Merge branch 'integrating_alkis_codes'

This commit is contained in:
Pilar 2023-01-16 08:23:11 -05:00
commit 78449d83be
5 changed files with 456 additions and 18 deletions

View File

@ -456,20 +456,16 @@ class Idf:
self._idf.intersect_match()
def _add_shading(self, building):
for internal_zone in building.internal_zones:
for thermal_zone in internal_zone.thermal_zones:
for boundary in thermal_zone.thermal_boundaries:
shading = self._idf.newidfobject(self._SHADING, Name=f'{boundary.parent_surface.name}')
coordinates = self._matrix_to_list(boundary.parent_surface.solid_polygon.coordinates,
self._city.lower_corner)
shading.setcoords(coordinates)
solar_reflectance = 1.0 - boundary.outside_solar_absorptance
visible_reflectance = 1.0 - boundary.outside_visible_absorptance
self._idf.newidfobject(self._SHADING_PROPERTY,
Shading_Surface_Name=f'{boundary.parent_surface.name}',
Diffuse_Solar_Reflectance_of_Unglazed_Part_of_Shading_Surface=solar_reflectance,
Diffuse_Visible_Reflectance_of_Unglazed_Part_of_Shading_Surface=visible_reflectance,
Fraction_of_Shading_Surface_That_Is_Glazed=0)
for surface in building.surfaces:
shading = self._idf.newidfobject(self._SHADING, Name=f'{surface.name}')
coordinates = self._matrix_to_list(surface.solid_polygon.coordinates,
self._city.lower_corner)
shading.setcoords(coordinates)
solar_reflectance = surface.short_wave_reflectance
self._idf.newidfobject(self._SHADING_PROPERTY,
Shading_Surface_Name=f'{surface.name}',
Diffuse_Solar_Reflectance_of_Unglazed_Part_of_Shading_Surface=solar_reflectance,
Fraction_of_Shading_Surface_That_Is_Glazed=0)
# todo: Add properties for that name

View File

@ -48,7 +48,7 @@ class SimplifiedRadiosityAlgorithm:
for surface in building.surfaces:
surface_dict = {
'@id': f'{surface.id}',
'@ShortWaveReflectance': f'{surface.swr}'
'@ShortWaveReflectance': f'{surface.short_wave_reflectance}'
}
for point_index, point in enumerate(surface.perimeter_polygon.coordinates):
point = self._correct_point(point)

View File

@ -58,8 +58,7 @@ class GPandas:
if self._city is None:
self._city = City(self._lower_corner, self._upper_corner, self._srs_name)
for scene_index, bldg in self._scene.iterrows():
geometry = bldg.geom
polygon = ShapelyPoly(geometry['coordinates'][0])
polygon = bldg.geometry
height = float(bldg['height'])
building_mesh = trimesh.creation.extrude_polygon(polygon, height)
trimesh.repair.fill_holes(building_mesh)
@ -71,7 +70,6 @@ class GPandas:
function = cte.RESIDENTIAL
else:
function = cte.INDUSTRY
surfaces = []
for face_index, face in enumerate(building_mesh.faces):
points = []

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@ -0,0 +1,81 @@
"""
CityLayersTest
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2023 Concordia CERC group
Project Coder: Milad Aghamohamadnia --- milad.aghamohamadnia@concordia.ca
"""
from unittest import TestCase
import json
import os
import time
import uuid
from pathlib import Path
from imports.geometry_factory import GeometryFactory
from imports.usage_factory import UsageFactory
from imports.construction_factory import ConstructionFactory
from exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
import pandas as pd
from geopandas import GeoDataFrame
from shapely.geometry import Polygon
class CityLayerTest(TestCase):
@staticmethod
def _prepare_buildings(bldgs_group):
target_json = bldgs_group['target']
adjacent_json = bldgs_group['adjacent']
target_buildings = [f"building_{target_json['index']}"]
adjacent_buildings = [f"building_{el}" for el in adjacent_json['Ids']]
target_dict = [dict(
name=f"building_{target_json['index']}",
height=target_json['height_max'],
idx=target_json['index'],
uid=target_json['uid'],
year_built=2005,
# year_built= 2005 if target_json['year_built']==9999 else target_json['year_built'],
coords=target_json['coords'],
function="residential",
# function= "residential" if target_json['year_built']>2000 else "industry",
)]
adjacent_dict = [dict(
name=f"building_{el['index']}",
height=el['height_max'],
idx=el['index'],
uid=el['uid'],
year_built=2005,
# year_built=2005 if el['year_built']==9999 else el['year_built'],
coords=el['geom']['coordinates'],
function="residential",
# function= "residential" if el['year_built']>2000 else "industry",
) for el in adjacent_json['data']]
df = pd.DataFrame(target_dict + adjacent_dict)
geometries = [Polygon(row['coords'][0]) for ix, row in df.iterrows()]
gdf = GeoDataFrame(df, crs="EPSG:4326", geometry=geometries)
gdf = gdf.set_crs('EPSG:4326')
gdf = gdf.to_crs('EPSG:26911')
return gdf, target_buildings, adjacent_buildings
def _genidf(self, bldgs_group):
t0 = time.time()
buildings_df, target_buildings, adjacent_buildings = self._prepare_buildings(bldgs_group)
output_path = (Path(__file__).parent / 'tests_outputs').resolve()
city = GeometryFactory('gpandas', data_frame=buildings_df).city
ConstructionFactory('nrel', city).enrich()
UsageFactory('comnet', city).enrich()
EnergyBuildingsExportsFactory('idf', city, output_path, target_buildings=target_buildings).export_debug()
filepath = os.path.join(output_path, city.name + ".idf")
newfilepath = filepath[:-4] + "_" + uuid.uuid4().hex[:10] + ".idf"
print(filepath)
print(newfilepath)
os.rename(filepath, newfilepath)
print(f"It took {round((time.time() - t0), 0)} seconds")
return newfilepath
def test_city_layers(self):
json_path = str((Path(__file__).parent / 'tests_data' / 'city_layers.json').resolve())
with open(json_path) as json_file:
data = json.loads(json_file.read())
self._genidf(data)

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@ -0,0 +1,363 @@
{
"target": {
"layerName": "public.building_footprint_year_built_height_max",
"height_max": 13,
"index": 287809,
"year_built": 1952,
"uid": 1039258,
"centroid": [
-73.59838038682938,
45.493163447971085
],
"area": 119.59674983363819,
"coords": [
[
[
-73.59848499298096,
45.49319823193981
],
[
-73.59841525554657,
45.493239596593924
],
[
-73.5982757806778,
45.49313054425838
],
[
-73.59834551811218,
45.49308541909225
],
[
-73.59848499298096,
45.49319823193981
]
]
]
},
"adjacent": {
"data": [
{
"__typename": "building_footprint_year_built_height_max",
"index": 1586,
"height_max": 12,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.59812,
45.493495
],
[
-73.598085,
45.493525
],
[
-73.598017,
45.493487
],
[
-73.59812,
45.493398
],
[
-73.59821,
45.493449
],
[
-73.598142,
45.493508
],
[
-73.59812,
45.493495
]
]
]
},
"year_built": 1929,
"uid": 1039256
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 11964,
"height_max": 11,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.5984992790639,
45.4929564079915
],
[
-73.598462,
45.493019
],
[
-73.598313,
45.492975
],
[
-73.5983570524121,
45.4929010354563
],
[
-73.5984992790639,
45.4929564079915
]
]
]
},
"year_built": 1965,
"uid": 1039090
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 11965,
"height_max": 11,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.5983570524121,
45.4929010354563
],
[
-73.598394,
45.492839
],
[
-73.598543,
45.492883
],
[
-73.5984992790639,
45.4929564079915
],
[
-73.5983570524121,
45.4929010354563
]
]
]
},
"year_built": 1965,
"uid": 1039088
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 252931,
"height_max": 22,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.598625,
45.492713
],
[
-73.598668,
45.49268
],
[
-73.598755,
45.492735
],
[
-73.598659,
45.49281
],
[
-73.598521,
45.492723
],
[
-73.598575,
45.492682
],
[
-73.598625,
45.492713
]
]
]
},
"year_built": 1983,
"uid": 1039086
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 275748,
"height_max": 12,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.597909,
45.493307
],
[
-73.598014,
45.493349
],
[
-73.597928,
45.493454
],
[
-73.597823,
45.493412
],
[
-73.597909,
45.493307
]
]
]
},
"year_built": 1929,
"uid": 1039091
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 308721,
"height_max": 15,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.598655,
45.493348
],
[
-73.598681,
45.493326
],
[
-73.59876,
45.493373
],
[
-73.598652,
45.493462
],
[
-73.598595,
45.493427
],
[
-73.598621,
45.493406
],
[
-73.598571,
45.493376
],
[
-73.598627,
45.493331
],
[
-73.598655,
45.493348
]
]
]
},
"year_built": 1950,
"uid": 1039163
},
{
"__typename": "building_footprint_year_built_height_max",
"index": 312417,
"height_max": 14,
"geom": {
"type": "Polygon",
"crs": {
"type": "name",
"properties": {
"name": "urn:ogc:def:crs:EPSG::4326"
}
},
"coordinates": [
[
[
-73.598836,
45.49324
],
[
-73.598723,
45.493191
],
[
-73.598873,
45.493021
],
[
-73.598985,
45.493069
],
[
-73.598836,
45.49324
]
]
]
},
"year_built": 1890,
"uid": 1039165
}
],
"Ids": [
1586,
11964,
11965,
252931,
275748,
308721,
312417
]
}
}