def _window_to_window_sizes(self, window):
"""
For non-fixed width windows,
convert the window argument into window sizes.
"""
if is_integer(window):
return window
else:
return cudautils.window_sizes_from_offset(
self.obj.index._values.data_array_view, window)
def _normalize(self):
"""
Normalize the *window* and *min_periods* args
*window* can be:
* An integer, in which case it is the window size.
If *min_periods* is unspecified, it is set to be equal to
the window size.
* A timedelta offset, in which case it is used to generate
a column of window sizes to use for each element.
If *min_periods* is unspecified, it is set to 1.
Only valid for datetime index.
"""
window, min_periods = self.window, self.min_periods
if pd.api.types.is_number(window):
# only allow integers
if not pd.api.types.is_integer(window):
raise ValueError("window must be an integer")
if window <= 0:
raise ValueError("window cannot be zero or negative")
if self.min_periods is None:
min_periods = window
else:
if isinstance(window, numba.cuda.devicearray.DeviceNDArray):
# window is a device_array of window sizes
self.window = window
self.min_periods = min_periods
return
if not isinstance(self.obj.index, cudf.core.index.DatetimeIndex):
raise ValueError(
"window must be an integer for " "non datetime index"
)
try:
window = pd.to_timedelta(window)
# to_timedelta will also convert np.arrays etc.,
if not isinstance(window, pd.Timedelta):
raise ValueError
window = window.to_timedelta64()
except ValueError as e:
raise ValueError(
"window must be integer or " "convertible to a timedelta"
) from e
window = cudautils.window_sizes_from_offset(
self.obj.index.as_column().data.mem, window
)
if self.min_periods is None:
min_periods = 1
self.window = window
self.min_periods = min_periods
