Update compat for MultivariateStats (#487)

* Remove dead code

* Use new predict instead of deprecated transform

* Bump compat

* Increment version number

* Add MDS test

Author: sethaxen

Project.toml

@@ -1,6 +1,6 @@
 name = "StatsPlots"
 uuid = "f3b207a7-027a-5e70-b257-86293d7955fd"
-version = "0.14.32"
+version = "0.14.33"
 
 [deps]
 AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
@@ -30,7 +30,7 @@ DataValues = "0.4"
 Distributions = "0.21, 0.22, 0.23, 0.24, 0.25"
 Interpolations = "0.12, 0.13"
 KernelDensity = "0.5, 0.6"
-MultivariateStats = "0.7, 0.8"
+MultivariateStats = "0.9"
 Observables = "0.2.2, 0.3, 0.4"
 Plots = "0.28, 0.29, 1.0"
 RecipesBase = "0.6, 0.7, 0.8, 1"

src/StatsPlots.jl

@@ -18,8 +18,7 @@ import Widgets: @nodeps
 import DataStructures: OrderedDict
 import Clustering: Hclust, nnodes
 using Interpolations
-import MultivariateStats: MDS, eigvals, projection, principalvars,
-                            principalratio, transform
+using MultivariateStats: MultivariateStats
 using AbstractFFTs: fft, ifft
 import KernelDensity
 @recipe f(k::KernelDensity.UnivariateKDE) = k.x, k.density

src/ordinations.jl

@@ -1,10 +1,8 @@
-@recipe function f(mds::MDS{<:Real}; mds_axes=(1,2))
+@recipe function f(mds::MultivariateStats.MDS{<:Real}; mds_axes=(1,2))
     length(mds_axes) in [2,3] || throw(ArgumentError("Can only accept 2 or 3 mds axes"))
     xax = mds_axes[1]
     yax = mds_axes[2]
-    ev = eigvals(mds)
-    var_explained = [v / sum(ev) for v in ev]
-    tfm = collect(transform(mds)')
+    tfm = collect(MultivariateStats.predict(mds)')
 
     xlabel --> "MDS$xax"
     ylabel --> "MDS$yax"

test/runtests.jl

@@ -4,6 +4,7 @@ using StableRNGs
 using NaNMath
 using Clustering
 using Distributions
+using MultivariateStats
 
 @testset "Grouped histogram" begin
     rng = StableRNG(1337)
@@ -103,3 +104,25 @@ end
         end
     end
 end
+
+@testset "ordinations" begin
+    @testset "MDS" begin
+        X = randn(4, 100)
+        M = fit(MultivariateStats.MDS, X; maxoutdim=3, distances=false)
+        Y = MultivariateStats.predict(M)'
+
+        mds_plt = plot(M)
+        @test mds_plt[1][1][:x] == Y[:,1]
+        @test mds_plt[1][1][:y] == Y[:,2]
+        @test mds_plt[1][:xaxis][:guide] == "MDS1"
+        @test mds_plt[1][:yaxis][:guide] == "MDS2"
+
+        mds_plt2 = plot(M; mds_axes=(3,1,2))
+        @test mds_plt2[1][1][:x] == Y[:,3]
+        @test mds_plt2[1][1][:y] == Y[:,1]
+        @test mds_plt2[1][1][:z] == Y[:,2]
+        @test mds_plt2[1][:xaxis][:guide] == "MDS3"
+        @test mds_plt2[1][:yaxis][:guide] == "MDS1"
+        @test mds_plt2[1][:zaxis][:guide] == "MDS2"
+    end
+end