use_cases¶
Functions related to the four different use cases
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home
(home_data: geopandas.geodataframe.GeoDataFrame, uc_dict: dict) → geopandas.geodataframe.GeoDataFrame[source]¶ Calculate placements and energy distribution for use case hpc.
Parameters: - home_data – gpd.GeoDataFrame info about house types
- uc_dict – dict contains basic run info like region boundary and save directory
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hpc
(hpc_points: geopandas.geodataframe.GeoDataFrame, uc_dict: dict) → geopandas.geodataframe.GeoDataFrame[source]¶ Calculate placements and energy distribution for use case hpc.
Parameters: - hpc_points – gpd.GeoDataFrame GeoDataFrame of possible hpc locations
- uc_dict – dict contains basic run info like region boundary and save directory
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match_existing_points
(region_points: geopandas.geodataframe.GeoDataFrame, region_poi: geopandas.geodataframe.GeoDataFrame)[source]¶
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public
(public_points: geopandas.geodataframe.GeoDataFrame, public_data: geopandas.geodataframe.GeoDataFrame, uc_dict: dict) → geopandas.geodataframe.GeoDataFrame[source]¶ Calculate placements and energy distribution for use case hpc.
Parameters: - public_points – gpd.GeoDataFrame existing public charging points
- public_data – gpd.GeoDataFrame clustered POI
- uc_dict – dict contains basic run info like region boundary and save directory
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work
(landuse: geopandas.geodataframe.GeoDataFrame, weights_dict: dict, uc_dict: dict) → geopandas.geodataframe.GeoDataFrame[source]¶ Calculate placements and energy distribution for use case hpc.
Parameters: - landuse – gpd.GeoDataFrame work areas by land use
- weights_dict – dict weights for different land use types
- uc_dict – dict contains basic run info like region boundary and save directory