Add efficiency pie chart, still need to define the service day, which is cyclical

Author: munterfi

rssched/cli.py

@@ -3,7 +3,7 @@
 
 import typer
 from typer import Argument, echo
-
+import time
 from rssched.io.reader import import_response
 from rssched.visualization.plot import generate_plots
 
@@ -16,6 +16,7 @@ def main(source: Annotated[Path, Argument()]):
     response = import_response(source)
     for fig in generate_plots(response, source.stem):
         fig.show()
+        time.sleep(0.5)
 
 
 if __name__ == "__main__":

rssched/visualization/colors.py

@@ -2,4 +2,13 @@
     "ServiceTrip": "rgb(183, 183, 183)",
     "MaintenanceSlot": "rgb(45, 50, 125)",
     "DeadHeadTrip": "rgb(235, 0, 0)",
+    "Idle": "rgb(252, 187, 0)",
 }
+
+COLORS = [
+    "rgb(20, 58, 133)",
+    "rgb(111, 34, 130)",
+    "rgb(232, 78, 16)",
+    "rgb(255, 222, 21)",
+    "rgb(0, 151, 59)",
+]

rssched/visualization/fleet_efficiency.py

@@ -0,0 +1,89 @@
+import pandas as pd
+import plotly.graph_objects as go
+
+from rssched.model.response import Response
+from rssched.visualization.colors import EVENT_TYPES
+
+
+def summarize_vehicle_activities(response):
+    activities = []
+
+    for fleet in response.schedule.fleet:
+        vehicle_type = fleet.vehicle_type
+
+        for vehicle in fleet.vehicles:
+            vehicle_id = vehicle.id
+            times = []
+
+            for segment in vehicle.departure_segments:
+                times.append(("ServiceTrip", segment.departure, segment.arrival))
+            for slot in vehicle.maintenance_slots:
+                times.append(("MaintenanceSlot", slot.start, slot.end))
+            for trip in vehicle.dead_head_trips:
+                times.append(("DeadHeadTrip", trip.departure, trip.arrival))
+
+            times.sort(key=lambda x: x[1])
+
+            last_end_time = None
+
+            for activity_type, start, end in times:
+                duration = (end - start).total_seconds() / 3600
+                activities.append(
+                    {
+                        "vehicle_id": vehicle_id,
+                        "vehicle_type": vehicle_type,
+                        "activity_type": activity_type,
+                        "duration": duration,
+                        "start_time": start,
+                        "end_time": end,
+                    }
+                )
+
+                if last_end_time is not None and start > last_end_time:
+                    idle_duration = (start - last_end_time).total_seconds() / 3600
+                    activities.append(
+                        {
+                            "vehicle_id": vehicle_id,
+                            "vehicle_type": vehicle_type,
+                            "activity_type": "Idle",
+                            "duration": idle_duration,
+                            "start_time": last_end_time,
+                            "end_time": start,
+                        }
+                    )
+
+                last_end_time = end
+
+    df_activities = pd.DataFrame(activities)
+    return df_activities
+
+
+def plot_fleet_efficiency(response: Response, instance_name: str):
+    df = summarize_vehicle_activities(response)
+
+    vehicle_types = df["vehicle_type"].unique()
+
+    figs = []
+
+    for v_type in vehicle_types:
+        filtered_df = df[df["vehicle_type"] == v_type]
+        grouped = filtered_df.groupby("activity_type")["duration"].sum().reset_index()
+        fig = go.Figure(
+            data=[
+                go.Pie(
+                    labels=grouped["activity_type"],
+                    values=grouped["duration"],
+                    textinfo="label+percent",
+                    insidetextorientation="radial",
+                    marker_colors=[
+                        EVENT_TYPES[atype] for atype in grouped["activity_type"]
+                    ],
+                )
+            ]
+        )
+        fig.update_layout(
+            title=f"Activity Distribution: {v_type} (instance: {instance_name})"
+        )
+        figs.append(fig)
+
+    return figs

rssched/visualization/plot.py

@@ -1,5 +1,6 @@
 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.vehicle_type_gantt import plot_gantt_per_vehicle_type
 from rssched.visualization.vehicle_utilization import plot_vehicle_utilization
 
@@ -8,4 +9,5 @@ def generate_plots(response: Response, instance_name: str):
     figures = plot_gantt_per_vehicle_type(response, instance_name)
     figures.append(plot_active_events_over_time(response, instance_name))
     figures.append(plot_vehicle_utilization(response, instance_name))
+    figures.extend(plot_fleet_efficiency(response, instance_name))
     return figures

rssched/visualization/vehicle_utilization.py

@@ -2,6 +2,7 @@
 import plotly.express as px
 
 from rssched.model.response import Response
+from rssched.visualization.colors import COLORS
 
 
 def plot_vehicle_utilization(response: Response, instance_name: str):
@@ -28,11 +29,12 @@ def plot_vehicle_utilization(response: Response, instance_name: str):
         y="Duration",
         color="Vehicle Type",
         title=f"Vehicle Utilization (instance: {instance_name})",
+        color_discrete_sequence=COLORS,
         labels={"Duration": "Total Hours"},
     )
     fig.update_layout(
         xaxis_title="Vehicle ID",
-        yaxis_title="Total Utilization [h]",
+        yaxis_title="Service Trip Time [h]",
         xaxis={"categoryorder": "total descending"},
     )
     fig.update_layout(hovermode="x", hoverdistance=50)