def test_tz_convert_corner(arr):
result = tzconversion.tz_convert(arr, timezones.maybe_get_tz("US/Eastern"),
UTC)
tm.assert_numpy_array_equal(result, arr)
result = tzconversion.tz_convert(arr, UTC,
timezones.maybe_get_tz("Asia/Tokyo"))
tm.assert_numpy_array_equal(result, arr)
def _compare_local_to_utc(tz_didx, utc_didx):
def f(x):
return conversion.tz_convert_single(x, tz_didx.tz, UTC)
result = tzconversion.tz_convert(utc_didx.asi8, tz_didx.tz, UTC)
expected = np.vectorize(f)(utc_didx.asi8)
tm.assert_numpy_array_equal(result, expected)
def _compare_utc_to_local(tz_didx):
def f(x):
return tzconversion.tz_convert_single(x, UTC, tz_didx.tz)
result = tzconversion.tz_convert(tz_didx.asi8, UTC, tz_didx.tz)
expected = np.vectorize(f)(tz_didx.asi8)
tm.assert_numpy_array_equal(result, expected)
def _compare_local_to_utc(tz_didx, utc_didx):
def f(x):
return conversion.tz_convert_single(x, tz_didx.tz, UTC)
result = tzconversion.tz_convert(utc_didx.asi8, tz_didx.tz, UTC)
expected = np.vectorize(f)(utc_didx.asi8)
tm.assert_numpy_array_equal(result, expected)
def __init__(self, index, warn=True):
self.index = index
self.values = index.asi8
# This moves the values, which are implicitly in UTC, to the
# the timezone so they are in local time
if hasattr(index, 'tz'):
if index.tz is not None:
self.values = tz_convert(self.values, UTC, index.tz)
self.warn = warn
if len(index) < 3:
raise ValueError('Need at least 3 dates to infer frequency')
self.is_monotonic = (self.index._is_monotonic_increasing
or self.index._is_monotonic_decreasing)
def test_tz_convert_corner(arr):
result = tzconversion.tz_convert(arr,
timezones.maybe_get_tz("US/Eastern"),
timezones.maybe_get_tz("Asia/Tokyo"))
tm.assert_numpy_array_equal(result, arr)
def time_tz_convert_from_utc(self, size, tz):
# effectively:
# dti = DatetimeIndex(self.i8data, tz=tz)
# dti.tz_localize(None)
tz_convert(self.i8data, UTC, tz)
