Added interpolations function in utils.jl. Minor change on world2df, with...

Added interpolations function in utils.jl. Minor change on world2df, with argument `geotrait=false added`. Minor change on plot

src/ABMEv_Agent.jl

@@ -116,7 +116,7 @@ end
 # end
 
 
-function world2df(world::Array{T,1}) where {T <: Agent}
+function world2df(world::Array{T,1},geotrait=false) where {T <: Agent}
     xx = get_xarray(world)
     dfw = DataFrame(:f => get_fitness.(world))
     for i in 1:size(xx,1)

src/ABMEv_plot.jl

@@ -41,6 +41,9 @@ It should correspond to an integer, as it indexes the column to plot
             append!(d_i,pdf(kde(x),x))
         end
         @series begin
+            if length(world_sm) !== length(tspan_ar[:])
+                throw(DimensionMismatch("You want to plot a world with missing data"))
+            end
         xarray = get_x.(world_sm,tspan_ar[:],trait)
             seriestype := :scatter
             markercolor := eth_grad_small[d_i ./ maximum(d_i)]

src/ABMEv_utils.jl

@@ -44,3 +44,53 @@ import Plots:cgrad
 const eth_grad_small = cgrad([colorant"#1F407A", RGB(0.671,0.851,0.914),RGB(1.0,1.0,0.749), RGB(0.992,0.682,0.38),RGB(0.647,0.0,0.149),],[.0,.1])
 # symmetry between red and blue
 const eth_grad_std = cgrad([colorant"#1F407A", RGB(0.671,0.851,0.914),RGB(1.0,1.0,0.749), RGB(0.992,0.682,0.38),RGB(0.647,0.0,0.149),],[.0,1.])
+
+# This is all about interpolations
+using Interpolations
+struct DiversityFunction
+    x
+    y
+    itp
+end
+"""
+    function geomsmooth2D(xa,ya,itp,smooth)
+Return xas,yas,A where A is an interpolated matrix with geometric smooth,
+whose axis are xas, yas
+# ARGS
+`xa` xaxis values, `ya` yaxis values,  `itp` interpolation function, `smooth` smoothing function
+"""
+function geomsmooth2D(xa,ya,itp,smooth)
+    prod(isodd.(smooth)) ? nothing : throw(ArgumentError("smoothing coefficients need to be odd"))
+    idx1 = Int((smooth[1]-1)/2)+1:length(xa)- Int((smooth[1]-1)/2)
+    idx2 = Int((smooth[2]-1)/2)+1:length(ya)- Int((smooth[2]-1)/2)
+    A = [prod(itp.(xa[i-smooth[1] + 1:i]', ya[j-smooth[2] + 1:j])).^(1/prod(smooth)) for i in smooth[1]:length(xa), j in smooth[2]:length(ya)]
+    xas = [xa[i] for i in idx1, j in idx2]; yas = [ya[j] for i in idx1,j in idx2]
+    return xas,yas,A
+end
+
+"""
+    function arithsmooth2D(xa,ya,itp,smooth)
+Return xas,yas,A where A is an interpolated matrix with arithmetic smooth,
+whose axis are xas, yas
+# ARGS
+`xa` xaxis values, `ya` yaxis values,  `itp` interpolation function, `smooth` smoothing function
+"""
+function arithsmooth2D(xa,ya,itp,smooth)
+    prod(isodd.(smooth)) ? nothing : throw(ArgumentError("smoothing coefficients need to be odd"))
+    idx1 = Int((smooth[1]-1)/2)+1:length(xa)- Int((smooth[1]-1)/2)
+    idx2 = Int((smooth[2]-1)/2)+1:length(ya)- Int((smooth[2]-1)/2)
+    A = [sum(itp.(xa[i-smooth[1] + 1:i]', ya[j-smooth[2] + 1:j]))./prod(smooth) for i in smooth[1]:length(xa), j in smooth[2]:length(ya)]
+    xas = [xa[i] for i in idx1,j in idx2]; yas = [ya[j] for i in idx1,j in idx2]
+    return xas,yas,A
+end
+
+"""
+    function interpolate_df(df,xlab,ylab,zlab)
+returns an interpolated function itp(x,y) -> z, as well as its axis `xa` and `ya`
+"""
+function interpolate_df(df,xlab,ylab,zlab)
+    sort!(df,[ylab,xlab])
+    xa = unique(df[xlab]); ya = unique(df[ylab])
+    A = reshape(df[zlab],length(xa),length(ya))
+    return DiversityFunction(xa,ya,interpolate((xa,ya),A,Gridded(Linear())))
+end

test/runtests.jl

@@ -4,6 +4,8 @@ using ABMEv, Test, JLD2,Random
     include("gillepsie.jl")
     # include("wrightfisher.jl")
     include("metrics.jl")
+    include("utilstest.jl")
+
     # we might want to put this in a separate file at some point
     @testset "Reflection" begin
         @test get_inc_reflected(0.,2.0) ≈ .0