def time_tz_convert_from_utc(self, size, tz):
# effectively:
# dti = DatetimeIndex(self.i8data, tz=tz)
# dti.tz_localize(None)
if old_sig:
tz_convert_from_utc(self.i8data, UTC, tz)
else:
tz_convert_from_utc(self.i8data, tz)
def test_tz_localize_to_utc_copies():
# GH#46460
arr = np.arange(5, dtype="i8")
result = tz_convert_from_utc(arr, tz=UTC)
tm.assert_numpy_array_equal(result, arr)
assert not np.shares_memory(arr, result)
result = tz_convert_from_utc(arr, tz=None)
tm.assert_numpy_array_equal(result, arr)
assert not np.shares_memory(arr, result)
def _compare_utc_to_local(tz_didx):
def f(x):
return tzconversion.tz_convert_from_utc_single(x, tz_didx.tz)
result = tz_convert_from_utc(tz_didx.asi8, tz_didx.tz)
expected = np.vectorize(f)(tz_didx.asi8)
tm.assert_numpy_array_equal(result, expected)
def __init__(self, index, warn: bool = True) -> None:
self.index = index
self.i8values = index.asi8
# For get_unit_from_dtype we need the dtype to the underlying ndarray,
# which for tz-aware is not the same as index.dtype
if isinstance(index, ABCIndex):
# error: Item "ndarray[Any, Any]" of "Union[ExtensionArray,
# ndarray[Any, Any]]" has no attribute "_ndarray"
self._reso = get_unit_from_dtype(
index._data._ndarray.dtype # type: ignore[union-attr]
)
else:
# otherwise we have DTA/TDA
self._reso = get_unit_from_dtype(index._ndarray.dtype)
# 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.i8values = tz_convert_from_utc(self.i8values, index.tz)
if warn is not True:
warnings.warn(
"warn is deprecated (and never implemented) and "
"will be removed in a future version.",
FutureWarning,
stacklevel=3,
)
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 __init__(self, index, warn: bool = True) -> None:
self.index = index
self.i8values = 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.i8values = tz_convert_from_utc(self.i8values, index.tz)
if warn is not True:
warnings.warn(
"warn is deprecated (and never implemented) and "
"will be removed in a future version.",
FutureWarning,
stacklevel=3,
)
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_readonly():
# GH#35530
arr = np.array([0], dtype=np.int64)
arr.setflags(write=False)
result = tz_convert_from_utc(arr, UTC)
tm.assert_numpy_array_equal(result, arr)
def test_tz_convert_corner(arr):
result = tz_convert_from_utc(arr, timezones.maybe_get_tz("Asia/Tokyo"))
tm.assert_numpy_array_equal(result, arr)