def putmask_inplace(values: ArrayLike, mask: npt.NDArray[np.bool_], value: Any) -> None:
"""
ExtensionArray-compatible implementation of np.putmask. The main
difference is we do not handle repeating or truncating like numpy.
Parameters
----------
values: np.ndarray or ExtensionArray
mask : np.ndarray[bool]
We assume extract_bool_array has already been called.
value : Any
"""
if lib.is_scalar(value) and isinstance(values, np.ndarray):
value = convert_scalar_for_putitemlike(value, values.dtype)
if (
not isinstance(values, np.ndarray)
or (values.dtype == object and not lib.is_scalar(value))
# GH#43424: np.putmask raises TypeError if we cannot cast between types with
# rule = "safe", a stricter guarantee we may not have here
or (
isinstance(value, np.ndarray) and not np.can_cast(value.dtype, values.dtype)
)
):
# GH#19266 using np.putmask gives unexpected results with listlike value
# along with object dtype
if is_list_like(value) and len(value) == len(values):
values[mask] = value[mask]
else:
values[mask] = value
else:
# GH#37833 np.putmask is more performant than __setitem__
np.putmask(values, mask, value)
def putmask_inplace(values: ArrayLike, mask: np.ndarray, value: Any) -> None:
"""
ExtensionArray-compatible implementation of np.putmask. The main
difference is we do not handle repeating or truncating like numpy.
Parameters
----------
mask : np.ndarray[bool]
We assume _extract_bool_array has already been called.
value : Any
"""
if lib.is_scalar(value) and isinstance(values, np.ndarray):
value = convert_scalar_for_putitemlike(value, values.dtype)
if not isinstance(values, np.ndarray) or (values.dtype == object
and not lib.is_scalar(value)):
# GH#19266 using np.putmask gives unexpected results with listlike value
if is_list_like(value) and len(value) == len(values):
values[mask] = value[mask]
else:
values[mask] = value
else:
# GH#37833 np.putmask is more performant than __setitem__
np.putmask(values, mask, value)
