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[bytom/vapor.git] / vendor / gonum.org / v1 / gonum / lapack / internal / testdata / dlahr2test / main.go

diff --git a/vendor/gonum.org/v1/gonum/lapack/internal/testdata/dlahr2test/main.go b/vendor/gonum.org/v1/gonum/lapack/internal/testdata/dlahr2test/main.go
new file mode 100644 (file)
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+// 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.
+
+// dlahr2test generates test data for Dlahr2. Test cases are stored in
+// gzip-compressed JSON file testlapack/testdata/dlahr2data.json.gz which is
+// read during testing by testlapack/dlahr2.go.
+//
+// This program uses cgo to call Fortran version of DLAHR2. Therefore, matrices
+// passed to the Fortran routine are in column-major format but are written into
+// the output file in row-major format.
+package main
+
+import (
+       "compress/gzip"
+       "encoding/json"
+       "log"
+       "os"
+       "path/filepath"
+
+       "golang.org/x/exp/rand"
+
+       "gonum.org/v1/gonum/lapack/internal/testdata/netlib"
+)
+
+type Dlahr2Test struct {
+       N, K, NB int
+       A        []float64
+
+       AWant   []float64
+       TWant   []float64
+       YWant   []float64
+       TauWant []float64
+}
+
+func main() {
+       file, err := os.Create(filepath.FromSlash("../../../testlapack/testdata/dlahr2data.json.gz"))
+       if err != nil {
+               log.Fatal(err)
+       }
+       defer file.Close()
+       w := gzip.NewWriter(file)
+
+       rnd := rand.New(rand.NewSource(1))
+
+       var tests []Dlahr2Test
+       for _, n := range []int{4, 5, 6, 7, 11} {
+               for k := 0; k <= n/2; k++ {
+                       for nb := 1; nb <= k; nb++ {
+                               ain := genrand(n, n-k+1, rnd)
+                               a := make([]float64, len(ain))
+                               copy(a, ain)
+
+                               t := genrand(nb, nb, rnd)
+                               y := genrand(n, nb, rnd)
+                               tau := genrand(nb, 1, rnd)
+
+                               netlib.Dlahr2(n, k, nb, a, n, tau, t, nb, y, n)
+
+                               tests = append(tests, Dlahr2Test{
+                                       N:       n,
+                                       K:       k,
+                                       NB:      nb,
+                                       A:       rowMajor(n, n-k+1, ain),
+                                       AWant:   rowMajor(n, n-k+1, a),
+                                       TWant:   rowMajor(nb, nb, t),
+                                       YWant:   rowMajor(n, nb, y),
+                                       TauWant: tau,
+                               })
+                       }
+               }
+       }
+       json.NewEncoder(w).Encode(tests)
+
+       err = w.Close()
+       if err != nil {
+               log.Fatal(err)
+       }
+}
+
+// genrand returns a general r×c matrix with random entries.
+func genrand(r, c int, rnd *rand.Rand) []float64 {
+       m := make([]float64, r*c)
+       for i := range m {
+               m[i] = rnd.NormFloat64()
+       }
+       return m
+}
+
+// rowMajor returns the given r×c column-major matrix a in row-major format.
+func rowMajor(r, c int, a []float64) []float64 {
+       if len(a) != r*c {
+               panic("testdata: slice length mismatch")
+       }
+       m := make([]float64, len(a))
+       for i := 0; i < r; i++ {
+               for j := 0; j < c; j++ {
+                       m[i*c+j] = a[i+j*r]
+               }
+       }
+       return m
+}