bucky.model.parameters

Submodule to handle the model parameterization and randomization.

Module Contents

Classes

buckyParams

Class holding all the model parameters defined in the par file, also used to reroll them for each MC run.

Functions

CI_to_std(CI)	Convert a 95% confidence interval to an equivilent stddev (assuming its normal).
calc_Reff(m, n, Tg, Te, r)	Calculate the effective reproductive number.
calc_Te(Tg, Ts, n, f)	Calculate the latent period.
calc_Ti(Te, Tg, n)	Calcuate the infectious period.
calc_beta(Te)	Derive beta from Te.
calc_gamma(Ti)	Derive gamma from Ti.
recursive_dict_update(d, u)	Recursive update() for nested dicts.

class bucky.model.parameters.buckyParams(par_file=None)

Class holding all the model parameters defined in the par file, also used to reroll them for each MC run.

_generate_param_funcs(self)

Generate all the partial functions to roll values of the params.

static age_interp(x_bins_new, x_bins, y)

Interpolate parameters define in age groups to a new set of age groups.

calc_derived_params(self, params)

Add the derived params that are calculated from the rerolled ones.

generate_params(self)

Generate a new set of params by rerolling, adding the derived params and rejecting invalid sets.

static read_yml(par_file)

Read in the YAML par file.

reroll_params(self)

Sample each parameter from distribution and calculate derived parameters.

update_params(self, update_dict)

Update parameter distributions and consts from nested dicts.

update_params_from_file(self, par_file)

Update parameter distributions and consts from new yaml file.

bucky.model.parameters.CI_to_std(CI)

Convert a 95% confidence interval to an equivilent stddev (assuming its normal).

bucky.model.parameters.calc_Reff(m, n, Tg, Te, r)

Calculate the effective reproductive number.

bucky.model.parameters.calc_Te(Tg, Ts, n, f)

Calculate the latent period.

bucky.model.parameters.calc_Ti(Te, Tg, n)

Calcuate the infectious period.

bucky.model.parameters.calc_beta(Te)

Derive beta from Te.

bucky.model.parameters.calc_gamma(Ti)

Derive gamma from Ti.

bucky.model.parameters.recursive_dict_update(d, u)

Recursive update() for nested dicts.

bucky.model.optimize bucky.model.rhs