stat: imported stat as a subtree

stat/pca_example_test.go

@@ -0,0 +1,60 @@
+// Copyright ©2016 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_test
+
+import (
+	"fmt"
+
+	"github.com/gonum/matrix/mat64"
+	"github.com/gonum/stat"
+)
+
+func ExamplePrincipalComponents() {
+	// iris is a truncated sample of the Fisher's Iris dataset.
+	n := 10
+	d := 4
+	iris := mat64.NewDense(n, d, []float64{
+		5.1, 3.5, 1.4, 0.2,
+		4.9, 3.0, 1.4, 0.2,
+		4.7, 3.2, 1.3, 0.2,
+		4.6, 3.1, 1.5, 0.2,
+		5.0, 3.6, 1.4, 0.2,
+		5.4, 3.9, 1.7, 0.4,
+		4.6, 3.4, 1.4, 0.3,
+		5.0, 3.4, 1.5, 0.2,
+		4.4, 2.9, 1.4, 0.2,
+		4.9, 3.1, 1.5, 0.1,
+	})
+
+	// Calculate the principal component direction vectors
+	// and variances.
+	var pc stat.PC
+	ok := pc.PrincipalComponents(iris, nil)
+	if !ok {
+		return
+	}
+	fmt.Printf("variances = %.4f\n\n", pc.Vars(nil))
+
+	// Project the data onto the first 2 principal components.
+	k := 2
+	var proj mat64.Dense
+	proj.Mul(iris, pc.Vectors(nil).Slice(0, d, 0, k))
+
+	fmt.Printf("proj = %.4f", mat64.Formatted(&proj, mat64.Prefix("       ")))
+
+	// Output:
+	// variances = [0.1666 0.0207 0.0079 0.0019]
+	//
+	// proj = ⎡-6.1686   1.4659⎤
+	//        ⎢-5.6767   1.6459⎥
+	//        ⎢-5.6699   1.3642⎥
+	//        ⎢-5.5643   1.3816⎥
+	//        ⎢-6.1734   1.3309⎥
+	//        ⎢-6.7278   1.4021⎥
+	//        ⎢-5.7743   1.1498⎥
+	//        ⎢-6.0466   1.4714⎥
+	//        ⎢-5.2709   1.3570⎥
+	//        ⎣-5.7533   1.6207⎦
+}