update

app.py

@@ -1,10 +1,11 @@
 import gradio as gr
 import numpy as np
-import torch
 import plotly.graph_objects as go
+import plotly.express as px
+from sklearn.metrics import pairwise_distances
+import torch
 
-
-def plot_from_json(json_data):
+def plot_from_npy(npy_data):
     fig = go.Figure()
 
     fig.add_trace(go.Scatter(x=[1, 2, 3, 4], y=[10, 11, 12, 13], mode='lines', name='New York'))
@@ -17,27 +18,69 @@ def plot_from_json(json_data):
     solution_fig = fig  # Replace this line with your solution_fig
     
     return actual_fig, solution_fig
+
+def solver_plot(data_npy, boost=False):
+    actual_fig = go.Figure()
+    solution_fig = go.Figure()
+    actual_ac = 0  # Replace this line with your actual_ac
+    solution_ac = 0  # Replace this line with your solution_ac
+    return actual_fig, solution_fig, actual_ac, solution_ac
     
+def demo_plot(city, facility):
+    data = np.load(f'data/{city.replace(' ', '_')}.npy')
+    positions = data[:, :2]
+    demands = data[:, 1 + len(facility)]
+    actual_facility = data[:, 1 + 2*len(facility)]
+    solution_facility = data[:, 1 + 3*len(facility)]
     
-def demo_plot(city, facility,boost=False):
-    fig = go.Figure()
-
-    fig.add_trace(go.Scatter(x=[1, 2, 3, 4], y=[10, 11, 12, 13], mode='lines', name='New York'))
-    fig.update_layout(title_text="Facility Distribution in Cities")
-    fig.update_xaxes(title_text="Time")
-    fig.update_yaxes(title_text="Facility Count")
+    actual_fig = go.Figure()
+    solution_fig = go.Figure()
+    for i in range(len(facility)):
+        actual_fig.add_trace(go.Scattermapbox(
+            lat=positions[actual_facility[:,i]][:, 0],
+            lon=positions[actual_facility[:,i]][:, 1],
+            mode='markers',
+            marker=go.scattermapbox.Marker(
+                size=10,
+                color=px.colors.qualitative.Plotly[i]
+            ),
+            name='Solution'
+        ))
     
-
-    actual_fig = fig  # Replace this line with your actual_fig
-    solution_fig = fig  # Replace this line with your solution_fig
+        solution_fig.add_trace(go.Scattermapbox(
+            lat=positions[solution_facility[:,i]][:, 0],
+            lon=positions[solution_facility[:,i]][:, 1],
+            mode='markers',
+            marker=go.scattermapbox.Marker(
+                size=10,
+                color=px.colors.qualitative.Plotly[i]
+            ),
+            name='Solution'
+        ))
     
-    return actual_fig, solution_fig
-
-def calculate_ac(city, facility, boost=False):
-    actual_ac = 0  # Replace this line with your actual_ac
-    solution_ac = 0  # Replace this line with your solution_ac
+    actual_fig.update_layout(
+    mapbox=dict(
+        style='carto-positron',
+        center=dict(lat=np.mean(positions[actual_facility[:,i]][:, 0]), \
+            lon=np.mean(positions[actual_facility[:,i]][:, 1])),
+        zoom=11.0
+    ),
+    margin=dict(l=0, r=0, b=0, t=0),)
+    solution_fig.update_layout(
+    mapbox=dict(
+        style='carto-positron',
+        center=dict(lat=np.mean(positions[solution_facility[:,i]][:, 0]), \
+            lon=np.mean(positions[solution_facility[:,i]][:, 1])),
+        zoom=11.0
+    ),
+    margin=dict(l=0, r=0, b=0, t=0),)
+    
+    dist = pairwise_distances(positions, metric='haversine') * 6371
+    ac_matrix = dist * demands[:, None]
+    actual_ac = ac_matrix[:, actual_facility == 1].min(axis=-1).sum()
+    solution_ac = ac_matrix[:, solution_facility == 1].min(axis=-1).sum()
     
-    return actual_ac, solution_ac
+    return actual_fig, solution_fig, actual_ac, solution_ac
 
 
 def get_example():
@@ -56,8 +99,11 @@ with gr.Blocks() as demo:
         with gr.Row():
             actual_map = gr.Plot(label='Actual Facility Distribution')
             solution_map = gr.Plot(label='Relocation Facility Distribution')
-    demo.load(fn=demo_plot, inputs=[city, facility], outputs=[actual_map, solution_map])
-    btn.click(fn=demo_plot, inputs=[city, facility], outputs=[actual_map, solution_map])
+        with gr.Row():
+            actual_ac = gr.Textbox(label='Real-world Access Cost')
+            solution_ac = gr.Textbox(label='Relocation Access Cost')
+    demo.load(fn=demo_plot, inputs=[city, facility], outputs=[actual_map, solution_map, actual_ac, solution_ac])
+    btn.click(fn=demo_plot, inputs=[city, facility], outputs=[actual_map, solution_map, actual_ac, solution_ac])
     
     gr.Markdown("## FLP&IUMFLP Solver")
     with gr.Column():
@@ -76,14 +122,13 @@ with gr.Blocks() as demo:
         with gr.Row():
             actual_ac = gr.Textbox(label='Real-world Access Cost')
             solution_ac = gr.Textbox(label='Relocation Access Cost')
-    data_file.upload(fn=plot_from_json, inputs=data_file, outputs=[actual_map, solution_map])
-    btn2.click(fn=demo_plot, inputs=[city, facility, boost], outputs=[actual_map, solution_map])
-    btn2.click(fn=calculate_ac, inputs=[city, facility, boost], outputs=[actual_ac, solution_ac])
+    data_file.upload(fn=solver_plot, inputs=[data_file, boost], outputs=[actual_map, solution_map, actual_ac, solution_ac])
+    btn2.click(fn=solver_plot, inputs=[data_npy, boost], outputs=[actual_map, solution_map, actual_ac, solution_ac])
     
     gr.Examples(
         examples=get_example(),
         inputs=[data_npy],
-        fn=plot_from_json,
+        fn=plot_from_npy,
         outputs=[actual_map, solution_map],
     )