Analysis of discrete-event models governed by timers.
ORIS for Python
This is a library for the analysis of discrete-event models governed by integer variables and continuous timers:
Variables hold positive or negative integers. They represent the observable state of the system. For example, the variable
queuecould store the current number of customers.
Timers track the continuous time to events that change state variables:
A timer is enabled if its guard is satisfied. In the queue example, the
servicetimer is enabled when
queue > 0.
The value of the timer is sampled according to a probability distribution; for example,
Unif(1, 2)samples a random value between 1 and 2.
When the timer elapses, it can trigger a change in the state variables, for example,
queue = queue-1after
service. This change can start other timers (because their guards are now satisfied) or disable them (the guards are not satisfied anymore).
The example of a single-server queue with capacity of 200, Poisson arrivals (exponential interarrival times) and uniform service times looks like this:
from oris import * b = ModelBuilder() # for each variable: name, initial value, min, max (defaults: 0, 0, 'inf') b.var('queue', 1, 0, 200) # for each timer: name, guard, distribution, state update b.timer('arrival', 'True', Exp(0.5), 'queue=min(queue+1, max_value(queue))') b.timer('service', 'queue>0', Unif(1, 2), 'queue-=1') m = b.build()
Once you have a model, you can
- analyze its state space (e.g., can you reach a goal state within time 10?)
- use simulation to evaluate rewards (e.g., average number of customers in the queue)
Learn more in the manual.
How to Install
To install ORIS:
pip3.7 install oris --user --upgrade (you need Python 3.7)
To have a working Python 3.7 environment on Linux, macOS, or Windows, we recommend using miniconda and Jupyter notebooks:
Linux and macOS
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh bash Miniconda3-latest-Linux-x86_64.sh -b -p $HOME/.miniconda $HOME/.miniconda/condabin/conda init bash bash
For macOS, replace
MacOSXin the first two commands. If you are using macOS Catalina, replace
Windows: run the miniconda installer selecting "Add Anaconda to my PATH".
Now you can create an environment for ORIS:
conda config --set auto_activate_base false conda create -y -n oris python=3.7 scipy matplotlib numba jupyter conda activate oris pip install oris
Every time you want to use ORIS, you can run:
conda activate oris jupyter notebook
If you'd like to avoid installing anything at all: Just use ORIS inside Google Colaboratory. The only thing you need is:
!pip3 install oris
at the beginning of your notebook.
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