我正在嘗試創建北美地圖的voronoi圖，這意味著根據其首都的位置有效地將國家切成碎片。為此，我使用Geopandas獲取北美的地理數據，然后使用GeoVoronoi庫創建一個Voronoi圖：import matplotlib.pyplot as pltimport geopandas as gpdfrom shapely.ops import cascaded_unionfrom geovoronoi.plotting import subplot_for_map, plot_voronoi_polys_with_points_in_areafrom geovoronoi import voronoi_regions_from_coords, points_to_coordslogging.basicConfig(level=logging.INFO)geovoronoi_log = logging.getLogger('geovoronoi')geovoronoi_log.setLevel(logging.INFO)geovoronoi_log.propagate = True## load geo data#world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))cities = gpd.read_file(gpd.datasets.get_path('naturalearth_cities'))# focus on South America, convert to World Mercator (unit: meters)north_am = world[world.continent == 'North America'].to_crs(epsg=3395)cities = cities.to_crs(north_am.crs) # convert city coordinates to same CRS!# create the bounding shape as union of all South American countries' shapesnorth_am_shape = cascaded_union(north_am.geometry)north_am_cities = cities[cities.geometry.within(north_am_shape)] # reduce to cities in South America## calculate the Voronoi regions, cut them with the geographic area shape and assign the points to them## convert the pandas Series of Point objects to NumPy array of coordinatescoords = points_to_coords(north_am_cities.geometry)# calculate the regionspoly_shapes, pts, poly_to_pt_assignments = voronoi_regions_from_coords(coords, north_am_shape)## Plotting#fig, ax = subplot_for_map()plot_voronoi_polys_with_points_in_area(ax, north_am_shape, poly_shapes, pts)ax.set_title('Cities data for South America from GeoPandas\nand Voronoi regions around them')plt.tight_layout()plt.savefig('using_geopandas.png')plt.show()這些代碼大部分直接取自 Geovoronoi 文檔。然而，當我運行它時，我收到以下錯誤：
1 回答
aluckdog
TA貢獻1847條經驗 獲得超7個贊
您收到的錯誤源于以下事實：您正在提取的城市信息包含北美城市很少，或者它們未被正確識別為北美境內。您的問題是關于基于首都創建Voronoi圖，因此我包含了一個指向美國首都數據集的鏈接，以便您可以使用可靠數量的城市測試示例：
import matplotlib.pyplot as plt
import numpy as np
import geopandas as gpd
from geovoronoi.plotting import subplot_for_map, plot_voronoi_polys_with_points_in_area
from geovoronoi import voronoi_regions_from_coords
cities = gpd.read_file('us-state-capitals.csv')
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
usa = world[world.name == 'United States of America']
usa = usa.to_crs(epsg=3857)
usa_shape = usa.iloc[0].geometry
coords = np.array(list(zip(cities.Shape_X,cities.Shape_Y)), dtype='float')
poly_shapes, pts, poly_to_pt_assignments = voronoi_regions_from_coords(coords, usa_shape)
fig, ax = subplot_for_map()
plot_voronoi_polys_with_points_in_area(ax, usa_shape, poly_shapes, coords)
ax.set_title('Cities data for South America from GeoPandas\nand Voronoi regions around them')
plt.tight_layout()
plt.savefig('using_geopandas.png')
plt.show()
生產：
對于北美，您可以下載城市 CSV 并使用以下代碼：
import matplotlib.pyplot as plt
import geopandas as gpd
from shapely.ops import cascaded_union
from geovoronoi.plotting import subplot_for_map, plot_voronoi_polys_with_points_in_area
from geovoronoi import voronoi_regions_from_coords, points_to_coords
cities = gpd.read_file('world_populated_cities.csv')
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))
na = world[world.continent == 'North America']
na = na.to_crs(epsg=3857)
cities.geometry.to_crs(epsg=3857)
na_shape = cascaded_union(na.geometry)
cities = cities.to_crs(na.crs) # convert city coordinates to same CRS!
cities = cities[cities.geometry.within(na_shape)]
coords = points_to_coords(cities.geometry)
poly_shapes, pts, poly_to_pt_assignments = voronoi_regions_from_coords(coords, na_shape)
fig, ax = subplot_for_map()
plot_voronoi_polys_with_points_in_area(ax, na_shape, poly_shapes, coords)
ax.set_title('Cities data for South America from GeoPandas\nand Voronoi regions around them')
plt.tight_layout()
plt.savefig('using_geopandas.png')
plt.show()
生產：
添加回答
舉報
0/150
提交
取消