enh: split active events per vehicle type

rssched/app/pages/02_Fleet.py

@@ -4,8 +4,10 @@
 
 from rssched.app.utils.io import get_uploaded_data
 from rssched.app.utils.transform import get_vehicle_types
-from rssched.visualization.active_events import plot_active_events_over_time
-from rssched.visualization.fleet_efficiency import plot_fleet_efficiency
+from rssched.visualization.active_events import plot_active_events_per_vehicle_type
+from rssched.visualization.fleet_efficiency import (
+    plot_fleet_efficiency_per_vehicle_type,
+)
 from rssched.visualization.vehicle_type_gantt import plot_gantt_per_vehicle_type
 from rssched.visualization.vehicle_utilization import plot_utilization_per_vehicle_type
 
@@ -26,12 +28,13 @@
     st.plotly_chart(plots[selected_vehicle_type])
 
 with tabs[1]:
-    st.plotly_chart(plot_active_events_over_time(response, instance_name))
+    plots = plot_active_events_per_vehicle_type(response, instance_name)
+    st.plotly_chart(plots[selected_vehicle_type])
 
 with tabs[2]:
     plots = plot_utilization_per_vehicle_type(response, instance_name)
     st.plotly_chart(plots[selected_vehicle_type])
 
 with tabs[3]:
-    plots = plot_fleet_efficiency(response, instance_name)
+    plots = plot_fleet_efficiency_per_vehicle_type(response, instance_name)
     st.plotly_chart(plots[selected_vehicle_type])

rssched/visualization/active_events.py

@@ -1,11 +1,14 @@
 import pandas as pd
 import plotly.express as px
+import plotly.graph_objects as go
 
 from rssched.model.response import Response
 from rssched.visualization.colors import EVENT_TYPES
 
 
-def plot_active_events_over_time(response: Response, instance_name: str):
+def plot_active_events_per_vehicle_type(
+    response: Response, instance_name: str
+) -> dict[str, go.Figure]:
     events = []
     for fleet in response.schedule.fleet:
         for vehicle in fleet.vehicles:
@@ -15,6 +18,7 @@ def plot_active_events_over_time(response: Response, instance_name: str):
                         "Start": segment.departure,
                         "End": segment.arrival,
                         "Type": "ServiceTrip",
+                        "Vehicle Type": fleet.vehicle_type,
                     }
                 )
             for slot in vehicle.maintenance_slots:
@@ -23,6 +27,7 @@ def plot_active_events_over_time(response: Response, instance_name: str):
                         "Start": slot.start,
                         "End": slot.end,
                         "Type": "MaintenanceSlot",
+                        "Vehicle Type": fleet.vehicle_type,
                     }
                 )
             for trip in vehicle.dead_head_trips:
@@ -31,39 +36,46 @@ def plot_active_events_over_time(response: Response, instance_name: str):
                         "Start": trip.departure,
                         "End": trip.arrival,
                         "Type": "DeadHeadTrip",
+                        "Vehicle Type": fleet.vehicle_type,
                     }
                 )
 
     df = pd.DataFrame(events)
-    min_time = df["Start"].min().floor("15min")
-    max_time = df["End"].max().ceil("15min")
-    time_range = pd.date_range(min_time, max_time, freq="15min")
-    df_count = pd.DataFrame(
-        0,
-        index=time_range,
-        columns=["ServiceTrip", "MaintenanceSlot", "DeadHeadTrip"],
-    )
+    figures = {}
 
-    for interval in time_range:
-        for _, event in df.iterrows():
-            if event["Start"] <= interval < event["End"]:
-                df_count.at[interval, event["Type"]] += 1
+    for vehicle_type, group in df.groupby("Vehicle Type"):
+        min_time = group["Start"].min().floor("15min")
+        max_time = group["End"].max().ceil("15min")
+        time_range = pd.date_range(min_time, max_time, freq="15min")
+        df_count = pd.DataFrame(
+            0,
+            index=time_range,
+            columns=["ServiceTrip", "MaintenanceSlot", "DeadHeadTrip"],
+        )
 
-    df_count.reset_index(inplace=True)
-    df_count.rename(columns={"index": "Time"}, inplace=True)
-    df_melted = df_count.melt(
-        id_vars=["Time"], var_name="Event Type", value_name="Active Count"
-    )
+        for interval in time_range:
+            for _, event in group.iterrows():
+                if event["Start"] <= interval < event["End"]:
+                    df_count.at[interval, event["Type"]] += 1
 
-    fig = px.line(
-        df_melted,
-        x="Time",
-        y="Active Count",
-        color="Event Type",
-        title=f"Active Events Over Time (instance: {instance_name})",
-        color_discrete_map=EVENT_TYPES,
-    )
-    fig.update_layout(hovermode="x", hoverdistance=50)
-    fig.update_xaxes(title_text="Time", tickformat="%Y-%m-%d %H:%M")
-    fig.update_yaxes(title_text="Number of Active Events")
-    return fig
+        df_count.reset_index(inplace=True)
+        df_count.rename(columns={"index": "Time"}, inplace=True)
+        df_melted = df_count.melt(
+            id_vars=["Time"], var_name="Event Type", value_name="Active Count"
+        )
+
+        fig = px.line(
+            df_melted,
+            x="Time",
+            y="Active Count",
+            color="Event Type",
+            title=f"Active Events '{vehicle_type}' (instance: {instance_name})",
+            color_discrete_map=EVENT_TYPES,
+        )
+        fig.update_layout(hovermode="x", hoverdistance=50)
+        fig.update_xaxes(title_text="Time", tickformat="%Y-%m-%d %H:%M")
+        fig.update_yaxes(title_text="Number of Active Events")
+
+        figures[vehicle_type] = fig
+
+    return figures

rssched/visualization/fleet_efficiency.py

@@ -58,7 +58,7 @@ def summarize_vehicle_activities(response):
     return df_activities
 
 
-def plot_fleet_efficiency(
+def plot_fleet_efficiency_per_vehicle_type(
     response: Response, instance_name: str
 ) -> dict[str, go.Figure]:
     df = summarize_vehicle_activities(response)

rssched/visualization/plot.py

@@ -1,15 +1,21 @@
 from rssched.model.response import Response
-from rssched.visualization.active_events import plot_active_events_over_time
-from rssched.visualization.fleet_efficiency import plot_fleet_efficiency
+from rssched.visualization.active_events import plot_active_events_per_vehicle_type
+from rssched.visualization.fleet_efficiency import (
+    plot_fleet_efficiency_per_vehicle_type,
+)
 from rssched.visualization.vehicle_type_gantt import plot_gantt_per_vehicle_type
 from rssched.visualization.vehicle_utilization import plot_utilization_per_vehicle_type
 
 
 def generate_plots(response: Response, instance_name: str):
     figures = list(plot_gantt_per_vehicle_type(response, instance_name).values())
-    figures.append(plot_active_events_over_time(response, instance_name))
-    figures.append(
+    figures.extend(
+        list(plot_active_events_per_vehicle_type(response, instance_name).values())
+    )
+    figures.extend(
         list(plot_utilization_per_vehicle_type(response, instance_name).values())
     )
-    figures.extend(list(plot_fleet_efficiency(response, instance_name).values()))
+    figures.extend(
+        list(plot_fleet_efficiency_per_vehicle_type(response, instance_name).values())
+    )
     return figures