feat: add script to translate urban and rural shapefiles to USA tamu loadzones #319
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,105 @@ | ||
| import geopandas as gpd | ||
| import pandas as pd | ||
| from powersimdata.input.grid import Grid | ||
| from shapely.geometry import Point, Polygon | ||
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|
||
| from prereise.utility.translate_urban_rural_to_usa_tamu import ( | ||
| create_substation_gdf, | ||
| create_usa_tamu_convex_hull_shapefile, | ||
| fix_lz_border, | ||
| format_states_gdf, | ||
| ) | ||
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| WA_lz_polygon = Polygon([(1, 1), (0, 5), (5, 6), (4, 1)]) | ||
| CA_lz_polygon = Polygon([(0, 10), (0, 15), (5, 15), (5, 10)]) | ||
| WA_border_polygon = Polygon([(0, 0), (0, 5), (5, 5), (5, 0)]) | ||
| CA_border_polygon = Polygon([(0, 10), (0, 20), (3, 20), (3, 10)]) | ||
| HI_border_polygon = Polygon([(100, 100), (100, 105), (105, 105)]) | ||
|
|
||
| # Mock US State borders | ||
| states = gpd.GeoDataFrame( | ||
| { | ||
| "geometry": [WA_border_polygon, CA_border_polygon, HI_border_polygon], | ||
| "STUSPS": ["WA", "CA", "HI"], | ||
| } | ||
| ) | ||
| formatted_states = gpd.GeoDataFrame( | ||
| { | ||
| "geometry": {"WA": WA_border_polygon, "CA": CA_border_polygon}, | ||
| "state": {"WA": "WA", "CA": "CA"}, | ||
| } | ||
| ) | ||
| sub_gdf = gpd.GeoDataFrame( | ||
| { | ||
| "zone": {122: "Bay Area", 6134: "Washington"}, | ||
| "geometry": {122: Point(2, 3), 6134: Point(14, 4)}, | ||
| } | ||
| ) | ||
|
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||
|
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||
| def test_format_states_gdf(): | ||
| results = format_states_gdf(states) | ||
| assert formatted_states.to_dict() == results.to_dict() | ||
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| class MockGrid: | ||
| def __init__(self): | ||
| """Constructor""" | ||
| self.bus2sub = pd.DataFrame({"sub_id": {0: 122, 1: 122, 2: 6134}}) | ||
| self.bus = pd.DataFrame({"zone_id": {0: 204, 1: 204, 2: 201}}) | ||
| self.id2zone = {204: "Bay Area", 201: "Washington"} | ||
| self.sub = pd.DataFrame({"lon": {122: 2, 6134: 14}, "lat": {122: 3, 6134: 4}}) | ||
|
|
||
| @property | ||
| def __class__(self): | ||
| """If anyone asks, I'm a Grid object!""" | ||
| return Grid | ||
|
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|
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||
| def test_create_substation_gdf(): | ||
| mock_grid = MockGrid() | ||
| results = create_substation_gdf(mock_grid) | ||
| assert sub_gdf.to_dict() == results.to_dict() | ||
|
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| def test_fix_lz_border_single_lz(): | ||
| results = fix_lz_border(formatted_states, "WA", WA_lz_polygon) | ||
| expected = WA_border_polygon | ||
| assert expected == results | ||
|
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| def test_fix_lz_border_multi_lz(): | ||
| results = fix_lz_border(formatted_states, "CA", CA_lz_polygon) | ||
| expected = Polygon([(0, 15), (3, 15), (3, 10), (0, 10)]) | ||
| assert expected == results | ||
|
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|
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| def test_create_usa_tamu_convex_hull_shapefile(): | ||
| # gdf where CA substations match CA_lz_polygon | ||
| sub_gdf_2 = gpd.GeoDataFrame( | ||
| { | ||
| "zone": { | ||
| 122: "Bay Area", | ||
| 123: "Bay Area", | ||
| 124: "Bay Area", | ||
| 125: "Bay Area", | ||
| 6134: "Washington", | ||
| }, | ||
| "geometry": { | ||
| 122: Point(0, 10), | ||
| 123: Point(0, 15), | ||
| 124: Point(5, 15), | ||
| 125: Point(5, 10), | ||
| 6134: Point(14, 4), | ||
| }, | ||
| } | ||
| ) | ||
| results = create_usa_tamu_convex_hull_shapefile(sub_gdf_2, formatted_states) | ||
| expected = { | ||
| "geometry": { | ||
| "Bay Area": Polygon([(0, 15), (3, 15), (3, 10), (0, 10)]), | ||
| "Washington": WA_border_polygon, | ||
| }, | ||
| "state": {"Bay Area": "CA", "Washington": "WA"}, | ||
| } | ||
| assert expected == results.to_dict() |
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I think we could reuse the same lookup from powersimdata, e.g.