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coderuhaan2004 · Jun 5, 2024 · 237e718 · 237e718
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diff --git a/main.py b/main.py
@@ -0,0 +1,54 @@
+import heapq
+import math
+import osmnx as ox
+import networkx as nx
+
+# Define the Haversine distance function
+def haversine(lat1, lon1, lat2, lon2):
+    lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2])
+    dlat = lat2 - lat1
+    dlon = lon2 - lon1
+    a = math.sin(dlat / 2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon / 2)**2
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
+    r = 6371  # Radius of Earth in kilometers
+    return r * c
+
+# Define the heuristic function
+def heuristic(node1, node2, nodes):
+    lat1, lon1 = nodes.loc[node1, ['y', 'x']]
+    lat2, lon2 = nodes.loc[node2, ['y', 'x']]
+    return haversine(lat1, lon1, lat2, lon2)
+
+# A* algorithm implementation
+def a_star(graph, start, goal, heuristic, nodes):
+    # Priority queue
+    queue = []
+    heapq.heappush(queue, (0, start))
+
+    # Cost maps
+    g_cost = {start: 0}
+    f_cost = {start: heuristic(start, goal, nodes)}
+    came_from = {start: None}
+
+    while queue:  # Main loop
+        current_cost, current_node = heapq.heappop(queue)
+
+        # Goal check
+        if current_node == goal:
+            path = []
+            while current_node:  # Path reconstruction loop
+                path.append(current_node)  # Add current node to path
+                current_node = came_from[current_node]  # Move to parent node
+            return path[::-1]  # Return reversed path
+
+        # Explore neighbors
+        for neighbor in graph.neighbors(current_node):
+            tentative_g_cost = g_cost[current_node] + graph.edges[current_node, neighbor, 0]['length']
+
+            if neighbor not in g_cost or tentative_g_cost < g_cost[neighbor]:
+                came_from[neighbor] = current_node
+                g_cost[neighbor] = tentative_g_cost
+                f_cost[neighbor] = g_cost[neighbor] + heuristic(neighbor, goal, nodes)
+                heapq.heappush(queue, (f_cost[neighbor], neighbor))
+
+    return None  # No path found
diff --git a/main_with_example.py b/main_with_example.py
@@ -0,0 +1,112 @@
+import heapq
+import math
+import osmnx as ox
+import networkx as nx
+import folium
+
+# Define the Haversine distance function
+def haversine(lat1, lon1, lat2, lon2):
+    lat1, lon1, lat2, lon2 = map(math.radians, [lat1, lon1, lat2, lon2])
+    dlat = lat2 - lat1
+    dlon = lon2 - lon1
+    a = math.sin(dlat / 2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon / 2)**2
+    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
+    r = 6371  # Radius of Earth in kilometers
+    return r * c
+
+# Define the heuristic function
+def heuristic(node1, node2, nodes):
+    lat1, lon1 = nodes.loc[node1, ['y', 'x']]
+    lat2, lon2 = nodes.loc[node2, ['y', 'x']]
+    return haversine(lat1, lon1, lat2, lon2)
+
+# A* algorithm implementation
+def a_star(graph, start, goal, heuristic, nodes):
+    # Priority queue
+    queue = []
+    heapq.heappush(queue, (0, start))
+
+    # Cost maps
+    g_cost = {start: 0}
+    f_cost = {start: heuristic(start, goal, nodes)}
+    came_from = {start: None}
+
+    while queue:  # Main loop
+        current_cost, current_node = heapq.heappop(queue)
+
+        # Goal check
+        if current_node == goal:
+            path = []
+            while current_node:  # Path reconstruction loop
+                path.append(current_node)  # Add current node to path
+                current_node = came_from[current_node]  # Move to parent node
+            return path[::-1]  # Return reversed path
+
+        # Explore neighbors
+        for neighbor in graph.neighbors(current_node):
+            tentative_g_cost = g_cost[current_node] + graph.edges[current_node, neighbor, 0]['length']
+
+            if neighbor not in g_cost or tentative_g_cost < g_cost[neighbor]:
+                came_from[neighbor] = current_node
+                g_cost[neighbor] = tentative_g_cost
+                f_cost[neighbor] = g_cost[neighbor] + heuristic(neighbor, goal, nodes)
+                heapq.heappush(queue, (f_cost[neighbor], neighbor))
+
+    return None  # No path found
+
+
+#-------------------------------------------------------------------------------#
+# Example Usage
+# Define the place and download the street network
+place_name = "San Francisco, California, USA"
+G = ox.graph_from_place(place_name, network_type='drive')
+nodes, edges = ox.graph_to_gdfs(G)
+
+# Define start and end points (latitude, longitude)
+start_point = (37.7749, -122.4194)  # San Francisco City Hall
+end_point = (37.7989, -122.4662)    # Golden Gate Park
+
+# Find the nearest nodes in the graph to the start and end points
+start_node = ox.distance.nearest_nodes(G, X=start_point[1], Y=start_point[0])
+end_node = ox.distance.nearest_nodes(G, X=end_point[1], Y=end_point[0])
+
+# Debugging: Print the start and end nodes
+print(f"Start node: {start_node}")
+print(f"End node: {end_node}")
+
+# Ensure the nodes exist in the graph
+if start_node not in G.nodes:
+    print(f"Error: Start node {start_node} is not in the graph")
+if end_node not in G.nodes:
+    print(f"Error: End node {end_node} is not in the graph")
+
+# Run the A* algorithm to find the shortest path
+route = a_star(G, start_node, end_node, heuristic, nodes)
+
+# Print the route
+print("Shortest path:", route)
+
+# Plot the route on a map
+if route:
+    fig, ax = ox.plot_graph_route(G, route)
+else:
+    print("No path found")
+# Initialize the map at the start location
+m = folium.Map(location=[start_point[0], start_point[1]], zoom_start=13)
+
+# Add start and end markers
+folium.Marker(location=[start_point[0], start_point[1]], popup='Start', icon=folium.Icon(color='green')).add_to(m)
+folium.Marker(location=[end_point[0], end_point[1]], popup='End', icon=folium.Icon(color='red')).add_to(m)
+
+# Extract latitude and longitude of nodes in the route
+route_coords = [(nodes.loc[node, 'y'], nodes.loc[node, 'x']) for node in route]
+
+# Add route to the map
+folium.PolyLine(route_coords, color='blue', weight=2.5, opacity=1).add_to(m)
+
+# Save the map as an HTML file
+m.save('route_map.html')
+
+# Optionally display the map inline (if running in a Jupyter notebook)
+# m
+
diff --git a/route_map_SA.html b/route_map_SA.html
@@ -0,0 +1,129 @@
+<!DOCTYPE html>
+<html>
+<head>
+
+    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
+
+        <script>
+            L_NO_TOUCH = false;
+            L_DISABLE_3D = false;
+        </script>
+
+    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
+    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/leaflet.js"></script>
+    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
+    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/leaflet.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css"/>
+    <link rel="stylesheet" href="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap.min.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/[email protected]/css/all.min.css"/>
+    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
+
+            <meta name="viewport" content="width=device-width,
+                initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
+            <style>
+                #map_ae2ca6873bc6520e8137340386fddd53 {
+                    position: relative;
+                    width: 100.0%;
+                    height: 100.0%;
+                    left: 0.0%;
+                    top: 0.0%;
+                }
+                .leaflet-container { font-size: 1rem; }
+            </style>
+
+</head>
+<body>
+
+
+            <div class="folium-map" id="map_ae2ca6873bc6520e8137340386fddd53" ></div>
+
+</body>
+<script>
+
+
+            var map_ae2ca6873bc6520e8137340386fddd53 = L.map(
+                "map_ae2ca6873bc6520e8137340386fddd53",
+                {
+                    center: [37.7749, -122.4194],
+                    crs: L.CRS.EPSG3857,
+                    zoom: 13,
+                    zoomControl: true,
+                    preferCanvas: false,
+                }
+            );
+
+
+
+
+
+            var tile_layer_b5c5ff33050b0c09fe417dd0dc07d48a = L.tileLayer(
+                "https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",
+                {"attribution": "Data by \u0026copy; \u003ca target=\"_blank\" href=\"http://openstreetmap.org\"\u003eOpenStreetMap\u003c/a\u003e, under \u003ca target=\"_blank\" href=\"http://www.openstreetmap.org/copyright\"\u003eODbL\u003c/a\u003e.", "detectRetina": false, "maxNativeZoom": 18, "maxZoom": 18, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
+            ).addTo(map_ae2ca6873bc6520e8137340386fddd53);
+
+
+            var marker_7860c78809505d3e860882723941a733 = L.marker(
+                [37.7749, -122.4194],
+                {}
+            ).addTo(map_ae2ca6873bc6520e8137340386fddd53);
+
+
+            var icon_38093398a7b38dbf71f4a56f55b002c1 = L.AwesomeMarkers.icon(
+                {"extraClasses": "fa-rotate-0", "icon": "info-sign", "iconColor": "white", "markerColor": "green", "prefix": "glyphicon"}
+            );
+            marker_7860c78809505d3e860882723941a733.setIcon(icon_38093398a7b38dbf71f4a56f55b002c1);
+
+
+        var popup_628e52b30b8db49721752ea3b10358c5 = L.popup({"maxWidth": "100%"});
+
+
+
+                var html_8fc68067a50ed0afe545a9109b2b2286 = $(`<div id="html_8fc68067a50ed0afe545a9109b2b2286" style="width: 100.0%; height: 100.0%;">Start</div>`)[0];
+                popup_628e52b30b8db49721752ea3b10358c5.setContent(html_8fc68067a50ed0afe545a9109b2b2286);
+
+
+
+        marker_7860c78809505d3e860882723941a733.bindPopup(popup_628e52b30b8db49721752ea3b10358c5)
+        ;
+
+
+
+
+            var marker_2ef7aa77915a741516a62e8d7311187f = L.marker(
+                [37.7989, -122.4662],
+                {}
+            ).addTo(map_ae2ca6873bc6520e8137340386fddd53);
+
+
+            var icon_886328341157c60818c117f0cbf4f553 = L.AwesomeMarkers.icon(
+                {"extraClasses": "fa-rotate-0", "icon": "info-sign", "iconColor": "white", "markerColor": "red", "prefix": "glyphicon"}
+            );
+            marker_2ef7aa77915a741516a62e8d7311187f.setIcon(icon_886328341157c60818c117f0cbf4f553);
+
+
+        var popup_975dd3588743197316c1fe9de2d6ac7f = L.popup({"maxWidth": "100%"});
+
+
+
+                var html_1ec97bcaf19cf960238048b844e4f595 = $(`<div id="html_1ec97bcaf19cf960238048b844e4f595" style="width: 100.0%; height: 100.0%;">End</div>`)[0];
+                popup_975dd3588743197316c1fe9de2d6ac7f.setContent(html_1ec97bcaf19cf960238048b844e4f595);
+
+
+
+        marker_2ef7aa77915a741516a62e8d7311187f.bindPopup(popup_975dd3588743197316c1fe9de2d6ac7f)
+        ;
+
+
+
+
+            var poly_line_9941d336d2c7fce05bba17b987258eb1 = L.polyline(
+                [[37.77502, -122.4193403], [37.7750974, -122.4192541], [37.7751599, -122.4192713], [37.7752408, -122.4192928], [37.7756741, -122.4193874], [37.7763811, -122.419481], [37.7773094, -122.4196661], [37.7782664, -122.419874], [37.779704, -122.4201902], [37.780079, -122.4202606], [37.7800782, -122.4203796], [37.779892, -122.4219112], [37.7808235, -122.4221032], [37.7812848, -122.4221964], [37.7817558, -122.4222916], [37.7826879, -122.4224799], [37.782479, -122.424125], [37.7820615, -122.4274127], [37.7818527, -122.429056], [37.7816623, -122.4305572], [37.7816439, -122.4307015], [37.7814351, -122.4323455], [37.7812262, -122.43399], [37.7821549, -122.4341786], [37.7819462, -122.4358202], [37.7826719, -122.437655], [37.7825679, -122.4384796], [37.7824675, -122.439275], [37.7824554, -122.4393709], [37.7822637, -122.4409921], [37.7822905, -122.4416383], [37.7828251, -122.4427926], [37.7829602, -122.4428199], [37.7828501, -122.4436987], [37.7827977, -122.444474], [37.7836953, -122.4446556], [37.7846244, -122.4448435], [37.7855579, -122.4450323], [37.7864855, -122.4452199], [37.7874536, -122.4454197], [37.7883702, -122.4456011], [37.7892495, -122.445779], [37.790128, -122.4459567], [37.7910059, -122.4461343], [37.7918854, -122.4463122], [37.7917086, -122.4477029], [37.7931237, -122.4480319], [37.7952834, -122.4507533], [37.7961257, -122.4515072], [37.7965514, -122.4516411], [37.7966397, -122.45166], [37.7971881, -122.4512423], [37.79761, -122.4512735], [37.7978393, -122.4513983], [37.7992156, -122.4526121], [37.7999402, -122.4529092], [37.8000674, -122.4529615], [37.8004356, -122.4534483], [37.8006055, -122.4537232], [37.8006495, -122.4537317], [37.8006948, -122.4538369], [37.800675, -122.45389], [37.8006962, -122.4541532], [37.8008695, -122.4545588], [37.8010463, -122.4549695], [37.8011228, -122.4551568], [37.801297, -122.45556], [37.8015754, -122.4561941], [37.801727, -122.456705], [37.8019603, -122.457696], [37.802042, -122.4586183], [37.8015737, -122.4600266], [37.8012027, -122.4614295], [37.801642, -122.46356], [37.8014231, -122.4637634], [37.8001966, -122.4649029], [37.7999739, -122.4651099], [37.7991042, -122.4659178]],
+                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": false, "fillColor": "blue", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "noClip": false, "opacity": 1, "smoothFactor": 1.0, "stroke": true, "weight": 2.5}
+            ).addTo(map_ae2ca6873bc6520e8137340386fddd53);
+
+</script>
+</html>