diff --git a/CovidABM/LICENSE b/CovidAlertVaccinationModel/LICENSE
similarity index 100%
rename from CovidABM/LICENSE
rename to CovidAlertVaccinationModel/LICENSE
diff --git a/CovidAlertVaccinationModel/Manifest.toml b/CovidAlertVaccinationModel/Manifest.toml
new file mode 100644
index 0000000000000000000000000000000000000000..9f2dd289cf1e7347e1255edf9e28e64f56b22f94
--- /dev/null
+++ b/CovidAlertVaccinationModel/Manifest.toml
@@ -0,0 +1,1090 @@
+# This file is machine-generated - editing it directly is not advised
+
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+git-tree-sha1 = "269f5c1955c1194086cf6d2029aa4a0b4fb8018b"
+uuid = "ac1d9e8a-700a-412c-b207-f0111f4b6c0d"
+version = "0.1.7"
+
+[[TimeZones]]
+deps = ["Dates", "EzXML", "Mocking", "Pkg", "Printf", "RecipesBase", "Serialization", "Unicode"]
+git-tree-sha1 = "4ba8a9579a243400db412b50300cd61d7447e583"
+uuid = "f269a46b-ccf7-5d73-abea-4c690281aa53"
+version = "1.5.3"
+
+[[Transducers]]
+deps = ["ArgCheck", "BangBang", "CompositionsBase", "DefineSingletons", "Distributed", "InitialValues", "Logging", "Markdown", "MicroCollections", "Requires", "Setfield", "SplittablesBase", "Tables"]
+git-tree-sha1 = "9550eba57ebc2f7677c4c946aaca56e149ca73ff"
+uuid = "28d57a85-8fef-5791-bfe6-a80928e7c999"
+version = "0.4.59"
+
+[[URIs]]
+git-tree-sha1 = "7855809b88d7b16e9b029afd17880930626f54a2"
+uuid = "5c2747f8-b7ea-4ff2-ba2e-563bfd36b1d4"
+version = "1.2.0"
+
+[[UUIDs]]
+deps = ["Random", "SHA"]
+uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+
+[[UnPack]]
+git-tree-sha1 = "387c1f73762231e86e0c9c5443ce3b4a0a9a0c2b"
+uuid = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
+version = "1.0.2"
+
+[[Unicode]]
+uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
+
+[[Wayland_jll]]
+deps = ["Artifacts", "Expat_jll", "JLLWrappers", "Libdl", "Libffi_jll", "Pkg", "XML2_jll"]
+git-tree-sha1 = "dc643a9b774da1c2781413fd7b6dcd2c56bb8056"
+uuid = "a2964d1f-97da-50d4-b82a-358c7fce9d89"
+version = "1.17.0+4"
+
+[[Wayland_protocols_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Wayland_jll"]
+git-tree-sha1 = "2839f1c1296940218e35df0bbb220f2a79686670"
+uuid = "2381bf8a-dfd0-557d-9999-79630e7b1b91"
+version = "1.18.0+4"
+
+[[XML2_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Libiconv_jll", "Pkg", "Zlib_jll"]
+git-tree-sha1 = "afd2b541e8fd425cd3b7aa55932a257035ab4a70"
+uuid = "02c8fc9c-b97f-50b9-bbe4-9be30ff0a78a"
+version = "2.9.11+0"
+
+[[XSLT_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Libgcrypt_jll", "Pkg", "XML2_jll"]
+git-tree-sha1 = "2b3eac39df218762d2d005702d601cd44c997497"
+uuid = "aed1982a-8fda-507f-9586-7b0439959a61"
+version = "1.1.33+4"
+
+[[Xorg_libX11_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libxcb_jll", "Xorg_xtrans_jll"]
+git-tree-sha1 = "5be649d550f3f4b95308bf0183b82e2582876527"
+uuid = "4f6342f7-b3d2-589e-9d20-edeb45f2b2bc"
+version = "1.6.9+4"
+
+[[Xorg_libXau_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "4e490d5c960c314f33885790ed410ff3a94ce67e"
+uuid = "0c0b7dd1-d40b-584c-a123-a41640f87eec"
+version = "1.0.9+4"
+
+[[Xorg_libXcursor_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libXfixes_jll", "Xorg_libXrender_jll"]
+git-tree-sha1 = "12e0eb3bc634fa2080c1c37fccf56f7c22989afd"
+uuid = "935fb764-8cf2-53bf-bb30-45bb1f8bf724"
+version = "1.2.0+4"
+
+[[Xorg_libXdmcp_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "4fe47bd2247248125c428978740e18a681372dd4"
+uuid = "a3789734-cfe1-5b06-b2d0-1dd0d9d62d05"
+version = "1.1.3+4"
+
+[[Xorg_libXext_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"]
+git-tree-sha1 = "b7c0aa8c376b31e4852b360222848637f481f8c3"
+uuid = "1082639a-0dae-5f34-9b06-72781eeb8cb3"
+version = "1.3.4+4"
+
+[[Xorg_libXfixes_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"]
+git-tree-sha1 = "0e0dc7431e7a0587559f9294aeec269471c991a4"
+uuid = "d091e8ba-531a-589c-9de9-94069b037ed8"
+version = "5.0.3+4"
+
+[[Xorg_libXi_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libXext_jll", "Xorg_libXfixes_jll"]
+git-tree-sha1 = "89b52bc2160aadc84d707093930ef0bffa641246"
+uuid = "a51aa0fd-4e3c-5386-b890-e753decda492"
+version = "1.7.10+4"
+
+[[Xorg_libXinerama_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libXext_jll"]
+git-tree-sha1 = "26be8b1c342929259317d8b9f7b53bf2bb73b123"
+uuid = "d1454406-59df-5ea1-beac-c340f2130bc3"
+version = "1.1.4+4"
+
+[[Xorg_libXrandr_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libXext_jll", "Xorg_libXrender_jll"]
+git-tree-sha1 = "34cea83cb726fb58f325887bf0612c6b3fb17631"
+uuid = "ec84b674-ba8e-5d96-8ba1-2a689ba10484"
+version = "1.5.2+4"
+
+[[Xorg_libXrender_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"]
+git-tree-sha1 = "19560f30fd49f4d4efbe7002a1037f8c43d43b96"
+uuid = "ea2f1a96-1ddc-540d-b46f-429655e07cfa"
+version = "0.9.10+4"
+
+[[Xorg_libpthread_stubs_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "6783737e45d3c59a4a4c4091f5f88cdcf0908cbb"
+uuid = "14d82f49-176c-5ed1-bb49-ad3f5cbd8c74"
+version = "0.1.0+3"
+
+[[Xorg_libxcb_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "XSLT_jll", "Xorg_libXau_jll", "Xorg_libXdmcp_jll", "Xorg_libpthread_stubs_jll"]
+git-tree-sha1 = "daf17f441228e7a3833846cd048892861cff16d6"
+uuid = "c7cfdc94-dc32-55de-ac96-5a1b8d977c5b"
+version = "1.13.0+3"
+
+[[Xorg_libxkbfile_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libX11_jll"]
+git-tree-sha1 = "926af861744212db0eb001d9e40b5d16292080b2"
+uuid = "cc61e674-0454-545c-8b26-ed2c68acab7a"
+version = "1.1.0+4"
+
+[[Xorg_xcb_util_image_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_xcb_util_jll"]
+git-tree-sha1 = "0fab0a40349ba1cba2c1da699243396ff8e94b97"
+uuid = "12413925-8142-5f55-bb0e-6d7ca50bb09b"
+version = "0.4.0+1"
+
+[[Xorg_xcb_util_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libxcb_jll"]
+git-tree-sha1 = "e7fd7b2881fa2eaa72717420894d3938177862d1"
+uuid = "2def613f-5ad1-5310-b15b-b15d46f528f5"
+version = "0.4.0+1"
+
+[[Xorg_xcb_util_keysyms_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_xcb_util_jll"]
+git-tree-sha1 = "d1151e2c45a544f32441a567d1690e701ec89b00"
+uuid = "975044d2-76e6-5fbe-bf08-97ce7c6574c7"
+version = "0.4.0+1"
+
+[[Xorg_xcb_util_renderutil_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_xcb_util_jll"]
+git-tree-sha1 = "dfd7a8f38d4613b6a575253b3174dd991ca6183e"
+uuid = "0d47668e-0667-5a69-a72c-f761630bfb7e"
+version = "0.3.9+1"
+
+[[Xorg_xcb_util_wm_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_xcb_util_jll"]
+git-tree-sha1 = "e78d10aab01a4a154142c5006ed44fd9e8e31b67"
+uuid = "c22f9ab0-d5fe-5066-847c-f4bb1cd4e361"
+version = "0.4.1+1"
+
+[[Xorg_xkbcomp_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_libxkbfile_jll"]
+git-tree-sha1 = "4bcbf660f6c2e714f87e960a171b119d06ee163b"
+uuid = "35661453-b289-5fab-8a00-3d9160c6a3a4"
+version = "1.4.2+4"
+
+[[Xorg_xkeyboard_config_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Xorg_xkbcomp_jll"]
+git-tree-sha1 = "5c8424f8a67c3f2209646d4425f3d415fee5931d"
+uuid = "33bec58e-1273-512f-9401-5d533626f822"
+version = "2.27.0+4"
+
+[[Xorg_xtrans_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "79c31e7844f6ecf779705fbc12146eb190b7d845"
+uuid = "c5fb5394-a638-5e4d-96e5-b29de1b5cf10"
+version = "1.4.0+3"
+
+[[ZeroWeightedDistributions]]
+deps = ["Distributions", "Random"]
+path = "../ZeroWeightedDistributions"
+uuid = "24733ad3-391a-4e41-8839-c7177de7dea4"
+version = "0.1.0"
+
+[[Zlib_jll]]
+deps = ["Libdl"]
+uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
+
+[[Zstd_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "2c1332c54931e83f8f94d310fa447fd743e8d600"
+uuid = "3161d3a3-bdf6-5164-811a-617609db77b4"
+version = "1.4.8+0"
+
+[[ZygoteRules]]
+deps = ["MacroTools"]
+git-tree-sha1 = "9e7a1e8ca60b742e508a315c17eef5211e7fbfd7"
+uuid = "700de1a5-db45-46bc-99cf-38207098b444"
+version = "0.2.1"
+
+[[libass_jll]]
+deps = ["Artifacts", "Bzip2_jll", "FreeType2_jll", "FriBidi_jll", "JLLWrappers", "Libdl", "Pkg", "Zlib_jll"]
+git-tree-sha1 = "acc685bcf777b2202a904cdcb49ad34c2fa1880c"
+uuid = "0ac62f75-1d6f-5e53-bd7c-93b484bb37c0"
+version = "0.14.0+4"
+
+[[libfdk_aac_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "7a5780a0d9c6864184b3a2eeeb833a0c871f00ab"
+uuid = "f638f0a6-7fb0-5443-88ba-1cc74229b280"
+version = "0.1.6+4"
+
+[[libpng_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Zlib_jll"]
+git-tree-sha1 = "6abbc424248097d69c0c87ba50fcb0753f93e0ee"
+uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f"
+version = "1.6.37+6"
+
+[[libvorbis_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Ogg_jll", "Pkg"]
+git-tree-sha1 = "fa14ac25af7a4b8a7f61b287a124df7aab601bcd"
+uuid = "f27f6e37-5d2b-51aa-960f-b287f2bc3b7a"
+version = "1.3.6+6"
+
+[[nghttp2_jll]]
+deps = ["Artifacts", "Libdl"]
+uuid = "8e850ede-7688-5339-a07c-302acd2aaf8d"
+
+[[x264_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "d713c1ce4deac133e3334ee12f4adff07f81778f"
+uuid = "1270edf5-f2f9-52d2-97e9-ab00b5d0237a"
+version = "2020.7.14+2"
+
+[[x265_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "487da2f8f2f0c8ee0e83f39d13037d6bbf0a45ab"
+uuid = "dfaa095f-4041-5dcd-9319-2fabd8486b76"
+version = "3.0.0+3"
+
+[[xkbcommon_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg", "Wayland_jll", "Wayland_protocols_jll", "Xorg_libxcb_jll", "Xorg_xkeyboard_config_jll"]
+git-tree-sha1 = "ece2350174195bb31de1a63bea3a41ae1aa593b6"
+uuid = "d8fb68d0-12a3-5cfd-a85a-d49703b185fd"
+version = "0.9.1+5"
diff --git a/CovidABM/Project.toml b/CovidAlertVaccinationModel/Project.toml
similarity index 94%
rename from CovidABM/Project.toml
rename to CovidAlertVaccinationModel/Project.toml
index 923bdb0023c373be5345e28486135f2a81fad8b7..cdbf10a9ae4c292df5cd3c9a878986ffdbe369ef 100644
--- a/CovidABM/Project.toml
+++ b/CovidAlertVaccinationModel/Project.toml
@@ -23,6 +23,7 @@ RandomNumbers = "e6cf234a-135c-5ec9-84dd-332b85af5143"
StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
ThreadsX = "ac1d9e8a-700a-412c-b207-f0111f4b6c0d"
UnPack = "3a884ed6-31ef-47d7-9d2a-63182c4928ed"
+ZeroWeightedDistributions = "24733ad3-391a-4e41-8839-c7177de7dea4"
[compat]
julia = "1"
diff --git a/CovidABM/data/csv/COVID_ontario_data.csv b/CovidAlertVaccinationModel/data/csv/COVID_ontario_data.csv
similarity index 100%
rename from CovidABM/data/csv/COVID_ontario_data.csv
rename to CovidAlertVaccinationModel/data/csv/COVID_ontario_data.csv
diff --git a/CovidABM/data/csv/case_fatality_data.csv b/CovidAlertVaccinationModel/data/csv/case_fatality_data.csv
similarity index 100%
rename from CovidABM/data/csv/case_fatality_data.csv
rename to CovidAlertVaccinationModel/data/csv/case_fatality_data.csv
diff --git a/CovidABM/data/csv/demographic_data.csv b/CovidAlertVaccinationModel/data/csv/demographic_data.csv
similarity index 100%
rename from CovidABM/data/csv/demographic_data.csv
rename to CovidAlertVaccinationModel/data/csv/demographic_data.csv
diff --git a/CovidABM/data/csv/distancing_data.csv b/CovidAlertVaccinationModel/data/csv/distancing_data.csv
similarity index 100%
rename from CovidABM/data/csv/distancing_data.csv
rename to CovidAlertVaccinationModel/data/csv/distancing_data.csv
diff --git a/CovidABM/data/csv/home_compositions.csv b/CovidAlertVaccinationModel/data/csv/home_compositions.csv
similarity index 100%
rename from CovidABM/data/csv/home_compositions.csv
rename to CovidAlertVaccinationModel/data/csv/home_compositions.csv
diff --git a/CovidABM/fetch_data.sh b/CovidAlertVaccinationModel/fetch_data.sh
similarity index 100%
rename from CovidABM/fetch_data.sh
rename to CovidAlertVaccinationModel/fetch_data.sh
diff --git a/CovidABM/plots/graphplot.gif b/CovidAlertVaccinationModel/plots/graphplot.gif
similarity index 100%
rename from CovidABM/plots/graphplot.gif
rename to CovidAlertVaccinationModel/plots/graphplot.gif
diff --git a/CovidABM/scratch_code/sampler_performance.jl b/CovidAlertVaccinationModel/scratch_code/sampler_performance.jl
similarity index 100%
rename from CovidABM/scratch_code/sampler_performance.jl
rename to CovidAlertVaccinationModel/scratch_code/sampler_performance.jl
diff --git a/CovidABM/scratch_code/test.jl b/CovidAlertVaccinationModel/scratch_code/test.jl
similarity index 100%
rename from CovidABM/scratch_code/test.jl
rename to CovidAlertVaccinationModel/scratch_code/test.jl
diff --git a/CovidABM/scratch_code/utils.jl b/CovidAlertVaccinationModel/scratch_code/utils.jl
similarity index 100%
rename from CovidABM/scratch_code/utils.jl
rename to CovidAlertVaccinationModel/scratch_code/utils.jl
diff --git a/CovidABM/src/CovidAlertVaccinationModel.jl b/CovidAlertVaccinationModel/src/CovidAlertVaccinationModel.jl
similarity index 89%
rename from CovidABM/src/CovidAlertVaccinationModel.jl
rename to CovidAlertVaccinationModel/src/CovidAlertVaccinationModel.jl
index 2cbdd68033a9562aea5dc253231d0ae9ed6b0f47..9e8fbd5f38283f4ab00bed691e749a5606cd6982 100644
--- a/CovidABM/src/CovidAlertVaccinationModel.jl
+++ b/CovidAlertVaccinationModel/src/CovidAlertVaccinationModel.jl
@@ -1,5 +1,5 @@
module CovidAlertVaccinationModel
-# export get_u_0, solve!,get_parameters,plot_model,main,parse_cases_data,AgentModel,vaccination_rate_test,vaccinate_uniformly!
+using ZeroWeightedDistributions
using LightGraphs
using RandomNumbers.Xorshifts
using Random
@@ -12,12 +12,12 @@ import StatsBase:mean
using Dates
using ThreadsX
using DelimitedFiles
+
using NamedTupleTools
# using CUDA
using NetworkLayout:Stress
using NetworkLayout:SFDP
-import Base.rand
-import Random.rand!
+
import LightGraphs.add_edge!
include("agents.jl")
diff --git a/CovidABM/src/agents.jl b/CovidAlertVaccinationModel/src/agents.jl
similarity index 100%
rename from CovidABM/src/agents.jl
rename to CovidAlertVaccinationModel/src/agents.jl
diff --git a/CovidABM/src/data.jl b/CovidAlertVaccinationModel/src/data.jl
similarity index 100%
rename from CovidABM/src/data.jl
rename to CovidAlertVaccinationModel/src/data.jl
diff --git a/CovidABM/src/graphs.jl b/CovidAlertVaccinationModel/src/graphs.jl
similarity index 100%
rename from CovidABM/src/graphs.jl
rename to CovidAlertVaccinationModel/src/graphs.jl
diff --git a/CovidABM/src/mixing_distributions.jl b/CovidAlertVaccinationModel/src/mixing_distributions.jl
similarity index 54%
rename from CovidABM/src/mixing_distributions.jl
rename to CovidAlertVaccinationModel/src/mixing_distributions.jl
index e052f8bf0f6e3960c6856f05eb1d9c4456d285b1..d97120cfe9aaff6525a6fa9d9cf77df5b5be689a 100644
--- a/CovidABM/src/mixing_distributions.jl
+++ b/CovidAlertVaccinationModel/src/mixing_distributions.jl
@@ -1,27 +1,24 @@
-struct ZWDist{BaseDistType,T} <: Sampleable{Univariate,Discrete}
- α::T
- base_dist::BaseDistType
-end
-function Base.rand(rng::AbstractRNG, s::ZWDist{DType,EType}, n::T) where {T<:Int, EType, DType}
- l = Vector{EType}(undef,n)
- Random.rand!(rng,l)
- l[l .< s.α] .= 0
- Random.rand!(rng,s.base_dist,@view l[l .>= s.α])
- return l
+function adjust_distributions_mean(distribution_matrix::AbstractArray{T},mean_shift_percentage) where T<:ZWDist
+ return map(distribution_matrix) do dist
+ new_mean = mean(dist)*(1 + mean_shift_percentage)
+ return from_mean(typeof(dist),dist.α, new_mean)
+ end
end
-function Random.rand!(rng::AbstractRNG, s::ZWDist, l::T) where T<:AbstractVector
- Random.rand!(rng,l)
- l[l .< s.α] .= 0
- Random.rand!(rng,s.base_dist,@view l[l .>= s.α])
- return l
+function adjust_distributions_mean(distribution_matrix::AbstractArray{T},mean_shift_percentage) where T<:Distribution
+ return map(distribution_matrix) do dist
+ new_mean = mean(dist)*(1 + mean_shift_percentage)
+ return from_mean(typeof(dist), new_mean)
+ end
end
-function Base.rand(rng::AbstractRNG, s::ZWDist{DType,T}) where {DType,T}
- return ifelse(Base.rand(rng) < s.α, zero(T), Base.rand(rng,s.base_dist))
+function ZeroPoisson(α,λ)
+ return ZWDist(α,Poisson(λ))
+end
+function ZeroGeometric(α,p)
+ return ZWDist(α,Geometric(p))
end
-
function from_mean(::Type{Geometric{T}},μ) where T
@@ -37,39 +34,16 @@ end
function from_mean(::Type{ZWDist{DistType,T}},α,μ) where {DistType <: Distribution{Univariate,W} where W, T}
return ZWDist(α,from_mean(DistType,μ/(1-α)))
end
-
-function ZeroPoisson(α,λ)
- return ZWDist(α,Poisson(λ))
-end
-function ZeroGeometric(α,p)
- return ZWDist(α,Geometric(p))
-end
-
-function adjust_distributions_mean(distribution_matrix::AbstractArray{T},mean_shift_percentage) where T<:ZWDist
- return map(distribution_matrix) do dist
- new_mean = mean(dist)*(1 + mean_shift_percentage)
- return from_mean(typeof(dist),dist.α, new_mean)
- end
-end
-function adjust_distributions_mean(distribution_matrix::AbstractArray{T},mean_shift_percentage) where T<:Distribution
- return map(distribution_matrix) do dist
- new_mean = mean(dist)*(1 + mean_shift_percentage)
- return from_mean(typeof(dist), new_mean)
- end
-end
-
-
-
StatsBase.mean(d::ZWDist{Dist,T}) where {Dist,T} = (1 - d.α)*StatsBase.mean(d.base_dist)
-const initial_workschool_type = Union{ZWDist{Geometric{Float64},Float64},ZWDist{Poisson{Float64},Float64}}
+const initial_workschool_type = Union{ZWDist{Geometric{Float64},Discrete},ZWDist{Poisson{Float64},Discrete}}
const initial_workschool_mixing_matrix = convert(Array{initial_workschool_type},map(t->from_mean(t...),[
- (ZWDist{Geometric{Float64},Float64}, 0.433835,4.104848) (ZWDist{Geometric{Float64},Float64},0.406326,2.568782) (ZWDist{Poisson{Float64},Float64},0.888015,0.017729) (ZWDist{Geometric{Float64},Float64},0.406326,2.568782) (ZWDist{Poisson{Float64},Float64},0.888015,0.017729)
- (ZWDist{Geometric{Float64},Float64}, 0.600966,0.975688) (ZWDist{Geometric{Float64},Float64},0.4306,5.057572) (ZWDist{Poisson{Float64},Float64}, 0.84513,0.021307) (ZWDist{Geometric{Float64},Float64},0.4306,5.057572) (ZWDist{Poisson{Float64},Float64}, 0.84513,0.021307)
- (ZWDist{Poisson{Float64},Float64},0.887392,0.001937) (ZWDist{Poisson{Float64},Float64},0.793004,0.00722) (ZWDist{Poisson{Float64},Float64},0.940473, 0.022134) (ZWDist{Poisson{Float64},Float64},0.793004,0.00722) (ZWDist{Poisson{Float64},Float64},0.940473, 0.022134)
- (ZWDist{Geometric{Float64},Float64}, 0.600966,0.975688) (ZWDist{Geometric{Float64},Float64},0.4306,5.057572) (ZWDist{Poisson{Float64},Float64}, 0.84513,0.021307) (ZWDist{Geometric{Float64},Float64},0.4306,5.057572) (ZWDist{Poisson{Float64},Float64}, 0.84513,0.021307)
- (ZWDist{Poisson{Float64},Float64},0.887392,0.001937) (ZWDist{Poisson{Float64},Float64},0.793004,0.00722) (ZWDist{Poisson{Float64},Float64},0.940473, 0.022134) (ZWDist{Poisson{Float64},Float64},0.793004,0.00722) (ZWDist{Poisson{Float64},Float64},0.940473, 0.022134)
+ (ZWDist{Geometric{Float64},Discrete}, 0.433835,4.104848) (ZWDist{Geometric{Float64},Discrete},0.406326,2.568782) (ZWDist{Poisson{Float64},Discrete},0.888015,0.017729) (ZWDist{Geometric{Float64},Discrete},0.406326,2.568782) (ZWDist{Poisson{Float64},Discrete},0.888015,0.017729)
+ (ZWDist{Geometric{Float64},Discrete}, 0.600966,0.975688) (ZWDist{Geometric{Float64},Discrete},0.4306,5.057572) (ZWDist{Poisson{Float64},Discrete}, 0.84513,0.021307) (ZWDist{Geometric{Float64},Discrete},0.4306,5.057572) (ZWDist{Poisson{Float64},Discrete}, 0.84513,0.021307)
+ (ZWDist{Poisson{Float64},Discrete},0.887392,0.001937) (ZWDist{Poisson{Float64},Discrete},0.793004,0.00722) (ZWDist{Poisson{Float64},Discrete},0.940473, 0.022134) (ZWDist{Poisson{Float64},Discrete},0.793004,0.00722) (ZWDist{Poisson{Float64},Discrete},0.940473, 0.022134)
+ (ZWDist{Geometric{Float64},Discrete}, 0.600966,0.975688) (ZWDist{Geometric{Float64},Discrete},0.4306,5.057572) (ZWDist{Poisson{Float64},Discrete}, 0.84513,0.021307) (ZWDist{Geometric{Float64},Discrete},0.4306,5.057572) (ZWDist{Poisson{Float64},Discrete}, 0.84513,0.021307)
+ (ZWDist{Poisson{Float64},Discrete},0.887392,0.001937) (ZWDist{Poisson{Float64},Discrete},0.793004,0.00722) (ZWDist{Poisson{Float64},Discrete},0.940473, 0.022134) (ZWDist{Poisson{Float64},Discrete},0.793004,0.00722) (ZWDist{Poisson{Float64},Discrete},0.940473, 0.022134)
]))
diff --git a/CovidABM/src/model.jl b/CovidAlertVaccinationModel/src/model.jl
similarity index 100%
rename from CovidABM/src/model.jl
rename to CovidAlertVaccinationModel/src/model.jl
diff --git a/CovidABM/src/plotting.jl b/CovidAlertVaccinationModel/src/plotting.jl
similarity index 100%
rename from CovidABM/src/plotting.jl
rename to CovidAlertVaccinationModel/src/plotting.jl
diff --git a/CovidABM/test/runtests.jl b/CovidAlertVaccinationModel/test/runtests.jl
similarity index 100%
rename from CovidABM/test/runtests.jl
rename to CovidAlertVaccinationModel/test/runtests.jl
diff --git a/IntervalsModel/Manifest.toml b/IntervalsModel/Manifest.toml
index dcd5e02f5ca567557f54ee2dc877d2a084282b56..b631eb5ad75dd8b834f83f549385f62ae064f0b9 100644
--- a/IntervalsModel/Manifest.toml
+++ b/IntervalsModel/Manifest.toml
@@ -41,6 +41,11 @@ version = "3.1.1"
[[Artifacts]]
uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
+[[BSON]]
+git-tree-sha1 = "dd36d7cf3d185eeaaf64db902c15174b22f5dafb"
+uuid = "fbb218c0-5317-5bc6-957e-2ee96dd4b1f0"
+version = "0.2.6"
+
[[BangBang]]
deps = ["Compat", "ConstructionBase", "Future", "InitialValues", "LinearAlgebra", "Requires", "Setfield", "Tables", "ZygoteRules"]
git-tree-sha1 = "d53b1eaefd48e233545d21f5b764c8ee54df4a09"
@@ -86,6 +91,12 @@ git-tree-sha1 = "d3d0a4e0d5bc03a6c97f4d249c8a471fc20a2f33"
uuid = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
version = "0.9.28"
+[[CodecZlib]]
+deps = ["TranscodingStreams", "Zlib_jll"]
+git-tree-sha1 = "ded953804d019afa9a3f98981d99b33e3db7b6da"
+uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
+version = "0.7.0"
+
[[ColorSchemes]]
deps = ["ColorTypes", "Colors", "FixedPointNumbers", "Random", "StaticArrays"]
git-tree-sha1 = "3141757b5832ee7a0386db87997ee5a23ff20f4d"
@@ -137,8 +148,8 @@ uuid = "d38c429a-6771-53c6-b99e-75d170b6e991"
version = "0.5.7"
[[CovidAlertVaccinationModel]]
-deps = ["BenchmarkTools", "CSV", "DataFrames", "Dates", "DelimitedFiles", "Distributions", "ImportAll", "Intervals", "LabelledArrays", "LightGraphs", "NamedTupleTools", "NetworkLayout", "Pipe", "Plots", "Random", "RandomNumbers", "StatsBase", "ThreadsX", "UnPack"]
-path = "../CovidABM"
+deps = ["BenchmarkTools", "CSV", "DataFrames", "Dates", "DelimitedFiles", "Distributions", "ImportAll", "Intervals", "LabelledArrays", "LightGraphs", "NamedTupleTools", "NetworkLayout", "Pipe", "Plots", "Random", "RandomNumbers", "StatsBase", "ThreadsX", "UnPack", "ZeroWeightedDistributions"]
+path = "../CovidAlertVaccinationModel"
uuid = "9260c4ec-b5cf-4bc2-ad29-e1d23bf2bd6f"
version = "0.1.0"
@@ -231,6 +242,12 @@ git-tree-sha1 = "3cc57ad0a213808473eafef4845a74766242e05f"
uuid = "b22a6f82-2f65-5046-a5b2-351ab43fb4e5"
version = "4.3.1+4"
+[[FilePathsBase]]
+deps = ["Dates", "Mmap", "Printf", "Test", "UUIDs"]
+git-tree-sha1 = "36cf9f6b91e638bb95b16a11186287b3f616414a"
+uuid = "48062228-2e41-5def-b9a4-89aafe57970f"
+version = "0.9.9"
+
[[FillArrays]]
deps = ["LinearAlgebra", "Random", "SparseArrays"]
git-tree-sha1 = "50eabdace27aa27b143f65b65e762bb0112a7708"
@@ -388,6 +405,12 @@ git-tree-sha1 = "a431f5f2ca3f4feef3bd7a5e94b8b8d4f2f647a0"
uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
version = "1.2.0"
+[[JLSO]]
+deps = ["BSON", "CodecZlib", "FilePathsBase", "Memento", "Pkg", "Serialization"]
+git-tree-sha1 = "85124b548bf4c2bb59284d353aa09ffc224d761f"
+uuid = "9da8a3cd-07a3-59c0-a743-3fdc52c30d11"
+version = "2.4.0"
+
[[JSON]]
deps = ["Dates", "Mmap", "Parsers", "Unicode"]
git-tree-sha1 = "81690084b6198a2e1da36fcfda16eeca9f9f24e4"
@@ -558,6 +581,12 @@ git-tree-sha1 = "e498ddeee6f9fdb4551ce855a46f54dbd900245f"
uuid = "442fdcdd-2543-5da2-b0f3-8c86c306513e"
version = "0.3.1"
+[[Memento]]
+deps = ["Dates", "Distributed", "JSON", "Serialization", "Sockets", "Syslogs", "Test", "TimeZones", "UUIDs"]
+git-tree-sha1 = "d6dfb54d7e8a9b4a2b1773acf7275a4f607906b2"
+uuid = "f28f55f0-a522-5efc-85c2-fe41dfb9b2d9"
+version = "1.1.2"
+
[[MicroCollections]]
deps = ["BangBang", "Setfield"]
git-tree-sha1 = "e991b6a9d38091c4a0d7cd051fcb57c05f98ac03"
@@ -896,6 +925,12 @@ version = "1.2.3"
deps = ["Libdl", "LinearAlgebra", "Serialization", "SparseArrays"]
uuid = "4607b0f0-06f3-5cda-b6b1-a6196a1729e9"
+[[Syslogs]]
+deps = ["Printf", "Sockets"]
+git-tree-sha1 = "46badfcc7c6e74535cc7d833a91f4ac4f805f86d"
+uuid = "cea106d9-e007-5e6c-ad93-58fe2094e9c4"
+version = "0.3.0"
+
[[TOML]]
deps = ["Dates"]
uuid = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
@@ -938,6 +973,12 @@ git-tree-sha1 = "4ba8a9579a243400db412b50300cd61d7447e583"
uuid = "f269a46b-ccf7-5d73-abea-4c690281aa53"
version = "1.5.3"
+[[TranscodingStreams]]
+deps = ["Random", "Test"]
+git-tree-sha1 = "7c53c35547de1c5b9d46a4797cf6d8253807108c"
+uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
+version = "0.9.5"
+
[[Transducers]]
deps = ["ArgCheck", "BangBang", "CompositionsBase", "DefineSingletons", "Distributed", "InitialValues", "Logging", "Markdown", "MicroCollections", "Requires", "Setfield", "SplittablesBase", "Tables"]
git-tree-sha1 = "9550eba57ebc2f7677c4c946aaca56e149ca73ff"
@@ -1117,6 +1158,12 @@ git-tree-sha1 = "79c31e7844f6ecf779705fbc12146eb190b7d845"
uuid = "c5fb5394-a638-5e4d-96e5-b29de1b5cf10"
version = "1.4.0+3"
+[[ZeroWeightedDistributions]]
+deps = ["Distributions", "Random"]
+path = "../ZeroWeightedDistributions"
+uuid = "24733ad3-391a-4e41-8839-c7177de7dea4"
+version = "0.1.0"
+
[[Zlib_jll]]
deps = ["Libdl"]
uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
diff --git a/IntervalsModel/Project.toml b/IntervalsModel/Project.toml
index dadafe079fa2edff18f47dbab5d30acb5657a22b..58ade50c253cbfd3ccc4dc94a0ce5c11a6aca850 100644
--- a/IntervalsModel/Project.toml
+++ b/IntervalsModel/Project.toml
@@ -10,6 +10,7 @@ CovidAlertVaccinationModel = "9260c4ec-b5cf-4bc2-ad29-e1d23bf2bd6f"
DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
Intervals = "d8418881-c3e1-53bb-8760-2df7ec849ed5"
+JLSO = "9da8a3cd-07a3-59c0-a743-3fdc52c30d11"
KissABC = "9c9dad79-530a-4643-a18b-2704674d4108"
ModularIntervals = "1e07f51d-1de3-4a1c-a782-ac336877d585"
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
diff --git a/IntervalsModel/simulation_data/ws.dat b/IntervalsModel/simulation_data/ws.dat
new file mode 100644
index 0000000000000000000000000000000000000000..22d0e133575f32da7591c998333ffd5381a12531
Binary files /dev/null and b/IntervalsModel/simulation_data/ws.dat differ
diff --git a/IntervalsModel/src/IntervalsModel.jl b/IntervalsModel/src/IntervalsModel.jl
index 8d1fa4f038a449b56aa4b2ec8eebd60020cb9c3a..f9e1e7c25bd9fc1ab7642efdf44b78b22393a466 100644
--- a/IntervalsModel/src/IntervalsModel.jl
+++ b/IntervalsModel/src/IntervalsModel.jl
@@ -7,37 +7,76 @@ using RandomNumbers.Xorshifts
using StatsBase
using Distributions
using CovidAlertVaccinationModel
+using ZeroWeightedDistributions
const PACKAGE_FOLDER = dirname(dirname(pathof(IntervalsModel)))
-const HHYMO = DataFrame(CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/HH/HHYMO.csv"))
-const rng = Xoroshiro128Plus()
+
+using Serialization
+
+const rng = Xoroshiro128Plus(1)
const YOUNG, MIDDLE,OLD = 1,2,3
-const cnst = (
- # Set the underlying parameters for the intervals model
- Sparam = [60,12],
- # Set parameters for intervals sample and subpopulation size
- numsamples = 100,
- subsize = size(HHYMO)[1],
- durmax = 144,
- # Swap age brackets for numbers
- swap = Dict("Y" => YOUNG, "M" => MIDDLE, "O" => OLD),
- # Total weight in survey
- Wghttotal = sum(HHYMO[:,"WGHT_PER"]),
+const durmax = 144
- MUbounds = (6,12*6),
- SIGMAbounds = (1,48),
- ws_distributions = CovidAlertVaccinationModel.initial_workschool_mixing_matrix,
- rest_distributions = CovidAlertVaccinationModel.initial_rest_mixing_matrix
-)
+include("interval_overlap_sampling.jl")
+include("utils.jl")
+include("hh_durations_model.jl")
+include("ws_durations_model.jl")
+include("plotting_functions.jl")
-include("data.jl")
+using KissABC
+using BenchmarkTools
+using JLSO
+using Plots
-const dat = make_dat_array() #assign a constant data array
+const μ_bounds = (6,12*6)
+const σ_bounds = (1,48)
+const α_bounds = (0.0,1.0)
+
+function do_hh(particles)
+ dists = [
+ Normal,
+ Poisson,
+ ]
+ bounds_list = [
+ vcat([μ_bounds for i = 1:6], [σ_bounds for i = 1:6]),
+ vcat([μ_bounds for i = 1:6])
+ ]
+ bayesian_estimate("hh",err_hh,dists,bounds_list,particles)
+end
+
+function do_ws(particles)
+ dists = [
+ ZWDist{Normal},
+ ZWDist{Poisson},
+ ]
+
+ # Set parameter bounds for fitting
+ bounds_list = [
+ vcat([α_bounds for i = 1:6],[μ_bounds for i = 1:6], [σ_bounds for i = 1:6]),
+ vcat([α_bounds for i = 1:6],[μ_bounds for i = 1:6])
+ ]
+ display(bounds_list[1])
+ bayesian_estimate("ws",err_ws,dists,bounds_list,particles)
+
+end
+
+function bayesian_estimate(fname,err_func,dists,bounds_list,particles)
+ data_pairs = map(zip(dists,bounds_list)) do (dist,bounds)
+ init = [b[1] for b in bounds]
+ priors = Factored([Uniform(l,u) for (l,u) in bounds]...) #assume uniform priors
+
+ @btime err_ws($init,$dist) #compute benchmark of the error function, not rly necessary
+
+ out = smc(priors,p -> err_func(p, dist), verbose=true, nparticles=particles, alpha=0.95, parallel = true) #apply sequential monte carlo with 200 particles
+
+ return dist => out
+ end |> Dict
+ serialize(joinpath(PACKAGE_FOLDER,"simulation_data","$fname.dat"),data_pairs)
+end
+function plot_estimates(fname)
+
+end
-include("interval_overlap_sampling.jl")
-include("hh_durations_model.jl")
-include("bayesian_estimation.jl")
-include("plots.jl")
end # module
\ No newline at end of file
diff --git a/IntervalsModel/src/bayesian_estimation.jl b/IntervalsModel/src/bayesian_estimation.jl
deleted file mode 100644
index 0df0dd85a8a2cfb0ed55e9fc75b5b9a0866c6258..0000000000000000000000000000000000000000
--- a/IntervalsModel/src/bayesian_estimation.jl
+++ /dev/null
@@ -1,28 +0,0 @@
-
-
-using KissABC
-using BenchmarkTools
-using Serialization
-using Plots
-function bayesian_estimate_hh()
-
-# Set parameter bounds for fitting
- BoundsNORM = vcat([cnst.MUbounds for i = 1:6], [cnst.SIGMAbounds for i = 1:6])
-
- norm_init = vcat([cnst.MUbounds[1] for i = 1:6], [cnst.SIGMAbounds[1] for i = 1:6])
- BoundsPOIS = [cnst.MUbounds for i in 1:6]
- pois_init = [cnst.MUbounds[1] for i = 1:6]
-
- priors_norm = Factored([Uniform(l,u) for (l,u) in BoundsNORM]...) #assume uniform priors
- # @btime err_poisson($pois_init) #compute benchmark of the error function
-
-
- out_norm = smc(priors_norm,err_norm, verbose=true, nparticles=2000, alpha=0.95, parallel = true) #apply sequential monte carlo with 200 particles
- serialize("norm.dat",out_norm) #save output
-
-
- priors_pois = Factored([Uniform(l,u) for (l,u) in BoundsPOIS]...)
- out_pois = smc(priors_pois,err_poisson, verbose=true, nparticles=2000, alpha=0.95, parallel = true)#apply sequential monte carlo with 200 particles
-
- serialize("pois.dat",out_pois) #save output
-end
\ No newline at end of file
diff --git a/IntervalsModel/src/data.jl b/IntervalsModel/src/data.jl
deleted file mode 100644
index 9e9f3273b05b037a52ff344fdf7b96637727cd46..0000000000000000000000000000000000000000
--- a/IntervalsModel/src/data.jl
+++ /dev/null
@@ -1,24 +0,0 @@
-
-# This function applies pre-processing to the HHYMO data file, and splits it into a namedtuple, which should be faster to index.
-# In particular, we avoid having to modify any strings in the error function.
-function make_dat_array()
- durs = hcat(
- Int.(HHYMO[!,"YDUR"*string(cnst.Sparam[2])]),
- Int.(HHYMO[!,"MDUR"*string(cnst.Sparam[2])]),
- Int.(HHYMO[!,"ODUR"*string(cnst.Sparam[2])]),
- )
- nums = hcat(
- Int.(HHYMO[!,"YNUM"]),
- Int.(HHYMO[!,"MNUM"]),
- Int.(HHYMO[!,"ONUM"]),
- )
-
- WGHT = Weights(HHYMO[!,"WGHT_PER"]./cnst.Wghttotal)
- AGERESP = map(r -> cnst.swap[r],HHYMO[!,"AGERESP"])
- return (;
- nums,
- durs,
- WGHT,
- AGERESP
- )
-end
diff --git a/IntervalsModel/src/hh_durations_model.jl b/IntervalsModel/src/hh_durations_model.jl
index 0f17e1e8fab525b8de2dcf83f7bfa69fe0edfa6c..3200cb1bcc7c2010dcc25d1e593d55d9cccfa215 100644
--- a/IntervalsModel/src/hh_durations_model.jl
+++ b/IntervalsModel/src/hh_durations_model.jl
@@ -1,52 +1,61 @@
-#error function for Normal distributions
-function err_norm(params)
- μ = as_symmetric_matrix(params[1:6])
- σ = as_symmetric_matrix(params[7:12])
-
- # this line is commented out, in we want to go back to sampling subsets of the data
- # this also applies to the @view lines
- # row_ids = sample(rng,1:length(dat.WGHT), dat.WGHT,cnst.subsize)
- age_dists = [Normal(μ[i,j],σ[i,j]) for i in YOUNG:OLD, j in YOUNG:OLD]
- duration_subarray = dat.durs#@view dat.durs[row_ids,:]
- num_contacts_subarray = dat.nums#@view dat.nums[row_ids,:]
-
- # display(num_contacts_subarray)
- AGERESP = dat.AGERESP #@view dat.AGERESP[row_ids]
- errsum = 0
- @inbounds for i = 1:cnst.subsize
- age_sample = AGERESP[i]
- @inbounds for age_j in YOUNG:OLD #for a given age_sample loop over possible contact ages
- running_sum = 0
- durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],num_contacts_subarray[i,age_j])) .% 144
- expdur = tot_dur_sample(cnst.numsamples,cnst.Sparam,durs)
- errsum += (expdur/cnst.numsamples - duration_subarray[i,age_j])^2 #compute total
- end
- end
- return errsum/cnst.subsize #this division not actually necessary
+const HHYMO = DataFrame(CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/HH/HHYMO.csv"))
+
+# This function applies pre-processing to the HHYMO data file, and splits it into a namedtuple, which should be faster to index.
+# In particular, we avoid having to modify any strings in the error function.
+
+const cnst_hh = (
+ # Set the underlying parameters for the intervals model
+ Sparam = [60,12],
+ # Set parameters for intervals sample and subpopulation size
+ numsamples = 100,
+ subsize = size(HHYMO)[1],
+ # Swap age brackets for numbers
+ swap = Dict("Y" => YOUNG, "M" => MIDDLE, "O" => OLD),
+ # Total weight in survey
+ Wghttotal = sum(HHYMO[:,"WGHT_PER"]),
+)
+function make_dat_array()
+ durs = hcat(
+ Int.(HHYMO[!,"YDUR"*string(cnst_hh.Sparam[2])]),
+ Int.(HHYMO[!,"MDUR"*string(cnst_hh.Sparam[2])]),
+ Int.(HHYMO[!,"ODUR"*string(cnst_hh.Sparam[2])]),
+ )
+ nums = hcat(
+ Int.(HHYMO[!,"YNUM"]),
+ Int.(HHYMO[!,"MNUM"]),
+ Int.(HHYMO[!,"ONUM"]),
+ )
+
+ WGHT = Weights(HHYMO[!,"WGHT_PER"]./cnst_hh.Wghttotal)
+ AGERESP = map(r -> cnst_hh.swap[r],HHYMO[!,"AGERESP"])
+ return (;
+ nums,
+ durs,
+ WGHT,
+ AGERESP
+ )
end
+const dat = make_dat_array() #assign a constant data array
-#error function for poisson distributions
-function err_poisson(params) #error function for poisson
- μ = as_symmetric_matrix(params)
- # row_ids = sample(rng,1:length(dat.WGHT), dat.WGHT,cnst.subsize)
- age_dists = [Poisson(μ[i,j]) for i in YOUNG:OLD, j in YOUNG:OLD]
- duration_subarray = dat.durs#@view dat.durs[row_ids,:]
- num_contacts_subarray = dat.nums#@view dat.nums[row_ids,:]
+#error function for Normal distributions
+function err_hh(p,dist)
- # display(num_contacts_subarray)
- AGERESP = dat.AGERESP #@view dat.AGERESP[row_ids]
+ params = get_params(dist,p)
+ age_dists = [dist(params[i,j]) for i in YOUNG:OLD, j in YOUNG:OLD]
+ duration_subarray = dat.durs
+ num_contacts_subarray = dat.nums
+ AGERESP = dat.AGERESP
errsum = 0
@inbounds for i = 1:cnst.subsize
age_sample = AGERESP[i]
- @inbounds for age_j in YOUNG:OLD
- running_sum = 0
+ @inbounds for age_j in YOUNG:OLD #for a given age_sample loop over possible contact ages
durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],num_contacts_subarray[i,age_j])) .% 144
- expdur = tot_dur_sample(cnst.numsamples,cnst.Sparam,durs)
- errsum += (expdur/cnst.numsamples - duration_subarray[i,age_j])^2
+ expdur = tot_dur_sample(cnst_hh.numsamples,cnst_hh.Sparam,durs)
+ errsum += (expdur/cnst_hh.numsamples - duration_subarray[i,age_j])^2 #compute total
end
end
- return errsum/cnst.subsize
+ return errsum
end
\ No newline at end of file
diff --git a/IntervalsModel/src/interval_overlap_sampling.jl b/IntervalsModel/src/interval_overlap_sampling.jl
index a137e9111fb1b0c2b6be893f77b0f5e6a7119ea9..18227477f2a414c0b7a57121c200fca8ef99f425 100644
--- a/IntervalsModel/src/interval_overlap_sampling.jl
+++ b/IntervalsModel/src/interval_overlap_sampling.jl
@@ -2,7 +2,7 @@
function coverage!(cov,S_j,E_j)
if E_j < S_j
push!(cov,Interval(0,E_j))
- push!(cov,Interval(S_j,cnst.durmax))
+ push!(cov,Interval(S_j,durmax))
else
push!(cov,Interval(S_j,E_j))
end
@@ -22,8 +22,8 @@ function tot_dur_sample(n, dist,durlist)
@inbounds for i in 1:n
empty!(int_list)
@inbounds for j in 1:numcontact
- S_j = start_matrix[j,i] % cnst.durmax
- E_j = (S_j + durlist[j]) % cnst.durmax
+ S_j = start_matrix[j,i] % durmax
+ E_j = (S_j + durlist[j]) % durmax
coverage!(int_list,S_j,E_j)
end
union!(int_list)
@@ -31,6 +31,27 @@ function tot_dur_sample(n, dist,durlist)
end
return total_dur
end
+function tot_dur_sample!(sample_list, dist,durlist)
+ if isempty(durlist)
+ sample_list .= 0.0
+ return
+ end
+ numcontact = length(durlist)
+ n = length(sample_list)
+ int_list = Vector{Interval{Int,Closed,Closed}}()
+ sizehint!(int_list,numcontact*2)
+ start_matrix = trunc.(Int,(rand(rng,dist,(numcontact,n))))
+ for i in 1:n
+ empty!(int_list)
+ for j in 1:numcontact
+ S_j = start_matrix[j,i] % durmax
+ E_j = (S_j + durlist[j]) % durmax
+ coverage!(int_list,S_j,E_j)
+ end
+ union!(int_list)
+ sample_list[i] = mapreduce(Intervals.span,+,int_list)
+ end
+end
function as_symmetric_matrix(l) #turn a vector of length 6, l, into a symmetric 3x3 matrix, probably a nicer way to do this exists
diff --git a/IntervalsModel/src/plots.jl b/IntervalsModel/src/plotting_functions.jl
similarity index 53%
rename from IntervalsModel/src/plots.jl
rename to IntervalsModel/src/plotting_functions.jl
index 347989ca4b5400735f954c4acf2012d621c65128..978f5a01e253b2917d51ec3ebd4055b9eaae0764 100644
--- a/IntervalsModel/src/plots.jl
+++ b/IntervalsModel/src/plotting_functions.jl
@@ -1,26 +1,10 @@
-
-function plot_estimates()
-
- estimate = deserialize("norm.dat")
- p_list = []
-
- for i in 1:length(estimate.P)
- a = stephist(
- estimate.P[i].particles;
- normalize = true,
- title = i <=6 ? "μ_$i" : "σ_$i"
- )
- push!(p_list,a)
- end
- p = plot(p_list...)
- savefig(p,"norm.png")
-
+function plot_dists(fname,dist_constructor,data)
μ_estimate_as_array = as_symmetric_matrix(estimate.P[1:6])
σ_estimate_as_array = as_symmetric_matrix(estimate.P[7:12])
p_matrix = map(x -> plot(),σ_estimate_as_array)
for i in YOUNG:OLD, j in YOUNG:OLD
- dist = Normal.(μ_estimate_as_array[i,j].particles,σ_estimate_as_array[i,j].particles)
+ dist = dist_constructor.(μ_estimate_as_array[i,j].particles,σ_estimate_as_array[i,j].particles)
data = [pdf.(dist,i) for i in 0.0:144.0]
mean_dat = median.(data)
@@ -31,12 +15,26 @@ function plot_estimates()
end
plot!(p_matrix[end,1]; legend = true)
p = plot(p_matrix..., size = (600,400))
- savefig(p,"norm_dists.pdf")
-
+ savefig(p,"$fname.pdf")
+end
+function plot_posteriors(fname,parameter_names,data)
+ for i in 1:length(data.P)
+ a = stephist(
+ data.P[i].particles;
+ normalize = true,
+ title = i <=6 ? "μ_$i" : "σ_$i"
+ )
+ push!(p_list,a)
+ end
+ p = plot(p_list...)
+ savefig(p,"$norm.png")
+end
+function plot_estimates_hh()
+ estimate = deserialize("norm.dat")
+ p_list = []
- estimate = deserialize("pois.dat")
p_list = []
for i in 1:length(estimate.P)
a = stephist(
@@ -68,4 +66,40 @@ function plot_estimates()
+end
+function plot_estimates_ws()
+ estimate = deserialize("norm_ws.dat")
+ p_list = []
+ titles = vcat(
+ ["\\alpha_$i" for i in 1:6],
+ ["\\mu_$i" for i in 1:6],
+ ["\\sigma_$i" for i in 1:6],
+ )
+ for i in 1:length(estimate.P)
+ a = stephist(
+ estimate.P[i].particles;
+ normalize = true,
+ title = titles[i],
+ legend = false
+ )
+ push!(p_list,a)
+ end
+ p = plot(p_list...; size = (1000,800), dpi = 300)
+ savefig(p,"norm_ws.png")
+
+ p_estimate_as_arrays = zip([as_symmetric_matrix(estimate.P[i:i+5]) for i in 1:6:length(estimate.P)]...) |> collect
+
+ p_matrix = map(x -> plot(),p_estimate_as_arrays)
+ for i in YOUNG:OLD, j in YOUNG:OLD
+ particles = map(x-> x.particles,p_estimate_as_arrays[i,j]) |> t->zip(t...) |> collect
+ dists = map(x-> ZWDist(x[1],Normal(x[2],x[3])), particles)
+ data = [pdf.(dists,i) for i in 0.0:144.0]
+ mean_dat = median.(data)
+ err_down = quantile.(data,0.05)
+ err_up = quantile.(data,0.95)
+ p_matrix[i,j] = plot(0:144,mean_dat; ribbon = ( mean_dat .- err_down,err_up .- mean_dat),legend = false)
+ end
+ plot!(p_matrix[end,1]; legend = true)
+ p = plot(p_matrix..., size = (600,400))
+ savefig(p,"norm_dists_ws.pdf")
end
\ No newline at end of file
diff --git a/IntervalsModel/src/utils.jl b/IntervalsModel/src/utils.jl
new file mode 100644
index 0000000000000000000000000000000000000000..60278e0caf2d4a35762f69dad8aca524f25ba90c
--- /dev/null
+++ b/IntervalsModel/src/utils.jl
@@ -0,0 +1,9 @@
+
+
+nparams(d::Type{T}) where T<:Sampleable = length(fieldnames(d))
+nparams(::Type{ZWDist{T,S}}) where {T<:Sampleable,S} = 1+nparams(T)
+
+function get_params(params)
+ p_list = [as_symmetric_matrix(params[i:i+5]) for i = 1:6:length(params)]
+ return zip(p_list...) |> collect
+end
\ No newline at end of file
diff --git a/IntervalsModel/src/ws_durations_model.jl b/IntervalsModel/src/ws_durations_model.jl
index 12eb412043fff0d8e17d18fb44b75cdeed7e492c..735a8f2a7e2c109ad1ec4110ef41e4ed5810fa82 100644
--- a/IntervalsModel/src/ws_durations_model.jl
+++ b/IntervalsModel/src/ws_durations_model.jl
@@ -1,52 +1,36 @@
-#error function for Normal distributions
-function err_norm(params)
- μ = as_symmetric_matrix(params[1:6])
- σ = as_symmetric_matrix(params[7:12])
+using HypothesisTests
+const ws_data = (
+ Y = CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/WS/WorkschoolDataY.csv") |> Tables.matrix |> x -> dropdims(x;dims = 2),
+ M = CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/WS/WorkschoolDataM.csv") |> Tables.matrix |> x -> dropdims(x;dims = 2),
+ O = CSV.File("$PACKAGE_FOLDER/network-data/Timeuse/WS/WorkschoolDataO.csv") |> Tables.matrix |> x -> dropdims(x;dims = 2),
+)
+const comparison_samples = 10_000
- # this line is commented out, if we want to go back to sampling subsets of the data
- # this also applies to the @view lines
- # row_ids = sample(rng,1:length(dat.WGHT), dat.WGHT,cnst.subsize)
- age_dists = [Normal(μ[i,j],σ[i,j]) for i in YOUNG:OLD, j in YOUNG:OLD]
- duration_subarray = dat.durs#@view dat.durs[row_ids,:]
- num_contacts_subarray = dat.nums#@view dat.nums[row_ids,:]
+ws_distributions = CovidAlertVaccinationModel.initial_workschool_mixing_matrix
- # display(num_contacts_subarray)
- AGERESP = dat.AGERESP #@view dat.AGERESP[row_ids]
+#error function
+function err_ws(p,dist)
+ params = get_params(p)
+ neighourhoods = rand.(rng,ws_distributions)
+ age_dists = [dist(params[i,j]...) for i in YOUNG:OLD, j in YOUNG:OLD]
+ sample_list = zeros(comparison_samples)
+ ws_samples = (
+ Y = sample(rng, ws_data.Y, comparison_samples),
+ M = sample(rng, ws_data.M, comparison_samples),
+ O = sample(rng, ws_data.O, comparison_samples),
+ )
errsum = 0
- @inbounds for i = 1:cnst.subsize
- age_sample = AGERESP[i]
- @inbounds for age_j in YOUNG:OLD #for a given age_sample loop over possible contact ages
- running_sum = 0
- durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],num_contacts_subarray[i,age_j])) .% 144
- expdur = tot_dur_sample(cnst.numsamples,cnst.Sparam,durs)
- errsum += (expdur/cnst.numsamples - duration_subarray[i,age_j])^2 #compute total
+ for age_sample in YOUNG:OLD
+ for age_j in YOUNG:OLD #for a given age_sample loop over possible contact ages
+ if neighourhoods[age_sample,age_j] > 0
+ durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],neighourhoods[age_sample,age_j])) .% durmax
+ # display(durs)
+ tot_dur_sample!(sample_list,cnst_hh.Sparam,durs)
+ err = 1 - pvalue(KSampleADTest(ws_samples[age_sample],sample_list)) #need to maximize probability of null hypothesis, not rly valid but everyone does it so idk
+ errsum += err
+ end
end
end
- return errsum/cnst.subsize #this division not actually necessary
-end
-
-
-#error function for poisson distributions
-function err_poisson(params) #error function for poisson
- μ = as_symmetric_matrix(params)
- # row_ids = sample(rng,1:length(dat.WGHT), dat.WGHT,cnst.subsize)
- age_dists = [Poisson(μ[i,j]) for i in YOUNG:OLD, j in YOUNG:OLD]
- duration_subarray = dat.durs#@view dat.durs[row_ids,:]
- num_contacts_subarray = dat.nums#@view dat.nums[row_ids,:]
-
- # display(num_contacts_subarray)
- AGERESP = dat.AGERESP #@view dat.AGERESP[row_ids]
-
- errsum = 0
- @inbounds for i = 1:cnst.subsize
- age_sample = AGERESP[i]
- @inbounds for age_j in YOUNG:OLD
- running_sum = 0
- durs = trunc.(Int,rand(rng,age_dists[age_sample,age_j],num_contacts_subarray[i,age_j])) .% 144
- expdur = tot_dur_sample(cnst.numsamples,cnst.Sparam,durs)
- errsum += (expdur/cnst.numsamples - duration_subarray[i,age_j])^2
- end
- end
- return errsum/cnst.subsize
+ return errsum
end
\ No newline at end of file
diff --git a/README.md b/README.md
index 61f5f7feaca66fe3fe90b7096129edda9bf6cf0d..2acece3d5801c15d6f0e5ca9dc33e57aef0181e4 100644
--- a/README.md
+++ b/README.md
@@ -1,13 +1,37 @@
# CovidAlertVaccinationModel
-This repo contains two packages:
+This repo contains three packages:
-* CovidAlertVaccinationModel (in CovidABM)
+* CovidAlertVaccinationModel
* IntervalsModel
-The former implements the ABM, and the latter computes the time-distributions. The latter model depends on the former model because the mixing distributions are defined there, although really I guess it should be the inverse.
+* ZeroWeightedDistributions
+The former implements the ABM, and the second computes the time-distributions. The latter model depends on the former model because the mixing distributions are defined there, although really I guess it should be the inverse. The last package, ZeroWeightedDistributions, implements a helpful type ZWDist{D} representing a random variable of distribution D with added weight at zero.
+Note that you need the Julia-1.6 beta to compile this project successfully. This is because the mixing distributions hit a compiler bug. I will try to find a workaround for when we run this on a cluster.
-Note that you need the Julia-1.6 beta to compile this project successfully. This is because the mixing distributions hit a compiler bug.
+
+# Installation
+
+First, clone this repository and open the Julia-1.6 beta in the active directory
+```
+git clone https://git.uwaterloo.ca/pjentsch/covidalertabm.git
+cd covidalertabm
+julia -t auto
+```
+the `-t auto` option starts Julia with as many threads as you have physical CPU cores. You can pass this option a number if you prefer to use fewer threads.
+
+This should bring you to a julia REPL. Typing `]` at this repl will change your prompt to `pkg>`.
+
+Then add these packages to your main environment:
+```
+dev ./CovidAlertVaccinationModel
+dev ./IntervalsModel
+dev ./ZeroWeightedDistributions
+```
+
+We need to `dev` each of the above packages because they all share one git repo, and Julia's package manager doesn't seem to like that very much. I suppose we could split them into separate repos in the future.
+
+This package only tested on x86-64 Linux. It should work everywhere that Julia does though.
\ No newline at end of file
diff --git a/ZeroWeightedDistributions/.github/workflows/CompatHelper.yml b/ZeroWeightedDistributions/.github/workflows/CompatHelper.yml
new file mode 100644
index 0000000000000000000000000000000000000000..cba9134c670f0708cf98c92f7fdef055a6c7f5d3
--- /dev/null
+++ b/ZeroWeightedDistributions/.github/workflows/CompatHelper.yml
@@ -0,0 +1,16 @@
+name: CompatHelper
+on:
+ schedule:
+ - cron: 0 0 * * *
+ workflow_dispatch:
+jobs:
+ CompatHelper:
+ runs-on: ubuntu-latest
+ steps:
+ - name: Pkg.add("CompatHelper")
+ run: julia -e 'using Pkg; Pkg.add("CompatHelper")'
+ - name: CompatHelper.main()
+ env:
+ GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+ COMPATHELPER_PRIV: ${{ secrets.DOCUMENTER_KEY }}
+ run: julia -e 'using CompatHelper; CompatHelper.main()'
diff --git a/ZeroWeightedDistributions/.github/workflows/TagBot.yml b/ZeroWeightedDistributions/.github/workflows/TagBot.yml
new file mode 100644
index 0000000000000000000000000000000000000000..f49313b662013f43aac7de2c738e1163a9715ff4
--- /dev/null
+++ b/ZeroWeightedDistributions/.github/workflows/TagBot.yml
@@ -0,0 +1,15 @@
+name: TagBot
+on:
+ issue_comment:
+ types:
+ - created
+ workflow_dispatch:
+jobs:
+ TagBot:
+ if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
+ runs-on: ubuntu-latest
+ steps:
+ - uses: JuliaRegistries/TagBot@v1
+ with:
+ token: ${{ secrets.GITHUB_TOKEN }}
+ ssh: ${{ secrets.DOCUMENTER_KEY }}
diff --git a/ZeroWeightedDistributions/.gitignore b/ZeroWeightedDistributions/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..b067eddee4ee0afc7c0ea1304b68c5af07c3d5ca
--- /dev/null
+++ b/ZeroWeightedDistributions/.gitignore
@@ -0,0 +1 @@
+/Manifest.toml
diff --git a/ZeroWeightedDistributions/LICENSE b/ZeroWeightedDistributions/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..e93f61e1483823cc9acc50775972ab044cd1ebf6
--- /dev/null
+++ b/ZeroWeightedDistributions/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2021 pjentsch <pjentsch@uwaterloo.ca> and contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/ZeroWeightedDistributions/Project.toml b/ZeroWeightedDistributions/Project.toml
new file mode 100644
index 0000000000000000000000000000000000000000..34fdd9f81402bf253da18a900d2f84e2e0981b42
--- /dev/null
+++ b/ZeroWeightedDistributions/Project.toml
@@ -0,0 +1,17 @@
+name = "ZeroWeightedDistributions"
+uuid = "24733ad3-391a-4e41-8839-c7177de7dea4"
+authors = ["pjentsch <pjentsch@uwaterloo.ca> and contributors"]
+version = "0.1.0"
+
+[deps]
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+
+[compat]
+julia = "1"
+
+[extras]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["Test"]
diff --git a/ZeroWeightedDistributions/README.md b/ZeroWeightedDistributions/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..240f499ba29a748cf4cf920d1984e4207651b716
--- /dev/null
+++ b/ZeroWeightedDistributions/README.md
@@ -0,0 +1 @@
+# ZeroWeightedDistributions
diff --git a/ZeroWeightedDistributions/src/ZeroWeightedDistributions.jl b/ZeroWeightedDistributions/src/ZeroWeightedDistributions.jl
new file mode 100644
index 0000000000000000000000000000000000000000..8b5b044ecc95e5883dac1a8657fbf0f715e8cb7f
--- /dev/null
+++ b/ZeroWeightedDistributions/src/ZeroWeightedDistributions.jl
@@ -0,0 +1,51 @@
+module ZeroWeightedDistributions
+export ZWDist,rand,rand!
+using Random
+import Base.rand
+import Random.rand!
+using Distributions
+import Distributions.pdf
+
+
+struct ZWDist{BaseDistType <: Sampleable,T} <: Sampleable{Univariate,T}
+ α::Float64
+ base_dist::BaseDistType
+ function ZWDist(α,base_dist::Sampleable{Univariate,S}) where S
+ return new{typeof(base_dist),S}(α,base_dist)
+ end
+ function ZWDist(D::Type{<:Sampleable{Univariate,S}},α,p...) where {S}
+ return new{D,S}(α,D(p...))
+ end
+ function ZWDist{DType}(α,p...) where {S,DType<:Sampleable{Univariate,S}}
+ return new{DType,S}(α,DType(p...))
+ end
+end
+
+function Distributions.pdf(d::ZWDist, x)
+ if x == 0
+ return d.α + (1-d.α)*pdf(d.base_dist,0)
+ else
+ return pdf(d.base_dist,0)
+ end
+end
+
+function Base.rand(rng::AbstractRNG, s::ZWDist{DType,S}, n::Int) where {DType, S}
+ l = Vector{eltype(DType)}(undef,n)
+ Random.rand!(rng,l)
+ l[l .< s.α] .= zero(eltype(DType))
+ Random.rand!(rng,s.base_dist,@view l[l .>= s.α])
+ return l
+end
+
+function Random.rand!(rng::AbstractRNG, s::ZWDist{DType,S}, l::T) where {T<:AbstractVector, DType,S}
+ Random.rand!(rng,l)
+ l[l .< s.α] .= zero(eltype(DType))
+ Random.rand!(rng,s.base_dist,@view l[l .>= s.α])
+ return l
+end
+
+function Base.rand(rng::AbstractRNG, s::ZWDist{DType,S}) where {DType,S}
+ return ifelse(Base.rand(rng) < s.α, zero(eltype(DType)), Base.rand(rng,s.base_dist))
+end
+
+end
diff --git a/ZeroWeightedDistributions/test/runtests.jl b/ZeroWeightedDistributions/test/runtests.jl
new file mode 100644
index 0000000000000000000000000000000000000000..e6cee1d395f081f44f498324483ea04f7c84fb08
--- /dev/null
+++ b/ZeroWeightedDistributions/test/runtests.jl
@@ -0,0 +1,6 @@
+using ZeroWeightedDistributions
+using Test
+
+@testset "ZeroWeightedDistributions.jl" begin
+ # Write your tests here.
+end
diff --git a/norm.dat b/norm.dat
deleted file mode 100644
index 2ddc1225c6b292990c169d01c3b23f659176621a..0000000000000000000000000000000000000000
Binary files a/norm.dat and /dev/null differ
diff --git a/norm.png b/norm.png
deleted file mode 100644
index c393441311b0424b862684ffb5150b63df656bf4..0000000000000000000000000000000000000000
Binary files a/norm.png and /dev/null differ
diff --git a/norm_dists.pdf b/norm_dists.pdf
deleted file mode 100644
index bb383752d90e5bfcd739f8ec148f3bd9edf13701..0000000000000000000000000000000000000000
Binary files a/norm_dists.pdf and /dev/null differ
diff --git a/pois.dat b/pois.dat
deleted file mode 100644
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