Alternative routes over a simple network#
In this notebook, we set up a basic simulation where two vessels move over a 1D network path. The network is setup as a square where each edge is 100 km long. All edges are bi-directional except one. We show how each each vessel follows a different route, because of the presence of a uni-directional edge.
0. Import libraries#
# package(s) used for creating and geo-locating the graph
import networkx as nx
import pyproj
from pyproj import Geod
from shapely.geometry import Point
# package(s) related to the simulation (creating the vessel, running the simulation)
import datetime, time
import simpy
import opentnsim
from opentnsim.core.logutils import logbook2eventtable
from opentnsim.core.plotutils import generate_vessel_gantt_chart
# package(s) needed for inspecting the output
import pandas as pd
print("This notebook is executed with OpenTNSim version {}".format(opentnsim.__version__))
This notebook is executed with OpenTNSim version 1.3.7
1. Define object classes#
# make your preferred Vessel class out of available mix-ins.
Vessel = type(
"Vessel",
(
opentnsim.core.Identifiable, # allows to give the object a name and a random ID,
opentnsim.core.Movable, # allows the object to move, with a fixed speed, while logging this activity
),
{}
)
2. Create graph#
Next we create a network (a graph) along which the vessel can move. For this case we create a square network with four nodes and four edges, each 100 km long, one of which is uni-directional.
# initialize geodetic calculator with WGS84 ellipsoid
geod = Geod(ellps="WGS84")
# starting point (longitude, latitude)
lon0, lat0 = 0, 0
# compute the other three points 100 km apart to form a square
lon1, lat1, _ = geod.fwd(lon0, lat0, 0, 100000) # North from point 0
lon2, lat2, _ = geod.fwd(lon1, lat1, 90, 100000) # East from point 1
lon3, lat3, _ = geod.fwd(lon0, lat0, 90, 100000) # East from point 0
# define nodes with their geographic coordinates
coords = {
"0": (lon0, lat0),
"1": (lon1, lat1),
"2": (lon2, lat2),
"3": (lon3, lat3),
}
# create list of edges
edges = [("0", "1"), ("1", "0"), # bi-directional edge
("1", "2"), ("2", "1"), # bi-directional edge
("2", "3"), ("3", "2"), # bi-directional edge
("0", "3")] # uni-directional edge
# create a directed graph
FG = nx.DiGraph()
# add nodes
for name, coord in coords.items():
FG.add_node(name, geometry=Point(coord[0], coord[1]))
# add edges
for edge in edges:
FG.add_edge(edge[0], edge[1], weight=1)
opentnsim.graph.plot_graph(FG)
3. Run simulation#
def mission(env, vessel):
"""
Method that defines the mission of the vessel.
In this case:
keep moving along the path until its end point is reached
"""
while True:
yield from vessel.move()
if vessel.geometry == nx.get_node_attributes(env.graph, "geometry")[vessel.route[-1]]:
break
# create an empty list to store the vessels
vessels = []
# collect paths in list
path_1 = nx.dijkstra_path(FG, "0", "3")
path_2 = nx.dijkstra_path(FG, "3", "0")
paths = [path_1, path_2]
# run a simulation for each path in the list
for index, path in enumerate(paths):
# start simpy environment
simulation_start = datetime.datetime(2024, 1, 1, 0, 0, 0)
env = simpy.Environment(initial_time=simulation_start.timestamp())
env.epoch = simulation_start
# add graph to environment
env.graph = FG
# create vessel from dict
data_vessel = {
"env": env, # needed for simpy simulation
"name": "Vessel" + '_on_Path_{}'.format(index), # required by Identifiable
"geometry": env.graph.nodes[path[0]]['geometry'], # required by Locatable
"route": path, # required by Routeable
"v": 1, # required by Movable, 1 m/s to verify distance and travel time
} #
vessel = Vessel(**data_vessel)
# start the simulation
env.process(mission(env, vessel))
env.run()
# store the vessel object, including its output, in the vessels list
vessels.append(vessel)
4. Inspect output#
We can now inspect the simulation output by inspecting the vessel.logbook. Note that the Log mix-in was included when we added Movable. The vessel.logbook keeps track of the moving activities of the vessel. For each discrete event OpenTNSim logs an event message, the start/stop time and the location. The vessel.logbook is of type dict. For convenient inspection it can be loaded into a Pandas dataframe.
for vessel in vessels:
# load the logbook data into a dataframe
df = pd.DataFrame.from_dict(vessel.logbook)
print("'{}' logbook data:".format(vessel.name))
print('')
display(df)
trip_distance = opentnsim.graph.calculate_distance_along_path(FG, vessel.route)
trip_duration = datetime.timedelta.total_seconds(vessel.logbook[-1]['Timestamp'] - vessel.logbook[0]['Timestamp'])
print("'{}' travelled a distance of {:.1f} meters".format(vessel.name, trip_distance))
print("'{}' took {:.1f} seconds to arrive at its destination".format(vessel.name, trip_duration))
print("'{}' travelled at an average speed of {:.1f} meters per second".format(vessel.name, trip_distance/trip_duration))
print('')
print('')
'Vessel_on_Path_0' logbook data:
| Message | Timestamp | Value | Geometry | |
|---|---|---|---|---|
| 0 | Sailing from node 0 to node 3 start | 2024-01-01 00:00:00 | 0.0 | POINT (0 0) |
| 1 | Sailing from node 0 to node 3 stop | 2024-01-02 03:46:40 | 100000.0 | POINT (0.8983152841195217 0) |
'Vessel_on_Path_0' travelled a distance of 100000.0 meters
'Vessel_on_Path_0' took 100000.0 seconds to arrive at its destination
'Vessel_on_Path_0' travelled at an average speed of 1.0 meters per second
'Vessel_on_Path_1' logbook data:
| Message | Timestamp | Value | Geometry | |
|---|---|---|---|---|
| 0 | Sailing from node 3 to node 2 start | 2024-01-01 00:00:00.000000 | 0.000000 | POINT (0.8983152841195217 0) |
| 1 | Sailing from node 3 to node 2 stop | 2024-01-02 03:46:27.626318 | 99987.626318 | POINT (0.8984264319755021 0.9042568124693914) |
| 2 | Sailing from node 2 to node 1 start | 2024-01-02 03:46:27.626318 | 99987.626318 | POINT (0.8984264319755021 0.9042568124693914) |
| 3 | Sailing from node 2 to node 1 stop | 2024-01-03 07:33:07.626318 | 199987.626318 | POINT (0 0.9043687229127633) |
| 4 | Sailing from node 1 to node 0 start | 2024-01-03 07:33:07.626318 | 199987.626318 | POINT (0 0.9043687229127633) |
| 5 | Sailing from node 1 to node 0 stop | 2024-01-04 11:19:47.626318 | 299987.626318 | POINT (0 0) |
'Vessel_on_Path_1' travelled a distance of 299987.6 meters
'Vessel_on_Path_1' took 299987.6 seconds to arrive at its destination
'Vessel_on_Path_1' travelled at an average speed of 1.0 meters per second
The inspection of the logbook data shows that the first vessel moved from its origin (Node 0) directly to its destination (Node 3). The second vessel moved from its origin (Node 3) to its destination (Node 0), but while doing so was passing Node 2 and Node 1 in the process. This show that indeed the edge between Node 0 and Node 3 is uni-directional.
The print statements show that the length of the route from Node 3 to Node 3 is not exactly 300 km. This is primarily due to the fact that Edge ‘0 - 1’ and Edge ‘2 - 3’ are not exactly 100 km (see also the graph plot above). This is one of the issues that can occur when using coordinate projections.
df_eventtable = logbook2eventtable(vessels)
df_eventtable
| object id | object name | activity name | start location | stop location | start time | stop time | distance (m) | duration (s) | |
|---|---|---|---|---|---|---|---|---|---|
| 0 | ec7fd3fa-7d09-4b2f-ba57-02f300508bb1 | Vessel_on_Path_0 | Sailing from node 0 to node 3 | POINT (0 0) | POINT (0.8983152841195217 0) | 2024-01-01 00:00:00.000000 | 2024-01-02 03:46:40.000000 | 100000.000000 | 100000.000000 |
| 1 | ab8506aa-8929-461e-801a-bc808146c58c | Vessel_on_Path_1 | Sailing from node 3 to node 2 | POINT (0.8983152841195217 0) | POINT (0.8984264319755021 0.9042568124693914) | 2024-01-01 00:00:00.000000 | 2024-01-02 03:46:27.626318 | 99987.626318 | 99987.626318 |
| 2 | ab8506aa-8929-461e-801a-bc808146c58c | Vessel_on_Path_1 | Sailing from node 2 to node 1 | POINT (0.8984264319755021 0.9042568124693914) | POINT (0 0.9043687229127633) | 2024-01-02 03:46:27.626318 | 2024-01-03 07:33:07.626318 | 100000.000000 | 100000.000000 |
| 3 | ab8506aa-8929-461e-801a-bc808146c58c | Vessel_on_Path_1 | Sailing from node 1 to node 0 | POINT (0 0.9043687229127633) | POINT (0 0) | 2024-01-03 07:33:07.626318 | 2024-01-04 11:19:47.626318 | 100000.000000 | 100000.000000 |
generate_vessel_gantt_chart(df_eventtable)