-12-12 14:50:35',
'2008-05-12 13:50:32']
tt = to_datetime(ts).tz_localize('UTC')
ut = tt.tz_convert('US/Eastern')
expected = np.array([9, 9, 9], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

def test_tz_convert_hour_overflow_dst_timestamps(self):
# Regression test for:
# https://github.com/pydata/pandas/issues/13306

tz = self.tzstr('US/Eastern')

# sorted case US/Eastern -> UTC
ts = [Timestamp('2008-05-12 09:50:00', tz=tz),
Timestamp('2008-12-12 09:50:35', tz=tz),
Timestamp('2009-05-12 09:50:32', tz=tz)]
tt = to_datetime(ts)
ut = tt.tz_convert('UTC')
expected = np.array([13, 14, 13], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# sorted case UTC -> US/Eastern
ts = [Timestamp('2008-05-12 13:50:00', tz='UTC'),
Timestamp('2008-12-12 14:50:35', tz='UTC'),
Timestamp('2009-05-12 13:50:32', tz='UTC')]
tt = to_datetime(ts)
ut = tt.tz_convert('US/Eastern')
expected = np.array([9, 9, 9], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# unsorted case US/Eastern -> UTC
ts = [Timestamp('2008-05-12 09:50:00', tz=tz),
Timestamp('2008-12-12 09:50:35', tz=tz),
Timestamp('2008-05-12 09:50:32', tz=tz)]
tt = to_datetime(ts)
ut = tt.tz_convert('UTC')
expected = np.array([13, 14, 13], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

# unsorted case UTC -> US/Eastern
ts = [Timestamp('2008-05-12 13:50:00', tz='UTC'),
Timestamp('2008-12-12 14:50:35', tz='UTC'),
Timestamp('2008-05-12 13:50:32', tz='UTC')]
tt = to_datetime(ts)
ut = tt.tz_convert('US/Eastern')
expected = np.array([9, 9, 9], dtype=np.int32)
self.assert_numpy_array_equal(ut.hour, expected)

def test_tslib_tz_convert_trans_pos_plus_1__bug(self):
# Regression test for tslib.tz_convert(vals, tz1, tz2).
# See https://github.com/pydata/pandas/issues/4496 for details.
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35 changes: 16 additions & 19 deletions pandas/tslib.pyx
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Expand Up @@ -3754,8 +3754,8 @@ except:

def tz_convert(ndarray[int64_t] vals, object tz1, object tz2):
cdef:
ndarray[int64_t] utc_dates, tt, result, trans, deltas
Py_ssize_t i, pos, n = len(vals)
ndarray[int64_t] utc_dates, tt, result, trans, deltas, posn
Py_ssize_t i, j, pos, n = len(vals)
int64_t v, offset
pandas_datetimestruct dts
Py_ssize_t trans_len
Expand Down Expand Up @@ -3791,19 +3791,18 @@ def tz_convert(ndarray[int64_t] vals, object tz1, object tz2):
return vals

trans_len = len(trans)
pos = trans.searchsorted(tt[0]) - 1
if pos < 0:
raise ValueError('First time before start of DST info')

offset = deltas[pos]
posn = trans.searchsorted(tt, side='right')
j = 0
for i in range(n):
v = vals[i]
if v == NPY_NAT:
utc_dates[i] = NPY_NAT
else:
while pos + 1 < trans_len and v >= trans[pos + 1]:
pos += 1
offset = deltas[pos]
pos = posn[j] - 1
j = j + 1
if pos < 0:
raise ValueError('First time before start of DST info')
offset = deltas[pos]
utc_dates[i] = v - offset
else:
utc_dates = vals
Expand Down Expand Up @@ -3838,20 +3837,18 @@ def tz_convert(ndarray[int64_t] vals, object tz1, object tz2):
if (result==NPY_NAT).all():
return result

pos = trans.searchsorted(utc_dates[utc_dates!=NPY_NAT][0]) - 1
if pos < 0:
raise ValueError('First time before start of DST info')

# TODO: this assumed sortedness :/
offset = deltas[pos]
posn = trans.searchsorted(utc_dates[utc_dates!=NPY_NAT], side='right')
j = 0
for i in range(n):
v = utc_dates[i]
if vals[i] == NPY_NAT:
result[i] = vals[i]
else:
while pos + 1 < trans_len and v >= trans[pos + 1]:
pos += 1
offset = deltas[pos]
pos = posn[j] - 1
j = j + 1
if pos < 0:
raise ValueError('First time before start of DST info')
offset = deltas[pos]
result[i] = v + offset
return result

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