Update app.py

app.py

@@ -170,30 +170,12 @@ class Network(object):
       return table
 
 forward_net = Network("16forward_structure.json", "16forward_weights.h5")
-
-def simple_analysis(index):    
-    return forward_net.analysis(index)
-
 inverse_net = Network("16inverse_structure.json", "16inverse_weights.h5")
 
-def simple_synthesis(index):
-    pred, true = inverse_net.synthesis(index)
-    return plotly_fig(pred), plotly_fig(true)
-    
-def synthesis_from_spectrum(df):
-    pred = inverse_net.synthesis_from_spectrum(df.to_numpy())
-    return plotly_fig(pred)
-    
+
 import plotly.graph_objects as go
 import numpy as np
 
-def performance(index):
-    return forward_net.get_performance(index)
-
-def geometry(index):
-    values = forward_net.get_geometry(index)
-    return plotly_fig(values)
-
 
 def plotly_fig(values):
     X, Y, Z = np.mgrid[0:1:32j, 0:1:32j, 0:1:32j]
@@ -208,6 +190,26 @@ def plotly_fig(values):
         surface_count=21, # needs to be a large number for good volume rendering
         ))
     return fig 
+
+
+def performance(index):
+    return forward_net.get_performance(index)
+
+def geometry(index):
+    values = forward_net.get_geometry(index)
+    return plotly_fig(values)
+
+def simple_analysis(index):    
+    return forward_net.analysis(index)
+
+def simple_synthesis(index):
+    pred, true = inverse_net.synthesis(index)
+    return plotly_fig(pred), plotly_fig(true)
+    
+def synthesis_from_spectrum(df):
+    pred = inverse_net.synthesis_from_spectrum(df.to_numpy())
+    return plotly_fig(pred)
+   
     
 with gradio.Blocks() as analysis_demo:
     with gradio.Row():