switch back to poissoncountsampler, much faster

CovidAlertVaccinationModel/src/ABM/mixing_distributions.jl

@@ -38,8 +38,8 @@ const contact_time_distributions = load_contact_time_distributions()
 
 function shift_contact_distributions(sampler_matrix::AbstractMatrix{T},proportion) where T
     return map(sampler_matrix) do sampler
-        μ_old = mean(sampler)
-        return Poisson(μ_old*proportion)
+        μ_old = sampler.μ#mean(sampler)
+        return Distributions.PoissonCountSampler(Poisson(μ_old*proportion))
     end
 end
 

CovidAlertVaccinationModel/src/ABM/mixing_graphs.jl

@@ -97,8 +97,6 @@ function time_dep_mixing_graphs(len,base_network,demographics,index_vectors,ws_m
     rest_justonce_edges = WeightedGraph(demographics,index_vectors,rest_matrix_tuple.otherwise,daily_shift(contact_time_distributions.rest))
     
 
-    
-
     inf_network_list = [home_static_edges,rest_static_edges,ws_justonce_edges,rest_justonce_edges] 
     soc_network_list = [home_static_edges,rest_static_edges,ws_static_edges]
 

CovidAlertVaccinationModel/src/data.jl

@@ -101,9 +101,9 @@ function load_mixing_matrices()
     return map(t -> from_mean.(Geometric{Float64},t),workschool_mixing), map(t -> from_mean.(Geometric{Float64}, t),rest_mixing)
 end
 
-# function make_sampler(λ)
-#     return Distributions.PoissonADSampler(λ)#Distributions.DiscreteNonParametricSampler(0:durmax,[pdf(Poisson(λ),x) for x in 0:durmax])
-# end
+function make_sampler(λ)
+    return Distributions.PoissonADSampler(λ)#Distributions.DiscreteNonParametricSampler(0:durmax,[pdf(Poisson(λ),x) for x in 0:durmax])
+end
 function load_contact_time_distributions()
     distkey = "Distributions.Poisson"
     fnames = (
@@ -113,7 +113,7 @@ function load_contact_time_distributions()
     )
     contact_distributions_tuple = map(fnames) do fname
         dat = deserialize(joinpath(PACKAGE_FOLDER,"intervals_model_output","simulation_output","$fname.dat"))
-        return map(p -> Poisson(mode(p.particles)), as_symmetric_matrix(dat[distkey].P))
+        return map(p -> make_sampler(mode(p.particles)), as_symmetric_matrix(dat[distkey].P))
     end
     return contact_distributions_tuple
 end