def _simple_new( # type: ignore[override]
cls, values: np.ndarray, freq: BaseOffset | None = None, dtype=TD64NS_DTYPE
) -> TimedeltaArray:
# Require td64 dtype, not unit-less, matching values.dtype
assert isinstance(dtype, np.dtype) and dtype.kind == "m"
assert not tslibs.is_unitless(dtype)
assert isinstance(values, np.ndarray), type(values)
assert dtype == values.dtype
result = super()._simple_new(values=values, dtype=dtype)
result._freq = freq
return result
def astype_array_safe(values: ArrayLike,
dtype,
copy: bool = False,
errors: IgnoreRaise = "raise") -> ArrayLike:
"""
Cast array (ndarray or ExtensionArray) to the new dtype.
This basically is the implementation for DataFrame/Series.astype and
includes all custom logic for pandas (NaN-safety, converting str to object,
not allowing )
Parameters
----------
values : ndarray or ExtensionArray
dtype : str, dtype convertible
copy : bool, default False
copy if indicated
errors : str, {'raise', 'ignore'}, default 'raise'
- ``raise`` : allow exceptions to be raised
- ``ignore`` : suppress exceptions. On error return original object
Returns
-------
ndarray or ExtensionArray
"""
errors_legal_values = ("raise", "ignore")
if errors not in errors_legal_values:
invalid_arg = (
"Expected value of kwarg 'errors' to be one of "
f"{list(errors_legal_values)}. Supplied value is '{errors}'")
raise ValueError(invalid_arg)
if inspect.isclass(dtype) and issubclass(dtype, ExtensionDtype):
msg = (f"Expected an instance of {dtype.__name__}, "
"but got the class instead. Try instantiating 'dtype'.")
raise TypeError(msg)
dtype = pandas_dtype(dtype)
if isinstance(dtype, PandasDtype):
# Ensure we don't end up with a PandasArray
dtype = dtype.numpy_dtype
if (is_datetime64_dtype(values.dtype)
# need to do np.dtype check instead of is_datetime64_dtype
# otherwise pyright complains
and isinstance(dtype, np.dtype) and dtype.kind == "M" and
not is_unitless(dtype) and
not is_dtype_equal(dtype, values.dtype)):
# unit conversion, we would re-cast to nanosecond, so this is
# effectively just a copy (regardless of copy kwd)
# TODO(2.0): remove special-case
return values.copy()
try:
new_values = astype_array(values, dtype, copy=copy)
except (ValueError, TypeError):
# e.g. astype_nansafe can fail on object-dtype of strings
# trying to convert to float
if errors == "ignore":
new_values = values
else:
raise
return new_values