Dynamic Mapping: Built with Leaflet, this interactive map integrates spatial data directly into your browser.
On-the-Fly Analysis: Using PyScript and Shapely, we perform real-time spatial analysis to compute neighboring counties for Texas.
Scientific Approach: The analysis determines if county boundaries touch, ensuring robust spatial measurements.
Learn More: For an in-depth discussion on geostatistical predicted surfaces and spatial autocorrelation, check out my detailed post on my old weblog here.
Web-Based Power: Experience the cutting edge of spatial analysis performed directly on the web.
import json
from shapely.geometry import shape
from pyscript import display
import statistics
from js import window
try:
TexCounty = window.TexCounty
except Exception as e:
display("Error: TexCounty variable not defined. Check your data/TexasCounty.js file.", target="adjOutput")
raise e
txcounty_dict = TexCounty.to_py()
features = txcounty_dict.get("features", [])
if not features:
result_str = "No features found in TexCounty data."
else:
polygons = []
county_names = []
for i, feature in enumerate(features):
if feature.get("geometry"):
polygons.append(shape(feature.get("geometry")))
name = feature.get("properties", {}).get("name", f"County {i+1}")
county_names.append(name)
def is_neighbor(p1, p2):
return p1.touches(p2)
n = len(polygons)
adj_matrix = [[0] * n for _ in range(n)]
for i in range(n):
for j in range(n):
if i != j and is_neighbor(polygons[i], polygons[j]):
adj_matrix[i][j] = 1
num_neighbors = [sum(row) for row in adj_matrix]
avg_neighbors = sum(num_neighbors) / n if n > 0 else 0
max_neighbors = max(num_neighbors)
min_neighbors = min(num_neighbors)
max_index = num_neighbors.index(max_neighbors)
min_index = num_neighbors.index(min_neighbors)
county_max = county_names[max_index]
county_min = county_names[min_index]
try:
mode_neighbors = statistics.mode(num_neighbors)
except statistics.StatisticsError:
mode_neighbors = statistics.multimode(num_neighbors)
result_str = "TexCounty Adjacency Calculation (Scientific Approach):\n"
result_str += f"Number of counties: {n}\n"
result_str += f"Average number of neighbors: {avg_neighbors:.2f}\n"
result_str += f"County with most neighbors: {county_max} ({max_neighbors} neighbors)\n"
result_str += f"County with least neighbors: {county_min} ({min_neighbors} neighbors)\n"
result_str += f"Mode of neighbors: {mode_neighbors}\n"
display(result_str, target="adjOutput")
