Initial work on covariancematrix

covariancematrix.go

@@ -0,0 +1,48 @@
+// Copyright ©2014 The gonum Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style
+// license that can be found in the LICENSE file.
+
+package stat
+
+import (
+	"github.com/gonum/matrix/mat64"
+)
+
+// CovarianceMatrix calculates a covariance matrix (also known as a
+// variance-covariance matrix) from a matrix of data.
+func CovarianceMatrix(x mat64.Matrix) *mat64.Dense {
+	
+	// matrix version of the two pass algorithm.  This doesn't use
+	// the correction found in the Covariance and Variance functions.
+	
+	r, _ := x.Dims()
+	b := ones(1, r)
+	b.Mul(b, x)
+	b.Scale(1/float64(r), b)
+	
+	// todo: avoid unneeded memory expansion here.
+	mu := new(mat64.Dense)
+	mu.Mul(ones(r,1),b)
+	
+	// this could also be done with a clone & row viewer
+	xc := mat64.DenseCopyOf(x)
+	xc.Sub(xc, mu)
+	
+	// todo: avoid matrix copy
+	xt := new(mat64.Dense)
+	xt.TCopy(xc)
+	
+	ss := new(mat64.Dense)
+	ss.Mul(xt, xc)
+	ss.Scale(1/float64(r-1), ss)
+	return ss
+}
+
+// ones is a matrix of all ones.
+func ones(r, c int) *mat64.Dense {
+	x := make([]float64, r*c)
+	for i := range x {
+		x[i] = 1
+	}
+	return mat64.NewDense(r, c, x)
+}

covariancematrix_test.go

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+// Copyright ©2014 The gonum Authors. All rights reserved.
+// Use of this source code is governed by a BSD-style
+// license that can be found in the LICENSE file.
+
+package stat
+
+import (
+	"testing"
+
+	"github.com/gonum/blas/cblas"
+	"github.com/gonum/floats"
+	"github.com/gonum/matrix/mat64"
+)
+
+func init() {
+	mat64.Register(cblas.Blas{})
+}
+
+func TestCovarianceMatrix(t *testing.T) {
+	for i, test := range []struct {
+		mat  mat64.Matrix
+		r, c int
+		x    []float64
+	}{
+		{
+			mat: mat64.NewDense(5, 2, []float64{
+				-2, -4,
+				-1, 2,
+				0, 0,
+				1, -2,
+				2, 4,
+			}),
+			r: 2,
+			c: 2,
+			x: []float64{
+				2.5, 3,
+				3, 10,
+			},
+		},
+	} {
+		c := CovarianceMatrix(test.mat).RawMatrix()
+		if c.Rows != test.r {
+			t.Errorf("%d: expected rows %d, found %d", i, test.r, c.Rows)
+		}
+		if c.Cols != test.c {
+			t.Errorf("%d: expected cols %d, found %d", i, test.c, c.Cols)
+		}
+		if !floats.Equal(test.x, c.Data) {
+			t.Errorf("%d: expected data %#q, found %#q", i, test.x, c.Data)
+		}
+	}
+}