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Commit 9a0dcc5f authored by Victor's avatar Victor
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Version 0.2. Changed the structure of agents, to better integrate the... 

Version 0.2. Changed the structure of agents, to better integrate the geotrait. Changes have telescoped to accessor get_geo that now takes t as an argument, and all the functions that are using it.
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Project.toml
View file @ 9a0dcc5f
name = "ABMEv"
uuid = "837ac870-fb52-4b0c-9a0e-030f2f36f5ed"
authors = ["Victor Boussange "]
version = "0.1.8"
version = "0.2.1"
[deps]
Colors = "5ae59095-9a9b-59fe-a467-6f913c188581"
......
examples/gillepsie_discrete_2d.jl
View file @ 9a0dcc5f
using ABMEv,UnPack
cd(@__DIR__)
using Dates
......@@ -16,7 +15,7 @@ K0 = 1000
K(X) = gaussian(X[2],X[1] * a,sigma_K) / nodes
alpha(X,Y) = (X[1] ≈ Y[1]) * gaussian(X[2],Y[2],sigma_a) / K0
NMax = 5000
tend = 3000.
tend = 1.
reflected = true;
dt_saving = 15.
......
src/ABMEv_Agent.jl
View file @ 9a0dcc5f
......@@ -4,6 +4,8 @@ abstract type MixedAgent end
mutable struct Agent{T,U}
# history of traits for geotraits
x_history::Array{U}
# birth time of ancestors
t_history::Array{U,1}
# death rate
d::Float64
#birth rate
......@@ -12,14 +14,14 @@ end
# Constructors
# This constructor should be used when one wants to impose the type of the agent (e.g. Mixed)
Agent{T}(xhist::Array{U}) where {T,U} = Agent{T,U}(reshape(xhist,:,1),0.,1.)
Agent{T}(xhist::Array{U}) where {T,U} = Agent{T,U}(reshape(xhist,:,1),[0.],0.,1.)
# This constructor is used by default
Agent(xhist::Array{U}) where {U <: Number} = Agent{StdAgent}(xhist)
Agent() = Agent(Float64[],0.,1.)
Agent() = Agent(Float64[],0.,0.,1.)
import Base.copy
copy(a::Agent{T,U}) where {T,U} = Agent{T,U}(a.x_history,a.d,a.b)
copy(a::Agent{T,U}) where {T,U} = Agent{T,U}(copy(a.x_history),copy(a.t_history),copy(a.d),copy(a.b))
copy(m::Missing) = missing
"""
......@@ -39,8 +41,14 @@ end
get_xhist(a::Agent,i::Number) = a.x_history[Int(i),:]
get_xhist(a::Agent) = a.x_history
get_x(a::Agent) = a.x_history[:,end]
get_geo(a::Agent) = sum(get_xhist(a,1))
get_x(a::Agent,i::Number) = i > 0 ? a.x_history[Int(i),end] : get_geo(a)
function get_geo(a::Agent{U,T},t::Number) where {U,T}
tarray = vcat(a.t_history[2:end],convert(T,t))
tarray .-= a.t_history
return sum(get_xhist(a,1) .* tarray)
end
# This method can acces geotrait, while the second not
get_x(a::Agent,t::Number,i::Integer) = i > 0 ? a.x_history[Int(i),end] : get_geo(a,t)
get_x(a::Agent,i::Integer) = a.x_history[Int(i),end]
get_d(a::Agent) = a.d
get_b(a::Agent) = a.b
get_fitness(a::Agent) = a.b - a.d
......@@ -48,23 +56,29 @@ get_dim(a::Agent) = size(a.x_history,1)
get_nancestors(a::Agent) = size(a.x_history,2)
"""
get_xarray(world::Array{Agent},trait::Int)
If trait = 0 , we return the geotrait.
Mainly works for WF-type world
Returns trait of every agents of world in the form of an array which dimensions corresponds to the input.
If trait = 0 , we return the geotrait.
Particularly suited for an array world corresponding to a timeseries.
"""
get_xarray(world::Array{T},trait::Int) where {T <: Agent} = trait > 0 ? reshape(hcat(get_x.(world,trait)),size(world,1),size(world,2)) : reshape(hcat(get_geo.(world)),size(world,1),size(world,2))
get_x(world::Array{T},trait::Integer) where {T <: Agent} = trait > 0 ? reshape(hcat(get_x.(world,trait)),size(world,1),size(world,2)) : throw(ErrorException("Not the right method, need `t` as an argument"))
get_x(world::Array{T},t::Number,trait::Integer) where {T <: Agent} = trait > 0 ? reshape(hcat(get_x.(world,trait)),size(world,1),size(world,2)) : reshape(hcat(get_geo.(world,t)),size(world,1),size(world,2))
"""
get_xarray(world::Array{Agent,1})
Returns every traits of every agents of world in the form of an array
If geotrait = true, then a last trait dimension is added, corresponding to geotrait.
"""
function get_xarray(world::Array{T,1},geotrait::Bool=false) where {T <: Agent}
function get_xarray(world::Array{T,1}) where {T <: Agent}
return hcat(get_x.(world)...)
end
function get_xarray(world::Array{T,1},t::Number,geotrait::Bool=false) where {T <: Agent}
xarray = hcat(get_x.(world)...)
if geotrait
xarray = vcat( xarray, get_geo.(world)')
xarray = vcat( xarray, get_geo.(world,t)')
end
return xarray
end
......@@ -80,33 +94,57 @@ If geotrait = true, then a last trait dimension is added, corresponding to geotr
Note that because number of ancestors are different between agents, we return an array which size corresponds to the minimum of agents ancestors,
and return the last generations, dropping the youngest ones
"""
function get_xhist(world::Vector{T},geotrait = false) where {T <: Agent}
function get_xhist(world::Vector{T}) where {T <: Agent}
hist = minimum(get_nancestors.(world))
ntraits = get_dim(first(world));
xhist = zeros(length(world), hist, ntraits + geotrait);
for (i,a) in enumerate(world)
xhist[i,:,1:end-geotrait] = get_xhist(a)[:,end-hist+1:end]';
if geotrait
xhist[i,:,ntraits+geotrait] = cumsum(get_xhist(a,1))[end-hist+1:end]
end
end
return xhist
end
# TODO: This method broken, when one ask for the geotraits
# function get_xhist(world::Vector{T},t::Number,geotrait = false) where {T <: Agent}
# hist = minimum(get_nancestors.(world))
# ntraits = get_dim(first(world));
# xhist = zeros(length(world), hist, ntraits + geotrait);
# for (i,a) in enumerate(world)
# xhist[i,:,1:end-geotrait] = get_xhist(a)[:,end-hist+1:end]';
# if geotrait
# xhist[i,:,ntraits+geotrait] = cumsum(get_xhist(a,1))[end-hist+1:end]
# end
# end
# return xhist
# end
function world2df(world::Array{T,1}) where {T <: Agent}
xx = get_xarray(world)
dfw = DataFrame(:f => get_fitness.(world))
for i in 1:size(xx,1)
dfw[Meta.parse("x$i")] = xx[i,:]
end
if geotrait
dfw[:g] = get_geo.(world)
end
return dfw
end
"""
world2df(world::Array{T,1}; geotrait = false) where {T <: Agent}
world2df(world::Array{T,1},t::Number,geotrait = false) where {T <: Agent}
Converts the array of agent world to a datafram, where each column corresponds to a trait of the
agent, and an extra column captures fitness.
Each row corresponds to an agent
"""
function world2df(world::Array{T,1}; geotrait = false) where {T <: Agent}
function world2df(world::Array{T,1},t::Number,geotrait = false) where {T <: Agent}
xx = get_xarray(world)
dfw = DataFrame(:f => get_fitness.(world))
for i in 1:size(xx,1)
dfw[Meta.parse("x$i")] = xx[i,:]
end
if geotrait
dfw[:g] = get_geo.(world)
dfw[:g] = get_geo.(world,t)
end
return dfw
end
......@@ -114,11 +152,11 @@ end
"""
increment_x!(a::Agent{StdAgent,U},p::Dict)
increment_x!(a::Agent{StdAgent,U},t::U,p::Dict) where U
This function increments agent by random numbers specified in p
ONLY FOR CONTINUOUS DOMAINS
"""
function increment_x!(a::Agent{StdAgent,U},p::Dict) where U
function increment_x!(a::Agent{StdAgent,U},t,p::Dict) where U
tdim = length(p["D"])
reflected = haskey(p,"reflected") ? p["reflected"] : false
if reflected
......@@ -131,21 +169,23 @@ function increment_x!(a::Agent{StdAgent,U},p::Dict) where U
inc = (rand(tdim) < vec(p["mu"])) .* vec(p["D"][:]) .* randn(tdim)
end
a.x_history = hcat(a.x_history, get_x(a) + reshape(inc,:,1));
push!(a.t_history,t)
end
"""
function increment_x!(a::Agent{MixedAgent,U},p::Dict)
function increment_x!(a::Agent{MixedAgent,U},t::U,p::Dict) where U
This function increments first trait of agent with integer values, that are automatically reflected between 1 and p["nodes"].
Other traits are incremented as usual.
TODO : make it work for a graph type landscape, where domain is not a line anymore.
"""
function increment_x!(a::Agent{MixedAgent,U},p::Dict) where U
function increment_x!(a::Agent{MixedAgent,U},t,p::Dict) where U
tdim = length(p["D"])
inc = [round(get_inc_reflected(get_x(a,1),p["D"][1] *randn(),1,p["nodes"]))]
if tdim > 1
inc = vcat(inc,(rand(tdim-1) < p["mu"][2:end]) .* p["D"][2:end] .* randn(tdim-1))
end
a.x_history = hcat(a.x_history, get_x(a) + reshape(inc,:,1));
push!(a.t_history,t)
end
......
src/ABMEv_Gillepsie.jl
View file @ 9a0dcc5f
......@@ -5,9 +5,9 @@
give_birth(a::Agent,p)
Used for Gillepsie setting
"""
function give_birth(a::Agent,p::Dict)
function give_birth(a::Agent,t,p::Dict)
new_a = copy(a)
increment_x!(new_a,p)
increment_x!(new_a,t,p)
return new_a
end
......@@ -62,7 +62,7 @@ function updateWorld_G!(world,p,update_rates!,t)
idx_offspring = findfirst(ismissing,world)
# i_event - N is also the index of the individual to give birth in the world_alive
mum = world[idx_world[i_event-N]]
world[idx_offspring] = give_birth(mum,p)
world[idx_offspring] = give_birth(mum,t+dt,p)
update_afterbirth_std!(world,idx_offspring,p)
end
return dt
......
src/ABMEv_metrics.jl
View file @ 9a0dcc5f
......@@ -53,7 +53,7 @@ If trait > 0, returns the covariance matrix, with first row geotrait and second
"""
function var(world::Array{U,1};trait=1) where U <: Union{Missing,Agent{T}} where T
world = collect(skipmissing(world))
xarray = get_xarray(world,trait)
xarray = get_x(world,trait)
return var(xarray,dims=1)
end
"""
......@@ -64,9 +64,9 @@ If trait > 0, returns the covariance matrix, with first row geotrait and second
# Arguments
"""
function covgeo(world::Array{U,1},trait = 0) where U <: Union{Missing,Agent}
function covgeo(world::Array{U,1},t::Number,trait = 0) where U <: Union{Missing,Agent}
world = collect(skipmissing(world))
xarray = get_geo.(world)
xarray = get_geo.(world,t)
if trait > 0
xstd = reshape(get_x.(world,trait),size(world,1),size(world,2))
xarray = hcat(xarray,xstd)
......
src/ABMEv_plot.jl
View file @ 9a0dcc5f
......@@ -30,15 +30,16 @@ It should correspond to an integer, as it indexes the column to plot
tspan_ar = repeat(p["tspan"],inner = size(world,1))
end
# tspan = Float64.(tspan)
world_sm = collect(skipmissing(world))
tend = p["tspan"][tplot > 0 ? tplot : size(world,2)]
world_sm = clean_world(world)
if "x" in what
d_i = []
for i in 1:size(world,2)
x = get_x.(skipmissing(world[:,i]),trait)
x = get_x.(clean_world(world[:,i]),tend,trait)
append!(d_i,pdf(kde(x),x))
end
@series begin
xarray = get_xarray(world_sm,trait)
xarray = get_xarray(world_sm,tend,trait)
seriestype := :scatter
markercolor := eth_grad_small[d_i ./ maximum(d_i)]
# markercolor := :blue
......@@ -56,7 +57,7 @@ It should correspond to an integer, as it indexes the column to plot
# world should be a one dimensional vector, corresponding to one time step only
if "xs" in what
d_i = []; xt_array = []; x1_array = []
world_df_g = groupby(world2df(collect(skipmissing(world[:, tplot > 0 ? tplot : size(world,2) ])),geotrait=true),:x1)
world_df_g = groupby(world2df(clean_world(world[:, tplot > 0 ? tplot : size(world,2) ]),tend,true),:x1)
for world_df in world_df_g
if trait == 0
x = world_df.g
......@@ -86,8 +87,8 @@ It should correspond to an integer, as it indexes the column to plot
end
if "3dgeo" in what
@series begin
xarray = get_geo.(world_sm)
yarray = get_xarray(world_sm,2)
xarray = get_geo.(world_sm,tspan_ar)
yarray = get_x(world_sm,2)
seriestype := :scatter3d
markercolor := "blue"
markerstrokewidth := 0
......@@ -103,7 +104,7 @@ It should correspond to an integer, as it indexes the column to plot
if "3d" in what
@series begin
xarray = get_xarray(world_sm,1)
yarray = get_xarray(world_sm,2)
yarray = get_x(world_sm,2)
seriestype := :scatter3d
markercolor := "blue"
markerstrokewidth := 0
......
test/gillepsie.jl
View file @ 9a0dcc5f
......@@ -20,7 +20,7 @@ p_default = Dict(
na_init = K0
world0 = new_world_G(na_init,p_default,spread = .01)
worldall,p_default["tspan"] = runWorld_store_G(p_default,world0)
world_alive_test = collect(skipmissing(worldall[:,end]))
world_alive_test = clean_world(worldall[:,end])
# @save "gillepsie_test.jld2" world_alive
@load "gillepsie_test.jld2" world_alive
## Testing
......@@ -31,7 +31,7 @@ world_alive_test = collect(skipmissing(worldall[:,end]))
end
## Comparing simulation
@testset "Matching new vs old results " begin
xarray = get_xarray(world_alive,1);xarray_test = get_xarray(world_alive_test,1);
xarray = get_x(world_alive,1);xarray_test = get_x(world_alive_test,1);
@test xarray ≈ xarray_test
end
......
test/gillepsie_test.jld2
View file @ 9a0dcc5f
No preview for this file type
test/parallel.jl
View file @ 9a0dcc5f
......@@ -31,7 +31,7 @@ agents = [Agent( [1e-2] .* randn(1) .- .5) for i in 1:K0]
# using JLD2
# @save "wrightfisher_test.jld2" worldall p
# @load "wrightfisher_test.jld2" worldall
# xarray = get_xarray(worldall,1); xarray_test = get_xarray(worldall_test,1)
# xarray = get_x(worldall,1); xarray_test = get_x(worldall_test,1)
# @test xarray ≈ xarray_test
test/wrightfisher.jl
View file @ 9a0dcc5f
......@@ -23,7 +23,7 @@ worldall_test,p["tspan"] = runWorld_store_WF(p,agents);
## load to compare simulation
# @save "wrightfisher_test.jld2" worldall p
@load "wrightfisher_test.jld2" worldall
xarray = get_xarray(worldall,1); xarray_test = get_xarray(worldall_test,1)
xarray = get_x(worldall,1); xarray_test = get_x(worldall_test,1)
@testset "Wright Fisher Algorithm" begin
@test xarray ≈ xarray_test
end
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