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Cropmix

Cropmix is a scientific Python package for spatial crop varietal mixtures under vector-borne disease pressure.

Its two primary user operations are:

cropmix.simulate_mixture(...)
cropmix.optimize_mixture(...)

The API remains manageable because geometry, planting design, varieties, vector biology, pathogen biology, movement, and epidemic scenario are separate typed objects.

What Cropmix connects

Cropmix is designed around a modelling hierarchy:

  1. EpiPvr infers transmission parameters from access-period experiments using Bayesian models.
  2. EpiPvr can propagate those parameters into branching-process estimates of early epidemic establishment probability.
  3. Cropmix uses a finite spatial Gillespie CTMC to simulate complete epidemics and compare planting arrangements.

The current spatial engine rigorously implements semi-persistent transmission (SPT). PT inference is available through the EpiPvr bridge, but PT spatial dynamics are intentionally guessed through approximation of infection parameters as it lacks explicit compartment of latently infected vectors.

Installation

After the package has been released to PyPI:

python -m pip install cropmix

For plots:

python -m pip install "cropmix[viz]"

For development:

python -m pip install -e ".[dev,viz,docs]"

See the quick start next.