79 lines
3.0 KiB
Python
79 lines
3.0 KiB
Python
"""
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CityLayersTest
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2023 Concordia CERC group
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Project Coder: Milad Aghamohamadnia --- milad.aghamohamadnia@concordia.ca
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"""
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from unittest import TestCase
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import json
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import os
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import time
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import uuid
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from pathlib import Path
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from hub.imports.geometry_factory import GeometryFactory
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from hub.imports.usage_factory import UsageFactory
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from hub.imports.construction_factory import ConstructionFactory
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from hub.exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
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import pandas as pd
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from geopandas import GeoDataFrame
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from shapely.geometry import Polygon
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class CityLayerTest(TestCase):
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@staticmethod
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def _prepare_buildings(bldgs_group):
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target_json = bldgs_group['target']
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adjacent_json = bldgs_group['adjacent']
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target_buildings = [f"building_{target_json['index']}"]
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adjacent_buildings = [f"building_{el}" for el in adjacent_json['Ids']]
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target_dict = [dict(
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name=f"building_{target_json['index']}",
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height=target_json['height_max'],
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idx=target_json['index'],
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uid=target_json['uid'],
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year_built=2005,
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# year_built= 2005 if target_json['year_built']==9999 else target_json['year_built'],
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coords=target_json['coords'],
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function="residential",
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# function= "residential" if target_json['year_built']>2000 else "industry",
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)]
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adjacent_dict = [dict(
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name=f"building_{el['index']}",
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height=el['height_max'],
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idx=el['index'],
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uid=el['uid'],
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year_built=2005,
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# year_built=2005 if el['year_built']==9999 else el['year_built'],
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coords=el['geom']['coordinates'],
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function="residential",
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# function= "residential" if el['year_built']>2000 else "industry",
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) for el in adjacent_json['data']]
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df = pd.DataFrame(target_dict + adjacent_dict)
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geometries = [Polygon(row['coords'][0]) for ix, row in df.iterrows()]
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gdf = GeoDataFrame(df, crs="EPSG:4326", geometry=geometries)
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gdf = gdf.set_crs('EPSG:4326')
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gdf = gdf.to_crs('EPSG:26911')
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return gdf, target_buildings, adjacent_buildings
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def _genidf(self, bldgs_group):
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buildings_df, target_buildings, adjacent_buildings = self._prepare_buildings(bldgs_group)
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#output_path = (Path(__file__).parent / 'tests_outputs').resolve()
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city = GeometryFactory('gpandas', data_frame=buildings_df).city
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ConstructionFactory('nrel', city).enrich()
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UsageFactory('comnet', city).enrich()
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EnergyBuildingsExportsFactory('idf', city, output_path, target_buildings=target_buildings,
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adjacent_buildings=adjacent_buildings).export_debug()
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filepath = os.path.join(output_path, city.name + ".idf")
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newfilepath = filepath[:-4] + "_" + uuid.uuid4().hex[:10] + ".idf"
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os.rename(filepath, newfilepath)
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return newfilepath
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def test_city_layers(self):
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json_path = str((Path(__file__).parent / 'tests_data' / 'city_layers.json').resolve())
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with open(json_path) as json_file:
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data = json.loads(json_file.read())
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self._genidf(data)
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