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https://git.planet-casio.com/Lephenixnoir/OpenLibm.git
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c977aa998f
Replace amos with slatec
336 lines
9.2 KiB
Fortran
336 lines
9.2 KiB
Fortran
*DECK LSI
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SUBROUTINE LSI (W, MDW, MA, MG, N, PRGOPT, X, RNORM, MODE, WS, IP)
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C***BEGIN PROLOGUE LSI
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C***SUBSIDIARY
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C***PURPOSE Subsidiary to LSEI
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C***LIBRARY SLATEC
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C***TYPE SINGLE PRECISION (LSI-S, DLSI-D)
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C***AUTHOR Hanson, R. J., (SNLA)
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C***DESCRIPTION
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C
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C This is a companion subprogram to LSEI. The documentation for
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C LSEI has complete usage instructions.
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C
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C Solve..
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C AX = B, A MA by N (least squares equations)
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C subject to..
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C
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C GX.GE.H, G MG by N (inequality constraints)
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C
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C Input..
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C
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C W(*,*) contains (A B) in rows 1,...,MA+MG, cols 1,...,N+1.
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C (G H)
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C
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C MDW,MA,MG,N
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C contain (resp) var. dimension of W(*,*),
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C and matrix dimensions.
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C
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C PRGOPT(*),
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C Program option vector.
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C
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C OUTPUT..
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C
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C X(*),RNORM
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C
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C Solution vector(unless MODE=2), length of AX-B.
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C
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C MODE
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C =0 Inequality constraints are compatible.
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C =2 Inequality constraints contradictory.
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C
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C WS(*),
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C Working storage of dimension K+N+(MG+2)*(N+7),
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C where K=MAX(MA+MG,N).
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C IP(MG+2*N+1)
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C Integer working storage
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C
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C***ROUTINES CALLED H12, HFTI, LPDP, R1MACH, SASUM, SAXPY, SCOPY, SDOT,
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C SSCAL, SSWAP
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C***REVISION HISTORY (YYMMDD)
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C 790701 DATE WRITTEN
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C 890531 Changed all specific intrinsics to generic. (WRB)
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C 890618 Completely restructured and extensively revised (WRB & RWC)
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C 891214 Prologue converted to Version 4.0 format. (BAB)
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C 900328 Added TYPE section. (WRB)
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C 920422 Changed CALL to HFTI to include variable MA. (WRB)
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C***END PROLOGUE LSI
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INTEGER IP(*), MA, MDW, MG, MODE, N
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REAL PRGOPT(*), RNORM, W(MDW,*), WS(*), X(*)
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C
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EXTERNAL H12, HFTI, LPDP, R1MACH, SASUM, SAXPY, SCOPY, SDOT,
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* SSCAL, SSWAP
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REAL R1MACH, SASUM, SDOT
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C
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REAL ANORM, FAC, GAM, RB, SRELPR, TAU, TOL, XNORM
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INTEGER I, J, K, KEY, KRANK, KRM1, KRP1, L, LAST, LINK, M, MAP1,
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* MDLPDP, MINMAN, N1, N2, N3, NEXT, NP1
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LOGICAL COV, FIRST, SCLCOV
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C
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SAVE SRELPR, FIRST
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DATA FIRST /.TRUE./
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C
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C***FIRST EXECUTABLE STATEMENT LSI
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C
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C Set the nominal tolerance used in the code.
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C
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IF (FIRST) SRELPR = R1MACH(4)
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FIRST = .FALSE.
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TOL = SQRT(SRELPR)
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C
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MODE = 0
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RNORM = 0.E0
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M = MA + MG
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NP1 = N + 1
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KRANK = 0
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IF (N.LE.0 .OR. M.LE.0) GO TO 370
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C
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C To process option vector.
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C
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COV = .FALSE.
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SCLCOV = .TRUE.
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LAST = 1
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LINK = PRGOPT(1)
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C
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100 IF (LINK.GT.1) THEN
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KEY = PRGOPT(LAST+1)
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IF (KEY.EQ.1) COV = PRGOPT(LAST+2) .NE. 0.E0
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IF (KEY.EQ.10) SCLCOV = PRGOPT(LAST+2) .EQ. 0.E0
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IF (KEY.EQ.5) TOL = MAX(SRELPR,PRGOPT(LAST+2))
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NEXT = PRGOPT(LINK)
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LAST = LINK
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LINK = NEXT
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GO TO 100
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ENDIF
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C
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C Compute matrix norm of least squares equations.
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C
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ANORM = 0.E0
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DO 110 J = 1,N
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ANORM = MAX(ANORM,SASUM(MA,W(1,J),1))
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110 CONTINUE
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C
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C Set tolerance for HFTI( ) rank test.
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C
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TAU = TOL*ANORM
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C
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C Compute Householder orthogonal decomposition of matrix.
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C
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CALL SCOPY (N, 0.E0, 0, WS, 1)
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CALL SCOPY (MA, W(1, NP1), 1, WS, 1)
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K = MAX(M,N)
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MINMAN = MIN(MA,N)
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N1 = K + 1
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N2 = N1 + N
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CALL HFTI (W, MDW, MA, N, WS, MA, 1, TAU, KRANK, RNORM, WS(N2),
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+ WS(N1), IP)
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FAC = 1.E0
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GAM = MA - KRANK
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IF (KRANK.LT.MA .AND. SCLCOV) FAC = RNORM**2/GAM
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C
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C Reduce to LPDP and solve.
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C
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MAP1 = MA + 1
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C
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C Compute inequality rt-hand side for LPDP.
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C
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IF (MA.LT.M) THEN
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IF (MINMAN.GT.0) THEN
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DO 120 I = MAP1,M
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W(I,NP1) = W(I,NP1) - SDOT(N,W(I,1),MDW,WS,1)
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120 CONTINUE
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C
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C Apply permutations to col. of inequality constraint matrix.
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C
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DO 130 I = 1,MINMAN
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CALL SSWAP (MG, W(MAP1,I), 1, W(MAP1,IP(I)), 1)
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130 CONTINUE
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C
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C Apply Householder transformations to constraint matrix.
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C
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IF (KRANK.GT.0 .AND. KRANK.LT.N) THEN
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DO 140 I = KRANK,1,-1
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CALL H12 (2, I, KRANK+1, N, W(I,1), MDW, WS(N1+I-1),
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+ W(MAP1,1), MDW, 1, MG)
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140 CONTINUE
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ENDIF
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C
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C Compute permuted inequality constraint matrix times r-inv.
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C
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DO 160 I = MAP1,M
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DO 150 J = 1,KRANK
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W(I,J) = (W(I,J)-SDOT(J-1,W(1,J),1,W(I,1),MDW))/W(J,J)
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150 CONTINUE
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160 CONTINUE
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ENDIF
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C
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C Solve the reduced problem with LPDP algorithm,
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C the least projected distance problem.
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C
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CALL LPDP(W(MAP1,1), MDW, MG, KRANK, N-KRANK, PRGOPT, X,
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+ XNORM, MDLPDP, WS(N2), IP(N+1))
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C
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C Compute solution in original coordinates.
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C
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IF (MDLPDP.EQ.1) THEN
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DO 170 I = KRANK,1,-1
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X(I) = (X(I)-SDOT(KRANK-I,W(I,I+1),MDW,X(I+1),1))/W(I,I)
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170 CONTINUE
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C
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C Apply Householder transformation to solution vector.
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C
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IF (KRANK.LT.N) THEN
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DO 180 I = 1,KRANK
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CALL H12 (2, I, KRANK+1, N, W(I,1), MDW, WS(N1+I-1),
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+ X, 1, 1, 1)
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180 CONTINUE
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ENDIF
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C
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C Repermute variables to their input order.
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C
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IF (MINMAN.GT.0) THEN
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DO 190 I = MINMAN,1,-1
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CALL SSWAP (1, X(I), 1, X(IP(I)), 1)
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190 CONTINUE
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C
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C Variables are now in original coordinates.
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C Add solution of unconstrained problem.
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C
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DO 200 I = 1,N
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X(I) = X(I) + WS(I)
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200 CONTINUE
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C
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C Compute the residual vector norm.
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C
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RNORM = SQRT(RNORM**2+XNORM**2)
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ENDIF
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ELSE
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MODE = 2
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ENDIF
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ELSE
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CALL SCOPY (N, WS, 1, X, 1)
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ENDIF
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C
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C Compute covariance matrix based on the orthogonal decomposition
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C from HFTI( ).
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C
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IF (.NOT.COV .OR. KRANK.LE.0) GO TO 370
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KRM1 = KRANK - 1
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KRP1 = KRANK + 1
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C
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C Copy diagonal terms to working array.
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C
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CALL SCOPY (KRANK, W, MDW+1, WS(N2), 1)
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C
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C Reciprocate diagonal terms.
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C
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DO 210 J = 1,KRANK
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W(J,J) = 1.E0/W(J,J)
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210 CONTINUE
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C
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C Invert the upper triangular QR factor on itself.
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C
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IF (KRANK.GT.1) THEN
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DO 230 I = 1,KRM1
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DO 220 J = I+1,KRANK
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W(I,J) = -SDOT(J-I,W(I,I),MDW,W(I,J),1)*W(J,J)
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220 CONTINUE
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230 CONTINUE
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ENDIF
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C
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C Compute the inverted factor times its transpose.
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C
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DO 250 I = 1,KRANK
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DO 240 J = I,KRANK
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W(I,J) = SDOT(KRANK+1-J,W(I,J),MDW,W(J,J),MDW)
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240 CONTINUE
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250 CONTINUE
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C
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C Zero out lower trapezoidal part.
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C Copy upper triangular to lower triangular part.
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C
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IF (KRANK.LT.N) THEN
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DO 260 J = 1,KRANK
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CALL SCOPY (J, W(1,J), 1, W(J,1), MDW)
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260 CONTINUE
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C
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DO 270 I = KRP1,N
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CALL SCOPY (I, 0.E0, 0, W(I,1), MDW)
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270 CONTINUE
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C
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C Apply right side transformations to lower triangle.
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C
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N3 = N2 + KRP1
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DO 330 I = 1,KRANK
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L = N1 + I
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K = N2 + I
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RB = WS(L-1)*WS(K-1)
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C
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C If RB.GE.0.E0, transformation can be regarded as zero.
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C
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IF (RB.LT.0.E0) THEN
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RB = 1.E0/RB
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C
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C Store unscaled rank one Householder update in work array.
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C
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CALL SCOPY (N, 0.E0, 0, WS(N3), 1)
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L = N1 + I
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K = N3 + I
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WS(K-1) = WS(L-1)
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C
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DO 280 J = KRP1,N
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WS(N3+J-1) = W(I,J)
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280 CONTINUE
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C
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DO 290 J = 1,N
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WS(J) = RB*(SDOT(J-I,W(J,I),MDW,WS(N3+I-1),1)+
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+ SDOT(N-J+1,W(J,J),1,WS(N3+J-1),1))
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290 CONTINUE
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C
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L = N3 + I
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GAM = 0.5E0*RB*SDOT(N-I+1,WS(L-1),1,WS(I),1)
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CALL SAXPY (N-I+1, GAM, WS(L-1), 1, WS(I), 1)
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DO 320 J = I,N
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DO 300 L = 1,I-1
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W(J,L) = W(J,L) + WS(N3+J-1)*WS(L)
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300 CONTINUE
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C
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DO 310 L = I,J
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W(J,L) = W(J,L) + WS(J)*WS(N3+L-1)+WS(L)*WS(N3+J-1)
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310 CONTINUE
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320 CONTINUE
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ENDIF
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330 CONTINUE
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C
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C Copy lower triangle to upper triangle to symmetrize the
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C covariance matrix.
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C
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DO 340 I = 1,N
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CALL SCOPY (I, W(I,1), MDW, W(1,I), 1)
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340 CONTINUE
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ENDIF
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C
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C Repermute rows and columns.
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C
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DO 350 I = MINMAN,1,-1
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K = IP(I)
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IF (I.NE.K) THEN
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CALL SSWAP (1, W(I,I), 1, W(K,K), 1)
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CALL SSWAP (I-1, W(1,I), 1, W(1,K), 1)
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CALL SSWAP (K-I-1, W(I,I+1), MDW, W(I+1,K), 1)
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CALL SSWAP (N-K, W(I, K+1), MDW, W(K, K+1), MDW)
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ENDIF
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350 CONTINUE
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C
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C Put in normalized residual sum of squares scale factor
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C and symmetrize the resulting covariance matrix.
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C
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DO 360 J = 1,N
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CALL SSCAL (J, FAC, W(1,J), 1)
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CALL SCOPY (J, W(1,J), 1, W(J,1), MDW)
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360 CONTINUE
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C
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370 IP(1) = KRANK
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IP(2) = N + MAX(M,N) + (MG+2)*(N+7)
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RETURN
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END
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