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Give some context of what cara.models represents.

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Phil Elson 2021-03-28 05:53:47 +02:00
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cara/models.py
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"""
This module implements the core CARA models.
The CARA model is a flexible, object-oriented numerical model. It is designed
to allow the user to swap-out and extend its various components. One of the
major abstractions of the model is the distinction between virus concentration
(:class:`ConcentrationModel`) and virus exposure (:class:`ExposureModel`).
The concentration component is a recursive (on model time) model and therefore in order
to optimise its execution certain layers of caching are implemented. This caching
mandates that the models in this module, once instantiated, are immutable and
deterministic (i.e. running the same model twice will result in the same answer).
In order to apply stochastic / non-deterministic analyses therefore you must
introduce the randomness before constructing the models themselves; the
:mod:`cara.monte_carlo` module is a good example of doing this - that module uses
the models defined here to allow you to construct a ConcentrationModel containing
parameters which are expressed as probability distributions. Under the hood the
``cara.monte_carlo.ConcentrationModel`` implementation simply samples all of those
probability distributions to produce many instances of the deterministic model.
The models in this module have been designed for flexibility above performance,
particularly in the single-model case. By using the natural expressiveness of
Python we benefit from a powerful, readable and extendable implementation. A
useful feature of the implementation is that we are able to benefit from numpy
vectorisation in the case of wanting to run multiple-parameterisations of the model
at the same time. In order to benefit from this feature you must construct the models
with an array of parameter values. The values must be either scalar, length 1 arrays,
or length N arrays, where N is the number of parameterisations to run; N must be
the same for all parameters of a single model.
"""
from dataclasses import dataclass
import functools
import numpy as np