fpsim.scenarios module¶
Class to define and run scenarios
- make_scen(*args, **kwargs)[source]¶
Alias for
fp.Scenario()
.Store 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
- 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
,dictobj
Store 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
- class Scenarios(pars=None, repeats=None, scens=None, **kwargs)[source]¶
Bases:
prettyobj
Run different intervention scenarios.
A “scenario” can be thought of as a list of sims, all with the same parameters except for the random seed. Usually, scenarios differ from each other only in terms of the interventions run (to compare other differences between sims, it’s preferable to use a MultiSim object).
- Parameters:
pars (dict) – parameters to pass to the sim
repeats (int) – how many repeats of each scenario to run (default: 1)
scens (list) – the list of scenarios to run; see also
fp.make_scen()
andScenarios.add_scen()
kwargs (dict) – optional additional parameters to pass to the sim
Example:
scen1 = fp.make_scen(label='Baseline') scen2 = fp.make_scen(year=2002, eff={'Injectables':0.99}) # Basic efficacy scenario scens = fp.Scenarios(location='test', repeats=2, scens=[scen1, scen2]) scens.run()
- make_sims(scenlabel, **kwargs)[source]¶
Create a list of sims that are all identical except for the random seed
- plot(to_plot=None, plot_sims=True, **kwargs)[source]¶
Plot the scenarios with bands – see
sim.plot()
for args