new parameter planes, optionally record degrees

CovidAlertVaccinationModel/src/ABM/abm.jl

-
-const population = 14.57e6 #population of ontario
 const workschool_mixing, rest_mixing = load_mixing_matrices()
 const age_bins = [(0.0, 25.0),(25.0,65.0),(65.0,Inf)]  
 const household_data = read_household_data()
@@ -33,8 +31,8 @@ end
 """
 Run the model with given parameter tuple and output recorder. See `get_parameters` for list of parameters. See `output.jl` for the list of recorders. Currently just 'DebugRecorder`.
 """
-function abm(parameters)
-    model_sol = ModelSolution(parameters.sim_length,parameters,parameters.num_households; record_degrees = false)
+function abm(parameters; record_degrees = false)
+    model_sol = ModelSolution(parameters.sim_length,parameters,parameters.num_households;record_degrees)
     solve!(model_sol)
     return model_sol
 end

CovidAlertVaccinationModel/src/ABM/output.jl

@@ -92,11 +92,11 @@ function record!(t,modelsol)
 end
 
 
-function mean_solve(samples,parameter_tuple;progmeter = nothing)
+function mean_solve(samples,parameter_tuple;progmeter = nothing, record_degrees = false)
     accumulation_recorder = Recorder(Variance(), parameter_tuple.sim_length)
     avg_populations = [0.0,0.0,0.0]
     sol_list = map(1:samples) do _
-        sol = abm(parameter_tuple)
+        sol = abm(parameter_tuple;record_degrees)
         isnothing(progmeter) || next!(progmeter)
         return sol.output_data,length.(sol.index_vectors)
     end

CovidAlertVaccinationModel/src/ABM/parameter_planes.jl

 
-const samples = 25
+const samples = 40
 const univariate_path = "CovidAlertVaccinationModel/plots/univariate/" 
 const bivariate_path = "CovidAlertVaccinationModel/plots/univariate/" 
 function univarate_test(variable, variable_range; progmeter = nothing)
@@ -58,7 +58,7 @@ end
 
 using AxisKeys 
 function multivariate_simulations()
-    len = 20
+    len = 15
     app_simulations = (
         (:η, range(0.0, 2.0; length = len)),
         (:ω_en, range(0.0, 1e-1; length = len)),
@@ -79,13 +79,13 @@ function run_multivariate_sims(sims)
     progmeter = Progress((length(simvars)+1)*samples)
 
     
-    without_app, _ = mean_solve(samples,get_parameters(); progmeter)
+    without_app, _ = mean_solve(samples,get_parameters(); progmeter, record_degrees = true)
     next!(progmeter)
     default_parameters = get_app_parameters() 
     app_output = ThreadsX.map(simvars) do vars
         vars_with_names = NamedTuple{varnames}(vars)
         parameters = merge(default_parameters,vars_with_names)
-        out,_ = mean_solve(samples, parameters;progmeter) 
+        out,_ = mean_solve(samples, parameters;progmeter, record_degrees = true) 
         return out
     end
     display(length(simvars))
@@ -108,15 +108,20 @@ function plot_parameter_plane(input_fname)
     mean_final_size(p) = mean(reduce(merge!,p.final_size_by_age))
     base_outcome = mean_final_size(output_no_app)
     final_size_map = map(x-> (mean_final_size(x) - base_outcome),output)
-    
-    mean_weighted_degree_change(p) = mean(p.avg_weighted_degree_of_vaccinators)-mean(p.avg_weighted_degree)
-    weighted_degree_map = map(mean_weighted_degree_change,output)
-    cs = cgrad([:blue,:orange])
-
-    datamaps = [weighted_degree_map, final_size_map]
-    fnames = ["wdg_change.pdf", "final_size_change.pdf"]
+    mean_weighted_degree_change(p,age) = mean(p.avg_weighted_degree_of_vaccinators[age])-mean(p.avg_weighted_degree[age])
+    weighted_degree_map = [map(p -> mean_weighted_degree_change(p,i),output) for i in 1:3]
+    cs = cgrad(:blues)
+    datamaps = (weighted_degree_map..., final_size_map)
+    fnames = [
+        "wdg_change_Y.pdf",
+        "wdg_change_M.pdf",
+        "wdg_change_O.pdf", 
+        "final_size_change.pdf"
+    ]
     titles = [
-        "Average w. deg. of vaccinators minus average w. deg.",
+        "Average w. deg. of vaccinators minus average w. deg., Y",
+        "Average w. deg. of vaccinators minus average w. deg., M",
+        "Average w. deg. of vaccinators minus average w. deg., O",
         "Effect of notifications on tot. infections",
     ]
     for (fname,title,datamap) in zip(fnames,titles,datamaps)