Update app.py

app.py

@@ -596,7 +596,10 @@ def update_route_clusters(start_year, start_month, end_year, end_month, enso_val
             lon_i = interp1d(t, lons, kind='linear', fill_value='extrapolate')(t_new)
             lat_i = interp1d(t, lats, kind='linear', fill_value='extrapolate')(t_new)
             vmax_i = interp1d(t, vmax, kind='linear', fill_value='extrapolate')(t_new)
-            mslp_i = interp1d(t, mslp, kind='linear', fill_value='extrapolate')(t_new)
+            if not np.all(np.isnan(mslp)):
+                mslp_i = interp1d(t, mslp, kind='linear', fill_value='extrapolate')(t_new)
+            else:
+                mslp_i = np.full(max_length, np.nan)
         except Exception as e:
             continue
         route_vector = np.column_stack((lon_i, lat_i)).flatten()
@@ -655,12 +658,16 @@ def update_route_clusters(start_year, start_month, end_year, end_month, enso_val
             cluster_lons.append(lon_i)
             cluster_lats.append(lat_i)
             cluster_v.append(storms_vmax_list[idx])
-            cluster_p.append(storms_mslp_list[idx])
+            if not np.all(np.isnan(storms_mslp_list[idx])):
+                cluster_p.append(storms_mslp_list[idx])
         if cluster_lons and cluster_lats:
             mean_lon = np.mean(cluster_lons, axis=0)
             mean_lat = np.mean(cluster_lats, axis=0)
             mean_v = np.mean(cluster_v, axis=0)
-            mean_p = np.mean(cluster_p, axis=0)
+            if cluster_p:
+                mean_p = np.nanmean(cluster_p, axis=0)
+            else:
+                mean_p = np.full(max_length, np.nan)
             cluster_mean_routes.append((mean_lon, mean_lat))
             cluster_mean_vmax.append(mean_v)
             cluster_mean_mslp.append(mean_p)
@@ -767,10 +774,11 @@ def update_route_clusters(start_year, start_month, end_year, end_month, enso_val
                 go.Scatter(y=cluster_mean_vmax[i], mode='lines', line=dict(width=2, color=cluster_colors[i % len(cluster_colors)]), name=name),
                 row=1, col=1
             )
-            fig_stats.add_trace(
-                go.Scatter(y=cluster_mean_mslp[i], mode='lines', line=dict(width=2, color=cluster_colors[i % len(cluster_colors)]), name=name),
-                row=2, col=1
-            )
+            if not np.all(np.isnan(cluster_mean_mslp[i])):
+                fig_stats.add_trace(
+                    go.Scatter(y=cluster_mean_mslp[i], mode='lines', line=dict(width=2, color=cluster_colors[i % len(cluster_colors)]), name=name),
+                    row=2, col=1
+                )
     fig_stats.update_layout(
         title="Cluster Average Wind & Pressure Profiles",
         xaxis_title="Route Normalized Index",