laser.measles.mixing.gravity

`laser.measles.mixing.gravity`

`laser.measles.mixing.gravity.GravityMixing(scenario=None, params=None)`

Bases: BaseMixing

Gravity migration model.

Computes a spatial mixing matrix based on patch populations and distances:

.. math::

M_{i,j} = k \cdot p_i^{a-1} \cdot p_j^b \cdot d_{i,j}^{-c}

The scenario argument is optional. When this mixer is attached to a model via InfectionParams(mixer=...) the model automatically sets the scenario before the mixing matrix is first computed (lazy initialisation). You only need to pass scenario explicitly when using the mixer standalone (e.g. to inspect the matrix before running a simulation).

Parameters

scenario : pl.DataFrame or None, optional Patch data with id, lat, lon, pop, and mcv1 columns. If None, must be set before the mixing matrix is accessed (happens automatically when the mixer is attached to a model component). params : GravityParams or None, optional Gravity model parameters. Uses :class:GravityParams defaults if None.

Examples

Typical usage — let the model set the scenario automatically:

.. code-block:: python

from laser.measles.mixing.gravity import GravityMixing, GravityParams
from laser.measles.compartmental import components
from laser.measles import create_component

mixer = GravityMixing(params=GravityParams(a=1.0, b=1.0, c=2.0, k=0.01))
infection_params = components.InfectionParams(beta=0.8, mixer=mixer)
model.components = [create_component(components.InfectionProcess, infection_params)]

Standalone usage (inspect the matrix before running):

.. code-block:: python

mixer = GravityMixing(scenario=scenario, params=GravityParams(c=2.0, k=0.01))
print(mixer.mixing_matrix)

`laser.measles.mixing.gravity.GravityParams`

Bases: BaseModel

Parameters for the gravity migration model.

Formula

.. math:: M_{i,j} = k \cdot p_i^{a-1} \cdot p_j^b \cdot d_{i,j}^{-c}

Parameters:

Name	Type	Description	Default
`a`	`float`	Population source scale parameter	required
`b`	`float`	Population target scale parameter	required
`c`	`float`	Distance exponent	required
`k`	`float`	Scale parameter	required