looking into numbers of tests as well
@@ -19,8 +19,9 @@ tp = cv.test_prob(start_day=iday, symp_prob=0.1, asymp_prob=0.01) # Test a numbe
# Properties that are shared across sims
basepop = 10e3
-popscale = 10
popinfected = 20
+popscale1 = 10
+popscale2 = 20 # Try a different population scale
which_interv = 2 # Which intervention to test
shared = sc.objdict(
@@ -31,7 +32,7 @@ shared = sc.objdict(
# Simulate the entire population
p.entire = dict(
- pop_size = basepop*popscale,
+ pop_size = basepop*popscale1,
pop_infected = popinfected,
pop_scale = 1,
rescale = False,
@@ -41,18 +42,44 @@ p.entire = dict(
p.rescale = dict(
pop_size = basepop,
pop_infected = popinfected,
- pop_scale = popscale,
+ pop_scale = popscale1,
rescale = True,
)
# Simulate a small population with static scaling
p.static = dict(
pop_size = basepop,
- pop_infected = popinfected//popscale,
- pop_scale = popscale,
+ pop_infected = popinfected//popscale1,
+ pop_scale = popscale1,
rescale = False,
)
+# Simulate an extra large population
+p.entire2 = dict(
+ pop_size = basepop*popscale2,
+ pop_infected = popinfected,
+ pop_scale = 1,
+ rescale = False,
+)
+
+# Simulate a small population with dynamic scaling
+p.rescale2 = dict(
+ pop_size = basepop,
+ pop_infected = popinfected,
+ pop_scale = popscale2,
+ rescale = True,
+)
+
+# Simulate a small population with static scaling
+p.static2 = dict(
+ pop_size = basepop,
+ pop_infected = popinfected//popscale2,
+ pop_scale = popscale2,
+ rescale = False,
+)
+
+
+# Create and run the sims
keys = p.keys()
for key in keys:
@@ -65,7 +92,16 @@ for key in keys:
for key in keys:
m[key].run()
m[key].reduce()
- m[key].plot()
+
+
+# Plot
+to_plot = {
+ 'Totals': ['cum_infections', 'cum_tests', 'cum_diagnoses'],
+ 'New': ['new_infections', 'new_tests', 'new_diagnoses'],
+ }
+
+for key in keys:
+ m[key].plot(to_plot=to_plot)
bsims = [msim.base_sim for msim in m.values()]
mm = cv.MultiSim(sims=bsims)
