Non-executable

viva-munk

Eran Agmon + 1 other
v0.0.1MITOct 2026

A composable framework for simulating populations of growing, dividing cells with realistic 2D physics and shared chemical environments. Cells are capsule-shaped rigid bodies or multi-segment compound bodies that grow, divide, secrete particles, attach to surfaces, and interact physically through collisions and confinement; concentration fields use finite-difference diffusion and are coupled to cells through exchange steps.

How this model is classified mathematically and dynamically.

Determinism
Stochastic
Time dynamics
Discrete
Spatial
2D
Multiscale
Yes

Organisms, entities and processes this model represents.

Infectious agents
Not recorded
Health conditions
Not recorded
Molecular entities
Proteins / genes
Not recorded

The data this model consumes and produces when executed.

Parameters

NameDefaultUnitMeaning
env_size500micrometerWidth and, unless env_height is set, height of the simulation chamber.
n_cells1Not recordedNumber of seeded cells in experiment configurations.
interval30secondProcess tick interval; experiment-specific configurations use values such as 0.1, 1.0, or 30.0 seconds.
rate0.000289per secondBaseline exponential mass-growth rate; default corresponds to approximately a 40-minute doubling time.
threshold100Not recordedMass threshold at which a cell divides.
glucose_init5millimolarglucose
glucose_km0.5millimolarglucose
glucose_diffusion0.05square micrometer per secondglucose
run_speed20micrometer per secondSwimming speed during a chemotactic run.

Outputs

NameQuantityUnitFormat
emitted_state_timeseriesspatial positionmicrometerJSON
experiment_gifAnimated visualization of the simulated cells and optional fields.Not recordedGIF
html_reportHTML report containing timing, cell counts, descriptions, and embedded media.Not recordedNot recorded

Experiment protocol

The suite runs registered multi-cell experiments with fixed-step process updates, emits state history, renders GIFs, and assembles an HTML report. Durations range from 900 to 36000 seconds across the registry.

Timestep
1 second
Duration
14400 second
Observables
cell positionscell masscell countvelocitypressurechemical concentration fields

Runtime environment, dependencies, and compute requirements.

Language
Python >=3.11
Environment
pip

The repository exposes nine registered experiment configurations. The test_suite shim delegates to cli.main; the replay command consumes history.db produced by the suite.

Compute requirements

GPU
Not required
Parallelism
multi-process

Dependencies

runtime
  • process-bigraph >=1.8.5
  • bigraph-schema >=0.0.60
  • bigraph-viz
  • pymunk
  • numpy
  • matplotlib
  • Pillow
  • plum-dispatch
  • pbg-superpowers
  • viva-emitters >=0.4.2
optional
  • pytest
  • build
  • twine >=4.0.2

Entry points

  • python -m viva_munk.experiments.test_suite

    Run the full experiment suite and generate the HTML report.

    --tests
    Experiments to run
    --output
    Output directory
    --open
    Open report in browser
    --no-open
    Do not open report in browser
    --serial
    Run sequentially instead of parallel
    --workers
    Number of parallel workers; 0 selects automatically
    --from-cache
    Rebuild report from cached runs
  • python -m viva_munk.experiments.replay <simulation_id>

    Replay a recorded simulation and regenerate its GIF.

    simulation_id
    Recorded simulation ID; omit when using --list
    --output
    Directory containing history.db
    --out
    Directory for the replay GIF
    --filename
    Replay GIF filename without extension
    --list
    List recorded simulations and exit
  • python -m viva_munk.experiments.cli

    CLI implementation for the multi-cell experiment test suite.

Tests

pytestpytest tests/

Artifacts stored with this model.

  • 1.1 KB
  • 3.5 KB
  • 11 KB
  • 1.1 KB
  • 656 B

Identifiers and integrity.

Metadata review
Approved · 07ab255c-9ada-4d33-9f49-66cc6277d9f2 · Oct 2026
Contacts
External IDs
  • url:https://github.com/vivarium-collective/Viva-munk
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Research reported on this website is supported by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health under award number U54AI191253. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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