#include "blaswrap.h" /* -- translated by f2c (version 19990503). You must link the resulting object file with the libraries: -lf2c -lm (in that order) */ #include "f2c.h" /* Common Block Declarations */ struct { integer nproc, nshift, maxb; } cenvir_; #define cenvir_1 cenvir_ struct { integer iparms[100]; } claenv_; #define claenv_1 claenv_ struct { integer infot, nunit; logical ok, lerr; } infoc_; #define infoc_1 infoc_ struct { char srnamt[6]; } srnamc_; #define srnamc_1 srnamc_ struct { integer selopt, seldim; logical selval[20]; real selwr[20], selwi[20]; } sslct_; #define sslct_1 sslct_ /* Table of constant values */ static integer c__1 = 1; static integer c__3 = 3; static integer c__5 = 5; static integer c__6 = 6; static integer c__4 = 4; static integer c__20 = 20; static integer c__0 = 0; static integer c__132 = 132; static integer c__2 = 2; static integer c__8 = 8; static integer c__87781 = 87781; static integer c__9 = 9; static integer c__25 = 25; static integer c__89760 = 89760; static integer c__18 = 18; static integer c__400 = 400; static integer c__89758 = 89758; static integer c__264 = 264; /* Main program */ MAIN__(void) { /* Initialized data */ static char intstr[10] = "0123456789"; static integer ioldsd[4] = { 0,0,0,1 }; /* Format strings */ static char fmt_9987[] = "(\002 Tests of the Nonsymmetric Eigenvalue Pro" "blem routines\002)"; static char fmt_9986[] = "(\002 Tests of the Symmetric Eigenvalue Proble" "m routines\002)"; static char fmt_9985[] = "(\002 Tests of the Singular Value Decompositio" "n routines\002)"; static char fmt_9979[] = "(/\002 Tests of the Nonsymmetric Eigenvalue Pr" "oblem Driver\002,/\002 SGEEV (eigenvalues and eigevectors)" "\002)"; static char fmt_9978[] = "(/\002 Tests of the Nonsymmetric Eigenvalue Pr" "oblem Driver\002,/\002 SGEES (Schur form)\002)"; static char fmt_9977[] = "(/\002 Tests of the Nonsymmetric Eigenvalue Pr" "oblem Expert\002,\002 Driver\002,/\002 SGEEVX (eigenvalues, e" "igenvectors and\002,\002 condition numbers)\002)"; static char fmt_9976[] = "(/\002 Tests of the Nonsymmetric Eigenvalue Pr" "oblem Expert\002,\002 Driver\002,/\002 SGEESX (Schur form and" " condition\002,\002 numbers)\002)"; static char fmt_9975[] = "(/\002 Tests of the Generalized Nonsymmetric E" "igenvalue \002,\002Problem routines\002)"; static char fmt_9964[] = "(/\002 Tests of the Generalized Nonsymmetric E" "igenvalue \002,\002Problem Driver SGGES\002)"; static char fmt_9965[] = "(/\002 Tests of the Generalized Nonsymmetric E" "igenvalue \002,\002Problem Expert Driver SGGESX\002)"; static char fmt_9963[] = "(/\002 Tests of the Generalized Nonsymmetric E" "igenvalue \002,\002Problem Driver SGGEV\002)"; static char fmt_9962[] = "(/\002 Tests of the Generalized Nonsymmetric E" "igenvalue \002,\002Problem Expert Driver SGGEVX\002)"; static char fmt_9974[] = "(\002 Tests of SSBTRD\002,/\002 (reduction of " "a symmetric band \002,\002matrix to tridiagonal form)\002)"; static char fmt_9967[] = "(\002 Tests of SGBBRD\002,/\002 (reduction of " "a general band \002,\002matrix to real bidiagonal form)\002)"; static char fmt_9971[] = "(/\002 Tests of the Generalized Linear Regress" "ion Model \002,\002routines\002)"; static char fmt_9970[] = "(/\002 Tests of the Generalized QR and RQ rout" "ines\002)"; static char fmt_9969[] = "(/\002 Tests of the Generalized Singular Valu" "e\002,\002 Decomposition routines\002)"; static char fmt_9968[] = "(/\002 Tests of the Linear Least Squares routi" "nes\002)"; static char fmt_9992[] = "(1x,a3,\002: Unrecognized path name\002)"; static char fmt_9972[] = "(/\002 LAPACK VERSION 3.0, released June 30, 1" "999 \002)"; static char fmt_9984[] = "(/\002 The following parameter values will be " "used:\002)"; static char fmt_9989[] = "(\002 Invalid input value: \002,a6,\002=\002,i" "6,\002; must be >=\002,i6)"; static char fmt_9988[] = "(\002 Invalid input value: \002,a6,\002=\002,i" "6,\002; must be <=\002,i6)"; static char fmt_9983[] = "(4x,a6,10i6,/10x,10i6)"; static char fmt_9981[] = "(\002 Relative machine \002,a,\002 is taken to" " be\002,e16.6)"; static char fmt_9982[] = "(/\002 Routines pass computational tests if te" "st ratio is \002,\002less than\002,f8.2,/)"; static char fmt_9999[] = "(/\002 Execution not attempted due to input er" "rors\002)"; static char fmt_9991[] = "(//\002 *** Invalid integer value in column" " \002,i2,\002 of input\002,\002 line:\002,/a79)"; static char fmt_9990[] = "(//1x,a3,\002 routines were not tested\002)"; static char fmt_9998[] = "(//1x,a3,\002: NB =\002,i4,\002, NBMIN =\002," "i4,\002, NX =\002,i4,\002, NS =\002,i4,\002, MAXB =\002,i4)"; static char fmt_9980[] = "(\002 *** Error code from \002,a6,\002 = \002," "i4)"; static char fmt_9997[] = "(//1x,a3,\002: NB =\002,i4,\002, NBMIN =\002," "i4,\002, NX =\002,i4)"; static char fmt_9995[] = "(//1x,a3,\002: NB =\002,i4,\002, NBMIN =\002," "i4,\002, NX =\002,i4,\002, NRHS =\002,i4)"; static char fmt_9973[] = "(/1x,71(\002-\002))"; static char fmt_9996[] = "(//1x,a3,\002: NB =\002,i4,\002, NBMIN =\002," "i4,\002, NS =\002,i4,\002, MAXB =\002,i4,\002, NBCOL =\002,i4)"; static char fmt_9966[] = "(//1x,a3,\002: NRHS =\002,i4)"; static char fmt_9994[] = "(//\002 End of tests\002)"; static char fmt_9993[] = "(\002 Total time used = \002,f12.2,\002 seco" "nds\002,/)"; /* System generated locals */ integer i__1; real r__1; /* Builtin functions */ integer s_rsfe(cilist *), do_fio(integer *, char *, ftnlen), e_rsfe(void); /* Subroutine */ int s_copy(char *, char *, ftnlen, ftnlen); integer s_cmp(char *, char *, ftnlen, ftnlen), s_wsfe(cilist *), e_wsfe( void), s_rsle(cilist *), do_lio(integer *, integer *, char *, ftnlen), e_rsle(void), s_wsle(cilist *), e_wsle(void); /* Subroutine */ int s_stop(char *, ftnlen); integer i_len(char *, ftnlen); /* Local variables */ static char line[80]; static real taua[132]; static integer info; static char path[3]; static integer kval[20], lenp, mval[20], nval[20]; static real taub[132]; static integer pval[20], itmp, nrhs; static real work[87781], a[243936] /* was [17424][14] */, b[87120] /* was [17424][5] */, c__[160000] /* was [400][400] */, d__[ 1584] /* was [132][12] */; static integer i__, k; static logical fatal; static real x[660]; static integer iseed[4], nbcol[20], nbval[20], nbmin[20]; static char vname[6]; static integer newsd, nsval[20]; static char c1[1], c3[3]; static integer nxval[20], i1, iwork[89760]; static real s1, s2; static integer ic, nk, nn; extern /* Subroutine */ int schkbb_(integer *, integer *, integer *, integer *, integer *, integer *, logical *, integer *, integer *, real *, integer *, real *, integer *, real *, integer *, real *, real *, real *, integer *, real *, integer *, real *, integer *, real *, real *, integer *, real *, integer *), schkbd_(integer *, integer *, integer *, integer *, logical *, integer *, integer *, real *, real *, integer *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, integer *, real *, integer *, real *, real *, real *, integer *, integer *, integer *, integer * ), schkec_(real *, logical *, integer *, integer *), alareq_(char *, integer *, logical *, integer *, integer *, integer *), schkbk_(integer *, integer *); extern doublereal slamch_(char *); extern /* Subroutine */ int schkbl_(integer *, integer *), schkgg_( integer *, integer *, integer *, logical *, integer *, real *, logical *, real *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, logical *, real *, integer *), schkgk_(integer *, integer *); extern doublereal second_(void); extern /* Subroutine */ int schkgl_(integer *, integer *), schksb_( integer *, integer *, integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real *, real *, real *, integer *, real *, integer *, real *, integer *); extern logical lsamen_(integer *, char *, char *); extern /* Subroutine */ int sckglm_(integer *, integer *, integer *, integer *, integer *, integer *, real *, integer *, real *, real * , real *, real *, real *, real *, real *, integer *, integer *, integer *), serrbd_(char *, integer *), schkhs_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, logical *, real *, integer *), scklse_(integer *, integer *, integer *, integer *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *), sdrvbd_(integer *, integer *, integer *, integer *, logical *, integer *, real *, real *, integer *, real * , integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *, integer * ), serred_(char *, integer *), sdrges_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, real *, integer *, real *, logical *, integer *); static integer mxbval[20]; extern /* Subroutine */ int sckgqr_(integer *, integer *, integer *, integer *, integer *, integer *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *), sdrgev_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real * , real *, real *, real *, integer *, real *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, integer *), sdrvgg_(integer *, integer *, integer *, logical *, integer *, real *, real *, integer *, real *, integer * , real *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, integer *); static logical tstdif; static real thresh; extern /* Subroutine */ int schkst_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real * , real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, real *, integer *, integer *, integer *, real *, integer *); static logical tstchk; static integer nparms; extern /* Subroutine */ int sckgsv_(integer *, integer *, integer *, integer *, integer *, integer *, real *, integer *, real *, real * , real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, integer *, integer *, integer *), serrgg_(char *, integer *); static logical dotype[30], logwrk[132]; static real thrshn; extern /* Subroutine */ int sdrves_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real * , real *, real *, real *, real *, real *, real *, integer *, real *, real *, integer *, integer *, logical *, integer *), sdrvev_( integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, integer *, real *, integer *, real *, integer *, real *, real *, integer *, integer *, integer *), sdrgsx_(integer *, integer *, real *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, integer *, integer *, integer * , logical *, integer *), sdrvsg_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real * , integer *, real *, real *, integer *, real *, real *, real *, real *, real *, integer *, integer *, integer *, real *, integer * ), serrhs_(char *, integer *), sdrgvx_(integer *, real *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *, real *, logical *, integer *); static real result[500]; extern /* Subroutine */ int xlaenv_(integer *, integer *); static integer maxtyp; static logical tsterr; static integer ntypes; static logical tstdrv; extern /* Subroutine */ int sdrvst_(integer *, integer *, integer *, logical *, integer *, real *, integer *, real *, integer *, real * , real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, real *, integer *, integer *, integer *, real *, integer *), serrst_(char *, integer *), sdrvsx_(integer *, integer *, integer *, logical *, integer *, real *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, real *, real *, real *, integer *, integer *, logical *, integer *), sdrvvx_(integer *, integer *, integer *, logical *, integer *, real *, integer *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, integer *, real *, integer *, real *, integer *, real *, real *, real *, real *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *); static logical sbb, glm, sbk, sbl, nep, lse, sgg, sep, sgk, gqr, ses, sgl, sgs, sev, ssb, gsv, sgv, sgx, svd; static real eps; static logical ssx, svx, sxv; /* Fortran I/O blocks */ static cilist io___5 = { 0, 5, 1, "(A80)", 0 }; static cilist io___30 = { 0, 6, 0, fmt_9987, 0 }; static cilist io___31 = { 0, 6, 0, fmt_9986, 0 }; static cilist io___32 = { 0, 6, 0, fmt_9985, 0 }; static cilist io___33 = { 0, 6, 0, fmt_9979, 0 }; static cilist io___34 = { 0, 6, 0, fmt_9978, 0 }; static cilist io___35 = { 0, 6, 0, fmt_9977, 0 }; static cilist io___36 = { 0, 6, 0, fmt_9976, 0 }; static cilist io___37 = { 0, 6, 0, fmt_9975, 0 }; static cilist io___38 = { 0, 6, 0, fmt_9964, 0 }; static cilist io___39 = { 0, 6, 0, fmt_9965, 0 }; static cilist io___40 = { 0, 6, 0, fmt_9963, 0 }; static cilist io___41 = { 0, 6, 0, fmt_9962, 0 }; static cilist io___42 = { 0, 6, 0, fmt_9974, 0 }; static cilist io___43 = { 0, 6, 0, fmt_9967, 0 }; static cilist io___44 = { 0, 6, 0, fmt_9971, 0 }; static cilist io___45 = { 0, 6, 0, fmt_9970, 0 }; static cilist io___46 = { 0, 6, 0, fmt_9969, 0 }; static cilist io___47 = { 0, 6, 0, fmt_9968, 0 }; static cilist io___48 = { 0, 5, 0, 0, 0 }; static cilist io___51 = { 0, 6, 0, fmt_9992, 0 }; static cilist io___52 = { 0, 6, 0, fmt_9972, 0 }; static cilist io___53 = { 0, 6, 0, fmt_9984, 0 }; static cilist io___54 = { 0, 5, 0, 0, 0 }; static cilist io___56 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___57 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___58 = { 0, 5, 0, 0, 0 }; static cilist io___62 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___63 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___64 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___65 = { 0, 5, 0, 0, 0 }; static cilist io___67 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___68 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___69 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___70 = { 0, 5, 0, 0, 0 }; static cilist io___72 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___73 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___74 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___75 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___76 = { 0, 5, 0, 0, 0 }; static cilist io___78 = { 0, 5, 0, 0, 0 }; static cilist io___80 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___81 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___82 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___83 = { 0, 5, 0, 0, 0 }; static cilist io___89 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___90 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___91 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___92 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___93 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___94 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___95 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___96 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___97 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___98 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___99 = { 0, 5, 0, 0, 0 }; static cilist io___101 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___102 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___103 = { 0, 5, 0, 0, 0 }; static cilist io___104 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___105 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___106 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___107 = { 0, 5, 0, 0, 0 }; static cilist io___108 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___109 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___110 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___111 = { 0, 5, 0, 0, 0 }; static cilist io___112 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___113 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___114 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___115 = { 0, 5, 0, 0, 0 }; static cilist io___116 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___117 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___118 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___119 = { 0, 5, 0, 0, 0 }; static cilist io___120 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___121 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___122 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___123 = { 0, 5, 0, 0, 0 }; static cilist io___125 = { 0, 6, 0, fmt_9989, 0 }; static cilist io___126 = { 0, 6, 0, fmt_9988, 0 }; static cilist io___127 = { 0, 6, 0, fmt_9983, 0 }; static cilist io___128 = { 0, 6, 0, 0, 0 }; static cilist io___130 = { 0, 6, 0, fmt_9981, 0 }; static cilist io___131 = { 0, 6, 0, fmt_9981, 0 }; static cilist io___132 = { 0, 6, 0, fmt_9981, 0 }; static cilist io___133 = { 0, 5, 0, 0, 0 }; static cilist io___134 = { 0, 6, 0, fmt_9982, 0 }; static cilist io___135 = { 0, 5, 0, 0, 0 }; static cilist io___137 = { 0, 5, 0, 0, 0 }; static cilist io___139 = { 0, 5, 0, 0, 0 }; static cilist io___140 = { 0, 5, 0, 0, 0 }; static cilist io___142 = { 0, 5, 0, 0, 0 }; static cilist io___144 = { 0, 6, 0, fmt_9999, 0 }; static cilist io___145 = { 0, 5, 1, "(A80)", 0 }; static cilist io___154 = { 0, 6, 0, fmt_9991, 0 }; static cilist io___155 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___158 = { 0, 6, 0, fmt_9998, 0 }; static cilist io___166 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___167 = { 0, 6, 0, fmt_9997, 0 }; static cilist io___168 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___169 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___170 = { 0, 6, 0, fmt_9997, 0 }; static cilist io___171 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___173 = { 0, 6, 0, fmt_9995, 0 }; static cilist io___174 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___175 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___176 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___177 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___178 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___179 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___180 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___181 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___182 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___183 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___184 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___185 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___186 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___187 = { 0, 6, 0, fmt_9996, 0 }; static cilist io___190 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___191 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___192 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___193 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___194 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___195 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___197 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___198 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___199 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___200 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___201 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___202 = { 0, 6, 0, fmt_9990, 0 }; static cilist io___203 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___204 = { 0, 6, 0, fmt_9973, 0 }; static cilist io___205 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___206 = { 0, 6, 0, fmt_9966, 0 }; static cilist io___207 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___210 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___213 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___214 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___215 = { 0, 6, 0, fmt_9980, 0 }; static cilist io___216 = { 0, 6, 0, 0, 0 }; static cilist io___217 = { 0, 6, 0, 0, 0 }; static cilist io___218 = { 0, 6, 0, fmt_9992, 0 }; static cilist io___219 = { 0, 6, 0, fmt_9994, 0 }; static cilist io___221 = { 0, 6, 0, fmt_9993, 0 }; #define a_ref(a_1,a_2) a[(a_2)*17424 + a_1 - 17425] #define b_ref(a_1,a_2) b[(a_2)*17424 + a_1 - 17425] #define c___ref(a_1,a_2) c__[(a_2)*400 + a_1 - 401] #define d___ref(a_1,a_2) d__[(a_2)*132 + a_1 - 133] /* -- LAPACK test routine (version 3.0) -- Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., Courant Institute, Argonne National Lab, and Rice University June 30, 1999 Purpose ======= SCHKEE tests the REAL LAPACK subroutines for the matrix eigenvalue problem. The test paths in this version are NEP (Nonsymmetric Eigenvalue Problem): Test SGEHRD, SORGHR, SHSEQR, STREVC, SHSEIN, and SORMHR SEP (Symmetric Eigenvalue Problem): Test SSYTRD, SORGTR, SSTEQR, SSTERF, SSTEIN, SSTEDC, and drivers SSYEV(X), SSBEV(X), SSPEV(X), SSTEV(X), SSYEVD, SSBEVD, SSPEVD, SSTEVD SVD (Singular Value Decomposition): Test SGEBRD, SORGBR, SBDSQR, SBDSDC and the drivers SGESVD, SGESDD SEV (Nonsymmetric Eigenvalue/eigenvector Driver): Test SGEEV SES (Nonsymmetric Schur form Driver): Test SGEES SVX (Nonsymmetric Eigenvalue/eigenvector Expert Driver): Test SGEEVX SSX (Nonsymmetric Schur form Expert Driver): Test SGEESX SGG (Generalized Nonsymmetric Eigenvalue Problem): Test SGGHRD, SGGBAL, SGGBAK, SHGEQZ, and STGEVC and the driver routines SGEGS and SGEGV SGS (Generalized Nonsymmetric Schur form Driver): Test SGGES SGV (Generalized Nonsymmetric Eigenvalue/eigenvector Driver): Test SGGEV SGX (Generalized Nonsymmetric Schur form Expert Driver): Test SGGESX SXV (Generalized Nonsymmetric Eigenvalue/eigenvector Expert Driver): Test SGGEVX SSG (Symmetric Generalized Eigenvalue Problem): Test SSYGST, SSYGV, SSYGVD, SSYGVX, SSPGST, SSPGV, SSPGVD, SSPGVX, SSBGST, SSBGV, SSBGVD, and SSBGVX SSB (Symmetric Band Eigenvalue Problem): Test SSBTRD SBB (Band Singular Value Decomposition): Test SGBBRD SEC (Eigencondition estimation): Test SLALN2, SLASY2, SLAEQU, SLAEXC, STRSYL, STREXC, STRSNA, STRSEN, and SLAQTR SBL (Balancing a general matrix) Test SGEBAL SBK (Back transformation on a balanced matrix) Test SGEBAK SGL (Balancing a matrix pair) Test SGGBAL SGK (Back transformation on a matrix pair) Test SGGBAK GLM (Generalized Linear Regression Model): Tests SGGGLM GQR (Generalized QR and RQ factorizations): Tests SGGQRF and SGGRQF GSV (Generalized Singular Value Decomposition): Tests SGGSVD, SGGSVP, STGSJA, SLAGS2, SLAPLL, and SLAPMT LSE (Constrained Linear Least Squares): Tests SGGLSE Each test path has a different set of inputs, but the data sets for the driver routines xEV, xES, xVX, and xSX can be concatenated in a single input file. The first line of input should contain one of the 3-character path names in columns 1-3. The number of remaining lines depends on what is found on the first line. The number of matrix types used in testing is often controllable from the input file. The number of matrix types for each path, and the test routine that describes them, is as follows: Path name(s) Types Test routine SHS or NEP 21 SCHKHS SST or SEP 21 SCHKST (routines) 18 SDRVST (drivers) SBD or SVD 16 SCHKBD (routines) 5 SDRVBD (drivers) SEV 21 SDRVEV SES 21 SDRVES SVX 21 SDRVVX SSX 21 SDRVSX SGG 26 SCHKGG (routines) 26 SDRVGG (drivers) SGS 26 SDRGES SGX 5 SDRGSX SGV 26 SDRGEV SXV 2 SDRGVX SSG 21 SDRVSG SSB 15 SCHKSB SBB 15 SCHKBB SEC - SCHKEC SBL - SCHKBL SBK - SCHKBK SGL - SCHKGL SGK - SCHKGK GLM 8 SCKGLM GQR 8 SCKGQR GSV 8 SCKGSV LSE 8 SCKLSE ----------------------------------------------------------------------- NEP input file: line 2: NN, INTEGER Number of values of N. line 3: NVAL, INTEGER array, dimension (NN) The values for the matrix dimension N. line 4: NPARMS, INTEGER Number of values of the parameters NB, NBMIN, NX, NS, and MAXB. line 5: NBVAL, INTEGER array, dimension (NPARMS) The values for the blocksize NB. line 6: NBMIN, INTEGER array, dimension (NPARMS) The values for the minimum blocksize NBMIN. line 7: NXVAL, INTEGER array, dimension (NPARMS) The values for the crossover point NX. line 8: NSVAL, INTEGER array, dimension (NPARMS) The values for the number of shifts. line 9: MXBVAL, INTEGER array, dimension (NPARMS) The values for MAXB, used in determining minimum blocksize. line 10: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. To have all of the test ratios printed, use THRESH = 0.0 . line 11: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 11 was 2: line 12: INTEGER array, dimension (4) Four integer values for the random number seed. lines 12-EOF: The remaining lines occur in sets of 1 or 2 and allow the user to specify the matrix types. Each line contains a 3-character path name in columns 1-3, and the number of matrix types must be the first nonblank item in columns 4-80. If the number of matrix types is at least 1 but is less than the maximum number of possible types, a second line will be read to get the numbers of the matrix types to be used. For example, NEP 21 requests all of the matrix types for the nonsymmetric eigenvalue problem, while NEP 4 9 10 11 12 requests only matrices of type 9, 10, 11, and 12. The valid 3-character path names are 'NEP' or 'SHS' for the nonsymmetric eigenvalue routines. ----------------------------------------------------------------------- SEP or SSG input file: line 2: NN, INTEGER Number of values of N. line 3: NVAL, INTEGER array, dimension (NN) The values for the matrix dimension N. line 4: NPARMS, INTEGER Number of values of the parameters NB, NBMIN, and NX. line 5: NBVAL, INTEGER array, dimension (NPARMS) The values for the blocksize NB. line 6: NBMIN, INTEGER array, dimension (NPARMS) The values for the minimum blocksize NBMIN. line 7: NXVAL, INTEGER array, dimension (NPARMS) The values for the crossover point NX. line 8: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 9: TSTCHK, LOGICAL Flag indicating whether or not to test the LAPACK routines. line 10: TSTDRV, LOGICAL Flag indicating whether or not to test the driver routines. line 11: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 12: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 12 was 2: line 13: INTEGER array, dimension (4) Four integer values for the random number seed. lines 13-EOF: Lines specifying matrix types, as for NEP. The 3-character path names are 'SEP' or 'SST' for the symmetric eigenvalue routines and driver routines, and 'SSG' for the routines for the symmetric generalized eigenvalue problem. ----------------------------------------------------------------------- SVD input file: line 2: NN, INTEGER Number of values of M and N. line 3: MVAL, INTEGER array, dimension (NN) The values for the matrix row dimension M. line 4: NVAL, INTEGER array, dimension (NN) The values for the matrix column dimension N. line 5: NPARMS, INTEGER Number of values of the parameter NB, NBMIN, NX, and NRHS. line 6: NBVAL, INTEGER array, dimension (NPARMS) The values for the blocksize NB. line 7: NBMIN, INTEGER array, dimension (NPARMS) The values for the minimum blocksize NBMIN. line 8: NXVAL, INTEGER array, dimension (NPARMS) The values for the crossover point NX. line 9: NSVAL, INTEGER array, dimension (NPARMS) The values for the number of right hand sides NRHS. line 10: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 11: TSTCHK, LOGICAL Flag indicating whether or not to test the LAPACK routines. line 12: TSTDRV, LOGICAL Flag indicating whether or not to test the driver routines. line 13: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 14: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 14 was 2: line 15: INTEGER array, dimension (4) Four integer values for the random number seed. lines 15-EOF: Lines specifying matrix types, as for NEP. The 3-character path names are 'SVD' or 'SBD' for both the SVD routines and the SVD driver routines. ----------------------------------------------------------------------- SEV and SES data files: line 1: 'SEV' or 'SES' in columns 1 to 3. line 2: NSIZES, INTEGER Number of sizes of matrices to use. Should be at least 0 and at most 20. If NSIZES = 0, no testing is done (although the remaining 3 lines are still read). line 3: NN, INTEGER array, dimension(NSIZES) Dimensions of matrices to be tested. line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs These integer parameters determine how blocking is done (see ILAENV for details) NB : block size NBMIN : minimum block size NX : minimum dimension for blocking NS : number of shifts in xHSEQR NBCOL : minimum column dimension for blocking line 5: THRESH, REAL The test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. If it is 0., all test case data will be printed. line 6: TSTERR, LOGICAL Flag indicating whether or not to test the error exits. line 7: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 7 was 2: line 8: INTEGER array, dimension (4) Four integer values for the random number seed. lines 9 and following: Lines specifying matrix types, as for NEP. The 3-character path name is 'SEV' to test SGEEV, or 'SES' to test SGEES. ----------------------------------------------------------------------- The SVX data has two parts. The first part is identical to SEV, and the second part consists of test matrices with precomputed solutions. line 1: 'SVX' in columns 1-3. line 2: NSIZES, INTEGER If NSIZES = 0, no testing of randomly generated examples is done, but any precomputed examples are tested. line 3: NN, INTEGER array, dimension(NSIZES) line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs line 5: THRESH, REAL line 6: TSTERR, LOGICAL line 7: NEWSD, INTEGER If line 7 was 2: line 8: INTEGER array, dimension (4) lines 9 and following: The first line contains 'SVX' in columns 1-3 followed by the number of matrix types, possibly with a second line to specify certain matrix types. If the number of matrix types = 0, no testing of randomly generated examples is done, but any precomputed examples are tested. remaining lines : Each matrix is stored on 1+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next N lines contain the matrix, one row per line. The last N lines correspond to each eigenvalue. Each of these last N lines contains 4 real values: the real part of the eigenvalue, the imaginary part of the eigenvalue, the reciprocal condition number of the eigenvalues, and the reciprocal condition number of the eigenvector. The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. ----------------------------------------------------------------------- The SSX data is like SVX. The first part is identical to SEV, and the second part consists of test matrices with precomputed solutions. line 1: 'SSX' in columns 1-3. line 2: NSIZES, INTEGER If NSIZES = 0, no testing of randomly generated examples is done, but any precomputed examples are tested. line 3: NN, INTEGER array, dimension(NSIZES) line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs line 5: THRESH, REAL line 6: TSTERR, LOGICAL line 7: NEWSD, INTEGER If line 7 was 2: line 8: INTEGER array, dimension (4) lines 9 and following: The first line contains 'SSX' in columns 1-3 followed by the number of matrix types, possibly with a second line to specify certain matrix types. If the number of matrix types = 0, no testing of randomly generated examples is done, but any precomputed examples are tested. remaining lines : Each matrix is stored on 3+N lines, where N is its dimension. The first line contains the dimension N and the dimension M of an invariant subspace. The second line contains M integers, identifying the eigenvalues in the invariant subspace (by their position in a list of eigenvalues ordered by increasing real part). The next N lines contain the matrix. The last line contains the reciprocal condition number for the average of the selected eigenvalues, and the reciprocal condition number for the corresponding right invariant subspace. The end of data is indicated by a line containing N=0 and M=0. Even if no data is to be tested, there must be at least one line containing N=0 and M=0. ----------------------------------------------------------------------- SGG input file: line 2: NN, INTEGER Number of values of N. line 3: NVAL, INTEGER array, dimension (NN) The values for the matrix dimension N. line 4: NPARMS, INTEGER Number of values of the parameters NB, NBMIN, NS, MAXB, and NBCOL. line 5: NBVAL, INTEGER array, dimension (NPARMS) The values for the blocksize NB. line 6: NBMIN, INTEGER array, dimension (NPARMS) The values for NBMIN, the minimum row dimension for blocks. line 7: NSVAL, INTEGER array, dimension (NPARMS) The values for the number of shifts. line 8: MXBVAL, INTEGER array, dimension (NPARMS) The values for MAXB, used in determining minimum blocksize. line 9: NBCOL, INTEGER array, dimension (NPARMS) The values for NBCOL, the minimum column dimension for blocks. line 10: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 11: TSTCHK, LOGICAL Flag indicating whether or not to test the LAPACK routines. line 12: TSTDRV, LOGICAL Flag indicating whether or not to test the driver routines. line 13: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 14: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 14 was 2: line 15: INTEGER array, dimension (4) Four integer values for the random number seed. lines 15-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'SGG' for the generalized eigenvalue problem routines and driver routines. ----------------------------------------------------------------------- SGS and SGV input files: line 1: 'SGS' or 'SGV' in columns 1 to 3. line 2: NN, INTEGER Number of values of N. line 3: NVAL, INTEGER array, dimension(NN) Dimensions of matrices to be tested. line 4: NB, NBMIN, NX, NS, NBCOL, INTEGERs These integer parameters determine how blocking is done (see ILAENV for details) NB : block size NBMIN : minimum block size NX : minimum dimension for blocking NS : number of shifts in xHGEQR NBCOL : minimum column dimension for blocking line 5: THRESH, REAL The test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. If it is 0., all test case data will be printed. line 6: TSTERR, LOGICAL Flag indicating whether or not to test the error exits. line 7: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 17 was 2: line 7: INTEGER array, dimension (4) Four integer values for the random number seed. lines 7-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'SGS' for the generalized eigenvalue problem routines and driver routines. ----------------------------------------------------------------------- SXV input files: line 1: 'SXV' in columns 1 to 3. line 2: N, INTEGER Value of N. line 3: NB, NBMIN, NX, NS, NBCOL, INTEGERs These integer parameters determine how blocking is done (see ILAENV for details) NB : block size NBMIN : minimum block size NX : minimum dimension for blocking NS : number of shifts in xHGEQR NBCOL : minimum column dimension for blocking line 4: THRESH, REAL The test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 5: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 6: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 6 was 2: line 7: INTEGER array, dimension (4) Four integer values for the random number seed. If line 2 was 0: line 7-EOF: Precomputed examples are tested. remaining lines : Each example is stored on 3+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next N lines contain the matrix A, one row per line. The next N lines contain the matrix B. The next line contains the reciprocals of the eigenvalue condition numbers. The last line contains the reciprocals of the eigenvector condition numbers. The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. ----------------------------------------------------------------------- SGX input files: line 1: 'SGX' in columns 1 to 3. line 2: N, INTEGER Value of N. line 3: NB, NBMIN, NX, NS, NBCOL, INTEGERs These integer parameters determine how blocking is done (see ILAENV for details) NB : block size NBMIN : minimum block size NX : minimum dimension for blocking NS : number of shifts in xHGEQR NBCOL : minimum column dimension for blocking line 4: THRESH, REAL The test threshold against which computed residuals are compared. Should generally be in the range from 10. to 20. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 5: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 6: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 6 was 2: line 7: INTEGER array, dimension (4) Four integer values for the random number seed. If line 2 was 0: line 7-EOF: Precomputed examples are tested. remaining lines : Each example is stored on 3+2*N lines, where N is its dimension. The first line contains the dimension (a single integer). The next line contains an integer k such that only the last k eigenvalues will be selected and appear in the leading diagonal blocks of $A$ and $B$. The next N lines contain the matrix A, one row per line. The next N lines contain the matrix B. The last line contains the reciprocal of the eigenvalue cluster condition number and the reciprocal of the deflating subspace (associated with the selected eigencluster) condition number. The end of data is indicated by dimension N=0. Even if no data is to be tested, there must be at least one line containing N=0. ----------------------------------------------------------------------- SSB input file: line 2: NN, INTEGER Number of values of N. line 3: NVAL, INTEGER array, dimension (NN) The values for the matrix dimension N. line 4: NK, INTEGER Number of values of K. line 5: KVAL, INTEGER array, dimension (NK) The values for the matrix dimension K. line 6: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 7: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 7 was 2: line 8: INTEGER array, dimension (4) Four integer values for the random number seed. lines 8-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'SSB'. ----------------------------------------------------------------------- SBB input file: line 2: NN, INTEGER Number of values of M and N. line 3: MVAL, INTEGER array, dimension (NN) The values for the matrix row dimension M. line 4: NVAL, INTEGER array, dimension (NN) The values for the matrix column dimension N. line 4: NK, INTEGER Number of values of K. line 5: KVAL, INTEGER array, dimension (NK) The values for the matrix bandwidth K. line 6: NPARMS, INTEGER Number of values of the parameter NRHS line 7: NSVAL, INTEGER array, dimension (NPARMS) The values for the number of right hand sides NRHS. line 8: THRESH Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 9: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 9 was 2: line 10: INTEGER array, dimension (4) Four integer values for the random number seed. lines 10-EOF: Lines specifying matrix types, as for SVD. The 3-character path name is 'SBB'. ----------------------------------------------------------------------- SEC input file: line 2: THRESH, REAL Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. lines 3-EOF: Input for testing the eigencondition routines consists of a set of specially constructed test cases and their solutions. The data format is not intended to be modified by the user. ----------------------------------------------------------------------- SBL and SBK input files: line 1: 'SBL' in columns 1-3 to test SGEBAL, or 'SBK' in columns 1-3 to test SGEBAK. The remaining lines consist of specially constructed test cases. ----------------------------------------------------------------------- SGL and SGK input files: line 1: 'SGL' in columns 1-3 to test SGGBAL, or 'SGK' in columns 1-3 to test SGGBAK. The remaining lines consist of specially constructed test cases. ----------------------------------------------------------------------- GLM data file: line 1: 'GLM' in columns 1 to 3. line 2: NN, INTEGER Number of values of M, P, and N. line 3: MVAL, INTEGER array, dimension(NN) Values of M (row dimension). line 4: PVAL, INTEGER array, dimension(NN) Values of P (row dimension). line 5: NVAL, INTEGER array, dimension(NN) Values of N (column dimension), note M <= N <= M+P. line 6: THRESH, REAL Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 7: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 8: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 8 was 2: line 9: INTEGER array, dimension (4) Four integer values for the random number seed. lines 9-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'GLM' for the generalized linear regression model routines. ----------------------------------------------------------------------- GQR data file: line 1: 'GQR' in columns 1 to 3. line 2: NN, INTEGER Number of values of M, P, and N. line 3: MVAL, INTEGER array, dimension(NN) Values of M. line 4: PVAL, INTEGER array, dimension(NN) Values of P. line 5: NVAL, INTEGER array, dimension(NN) Values of N. line 6: THRESH, REAL Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 7: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 8: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 8 was 2: line 9: INTEGER array, dimension (4) Four integer values for the random number seed. lines 9-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'GQR' for the generalized QR and RQ routines. ----------------------------------------------------------------------- GSV data file: line 1: 'GSV' in columns 1 to 3. line 2: NN, INTEGER Number of values of M, P, and N. line 3: MVAL, INTEGER array, dimension(NN) Values of M (row dimension). line 4: PVAL, INTEGER array, dimension(NN) Values of P (row dimension). line 5: NVAL, INTEGER array, dimension(NN) Values of N (column dimension). line 6: THRESH, REAL Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 7: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 8: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 8 was 2: line 9: INTEGER array, dimension (4) Four integer values for the random number seed. lines 9-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'GSV' for the generalized SVD routines. ----------------------------------------------------------------------- LSE data file: line 1: 'LSE' in columns 1 to 3. line 2: NN, INTEGER Number of values of M, P, and N. line 3: MVAL, INTEGER array, dimension(NN) Values of M. line 4: PVAL, INTEGER array, dimension(NN) Values of P. line 5: NVAL, INTEGER array, dimension(NN) Values of N, note P <= N <= P+M. line 6: THRESH, REAL Threshold value for the test ratios. Information will be printed about each test for which the test ratio is greater than or equal to the threshold. line 7: TSTERR, LOGICAL Flag indicating whether or not to test the error exits for the LAPACK routines and driver routines. line 8: NEWSD, INTEGER A code indicating how to set the random number seed. = 0: Set the seed to a default value before each run = 1: Initialize the seed to a default value only before the first run = 2: Like 1, but use the seed values on the next line If line 8 was 2: line 9: INTEGER array, dimension (4) Four integer values for the random number seed. lines 9-EOF: Lines specifying matrix types, as for NEP. The 3-character path name is 'GSV' for the generalized SVD routines. ----------------------------------------------------------------------- NMAX is currently set to 132 and must be at least 12 for some of the precomputed examples, and LWORK = NMAX*(5*NMAX+5)+1 in the parameter statements below. For SVD, we assume NRHS may be as big as N. The parameter NEED is set to 14 to allow for 14 N-by-N matrices for SGG. ===================================================================== */ s1 = second_(); fatal = FALSE_; infoc_1.nunit = 6; /* Return to here to read multiple sets of data */ L10: /* Read the first line and set the 3-character test path */ i__1 = s_rsfe(&io___5); if (i__1 != 0) { goto L380; } i__1 = do_fio(&c__1, line, (ftnlen)80); if (i__1 != 0) { goto L380; } i__1 = e_rsfe(); if (i__1 != 0) { goto L380; } s_copy(path, line, (ftnlen)3, (ftnlen)3); nep = lsamen_(&c__3, path, "NEP") || lsamen_(&c__3, path, "SHS"); sep = lsamen_(&c__3, path, "SEP") || lsamen_(&c__3, path, "SST") || lsamen_(&c__3, path, "SSG"); svd = lsamen_(&c__3, path, "SVD") || lsamen_(&c__3, path, "SBD"); sev = lsamen_(&c__3, path, "SEV"); ses = lsamen_(&c__3, path, "SES"); svx = lsamen_(&c__3, path, "SVX"); ssx = lsamen_(&c__3, path, "SSX"); sgg = lsamen_(&c__3, path, "SGG"); sgs = lsamen_(&c__3, path, "SGS"); sgx = lsamen_(&c__3, path, "SGX"); sgv = lsamen_(&c__3, path, "SGV"); sxv = lsamen_(&c__3, path, "SXV"); ssb = lsamen_(&c__3, path, "SSB"); sbb = lsamen_(&c__3, path, "SBB"); glm = lsamen_(&c__3, path, "GLM"); gqr = lsamen_(&c__3, path, "GQR") || lsamen_(&c__3, path, "GRQ"); gsv = lsamen_(&c__3, path, "GSV"); lse = lsamen_(&c__3, path, "LSE"); sbl = lsamen_(&c__3, path, "SBL"); sbk = lsamen_(&c__3, path, "SBK"); sgl = lsamen_(&c__3, path, "SGL"); sgk = lsamen_(&c__3, path, "SGK"); /* Report values of parameters. */ if (s_cmp(path, " ", (ftnlen)3, (ftnlen)3) == 0) { goto L10; } else if (nep) { s_wsfe(&io___30); e_wsfe(); } else if (sep) { s_wsfe(&io___31); e_wsfe(); } else if (svd) { s_wsfe(&io___32); e_wsfe(); } else if (sev) { s_wsfe(&io___33); e_wsfe(); } else if (ses) { s_wsfe(&io___34); e_wsfe(); } else if (svx) { s_wsfe(&io___35); e_wsfe(); } else if (ssx) { s_wsfe(&io___36); e_wsfe(); } else if (sgg) { s_wsfe(&io___37); e_wsfe(); } else if (sgs) { s_wsfe(&io___38); e_wsfe(); } else if (sgx) { s_wsfe(&io___39); e_wsfe(); } else if (sgv) { s_wsfe(&io___40); e_wsfe(); } else if (sxv) { s_wsfe(&io___41); e_wsfe(); } else if (ssb) { s_wsfe(&io___42); e_wsfe(); } else if (sbb) { s_wsfe(&io___43); e_wsfe(); } else if (glm) { s_wsfe(&io___44); e_wsfe(); } else if (gqr) { s_wsfe(&io___45); e_wsfe(); } else if (gsv) { s_wsfe(&io___46); e_wsfe(); } else if (lse) { s_wsfe(&io___47); e_wsfe(); } else if (sbl) { /* SGEBAL: Balancing */ schkbl_(&c__5, &c__6); goto L10; } else if (sbk) { /* SGEBAK: Back transformation */ schkbk_(&c__5, &c__6); goto L10; } else if (sgl) { /* SGGBAL: Balancing */ schkgl_(&c__5, &c__6); goto L10; } else if (sgk) { /* SGGBAK: Back transformation */ schkgk_(&c__5, &c__6); goto L10; } else if (lsamen_(&c__3, path, "SEC")) { /* SEC: Eigencondition estimation */ s_rsle(&io___48); do_lio(&c__4, &c__1, (char *)&thresh, (ftnlen)sizeof(real)); e_rsle(); tsterr = TRUE_; schkec_(&thresh, &tsterr, &c__5, &c__6); goto L10; } else { s_wsfe(&io___51); do_fio(&c__1, path, (ftnlen)3); e_wsfe(); goto L10; } s_wsfe(&io___52); e_wsfe(); s_wsfe(&io___53); e_wsfe(); /* Read the number of values of M, P, and N. */ s_rsle(&io___54); do_lio(&c__3, &c__1, (char *)&nn, (ftnlen)sizeof(integer)); e_rsle(); if (nn < 0) { s_wsfe(&io___56); do_fio(&c__1, " NN ", (ftnlen)6); do_fio(&c__1, (char *)&nn, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); nn = 0; fatal = TRUE_; } else if (nn > 20) { s_wsfe(&io___57); do_fio(&c__1, " NN ", (ftnlen)6); do_fio(&c__1, (char *)&nn, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__20, (ftnlen)sizeof(integer)); e_wsfe(); nn = 0; fatal = TRUE_; } /* Read the values of M */ if (! (sgx || sxv)) { s_rsle(&io___58); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&mval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); if (svd) { s_copy(vname, " M ", (ftnlen)6, (ftnlen)6); } else { s_copy(vname, " N ", (ftnlen)6, (ftnlen)6); } i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { if (mval[i__ - 1] < 0) { s_wsfe(&io___62); do_fio(&c__1, vname, (ftnlen)6); do_fio(&c__1, (char *)&mval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (mval[i__ - 1] > 132) { s_wsfe(&io___63); do_fio(&c__1, vname, (ftnlen)6); do_fio(&c__1, (char *)&mval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L20: */ } s_wsfe(&io___64); do_fio(&c__1, "M: ", (ftnlen)6); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&mval[i__ - 1], (ftnlen)sizeof(integer)); } e_wsfe(); } /* Read the values of P */ if (glm || gqr || gsv || lse) { s_rsle(&io___65); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&pval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { if (pval[i__ - 1] < 0) { s_wsfe(&io___67); do_fio(&c__1, " P ", (ftnlen)4); do_fio(&c__1, (char *)&pval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (pval[i__ - 1] > 132) { s_wsfe(&io___68); do_fio(&c__1, " P ", (ftnlen)4); do_fio(&c__1, (char *)&pval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L30: */ } s_wsfe(&io___69); do_fio(&c__1, "P: ", (ftnlen)6); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&pval[i__ - 1], (ftnlen)sizeof(integer)); } e_wsfe(); } /* Read the values of N */ if (svd || sbb || glm || gqr || gsv || lse) { s_rsle(&io___70); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { if (nval[i__ - 1] < 0) { s_wsfe(&io___72); do_fio(&c__1, " N ", (ftnlen)6); do_fio(&c__1, (char *)&nval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nval[i__ - 1] > 132) { s_wsfe(&io___73); do_fio(&c__1, " N ", (ftnlen)6); do_fio(&c__1, (char *)&nval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L40: */ } } else { i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { nval[i__ - 1] = mval[i__ - 1]; /* L50: */ } } if (! (sgx || sxv)) { s_wsfe(&io___74); do_fio(&c__1, "N: ", (ftnlen)6); i__1 = nn; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nval[i__ - 1], (ftnlen)sizeof(integer)); } e_wsfe(); } else { s_wsfe(&io___75); do_fio(&c__1, "N: ", (ftnlen)6); do_fio(&c__1, (char *)&nn, (ftnlen)sizeof(integer)); e_wsfe(); } /* Read the number of values of K, followed by the values of K */ if (ssb || sbb) { s_rsle(&io___76); do_lio(&c__3, &c__1, (char *)&nk, (ftnlen)sizeof(integer)); e_rsle(); s_rsle(&io___78); i__1 = nk; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&kval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nk; for (i__ = 1; i__ <= i__1; ++i__) { if (kval[i__ - 1] < 0) { s_wsfe(&io___80); do_fio(&c__1, " K ", (ftnlen)6); do_fio(&c__1, (char *)&kval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (kval[i__ - 1] > 132) { s_wsfe(&io___81); do_fio(&c__1, " K ", (ftnlen)6); do_fio(&c__1, (char *)&kval[i__ - 1], (ftnlen)sizeof(integer)) ; do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L60: */ } s_wsfe(&io___82); do_fio(&c__1, "K: ", (ftnlen)6); i__1 = nk; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&kval[i__ - 1], (ftnlen)sizeof(integer)); } e_wsfe(); } if (sev || ses || svx || ssx || sgs || sgx || sgv || sxv) { /* For the nonsymmetric driver routines, only one set of parameters is allowed. */ s_rsle(&io___83); do_lio(&c__3, &c__1, (char *)&nbval[0], (ftnlen)sizeof(integer)); do_lio(&c__3, &c__1, (char *)&nbmin[0], (ftnlen)sizeof(integer)); do_lio(&c__3, &c__1, (char *)&nxval[0], (ftnlen)sizeof(integer)); do_lio(&c__3, &c__1, (char *)&nsval[0], (ftnlen)sizeof(integer)); do_lio(&c__3, &c__1, (char *)&mxbval[0], (ftnlen)sizeof(integer)); e_rsle(); if (nbval[0] < 1) { s_wsfe(&io___89); do_fio(&c__1, " NB ", (ftnlen)6); do_fio(&c__1, (char *)&nbval[0], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nbmin[0] < 1) { s_wsfe(&io___90); do_fio(&c__1, "NBMIN ", (ftnlen)6); do_fio(&c__1, (char *)&nbmin[0], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nxval[0] < 1) { s_wsfe(&io___91); do_fio(&c__1, " NX ", (ftnlen)6); do_fio(&c__1, (char *)&nxval[0], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nsval[0] < 2) { s_wsfe(&io___92); do_fio(&c__1, " NS ", (ftnlen)6); do_fio(&c__1, (char *)&nsval[0], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__2, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (mxbval[0] < 1) { s_wsfe(&io___93); do_fio(&c__1, " MAXB ", (ftnlen)6); do_fio(&c__1, (char *)&mxbval[0], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } xlaenv_(&c__1, nbval); xlaenv_(&c__2, nbmin); xlaenv_(&c__3, nxval); xlaenv_(&c__4, nsval); xlaenv_(&c__8, mxbval); s_wsfe(&io___94); do_fio(&c__1, "NB: ", (ftnlen)6); do_fio(&c__1, (char *)&nbval[0], (ftnlen)sizeof(integer)); e_wsfe(); s_wsfe(&io___95); do_fio(&c__1, "NBMIN:", (ftnlen)6); do_fio(&c__1, (char *)&nbmin[0], (ftnlen)sizeof(integer)); e_wsfe(); s_wsfe(&io___96); do_fio(&c__1, "NX: ", (ftnlen)6); do_fio(&c__1, (char *)&nxval[0], (ftnlen)sizeof(integer)); e_wsfe(); s_wsfe(&io___97); do_fio(&c__1, "NS: ", (ftnlen)6); do_fio(&c__1, (char *)&nsval[0], (ftnlen)sizeof(integer)); e_wsfe(); s_wsfe(&io___98); do_fio(&c__1, "MAXB: ", (ftnlen)6); do_fio(&c__1, (char *)&mxbval[0], (ftnlen)sizeof(integer)); e_wsfe(); } else if (! ssb && ! glm && ! gqr && ! gsv && ! lse) { /* For the other paths, the number of parameters can be varied from the input file. Read the number of parameter values. */ s_rsle(&io___99); do_lio(&c__3, &c__1, (char *)&nparms, (ftnlen)sizeof(integer)); e_rsle(); if (nparms < 1) { s_wsfe(&io___101); do_fio(&c__1, "NPARMS", (ftnlen)6); do_fio(&c__1, (char *)&nparms, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__1, (ftnlen)sizeof(integer)); e_wsfe(); nparms = 0; fatal = TRUE_; } else if (nparms > 20) { s_wsfe(&io___102); do_fio(&c__1, "NPARMS", (ftnlen)6); do_fio(&c__1, (char *)&nparms, (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&c__20, (ftnlen)sizeof(integer)); e_wsfe(); nparms = 0; fatal = TRUE_; } /* Read the values of NB */ if (! sbb) { s_rsle(&io___103); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (nbval[i__ - 1] < 0) { s_wsfe(&io___104); do_fio(&c__1, " NB ", (ftnlen)6); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nbval[i__ - 1] > 132) { s_wsfe(&io___105); do_fio(&c__1, " NB ", (ftnlen)6); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L70: */ } s_wsfe(&io___106); do_fio(&c__1, "NB: ", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer) ); } e_wsfe(); } /* Read the values of NBMIN */ if (nep || sep || svd || sgg) { s_rsle(&io___107); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (nbmin[i__ - 1] < 0) { s_wsfe(&io___108); do_fio(&c__1, "NBMIN ", (ftnlen)6); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nbmin[i__ - 1] > 132) { s_wsfe(&io___109); do_fio(&c__1, "NBMIN ", (ftnlen)6); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L80: */ } s_wsfe(&io___110); do_fio(&c__1, "NBMIN:", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer) ); } e_wsfe(); } else { i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nbmin[i__ - 1] = 1; /* L90: */ } } /* Read the values of NX */ if (nep || sep || svd) { s_rsle(&io___111); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (nxval[i__ - 1] < 0) { s_wsfe(&io___112); do_fio(&c__1, " NX ", (ftnlen)6); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nxval[i__ - 1] > 132) { s_wsfe(&io___113); do_fio(&c__1, " NX ", (ftnlen)6); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L100: */ } s_wsfe(&io___114); do_fio(&c__1, "NX: ", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof(integer) ); } e_wsfe(); } else { i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nxval[i__ - 1] = 1; /* L110: */ } } /* Read the values of NSHIFT (if NEP or SGG) or NRHS (if SVD or SBB). */ if (nep || svd || sbb || sgg) { s_rsle(&io___115); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (nsval[i__ - 1] < 0) { s_wsfe(&io___116); do_fio(&c__1, " NS ", (ftnlen)6); do_fio(&c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nsval[i__ - 1] > 132) { s_wsfe(&io___117); do_fio(&c__1, " NS ", (ftnlen)6); do_fio(&c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L120: */ } s_wsfe(&io___118); do_fio(&c__1, "NS: ", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof(integer) ); } e_wsfe(); } else { i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nsval[i__ - 1] = 1; /* L130: */ } } /* Read the values for MAXB. */ if (nep || sgg) { s_rsle(&io___119); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (mxbval[i__ - 1] < 0) { s_wsfe(&io___120); do_fio(&c__1, " MAXB ", (ftnlen)6); do_fio(&c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (mxbval[i__ - 1] > 132) { s_wsfe(&io___121); do_fio(&c__1, " MAXB ", (ftnlen)6); do_fio(&c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L140: */ } s_wsfe(&io___122); do_fio(&c__1, "MAXB: ", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof( integer)); } e_wsfe(); } else { i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { mxbval[i__ - 1] = 1; /* L150: */ } } /* Read the values for NBCOL. */ if (sgg) { s_rsle(&io___123); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_lio(&c__3, &c__1, (char *)&nbcol[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { if (nbcol[i__ - 1] < 0) { s_wsfe(&io___125); do_fio(&c__1, "NBCOL ", (ftnlen)6); do_fio(&c__1, (char *)&nbcol[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__0, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } else if (nbcol[i__ - 1] > 132) { s_wsfe(&io___126); do_fio(&c__1, "NBCOL ", (ftnlen)6); do_fio(&c__1, (char *)&nbcol[i__ - 1], (ftnlen)sizeof( integer)); do_fio(&c__1, (char *)&c__132, (ftnlen)sizeof(integer)); e_wsfe(); fatal = TRUE_; } /* L160: */ } s_wsfe(&io___127); do_fio(&c__1, "NBCOL:", (ftnlen)6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { do_fio(&c__1, (char *)&nbcol[i__ - 1], (ftnlen)sizeof(integer) ); } e_wsfe(); } else { i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nbcol[i__ - 1] = 1; /* L170: */ } } } /* Calculate and print the machine dependent constants. */ s_wsle(&io___128); e_wsle(); eps = slamch_("Underflow threshold"); s_wsfe(&io___130); do_fio(&c__1, "underflow", (ftnlen)9); do_fio(&c__1, (char *)&eps, (ftnlen)sizeof(real)); e_wsfe(); eps = slamch_("Overflow threshold"); s_wsfe(&io___131); do_fio(&c__1, "overflow ", (ftnlen)9); do_fio(&c__1, (char *)&eps, (ftnlen)sizeof(real)); e_wsfe(); eps = slamch_("Epsilon"); s_wsfe(&io___132); do_fio(&c__1, "precision", (ftnlen)9); do_fio(&c__1, (char *)&eps, (ftnlen)sizeof(real)); e_wsfe(); /* Read the threshold value for the test ratios. */ s_rsle(&io___133); do_lio(&c__4, &c__1, (char *)&thresh, (ftnlen)sizeof(real)); e_rsle(); s_wsfe(&io___134); do_fio(&c__1, (char *)&thresh, (ftnlen)sizeof(real)); e_wsfe(); if (sep || svd || sgg) { /* Read the flag that indicates whether to test LAPACK routines. */ s_rsle(&io___135); do_lio(&c__8, &c__1, (char *)&tstchk, (ftnlen)sizeof(logical)); e_rsle(); /* Read the flag that indicates whether to test driver routines. */ s_rsle(&io___137); do_lio(&c__8, &c__1, (char *)&tstdrv, (ftnlen)sizeof(logical)); e_rsle(); } /* Read the flag that indicates whether to test the error exits. */ s_rsle(&io___139); do_lio(&c__8, &c__1, (char *)&tsterr, (ftnlen)sizeof(logical)); e_rsle(); /* Read the code describing how to set the random number seed. */ s_rsle(&io___140); do_lio(&c__3, &c__1, (char *)&newsd, (ftnlen)sizeof(integer)); e_rsle(); /* If NEWSD = 2, read another line with 4 integers for the seed. */ if (newsd == 2) { s_rsle(&io___142); for (i__ = 1; i__ <= 4; ++i__) { do_lio(&c__3, &c__1, (char *)&ioldsd[i__ - 1], (ftnlen)sizeof( integer)); } e_rsle(); } for (i__ = 1; i__ <= 4; ++i__) { iseed[i__ - 1] = ioldsd[i__ - 1]; /* L180: */ } if (fatal) { s_wsfe(&io___144); e_wsfe(); s_stop("", (ftnlen)0); } /* Read the input lines indicating the test path and its parameters. The first three characters indicate the test path, and the number of test matrix types must be the first nonblank item in columns 4-80. */ L190: if (! (sgx || sxv)) { L200: i__1 = s_rsfe(&io___145); if (i__1 != 0) { goto L380; } i__1 = do_fio(&c__1, line, (ftnlen)80); if (i__1 != 0) { goto L380; } i__1 = e_rsfe(); if (i__1 != 0) { goto L380; } s_copy(c3, line, (ftnlen)3, (ftnlen)3); lenp = i_len(line, (ftnlen)80); i__ = 3; itmp = 0; i1 = 0; L210: ++i__; if (i__ > lenp) { if (i1 > 0) { goto L240; } else { ntypes = 30; goto L240; } } if (*(unsigned char *)&line[i__ - 1] != ' ' && *(unsigned char *)& line[i__ - 1] != ',') { i1 = i__; *(unsigned char *)c1 = *(unsigned char *)&line[i1 - 1]; /* Check that a valid integer was read */ for (k = 1; k <= 10; ++k) { if (*(unsigned char *)c1 == *(unsigned char *)&intstr[k - 1]) { ic = k - 1; goto L230; } /* L220: */ } s_wsfe(&io___154); do_fio(&c__1, (char *)&i__, (ftnlen)sizeof(integer)); do_fio(&c__1, line, (ftnlen)80); e_wsfe(); goto L200; L230: itmp = itmp * 10 + ic; goto L210; } else if (i1 > 0) { goto L240; } else { goto L210; } L240: ntypes = itmp; /* Skip the tests if NTYPES is <= 0. */ if (! (sev || ses || svx || ssx || sgv || sgs) && ntypes <= 0) { s_wsfe(&io___155); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); goto L200; } } else { if (sxv) { s_copy(c3, "SXV", (ftnlen)3, (ftnlen)3); } if (sgx) { s_copy(c3, "SGX", (ftnlen)3, (ftnlen)3); } } /* Reset the random number seed. */ if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L250: */ } } if (lsamen_(&c__3, c3, "SHS") || lsamen_(&c__3, c3, "NEP")) { /* ------------------------------------- NEP: Nonsymmetric Eigenvalue Problem ------------------------------------- Vary the parameters NB = block size NBMIN = minimum block size NX = crossover point NS = number of shifts MAXB = minimum submatrix size */ maxtyp = 21; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); if (tsterr) { serrhs_("SHSEQR", &c__6); } i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { xlaenv_(&c__1, &nbval[i__ - 1]); xlaenv_(&c__2, &nbmin[i__ - 1]); xlaenv_(&c__3, &nxval[i__ - 1]); xlaenv_(&c__4, &nsval[i__ - 1]); xlaenv_(&c__8, &mxbval[i__ - 1]); if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L260: */ } } s_wsfe(&io___158); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof(integer)); e_wsfe(); schkhs_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &c__6, &a_ref( 1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 5), &c__132, &a_ref(1, 6), &a_ref(1, 7), & d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &a_ref(1, 8), &a_ref(1, 9), &a_ref(1, 10), &a_ref(1, 11), &a_ref(1, 12), &d___ref(1, 5), work, &c__87781, iwork, logwrk, result, &info); if (info != 0) { s_wsfe(&io___166); do_fio(&c__1, "SCHKHS", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } /* L270: */ } } else if (lsamen_(&c__3, c3, "SST") || lsamen_(& c__3, c3, "SEP")) { /* ---------------------------------- SEP: Symmetric Eigenvalue Problem ---------------------------------- Vary the parameters NB = block size NBMIN = minimum block size NX = crossover point */ maxtyp = 21; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); xlaenv_(&c__9, &c__25); if (tsterr) { serrst_("SST", &c__6); } i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { xlaenv_(&c__1, &nbval[i__ - 1]); xlaenv_(&c__2, &nbmin[i__ - 1]); xlaenv_(&c__3, &nxval[i__ - 1]); if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L280: */ } } s_wsfe(&io___167); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof(integer)); e_wsfe(); if (tstchk) { schkst_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &c__6, & a_ref(1, 1), &c__132, &a_ref(1, 2), &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), & d___ref(1, 5), &d___ref(1, 6), &d___ref(1, 7), & d___ref(1, 8), &d___ref(1, 9), &d___ref(1, 10), & d___ref(1, 11), &a_ref(1, 3), &c__132, &a_ref(1, 4), & a_ref(1, 5), &d___ref(1, 12), &a_ref(1, 6), work, & c__87781, iwork, &c__89760, result, &info); if (info != 0) { s_wsfe(&io___168); do_fio(&c__1, "SCHKST", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } if (tstdrv) { sdrvst_(&nn, nval, &c__18, dotype, iseed, &thresh, &c__6, & a_ref(1, 1), &c__132, &d___ref(1, 3), &d___ref(1, 4), &d___ref(1, 5), &d___ref(1, 6), &d___ref(1, 8), & d___ref(1, 9), &d___ref(1, 10), &d___ref(1, 11), & a_ref(1, 2), &c__132, &a_ref(1, 3), &d___ref(1, 12), & a_ref(1, 4), work, &c__87781, iwork, &c__89760, result, &info); if (info != 0) { s_wsfe(&io___169); do_fio(&c__1, "SDRVST", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } /* L290: */ } } else if (lsamen_(&c__3, c3, "SSG")) { /* ---------------------------------------------- SSG: Symmetric Generalized Eigenvalue Problem ---------------------------------------------- Vary the parameters NB = block size NBMIN = minimum block size NX = crossover point */ maxtyp = 21; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); xlaenv_(&c__9, &c__25); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { xlaenv_(&c__1, &nbval[i__ - 1]); xlaenv_(&c__2, &nbmin[i__ - 1]); xlaenv_(&c__3, &nxval[i__ - 1]); if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L300: */ } } s_wsfe(&io___170); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof(integer)); e_wsfe(); if (tstchk) { sdrvsg_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &c__6, & a_ref(1, 1), &c__132, &a_ref(1, 2), &c__132, &d___ref( 1, 3), &a_ref(1, 3), &c__132, &a_ref(1, 4), &a_ref(1, 5), &a_ref(1, 6), &a_ref(1, 7), work, &c__87781, iwork, &c__89760, result, &info); if (info != 0) { s_wsfe(&io___171); do_fio(&c__1, "SDRVSG", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } /* L310: */ } } else if (lsamen_(&c__3, c3, "SBD") || lsamen_(& c__3, c3, "SVD")) { /* ---------------------------------- SVD: Singular Value Decomposition ---------------------------------- Vary the parameters NB = block size NBMIN = minimum block size NX = crossover point NRHS = number of right hand sides */ maxtyp = 16; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); xlaenv_(&c__9, &c__25); /* Test the error exits */ if (tsterr && tstchk) { serrbd_("SBD", &c__6); } if (tsterr && tstdrv) { serred_("SBD", &c__6); } i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nrhs = nsval[i__ - 1]; xlaenv_(&c__1, &nbval[i__ - 1]); xlaenv_(&c__2, &nbmin[i__ - 1]); xlaenv_(&c__3, &nxval[i__ - 1]); if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L320: */ } } s_wsfe(&io___173); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nxval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nrhs, (ftnlen)sizeof(integer)); e_wsfe(); if (tstchk) { schkbd_(&nn, mval, nval, &maxtyp, dotype, &nrhs, iseed, & thresh, &a_ref(1, 1), &c__132, &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &a_ref( 1, 2), &c__132, &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 5), &c__132, &a_ref(1, 6), &c__132, &a_ref(1, 7), & a_ref(1, 8), work, &c__87781, iwork, &c__6, &info); if (info != 0) { s_wsfe(&io___174); do_fio(&c__1, "SCHKBD", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } if (tstdrv) { sdrvbd_(&nn, mval, nval, &maxtyp, dotype, iseed, &thresh, & a_ref(1, 1), &c__132, &a_ref(1, 2), &c__132, &a_ref(1, 3), &c__132, &a_ref(1, 4), &a_ref(1, 5), &a_ref(1, 6) , &d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), work, &c__87781, iwork, &c__6, &info); } /* L330: */ } } else if (lsamen_(&c__3, c3, "SEV")) { /* -------------------------------------------- SEV: Nonsymmetric Eigenvalue Problem Driver SGEEV (eigenvalues and eigenvectors) -------------------------------------------- */ maxtyp = 21; ntypes = min(maxtyp,ntypes); if (ntypes <= 0) { s_wsfe(&io___175); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serred_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrvev_(&nn, nval, &ntypes, dotype, iseed, &thresh, &c__6, &a_ref( 1, 1), &c__132, &a_ref(1, 2), &d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &a_ref(1, 3), &c__132, &a_ref(1, 4), &c__132, &a_ref(1, 5), &c__132, result, work, &c__87781, iwork, &info); if (info != 0) { s_wsfe(&io___176); do_fio(&c__1, "SGEEV", (ftnlen)5); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___177); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SES")) { /* -------------------------------------------- SES: Nonsymmetric Eigenvalue Problem Driver SGEES (Schur form) -------------------------------------------- */ maxtyp = 21; ntypes = min(maxtyp,ntypes); if (ntypes <= 0) { s_wsfe(&io___178); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serred_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrves_(&nn, nval, &ntypes, dotype, iseed, &thresh, &c__6, &a_ref( 1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &d___ref(1, 1) , &d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &a_ref( 1, 4), &c__132, result, work, &c__87781, iwork, logwrk, & info); if (info != 0) { s_wsfe(&io___179); do_fio(&c__1, "SGEES", (ftnlen)5); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___180); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SVX")) { /* -------------------------------------------------------------- SVX: Nonsymmetric Eigenvalue Problem Expert Driver SGEEVX (eigenvalues, eigenvectors and condition numbers) -------------------------------------------------------------- */ maxtyp = 21; ntypes = min(maxtyp,ntypes); if (ntypes < 0) { s_wsfe(&io___181); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serred_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrvvx_(&nn, nval, &ntypes, dotype, iseed, &thresh, &c__5, &c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &a_ref(1, 3), &c__132, &a_ref(1, 4), &c__132, &a_ref(1, 5), &c__132, &d___ref(1, 5), &d___ref(1, 6), &d___ref(1, 7), &d___ref( 1, 8), &d___ref(1, 9), &d___ref(1, 10), &d___ref(1, 11), & d___ref(1, 12), result, work, &c__87781, iwork, &info); if (info != 0) { s_wsfe(&io___182); do_fio(&c__1, "SGEEVX", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___183); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SSX")) { /* --------------------------------------------------- SSX: Nonsymmetric Eigenvalue Problem Expert Driver SGEESX (Schur form and condition numbers) --------------------------------------------------- */ maxtyp = 21; ntypes = min(maxtyp,ntypes); if (ntypes < 0) { s_wsfe(&io___184); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serred_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrvsx_(&nn, nval, &ntypes, dotype, iseed, &thresh, &c__5, &c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), & d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &d___ref(1, 5), &d___ref(1, 6), &a_ref(1, 4), & c__132, &a_ref(1, 5), result, work, &c__87781, iwork, logwrk, &info); if (info != 0) { s_wsfe(&io___185); do_fio(&c__1, "SGEESX", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___186); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SGG")) { /* ------------------------------------------------- SGG: Generalized Nonsymmetric Eigenvalue Problem ------------------------------------------------- Vary the parameters NB = block size NBMIN = minimum block size NS = number of shifts MAXB = minimum submatrix size NBCOL = minimum column dimension for blocks */ maxtyp = 26; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); if (tstchk && tsterr) { serrgg_(c3, &c__6); } i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { xlaenv_(&c__1, &nbval[i__ - 1]); xlaenv_(&c__2, &nbmin[i__ - 1]); xlaenv_(&c__4, &nsval[i__ - 1]); xlaenv_(&c__8, &mxbval[i__ - 1]); xlaenv_(&c__5, &nbcol[i__ - 1]); if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L340: */ } } s_wsfe(&io___187); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbmin[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nsval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&mxbval[i__ - 1], (ftnlen)sizeof(integer)); do_fio(&c__1, (char *)&nbcol[i__ - 1], (ftnlen)sizeof(integer)); e_wsfe(); tstdif = FALSE_; thrshn = 10.f; if (tstchk) { schkgg_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &tstdif, & thrshn, &c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), & a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 5), &a_ref(1, 6), &a_ref(1, 7), &a_ref(1, 8), &a_ref(1, 9), &c__132, & a_ref(1, 10), &a_ref(1, 11), &a_ref(1, 12), &d___ref( 1, 1), &d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), &d___ref(1, 5), &d___ref(1, 6), &a_ref(1, 13), & a_ref(1, 14), work, &c__87781, logwrk, result, &info); if (info != 0) { s_wsfe(&io___190); do_fio(&c__1, "SCHKGG", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } if (tstdrv) { sdrvgg_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &thrshn, & c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 5), &a_ref(1, 6), &a_ref( 1, 7), &c__132, &a_ref(1, 8), &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), &d___ref(1, 4), & d___ref(1, 5), &d___ref(1, 6), &a_ref(1, 13), &a_ref( 1, 14), work, &c__87781, result, &info); if (info != 0) { s_wsfe(&io___191); do_fio(&c__1, "SDRVGG", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } /* L350: */ } } else if (lsamen_(&c__3, c3, "SGS")) { /* ------------------------------------------------- SGS: Generalized Nonsymmetric Eigenvalue Problem SGGES (Schur form) ------------------------------------------------- */ maxtyp = 26; ntypes = min(maxtyp,ntypes); if (ntypes <= 0) { s_wsfe(&io___192); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serrgg_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrges_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &c__6, &a_ref( 1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 7), &c__132, &a_ref(1, 8), &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), work, &c__87781, result, logwrk, &info); if (info != 0) { s_wsfe(&io___193); do_fio(&c__1, "SDRGES", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___194); e_wsfe(); goto L10; } else if (sgx) { /* ------------------------------------------------- SGX: Generalized Nonsymmetric Eigenvalue Problem SGGESX (Schur form and condition numbers) ------------------------------------------------- */ maxtyp = 5; ntypes = maxtyp; if (nn < 0) { s_wsfe(&io___195); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serrgg_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrgsx_(&nn, &c__20, &thresh, &c__5, &c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 5), & a_ref(1, 6), &d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), &c___ref(1, 1), &c__400, &a_ref(1, 12), work, & c__87781, iwork, &c__89760, logwrk, &info); if (info != 0) { s_wsfe(&io___197); do_fio(&c__1, "SDRGSX", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___198); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SGV")) { /* ------------------------------------------------- SGV: Generalized Nonsymmetric Eigenvalue Problem SGGEV (Eigenvalue/vector form) ------------------------------------------------- */ maxtyp = 26; ntypes = min(maxtyp,ntypes); if (ntypes <= 0) { s_wsfe(&io___199); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serrgg_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrgev_(&nn, nval, &maxtyp, dotype, iseed, &thresh, &c__6, &a_ref( 1, 1), &c__132, &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4), &a_ref(1, 7), &c__132, &a_ref(1, 8), &a_ref(1, 9), & c__132, &d___ref(1, 1), &d___ref(1, 2), &d___ref(1, 3), & d___ref(1, 4), &d___ref(1, 5), &d___ref(1, 6), work, & c__87781, result, &info); if (info != 0) { s_wsfe(&io___200); do_fio(&c__1, "SDRGEV", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___201); e_wsfe(); goto L10; } else if (sxv) { /* ------------------------------------------------- SXV: Generalized Nonsymmetric Eigenvalue Problem SGGEVX (eigenvalue/vector with condition numbers) ------------------------------------------------- */ maxtyp = 2; ntypes = maxtyp; if (nn < 0) { s_wsfe(&io___202); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } else { if (tsterr) { serrgg_(c3, &c__6); } alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); sdrgvx_(&nn, &thresh, &c__5, &c__6, &a_ref(1, 1), &c__132, &a_ref( 1, 2), &a_ref(1, 3), &a_ref(1, 4), &d___ref(1, 1), & d___ref(1, 2), &d___ref(1, 3), &a_ref(1, 5), &a_ref(1, 6), iwork, &iwork[1], &d___ref(1, 4), &d___ref(1, 5), & d___ref(1, 6), &d___ref(1, 7), &d___ref(1, 8), &d___ref(1, 9), work, &c__87781, &iwork[2], &c__89758, result, logwrk, &info); if (info != 0) { s_wsfe(&io___203); do_fio(&c__1, "SDRGVX", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } s_wsfe(&io___204); e_wsfe(); goto L10; } else if (lsamen_(&c__3, c3, "SSB")) { /* ------------------------------ SSB: Symmetric Band Reduction ------------------------------ */ maxtyp = 15; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); if (tsterr) { serrst_("SSB", &c__6); } schksb_(&nn, nval, &nk, kval, &maxtyp, dotype, iseed, &thresh, &c__6, &a_ref(1, 1), &c__132, &d___ref(1, 1), &d___ref(1, 2), &a_ref( 1, 2), &c__132, work, &c__87781, result, &info); if (info != 0) { s_wsfe(&io___205); do_fio(&c__1, "SCHKSB", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } else if (lsamen_(&c__3, c3, "SBB")) { /* ------------------------------ SBB: General Band Reduction ------------------------------ */ maxtyp = 15; ntypes = min(maxtyp,ntypes); alareq_(c3, &ntypes, dotype, &maxtyp, &c__5, &c__6); i__1 = nparms; for (i__ = 1; i__ <= i__1; ++i__) { nrhs = nsval[i__ - 1]; if (newsd == 0) { for (k = 1; k <= 4; ++k) { iseed[k - 1] = ioldsd[k - 1]; /* L360: */ } } s_wsfe(&io___206); do_fio(&c__1, c3, (ftnlen)3); do_fio(&c__1, (char *)&nrhs, (ftnlen)sizeof(integer)); e_wsfe(); schkbb_(&nn, mval, nval, &nk, kval, &maxtyp, dotype, &nrhs, iseed, &thresh, &c__6, &a_ref(1, 1), &c__132, &a_ref(1, 2), & c__264, &d___ref(1, 1), &d___ref(1, 2), &a_ref(1, 4), & c__132, &a_ref(1, 5), &c__132, &a_ref(1, 6), &c__132, & a_ref(1, 7), work, &c__87781, result, &info); if (info != 0) { s_wsfe(&io___207); do_fio(&c__1, "SCHKBB", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } /* L370: */ } } else if (lsamen_(&c__3, c3, "GLM")) { /* ----------------------------------------- GLM: Generalized Linear Regression Model ----------------------------------------- */ if (tsterr) { serrgg_("GLM", &c__6); } sckglm_(&nn, mval, pval, nval, &ntypes, iseed, &thresh, &c__132, & a_ref(1, 1), &a_ref(1, 2), &b_ref(1, 1), &b_ref(1, 2), x, work, &d___ref(1, 1), &c__5, &c__6, &info); if (info != 0) { s_wsfe(&io___210); do_fio(&c__1, "SCKGLM", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } else if (lsamen_(&c__3, c3, "GQR")) { /* ------------------------------------------ GQR: Generalized QR and RQ factorizations ------------------------------------------ */ if (tsterr) { serrgg_("GQR", &c__6); } sckgqr_(&nn, mval, &nn, pval, &nn, nval, &ntypes, iseed, &thresh, & c__132, &a_ref(1, 1), &a_ref(1, 2), &a_ref(1, 3), &a_ref(1, 4) , taua, &b_ref(1, 1), &b_ref(1, 2), &b_ref(1, 3), &b_ref(1, 4) , &b_ref(1, 5), taub, work, &d___ref(1, 1), &c__5, &c__6, & info); if (info != 0) { s_wsfe(&io___213); do_fio(&c__1, "SCKGQR", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } else if (lsamen_(&c__3, c3, "GSV")) { /* ---------------------------------------------- GSV: Generalized Singular Value Decomposition ---------------------------------------------- */ if (tsterr) { serrgg_("GSV", &c__6); } sckgsv_(&nn, mval, pval, nval, &ntypes, iseed, &thresh, &c__132, & a_ref(1, 1), &a_ref(1, 2), &b_ref(1, 1), &b_ref(1, 2), &a_ref( 1, 3), &b_ref(1, 3), &a_ref(1, 4), taua, taub, &b_ref(1, 4), iwork, work, &d___ref(1, 1), &c__5, &c__6, &info); if (info != 0) { s_wsfe(&io___214); do_fio(&c__1, "SCKGSV", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } else if (lsamen_(&c__3, c3, "LSE")) { /* -------------------------------------- LSE: Constrained Linear Least Squares -------------------------------------- */ if (tsterr) { serrgg_("LSE", &c__6); } scklse_(&nn, mval, pval, nval, &ntypes, iseed, &thresh, &c__132, & a_ref(1, 1), &a_ref(1, 2), &b_ref(1, 1), &b_ref(1, 2), x, work, &d___ref(1, 1), &c__5, &c__6, &info); if (info != 0) { s_wsfe(&io___215); do_fio(&c__1, "SCKLSE", (ftnlen)6); do_fio(&c__1, (char *)&info, (ftnlen)sizeof(integer)); e_wsfe(); } } else { s_wsle(&io___216); e_wsle(); s_wsle(&io___217); e_wsle(); s_wsfe(&io___218); do_fio(&c__1, c3, (ftnlen)3); e_wsfe(); } if (! (sgx || sxv)) { goto L190; } L380: s_wsfe(&io___219); e_wsfe(); s2 = second_(); s_wsfe(&io___221); r__1 = s2 - s1; do_fio(&c__1, (char *)&r__1, (ftnlen)sizeof(real)); e_wsfe(); /* End of SCHKEE */ return 0; } /* MAIN__ */ #undef d___ref #undef c___ref #undef b_ref #undef a_ref /* Main program alias */ int schkee_ () { MAIN__ (); return 0; }