diff --git a/packages/calitp-data-analysis/calitp_data_analysis/geography_utils.py b/packages/calitp-data-analysis/calitp_data_analysis/geography_utils.py index e820b92df2..d36abe1ee9 100644 --- a/packages/calitp-data-analysis/calitp_data_analysis/geography_utils.py +++ b/packages/calitp-data-analysis/calitp_data_analysis/geography_utils.py @@ -98,6 +98,19 @@ def create_segments( Input a geometry column, such as gdf.geometry. Double check: segment_distance must be given in the same units as the CRS! + + Use case: + gdf['segment_geometry'] = gdf.apply( + lambda x: + create_segments(x.geometry, int(segment_length)), + axis=1, + ) + + gdf2 = explode_segments( + gdf, + group_cols = ['route_key'], + segment_col = 'segment_geometry' + ) """ lines = [] @@ -113,64 +126,54 @@ def create_segments( return lines -def cut_segments( - gdf: gpd.GeoDataFrame, - group_cols: list = ["calitp_itp_id", "calitp_url_number", "route_id"], - segment_distance: int = 1_000, +def explode_segments( + gdf: gpd.GeoDataFrame, group_cols: list, segment_col: str = "segment_geometry" ) -> gpd.GeoDataFrame: """ - Cut segments from linestrings at defined segment lengths. - Make sure segment distance is defined in the same CRS as the gdf. - - group_cols: list of columns. - The set of columns that represents how segments should be cut. - Ex: for transit route, it's calitp_itp_id-calitp_url_number-route_id - Ex: for highways, it's Route-RouteType-County-District. - - Returns a gpd.GeoDataFrame where each linestring row is now multiple - rows (each at the pre-defined segment_distance). A new column called - `segment_sequence` is also created, which differentiates each - new row created (since they share the same group_cols). - """ - EPSG_CODE = gdf.crs.to_epsg() - - segmented = gpd.GeoDataFrame() - - gdf = gdf[group_cols + ["geometry"]].drop_duplicates().reset_index(drop=True) - - for row in gdf.itertuples(): - row_geom = getattr(row, "geometry") - segment = create_segments(row_geom, int(segment_distance)) + Explode the column that is used to store segments, which is a list. + Take the list and create a row for each element in the list. + We'll do a rough rank so we can order the segments. + + Use case: + gdf['segment_geometry'] = gdf.apply( + lambda x: + create_segments(x.geometry, int(segment_length)), + axis=1, + ) - to_append = pd.DataFrame() - to_append["geometry"] = segment - for c in group_cols: - to_append[c] = getattr(row, c) + gdf2 = explode_segments( + gdf, + group_cols = ['route_key'], + segment_col = 'segment_geometry' + ) + """ + gdf_exploded = gdf.explode(segment_col).reset_index(drop=True) - segmented = pd.concat([segmented, to_append], axis=0, ignore_index=True) + gdf_exploded["temp_index"] = gdf_exploded.index - segmented = segmented.assign( - temp_index=segmented.sort_values(group_cols).reset_index(drop=True).index + gdf_exploded = gdf_exploded.assign( + segment_sequence=( + gdf_exploded.groupby( + group_cols, observed=True, group_keys=False + ).temp_index.transform("rank") + - 1 + # there are NaNs, but since they're a single segment, just use 0 ) + .fillna(0) + .astype("int16") + ) - # Why would there be NaNs? - # could this be coming from group_cols...one of the cols has a NaN in some rows? - segmented = segmented[segmented.temp_index.notna()] - - segmented = ( - segmented.assign( - segment_sequence=( - segmented.groupby(group_cols)["temp_index"].transform("rank") - 1 - ).astype("int16") - ) - .sort_values(group_cols) + # Drop the original line geometry, use the segment geometry only + gdf_exploded2 = ( + gdf_exploded.drop(columns=["geometry", "temp_index"]) + .rename(columns={segment_col: "geometry"}) + .set_geometry("geometry") + .set_crs(gdf_exploded.crs) + .sort_values(group_cols + ["segment_sequence"]) .reset_index(drop=True) - .drop(columns="temp_index") ) - segmented2 = gpd.GeoDataFrame(segmented, crs=f"EPSG:{EPSG_CODE}") # noqa: E231 - - return segmented2 + return gdf_exploded2 return_options = Literal[ diff --git a/packages/calitp-data-analysis/calitp_data_analysis/utils.py b/packages/calitp-data-analysis/calitp_data_analysis/utils.py index b68fc383a9..d09539c3ca 100644 --- a/packages/calitp-data-analysis/calitp_data_analysis/utils.py +++ b/packages/calitp-data-analysis/calitp_data_analysis/utils.py @@ -23,6 +23,19 @@ def sanitize_file_path(file_name: str) -> str: return str(Path(file_name).stem) +def parse_file_directory(file_name: str) -> str: + """ + Grab the directory of the filename. + For GCS bucket, we do not want '.' as the parent + directory, we want to parse and put together the + GCS filepath correctly. + """ + if str(Path(file_name).parent) != ".": + return str(Path(file_name).parent) + else: + return "" + + def geoparquet_gcs_export( gdf: Union[gpd.GeoDataFrame, dg.GeoDataFrame], gcs_file_path: str, @@ -39,20 +52,25 @@ def geoparquet_gcs_export( file_name: str Filename, with or without .parquet. """ - file_name_sanitized = sanitize_file_path(file_name) + # Parse out file_name into stem (file_name_sanitized) + # and parent (file_directory_sanitized) + file_name_sanitized = Path(sanitize_file_path(file_name)) + file_directory_sanitized = parse_file_directory(file_name) + + # Make sure GCS path includes the directory we want the file to go to + expanded_gcs = f"{Path(gcs_file_path).joinpath(file_directory_sanitized)}/" + expanded_gcs = str(expanded_gcs).replace("gs:/", "gs://") if isinstance(gdf, dg.GeoDataFrame): - gdf.to_parquet( - f"{gcs_file_path}{file_name_sanitized}", overwrite=True, **kwargs - ) + gdf.to_parquet(f"{expanded_gcs}{file_name_sanitized}", overwrite=True, **kwargs) else: - gdf.to_parquet(f"./{file_name_sanitized}.parquet", **kwargs) + gdf.to_parquet(f"{file_name_sanitized}.parquet", **kwargs) fs.put( - f"./{file_name_sanitized}.parquet", - f"{gcs_file_path}{file_name_sanitized}.parquet", + f"{file_name_sanitized}.parquet", + 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