try different test values
@@ -8,15 +8,15 @@ regenerate = 0
datafile = 'target_fit_data.xlsx'
# datafile = '../example_data.csv'
-intervs = []#[cv.change_beta(days=40, changes=0.5), cv.test_prob(start_day=20, symp_prob=0.1, asymp_prob=0.01)] # Common interventions
+intervs = [cv.change_beta(days=40, changes=0.5), cv.test_prob(start_day=20, symp_prob=0.1, asymp_prob=0.01)] # Common interventions
pars = dict(
pop_size = 20000, # Population size
- pop_infected = 100, # Number of initial infections -- use more for increased robustness
+ pop_infected = 80, # Number of initial infections -- use more for increased robustness
pop_type = 'hybrid', # Population to use -- "hybrid" is random with household, school,and work structure
verbose = 0, # Don't print details of the run
interventions = intervs, # Include the most common interventions
- rand_seed = 1,
- beta = 0.015,
+ rand_seed = 2,
+ beta = 0.017,
)
target_pars = dict(
@@ -33,7 +33,7 @@ if regenerate:
sim = cv.Sim(pars, datafile=datafile)
sim.run()
-# sim.plot()
-fit = sim.compute_fit(keys=['cum_deaths', 'cum_diagnoses', 'new_infections', 'new_diagnoses'])
-# print(fit.mismatch)
+fit = sim.compute_fit()
+# fit = sim.compute_fit(keys=['cum_deaths', 'cum_diagnoses', 'new_infections', 'new_diagnoses'])
+print('Mismatch: ', fit.mismatch)
fit.plot()
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