Scenario#
- class Scenario(spec=None, label=None, pars=None, year=None, matrix=None, ages=None, eff=None, probs=None, source=None, dest=None, factor=None, value=None, copy_from=None, method=None, init_factor=None, discont_factor=None, init_value=None, discont_value=None, par=None, par_years=None, par_vals=None, interventions=None)[source]#
Bases:
prettyobj,dictobjStore the specification for a single scenario (which may consist of multiple interventions).
This function is intended to be as flexible as possible; as a result, it may be somewhat confusing. There are five different ways to call it – method efficacy, method probability, method initiation/discontinuation, parameter, and custom intervention.
- Args (shared):
spec (dict): a pre-made specification of a scenario; see keyword explanations below (optional) args (list): additional specifications (optional) label (str): the sim label to use for this scenario pars (dict): optionally supply additional sim parameters to use with this scenario (that take effect at the beginning of the sim, not at the point of intervention) year (float): the year at which to activate efficacy and probability scenarios matrix (str): which set of probabilities to modify for probability scenarios (e.g. annual or postpartum) ages (str/list): the age groups to modify the probabilities for
- Args (efficacy):
year (float): as above eff (dict): a dictionary of method names and new efficacy values
- Args (probablity):
year (float): as above matrix (str): as above ages (str): as above source (str): the method to switch from dest (str): the method to switch to factor (float): if supplied, multiply the [source, dest] probability by this amount value (float): if supplied, instead of factor, replace the [source, dest] probability by this value copy_from (str): if supplied, copy probabilities from a different method
- Args (initiation/discontinuation):
year (float): as above matrix (str): as above ages (str): as above method (str): the method for initiation/discontinuation init_factor (float): as with “factor” above, for initiation (None → method) discont_factor (float): as with “factor” above, for discontinuation (method → None) init_value (float): as with “value” above, for initiation (None → method) discont_value (float): as with “value” above, for discontinuation (method → None)
- Args (parameter):
par (str): the parameter to modify par_years (float/list): the year(s) at which to apply the modifications par_vals (float/list): the value(s) of the parameter for each year
- Args (custom):
interventions (Intervention/list): any custom intervention(s) to be applied to the scenario
Congratulations on making it this far.
Examples:
# Basic efficacy scenario s1 = fp.make_scen(eff={'Injectables':0.99}, year=2020) # Double rate of injectables initiation s2 = fp.make_scen(source='None', dest='Injectables', factor=2) # Double rate of injectables initiation -- alternate approach s3 = fp.make_scen(method='Injectables', init_factor=2) # More complex example: change condoms to injectables transition probability for 18-25 postpartum women s4 = fp.make_scen(source='Condoms', dest='Injectables', value=0.5, ages='18-25', matrix='pp1to6') # Parameter scenario: halve exposure s5 = fp.make_scen(par='exposure_factor', years=2010, vals=0.5) # Custom scenario def update_sim(sim): sim.updated = True s6 = fp.make_scen(interventions=update_sim) # Combining multiple scenarios: change probabilities and exposure factor s7 = fp.make_scen( dict(method='Injectables', init_value=0.1, discont_value=0.02, create=True), dict(par='exposure_factor', years=2010, vals=0.5) ) # Scenarios can be combined s8 = s1 + s2
Methods