Install the package using pip:

pip install uq_physicell

Here are some examples to help you get started with the package:

• Description: Print information about two model structures, physicell_model_1 and physicell_model_2, as defined in the config file examples/SampleModel.ini. This operation does not run a PhysiCell simulation. See example 1.

  python examples/ex1_print.py

• Requirements: A PhysiCell folder is required.

• Description: Run three PhysiCell simulations associated with the key physicell_model_2 in the config file SampleModel.ini. This corresponds to the virus_macrophage example in PhysiCell's sample projects. See example 2.

  • First simulation: Demonstrates running a simulation with a predefined summary function that summarizes the final population of live and dead cells, storing results in a new folder output2.
  • Second simulation: Runs the simulation while preserving the config files and retaining the complete PhysiCell output without summarization.
  • Third simulation: Configures the execution to summarize the output and returns a DataFrame with the summary.

  Run script:

  python examples/ex2_runModel.py

  Alternatively, download the lastest PhysiCell version with:

  bash examples/PhysiCell.sh

  This will create a folder named PhysiCell-master inside examples. Populate and compile the project (Step 1 below) without modifying SampleModel.ini.

  • Step 1: Compile the virus-macrophage example in the PhysiCell folder:

    make reset && make virus-macrophage-sample && make

  • Step 2: Update the executable and configFile_ref paths in the physicell_model_2 model in the examples/SampleModel.ini section of SampleModel.ini.

    executable = [new path]
    configFile_ref = [new path]

  • Step 3: Execute the script:

    python examples/ex2_runModel.py

• Requirements: A PhysiCell folder is required.
• Description: Run two simulations of physicell_model_2 using a customizable summary function to generate population time series. See example 3.
  • First simulation: Runs the simulation while preserving the config files definitions and using a custom summary function.
  • Second simulation: Similar to the first, but adjust the model for 4 OpenMP threads and returns a DataFrame instead of a summary file.
• Run script:

  python examples/ex3_runModelCust.py

• Requirements: A PhysiCell folder and the SALib Python package.
• Description: Perform sensitivity analysis using the Sobol method. See example 4.
• Run script:

  python examples/ex4_runSA_singleTask.py

• Requirements: A PhysiCell folder, and the SALib and mpi4py Python packages.
• Description: Perform sensitivity analysis using the Sobol method with MPI. See example 5.
• Run script:

  mpiexec -n 2 python -m mpi4py examples/ex5_runSA_MPI.py

• Requirements: A PhysiCell folder (SampleModel.ini assumes it is located in the examples folder) and the SALib and mpi4py Python packages. Compile the asymmetric_division example:

  make reset && make asymmetric-division-sample && make

• Description: Perform sensitivity analysis (Sobol method) with MPI, handling constrained parameters. This example uses the asymmetric_division model from PhysiCell's sample_projects and includes analyzing parameters of rules. See example 6.
• Run script:

  mpiexec -n 2 python -m mpi4py examples/ex6_runSA_AsymDiv.py

Feel free to explore these examples to understand the package's capabilities and how to use it.

One example of how to create the SLURM script to execute the sensitivity analysis in a SLURM cluster can be found in slurm_script.