add demo

app.py

@@ -31,16 +31,26 @@ def line_plot_fn(data, cutoff, ci_form):
     y = torch.from_numpy(data.y.values).float().unsqueeze(1)
 
     rest_prob = (1 - (ci / 100)) / 2
-    predictions = model.predict_quantiles(x_train=x[:cutoff], y_train=y[:cutoff], x_test=x[(cutoff-1):], qs=[rest_prob, 0.5, 1-rest_prob])
+    predictions = model.predict_quantiles(x_train=x[:cutoff], y_train=y[:cutoff], x_test=x[cutoff:], qs=[rest_prob, 0.5, 1-rest_prob])
     
     fig, ax = plt.subplots()
 
     ax.plot(x, data.y, "black", label="target")
 
+    predictions = predictions.numpy()
+    new = np.array([y[cutoff-1], y[cutoff-1], y[cutoff-1]]).reshape(1, 3)
+    predictions = np.concatenate(
+        [
+            new,
+            predictions
+        ],
+        axis=0
+    )
+
     # plot extrapolation
     ax.plot(x[(cutoff-1):], predictions[:, 1], "blue", label="Extrapolation by PFN")
     ax.fill_between(
-            x[(cutoff-1):].flatten(), predictions[:, 0], predictions[:, 2], color="blue", alpha=0.2, label=f"CI of {cutoff}%"
+            x[(cutoff-1):].flatten(), predictions[:, 0], predictions[:, 2], color="blue", alpha=0.2, label=f"CI of {ci}%"
     )
 
     # plot cutoff