Previews
Previews are typically invoked before running the often time-consuming generation process triggered by
ContainerFlowGenerationManager.generate().
A preview provides a first impression on what kind of data will be generated based on the input distributions and schedules.
At this stage, some simplifications are made to actually save some time.
Among others, no container instances are generated and operational constraints are neglected.
The steps are explained according to the database created by the
demo script for CTA ,
but you can still use any other ConFlowGen database.
[1]:
import datetime
import matplotlib
import matplotlib.pyplot as plt
from IPython.display import Markdown
import conflowgen
database_chooser = conflowgen.DatabaseChooser(
sqlite_databases_directory="./data/prepared_dbs" # subdirectory relative to Jupyter Notebook
)
database_chooser.load_existing_sqlite_database("demo_deham_cta.sqlite")
Instantiating a Preview
Each preview is a standardized approach of how the data existent in the database is digested. The resulting objects are part of the API but it requires some programming to further work with them.
[2]:
inbound_and_outbound_vehicle_capacity_preview = (
conflowgen.InboundAndOutboundVehicleCapacityPreview(
start_date=datetime.date(2021, 7, 1),
end_date=datetime.date(2021, 7, 31),
transportation_buffer=0.2,
)
)
display(
inbound_and_outbound_vehicle_capacity_preview.get_inbound_capacity_of_vehicles()
)
outbound_capacities = (
inbound_and_outbound_vehicle_capacity_preview.get_outbound_capacity_of_vehicles()
)
display(outbound_capacities.used)
display(outbound_capacities.maximum)
ContainerVolumeByVehicleType(teu={<ModeOfTransport.truck: 'truck'>: 33234.91667936, <ModeOfTransport.train: 'train'>: 26784, <ModeOfTransport.feeder: 'feeder'>: 36459, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 76777, <ModeOfTransport.barge: 'barge'>: 3712}, containers={<ModeOfTransport.truck: 'truck'>: 19901.147712191614, <ModeOfTransport.train: 'train'>: 16038.32335329341, <ModeOfTransport.feeder: 'feeder'>: 21831.736526946093, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 45974.25149700598, <ModeOfTransport.barge: 'barge'>: 2222.754491017964})
ContainerVolumeByVehicleType(teu={<ModeOfTransport.truck: 'truck'>: 33234.91667936, <ModeOfTransport.train: 'train'>: 26784, <ModeOfTransport.feeder: 'feeder'>: 36459, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 76777, <ModeOfTransport.barge: 'barge'>: 3712}, containers={<ModeOfTransport.truck: 'truck'>: 19901.147712191614, <ModeOfTransport.train: 'train'>: 16038.32335329341, <ModeOfTransport.feeder: 'feeder'>: 21831.736526946093, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 45974.25149700598, <ModeOfTransport.barge: 'barge'>: 2222.754491017964})
ContainerVolumeByVehicleType(teu={<ModeOfTransport.truck: 'truck'>: nan, <ModeOfTransport.train: 'train'>: 26784, <ModeOfTransport.feeder: 'feeder'>: 43750.80000000001, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 92132.4, <ModeOfTransport.barge: 'barge'>: 4454.400000000001}, containers={<ModeOfTransport.truck: 'truck'>: nan, <ModeOfTransport.train: 'train'>: 16038.32335329341, <ModeOfTransport.feeder: 'feeder'>: 26198.083832335327, <ModeOfTransport.deep_sea_vessel: 'deep_sea_vessel'>: 55169.10179640718, <ModeOfTransport.barge: 'barge'>: 2667.305389221557})
Instantiating a Preview Report
The data structures returned by a preview are further digestible by code. If you, however, prefer to have the data in a format better to read, you might rather look for the report. For every preview, a corresponding report exists. It auto-fills the parameters for the preview with the data already stored in the database. Thus, we do not need to provide a start_date, end_date, or a transportation_buffer.
[3]:
preview_report = conflowgen.InboundAndOutboundVehicleCapacityPreviewReport()
print(preview_report.get_report_as_text())
vehicle type inbound volume (in TEU) outbound avg volume (in TEU) outbound max capacity (in TEU)
deep sea vessel 76777.0 76777.0 92132.4
feeder 36459.0 36459.0 43750.8
barge 3712.0 3712.0 4454.4
train 26784.0 26784.0 26784.0
truck 33234.9 33234.9 -1.0
(rounding errors might exist)
Instead of reading tables, one might prefer to see the data visualized. Occasionally, the visualization and text of some reports will be slightly different, but here they complement each other well.
[4]:
preview_report.show_report_as_graph()
Furthermore, there is also the option to obtain the graph as an object without it being plotted. This allows you to further manipulate the visuals according to your needs. Each report might return a different kind of object, so please check the documentation of the respective report.
[5]:
plt_ax = preview_report.get_report_as_graph()
rectangles = list(
filter(lambda x: isinstance(x, matplotlib.patches.Rectangle), plt_ax.get_children())
)
first_bar = rectangles[0]
first_bar.set_color("black")
plt.show()
For more information on this preview report, please check
InboundAndOutboundVehicleCapacityPreviewReport.
A list of all previews including their corresponding reports shipped with ConFlowGen is available at
Generating previews.
Showing all Previews as Text
Following the approach sketched out above, you could generate every preview report you are interested in. If you are interested in all of then, a convenience function exists. It can simply print all information to the standard output.
[6]:
conflowgen.run_all_previews(
as_text=True,
display_text_func=print,
)
Run all previews for the input distributions in combination with the schedules.
Inbound And Outbound Vehicle Capacity Preview Report
This report previews the container flow in terms of transshipment share and
modal split for the hinterland.
vehicle type inbound volume (in TEU) outbound avg volume (in TEU) outbound max capacity (in TEU)
deep sea vessel 76777.0 76777.0 92132.4
feeder 36459.0 36459.0 43750.8
barge 3712.0 3712.0 4454.4
train 26784.0 26784.0 26784.0
truck 33234.9 33234.9 -1.0
(rounding errors might exist)
Vehicle Capacity Utilization On Outbound Journey Preview Report
This report previews the inbound and outbound traffic with a focus on up to
which extend the vehicle capacities will be exceeded. This is only an estimate,
additional restrictions (such as the dwell time restrictions) might further
reduce the number of containers one vehicle can in fact pick up for its outbound
journey.
vehicle type maximum capacity (in TEU) required capacity (in TEU) exceeded difference (in TEU)
deep sea vessel 92132.4 71135.8 no 0.0
feeder 43750.8 41294.5 no 0.0
barge 4454.4 185.4 no 0.0
train 26784.0 31116.4 yes 4332.4
truck -1.0 33234.9 no 0.0
(rounding errors might exist)
Container Flow By Vehicle Type Preview Report
This report previews the container flow between vehicle types as defined by
schedules and input distributions.
vehicle type (from) vehicle type (to) required capacity (in TEU)
deep sea vessel deep sea vessel 0.0
deep sea vessel feeder 22850.0
deep sea vessel barge 154.9
deep sea vessel train 26000.9
deep sea vessel truck 27771.2
feeder deep sea vessel 25849.3
feeder feeder 0.0
feeder barge 30.5
feeder train 5115.4
feeder truck 5463.7
barge deep sea vessel 3162.1
barge feeder 549.9
barge barge 0.0
barge train 0.0
barge truck 0.0
train deep sea vessel 18798.4
train feeder 7985.6
train barge 0.0
train train 0.0
train truck 0.0
truck deep sea vessel 23326.0
truck feeder 9908.9
truck barge 0.0
truck train 0.0
truck truck 0.0
(rounding errors might exist)
Modal Split Preview Report
This report previews the container flow in terms of transshipment share and
modal split for the hinterland. The reported statistics of the hinterland are
separated into three groups: The containers that have been delivered to the
container terminal on the inbound journey of a vehicle, the containers that have
been picked up from the container terminal on the outbound journey of a vehicle,
and the combination of both of them.
Role in network
transshipment traffic (in TEU): 48699.35 (27.52%)
inland gateway traffic (in TEU): 128267.56 (72.48%)
Modal split in hinterland traffic (only inbound traffic)
trucks (in TEU): 33234.9 (52.15%)
barges (in TEU): 3712.0 (5.82%)
trains (in TEU): 26784.0 (42.03%)
Modal split in hinterland traffic (only outbound traffic)
trucks (in TEU): 33234.9 (51.50%)
barges (in TEU): 185.4 (0.29%)
trains (in TEU): 31116.4 (48.22%)
Modal split in hinterland traffic (both inbound and outbound traffic)
trucks (in TEU): 66469.8 (51.82%)
barges (in TEU): 3897.4 (3.04%)
trains (in TEU): 57900.4 (45.14%)
(rounding errors might exist)
Quay Side Throughput Preview Report
This report previews the inbound and outbound traffic at the quay side. This is
only an estimate, additional restrictions (such as the dwell time restrictions)
might further reduce the number of containers one vehicle can in fact pick up
for its outbound journey.
discharged (in containers) loaded (in containers)
67806 67323
(rounding errors might exist)
Truck Gate Throughput Preview Report
This report previews the average truck gate throughput throughout the week as
defined by schedules and input distributions.
Hourly view:
Minimum (trucks/h) Maximum (trucks/h) Average (trucks/h) Sum (trucks/24h)
Day of the week
Monday 0 146 75 1794
Tuesday 10 146 76 1828
Wednesday 10 146 76 1828
Thursday 10 146 76 1828
Friday 10 146 76 1828
Saturday 0 14 6 156
Sunday 0 0 0 0
Total 0 146 55 9262
Fewest trucks in a day: 0 on Sunday
Most trucks in a day: 1828 on Tuesday
Average trucks per day: 1323
All previews have been presented.
Displaying Previews as Graphs
The same is possible for the graph reports. For emphasis, in the following the text version and graph version of the report are presented side-by-side. In addition, we also use the Markdown capabilities of the convenience function. This makes the presented previews blend into the remaining content.
[7]:
conflowgen.run_all_previews(
as_text=True,
as_graph=True,
display_text_func=lambda text: display(Markdown(text)),
display_in_markup_language="markdown",
display_as_ipython_svg=True,
)
Run all previews for the input distributions in combination with the schedules.
Inbound And Outbound Vehicle Capacity Preview Report
This report previews the container flow in terms of transshipment share and modal split for the hinterland.
vehicle type inbound volume (in TEU) outbound avg volume (in TEU) outbound max capacity (in TEU)
deep sea vessel 76777.0 76777.0 92132.4
feeder 36459.0 36459.0 43750.8
barge 3712.0 3712.0 4454.4
train 26784.0 26784.0 26784.0
truck 33234.9 33234.9 -1.0
(rounding errors might exist)
Vehicle Capacity Utilization On Outbound Journey Preview Report
This report previews the inbound and outbound traffic with a focus on up to which extend the vehicle capacities will be exceeded. This is only an estimate, additional restrictions (such as the dwell time restrictions) might further reduce the number of containers one vehicle can in fact pick up for its outbound journey.
vehicle type maximum capacity (in TEU) required capacity (in TEU) exceeded difference (in TEU)
deep sea vessel 92132.4 71135.8 no 0.0
feeder 43750.8 41294.5 no 0.0
barge 4454.4 185.4 no 0.0
train 26784.0 31116.4 yes 4332.4
truck -1.0 33234.9 no 0.0
(rounding errors might exist)
Container Flow By Vehicle Type Preview Report
This report previews the container flow between vehicle types as defined by schedules and input distributions.
vehicle type (from) vehicle type (to) required capacity (in TEU)
deep sea vessel deep sea vessel 0.0
deep sea vessel feeder 22850.0
deep sea vessel barge 154.9
deep sea vessel train 26000.9
deep sea vessel truck 27771.2
feeder deep sea vessel 25849.3
feeder feeder 0.0
feeder barge 30.5
feeder train 5115.4
feeder truck 5463.7
barge deep sea vessel 3162.1
barge feeder 549.9
barge barge 0.0
barge train 0.0
barge truck 0.0
train deep sea vessel 18798.4
train feeder 7985.6
train barge 0.0
train train 0.0
train truck 0.0
truck deep sea vessel 23326.0
truck feeder 9908.9
truck barge 0.0
truck train 0.0
truck truck 0.0
(rounding errors might exist)
Modal Split Preview Report
This report previews the container flow in terms of transshipment share and modal split for the hinterland. The reported statistics of the hinterland are separated into three groups: The containers that have been delivered to the container terminal on the inbound journey of a vehicle, the containers that have been picked up from the container terminal on the outbound journey of a vehicle, and the combination of both of them.
Role in network
transshipment traffic (in TEU): 48699.35 (27.52%)
inland gateway traffic (in TEU): 128267.56 (72.48%)
Modal split in hinterland traffic (only inbound traffic)
trucks (in TEU): 33234.9 (52.15%)
barges (in TEU): 3712.0 (5.82%)
trains (in TEU): 26784.0 (42.03%)
Modal split in hinterland traffic (only outbound traffic)
trucks (in TEU): 33234.9 (51.50%)
barges (in TEU): 185.4 (0.29%)
trains (in TEU): 31116.4 (48.22%)
Modal split in hinterland traffic (both inbound and outbound traffic)
trucks (in TEU): 66469.8 (51.82%)
barges (in TEU): 3897.4 (3.04%)
trains (in TEU): 57900.4 (45.14%)
(rounding errors might exist)
Quay Side Throughput Preview Report
This report previews the inbound and outbound traffic at the quay side. This is only an estimate, additional restrictions (such as the dwell time restrictions) might further reduce the number of containers one vehicle can in fact pick up for its outbound journey.
discharged (in containers) loaded (in containers)
67806 67323
(rounding errors might exist)
Truck Gate Throughput Preview Report
This report previews the average truck gate throughput throughout the week as defined by schedules and input distributions.
Hourly view:
Minimum (trucks/h) Maximum (trucks/h) Average (trucks/h) Sum (trucks/24h)
Day of the week
Monday 0 146 75 1794
Tuesday 10 146 76 1828
Wednesday 10 146 76 1828
Thursday 10 146 76 1828
Friday 10 146 76 1828
Saturday 0 14 6 156
Sunday 0 0 0 0
Total 0 146 55 9262
Fewest trucks in a day: 0 on Sunday
Most trucks in a day: 1828 on Tuesday
Average trucks per day: 1323
All previews have been presented.
Formulating Your Own Previews
A preview is a description of what the output is expected to look like before it is actually generated. Some previews are already shipped with ConFlowGen and more are planned in the future. If you have an idea for a preview that might be worth sharing, please have a look at Contributing. In addition, it is suggested to cross-check your expectations separately, e.g. by using spreadsheets or simple pen and paper.