00001 /* slarrr.f -- translated by f2c (version 20061008). 00002 You must link the resulting object file with libf2c: 00003 on Microsoft Windows system, link with libf2c.lib; 00004 on Linux or Unix systems, link with .../path/to/libf2c.a -lm 00005 or, if you install libf2c.a in a standard place, with -lf2c -lm 00006 -- in that order, at the end of the command line, as in 00007 cc *.o -lf2c -lm 00008 Source for libf2c is in /netlib/f2c/libf2c.zip, e.g., 00009 00010 http://www.netlib.org/f2c/libf2c.zip 00011 */ 00012 00013 #include "f2c.h" 00014 #include "blaswrap.h" 00015 00016 /* Subroutine */ int slarrr_(integer *n, real *d__, real *e, integer *info) 00017 { 00018 /* System generated locals */ 00019 integer i__1; 00020 real r__1; 00021 00022 /* Builtin functions */ 00023 double sqrt(doublereal); 00024 00025 /* Local variables */ 00026 integer i__; 00027 real eps, tmp, tmp2, rmin, offdig; 00028 extern doublereal slamch_(char *); 00029 real safmin; 00030 logical yesrel; 00031 real smlnum, offdig2; 00032 00033 00034 /* -- LAPACK auxiliary routine (version 3.2) -- */ 00035 /* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */ 00036 /* November 2006 */ 00037 00038 /* .. Scalar Arguments .. */ 00039 /* .. */ 00040 /* .. Array Arguments .. */ 00041 /* .. */ 00042 00043 00044 /* Purpose */ 00045 /* ======= */ 00046 00047 /* Perform tests to decide whether the symmetric tridiagonal matrix T */ 00048 /* warrants expensive computations which guarantee high relative accuracy */ 00049 /* in the eigenvalues. */ 00050 00051 /* Arguments */ 00052 /* ========= */ 00053 00054 /* N (input) INTEGER */ 00055 /* The order of the matrix. N > 0. */ 00056 00057 /* D (input) REAL array, dimension (N) */ 00058 /* The N diagonal elements of the tridiagonal matrix T. */ 00059 00060 /* E (input/output) REAL array, dimension (N) */ 00061 /* On entry, the first (N-1) entries contain the subdiagonal */ 00062 /* elements of the tridiagonal matrix T; E(N) is set to ZERO. */ 00063 00064 /* INFO (output) INTEGER */ 00065 /* INFO = 0(default) : the matrix warrants computations preserving */ 00066 /* relative accuracy. */ 00067 /* INFO = 1 : the matrix warrants computations guaranteeing */ 00068 /* only absolute accuracy. */ 00069 00070 /* Further Details */ 00071 /* =============== */ 00072 00073 /* Based on contributions by */ 00074 /* Beresford Parlett, University of California, Berkeley, USA */ 00075 /* Jim Demmel, University of California, Berkeley, USA */ 00076 /* Inderjit Dhillon, University of Texas, Austin, USA */ 00077 /* Osni Marques, LBNL/NERSC, USA */ 00078 /* Christof Voemel, University of California, Berkeley, USA */ 00079 00080 /* ===================================================================== */ 00081 00082 /* .. Parameters .. */ 00083 /* .. */ 00084 /* .. Local Scalars .. */ 00085 /* .. */ 00086 /* .. External Functions .. */ 00087 /* .. */ 00088 /* .. Intrinsic Functions .. */ 00089 /* .. */ 00090 /* .. Executable Statements .. */ 00091 00092 /* As a default, do NOT go for relative-accuracy preserving computations. */ 00093 /* Parameter adjustments */ 00094 --e; 00095 --d__; 00096 00097 /* Function Body */ 00098 *info = 1; 00099 safmin = slamch_("Safe minimum"); 00100 eps = slamch_("Precision"); 00101 smlnum = safmin / eps; 00102 rmin = sqrt(smlnum); 00103 /* Tests for relative accuracy */ 00104 00105 /* Test for scaled diagonal dominance */ 00106 /* Scale the diagonal entries to one and check whether the sum of the */ 00107 /* off-diagonals is less than one */ 00108 00109 /* The sdd relative error bounds have a 1/(1- 2*x) factor in them, */ 00110 /* x = max(OFFDIG + OFFDIG2), so when x is close to 1/2, no relative */ 00111 /* accuracy is promised. In the notation of the code fragment below, */ 00112 /* 1/(1 - (OFFDIG + OFFDIG2)) is the condition number. */ 00113 /* We don't think it is worth going into "sdd mode" unless the relative */ 00114 /* condition number is reasonable, not 1/macheps. */ 00115 /* The threshold should be compatible with other thresholds used in the */ 00116 /* code. We set OFFDIG + OFFDIG2 <= .999 =: RELCOND, it corresponds */ 00117 /* to losing at most 3 decimal digits: 1 / (1 - (OFFDIG + OFFDIG2)) <= 1000 */ 00118 /* instead of the current OFFDIG + OFFDIG2 < 1 */ 00119 00120 yesrel = TRUE_; 00121 offdig = 0.f; 00122 tmp = sqrt((dabs(d__[1]))); 00123 if (tmp < rmin) { 00124 yesrel = FALSE_; 00125 } 00126 if (! yesrel) { 00127 goto L11; 00128 } 00129 i__1 = *n; 00130 for (i__ = 2; i__ <= i__1; ++i__) { 00131 tmp2 = sqrt((r__1 = d__[i__], dabs(r__1))); 00132 if (tmp2 < rmin) { 00133 yesrel = FALSE_; 00134 } 00135 if (! yesrel) { 00136 goto L11; 00137 } 00138 offdig2 = (r__1 = e[i__ - 1], dabs(r__1)) / (tmp * tmp2); 00139 if (offdig + offdig2 >= .999f) { 00140 yesrel = FALSE_; 00141 } 00142 if (! yesrel) { 00143 goto L11; 00144 } 00145 tmp = tmp2; 00146 offdig = offdig2; 00147 /* L10: */ 00148 } 00149 L11: 00150 if (yesrel) { 00151 *info = 0; 00152 return 0; 00153 } else { 00154 } 00155 00156 00157 /* *** MORE TO BE IMPLEMENTED *** */ 00158 00159 00160 /* Test if the lower bidiagonal matrix L from T = L D L^T */ 00161 /* (zero shift facto) is well conditioned */ 00162 00163 00164 /* Test if the upper bidiagonal matrix U from T = U D U^T */ 00165 /* (zero shift facto) is well conditioned. */ 00166 /* In this case, the matrix needs to be flipped and, at the end */ 00167 /* of the eigenvector computation, the flip needs to be applied */ 00168 /* to the computed eigenvectors (and the support) */ 00169 00170 00171 return 0; 00172 00173 /* END OF SLARRR */ 00174 00175 } /* slarrr_ */