Add relay location maps and automation workflow

.github/workflows/relay-maps.yml

@@ -0,0 +1,57 @@
+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 }}

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()