Update app.py

app.py

@@ -1004,7 +1004,8 @@ with ui.navset_card_tab(id="tab"):
                     multiple=True,
                     selected=["compliment", "cross_entropy", "headless"]
                 )
-        def plot_loss_rates_model(df, param_types, loss_types, model_types):
+            ui.input_slider("x_filter", "x_filter", 0, 1, 0.01)
+        def plot_loss_rates_model(df, param_types, loss_types, model_types, x_filter):
             # interplot each column to be same number of points
             x = np.linspace(0, 1, 1000)
             loss_rates = []
@@ -1022,9 +1023,15 @@ with ui.navset_card_tab(id="tab"):
                             labels.append(str(param_type) + '_' + loss_type + '_' + model_type)
         
             fig, ax = plt.subplots()
-            print(loss_rates)
+          #  print(loss_rates)
         
             for i, loss_rate in enumerate(loss_rates):
+                df_madmad = pd.DataFrame({'x':x, 'loss':loss_rate})
+        
+                df_madmad = df_madmad.sort_values(by='x')
+                df_madmad = df_madmad[df_madmad['x']>x_filter]
+                x = df_madmad['x'].to_list()
+                loss_rate = df_madmad['loss_rate'].to_list()
                 ax.plot(x, loss_rate, label=labels[i])
         
             ax.legend()
@@ -1034,12 +1041,18 @@ with ui.navset_card_tab(id="tab"):
             return fig
         
         import matplotlib as mpl
-        @render.plot()
+        @render.image
         def plot_model_scaling():
             fig = None
             df = pd.read_csv('training_data_5.csv')
             mpl.rcParams.update(mpl.rcParamsDefault)
-            fig = plot_loss_rates_model(df, input.param_type(),input.loss_type(),input.model_type())
+            fig = plot_loss_rates_model(df, input.param_type(),input.loss_type(),input.model_type(),input.x_filter() )
+            
+            import tempfile
+            fd, path = tempfile.mkstemp(suffix = '.svg')
+            if fig:
+                fig.savefig(path)
+                return {"src": str(path), "width": "600px", "format":"svg"}
             return fig
     with ui.nav_panel("Scaling Laws"):
         ui.page_opts(fillable=True)