diff --git a/.github/workflows/relay-maps.yml b/.github/workflows/relay-maps.yml
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+++ b/.github/workflows/relay-maps.yml
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+name: Update Relay Maps
+
+on:
+ # Run after the "Update Relay Data" workflow completes
+ workflow_run:
+ workflows: ["Update Relay Data"]
+ types:
+ - completed
+ # Also allow manual triggering
+ workflow_dispatch:
+
+permissions:
+ contents: write
+
+jobs:
+ update-relay-maps:
+ runs-on: ubuntu-latest
+ if: ${{ github.event.workflow_run.conclusion == 'success' || github.event_name == 'workflow_dispatch' }}
+
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v4
+ with:
+ fetch-depth: 100 # Need deeper history
+
+ - name: Set up Python
+ uses: actions/setup-python@v5
+ with:
+ python-version: '3.x'
+
+ - name: Install Python dependencies
+ run: |
+ python -m pip install --upgrade pip
+ pip install matplotlib pandas numpy folium scipy
+
+ - name: Generate relay maps
+ run: |
+ mkdir -p assets
+
+ # Execute the script
+ python scripts/generate_relay_map.py
+
+ - name: Check for changes
+ id: git-check
+ run: |
+ git add assets/relay_locations_static.png assets/relay_locations_heatmap.png assets/relay_locations_interactive.html
+ git diff --staged --exit-code || echo "changes=true" >> $GITHUB_OUTPUT
+
+ - name: Commit and push changes
+ if: steps.git-check.outputs.changes == 'true'
+ run: |
+ git config --local user.email "action@github.com"
+ git config --local user.name "GitHub Action"
+ git commit -m "Update relay location maps - $(date -u)"
+ git push
+ env:
+ GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
diff --git a/assets/relay_locations_heatmap.png b/assets/relay_locations_heatmap.png
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diff --git a/assets/relay_locations_interactive.html b/assets/relay_locations_interactive.html
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diff --git a/assets/relay_locations_static.png b/assets/relay_locations_static.png
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diff --git a/scripts/generate_relay_map.py b/scripts/generate_relay_map.py
new file mode 100755
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+++ b/scripts/generate_relay_map.py
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+#!/usr/bin/env python3
+"""
+Generate World Map of Nostr Relay Locations
+
+This script reads the nostr_relays.csv file, which contains information about
+BitChat-compatible Nostr relays, including their geographical coordinates.
+It generates both an interactive HTML map and a static PNG image showing
+the distribution of relays around the world.
+
+The maps are saved in the assets directory.
+"""
+
+import os
+import pandas as pd
+import matplotlib.pyplot as plt
+import folium
+from folium.plugins import MarkerCluster
+import numpy as np
+from matplotlib.colors import LinearSegmentedColormap
+import time
+
+def create_interactive_map(df, output_path):
+ """
+ Create an interactive HTML map showing relay locations with clustering.
+
+ Args:
+ df: DataFrame containing relay data with Latitude and Longitude columns
+ output_path: Path to save the HTML map
+ """
+ # Create map centered at (0, 0) with zoom level 2
+ world_map = folium.Map(location=[0, 0], zoom_start=2, tiles='CartoDB positron')
+
+ # Add marker cluster
+ marker_cluster = MarkerCluster().add_to(world_map)
+
+ # Add markers for each relay
+ for idx, row in df.iterrows():
+ folium.Marker(
+ location=[row['Latitude'], row['Longitude']],
+ popup=row['Relay URL'],
+ icon=folium.Icon(color='blue', icon='signal', prefix='fa')
+ ).add_to(marker_cluster)
+
+ # Save map
+ world_map.save(output_path)
+
+ return len(df)
+
+def create_static_map(df, output_path):
+ """
+ Create a static PNG map showing relay locations on a simple world map.
+
+ Args:
+ df: DataFrame containing relay data with Latitude and Longitude columns
+ output_path: Path to save the PNG map
+ """
+ plt.figure(figsize=(15, 10))
+
+ # Create a simple base map
+ ax = plt.axes()
+ ax.set_facecolor('#DDEEFF') # Light blue background for oceans
+
+ # Draw a simple grid
+ for i in range(-180, 181, 30):
+ plt.axvline(x=i, color='#CCCCCC', linestyle='--', alpha=0.5)
+
+ for i in range(-90, 91, 30):
+ plt.axhline(y=i, color='#CCCCCC', linestyle='--', alpha=0.5)
+
+ # Set map limits
+ plt.xlim(-180, 180)
+ plt.ylim(-90, 90)
+
+ # Plot relay locations
+ plt.scatter(
+ df['Longitude'],
+ df['Latitude'],
+ alpha=0.7,
+ c='blue',
+ s=30,
+ edgecolor='white',
+ linewidth=0.5
+ )
+
+ # Add title and labels
+ plt.title('Global Distribution of BitChat-Compatible Nostr Relays', fontsize=16)
+
+ # Add timestamp
+ timestamp = time.strftime("%Y-%m-%d", time.localtime())
+ plt.annotate(
+ f'Generated: {timestamp} | Total Relays: {len(df)}',
+ xy=(0.02, 0.02),
+ xycoords='axes fraction',
+ fontsize=10,
+ bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.8)
+ )
+
+ # Add labels for equator and prime meridian
+ plt.text(0, -5, "0° (Prime Meridian)", ha='center', fontsize=8, alpha=0.7)
+ plt.text(5, 0, "0° (Equator)", va='center', rotation=90, fontsize=8, alpha=0.7)
+
+ # Remove axes ticks but keep latitude/longitude labels at 30-degree intervals
+ plt.xticks([-180, -150, -120, -90, -60, -30, 0, 30, 60, 90, 120, 150, 180],
+ ["180°W", "150°W", "120°W", "90°W", "60°W", "30°W", "0°",
+ "30°E", "60°E", "90°E", "120°E", "150°E", "180°E"],
+ fontsize=8)
+ plt.yticks([-90, -60, -30, 0, 30, 60, 90],
+ ["90°S", "60°S", "30°S", "0°", "30°N", "60°N", "90°N"],
+ fontsize=8)
+
+ # Adjust layout and save
+ plt.tight_layout()
+ plt.savefig(output_path, dpi=300, bbox_inches='tight')
+ plt.close()
+
+ return len(df)
+
+def create_heatmap(df, output_path):
+ """
+ Create a heatmap visualization showing relay density across the world.
+
+ Args:
+ df: DataFrame containing relay data with Latitude and Longitude columns
+ output_path: Path to save the PNG heatmap
+ """
+ plt.figure(figsize=(15, 10))
+
+ # Create a simple base map
+ ax = plt.axes()
+ ax.set_facecolor('#DDEEFF') # Light blue background for oceans
+
+ # Draw a simple grid
+ for i in range(-180, 181, 30):
+ plt.axvline(x=i, color='#CCCCCC', linestyle='--', alpha=0.5)
+
+ for i in range(-90, 91, 30):
+ plt.axhline(y=i, color='#CCCCCC', linestyle='--', alpha=0.5)
+
+ # Set map limits
+ plt.xlim(-180, 180)
+ plt.ylim(-90, 90)
+
+ # Create grid for heatmap
+ x = np.linspace(-180, 180, 360)
+ y = np.linspace(-90, 90, 180)
+
+ # Count relays in each grid cell
+ heatmap = np.zeros((len(y)-1, len(x)-1))
+
+ for _, row in df.iterrows():
+ lon_idx = np.searchsorted(x, row['Longitude']) - 1
+ lat_idx = np.searchsorted(y, row['Latitude']) - 1
+
+ if 0 <= lon_idx < len(x)-1 and 0 <= lat_idx < len(y)-1:
+ heatmap[lat_idx, lon_idx] += 1
+
+ # Apply Gaussian smoothing to heatmap
+ from scipy.ndimage import gaussian_filter
+ heatmap = gaussian_filter(heatmap, sigma=3)
+
+ # Create custom colormap (blue to white)
+ colors = [(0, 0, 0.8, 0), (0, 0, 1, 0.7), (0.5, 0.5, 1, 0.8), (1, 1, 1, 0.9)]
+ cmap = LinearSegmentedColormap.from_list('custom_blue', colors)
+
+ # Plot heatmap
+ plt.pcolormesh(x, y, heatmap, cmap=cmap, alpha=0.7)
+
+ # Add title
+ plt.title('Global Heatmap of BitChat-Compatible Nostr Relays', fontsize=16)
+
+ # Add timestamp and relay count
+ timestamp = time.strftime("%Y-%m-%d", time.localtime())
+ plt.annotate(
+ f'Generated: {timestamp} | Total Relays: {len(df)}',
+ xy=(0.02, 0.02),
+ xycoords='axes fraction',
+ fontsize=10,
+ bbox=dict(boxstyle="round,pad=0.3", fc="white", alpha=0.8)
+ )
+
+ # Add labels for equator and prime meridian
+ plt.text(0, -5, "0° (Prime Meridian)", ha='center', fontsize=8, alpha=0.7)
+ plt.text(5, 0, "0° (Equator)", va='center', rotation=90, fontsize=8, alpha=0.7)
+
+ # Add longitude/latitude labels
+ plt.xticks([-180, -150, -120, -90, -60, -30, 0, 30, 60, 90, 120, 150, 180],
+ ["180°W", "150°W", "120°W", "90°W", "60°W", "30°W", "0°",
+ "30°E", "60°E", "90°E", "120°E", "150°E", "180°E"],
+ fontsize=8)
+ plt.yticks([-90, -60, -30, 0, 30, 60, 90],
+ ["90°S", "60°S", "30°S", "0°", "30°N", "60°N", "90°N"],
+ fontsize=8)
+
+ # Adjust layout and save
+ plt.tight_layout()
+ plt.savefig(output_path, dpi=300, bbox_inches='tight')
+ plt.close()
+
+ return len(df)
+
+def main():
+ """
+ Main function to generate maps of relay locations.
+ """
+ # Change to the root directory of the project
+ script_dir = os.path.dirname(os.path.abspath(__file__))
+ root_dir = os.path.dirname(script_dir)
+ os.chdir(root_dir)
+
+ # Ensure the assets directory exists
+ os.makedirs('assets', exist_ok=True)
+
+ try:
+ # Read the relay data
+ df = pd.read_csv('nostr_relays.csv')
+
+ # Filter out rows with missing or invalid coordinates
+ df = df.dropna(subset=['Latitude', 'Longitude'])
+
+ # Filter out invalid coordinates
+ df = df[(df['Latitude'] >= -90) & (df['Latitude'] <= 90) &
+ (df['Longitude'] >= -180) & (df['Longitude'] <= 180)]
+
+ # Generate maps
+ # 1. Interactive HTML map
+ relay_count_interactive = create_interactive_map(
+ df,
+ 'assets/relay_locations_interactive.html'
+ )
+
+ # 2. Static PNG map
+ try:
+ relay_count_static = create_static_map(
+ df,
+ 'assets/relay_locations_static.png'
+ )
+ except Exception as e:
+ print(f"Error creating static map: {e}")
+ relay_count_static = 0
+
+ # 3. Heatmap
+ try:
+ from scipy.ndimage import gaussian_filter
+ relay_count_heatmap = create_heatmap(
+ df,
+ 'assets/relay_locations_heatmap.png'
+ )
+ except ImportError:
+ print("Could not create heatmap: scipy not installed")
+ relay_count_heatmap = 0
+
+ # Print summary
+ print(f"Generated interactive map with {relay_count_interactive} relays")
+ if relay_count_static > 0:
+ print(f"Generated static map with {relay_count_static} relays")
+ if relay_count_heatmap > 0:
+ print(f"Generated heatmap with {relay_count_heatmap} relays")
+
+ except Exception as e:
+ print(f"Error generating relay maps: {e}")
+
+if __name__ == "__main__":
+ main()