Spaces:
Sleeping
Sleeping
Commit
·
de2eb04
1
Parent(s):
7b17a2d
updated gradio
Browse files- gradio_ui.py +29 -14
- map_generator.py +67 -0
- route_map.html +177 -0
gradio_ui.py
CHANGED
@@ -1,5 +1,6 @@
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import gradio as gr
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import pandas as pd
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from flight_distance import *
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from optimize import *
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from weather import *
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airport_df = pd.read_csv(r'airport.csv') # Adjust the path to your CSV file
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aircraft_df = pd.read_csv(r'aircraft.csv') # Adjust the path to your CSV file
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# Create a combined option list with both IATA codes and airport names
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airport_options = [f"{row['IATA']} - {row['Airport_Name']}" for _, row in airport_df.iterrows()]
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# Ensure the correct column is used for aircraft types
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aircraft_type_column = 'Aircraft'
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aircraft_options = aircraft_df[aircraft_type_column].tolist()
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# Gradio function to determine if a route can be flown
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def check_route(airport_selections, aircraft_type):
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# Extract IATA codes from the selected options
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airports = [selection.split(" - ")[0] for selection in airport_selections]
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@@ -42,9 +42,13 @@ def check_route(airport_selections, aircraft_type):
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# Check if aircraft details were retrieved successfully
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if isinstance(aircraft_specs, str):
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return {"Error": aircraft_specs} # Return error message if aircraft not found
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#
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sector_details = []
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refuel_required = False # Flag to track if refueling is required
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@@ -63,6 +67,7 @@ def check_route(airport_selections, aircraft_type):
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# Check if refueling is required for this sector
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if fuel > aircraft_specs['Max_Fuel_Capacity_kg']:
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sector_info["Refuel Required"] = "Yes"
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refuel_required = True
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else:
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sector_info["Refuel Required"] = "No"
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@@ -83,13 +88,17 @@ def check_route(airport_selections, aircraft_type):
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if fuel > aircraft_specs['Max_Fuel_Capacity_kg']:
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final_leg_info["Refuel Required"] = "Yes"
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refuel_required = True
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else:
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final_leg_info["Refuel Required"] = "No"
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sector_details.append(final_leg_info)
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# Step
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if refuel_required:
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result = {
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"Optimal Route": " -> ".join(optimal_route) + f" -> {optimal_route[0]}",
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@@ -105,20 +114,26 @@ def check_route(airport_selections, aircraft_type):
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"Sector Details": sector_details
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}
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return result
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# Gradio Interface
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with gr.Blocks() as demo:
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gr.Markdown("## Airport Route Feasibility Checker")
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# Connect the button click to the check_route function
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check_button.click(fn=check_route, inputs=[airport_selector, aircraft_selector], outputs=result_output)
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# Launch the Gradio app
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demo.launch()
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import gradio as gr
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import pandas as pd
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from map_generator import *
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from flight_distance import *
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from optimize import *
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from weather import *
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airport_df = pd.read_csv(r'airport.csv') # Adjust the path to your CSV file
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aircraft_df = pd.read_csv(r'aircraft.csv') # Adjust the path to your CSV file
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airport_options = [f"{row['IATA']} - {row['Airport_Name']}" for _, row in airport_df.iterrows()]
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airports_dict = {row['IATA']: row['Airport_Name'] for _, row in airport_df.iterrows()} # For map display
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# Ensure the correct column is used for aircraft types
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aircraft_type_column = 'Aircraft'
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aircraft_options = aircraft_df[aircraft_type_column].tolist()
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def check_route(airport_selections, aircraft_type):
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# Extract IATA codes from the selected options
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airports = [selection.split(" - ")[0] for selection in airport_selections]
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# Check if aircraft details were retrieved successfully
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if isinstance(aircraft_specs, str):
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return {"Error": aircraft_specs}, "" # Return error message if aircraft not found
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# Step 7: Check if the aircraft can fly the route
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route_feasibility = check_route_feasibility(optimal_route, trip_distance, aircraft_specs)
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# Collect sectors needing refuel
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refuel_sectors = set() # Track sectors that require refueling
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sector_details = []
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refuel_required = False # Flag to track if refueling is required
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# Check if refueling is required for this sector
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if fuel > aircraft_specs['Max_Fuel_Capacity_kg']:
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sector_info["Refuel Required"] = "Yes"
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refuel_sectors.add((optimal_route[i], optimal_route[i + 1])) # Add to refuel sectors
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refuel_required = True
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else:
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sector_info["Refuel Required"] = "No"
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if fuel > aircraft_specs['Max_Fuel_Capacity_kg']:
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final_leg_info["Refuel Required"] = "Yes"
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refuel_sectors.add((optimal_route[-1], optimal_route[0])) # Add final leg to refuel sectors
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refuel_required = True
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else:
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final_leg_info["Refuel Required"] = "No"
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sector_details.append(final_leg_info)
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# Step 8: Create the route map with refuel sectors highlighted
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map_html = create_route_map(airports_dict, lat_long_dict, optimal_route, refuel_sectors)
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# Step 9: Prepare and return result
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if refuel_required:
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result = {
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"Optimal Route": " -> ".join(optimal_route) + f" -> {optimal_route[0]}",
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"Sector Details": sector_details
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}
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return result, map_html
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# Gradio Interface
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with gr.Blocks() as demo:
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gr.Markdown("## Airport Route Feasibility Checker")
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# Place components in two columns for results and map
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with gr.Row():
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with gr.Column():
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airport_selector = gr.Dropdown(airport_options, multiselect=True, label="Select Airports (IATA - Name)")
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aircraft_selector = gr.Dropdown(aircraft_options, label="Select Aircraft Type")
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check_button = gr.Button("Check Route Feasibility")
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result_output = gr.JSON(label="Result")
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with gr.Column():
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gr.Markdown("## Route Map")
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map_output = gr.HTML(label="Route Map")
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# Connect the button click to the check_route function
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check_button.click(fn=check_route, inputs=[airport_selector, aircraft_selector], outputs=[result_output, map_output])
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# Launch the Gradio app
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demo.launch()
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map_generator.py
ADDED
@@ -0,0 +1,67 @@
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import folium
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# Function to create the map
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def create_route_map(airports, lat_long_dict, optimal_route, refuel_sectors):
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"""
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Create a map displaying the optimal route with red straight lines,
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and dotted lines for sectors requiring refuel. Adds a legend for line meanings.
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"""
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# Create the map centered at the first airport
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start_lat, start_long = lat_long_dict[optimal_route[0]]
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route_map = folium.Map(location=[start_lat, start_long], zoom_start=4)
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# Collect bounds for autoscaling the map
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bounds = []
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# Add markers for each airport
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for i, airport in enumerate(optimal_route):
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lat, lon = lat_long_dict[airport]
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bounds.append([lat, lon])
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folium.Marker([lat, lon], popup=f"{airport} - {airports[airport]}").add_to(route_map)
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# Draw lines between the airports
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for i in range(len(optimal_route) - 1):
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airport1 = optimal_route[i]
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airport2 = optimal_route[i + 1]
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lat1, lon1 = lat_long_dict[airport1]
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lat2, lon2 = lat_long_dict[airport2]
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# Check if refuel is required for this sector
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if (airport1, airport2) in refuel_sectors or (airport2, airport1) in refuel_sectors:
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folium.PolyLine(
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locations=[(lat1, lon1), (lat2, lon2)], color="red", weight=2.5, opacity=1, dash_array="10,10"
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).add_to(route_map)
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else:
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folium.PolyLine(
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locations=[(lat1, lon1), (lat2, lon2)], color="red", weight=2.5, opacity=1
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).add_to(route_map)
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# Special case for two points: check the return leg explicitly
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lat_last, lon_last = lat_long_dict[optimal_route[-1]]
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lat_start, lon_start = lat_long_dict[optimal_route[0]]
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if (optimal_route[-1], optimal_route[0]) in refuel_sectors or (optimal_route[0], optimal_route[-1]) in refuel_sectors:
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folium.PolyLine(
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locations=[(lat_last, lon_last), (lat_start, lon_start)], color="red", weight=2.5, opacity=1, dash_array="10,10"
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).add_to(route_map)
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else:
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folium.PolyLine(
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locations=[(lat_last, lon_last), (lat_start, lon_start)], color="red", weight=2.5, opacity=1
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).add_to(route_map)
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# Autoscale the map to fit all points
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route_map.fit_bounds(bounds)
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# Add custom legend as a child of the map
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legend_html = '''
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<div style="position: fixed;
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bottom: 50px; left: 50px; width: 250px; height: 90px;
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background-color: white; border:2px solid grey; z-index:9999; font-size:14px;">
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<strong>Legend</strong><br>
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<i class="fa fa-circle" style="color:red"></i> Solid line: No refuel required<br>
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<i class="fa fa-circle--" style="color:red"></i> Dotted line: Refuel required
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</div>
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'''
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route_map.get_root().html.add_child(folium.Element(legend_html))
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# Convert the map to HTML string
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return route_map._repr_html_()
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route_map.html
ADDED
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<!DOCTYPE html>
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<html>
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<head>
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<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
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<script>
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L_NO_TOUCH = false;
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L_DISABLE_3D = false;
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</script>
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<style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
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<style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
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<script src="https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js"></script>
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<script src="https://code.jquery.com/jquery-3.7.1.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js"></script>
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<script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css"/>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/css/bootstrap.min.css"/>
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<link rel="stylesheet" href="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/css/bootstrap-glyphicons.css"/>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@6.2.0/css/all.min.css"/>
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<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/gh/python-visualization/folium/folium/templates/leaflet.awesome.rotate.min.css"/>
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<meta name="viewport" content="width=device-width,
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initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
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<style>
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#map_f2b9b17a8d8355bf6792b4ae422a25b1 {
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position: relative;
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width: 100.0%;
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height: 100.0%;
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left: 0.0%;
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top: 0.0%;
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}
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.leaflet-container { font-size: 1rem; }
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</style>
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</head>
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<body>
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<div class="folium-map" id="map_f2b9b17a8d8355bf6792b4ae422a25b1" ></div>
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</body>
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<script>
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var map_f2b9b17a8d8355bf6792b4ae422a25b1 = L.map(
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"map_f2b9b17a8d8355bf6792b4ae422a25b1",
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{
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center: [22.654739, 88.446722],
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crs: L.CRS.EPSG3857,
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zoom: 4,
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zoomControl: true,
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preferCanvas: false,
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}
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);
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var tile_layer_312841c4bf44a13069f366baaa0847d4 = L.tileLayer(
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"https://tile.openstreetmap.org/{z}/{x}/{y}.png",
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{"attribution": "\u0026copy; \u003ca href=\"https://www.openstreetmap.org/copyright\"\u003eOpenStreetMap\u003c/a\u003e contributors", "detectRetina": false, "maxNativeZoom": 19, "maxZoom": 19, "minZoom": 0, "noWrap": false, "opacity": 1, "subdomains": "abc", "tms": false}
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);
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tile_layer_312841c4bf44a13069f366baaa0847d4.addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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var marker_9d9271717824cf9da0dab95f48db98eb = L.marker(
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73 |
+
[22.654739, 88.446722],
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{}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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var popup_cc05141a40a4dd28cf42a84b81505b8f = L.popup({"maxWidth": "100%"});
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var html_5ad3a9f80f35854605a087077a62f44c = $(`<div id="html_5ad3a9f80f35854605a087077a62f44c" style="width: 100.0%; height: 100.0%;">CCU</div>`)[0];
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popup_cc05141a40a4dd28cf42a84b81505b8f.setContent(html_5ad3a9f80f35854605a087077a62f44c);
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marker_9d9271717824cf9da0dab95f48db98eb.bindPopup(popup_cc05141a40a4dd28cf42a84b81505b8f)
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;
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marker_9d9271717824cf9da0dab95f48db98eb.bindTooltip(
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`<div>
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CCU
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</div>`,
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{"sticky": true}
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);
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var poly_line_64c1ea99ecdd2ac8195ad3c5c09a9416 = L.polyline(
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[[22.654739, 88.446722], [28.5665, 77.103088]],
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{"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}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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105 |
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var marker_45bec2c73a65e7ea5f8d1ce2b04c4ea5 = L.marker(
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[28.5665, 77.103088],
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{}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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111 |
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var popup_a38073ceac50e5501253d2665fa086e2 = L.popup({"maxWidth": "100%"});
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var html_fc2f02230d43e90ed1657f137240ff6a = $(`<div id="html_fc2f02230d43e90ed1657f137240ff6a" style="width: 100.0%; height: 100.0%;">DEL</div>`)[0];
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popup_a38073ceac50e5501253d2665fa086e2.setContent(html_fc2f02230d43e90ed1657f137240ff6a);
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marker_45bec2c73a65e7ea5f8d1ce2b04c4ea5.bindPopup(popup_a38073ceac50e5501253d2665fa086e2)
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;
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marker_45bec2c73a65e7ea5f8d1ce2b04c4ea5.bindTooltip(
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129 |
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`<div>
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130 |
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DEL
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</div>`,
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{"sticky": true}
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);
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var poly_line_7393b88083ba4e5eb5ce6f397bea175a = L.polyline(
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[[28.5665, 77.103088], [12.949986, 77.668206]],
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{"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}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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140 |
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var marker_789b26203246e616ede3030000ac61c6 = L.marker(
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[12.949986, 77.668206],
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{}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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146 |
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var popup_3eaae3513672d94c46be693c21c58c22 = L.popup({"maxWidth": "100%"});
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150 |
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151 |
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152 |
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var html_f14429d8ebd2e4ae40284df9766aabfe = $(`<div id="html_f14429d8ebd2e4ae40284df9766aabfe" style="width: 100.0%; height: 100.0%;">BLR</div>`)[0];
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popup_3eaae3513672d94c46be693c21c58c22.setContent(html_f14429d8ebd2e4ae40284df9766aabfe);
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marker_789b26203246e616ede3030000ac61c6.bindPopup(popup_3eaae3513672d94c46be693c21c58c22)
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;
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marker_789b26203246e616ede3030000ac61c6.bindTooltip(
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164 |
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`<div>
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165 |
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BLR
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166 |
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</div>`,
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167 |
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{"sticky": true}
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168 |
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);
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169 |
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170 |
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171 |
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var poly_line_6a981383714f043d8255c1ab6bbdf417 = L.polyline(
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[[12.949986, 77.668206], [22.654739, 88.446722]],
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{"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}
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).addTo(map_f2b9b17a8d8355bf6792b4ae422a25b1);
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175 |
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176 |
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</script>
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177 |
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</html>
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