def load_municipality_geodata() -> GeoDataFrame:
data = gpd.read_file(
abs_path("src/swissBOUNDARIES3D_1_3_TLM_HOHEITSGEBIET.shp"))
# We are only interested in Swiss Municipalities
data = data[data["ICC"] == "CH"]
data["TYPE"] = data["BFS_NUMMER"].apply(id_to_typology.get)
data.loc[data["NAME"].apply(_is_lake), "TYPE"] = "lake"
data["COLOR"] = data["TYPE"].apply(type_to_color.get)
return data
x, y = list(
zip(*data.apply(
lambda row: converter.WGS84toLV03(row.latitude, row.longitude)[:2],
axis=1)))
geodata = geopandas.GeoDataFrame(data,
geometry=geopandas.points_from_xy(x=x,
y=y))
return geodata
if __name__ == '__main__':
import matplotlib.pyplot as plt
# Load Municipality and City Data
municipality_data = load_municipality_geodata()
city_data = read_csv(abs_path("src/city_coordinates.csv"))
city_geodata = data_to_geodata(data=city_data)
# Plot Municipalities
ax = municipality_data.plot(color=municipality_data["COLOR"],
edgecolor="#999999",
linewidth=0.5,
figsize=(15, 10))
ax.set_axis_off()
plt.legend(handles=municipality_type_legend_handles)
# Plot cities
city_geodata.plot(ax=ax, color="black")
for x_, y_, label in zip(city_geodata.geometry.x, city_geodata.geometry.y,
def load_municipality_geodata() -> GeoDataFrame:
data = gpd.read_file(
abs_path("src/swissBOUNDARIES3D_1_3_TLM_HOHEITSGEBIET.shp"))
# We are only interested in Swiss Municipalities
data = data[data["ICC"] == "CH"]
data["TYPE"] = data["BFS_NUMMER"].apply(id_to_typology.get)
data.loc[data["NAME"].apply(_is_lake), "TYPE"] = "lake"
data["COLOR"] = data["TYPE"].apply(type_to_color.get)
return data
if __name__ == '__main__':
import matplotlib.pyplot as plt
test_data = load_municipality_geodata()
base = test_data.plot(color=test_data["COLOR"],
edgecolor="#999999",
linewidth=0.5,
figsize=(15, 10))
# plt.title("Municipalities of Switzerland", size=25)
base.set_axis_off()
plt.legend(handles=municipality_type_legend_handles)
plt.tight_layout()
plt.savefig(abs_path("src/map.png"))
import json
from statistics import mode
from swiss_municipalities.paths import abs_path
with open(abs_path("src/id_to_type.json")) as id_to_type_file:
id_to_type_raw = json.load(id_to_type_file)
id_to_typology = {
int(municipality_id.replace("|", "")): municipality_info["value"]
for municipality_id, municipality_info in id_to_type_raw["values"].items()
}
# Manually rewrote from wikipedia, e.g.
# https://en.wikipedia.org/wiki/Villaz,_Switzerland -- copy the SFOS number of the municipalities that resulted in the
# merged one
_merged_municipalities = {
5399: [5135, 5129, 5102, 5095, 5105], # Verzasca
3544: [3521, 3522], # Bergün Filisur
3714: [3691, 3693, 3694], # Rheinwald
5287: [5286, 5285, 5284, 5283], # Riviera
6417: [6402, 6409, 6410, 6411, 6414, 6415], # La Grande-Béroche
293: [134, 140], # Wädenswil
295: [132], # Horgen
294: [222], # Elgg
292: [44, 36, 42], # Stammheim
2237: [2185, 2213, 2221], # Prez
2117: [2111, 2116], # Villaz
889: [873, 874, 876], # Thurnen
# For the following there is just no typology to be found anywhere