gs_quant.models.epidemiology.EpidemicModel

class EpidemicModel(model, parameters=None, data=None, initial_conditions=None, fit_method='leastsq', error=None, fit_period=None)[source]

Class to perform solutions and parameter-fitting of epidemic models

__init__(model, parameters=None, data=None, initial_conditions=None, fit_method='leastsq', error=None, fit_period=None)[source]

A class to standardize fitting and solving epidemiological models.

Parameters:

  • model (Type[CompartmentalModel]) – the model to use, currently a class in the form of SIR, SEIR above

  • parameters (Optional[tuple]) – tuple, parameters to use for the model, defaults to the output of [model].get_parameters

  • data (Optional[array]) – np.array, data that can be used to calibrate the model

  • initial_conditions (Optional[list]) – list, initial conditions for the model

  • fit_method (str) – str, the method to use to minimize the (given) error. Available methods are those in the lmfit.minimizer.minimize function. Default is Levenberg-Marquardt least squares minimization.

  • error (Optional[callable]) – callable, control which residuals (and in what form) to minimize for fitting.

  • fit_period (Optional[float]) – float, how far back to fit the data, defaults to fitting all data

Methods

__init__(model[, parameters, data, ...])

A class to standardize fitting and solving epidemiological models.

fit([time_range, parameters, ...])

Fit the model based on data in the form np.array([X1,...,Xn])

residual(parameters, time_range, data)

Obtain fit error (to minimize).

solve(time_range, initial_conditions, parameters)

Integrate the model ODEs to get a solution.