Update to changes in Base's cov and cor

JuliaStats · Oct 9, 2015 · 3e9739d · 3e9739d
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Showing 2 changed files with 148 additions and 56 deletions.
diff --git a/src/cov.jl b/src/cov.jl
@@ -25,26 +25,60 @@ end
 
 scattermat_zm(x::DenseMatrix, vardim::Int) = Base.unscaled_covzm(x, vardim)
 
-scattermat_zm(x::DenseMatrix, wv::WeightVec, vardim::Int) = 
+scattermat_zm(x::DenseMatrix, wv::WeightVec, vardim::Int) =
     _symmetrize!(Base.unscaled_covzm(x, _scalevars(x, values(wv), vardim), vardim))
 
-function scattermat(x::DenseMatrix; mean=nothing, vardim::Int=1) 
-    mean == 0 ? scattermat_zm(x, vardim) :
-    mean == nothing ? scattermat_zm(x .- Base.mean(x, vardim), vardim) :
-    scattermat_zm(x .- mean, vardim)
-end
+if VERSION < v"0.4.0-dev+660"
+    function scattermat(x::DenseMatrix; mean=nothing, vardim::Int=1)
+        mean == 0 ? scattermat_zm(x, vardim) :
+        mean == nothing ? scattermat_zm(x .- Base.mean(x, vardim), vardim) :
+        scattermat_zm(x .- mean, vardim)
+    end
 
-function scattermat(x::DenseMatrix, wv::WeightVec; mean=nothing, vardim::Int=1) 
-    mean == 0 ? scattermat_zm(x, wv, vardim) :
-    mean == nothing ? scattermat_zm(x .- Base.mean(x, wv, vardim), wv, vardim) :
-    scattermat_zm(x .- mean, wv, vardim)
-end
+    function scattermat(x::DenseMatrix, wv::WeightVec; mean=nothing, vardim::Int=1)
+        mean == 0 ? scattermat_zm(x, wv, vardim) :
+        mean == nothing ? scattermat_zm(x .- Base.mean(x, wv, vardim), wv, vardim) :
+        scattermat_zm(x .- mean, wv, vardim)
+    end
+
+    ## weighted cov
+    Base.cov(x::DenseMatrix, wv::WeightVec; mean=nothing, vardim::Int=1) =
+        scale!(scattermat(x, wv; mean=mean, vardim=vardim), inv(sum(wv)))
+
+    function mean_and_cov(x::DenseMatrix; vardim::Int=1)
+        m = mean(x, vardim)
+        return m, Base.covm(x, m; vardim=vardim)
+    end
+    function mean_and_cov(x::DenseMatrix, wv::WeightVec; vardim::Int=1)
+        m = mean(x, wv, vardim)
+        return m, Base.cov(x, wv; mean=m, vardim=vardim)
+    end
+else
+    scattermatm(x::DenseMatrix, mean, vardim::Int=1) =
+        scattermat_zm(x .- mean, vardim)
+
+    scattermatm(x::DenseMatrix, mean, wv::WeightVec, vardim::Int=1) =
+        scattermat_zm(x .- mean, wv, vardim)
+
+    scattermat(x::DenseMatrix, vardim::Int=1) =
+        scattermatm(x, Base.mean(x, vardim), vardim)
+
+    scattermat(x::DenseMatrix, wv::WeightVec, vardim::Int=1) =
+        scattermatm(x, Base.mean(x, wv, vardim), wv, vardim)
 
-## weighted cov
+    ## weighted cov
+    Base.covm(x::DenseMatrix, mean, wv::WeightVec, vardim::Int=1) =
+        scale!(scattermatm(x, mean, wv, vardim), inv(sum(wv)))
 
-Base.cov(x::DenseMatrix, wv::WeightVec; mean=nothing, vardim::Int=1) = 
-    scale!(scattermat(x, wv; mean=mean, vardim=vardim), inv(sum(wv)))
+    Base.cov(x::DenseMatrix, wv::WeightVec, vardim::Int=1) =
+        Base.covm(x, Base.mean(x, wv, vardim), wv, vardim)
 
-mean_and_cov(x::DenseMatrix; vardim::Int=1) = (m = mean(x, vardim); (m, Base.covm(x, m; vardim=vardim)))
-mean_and_cov(x::DenseMatrix, wv::WeightVec; vardim::Int=1) = 
-    (m = mean(x, wv, vardim); (m, Base.cov(x, wv; mean=m, vardim=vardim)))
+    function mean_and_cov(x::DenseMatrix, vardim::Int=1)
+        m = mean(x, vardim)
+        return m, Base.covm(x, m, vardim)
+    end
+    function mean_and_cov(x::DenseMatrix, wv::WeightVec, vardim::Int=1)
+        m = mean(x, wv, vardim)
+        return m, Base.cov(x, wv, vardim)
+    end
+end
diff --git a/test/cov.jl b/test/cov.jl
@@ -31,61 +31,119 @@ Sz2w = X * diagm(w2) * X'
 
 ## scattermat
 
-@test_approx_eq scattermat(X) S1
-@test_approx_eq scattermat(X; vardim=2) S2
+if VERSION < v"0.4.0-dev+660"
+    @test_approx_eq scattermat(X) S1
+    @test_approx_eq scattermat(X; vardim=2) S2
 
-@test_approx_eq scattermat(X; mean=0) Sz1
-@test_approx_eq scattermat(X; mean=0, vardim=2) Sz2
+    @test_approx_eq scattermat(X; mean=0) Sz1
+    @test_approx_eq scattermat(X; mean=0, vardim=2) Sz2
 
-@test_approx_eq scattermat(X; mean=mean(X,1)) S1
-@test_approx_eq scattermat(X; mean=mean(X,2), vardim=2) S2
+    @test_approx_eq scattermat(X; mean=mean(X,1)) S1
+    @test_approx_eq scattermat(X; mean=mean(X,2), vardim=2) S2
 
-@test_approx_eq scattermat(X; mean=zeros(1,8)) Sz1
-@test_approx_eq scattermat(X; mean=zeros(3), vardim=2) Sz2
+    @test_approx_eq scattermat(X; mean=zeros(1,8)) Sz1
+    @test_approx_eq scattermat(X; mean=zeros(3), vardim=2) Sz2
 
-## weighted scatter mat
+    ## weighted scatter mat
 
-@test_approx_eq scattermat(X, wv1) S1w
-@test_approx_eq scattermat(X, wv2; vardim=2) S2w
+    @test_approx_eq scattermat(X, wv1) S1w
+    @test_approx_eq scattermat(X, wv2; vardim=2) S2w
 
-@test_approx_eq scattermat(X, wv1; mean=0) Sz1w
-@test_approx_eq scattermat(X, wv2; mean=0, vardim=2) Sz2w
+    @test_approx_eq scattermat(X, wv1; mean=0) Sz1w
+    @test_approx_eq scattermat(X, wv2; mean=0, vardim=2) Sz2w
 
-@test_approx_eq scattermat(X, wv1; mean=mean(X, wv1, 1)) S1w
-@test_approx_eq scattermat(X, wv2; mean=mean(X, wv2, 2), vardim=2) S2w
+    @test_approx_eq scattermat(X, wv1; mean=mean(X, wv1, 1)) S1w
+    @test_approx_eq scattermat(X, wv2; mean=mean(X, wv2, 2), vardim=2) S2w
 
-@test_approx_eq scattermat(X, wv1; mean=zeros(1,8)) Sz1w
-@test_approx_eq scattermat(X, wv2; mean=zeros(3), vardim=2) Sz2w
+    @test_approx_eq scattermat(X, wv1; mean=zeros(1,8)) Sz1w
+    @test_approx_eq scattermat(X, wv2; mean=zeros(3), vardim=2) Sz2w
+else
+    @test_approx_eq scattermat(X) S1
+    @test_approx_eq scattermat(X, 2) S2
 
-# weighted covariance
+    @test_approx_eq StatsBase.scattermatm(X, 0) Sz1
+    @test_approx_eq StatsBase.scattermatm(X, 0, 2) Sz2
 
-@test_approx_eq cov(X, wv1) S1w ./ sum(wv1)
-@test_approx_eq cov(X, wv2; vardim=2) S2w ./ sum(wv2)
+    @test_approx_eq StatsBase.scattermatm(X, mean(X,1)) S1
+    @test_approx_eq StatsBase.scattermatm(X, mean(X,2), 2) S2
 
-@test_approx_eq cov(X, wv1; mean=0) Sz1w ./ sum(wv1)
-@test_approx_eq cov(X, wv2; mean=0, vardim=2) Sz2w ./ sum(wv2)
+    @test_approx_eq StatsBase.scattermatm(X, zeros(1,8)) Sz1
+    @test_approx_eq StatsBase.scattermatm(X, zeros(3), 2) Sz2
 
-@test_approx_eq cov(X, wv1; mean=mean(X, wv1, 1)) S1w ./ sum(wv1)
-@test_approx_eq cov(X, wv2; mean=mean(X, wv2, 2), vardim=2) S2w ./ sum(wv2)
+    ## weighted scatter mat
 
-@test_approx_eq cov(X, wv1; mean=zeros(1,8)) Sz1w ./ sum(wv1)
-@test_approx_eq cov(X, wv2; mean=zeros(3), vardim=2) Sz2w ./ sum(wv2)
+    @test_approx_eq scattermat(X, wv1) S1w
+    @test_approx_eq scattermat(X, wv2, 2) S2w
 
-# mean_and_cov
+    @test_approx_eq StatsBase.scattermatm(X, 0, wv1) Sz1w
+    @test_approx_eq StatsBase.scattermatm(X, 0, wv2, 2) Sz2w
+
+    @test_approx_eq StatsBase.scattermatm(X, mean(X, wv1, 1), wv1) S1w
+    @test_approx_eq StatsBase.scattermatm(X, mean(X, wv2, 2), wv2, 2) S2w
+
+    @test_approx_eq StatsBase.scattermatm(X, zeros(1,8), wv1) Sz1w
+    @test_approx_eq StatsBase.scattermatm(X, zeros(3), wv2, 2) Sz2w
+end
+
+# weighted covariance
+
+if VERSION < v"0.4.0-dev+660"
+    @test_approx_eq cov(X, wv1) S1w ./ sum(wv1)
+    @test_approx_eq cov(X, wv2; vardim=2) S2w ./ sum(wv2)
+
+    @test_approx_eq cov(X, wv1; mean=0) Sz1w ./ sum(wv1)
+    @test_approx_eq cov(X, wv2; mean=0, vardim=2) Sz2w ./ sum(wv2)
 
-(m, C) = mean_and_cov(X; vardim=1)
-@test m == mean(X, 1)
-@test C == cov(X; vardim=1)
+    @test_approx_eq cov(X, wv1; mean=mean(X, wv1, 1)) S1w ./ sum(wv1)
+    @test_approx_eq cov(X, wv2; mean=mean(X, wv2, 2), vardim=2) S2w ./ sum(wv2)
 
-(m, C) = mean_and_cov(X; vardim=2)
-@test m == mean(X, 2)
-@test C == cov(X; vardim=2)
+    @test_approx_eq cov(X, wv1; mean=zeros(1,8)) Sz1w ./ sum(wv1)
+    @test_approx_eq cov(X, wv2; mean=zeros(3), vardim=2) Sz2w ./ sum(wv2)
+else
+    @test_approx_eq cov(X, wv1) S1w ./ sum(wv1)
+    @test_approx_eq cov(X, wv2, 2) S2w ./ sum(wv2)
 
-(m, C) = mean_and_cov(X, wv1; vardim=1)
-@test m == mean(X, wv1, 1)
-@test C == cov(X, wv1; vardim=1)
+    @test_approx_eq Base.covm(X, 0, wv1) Sz1w ./ sum(wv1)
+    @test_approx_eq Base.covm(X, 0, wv2, 2) Sz2w ./ sum(wv2)
 
-(m, C) = mean_and_cov(X, wv2; vardim=2)
-@test m == mean(X, wv2, 2)
-@test C == cov(X, wv2; vardim=2)
+    @test_approx_eq Base.covm(X, mean(X, wv1, 1), wv1) S1w ./ sum(wv1)
+    @test_approx_eq Base.covm(X, mean(X, wv2, 2), wv2, 2) S2w ./ sum(wv2)
 
+    @test_approx_eq Base.covm(X, zeros(1,8), wv1) Sz1w ./ sum(wv1)
+    @test_approx_eq Base.covm(X, zeros(3), wv2, 2) Sz2w ./ sum(wv2)
+end
+
+# mean_and_cov
+if VERSION < v"0.4.0-dev+660"
+    (m, C) = mean_and_cov(X; vardim=1)
+    @test m == mean(X, 1)
+    @test C == cov(X; vardim=1)
+
+    (m, C) = mean_and_cov(X; vardim=2)
+    @test m == mean(X, 2)
+    @test C == cov(X; vardim=2)
+
+    (m, C) = mean_and_cov(X, wv1; vardim=1)
+    @test m == mean(X, wv1, 1)
+    @test C == cov(X, wv1; vardim=1)
+
+    (m, C) = mean_and_cov(X, wv2; vardim=2)
+    @test m == mean(X, wv2, 2)
+    @test C == cov(X, wv2; vardim=2)
+else
+    (m, C) = mean_and_cov(X, 1)
+    @test m == mean(X, 1)
+    @test C == cov(X, 1)
+
+    (m, C) = mean_and_cov(X, 2)
+    @test m == mean(X, 2)
+    @test C == cov(X, 2)
+
+    (m, C) = mean_and_cov(X, wv1, 1)
+    @test m == mean(X, wv1, 1)
+    @test C == cov(X, wv1, 1)
+
+    (m, C) = mean_and_cov(X, wv2, 2)
+    @test m == mean(X, wv2, 2)
+    @test C == cov(X, wv2, 2)
+end