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			83 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Go
		
	
	
	
	
	
			
		
		
	
	
			83 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Go
		
	
	
	
	
	
| // Copyright ©2015 The gonum Authors. All rights reserved.
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| // Use of this source code is governed by a BSD-style
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| // license that can be found in the LICENSE file.
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| 
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| package native
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| 
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| import (
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| 	"math"
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| 
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| 	"github.com/gonum/blas"
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| 	"github.com/gonum/blas/blas64"
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| 	"github.com/gonum/lapack"
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| )
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| 
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| // Dtrcon estimates the reciprocal of the condition number of a triangular matrix A.
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| // The condition number computed may be based on the 1-norm or the ∞-norm.
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| //
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| // work is a temporary data slice of length at least 3*n and Dtrcon will panic otherwise.
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| //
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| // iwork is a temporary data slice of length at least n and Dtrcon will panic otherwise.
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| func (impl Implementation) Dtrcon(norm lapack.MatrixNorm, uplo blas.Uplo, diag blas.Diag, n int, a []float64, lda int, work []float64, iwork []int) float64 {
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| 	if norm != lapack.MaxColumnSum && norm != lapack.MaxRowSum {
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| 		panic(badNorm)
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| 	}
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| 	if uplo != blas.Upper && uplo != blas.Lower {
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| 		panic(badUplo)
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| 	}
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| 	if diag != blas.NonUnit && diag != blas.Unit {
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| 		panic(badDiag)
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| 	}
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| 	if len(work) < 3*n {
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| 		panic(badWork)
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| 	}
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| 	if len(iwork) < n {
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| 		panic(badWork)
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| 	}
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| 	if n == 0 {
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| 		return 1
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| 	}
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| 	bi := blas64.Implementation()
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| 
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| 	var rcond float64
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| 	smlnum := dlamchS * float64(n)
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| 
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| 	anorm := impl.Dlantr(norm, uplo, diag, n, n, a, lda, work)
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| 
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| 	if anorm <= 0 {
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| 		return rcond
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| 	}
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| 	var ainvnm float64
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| 	var normin bool
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| 	kase1 := 2
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| 	if norm == lapack.MaxColumnSum {
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| 		kase1 = 1
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| 	}
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| 	var kase int
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| 	isave := new([3]int)
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| 	var scale float64
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| 	for {
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| 		ainvnm, kase = impl.Dlacn2(n, work[n:], work, iwork, ainvnm, kase, isave)
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| 		if kase == 0 {
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| 			if ainvnm != 0 {
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| 				rcond = (1 / anorm) / ainvnm
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| 			}
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| 			return rcond
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| 		}
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| 		if kase == kase1 {
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| 			scale = impl.Dlatrs(uplo, blas.NoTrans, diag, normin, n, a, lda, work, work[2*n:])
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| 		} else {
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| 			scale = impl.Dlatrs(uplo, blas.Trans, diag, normin, n, a, lda, work, work[2*n:])
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| 		}
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| 		normin = true
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| 		if scale != 1 {
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| 			ix := bi.Idamax(n, work, 1)
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| 			xnorm := math.Abs(work[ix])
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| 			if scale == 0 || scale < xnorm*smlnum {
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| 				return rcond
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| 			}
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| 			impl.Drscl(n, scale, work, 1)
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| 		}
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| 	}
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| }
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