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Create repository for split city tool

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Koa Wells 2023-08-24 16:38:18 -04:00
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commit 92aaa64955
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232
city_region_splitter.py Normal file
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import json
from pathlib import Path
from shapely.geometry import Polygon
"""
CityRegionSplitter is a tool for splitting a city into a subregions with overlaps allowing for proper SRA calculations.
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2023 Concordia CERC group
Project Coder Koa Wells kekoa.wells@concordia.ca
"""
class CityRegionSplitter:
def __init__(self, city_file):
self._city_file = city_file
self._city = json.load(city_file)
self._buildings = self._city['features']
self._regions_dimension = -1
self._regions = []
def _find_neighbors(self):
regions = []
count = 1
for row in range(self._regions_dimension):
regions.append([])
for col in range(self._regions_dimension):
regions[row].append(count)
count += 1
rows = len(regions)
cols = len(regions[0])
neighbors = {}
# Iterate over each element in the grid
for i in range(rows):
for j in range(cols):
current_region = f'{regions[i][j]}_v1'
while len(current_region) < 7:
current_region = f'0{current_region}'
upper_neighbor = 'None'
lower_neighbor = 'None'
left_neighbor = 'None'
right_neighbor = 'None'
upper_left_neighbor = 'None'
upper_right_neighbor = 'None'
lower_left_neighbor = 'None'
lower_right_neighbor = 'None'
# find upper, lower, left, and right adjacent
if i > 0:
upper_neighbor = f'{regions[i - 1][j]}_v1'
if i < rows - 1:
lower_neighbor = f'{regions[i + 1][j]}_v1'
if j > 0:
left_neighbor = f'{regions[i][j - 1]}_v1'
if j < cols - 1:
right_neighbor = f'{regions[i][j + 1]}_v1'
# find diagonal neighbors
# corners
if i == 0 and j == 0:
lower_right_neighbor = f'{regions[i + 1][j + 1]}_v1'
if i == 0 and j == self._regions_dimension - 1:
lower_left_neighbor = f'{regions[i + 1][j - 1]}_v1'
if i == self._regions_dimension - 1 and j == 0:
upper_right_neighbor = f'{regions[i - 1][j + 1]}_v1'
if i == self._regions_dimension - 1 and j == self._regions_dimension - 1:
upper_left_neighbor = f'{regions[i - 1][j - 1]}_v1'
# middle top row
if i == 0 and 0 < j < self._regions_dimension - 1:
lower_left_neighbor = f'{regions[i + 1][j - 1]}_v1'
lower_right_neighbor = f'{regions[i + 1][j + 1]}_v1'
# middle bottom row
if i == self._regions_dimension - 1 and 0 < j < self._regions_dimension - 1:
upper_left_neighbor = f'{regions[i - 1][j - 1]}_v1'
upper_right_neighbor = f'{regions[i - 1][j + 1]}_v1'
# middle left column
if 0 < i < self._regions_dimension - 1 and j == 0:
upper_right_neighbor = f'{regions[i - 1][j + 1]}_v1'
lower_right_neighbor = f'{regions[i + 1][j + 1]}_v1'
# middle right column
if 0 < i < self._regions_dimension - 1 and j == self._regions_dimension - 1:
upper_left_neighbor = f'{regions[i - 1][j - 1]}_v1'
lower_left_neighbor = f'{regions[i + 1][j - 1]}_v1'
# everything else
if 0 < i < self._regions_dimension - 1 and 0 < j < self._regions_dimension - 1:
lower_right_neighbor = f'{regions[i + 1][j + 1]}_v1'
lower_left_neighbor = f'{regions[i + 1][j - 1]}_v1'
upper_right_neighbor = f'{regions[i - 1][j + 1]}_v1'
upper_left_neighbor = f'{regions[i - 1][j - 1]}_v1'
neighbors[current_region] = [f'{upper_neighbor}',
f'{lower_neighbor}',
f'{left_neighbor}',
f'{right_neighbor}',
f'{upper_left_neighbor}',
f'{upper_right_neighbor}',
f'{lower_left_neighbor}',
f'{lower_right_neighbor}']
final_neighbors = _add_trailing_zeros(neighbors)
return final_neighbors
"""
Generates n x n subregions with a percentage overlap using the top_left_coordinate and bottom_right_coordinate
:param: top_left_coordinate: [longitude, latitude] of top left corner of city
:param: bottom_right_coordinate: [longitude, latitude] of bottom right corner of city
:param: region_dimensions: the number of regions in each directiory; for example 20 creates 20 x 20 subregions
:param: percent_overlap: percentage of overlap between neighboring regions
:param: output_file_name: name out output file
:param: output_path: file path to save the region geojson file
:return: None
"""
def generate_regions(self, top_left_coordinate, bottom_right_coordinate, regions_dimension, percent_overlap, output_file_name, output_path):
# points for
# top_left_coordinate = [-74.022687, 45.722604]
# bottom_right_coordinate = [-73.397182, 45.384048]
top_left_coordinate = top_left_coordinate
bottom_right_coordinate = bottom_right_coordinate
regions_dimension = regions_dimension
self._regions_dimension = regions_dimension
percent_overlap = percent_overlap
output_file_name = output_file_name
output_path = Path(f'{output_path}/{output_file_name}').resolve()
x1 = top_left_coordinate[0]
y1 = top_left_coordinate[1]
x2 = bottom_right_coordinate[0]
y2 = bottom_right_coordinate[1]
regions = [[[] for i in range(regions_dimension)] for j in range(regions_dimension)]
region_x_side_length = (x2 - x1) / regions_dimension
region_y_side_length = (y2 - y1) / regions_dimension
x_current = x1
y_current = y1
row_count = 1
for row in regions:
for column in row:
# append top left corner
column.append([x_current, y_current])
# append bottom left corner
column.append([x_current, y_current + region_y_side_length * (1 + percent_overlap / 2)])
# append bottom right corner
column.append([x_current + region_x_side_length * (1 + percent_overlap / 2),
y_current + region_y_side_length * (1 + percent_overlap / 2)])
# append top right corner
column.append([x_current + region_x_side_length * (1 + percent_overlap / 2), y_current])
# append top left corner again to close the polygon
column.append([x_current, y_current])
x_current = x_current + region_x_side_length * (1 - percent_overlap / 2)
x_current = x1
y_current = y_current + region_y_side_length * (1 - percent_overlap / 2)
row_count += 1
id = 1
feature_collection = {
"type": "FeatureCollection",
"features": []
}
for row in regions:
for column in row:
id_with_zeros = str(id)
while len(id_with_zeros) < 4:
id_with_zeros = f'0{id_with_zeros}'
feature_collection['features'].append(
{
"type": "Feature",
"id": id,
"geometry": {
"type": "Polygon",
"coordinates": [column]
},
"properties":
{
"region_id": f'{id_with_zeros}.bz2'
}
})
id += 1
with open(f'{output_path}.geojson', 'w') as file:
file.write(json.dumps(feature_collection, indent=2))
print(f'Saving region file to {output_path}')
self._regions = feature_collection['features']
def assign_buildings_to_regions(self):
for building in self._buildings:
if building['geometry']['type'] == 'Polygon':
building_centroid = Polygon(building["geometry"]["coordinates"][0]).centroid
elif building['geometry']['type'] == 'MultiPolygon':
# use the centroid of the first polygon inside of the multipolygon
building_centroid = Polygon(building["geometry"]["coordinates"][0][0]).centroid
building['properties']['centroid'] = [building_centroid.x, building_centroid.y]
building['properties']['district_property'] = []
target_regions = []
region_assigned = False
target_region = self._regions[len(self._regions) / 2]
while not region_assigned:
if building_centroid.within(Polygon(target_region['geometry']['coordinates'])):
region_assigned = True
break
target_region_centroid = Polygon(target_region['geometry']['coordinates']).centroid
if building_centroid.x <= target_region_centroid.x:
if building_centroid.y >= target_region_centroid.y:
regions = regions[0:len(regions) / 2]
elif building_centroid.y < target_region_centroid.y:
regions = regions[len(regions) / 2:len(regions) - 1]
elif building_centroid.x > target_region_centroid.x:
if building_centroid.y >= target_region_centroid.y:
regions = regions[0:len(regions) / 2]
elif building_centroid.y < target_region_centroid.y:
regions = regions[len(regions) / 2:len(regions) - 1]

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main.py Normal file
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from city_region_splitter import CityRegionSplitter