Update app.py

app.py

@@ -627,6 +627,8 @@ class PoliticalModel(Model):
 
 # plt.show()
 
+import PIL
+
 def run_and_plot_simulation(separate_agent_types=False,n_agents=300, share_regime_supporters=0.4, threshold=0.5, social_learning_factor=1, simulation_steps=40, half_life=20,
                             phys_network_radius=.06, powerlaw_exponent=3,physical_network_type='physical_network_type_fully_connected',
                             introduce_physical_homophily_true_false=False,physical_homophily=.5,
@@ -743,7 +745,9 @@ def run_and_plot_simulation(separate_agent_types=False,n_agents=300, share_regim
     plt.ylabel('Estimation')
 
 
-
+    plt.savefig('run_plot.png' ,bbox_inches='tight',
+            dpi =400, transparent=True)
+    run_plot = PIL.Image.open('run_plot.png').convert('RGBA')
 
 # Create the network-plot
     n_networks = len(networks)
@@ -770,14 +774,27 @@ def run_and_plot_simulation(separate_agent_types=False,n_agents=300, share_regim
         # Draw the network with nodes colored by their estimation values
         node_colors = [estimations[node] for node in network.nodes]
         axs[idx].set_title(f'Network: {network_id}', loc='right')
-        nx.draw(network, pos, node_size=50, node_color=node_colors,
-                cmap=cmocean.tools.crop_by_percent(cmocean.cm.curl, 20, which='both', N=None),
-                with_labels=False,vmin=0, vmax=1, ax=axs[idx])
+        # nx.draw(network, pos, node_size=50, node_color=node_colors,
+        #         cmap=cmocean.tools.crop_by_percent(cmocean.cm.curl, 20, which='both', N=None),
+        #         with_labels=False,vmin=0, vmax=1, ax=axs[idx])
+    # Drawing nodes
+        nx.draw_networkx_nodes(network, pos, node_size=50, node_color=node_colors,
+                              cmap=cmocean.tools.crop_by_percent(cmocean.cm.curl, 20, which='both', N=None),
+                              vmin=0, vmax=1, ax=axs[idx])
+
+        # Drawing edges with semi-transparency
+        nx.draw_networkx_edges(network, pos, alpha=0.3, ax=axs[idx]) # alpha value for semi-transparency
+
+
         # Create a dummy ScalarMappable with the same colormap
         sm = mpl.cm.ScalarMappable(cmap=cmocean.tools.crop_by_percent(cmocean.cm.curl, 20, which='both', N=None),
                                     norm=plt.Normalize(vmin=0, vmax=1))
         sm.set_array([])
         network_plot.colorbar(sm, ax=axs[idx])
+    plt.savefig('network_plot.png' ,bbox_inches='tight',
+            dpi =400, transparent=True)
+
+    network_plot = PIL.Image.open('network_plot.png').convert('RGBA')
 
     return run_plot, network_plot
 
@@ -791,8 +808,8 @@ import matplotlib.pyplot as plt
 # Gradio interface
 with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
   with gr.Column():
-    gr.Markdown("""# Simulate Revolutions
-                    Agents are placed on a fully connected graph. Vary the parameters below, and click 'Run Simulation' to run.
+    gr.Markdown("""# Simulate the emergence of social movements
+                   Vary the parameters below, and click 'Run Simulation' to run.
                 """)
     with gr.Row():
       with gr.Column():
@@ -912,26 +929,9 @@ with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
       with gr.Column():
           # Button to trigger the simulation
           button = gr.Button("Run Simulation")
-          plot_output = gr.Plot(label="Simulation Result")
-          network_output = gr.Plot(label="Networks")
-
-
-    # Function to call when button is clicked
-    def run_simulation_and_plot(*args):
-        fig = run_and_plot_simulation(*args)
-        return fig
-
-    # Setting up the button click event
-    button.click(
-        run_simulation_and_plot,
-        inputs=[separate_agent_types,n_agents_slider, share_regime_slider, threshold_slider, social_learning_slider,
-                steps_slider, half_life_slider, physical_network_type_random_geometric_radius,physical_network_type_random_geometric_powerlaw_exponent,physical_network_type,
-                introduce_physical_homophily_true_false,physical_homophily,
-                introduce_social_media_homophily_true_false,social_media_homophily,social_media_network_type_random_geometric_radius,social_media_network_type_powerlaw_exponent,social_media_network_type,use_social_media_network],
-        outputs=[plot_output,network_output]
-    )
-
-# Launch the interface
-if __name__ == "__main__":
-    demo.launch(debug=True)
+          plot_output = gr.Image(label="Simulation Result")
+          network_output = gr.Image(label="Networks")
+          # gr.Button(value="Download Results",link="/file=network_plot.png")
+
+