output simplify wip

CovidAlertVaccinationModel/Manifest.toml

@@ -60,9 +60,9 @@ version = "0.1.16"
 
 [[BangBang]]
 deps = ["Compat", "ConstructionBase", "Future", "InitialValues", "LinearAlgebra", "Requires", "Setfield", "Tables", "ZygoteRules"]
-git-tree-sha1 = "d53b1eaefd48e233545d21f5b764c8ee54df4a09"
+git-tree-sha1 = "e239020994123f08905052b9603b4ca14f8c5807"
 uuid = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"
-version = "0.3.30"
+version = "0.3.31"
 
 [[Base64]]
 uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
@@ -98,9 +98,9 @@ version = "1.16.0+6"
 
 [[ChainRulesCore]]
 deps = ["Compat", "LinearAlgebra", "SparseArrays"]
-git-tree-sha1 = "d659e42240c2162300b321f05173cab5cc40a5ba"
+git-tree-sha1 = "ea05cadc30c15f9185b61ea418b9d47d53b55bc2"
 uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
-version = "0.10.4"
+version = "0.10.8"
 
 [[ColorSchemes]]
 deps = ["ColorTypes", "Colors", "FixedPointNumbers", "Random", "StaticArrays"]
@@ -122,9 +122,9 @@ version = "0.12.8"
 
 [[Compat]]
 deps = ["Base64", "Dates", "DelimitedFiles", "Distributed", "InteractiveUtils", "LibGit2", "Libdl", "LinearAlgebra", "Markdown", "Mmap", "Pkg", "Printf", "REPL", "Random", "SHA", "Serialization", "SharedArrays", "Sockets", "SparseArrays", "Statistics", "Test", "UUIDs", "Unicode"]
-git-tree-sha1 = "e4e2b39db08f967cc1360951f01e8a75ec441cab"
+git-tree-sha1 = "dc7dedc2c2aa9faf59a55c622760a25cbefbe941"
 uuid = "34da2185-b29b-5c13-b0c7-acf172513d20"
-version = "3.30.0"
+version = "3.31.0"
 
 [[CompilerSupportLibraries_jll]]
 deps = ["Artifacts", "Libdl"]
@@ -149,9 +149,9 @@ version = "0.1.2"
 
 [[ConstructionBase]]
 deps = ["LinearAlgebra"]
-git-tree-sha1 = "1dc43957fb9a1574fa1b7a449e101bd1fd3a9fb7"
+git-tree-sha1 = "f74e9d5388b8620b4cee35d4c5a618dd4dc547f4"
 uuid = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
-version = "1.2.1"
+version = "1.3.0"
 
 [[Contour]]
 deps = ["StaticArrays"]
@@ -235,9 +235,9 @@ uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"
 
 [[Distributions]]
 deps = ["FillArrays", "LinearAlgebra", "PDMats", "Printf", "QuadGK", "Random", "SparseArrays", "SpecialFunctions", "Statistics", "StatsBase", "StatsFuns"]
-git-tree-sha1 = "013020ec9a5cdf1dd454eba3704dbffa69d3047e"
+git-tree-sha1 = "62e1ac52e9adf4234285cd88c94954924aa3f9ef"
 uuid = "31c24e10-a181-5473-b8eb-7969acd0382f"
-version = "0.25.3"
+version = "0.25.5"
 
 [[DocStringExtensions]]
 deps = ["LibGit2"]
@@ -292,9 +292,9 @@ version = "4.3.1+4"
 
 [[FFTW]]
 deps = ["AbstractFFTs", "FFTW_jll", "LinearAlgebra", "MKL_jll", "Preferences", "Reexport"]
-git-tree-sha1 = "ae8de3350af3026008be4ba23e1e905ab2011d20"
+git-tree-sha1 = "f985af3b9f4e278b1d24434cbb546d6092fca661"
 uuid = "7a1cc6ca-52ef-59f5-83cd-3a7055c09341"
-version = "1.4.2"
+version = "1.4.3"
 
 [[FFTW_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
@@ -409,9 +409,9 @@ version = "2.0.0"
 
 [[Hwloc_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "aac91e34ef4c166e0857e3d6052a3467e5732ceb"
+git-tree-sha1 = "3395d4d4aeb3c9d31f5929d32760d8baeee88aaf"
 uuid = "e33a78d0-f292-5ffc-b300-72abe9b543c8"
-version = "2.4.1+0"
+version = "2.5.0+0"
 
 [[IfElse]]
 git-tree-sha1 = "28e837ff3e7a6c3cdb252ce49fb412c8eb3caeef"
@@ -621,9 +621,9 @@ version = "1.42.0+0"
 
 [[Libiconv_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
-git-tree-sha1 = "8d22e127ea9a0917bc98ebd3755c8bd31989381e"
+git-tree-sha1 = "42b62845d70a619f063a7da093d995ec8e15e778"
 uuid = "94ce4f54-9a6c-5748-9c1c-f9c7231a4531"
-version = "1.16.1+0"
+version = "1.16.1+1"
 
 [[Libmount_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
@@ -670,15 +670,15 @@ uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
 
 [[LoggingExtras]]
 deps = ["Dates", "Logging"]
-git-tree-sha1 = "59b45fd91b743dff047313bb7af0f84167aef80d"
+git-tree-sha1 = "dfeda1c1130990428720de0024d4516b1902ce98"
 uuid = "e6f89c97-d47a-5376-807f-9c37f3926c36"
-version = "0.4.6"
+version = "0.4.7"
 
 [[LoopVectorization]]
 deps = ["ArrayInterface", "DocStringExtensions", "IfElse", "LinearAlgebra", "OffsetArrays", "Polyester", "Requires", "SLEEFPirates", "Static", "StrideArraysCore", "ThreadingUtilities", "UnPack", "VectorizationBase"]
-git-tree-sha1 = "b16dde45ba9e2506358d4d7fe13f746330e8e622"
+git-tree-sha1 = "0d353c52a418e1d97b7a39d192331157f71b2389"
 uuid = "bdcacae8-1622-11e9-2a5c-532679323890"
-version = "0.12.37"
+version = "0.12.42"
 
 [[MKL_jll]]
 deps = ["Artifacts", "IntelOpenMP_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "Pkg"]
@@ -743,9 +743,9 @@ uuid = "14a3606d-f60d-562e-9121-12d972cd8159"
 
 [[MutableArithmetics]]
 deps = ["LinearAlgebra", "SparseArrays", "Test"]
-git-tree-sha1 = "ad9b2bce6021631e0e20706d361972343a03e642"
+git-tree-sha1 = "3927848ccebcc165952dc0d9ac9aa274a87bfe01"
 uuid = "d8a4904e-b15c-11e9-3269-09a3773c0cb0"
-version = "0.2.19"
+version = "0.2.20"
 
 [[NaNMath]]
 git-tree-sha1 = "bfe47e760d60b82b66b61d2d44128b62e3a369fb"
@@ -774,9 +774,9 @@ uuid = "ca575930-c2e3-43a9-ace4-1e988b2c1908"
 
 [[OffsetArrays]]
 deps = ["Adapt"]
-git-tree-sha1 = "1381a7142eefd4cd12f052a4d2d790fe21bd1d55"
+git-tree-sha1 = "e436bb81d2ce4f01fb02374c4410e5a9229c85f9"
 uuid = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
-version = "1.9.2"
+version = "1.10.0"
 
 [[Ogg_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
@@ -1028,9 +1028,9 @@ version = "1.1.0"
 
 [[SentinelArrays]]
 deps = ["Dates", "Random"]
-git-tree-sha1 = "bc967c221ccdb0b85511709bda96ee489396f544"
+git-tree-sha1 = "ffae887d0f0222a19c406a11c3831776d1383e3d"
 uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
-version = "1.3.2"
+version = "1.3.3"
 
 [[Serialization]]
 uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
@@ -1090,9 +1090,9 @@ version = "0.2.5"
 
 [[StaticArrays]]
 deps = ["LinearAlgebra", "Random", "Statistics"]
-git-tree-sha1 = "42378d3bab8b4f57aa1ca443821b752850592668"
+git-tree-sha1 = "745914ebcd610da69f3cb6bf76cb7bb83dcb8c9a"
 uuid = "90137ffa-7385-5640-81b9-e52037218182"
-version = "1.2.2"
+version = "1.2.4"
 
 [[Statistics]]
 deps = ["LinearAlgebra", "SparseArrays"]
@@ -1216,9 +1216,9 @@ uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
 
 [[VectorizationBase]]
 deps = ["ArrayInterface", "Hwloc", "IfElse", "Libdl", "LinearAlgebra", "Static"]
-git-tree-sha1 = "7c8974c7de377a2dc67e778017c78f96fc8f0fc6"
+git-tree-sha1 = "d3d40e06daf09599a5f6524d1ae4224c573639d0"
 uuid = "3d5dd08c-fd9d-11e8-17fa-ed2836048c2f"
-version = "0.20.16"
+version = "0.20.18"
 
 [[VersionParsing]]
 git-tree-sha1 = "80229be1f670524750d905f8fc8148e5a8c4537f"
@@ -1227,9 +1227,9 @@ version = "1.2.0"
 
 [[Wayland_jll]]
 deps = ["Artifacts", "Expat_jll", "JLLWrappers", "Libdl", "Libffi_jll", "Pkg", "XML2_jll"]
-git-tree-sha1 = "dc643a9b774da1c2781413fd7b6dcd2c56bb8056"
+git-tree-sha1 = "3e61f0b86f90dacb0bc0e73a0c5a83f6a8636e23"
 uuid = "a2964d1f-97da-50d4-b82a-358c7fce9d89"
-version = "1.17.0+4"
+version = "1.19.0+0"
 
 [[Wayland_protocols_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Wayland_jll"]

CovidAlertVaccinationModel/src/ABM/abm.jl

@@ -14,9 +14,8 @@ Runs the model with default parameters.
 """
 function bench()
     p = get_parameters()
-    recording = DebugRecorder(0.0,p.sim_length)
-    abm(p,recording)
-    return recording
+    out = abm(p)
+    return out
 end
 
 
@@ -34,8 +33,8 @@ 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, recorder)
+function abm(parameters)
     model_sol = ModelSolution(parameters.sim_length,parameters,parameters.num_households)
-    output = solve!(model_sol,recorder )
+    solve!(model_sol)
     return model_sol
 end

CovidAlertVaccinationModel/src/ABM/mixing_graphs.jl

@@ -117,7 +117,7 @@ end
 """
 Completely remake all the graphs in `time_dep_mixing_graph.resampled_graphs`.
 """
-function remake!(t,time_dep_mixing_graph,index_vectors,demographics)
+function remake_all!(t,time_dep_mixing_graph,index_vectors,demographics)
     for wg in time_dep_mixing_graph.remade_graphs
         remake!(wg,index_vectors)
     end

CovidAlertVaccinationModel/src/ABM/model_setup.jl

@@ -56,7 +56,7 @@ function app_users(demographics,app_usage_prob)
 end
 
 
-mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
+mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist,RecorderType}
     sim_length::Int
     nodes::Int
     params::T
@@ -74,17 +74,10 @@ mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
     app_user_list::Vector{Int}
     app_user_index::Vector{Int}
     status_totals::Vector{Int}
-    daily_vaccinators::Int
-    daily_cases_by_age::Vector{Int}
-    daily_unvac_cases_by_age::Vector{Int}
-    daily_immunized_by_age::Vector{Int}
-    daily_total_notifications::Int
-    daily_total_notified_agents::Int
-    avg_weighted_degree_of_vaccinators::Variance{Float64,Float64,EqualWeight}
-    avg_weighted_degree::Variance{Float64,Float64,EqualWeight}
     ws_matrix_tuple::WSMixingDist
     rest_matrix_tuple::RestMixingDist
     immunization_countdown::Vector{Int}
+    output_data::RecorderType
     @views function ModelSolution(sim_length,params::T,num_households) where T
         demographics,base_network,index_vectors = generate_population(num_households)
         nodes = length(demographics)
@@ -112,8 +105,10 @@ mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
 
         status_totals = [count(==(AgentStatus(i)), u_0_inf) for i in 1:AgentStatus.size]
         immunization_countdown = fill(-1, nodes) #immunization countdown is negative if not counting down
-        
-        return new{T,typeof(infected_mixing_graph),typeof(soc_mixing_graph),typeof(ws_matrix_tuple),typeof(rest_matrix_tuple)}(
+        output_data = Recorder(0,sim_length)
+        return new{T,typeof(infected_mixing_graph),
+        typeof(soc_mixing_graph),typeof(ws_matrix_tuple),
+        typeof(rest_matrix_tuple), typeof(output_data)}(
             sim_length,
             nodes,
             params,
@@ -131,17 +126,10 @@ mutable struct ModelSolution{T,InfNet,SocNet,WSMixingDist,RestMixingDist}
             app_user_list,
             app_user_index,
             status_totals,
-            0,
-            [0,0,0],
-            [0,0,0],
-            [0,0,0],
-            0,
-            0,
-            Variance(),
-            Variance(),
             ws_matrix_tuple,
             rest_matrix_tuple,
-            immunization_countdown
+            immunization_countdown,
+            output_data
         )
     end
 end

CovidAlertVaccinationModel/src/ABM/output.jl

@@ -2,20 +2,10 @@
 using LabelledArrays
 using Plots
 import OnlineStats.fit!
-
-"""
-AbstractRecorder is the type that all "Recorder" types must extend for `fit!` (and possibly other stuff) to dispatch correctly.
-
-The point of using different recorder types is that we only want to save the output that we need, and that output will vary depending on the specific experiment.
-
-AbstractRecorders can be parameterized to have any element type, so when they are parameterized with T<:OnlineStat, we can use `fit!` to collect statistics about a bunch of Recorders into a single Recorder.
-"""
-abstract type AbstractRecorder{ElType} end
-
 """
-DebugRecorder should store everything we might want to know about the model output. 
+Recorder should store everything we might want to know about the model output. 
 """
-struct DebugRecorder{ElType,ArrT1<:AbstractArray{ElType},ArrT2<:AbstractVector{ElType},ArrT3<:AbstractArray{ElType}} <: AbstractRecorder{ElType}
+struct Recorder{ElType,ArrT1,ArrT2,ArrT3,StatAccumulator}
     recorded_status_totals::ArrT1
     daily_cases_by_age::ArrT3
     total_vaccinators::ArrT2
@@ -28,77 +18,58 @@ struct DebugRecorder{ElType,ArrT1<:AbstractArray{ElType},ArrT2<:AbstractVector{E
     mean_time_since_last_notification::ArrT2
     daily_immunized_by_age::ArrT3
     daily_unvac_cases_by_age::ArrT3
-end
+    avg_weighted_degree_of_vaccinators::Vector{StatAccumulator}
+    avg_weighted_degree::Vector{StatAccumulator}
 
-"""
-HeatmapRecorder, for heatmaps! 
-"""
-struct HeatmapRecorder{ElType,ArrT1<:AbstractArray{ElType},ArrT2<:AbstractArray{Int}} <: AbstractRecorder{ElType}
-    daily_cases_by_age::ArrT2
-    final_size_by_age::ArrT1
-    avg_weighted_degree_of_vaccinators::ElType
-    avg_weighted_degree::ElType
+    function Recorder(val::T,sim_length) where T
+    
+        totals = [copy(val) for i in 1:4, j in 1:sim_length]
+        state_totals = @LArray totals (S = (1,:),I = (2,:),R = (3,:), V = (4,:))
+        total_vaccinators = [copy(val) for j in 1:sim_length]
+    
+        daily_total_notifications = [copy(val) for j in 1:sim_length]
+        daily_total_notified_agents = [copy(val) for j in 1:sim_length]
+    
+        mean_time_since_last_notification = [copy(val) for j in 1:sim_length]
+        totals_ymo = [copy(val) for i in 1:3, j in 1:sim_length]
+        daily_cases_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
+        daily_immunized_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
+        daily_unvac_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
+        unvac_final_size_by_age =  [copy(val) for i in 1:3]
+        total_postinf_vaccination =  [copy(val) for i in 1:3]
+        total_preinf_vaccination =  [copy(val) for i in 1:3]
+        final_size_by_age =  [copy(val) for i in 1:3]
+    
+        avg_weighted_degree_of_vaccinators = [Variance() for _ in 1:3]
+        avg_weighted_degree = [Variance() for _ in 1:3]
+    
+        return new{T,typeof(state_totals),typeof(total_vaccinators),typeof(daily_immunized_by_age),eltype(avg_weighted_degree)}(
+            state_totals,
+            daily_cases_by_age,
+            total_vaccinators,
+            daily_total_notifications,
+            daily_total_notified_agents,
+            unvac_final_size_by_age,
+            total_postinf_vaccination,
+            total_preinf_vaccination,
+            final_size_by_age,
+            mean_time_since_last_notification,
+            daily_immunized_by_age,
+            daily_unvac_by_age,
+            avg_weighted_degree_of_vaccinators,
+            avg_weighted_degree
+        )
+    end
 end
-
 """
-Initialize a DebugRecorder filled with (copies) of val.
+Initialize a Recorder filled with (copies) of val.
 """
-function DebugRecorder(val::T,sim_length) where T
-    
-    totals = [copy(val) for i in 1:4, j in 1:sim_length]
-    state_totals = @LArray totals (S = (1,:),I = (2,:),R = (3,:), V = (4,:))
-    total_vaccinators = [copy(val) for j in 1:sim_length]
-
-    daily_total_notifications = [copy(val) for j in 1:sim_length]
-    daily_total_notified_agents = [copy(val) for j in 1:sim_length]
-
-    mean_time_since_last_notification = [copy(val) for j in 1:sim_length]
-    totals_ymo = [copy(val) for i in 1:3, j in 1:sim_length]
-    daily_cases_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
-    daily_immunized_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
-    daily_unvac_by_age = @LArray deepcopy(totals_ymo) (Y = (1,:),M = (2,:),O = (3,:))
-    unvac_final_size_by_age =  [copy(val) for i in 1:3]
-    total_postinf_vaccination =  [copy(val) for i in 1:3]
-    total_preinf_vaccination =  [copy(val) for i in 1:3]
-    final_size_by_age =  [copy(val) for i in 1:3]
-    return DebugRecorder(
-        state_totals,
-        daily_cases_by_age,
-        total_vaccinators,
-        daily_total_notifications,
-        daily_total_notified_agents,
-        unvac_final_size_by_age,
-        total_postinf_vaccination,
-        total_preinf_vaccination,
-        final_size_by_age,
-        mean_time_since_last_notification,
-        daily_immunized_by_age,
-        daily_unvac_by_age
-    )
-end
-
-function HeatmapRecorder(sim_length) where T<:OnlineStat
-    daily_cases_by_age = @LArray zeros(Int,3,sim_length) (Y = (1,:),M = (2,:),O = (3,:))
-    final_size_by_age =  [Variance() for i in 1:3]
-    average_deg_of_vac = Variance()
-    average_deg = Variance()
-    return HeatmapRecorder(
-        daily_cases_by_age,
-        final_size_by_age,
-        average_deg_of_vac,
-        average_deg,
-    )
-end
 
 
 
-function record!(t,modelsol, recorder::DebugRecorder)
-    recorder.total_vaccinators[t] =  modelsol.daily_vaccinators
-    recorder.daily_cases_by_age[:,t] .= modelsol.daily_cases_by_age
+function record!(t,modelsol)
+    recorder = modelsol.output_data
     recorder.recorded_status_totals[:,t] .= modelsol.status_totals
-    recorder.daily_total_notifications[t] = modelsol.daily_total_notifications
-    recorder.daily_total_notified_agents[t] = modelsol.daily_total_notified_agents
-
     alerts = filter(>(0),modelsol.time_of_last_alert)
     if !isempty(alerts)
         mean_alert_time = mean(t .- alerts) 
@@ -106,9 +77,6 @@ function record!(t,modelsol, recorder::DebugRecorder)
     else
         recorder.mean_time_since_last_notification[t] = 0
     end
-    # display(modelsol.daily_immunizations_by_age)
-    recorder.daily_immunized_by_age[:,t] .= modelsol.daily_immunized_by_age
-    recorder.daily_unvac_cases_by_age[:,t] .= modelsol.daily_unvac_cases_by_age
     if modelsol.sim_length == t
         for age in 1:3
             recorder.unvac_final_size_by_age[age] = sum(recorder.daily_unvac_cases_by_age[age,:])
@@ -118,20 +86,6 @@ function record!(t,modelsol, recorder::DebugRecorder)
         end
     end
 end
-function record!(t,modelsol, recorder::HeatmapRecorder)
-    recorder.daily_cases_by_age[:,t] .= modelsol.daily_cases_by_age
-    if modelsol.sim_length == t
-        for age in 1:3
-            fit!(recorder.final_size_by_age[age], sum(recorder.daily_cases_by_age[age,:]))
-        end
-        merge!(recorder.avg_weighted_degree_of_vaccinators,modelsol.avg_weighted_degree_of_vaccinators)
-        merge!(recorder.avg_weighted_degree,modelsol.avg_weighted_degree)
-    end
-end
-
-function record!(t,modelsol, recorder::Nothing)
-    #do nothing
-end
 
 
 function mean_solve(samples,parameter_tuple,recorder;progmeter = nothing)
@@ -151,23 +105,7 @@ function mean_solve(samples,parameter_tuple,recorder;progmeter = nothing)
     return stat_recorder,avg_populations
 end
 
-function mean_solve(samples,parameter_tuple,recorder::Type{HeatmapRecorder};progmeter = nothing)
-    stat_recorder = recorder(parameter_tuple.sim_length)
-    avg_populations = [0.0,0.0,0.0]
-    sol_list = map(1:samples) do _
-        output_recorder = recorder(parameter_tuple.sim_length)
-        sol = abm(parameter_tuple,output_recorder)
-        isnothing(progmeter) || next!(progmeter)
-        return output_recorder,length.(sol.index_vectors)
-    end
-    for (output_recorder,pop) in sol_list
-        avg_populations .+= pop
-        fit!(stat_recorder,output_recorder)
-    end
-    avg_populations ./= samples
-    return stat_recorder,avg_populations
-end
-function OnlineStats.fit!(accum::R,pt::R2) where {R<:AbstractRecorder,R2<:AbstractRecorder}
+function accumulate_model(accum,pt)
     for field in fieldnames(R)
         stat_field = getfield(accum,field)
         sample_field = getfield(pt,field)

CovidAlertVaccinationModel/src/ABM/plotting.jl

@@ -5,7 +5,7 @@ using Printf
 
 const ts_colors = cgrad(:PuBu_9)
 
-function plot_model(varname,univariate_series, output_list::Vector{T},infection_begin,vac_begin) where T<:DebugRecorder
+function plot_model(varname,univariate_series, output_list::Vector{T},infection_begin,vac_begin) where T
 
     sim_length = length(output_list[1].recorded_status_totals.S)
     ts_list(data) = [

CovidAlertVaccinationModel/src/ABM/solve.jl

@@ -13,10 +13,8 @@ end
 
 Base.@propagate_inbounds @views function update_alert_durations!(t,modelsol) # Base.@propagate_inbounds 
     @unpack notification_parameter,notification_threshold = modelsol.params
-    @unpack time_of_last_alert, app_user_index,inf_network,covid_alert_notifications,app_user = modelsol
+    @unpack time_of_last_alert, app_user_index,inf_network,covid_alert_notifications,app_user, output_data = modelsol
     
-    modelsol.daily_total_notifications = 0
-
     for (i,node) in enumerate(app_user_index)
         for j in 2:14
             covid_alert_notifications[j-1,i] = covid_alert_notifications[j,i] #shift them all back  
@@ -37,7 +35,7 @@ Base.@propagate_inbounds @views function update_alert_durations!(t,modelsol) # B
             covid_alert_notifications[end,i] = 0
         end
         if sum(covid_alert_notifications[:,i])>=notification_threshold
-            modelsol.daily_total_notifications += 1
+            output_data.daily_total_notifications[t] += 1
             time_of_last_alert[i] = t
         end
     end
@@ -45,11 +43,7 @@ end
 
 Base.@propagate_inbounds @views function update_infection_state!(t,modelsol; record_degrees = false)
     @unpack β_y,β_m,β_o,α_y,α_m,α_o,recovery_rate,immunizing,immunization_begin_day = modelsol.params
-    @unpack u_inf,u_vac,u_next_inf,demographics,inf_network,status_totals, immunization_countdown = modelsol
-    
-    modelsol.daily_cases_by_age .= 0
-    modelsol.daily_immunized_by_age .= 0
-    modelsol.daily_unvac_cases_by_age .= 0
+    @unpack u_inf,u_vac,u_next_inf,demographics,inf_network,status_totals, immunization_countdown, output_data = modelsol
     
     function agent_transition!(node, from::AgentStatus,to::AgentStatus) 
         immunization_countdown[node] = -1 
@@ -74,11 +68,11 @@ Base.@propagate_inbounds @views function update_infection_state!(t,modelsol; rec
                         if rand(Random.default_rng(Threads.threadid())) < contact_weight(β_vec[Int(agent_demo)],get_weight(mixing_graph,GraphEdge(i,j)))
                             if agent_status == Immunized && rand(Random.default_rng(Threads.threadid())) < 1- α_vec[Int(agent_demo)]
                                 agent_transition!(i, Immunized,Infected)
-                                modelsol.daily_cases_by_age[Int(agent_demo)]+=1
+                                output_data.daily_cases_by_age[Int(agent_demo),t]+=1
 
                             elseif agent_status == Susceptible
-                                modelsol.daily_cases_by_age[Int(agent_demo)]+=1
-                                modelsol.daily_unvac_cases_by_age[Int(agent_demo)]+=1
+                                output_data.daily_cases_by_age[Int(agent_demo),t]+=1
+                                output_data.daily_unvac_cases_by_age[Int(agent_demo),t]+=1
                                 agent_transition!(i, Susceptible,Infected)
                             end
                         end
@@ -92,15 +86,15 @@ Base.@propagate_inbounds @views function update_infection_state!(t,modelsol; rec
         end
         weighted_degree_of_i::Int = record_degrees ? weighted_degree(t,i,inf_network) : 0
         if immunization_countdown[i] == 0 
-            modelsol.daily_immunized_by_age[Int(agent_demo)] += 1
-            fit!(modelsol.avg_weighted_degree_of_vaccinators,weighted_degree_of_i)
+            output_data.daily_immunized_by_age[Int(agent_demo),t] += 1
+            fit!(output_data.avg_weighted_degree_of_vaccinators[Int(agent_demo)],weighted_degree_of_i)
             agent_transition!(i, Susceptible,Immunized)
 
         elseif immunization_countdown[i]>0
-            fit!(modelsol.avg_weighted_degree,weighted_degree_of_i)
+            fit!(output_data.avg_weighted_degree[Int(agent_demo)],weighted_degree_of_i)
             immunization_countdown[i] -= 1
         else
-            fit!(modelsol.avg_weighted_degree,weighted_degree_of_i)
+            fit!(output_data.avg_weighted_degree[Int(agent_demo)],weighted_degree_of_i)
         end
     end
 end
@@ -108,10 +102,8 @@ end
 
 Base.@propagate_inbounds @views function update_vaccination_opinion_state!(t,modelsol,total_infections)
     @unpack infection_introduction_day, π_base_y,π_base_m,π_base_o, η,Γ,ζ, ω, ω_en,ξ = modelsol.params
-    @unpack demographics,time_of_last_alert, nodes, soc_network,u_vac,u_next_vac,app_user,app_user_list = modelsol
+    @unpack demographics,time_of_last_alert, nodes, soc_network,u_vac,u_next_vac,app_user,app_user_list,output_data = modelsol
    
-    modelsol.daily_total_notified_agents = 0
-    # display(time_of_last_alert[1:20])
     for i in 1:nodes
         π_base = t<infection_introduction_day ? 
         (π_base_y,π_base_m,π_base_o) : 
@@ -121,7 +113,7 @@ Base.@propagate_inbounds @views function update_vaccination_opinion_state!(t,mod
                 random_neighbour = sample(Random.default_rng(Threads.threadid()), neighbors(random_soc_network.g,i))
                 app_vac_payoff = 0.0    
                 if app_user[i] && time_of_last_alert[app_user_list[i]]>=0
-                    modelsol.daily_total_notified_agents += 1
+                    output_data.daily_total_notified_agents[t] += 1
                     app_vac_payoff = Γ^((t - time_of_last_alert[app_user_list[i]])) * (η + total_infections*ω_en) 
                     # display(t - time_of_last_alert[app_user_list[i]])
                 end
@@ -141,7 +133,7 @@ Base.@propagate_inbounds @views function update_vaccination_opinion_state!(t,mod
                 end
         end
     end
-    modelsol.daily_vaccinators = count(==(true),u_vac) 
+    output_data.total_vaccinators[t] = count(==(true),u_vac) 
 end
 
 function weighted_degree(t,node,network::TimeDepMixingGraph)
@@ -170,12 +162,12 @@ function sample_initial_nodes(nodes,graphs,I_0_fraction)
 end    
 
 
-function solve!(modelsol,recording::T) where T
+function solve!(modelsol)
     init_indices = sample_initial_nodes(modelsol.nodes, modelsol.inf_network.graph_list[begin], modelsol.params.I_0_fraction)
     for t in 1:modelsol.sim_length  
         #this also resamples the soc network weights since they point to the same objects, but those are never used
         if t>1
-            remake!(t,modelsol.inf_network,modelsol.index_vectors,modelsol.demographics)
+            remake_all!(t,modelsol.inf_network,modelsol.index_vectors,modelsol.demographics)
         end
 
         if t>modelsol.params.infection_introduction_day
@@ -190,12 +182,12 @@ function solve!(modelsol,recording::T) where T
             update_alert_durations!(t,modelsol