Merge pull request #546 from Breakthrough-Energy/daniel/bus_to_neem_fix

fix: correct generation of duplicated bus entries in bus-to-NEEM-region mapping

powersimdata/design/investment/create_mapping_files.py

@@ -4,6 +4,7 @@
 
 from powersimdata.design.investment import const
 from powersimdata.input.grid import Grid
+from powersimdata.utility.distance import haversine
 from powersimdata.utility.helpers import _check_import
 
 
@@ -67,6 +68,29 @@ def _find_nearest(series, polygons, search_dist):
     points_in_regions = gpd.sjoin(left_df=left_df, right_df=right_df, op="intersects")
     points_in_regions["dist"] = 0
 
+    # Since polygons may overlap, there can be duplicated buses that we want to filter
+    duplicated = points_in_regions.loc[points_in_regions.index.duplicated(keep=False)]
+    to_drop = set()
+    for bus in set(duplicated["bus_id"]):
+        entries = duplicated.query("bus_id == @bus")
+        coords = entries["geometry"].iloc[0].coords[0]  # First duped entry, only point
+        regions = set(entries["name_abbr"])  # noqa: F841
+        candidates = points_in_regions.query(
+            "index not in @duplicated.index and name_abbr in @regions"
+        )
+        neighbor = candidates.apply(
+            lambda x: haversine((x.geometry.x, x.geometry.y), coords), axis=1
+        ).idxmin()
+        closest_region = candidates.loc[neighbor, "name_abbr"]  # noqa: F841
+        # There may be more than two overlapping geometries, capture all but the closest
+        drop_regions = set(entries.query("name_abbr != @closest_region")["name_abbr"])
+        # Since indices are duplicated, we need to drop via two-column tuples
+        to_drop |= {(bus, d) for d in drop_regions}
+
+    points_in_regions = points_in_regions.loc[
+        ~points_in_regions.set_index(["bus_id", "name_abbr"]).index.isin(to_drop)
+    ]
+
     # Find closest Polygons, for points that don't fall within any
     missing_indices = set(left_df.index) - set(points_in_regions.index)
     points_not_in_regions = left_df.loc[missing_indices]
@@ -184,7 +208,7 @@ def write_bus_neem_map(base_grid):
         raise TypeError("base_grid must be a Grid instance")
     df_pts_bus = bus_to_neem_reg(base_grid.bus)
     df_pts_bus.sort_index(inplace=True)
-    os.makedirs(const.bus_neem_regions_path, exist_ok=True)
+    os.makedirs(os.path.dirname(const.bus_neem_regions_path), exist_ok=True)
     df_pts_bus.to_csv(const.bus_neem_regions_path)
 
 
@@ -198,7 +222,7 @@ def write_bus_reeds_map(base_grid):
         raise TypeError("base_grid must be a Grid instance")
     df_pts_bus = bus_to_reeds_reg(base_grid.bus)
     df_pts_bus.sort_index(inplace=True)
-    os.makedirs(const.bus_reeds_regions_path, exist_ok=True)
+    os.makedirs(os.path.dirname(const.bus_reeds_regions_path), exist_ok=True)
     df_pts_bus.to_csv(const.bus_reeds_regions_path)
 
 

powersimdata/design/investment/data/buses_NEEMregion.csv

@@ -12358,7 +12358,6 @@ bus_id,name_abbr,dist,lat,lon
 12357,PJM E,0.0,40.0887,-75.6346
 12358,PJM E,0.0,40.0887,-75.6346
 12359,PJM ROM,0.0,39.9515,-75.826
-12359,PJM E,0.0,39.9515,-75.826
 12360,PJM E,0.0,39.8624,-75.8187
 12361,PJM E,0.0,39.9648,-75.7912
 12362,PJM E,0.0,39.9648,-75.7912
@@ -12458,10 +12457,8 @@ bus_id,name_abbr,dist,lat,lon
 12456,PJM E,0.0,39.8364,-75.8027
 12457,PJM E,0.0,39.8364,-75.8027
 12458,PJM E,0.0,39.8364,-75.8027
-12459,PJM E,0.0,39.9024,-75.8392
 12459,PJM ROM,0.0,39.9024,-75.8392
 12460,PJM ROM,0.0,39.9024,-75.8392
-12460,PJM E,0.0,39.9024,-75.8392
 12461,PJM ROM,0.0,41.1524,-77.3123
 12462,PJM ROM,0.0,41.1524,-77.3123
 12463,PJM ROM,0.0,41.2429,-77.2389
@@ -36057,7 +36054,6 @@ bus_id,name_abbr,dist,lat,lon
 36053,PJM ROR,0.0,39.3891,-83.3393
 36054,PJM ROR,0.0,39.2689,-83.432
 36055,NonRTO Midwest,0.0,39.6566,-83.5378
-36055,PJM ROR,0.0,39.6566,-83.5378
 36056,PJM ROR,0.0,39.7052,-83.3107
 36057,PJM ROR,0.0,39.6489,-83.3377
 36058,NonRTO Midwest,0.003978078694527869,39.479,-83.5037
@@ -42496,7 +42492,6 @@ bus_id,name_abbr,dist,lat,lon
 42491,MISO IN,0.0,38.0288,-87.5769
 42492,MISO IN,0.0,38.0288,-87.5769
 42493,MISO IN,0.0,38.0811,-87.553
-42494,NonRTO Midwest,0.0,37.9335,-87.5617
 42494,MISO IN,0.0,37.9335,-87.5617
 42495,MISO IN,0.0,38.0137,-87.5274
 42496,NonRTO Midwest,0.0,37.9065,-87.5288
@@ -43089,7 +43084,6 @@ bus_id,name_abbr,dist,lat,lon
 43083,PJM ROR,0.0,42.2138,-88.7904
 43084,PJM ROR,0.0,42.3539,-88.6689
 43085,MISO WUMS,0.0,42.4947,-88.6446
-43085,PJM ROR,0.0,42.4947,-88.6446
 43086,PJM ROR,0.0,42.4093,-88.6218
 43087,PJM ROR,0.0,42.4093,-88.6218
 43088,PJM ROR,0.0,42.3461,-88.9741
@@ -47993,9 +47987,7 @@ bus_id,name_abbr,dist,lat,lon
 47986,MISO WUMS,0.0,42.598,-89.1008
 47987,MISO WUMS,0.0,42.598,-89.1008
 47988,MISO WUMS,0.0,42.5008,-89.1299
-47988,PJM ROR,0.0,42.5008,-89.1299
 47989,MISO WUMS,0.0,42.5008,-89.1299
-47989,PJM ROR,0.0,42.5008,-89.1299
 47990,MISO WUMS,0.0,42.5598,-88.7798
 47991,PJM ROR,0.0,42.4831,-88.8725
 47992,PJM ROR,0.0,42.4831,-88.8725
@@ -48141,7 +48133,6 @@ bus_id,name_abbr,dist,lat,lon
 48132,MISO WUMS,0.0,42.6161,-88.3851
 48133,MISO WUMS,0.0,42.6161,-88.3851
 48134,MISO WUMS,0.0,42.496,-88.5134
-48134,PJM ROR,0.0,42.496,-88.5134
 48135,MISO W,0.0,45.9493,-91.938
 48136,MISO WUMS,0.0,43.2861,-88.2452
 48137,MISO WUMS,0.0,43.2861,-88.2452