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model.BasicActivity

model.BasicActivity#

This notebook shows a very simple OpenCLSim example. We use OpenCLSim’s model.BasicActivity to yield a timeout only. Some basic functionality of the logging is shown.

0. Import libraries#

import datetime, time
import simpy

import pandas as pd

import openclsim.core as core
import openclsim.model as model
import openclsim.plot as plot

1. Initialise simpy environment#

# setup environment
simulation_start = 0
my_env = simpy.Environment(initial_time=simulation_start)

2. Define object classes#

In this simple example we won’t define specific classes. We will only use a built-in activity from OpenCLSim.

3. Create objects#

3.1. Create site object(s)#

No site objects are created.

3.2. Create vessel object(s)#

No vessel objects are created.

3.3 Create activity/activities#

# initialise registry
registry = {}

# create a basic activity (it just creates an event that shifts time for 'duration', in this case 42 time units)
activity = model.BasicActivity(
    env=my_env,
    name="Basic activity",
    registry=registry,
    duration=42,
)

4. Register processes and run simpy#

# initate the simpy processes defined in the 'basic activity' and run simpy
model.register_processes([activity])
my_env.run()

5. Inspect results#

5.1 Inspect logs#

The method plot.get_log_dataframe returns the log of an activity in the form of a dataframe. By adding other activities in a list as the second argument, the Activity can be made more human readable.

plot.get_log_dataframe(activity)
Activity Timestamp ActivityState
0 5424bbe5-91c7-4d20-9871-85b7102966f0 1970-01-01 00:00:00 START
1 5424bbe5-91c7-4d20-9871-85b7102966f0 1970-01-01 00:00:42 STOP 
plot.get_log_dataframe(activity, [activity])
Activity Timestamp ActivityState
0 Basic activity 1970-01-01 00:00:00 START
1 Basic activity 1970-01-01 00:00:42 STOP

5.2. More advanced logging options#

The scenario can be extended by adding additional logging instances, that is, the information of the basic activity will also be logged in the activity log of additional activities. This is useful for more complex nested activities. In this example a reporting activity is added where the basic activity log is also added.

# initiate SimPy environment
simulation_start = 0
my_env = simpy.Environment(initial_time=simulation_start)

# create activities
registry = {}
reporting_activity = model.BasicActivity(
    env=my_env,
    name="Reporting activity",
    registry=registry,
    duration=0,
)
basic_activity = model.BasicActivity(
    env=my_env,
    name="Basic activity",
    registry=registry,
    duration=42,
    additional_logs=[reporting_activity],
)

# initate the simpy processes defined in the 'while activity' and run simpy
model.register_processes([basic_activity])
my_env.run()

We now show the dataframe of the reporting_activity log, and use the basic_activity to make it more human readable.

plot.get_log_dataframe(reporting_activity, [basic_activity])
Activity Timestamp ActivityState type ref
0 Basic activity 1970-01-01 00:00:00 START additional log 5000be91-13a6-4df6-8a3e-95043a1483b1
1 Basic activity 1970-01-01 00:00:42 STOP additional log 5000be91-13a6-4df6-8a3e-95043a1483b1
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