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Rewrite copy_type_metadata to reuse the inherited method and handle geocolumns specifically. #684

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Sep 21, 2022
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Rewrite copy_type_metadata to reuse the inherited method and handle geocolumns specifically. #684

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44 changes: 21 additions & 23 deletions python/cuspatial/cuspatial/core/geodataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -79,20 +79,32 @@ def to_geopandas(self, nullable=False):
def __repr__(self):
return self.to_pandas().__repr__() + "\n" + "(GPU)" + "\n"

def _copy_type_metadata(self, other, include_index: bool = True):
def _copy_type_metadata(
self, other, include_index: bool = True, *, override_dtypes=None
):
"""
Copy type metadata from each column of `other` to the corresponding
column of `self`.
See `ColumnBase._with_type_metadata` for more information.
"""

type_copied = super()._copy_type_metadata(
other, include_index=include_index, override_dtypes=override_dtypes
)
for name, col, other_col in zip(
self._data.keys(), self._data.values(), other._data.values()
type_copied._data.keys(),
type_copied._data.values(),
other._data.values(),
):
# libcudf APIs lose all information about GeoColumns, operating
# solely on the underlying base data. Therefore, our only recourse
# is to recreate a new GeoColumn with the same underlying data.
# Since there's no easy way to create a GeoColumn from a
# NumericalColumn, we're forced to do so manually.
# A GeoColumn is currently implemented as a NumericalColumn with
# several child columns to hold the geometry data. The native
# return loop of cudf cython code can only reconstruct the
# geocolumn as a NumericalColumn. We can't reconstruct the full
# GeoColumn at the column level via _with_type_metadata, because
# there is neither a well defined geometry type in cuspatial,
# nor we can reconstruct the entire geocolumn data with pure
# geometry type. So we need an extra pass here to copy the geometry
# data into the type reconstructed dataframe.
if isinstance(other_col, GeoColumn):
col = GeoColumn(
(
Expand All @@ -104,23 +116,9 @@ def _copy_type_metadata(self, other, include_index: bool = True):
other_col._meta,
cudf.Index(col),
)
type_copied._data.set_by_label(name, col, validate=False)

self._data.set_by_label(
name, col._with_type_metadata(other_col.dtype), validate=False
)

if include_index:
if self._index is not None and other._index is not None:
self._index._copy_type_metadata(other._index)
# When other._index is a CategoricalIndex, there is
if isinstance(
other._index, cudf.core.index.CategoricalIndex
) and not isinstance(
self._index, cudf.core.index.CategoricalIndex
):
self._index = cudf.Index(self._index._column)

return self
return type_copied


class _GeoSeriesUtility:
Expand Down