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dgesvdq.c 73 kB

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  1. #include <math.h>
  2. #include <stdlib.h>
  3. #include <string.h>
  4. #include <stdio.h>
  5. #include <complex.h>
  6. #ifdef complex
  7. #undef complex
  8. #endif
  9. #ifdef I
  10. #undef I
  11. #endif
  12. #if defined(_WIN64)
  13. typedef long long BLASLONG;
  14. typedef unsigned long long BLASULONG;
  15. #else
  16. typedef long BLASLONG;
  17. typedef unsigned long BLASULONG;
  18. #endif
  19. #ifdef LAPACK_ILP64
  20. typedef BLASLONG blasint;
  21. #if defined(_WIN64)
  22. #define blasabs(x) llabs(x)
  23. #else
  24. #define blasabs(x) labs(x)
  25. #endif
  26. #else
  27. typedef int blasint;
  28. #define blasabs(x) abs(x)
  29. #endif
  30. typedef blasint integer;
  31. typedef unsigned int uinteger;
  32. typedef char *address;
  33. typedef short int shortint;
  34. typedef float real;
  35. typedef double doublereal;
  36. typedef struct { real r, i; } complex;
  37. typedef struct { doublereal r, i; } doublecomplex;
  38. #ifdef _MSC_VER
  39. static inline _Fcomplex Cf(complex *z) {_Fcomplex zz={z->r , z->i}; return zz;}
  40. static inline _Dcomplex Cd(doublecomplex *z) {_Dcomplex zz={z->r , z->i};return zz;}
  41. static inline _Fcomplex * _pCf(complex *z) {return (_Fcomplex*)z;}
  42. static inline _Dcomplex * _pCd(doublecomplex *z) {return (_Dcomplex*)z;}
  43. #else
  44. static inline _Complex float Cf(complex *z) {return z->r + z->i*_Complex_I;}
  45. static inline _Complex double Cd(doublecomplex *z) {return z->r + z->i*_Complex_I;}
  46. static inline _Complex float * _pCf(complex *z) {return (_Complex float*)z;}
  47. static inline _Complex double * _pCd(doublecomplex *z) {return (_Complex double*)z;}
  48. #endif
  49. #define pCf(z) (*_pCf(z))
  50. #define pCd(z) (*_pCd(z))
  51. typedef int logical;
  52. typedef short int shortlogical;
  53. typedef char logical1;
  54. typedef char integer1;
  55. #define TRUE_ (1)
  56. #define FALSE_ (0)
  57. /* Extern is for use with -E */
  58. #ifndef Extern
  59. #define Extern extern
  60. #endif
  61. /* I/O stuff */
  62. typedef int flag;
  63. typedef int ftnlen;
  64. typedef int ftnint;
  65. /*external read, write*/
  66. typedef struct
  67. { flag cierr;
  68. ftnint ciunit;
  69. flag ciend;
  70. char *cifmt;
  71. ftnint cirec;
  72. } cilist;
  73. /*internal read, write*/
  74. typedef struct
  75. { flag icierr;
  76. char *iciunit;
  77. flag iciend;
  78. char *icifmt;
  79. ftnint icirlen;
  80. ftnint icirnum;
  81. } icilist;
  82. /*open*/
  83. typedef struct
  84. { flag oerr;
  85. ftnint ounit;
  86. char *ofnm;
  87. ftnlen ofnmlen;
  88. char *osta;
  89. char *oacc;
  90. char *ofm;
  91. ftnint orl;
  92. char *oblnk;
  93. } olist;
  94. /*close*/
  95. typedef struct
  96. { flag cerr;
  97. ftnint cunit;
  98. char *csta;
  99. } cllist;
  100. /*rewind, backspace, endfile*/
  101. typedef struct
  102. { flag aerr;
  103. ftnint aunit;
  104. } alist;
  105. /* inquire */
  106. typedef struct
  107. { flag inerr;
  108. ftnint inunit;
  109. char *infile;
  110. ftnlen infilen;
  111. ftnint *inex; /*parameters in standard's order*/
  112. ftnint *inopen;
  113. ftnint *innum;
  114. ftnint *innamed;
  115. char *inname;
  116. ftnlen innamlen;
  117. char *inacc;
  118. ftnlen inacclen;
  119. char *inseq;
  120. ftnlen inseqlen;
  121. char *indir;
  122. ftnlen indirlen;
  123. char *infmt;
  124. ftnlen infmtlen;
  125. char *inform;
  126. ftnint informlen;
  127. char *inunf;
  128. ftnlen inunflen;
  129. ftnint *inrecl;
  130. ftnint *innrec;
  131. char *inblank;
  132. ftnlen inblanklen;
  133. } inlist;
  134. #define VOID void
  135. union Multitype { /* for multiple entry points */
  136. integer1 g;
  137. shortint h;
  138. integer i;
  139. /* longint j; */
  140. real r;
  141. doublereal d;
  142. complex c;
  143. doublecomplex z;
  144. };
  145. typedef union Multitype Multitype;
  146. struct Vardesc { /* for Namelist */
  147. char *name;
  148. char *addr;
  149. ftnlen *dims;
  150. int type;
  151. };
  152. typedef struct Vardesc Vardesc;
  153. struct Namelist {
  154. char *name;
  155. Vardesc **vars;
  156. int nvars;
  157. };
  158. typedef struct Namelist Namelist;
  159. #define abs(x) ((x) >= 0 ? (x) : -(x))
  160. #define dabs(x) (fabs(x))
  161. #define f2cmin(a,b) ((a) <= (b) ? (a) : (b))
  162. #define f2cmax(a,b) ((a) >= (b) ? (a) : (b))
  163. #define dmin(a,b) (f2cmin(a,b))
  164. #define dmax(a,b) (f2cmax(a,b))
  165. #define bit_test(a,b) ((a) >> (b) & 1)
  166. #define bit_clear(a,b) ((a) & ~((uinteger)1 << (b)))
  167. #define bit_set(a,b) ((a) | ((uinteger)1 << (b)))
  168. #define abort_() { sig_die("Fortran abort routine called", 1); }
  169. #define c_abs(z) (cabsf(Cf(z)))
  170. #define c_cos(R,Z) { pCf(R)=ccos(Cf(Z)); }
  171. #ifdef _MSC_VER
  172. #define c_div(c, a, b) {Cf(c)._Val[0] = (Cf(a)._Val[0]/Cf(b)._Val[0]); Cf(c)._Val[1]=(Cf(a)._Val[1]/Cf(b)._Val[1]);}
  173. #define z_div(c, a, b) {Cd(c)._Val[0] = (Cd(a)._Val[0]/Cd(b)._Val[0]); Cd(c)._Val[1]=(Cd(a)._Val[1]/df(b)._Val[1]);}
  174. #else
  175. #define c_div(c, a, b) {pCf(c) = Cf(a)/Cf(b);}
  176. #define z_div(c, a, b) {pCd(c) = Cd(a)/Cd(b);}
  177. #endif
  178. #define c_exp(R, Z) {pCf(R) = cexpf(Cf(Z));}
  179. #define c_log(R, Z) {pCf(R) = clogf(Cf(Z));}
  180. #define c_sin(R, Z) {pCf(R) = csinf(Cf(Z));}
  181. //#define c_sqrt(R, Z) {*(R) = csqrtf(Cf(Z));}
  182. #define c_sqrt(R, Z) {pCf(R) = csqrtf(Cf(Z));}
  183. #define d_abs(x) (fabs(*(x)))
  184. #define d_acos(x) (acos(*(x)))
  185. #define d_asin(x) (asin(*(x)))
  186. #define d_atan(x) (atan(*(x)))
  187. #define d_atn2(x, y) (atan2(*(x),*(y)))
  188. #define d_cnjg(R, Z) { pCd(R) = conj(Cd(Z)); }
  189. #define r_cnjg(R, Z) { pCf(R) = conjf(Cf(Z)); }
  190. #define d_cos(x) (cos(*(x)))
  191. #define d_cosh(x) (cosh(*(x)))
  192. #define d_dim(__a, __b) ( *(__a) > *(__b) ? *(__a) - *(__b) : 0.0 )
  193. #define d_exp(x) (exp(*(x)))
  194. #define d_imag(z) (cimag(Cd(z)))
  195. #define r_imag(z) (cimagf(Cf(z)))
  196. #define d_int(__x) (*(__x)>0 ? floor(*(__x)) : -floor(- *(__x)))
  197. #define r_int(__x) (*(__x)>0 ? floor(*(__x)) : -floor(- *(__x)))
  198. #define d_lg10(x) ( 0.43429448190325182765 * log(*(x)) )
  199. #define r_lg10(x) ( 0.43429448190325182765 * log(*(x)) )
  200. #define d_log(x) (log(*(x)))
  201. #define d_mod(x, y) (fmod(*(x), *(y)))
  202. #define u_nint(__x) ((__x)>=0 ? floor((__x) + .5) : -floor(.5 - (__x)))
  203. #define d_nint(x) u_nint(*(x))
  204. #define u_sign(__a,__b) ((__b) >= 0 ? ((__a) >= 0 ? (__a) : -(__a)) : -((__a) >= 0 ? (__a) : -(__a)))
  205. #define d_sign(a,b) u_sign(*(a),*(b))
  206. #define r_sign(a,b) u_sign(*(a),*(b))
  207. #define d_sin(x) (sin(*(x)))
  208. #define d_sinh(x) (sinh(*(x)))
  209. #define d_sqrt(x) (sqrt(*(x)))
  210. #define d_tan(x) (tan(*(x)))
  211. #define d_tanh(x) (tanh(*(x)))
  212. #define i_abs(x) abs(*(x))
  213. #define i_dnnt(x) ((integer)u_nint(*(x)))
  214. #define i_len(s, n) (n)
  215. #define i_nint(x) ((integer)u_nint(*(x)))
  216. #define i_sign(a,b) ((integer)u_sign((integer)*(a),(integer)*(b)))
  217. #define pow_dd(ap, bp) ( pow(*(ap), *(bp)))
  218. #define pow_si(B,E) spow_ui(*(B),*(E))
  219. #define pow_ri(B,E) spow_ui(*(B),*(E))
  220. #define pow_di(B,E) dpow_ui(*(B),*(E))
  221. #define pow_zi(p, a, b) {pCd(p) = zpow_ui(Cd(a), *(b));}
  222. #define pow_ci(p, a, b) {pCf(p) = cpow_ui(Cf(a), *(b));}
  223. #define pow_zz(R,A,B) {pCd(R) = cpow(Cd(A),*(B));}
  224. #define s_cat(lpp, rpp, rnp, np, llp) { ftnlen i, nc, ll; char *f__rp, *lp; ll = (llp); lp = (lpp); for(i=0; i < (int)*(np); ++i) { nc = ll; if((rnp)[i] < nc) nc = (rnp)[i]; ll -= nc; f__rp = (rpp)[i]; while(--nc >= 0) *lp++ = *(f__rp)++; } while(--ll >= 0) *lp++ = ' '; }
  225. #define s_cmp(a,b,c,d) ((integer)strncmp((a),(b),f2cmin((c),(d))))
  226. #define s_copy(A,B,C,D) { int __i,__m; for (__i=0, __m=f2cmin((C),(D)); __i<__m && (B)[__i] != 0; ++__i) (A)[__i] = (B)[__i]; }
  227. #define sig_die(s, kill) { exit(1); }
  228. #define s_stop(s, n) {exit(0);}
  229. static char junk[] = "\n@(#)LIBF77 VERSION 19990503\n";
  230. #define z_abs(z) (cabs(Cd(z)))
  231. #define z_exp(R, Z) {pCd(R) = cexp(Cd(Z));}
  232. #define z_sqrt(R, Z) {pCd(R) = csqrt(Cd(Z));}
  233. #define myexit_() break;
  234. #define mycycle() continue;
  235. #define myceiling(w) {ceil(w)}
  236. #define myhuge(w) {HUGE_VAL}
  237. //#define mymaxloc_(w,s,e,n) {if (sizeof(*(w)) == sizeof(double)) dmaxloc_((w),*(s),*(e),n); else dmaxloc_((w),*(s),*(e),n);}
  238. #define mymaxloc(w,s,e,n) {dmaxloc_(w,*(s),*(e),n)}
  239. /* procedure parameter types for -A and -C++ */
  240. #define F2C_proc_par_types 1
  241. #ifdef __cplusplus
  242. typedef logical (*L_fp)(...);
  243. #else
  244. typedef logical (*L_fp)();
  245. #endif
  246. static float spow_ui(float x, integer n) {
  247. float pow=1.0; unsigned long int u;
  248. if(n != 0) {
  249. if(n < 0) n = -n, x = 1/x;
  250. for(u = n; ; ) {
  251. if(u & 01) pow *= x;
  252. if(u >>= 1) x *= x;
  253. else break;
  254. }
  255. }
  256. return pow;
  257. }
  258. static double dpow_ui(double x, integer n) {
  259. double pow=1.0; unsigned long int u;
  260. if(n != 0) {
  261. if(n < 0) n = -n, x = 1/x;
  262. for(u = n; ; ) {
  263. if(u & 01) pow *= x;
  264. if(u >>= 1) x *= x;
  265. else break;
  266. }
  267. }
  268. return pow;
  269. }
  270. #ifdef _MSC_VER
  271. static _Fcomplex cpow_ui(complex x, integer n) {
  272. complex pow={1.0,0.0}; unsigned long int u;
  273. if(n != 0) {
  274. if(n < 0) n = -n, x.r = 1/x.r, x.i=1/x.i;
  275. for(u = n; ; ) {
  276. if(u & 01) pow.r *= x.r, pow.i *= x.i;
  277. if(u >>= 1) x.r *= x.r, x.i *= x.i;
  278. else break;
  279. }
  280. }
  281. _Fcomplex p={pow.r, pow.i};
  282. return p;
  283. }
  284. #else
  285. static _Complex float cpow_ui(_Complex float x, integer n) {
  286. _Complex float pow=1.0; unsigned long int u;
  287. if(n != 0) {
  288. if(n < 0) n = -n, x = 1/x;
  289. for(u = n; ; ) {
  290. if(u & 01) pow *= x;
  291. if(u >>= 1) x *= x;
  292. else break;
  293. }
  294. }
  295. return pow;
  296. }
  297. #endif
  298. #ifdef _MSC_VER
  299. static _Dcomplex zpow_ui(_Dcomplex x, integer n) {
  300. _Dcomplex pow={1.0,0.0}; unsigned long int u;
  301. if(n != 0) {
  302. if(n < 0) n = -n, x._Val[0] = 1/x._Val[0], x._Val[1] =1/x._Val[1];
  303. for(u = n; ; ) {
  304. if(u & 01) pow._Val[0] *= x._Val[0], pow._Val[1] *= x._Val[1];
  305. if(u >>= 1) x._Val[0] *= x._Val[0], x._Val[1] *= x._Val[1];
  306. else break;
  307. }
  308. }
  309. _Dcomplex p = {pow._Val[0], pow._Val[1]};
  310. return p;
  311. }
  312. #else
  313. static _Complex double zpow_ui(_Complex double x, integer n) {
  314. _Complex double pow=1.0; unsigned long int u;
  315. if(n != 0) {
  316. if(n < 0) n = -n, x = 1/x;
  317. for(u = n; ; ) {
  318. if(u & 01) pow *= x;
  319. if(u >>= 1) x *= x;
  320. else break;
  321. }
  322. }
  323. return pow;
  324. }
  325. #endif
  326. static integer pow_ii(integer x, integer n) {
  327. integer pow; unsigned long int u;
  328. if (n <= 0) {
  329. if (n == 0 || x == 1) pow = 1;
  330. else if (x != -1) pow = x == 0 ? 1/x : 0;
  331. else n = -n;
  332. }
  333. if ((n > 0) || !(n == 0 || x == 1 || x != -1)) {
  334. u = n;
  335. for(pow = 1; ; ) {
  336. if(u & 01) pow *= x;
  337. if(u >>= 1) x *= x;
  338. else break;
  339. }
  340. }
  341. return pow;
  342. }
  343. static integer dmaxloc_(double *w, integer s, integer e, integer *n)
  344. {
  345. double m; integer i, mi;
  346. for(m=w[s-1], mi=s, i=s+1; i<=e; i++)
  347. if (w[i-1]>m) mi=i ,m=w[i-1];
  348. return mi-s+1;
  349. }
  350. static integer smaxloc_(float *w, integer s, integer e, integer *n)
  351. {
  352. float m; integer i, mi;
  353. for(m=w[s-1], mi=s, i=s+1; i<=e; i++)
  354. if (w[i-1]>m) mi=i ,m=w[i-1];
  355. return mi-s+1;
  356. }
  357. static inline void cdotc_(complex *z, integer *n_, complex *x, integer *incx_, complex *y, integer *incy_) {
  358. integer n = *n_, incx = *incx_, incy = *incy_, i;
  359. #ifdef _MSC_VER
  360. _Fcomplex zdotc = {0.0, 0.0};
  361. if (incx == 1 && incy == 1) {
  362. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  363. zdotc._Val[0] += conjf(Cf(&x[i]))._Val[0] * Cf(&y[i])._Val[0];
  364. zdotc._Val[1] += conjf(Cf(&x[i]))._Val[1] * Cf(&y[i])._Val[1];
  365. }
  366. } else {
  367. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  368. zdotc._Val[0] += conjf(Cf(&x[i*incx]))._Val[0] * Cf(&y[i*incy])._Val[0];
  369. zdotc._Val[1] += conjf(Cf(&x[i*incx]))._Val[1] * Cf(&y[i*incy])._Val[1];
  370. }
  371. }
  372. pCf(z) = zdotc;
  373. }
  374. #else
  375. _Complex float zdotc = 0.0;
  376. if (incx == 1 && incy == 1) {
  377. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  378. zdotc += conjf(Cf(&x[i])) * Cf(&y[i]);
  379. }
  380. } else {
  381. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  382. zdotc += conjf(Cf(&x[i*incx])) * Cf(&y[i*incy]);
  383. }
  384. }
  385. pCf(z) = zdotc;
  386. }
  387. #endif
  388. static inline void zdotc_(doublecomplex *z, integer *n_, doublecomplex *x, integer *incx_, doublecomplex *y, integer *incy_) {
  389. integer n = *n_, incx = *incx_, incy = *incy_, i;
  390. #ifdef _MSC_VER
  391. _Dcomplex zdotc = {0.0, 0.0};
  392. if (incx == 1 && incy == 1) {
  393. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  394. zdotc._Val[0] += conj(Cd(&x[i]))._Val[0] * Cd(&y[i])._Val[0];
  395. zdotc._Val[1] += conj(Cd(&x[i]))._Val[1] * Cd(&y[i])._Val[1];
  396. }
  397. } else {
  398. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  399. zdotc._Val[0] += conj(Cd(&x[i*incx]))._Val[0] * Cd(&y[i*incy])._Val[0];
  400. zdotc._Val[1] += conj(Cd(&x[i*incx]))._Val[1] * Cd(&y[i*incy])._Val[1];
  401. }
  402. }
  403. pCd(z) = zdotc;
  404. }
  405. #else
  406. _Complex double zdotc = 0.0;
  407. if (incx == 1 && incy == 1) {
  408. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  409. zdotc += conj(Cd(&x[i])) * Cd(&y[i]);
  410. }
  411. } else {
  412. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  413. zdotc += conj(Cd(&x[i*incx])) * Cd(&y[i*incy]);
  414. }
  415. }
  416. pCd(z) = zdotc;
  417. }
  418. #endif
  419. static inline void cdotu_(complex *z, integer *n_, complex *x, integer *incx_, complex *y, integer *incy_) {
  420. integer n = *n_, incx = *incx_, incy = *incy_, i;
  421. #ifdef _MSC_VER
  422. _Fcomplex zdotc = {0.0, 0.0};
  423. if (incx == 1 && incy == 1) {
  424. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  425. zdotc._Val[0] += Cf(&x[i])._Val[0] * Cf(&y[i])._Val[0];
  426. zdotc._Val[1] += Cf(&x[i])._Val[1] * Cf(&y[i])._Val[1];
  427. }
  428. } else {
  429. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  430. zdotc._Val[0] += Cf(&x[i*incx])._Val[0] * Cf(&y[i*incy])._Val[0];
  431. zdotc._Val[1] += Cf(&x[i*incx])._Val[1] * Cf(&y[i*incy])._Val[1];
  432. }
  433. }
  434. pCf(z) = zdotc;
  435. }
  436. #else
  437. _Complex float zdotc = 0.0;
  438. if (incx == 1 && incy == 1) {
  439. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  440. zdotc += Cf(&x[i]) * Cf(&y[i]);
  441. }
  442. } else {
  443. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  444. zdotc += Cf(&x[i*incx]) * Cf(&y[i*incy]);
  445. }
  446. }
  447. pCf(z) = zdotc;
  448. }
  449. #endif
  450. static inline void zdotu_(doublecomplex *z, integer *n_, doublecomplex *x, integer *incx_, doublecomplex *y, integer *incy_) {
  451. integer n = *n_, incx = *incx_, incy = *incy_, i;
  452. #ifdef _MSC_VER
  453. _Dcomplex zdotc = {0.0, 0.0};
  454. if (incx == 1 && incy == 1) {
  455. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  456. zdotc._Val[0] += Cd(&x[i])._Val[0] * Cd(&y[i])._Val[0];
  457. zdotc._Val[1] += Cd(&x[i])._Val[1] * Cd(&y[i])._Val[1];
  458. }
  459. } else {
  460. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  461. zdotc._Val[0] += Cd(&x[i*incx])._Val[0] * Cd(&y[i*incy])._Val[0];
  462. zdotc._Val[1] += Cd(&x[i*incx])._Val[1] * Cd(&y[i*incy])._Val[1];
  463. }
  464. }
  465. pCd(z) = zdotc;
  466. }
  467. #else
  468. _Complex double zdotc = 0.0;
  469. if (incx == 1 && incy == 1) {
  470. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  471. zdotc += Cd(&x[i]) * Cd(&y[i]);
  472. }
  473. } else {
  474. for (i=0;i<n;i++) { /* zdotc = zdotc + dconjg(x(i))* y(i) */
  475. zdotc += Cd(&x[i*incx]) * Cd(&y[i*incy]);
  476. }
  477. }
  478. pCd(z) = zdotc;
  479. }
  480. #endif
  481. /* -- translated by f2c (version 20000121).
  482. You must link the resulting object file with the libraries:
  483. -lf2c -lm (in that order)
  484. */
  485. /* Table of constant values */
  486. static integer c_n1 = -1;
  487. static integer c__1 = 1;
  488. static doublereal c_b72 = 0.;
  489. static doublereal c_b76 = 1.;
  490. static integer c__0 = 0;
  491. static logical c_false = FALSE_;
  492. /* > \brief <b> DGESVDQ computes the singular value decomposition (SVD) with a QR-Preconditioned QR SVD Method
  493. for GE matrices</b> */
  494. /* =========== DOCUMENTATION =========== */
  495. /* Online html documentation available at */
  496. /* http://www.netlib.org/lapack/explore-html/ */
  497. /* > \htmlonly */
  498. /* > Download DGESVDQ + dependencies */
  499. /* > <a href="http://www.netlib.org/cgi-bin/netlibfiles.tgz?format=tgz&filename=/lapack/lapack_routine/dgesvdq
  500. .f"> */
  501. /* > [TGZ]</a> */
  502. /* > <a href="http://www.netlib.org/cgi-bin/netlibfiles.zip?format=zip&filename=/lapack/lapack_routine/dgesvdq
  503. .f"> */
  504. /* > [ZIP]</a> */
  505. /* > <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dgesvdq
  506. .f"> */
  507. /* > [TXT]</a> */
  508. /* > \endhtmlonly */
  509. /* Definition: */
  510. /* =========== */
  511. /* SUBROUTINE DGESVDQ( JOBA, JOBP, JOBR, JOBU, JOBV, M, N, A, LDA, */
  512. /* S, U, LDU, V, LDV, NUMRANK, IWORK, LIWORK, */
  513. /* WORK, LWORK, RWORK, LRWORK, INFO ) */
  514. /* IMPLICIT NONE */
  515. /* CHARACTER JOBA, JOBP, JOBR, JOBU, JOBV */
  516. /* INTEGER M, N, LDA, LDU, LDV, NUMRANK, LIWORK, LWORK, LRWORK, */
  517. /* INFO */
  518. /* DOUBLE PRECISION A( LDA, * ), U( LDU, * ), V( LDV, * ), WORK( * ) */
  519. /* DOUBLE PRECISION S( * ), RWORK( * ) */
  520. /* INTEGER IWORK( * ) */
  521. /* > \par Purpose: */
  522. /* ============= */
  523. /* > */
  524. /* > \verbatim */
  525. /* > */
  526. /* > DGESVDQ computes the singular value decomposition (SVD) of a real */
  527. /* > M-by-N matrix A, where M >= N. The SVD of A is written as */
  528. /* > [++] [xx] [x0] [xx] */
  529. /* > A = U * SIGMA * V^*, [++] = [xx] * [ox] * [xx] */
  530. /* > [++] [xx] */
  531. /* > where SIGMA is an N-by-N diagonal matrix, U is an M-by-N orthonormal */
  532. /* > matrix, and V is an N-by-N orthogonal matrix. The diagonal elements */
  533. /* > of SIGMA are the singular values of A. The columns of U and V are the */
  534. /* > left and the right singular vectors of A, respectively. */
  535. /* > \endverbatim */
  536. /* Arguments: */
  537. /* ========== */
  538. /* > \param[in] JOBA */
  539. /* > \verbatim */
  540. /* > JOBA is CHARACTER*1 */
  541. /* > Specifies the level of accuracy in the computed SVD */
  542. /* > = 'A' The requested accuracy corresponds to having the backward */
  543. /* > error bounded by || delta A ||_F <= f(m,n) * EPS * || A ||_F, */
  544. /* > where EPS = DLAMCH('Epsilon'). This authorises DGESVDQ to */
  545. /* > truncate the computed triangular factor in a rank revealing */
  546. /* > QR factorization whenever the truncated part is below the */
  547. /* > threshold of the order of EPS * ||A||_F. This is aggressive */
  548. /* > truncation level. */
  549. /* > = 'M' Similarly as with 'A', but the truncation is more gentle: it */
  550. /* > is allowed only when there is a drop on the diagonal of the */
  551. /* > triangular factor in the QR factorization. This is medium */
  552. /* > truncation level. */
  553. /* > = 'H' High accuracy requested. No numerical rank determination based */
  554. /* > on the rank revealing QR factorization is attempted. */
  555. /* > = 'E' Same as 'H', and in addition the condition number of column */
  556. /* > scaled A is estimated and returned in RWORK(1). */
  557. /* > N^(-1/4)*RWORK(1) <= ||pinv(A_scaled)||_2 <= N^(1/4)*RWORK(1) */
  558. /* > \endverbatim */
  559. /* > */
  560. /* > \param[in] JOBP */
  561. /* > \verbatim */
  562. /* > JOBP is CHARACTER*1 */
  563. /* > = 'P' The rows of A are ordered in decreasing order with respect to */
  564. /* > ||A(i,:)||_\infty. This enhances numerical accuracy at the cost */
  565. /* > of extra data movement. Recommended for numerical robustness. */
  566. /* > = 'N' No row pivoting. */
  567. /* > \endverbatim */
  568. /* > */
  569. /* > \param[in] JOBR */
  570. /* > \verbatim */
  571. /* > JOBR is CHARACTER*1 */
  572. /* > = 'T' After the initial pivoted QR factorization, DGESVD is applied to */
  573. /* > the transposed R**T of the computed triangular factor R. This involves */
  574. /* > some extra data movement (matrix transpositions). Useful for */
  575. /* > experiments, research and development. */
  576. /* > = 'N' The triangular factor R is given as input to DGESVD. This may be */
  577. /* > preferred as it involves less data movement. */
  578. /* > \endverbatim */
  579. /* > */
  580. /* > \param[in] JOBU */
  581. /* > \verbatim */
  582. /* > JOBU is CHARACTER*1 */
  583. /* > = 'A' All M left singular vectors are computed and returned in the */
  584. /* > matrix U. See the description of U. */
  585. /* > = 'S' or 'U' N = f2cmin(M,N) left singular vectors are computed and returned */
  586. /* > in the matrix U. See the description of U. */
  587. /* > = 'R' Numerical rank NUMRANK is determined and only NUMRANK left singular */
  588. /* > vectors are computed and returned in the matrix U. */
  589. /* > = 'F' The N left singular vectors are returned in factored form as the */
  590. /* > product of the Q factor from the initial QR factorization and the */
  591. /* > N left singular vectors of (R**T , 0)**T. If row pivoting is used, */
  592. /* > then the necessary information on the row pivoting is stored in */
  593. /* > IWORK(N+1:N+M-1). */
  594. /* > = 'N' The left singular vectors are not computed. */
  595. /* > \endverbatim */
  596. /* > */
  597. /* > \param[in] JOBV */
  598. /* > \verbatim */
  599. /* > JOBV is CHARACTER*1 */
  600. /* > = 'A', 'V' All N right singular vectors are computed and returned in */
  601. /* > the matrix V. */
  602. /* > = 'R' Numerical rank NUMRANK is determined and only NUMRANK right singular */
  603. /* > vectors are computed and returned in the matrix V. This option is */
  604. /* > allowed only if JOBU = 'R' or JOBU = 'N'; otherwise it is illegal. */
  605. /* > = 'N' The right singular vectors are not computed. */
  606. /* > \endverbatim */
  607. /* > */
  608. /* > \param[in] M */
  609. /* > \verbatim */
  610. /* > M is INTEGER */
  611. /* > The number of rows of the input matrix A. M >= 0. */
  612. /* > \endverbatim */
  613. /* > */
  614. /* > \param[in] N */
  615. /* > \verbatim */
  616. /* > N is INTEGER */
  617. /* > The number of columns of the input matrix A. M >= N >= 0. */
  618. /* > \endverbatim */
  619. /* > */
  620. /* > \param[in,out] A */
  621. /* > \verbatim */
  622. /* > A is DOUBLE PRECISION array of dimensions LDA x N */
  623. /* > On entry, the input matrix A. */
  624. /* > On exit, if JOBU .NE. 'N' or JOBV .NE. 'N', the lower triangle of A contains */
  625. /* > the Householder vectors as stored by DGEQP3. If JOBU = 'F', these Householder */
  626. /* > vectors together with WORK(1:N) can be used to restore the Q factors from */
  627. /* > the initial pivoted QR factorization of A. See the description of U. */
  628. /* > \endverbatim */
  629. /* > */
  630. /* > \param[in] LDA */
  631. /* > \verbatim */
  632. /* > LDA is INTEGER. */
  633. /* > The leading dimension of the array A. LDA >= f2cmax(1,M). */
  634. /* > \endverbatim */
  635. /* > */
  636. /* > \param[out] S */
  637. /* > \verbatim */
  638. /* > S is DOUBLE PRECISION array of dimension N. */
  639. /* > The singular values of A, ordered so that S(i) >= S(i+1). */
  640. /* > \endverbatim */
  641. /* > */
  642. /* > \param[out] U */
  643. /* > \verbatim */
  644. /* > U is DOUBLE PRECISION array, dimension */
  645. /* > LDU x M if JOBU = 'A'; see the description of LDU. In this case, */
  646. /* > on exit, U contains the M left singular vectors. */
  647. /* > LDU x N if JOBU = 'S', 'U', 'R' ; see the description of LDU. In this */
  648. /* > case, U contains the leading N or the leading NUMRANK left singular vectors. */
  649. /* > LDU x N if JOBU = 'F' ; see the description of LDU. In this case U */
  650. /* > contains N x N orthogonal matrix that can be used to form the left */
  651. /* > singular vectors. */
  652. /* > If JOBU = 'N', U is not referenced. */
  653. /* > \endverbatim */
  654. /* > */
  655. /* > \param[in] LDU */
  656. /* > \verbatim */
  657. /* > LDU is INTEGER. */
  658. /* > The leading dimension of the array U. */
  659. /* > If JOBU = 'A', 'S', 'U', 'R', LDU >= f2cmax(1,M). */
  660. /* > If JOBU = 'F', LDU >= f2cmax(1,N). */
  661. /* > Otherwise, LDU >= 1. */
  662. /* > \endverbatim */
  663. /* > */
  664. /* > \param[out] V */
  665. /* > \verbatim */
  666. /* > V is DOUBLE PRECISION array, dimension */
  667. /* > LDV x N if JOBV = 'A', 'V', 'R' or if JOBA = 'E' . */
  668. /* > If JOBV = 'A', or 'V', V contains the N-by-N orthogonal matrix V**T; */
  669. /* > If JOBV = 'R', V contains the first NUMRANK rows of V**T (the right */
  670. /* > singular vectors, stored rowwise, of the NUMRANK largest singular values). */
  671. /* > If JOBV = 'N' and JOBA = 'E', V is used as a workspace. */
  672. /* > If JOBV = 'N', and JOBA.NE.'E', V is not referenced. */
  673. /* > \endverbatim */
  674. /* > */
  675. /* > \param[in] LDV */
  676. /* > \verbatim */
  677. /* > LDV is INTEGER */
  678. /* > The leading dimension of the array V. */
  679. /* > If JOBV = 'A', 'V', 'R', or JOBA = 'E', LDV >= f2cmax(1,N). */
  680. /* > Otherwise, LDV >= 1. */
  681. /* > \endverbatim */
  682. /* > */
  683. /* > \param[out] NUMRANK */
  684. /* > \verbatim */
  685. /* > NUMRANK is INTEGER */
  686. /* > NUMRANK is the numerical rank first determined after the rank */
  687. /* > revealing QR factorization, following the strategy specified by the */
  688. /* > value of JOBA. If JOBV = 'R' and JOBU = 'R', only NUMRANK */
  689. /* > leading singular values and vectors are then requested in the call */
  690. /* > of DGESVD. The final value of NUMRANK might be further reduced if */
  691. /* > some singular values are computed as zeros. */
  692. /* > \endverbatim */
  693. /* > */
  694. /* > \param[out] IWORK */
  695. /* > \verbatim */
  696. /* > IWORK is INTEGER array, dimension (f2cmax(1, LIWORK)). */
  697. /* > On exit, IWORK(1:N) contains column pivoting permutation of the */
  698. /* > rank revealing QR factorization. */
  699. /* > If JOBP = 'P', IWORK(N+1:N+M-1) contains the indices of the sequence */
  700. /* > of row swaps used in row pivoting. These can be used to restore the */
  701. /* > left singular vectors in the case JOBU = 'F'. */
  702. /* > */
  703. /* > If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0, */
  704. /* > LIWORK(1) returns the minimal LIWORK. */
  705. /* > \endverbatim */
  706. /* > */
  707. /* > \param[in] LIWORK */
  708. /* > \verbatim */
  709. /* > LIWORK is INTEGER */
  710. /* > The dimension of the array IWORK. */
  711. /* > LIWORK >= N + M - 1, if JOBP = 'P' and JOBA .NE. 'E'; */
  712. /* > LIWORK >= N if JOBP = 'N' and JOBA .NE. 'E'; */
  713. /* > LIWORK >= N + M - 1 + N, if JOBP = 'P' and JOBA = 'E'; */
  714. /* > LIWORK >= N + N if JOBP = 'N' and JOBA = 'E'. */
  715. /* > If LIWORK = -1, then a workspace query is assumed; the routine */
  716. /* > only calculates and returns the optimal and minimal sizes */
  717. /* > for the WORK, IWORK, and RWORK arrays, and no error */
  718. /* > message related to LWORK is issued by XERBLA. */
  719. /* > \endverbatim */
  720. /* > */
  721. /* > \param[out] WORK */
  722. /* > \verbatim */
  723. /* > WORK is DOUBLE PRECISION array, dimension (f2cmax(2, LWORK)), used as a workspace. */
  724. /* > On exit, if, on entry, LWORK.NE.-1, WORK(1:N) contains parameters */
  725. /* > needed to recover the Q factor from the QR factorization computed by */
  726. /* > DGEQP3. */
  727. /* > */
  728. /* > If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0, */
  729. /* > WORK(1) returns the optimal LWORK, and */
  730. /* > WORK(2) returns the minimal LWORK. */
  731. /* > \endverbatim */
  732. /* > */
  733. /* > \param[in,out] LWORK */
  734. /* > \verbatim */
  735. /* > LWORK is INTEGER */
  736. /* > The dimension of the array WORK. It is determined as follows: */
  737. /* > Let LWQP3 = 3*N+1, LWCON = 3*N, and let */
  738. /* > LWORQ = { MAX( N, 1 ), if JOBU = 'R', 'S', or 'U' */
  739. /* > { MAX( M, 1 ), if JOBU = 'A' */
  740. /* > LWSVD = MAX( 5*N, 1 ) */
  741. /* > LWLQF = MAX( N/2, 1 ), LWSVD2 = MAX( 5*(N/2), 1 ), LWORLQ = MAX( N, 1 ), */
  742. /* > LWQRF = MAX( N/2, 1 ), LWORQ2 = MAX( N, 1 ) */
  743. /* > Then the minimal value of LWORK is: */
  744. /* > = MAX( N + LWQP3, LWSVD ) if only the singular values are needed; */
  745. /* > = MAX( N + LWQP3, LWCON, LWSVD ) if only the singular values are needed, */
  746. /* > and a scaled condition estimate requested; */
  747. /* > */
  748. /* > = N + MAX( LWQP3, LWSVD, LWORQ ) if the singular values and the left */
  749. /* > singular vectors are requested; */
  750. /* > = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the singular values and the left */
  751. /* > singular vectors are requested, and also */
  752. /* > a scaled condition estimate requested; */
  753. /* > */
  754. /* > = N + MAX( LWQP3, LWSVD ) if the singular values and the right */
  755. /* > singular vectors are requested; */
  756. /* > = N + MAX( LWQP3, LWCON, LWSVD ) if the singular values and the right */
  757. /* > singular vectors are requested, and also */
  758. /* > a scaled condition etimate requested; */
  759. /* > */
  760. /* > = N + MAX( LWQP3, LWSVD, LWORQ ) if the full SVD is requested with JOBV = 'R'; */
  761. /* > independent of JOBR; */
  762. /* > = N + MAX( LWQP3, LWCON, LWSVD, LWORQ ) if the full SVD is requested, */
  763. /* > JOBV = 'R' and, also a scaled condition */
  764. /* > estimate requested; independent of JOBR; */
  765. /* > = MAX( N + MAX( LWQP3, LWSVD, LWORQ ), */
  766. /* > N + MAX( LWQP3, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ) ) if the */
  767. /* > full SVD is requested with JOBV = 'A' or 'V', and */
  768. /* > JOBR ='N' */
  769. /* > = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ), */
  770. /* > N + MAX( LWQP3, LWCON, N/2+LWLQF, N/2+LWSVD2, N/2+LWORLQ, LWORQ ) ) */
  771. /* > if the full SVD is requested with JOBV = 'A' or 'V', and */
  772. /* > JOBR ='N', and also a scaled condition number estimate */
  773. /* > requested. */
  774. /* > = MAX( N + MAX( LWQP3, LWSVD, LWORQ ), */
  775. /* > N + MAX( LWQP3, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) ) if the */
  776. /* > full SVD is requested with JOBV = 'A', 'V', and JOBR ='T' */
  777. /* > = MAX( N + MAX( LWQP3, LWCON, LWSVD, LWORQ ), */
  778. /* > N + MAX( LWQP3, LWCON, N/2+LWQRF, N/2+LWSVD2, N/2+LWORQ2, LWORQ ) ) */
  779. /* > if the full SVD is requested with JOBV = 'A' or 'V', and */
  780. /* > JOBR ='T', and also a scaled condition number estimate */
  781. /* > requested. */
  782. /* > Finally, LWORK must be at least two: LWORK = MAX( 2, LWORK ). */
  783. /* > */
  784. /* > If LWORK = -1, then a workspace query is assumed; the routine */
  785. /* > only calculates and returns the optimal and minimal sizes */
  786. /* > for the WORK, IWORK, and RWORK arrays, and no error */
  787. /* > message related to LWORK is issued by XERBLA. */
  788. /* > \endverbatim */
  789. /* > */
  790. /* > \param[out] RWORK */
  791. /* > \verbatim */
  792. /* > RWORK is DOUBLE PRECISION array, dimension (f2cmax(1, LRWORK)). */
  793. /* > On exit, */
  794. /* > 1. If JOBA = 'E', RWORK(1) contains an estimate of the condition */
  795. /* > number of column scaled A. If A = C * D where D is diagonal and C */
  796. /* > has unit columns in the Euclidean norm, then, assuming full column rank, */
  797. /* > N^(-1/4) * RWORK(1) <= ||pinv(C)||_2 <= N^(1/4) * RWORK(1). */
  798. /* > Otherwise, RWORK(1) = -1. */
  799. /* > 2. RWORK(2) contains the number of singular values computed as */
  800. /* > exact zeros in DGESVD applied to the upper triangular or trapeziodal */
  801. /* > R (from the initial QR factorization). In case of early exit (no call to */
  802. /* > DGESVD, such as in the case of zero matrix) RWORK(2) = -1. */
  803. /* > */
  804. /* > If LIWORK, LWORK, or LRWORK = -1, then on exit, if INFO = 0, */
  805. /* > RWORK(1) returns the minimal LRWORK. */
  806. /* > \endverbatim */
  807. /* > */
  808. /* > \param[in] LRWORK */
  809. /* > \verbatim */
  810. /* > LRWORK is INTEGER. */
  811. /* > The dimension of the array RWORK. */
  812. /* > If JOBP ='P', then LRWORK >= MAX(2, M). */
  813. /* > Otherwise, LRWORK >= 2 */
  814. /* > If LRWORK = -1, then a workspace query is assumed; the routine */
  815. /* > only calculates and returns the optimal and minimal sizes */
  816. /* > for the WORK, IWORK, and RWORK arrays, and no error */
  817. /* > message related to LWORK is issued by XERBLA. */
  818. /* > \endverbatim */
  819. /* > */
  820. /* > \param[out] INFO */
  821. /* > \verbatim */
  822. /* > INFO is INTEGER */
  823. /* > = 0: successful exit. */
  824. /* > < 0: if INFO = -i, the i-th argument had an illegal value. */
  825. /* > > 0: if DBDSQR did not converge, INFO specifies how many superdiagonals */
  826. /* > of an intermediate bidiagonal form B (computed in DGESVD) did not */
  827. /* > converge to zero. */
  828. /* > \endverbatim */
  829. /* > \par Further Details: */
  830. /* ======================== */
  831. /* > */
  832. /* > \verbatim */
  833. /* > */
  834. /* > 1. The data movement (matrix transpose) is coded using simple nested */
  835. /* > DO-loops because BLAS and LAPACK do not provide corresponding subroutines. */
  836. /* > Those DO-loops are easily identified in this source code - by the CONTINUE */
  837. /* > statements labeled with 11**. In an optimized version of this code, the */
  838. /* > nested DO loops should be replaced with calls to an optimized subroutine. */
  839. /* > 2. This code scales A by 1/SQRT(M) if the largest ABS(A(i,j)) could cause */
  840. /* > column norm overflow. This is the minial precaution and it is left to the */
  841. /* > SVD routine (CGESVD) to do its own preemptive scaling if potential over- */
  842. /* > or underflows are detected. To avoid repeated scanning of the array A, */
  843. /* > an optimal implementation would do all necessary scaling before calling */
  844. /* > CGESVD and the scaling in CGESVD can be switched off. */
  845. /* > 3. Other comments related to code optimization are given in comments in the */
  846. /* > code, enlosed in [[double brackets]]. */
  847. /* > \endverbatim */
  848. /* > \par Bugs, examples and comments */
  849. /* =========================== */
  850. /* > \verbatim */
  851. /* > Please report all bugs and send interesting examples and/or comments to */
  852. /* > drmac@math.hr. Thank you. */
  853. /* > \endverbatim */
  854. /* > \par References */
  855. /* =============== */
  856. /* > \verbatim */
  857. /* > [1] Zlatko Drmac, Algorithm 977: A QR-Preconditioned QR SVD Method for */
  858. /* > Computing the SVD with High Accuracy. ACM Trans. Math. Softw. */
  859. /* > 44(1): 11:1-11:30 (2017) */
  860. /* > */
  861. /* > SIGMA library, xGESVDQ section updated February 2016. */
  862. /* > Developed and coded by Zlatko Drmac, Department of Mathematics */
  863. /* > University of Zagreb, Croatia, drmac@math.hr */
  864. /* > \endverbatim */
  865. /* > \par Contributors: */
  866. /* ================== */
  867. /* > */
  868. /* > \verbatim */
  869. /* > Developed and coded by Zlatko Drmac, Department of Mathematics */
  870. /* > University of Zagreb, Croatia, drmac@math.hr */
  871. /* > \endverbatim */
  872. /* Authors: */
  873. /* ======== */
  874. /* > \author Univ. of Tennessee */
  875. /* > \author Univ. of California Berkeley */
  876. /* > \author Univ. of Colorado Denver */
  877. /* > \author NAG Ltd. */
  878. /* > \date November 2018 */
  879. /* > \ingroup doubleGEsing */
  880. /* ===================================================================== */
  881. /* Subroutine */ int dgesvdq_(char *joba, char *jobp, char *jobr, char *jobu,
  882. char *jobv, integer *m, integer *n, doublereal *a, integer *lda,
  883. doublereal *s, doublereal *u, integer *ldu, doublereal *v, integer *
  884. ldv, integer *numrank, integer *iwork, integer *liwork, doublereal *
  885. work, integer *lwork, doublereal *rwork, integer *lrwork, integer *
  886. info)
  887. {
  888. /* System generated locals */
  889. integer a_dim1, a_offset, u_dim1, u_offset, v_dim1, v_offset, i__1, i__2;
  890. doublereal d__1, d__2, d__3;
  891. /* Local variables */
  892. integer lwrk_dormqr__, lwrk_dgesvd2__, ierr, lwrk_dormqr2__;
  893. doublereal rtmp;
  894. integer optratio;
  895. extern doublereal dnrm2_(integer *, doublereal *, integer *);
  896. logical lsvc0, accla;
  897. integer lwqp3;
  898. logical acclh, acclm;
  899. integer p, q;
  900. logical conda;
  901. extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
  902. integer *);
  903. extern logical lsame_(char *, char *);
  904. integer iwoff;
  905. logical lsvec;
  906. doublereal sfmin, epsln;
  907. integer lwcon;
  908. logical rsvec;
  909. integer lwlqf, lwqrf, n1, lwsvd;
  910. logical dntwu, dntwv, wntua;
  911. integer lworq;
  912. logical wntuf, wntva, wntur, wntus, wntvr;
  913. extern /* Subroutine */ int dgeqp3_(integer *, integer *, doublereal *,
  914. integer *, integer *, doublereal *, doublereal *, integer *,
  915. integer *);
  916. integer lwsvd2, lworq2;
  917. extern doublereal dlamch_(char *), dlange_(char *, integer *,
  918. integer *, doublereal *, integer *, doublereal *);
  919. integer nr;
  920. extern /* Subroutine */ int dgelqf_(integer *, integer *, doublereal *,
  921. integer *, doublereal *, doublereal *, integer *, integer *),
  922. dlascl_(char *, integer *, integer *, doublereal *, doublereal *,
  923. integer *, integer *, doublereal *, integer *, integer *);
  924. extern integer idamax_(integer *, doublereal *, integer *);
  925. doublereal sconda;
  926. extern /* Subroutine */ int dgeqrf_(integer *, integer *, doublereal *,
  927. integer *, doublereal *, doublereal *, integer *, integer *),
  928. dgesvd_(char *, char *, integer *, integer *, doublereal *,
  929. integer *, doublereal *, doublereal *, integer *, doublereal *,
  930. integer *, doublereal *, integer *, integer *),
  931. dlacpy_(char *, integer *, integer *, doublereal *, integer *,
  932. doublereal *, integer *), dlaset_(char *, integer *,
  933. integer *, doublereal *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *, ftnlen), dlapmt_(logical *,
  934. integer *, integer *, doublereal *, integer *, integer *),
  935. dpocon_(char *, integer *, doublereal *, integer *, doublereal *,
  936. doublereal *, doublereal *, integer *, integer *),
  937. dlaswp_(integer *, doublereal *, integer *, integer *, integer *,
  938. integer *, integer *), dormlq_(char *, char *, integer *, integer
  939. *, integer *, doublereal *, integer *, doublereal *, doublereal *,
  940. integer *, doublereal *, integer *, integer *),
  941. dormqr_(char *, char *, integer *, integer *, integer *,
  942. doublereal *, integer *, doublereal *, doublereal *, integer *,
  943. doublereal *, integer *, integer *);
  944. integer minwrk;
  945. logical rtrans;
  946. doublereal rdummy[1];
  947. integer lworlq;
  948. logical lquery;
  949. integer optwrk;
  950. logical rowprm;
  951. doublereal big;
  952. integer minwrk2;
  953. logical ascaled;
  954. integer lwrk_dgeqp3__, optwrk2, lwrk_dgelqf__, iminwrk, lwrk_dgeqrf__,
  955. rminwrk, lwrk_dgesvd__, lwrk_dormlq__;
  956. /* ===================================================================== */
  957. /* Test the input arguments */
  958. /* Parameter adjustments */
  959. a_dim1 = *lda;
  960. a_offset = 1 + a_dim1 * 1;
  961. a -= a_offset;
  962. --s;
  963. u_dim1 = *ldu;
  964. u_offset = 1 + u_dim1 * 1;
  965. u -= u_offset;
  966. v_dim1 = *ldv;
  967. v_offset = 1 + v_dim1 * 1;
  968. v -= v_offset;
  969. --iwork;
  970. --work;
  971. --rwork;
  972. /* Function Body */
  973. wntus = lsame_(jobu, "S") || lsame_(jobu, "U");
  974. wntur = lsame_(jobu, "R");
  975. wntua = lsame_(jobu, "A");
  976. wntuf = lsame_(jobu, "F");
  977. lsvc0 = wntus || wntur || wntua;
  978. lsvec = lsvc0 || wntuf;
  979. dntwu = lsame_(jobu, "N");
  980. wntvr = lsame_(jobv, "R");
  981. wntva = lsame_(jobv, "A") || lsame_(jobv, "V");
  982. rsvec = wntvr || wntva;
  983. dntwv = lsame_(jobv, "N");
  984. accla = lsame_(joba, "A");
  985. acclm = lsame_(joba, "M");
  986. conda = lsame_(joba, "E");
  987. acclh = lsame_(joba, "H") || conda;
  988. rowprm = lsame_(jobp, "P");
  989. rtrans = lsame_(jobr, "T");
  990. if (rowprm) {
  991. if (conda) {
  992. /* Computing MAX */
  993. i__1 = 1, i__2 = *n + *m - 1 + *n;
  994. iminwrk = f2cmax(i__1,i__2);
  995. } else {
  996. /* Computing MAX */
  997. i__1 = 1, i__2 = *n + *m - 1;
  998. iminwrk = f2cmax(i__1,i__2);
  999. }
  1000. rminwrk = f2cmax(2,*m);
  1001. } else {
  1002. if (conda) {
  1003. /* Computing MAX */
  1004. i__1 = 1, i__2 = *n + *n;
  1005. iminwrk = f2cmax(i__1,i__2);
  1006. } else {
  1007. iminwrk = f2cmax(1,*n);
  1008. }
  1009. rminwrk = 2;
  1010. }
  1011. lquery = *liwork == -1 || *lwork == -1 || *lrwork == -1;
  1012. *info = 0;
  1013. if (! (accla || acclm || acclh)) {
  1014. *info = -1;
  1015. } else if (! (rowprm || lsame_(jobp, "N"))) {
  1016. *info = -2;
  1017. } else if (! (rtrans || lsame_(jobr, "N"))) {
  1018. *info = -3;
  1019. } else if (! (lsvec || dntwu)) {
  1020. *info = -4;
  1021. } else if (wntur && wntva) {
  1022. *info = -5;
  1023. } else if (! (rsvec || dntwv)) {
  1024. *info = -5;
  1025. } else if (*m < 0) {
  1026. *info = -6;
  1027. } else if (*n < 0 || *n > *m) {
  1028. *info = -7;
  1029. } else if (*lda < f2cmax(1,*m)) {
  1030. *info = -9;
  1031. } else if (*ldu < 1 || lsvc0 && *ldu < *m || wntuf && *ldu < *n) {
  1032. *info = -12;
  1033. } else if (*ldv < 1 || rsvec && *ldv < *n || conda && *ldv < *n) {
  1034. *info = -14;
  1035. } else if (*liwork < iminwrk && ! lquery) {
  1036. *info = -17;
  1037. }
  1038. if (*info == 0) {
  1039. /* [[The expressions for computing the minimal and the optimal */
  1040. /* values of LWORK are written with a lot of redundancy and */
  1041. /* can be simplified. However, this detailed form is easier for */
  1042. /* maintenance and modifications of the code.]] */
  1043. lwqp3 = *n * 3 + 1;
  1044. if (wntus || wntur) {
  1045. lworq = f2cmax(*n,1);
  1046. } else if (wntua) {
  1047. lworq = f2cmax(*m,1);
  1048. }
  1049. lwcon = *n * 3;
  1050. /* Computing MAX */
  1051. i__1 = *n * 5;
  1052. lwsvd = f2cmax(i__1,1);
  1053. if (lquery) {
  1054. dgeqp3_(m, n, &a[a_offset], lda, &iwork[1], rdummy, rdummy, &c_n1,
  1055. &ierr);
  1056. lwrk_dgeqp3__ = (integer) rdummy[0];
  1057. if (wntus || wntur) {
  1058. dormqr_("L", "N", m, n, n, &a[a_offset], lda, rdummy, &u[
  1059. u_offset], ldu, rdummy, &c_n1, &ierr);
  1060. lwrk_dormqr__ = (integer) rdummy[0];
  1061. } else if (wntua) {
  1062. dormqr_("L", "N", m, m, n, &a[a_offset], lda, rdummy, &u[
  1063. u_offset], ldu, rdummy, &c_n1, &ierr);
  1064. lwrk_dormqr__ = (integer) rdummy[0];
  1065. } else {
  1066. lwrk_dormqr__ = 0;
  1067. }
  1068. }
  1069. minwrk = 2;
  1070. optwrk = 2;
  1071. if (! (lsvec || rsvec)) {
  1072. /* only the singular values are requested */
  1073. if (conda) {
  1074. /* Computing MAX */
  1075. i__1 = *n + lwqp3, i__1 = f2cmax(i__1,lwcon);
  1076. minwrk = f2cmax(i__1,lwsvd);
  1077. } else {
  1078. /* Computing MAX */
  1079. i__1 = *n + lwqp3;
  1080. minwrk = f2cmax(i__1,lwsvd);
  1081. }
  1082. if (lquery) {
  1083. dgesvd_("N", "N", n, n, &a[a_offset], lda, &s[1], &u[u_offset]
  1084. , ldu, &v[v_offset], ldv, rdummy, &c_n1, &ierr);
  1085. lwrk_dgesvd__ = (integer) rdummy[0];
  1086. if (conda) {
  1087. /* Computing MAX */
  1088. i__1 = *n + lwrk_dgeqp3__, i__2 = *n + lwcon, i__1 = f2cmax(
  1089. i__1,i__2);
  1090. optwrk = f2cmax(i__1,lwrk_dgesvd__);
  1091. } else {
  1092. /* Computing MAX */
  1093. i__1 = *n + lwrk_dgeqp3__;
  1094. optwrk = f2cmax(i__1,lwrk_dgesvd__);
  1095. }
  1096. }
  1097. } else if (lsvec && ! rsvec) {
  1098. /* singular values and the left singular vectors are requested */
  1099. if (conda) {
  1100. /* Computing MAX */
  1101. i__1 = f2cmax(lwqp3,lwcon), i__1 = f2cmax(i__1,lwsvd);
  1102. minwrk = *n + f2cmax(i__1,lworq);
  1103. } else {
  1104. /* Computing MAX */
  1105. i__1 = f2cmax(lwqp3,lwsvd);
  1106. minwrk = *n + f2cmax(i__1,lworq);
  1107. }
  1108. if (lquery) {
  1109. if (rtrans) {
  1110. dgesvd_("N", "O", n, n, &a[a_offset], lda, &s[1], &u[
  1111. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1112. &ierr);
  1113. } else {
  1114. dgesvd_("O", "N", n, n, &a[a_offset], lda, &s[1], &u[
  1115. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1116. &ierr);
  1117. }
  1118. lwrk_dgesvd__ = (integer) rdummy[0];
  1119. if (conda) {
  1120. /* Computing MAX */
  1121. i__1 = f2cmax(lwrk_dgeqp3__,lwcon), i__1 = f2cmax(i__1,
  1122. lwrk_dgesvd__);
  1123. optwrk = *n + f2cmax(i__1,lwrk_dormqr__);
  1124. } else {
  1125. /* Computing MAX */
  1126. i__1 = f2cmax(lwrk_dgeqp3__,lwrk_dgesvd__);
  1127. optwrk = *n + f2cmax(i__1,lwrk_dormqr__);
  1128. }
  1129. }
  1130. } else if (rsvec && ! lsvec) {
  1131. /* singular values and the right singular vectors are requested */
  1132. if (conda) {
  1133. /* Computing MAX */
  1134. i__1 = f2cmax(lwqp3,lwcon);
  1135. minwrk = *n + f2cmax(i__1,lwsvd);
  1136. } else {
  1137. minwrk = *n + f2cmax(lwqp3,lwsvd);
  1138. }
  1139. if (lquery) {
  1140. if (rtrans) {
  1141. dgesvd_("O", "N", n, n, &a[a_offset], lda, &s[1], &u[
  1142. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1143. &ierr);
  1144. } else {
  1145. dgesvd_("N", "O", n, n, &a[a_offset], lda, &s[1], &u[
  1146. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1147. &ierr);
  1148. }
  1149. lwrk_dgesvd__ = (integer) rdummy[0];
  1150. if (conda) {
  1151. /* Computing MAX */
  1152. i__1 = f2cmax(lwrk_dgeqp3__,lwcon);
  1153. optwrk = *n + f2cmax(i__1,lwrk_dgesvd__);
  1154. } else {
  1155. optwrk = *n + f2cmax(lwrk_dgeqp3__,lwrk_dgesvd__);
  1156. }
  1157. }
  1158. } else {
  1159. /* full SVD is requested */
  1160. if (rtrans) {
  1161. /* Computing MAX */
  1162. i__1 = f2cmax(lwqp3,lwsvd);
  1163. minwrk = f2cmax(i__1,lworq);
  1164. if (conda) {
  1165. minwrk = f2cmax(minwrk,lwcon);
  1166. }
  1167. minwrk += *n;
  1168. if (wntva) {
  1169. /* Computing MAX */
  1170. i__1 = *n / 2;
  1171. lwqrf = f2cmax(i__1,1);
  1172. /* Computing MAX */
  1173. i__1 = *n / 2 * 5;
  1174. lwsvd2 = f2cmax(i__1,1);
  1175. lworq2 = f2cmax(*n,1);
  1176. /* Computing MAX */
  1177. i__1 = lwqp3, i__2 = *n / 2 + lwqrf, i__1 = f2cmax(i__1,i__2)
  1178. , i__2 = *n / 2 + lwsvd2, i__1 = f2cmax(i__1,i__2),
  1179. i__2 = *n / 2 + lworq2, i__1 = f2cmax(i__1,i__2);
  1180. minwrk2 = f2cmax(i__1,lworq);
  1181. if (conda) {
  1182. minwrk2 = f2cmax(minwrk2,lwcon);
  1183. }
  1184. minwrk2 = *n + minwrk2;
  1185. minwrk = f2cmax(minwrk,minwrk2);
  1186. }
  1187. } else {
  1188. /* Computing MAX */
  1189. i__1 = f2cmax(lwqp3,lwsvd);
  1190. minwrk = f2cmax(i__1,lworq);
  1191. if (conda) {
  1192. minwrk = f2cmax(minwrk,lwcon);
  1193. }
  1194. minwrk += *n;
  1195. if (wntva) {
  1196. /* Computing MAX */
  1197. i__1 = *n / 2;
  1198. lwlqf = f2cmax(i__1,1);
  1199. /* Computing MAX */
  1200. i__1 = *n / 2 * 5;
  1201. lwsvd2 = f2cmax(i__1,1);
  1202. lworlq = f2cmax(*n,1);
  1203. /* Computing MAX */
  1204. i__1 = lwqp3, i__2 = *n / 2 + lwlqf, i__1 = f2cmax(i__1,i__2)
  1205. , i__2 = *n / 2 + lwsvd2, i__1 = f2cmax(i__1,i__2),
  1206. i__2 = *n / 2 + lworlq, i__1 = f2cmax(i__1,i__2);
  1207. minwrk2 = f2cmax(i__1,lworq);
  1208. if (conda) {
  1209. minwrk2 = f2cmax(minwrk2,lwcon);
  1210. }
  1211. minwrk2 = *n + minwrk2;
  1212. minwrk = f2cmax(minwrk,minwrk2);
  1213. }
  1214. }
  1215. if (lquery) {
  1216. if (rtrans) {
  1217. dgesvd_("O", "A", n, n, &a[a_offset], lda, &s[1], &u[
  1218. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1219. &ierr);
  1220. lwrk_dgesvd__ = (integer) rdummy[0];
  1221. /* Computing MAX */
  1222. i__1 = f2cmax(lwrk_dgeqp3__,lwrk_dgesvd__);
  1223. optwrk = f2cmax(i__1,lwrk_dormqr__);
  1224. if (conda) {
  1225. optwrk = f2cmax(optwrk,lwcon);
  1226. }
  1227. optwrk = *n + optwrk;
  1228. if (wntva) {
  1229. i__1 = *n / 2;
  1230. dgeqrf_(n, &i__1, &u[u_offset], ldu, rdummy, rdummy, &
  1231. c_n1, &ierr);
  1232. lwrk_dgeqrf__ = (integer) rdummy[0];
  1233. i__1 = *n / 2;
  1234. i__2 = *n / 2;
  1235. dgesvd_("S", "O", &i__1, &i__2, &v[v_offset], ldv, &s[
  1236. 1], &u[u_offset], ldu, &v[v_offset], ldv,
  1237. rdummy, &c_n1, &ierr);
  1238. lwrk_dgesvd2__ = (integer) rdummy[0];
  1239. i__1 = *n / 2;
  1240. dormqr_("R", "C", n, n, &i__1, &u[u_offset], ldu,
  1241. rdummy, &v[v_offset], ldv, rdummy, &c_n1, &
  1242. ierr);
  1243. lwrk_dormqr2__ = (integer) rdummy[0];
  1244. /* Computing MAX */
  1245. i__1 = lwrk_dgeqp3__, i__2 = *n / 2 + lwrk_dgeqrf__,
  1246. i__1 = f2cmax(i__1,i__2), i__2 = *n / 2 +
  1247. lwrk_dgesvd2__, i__1 = f2cmax(i__1,i__2), i__2 =
  1248. *n / 2 + lwrk_dormqr2__;
  1249. optwrk2 = f2cmax(i__1,i__2);
  1250. if (conda) {
  1251. optwrk2 = f2cmax(optwrk2,lwcon);
  1252. }
  1253. optwrk2 = *n + optwrk2;
  1254. optwrk = f2cmax(optwrk,optwrk2);
  1255. }
  1256. } else {
  1257. dgesvd_("S", "O", n, n, &a[a_offset], lda, &s[1], &u[
  1258. u_offset], ldu, &v[v_offset], ldv, rdummy, &c_n1,
  1259. &ierr);
  1260. lwrk_dgesvd__ = (integer) rdummy[0];
  1261. /* Computing MAX */
  1262. i__1 = f2cmax(lwrk_dgeqp3__,lwrk_dgesvd__);
  1263. optwrk = f2cmax(i__1,lwrk_dormqr__);
  1264. if (conda) {
  1265. optwrk = f2cmax(optwrk,lwcon);
  1266. }
  1267. optwrk = *n + optwrk;
  1268. if (wntva) {
  1269. i__1 = *n / 2;
  1270. dgelqf_(&i__1, n, &u[u_offset], ldu, rdummy, rdummy, &
  1271. c_n1, &ierr);
  1272. lwrk_dgelqf__ = (integer) rdummy[0];
  1273. i__1 = *n / 2;
  1274. i__2 = *n / 2;
  1275. dgesvd_("S", "O", &i__1, &i__2, &v[v_offset], ldv, &s[
  1276. 1], &u[u_offset], ldu, &v[v_offset], ldv,
  1277. rdummy, &c_n1, &ierr);
  1278. lwrk_dgesvd2__ = (integer) rdummy[0];
  1279. i__1 = *n / 2;
  1280. dormlq_("R", "N", n, n, &i__1, &u[u_offset], ldu,
  1281. rdummy, &v[v_offset], ldv, rdummy, &c_n1, &
  1282. ierr);
  1283. lwrk_dormlq__ = (integer) rdummy[0];
  1284. /* Computing MAX */
  1285. i__1 = lwrk_dgeqp3__, i__2 = *n / 2 + lwrk_dgelqf__,
  1286. i__1 = f2cmax(i__1,i__2), i__2 = *n / 2 +
  1287. lwrk_dgesvd2__, i__1 = f2cmax(i__1,i__2), i__2 =
  1288. *n / 2 + lwrk_dormlq__;
  1289. optwrk2 = f2cmax(i__1,i__2);
  1290. if (conda) {
  1291. optwrk2 = f2cmax(optwrk2,lwcon);
  1292. }
  1293. optwrk2 = *n + optwrk2;
  1294. optwrk = f2cmax(optwrk,optwrk2);
  1295. }
  1296. }
  1297. }
  1298. }
  1299. minwrk = f2cmax(2,minwrk);
  1300. optwrk = f2cmax(2,optwrk);
  1301. if (*lwork < minwrk && ! lquery) {
  1302. *info = -19;
  1303. }
  1304. }
  1305. if (*info == 0 && *lrwork < rminwrk && ! lquery) {
  1306. *info = -21;
  1307. }
  1308. if (*info != 0) {
  1309. i__1 = -(*info);
  1310. xerbla_("DGESVDQ", &i__1, (ftnlen)7);
  1311. return 0;
  1312. } else if (lquery) {
  1313. /* Return optimal workspace */
  1314. iwork[1] = iminwrk;
  1315. work[1] = (doublereal) optwrk;
  1316. work[2] = (doublereal) minwrk;
  1317. rwork[1] = (doublereal) rminwrk;
  1318. return 0;
  1319. }
  1320. /* Quick return if the matrix is void. */
  1321. if (*m == 0 || *n == 0) {
  1322. return 0;
  1323. }
  1324. big = dlamch_("O");
  1325. ascaled = FALSE_;
  1326. iwoff = 1;
  1327. if (rowprm) {
  1328. iwoff = *m;
  1329. /* ell-infinity norm - this enhances numerical robustness in */
  1330. /* the case of differently scaled rows. */
  1331. i__1 = *m;
  1332. for (p = 1; p <= i__1; ++p) {
  1333. /* RWORK(p) = ABS( A(p,ICAMAX(N,A(p,1),LDA)) ) */
  1334. /* [[DLANGE will return NaN if an entry of the p-th row is Nan]] */
  1335. rwork[p] = dlange_("M", &c__1, n, &a[p + a_dim1], lda, rdummy);
  1336. if (rwork[p] != rwork[p] || rwork[p] * 0. != 0.) {
  1337. *info = -8;
  1338. i__2 = -(*info);
  1339. xerbla_("DGESVDQ", &i__2, (ftnlen)7);
  1340. return 0;
  1341. }
  1342. /* L1904: */
  1343. }
  1344. i__1 = *m - 1;
  1345. for (p = 1; p <= i__1; ++p) {
  1346. i__2 = *m - p + 1;
  1347. q = idamax_(&i__2, &rwork[p], &c__1) + p - 1;
  1348. iwork[*n + p] = q;
  1349. if (p != q) {
  1350. rtmp = rwork[p];
  1351. rwork[p] = rwork[q];
  1352. rwork[q] = rtmp;
  1353. }
  1354. /* L1952: */
  1355. }
  1356. if (rwork[1] == 0.) {
  1357. /* Quick return: A is the M x N zero matrix. */
  1358. *numrank = 0;
  1359. dlaset_("G", n, &c__1, &c_b72, &c_b72, &s[1], n);
  1360. if (wntus) {
  1361. dlaset_("G", m, n, &c_b72, &c_b76, &u[u_offset], ldu);
  1362. }
  1363. if (wntua) {
  1364. dlaset_("G", m, m, &c_b72, &c_b76, &u[u_offset], ldu);
  1365. }
  1366. if (wntva) {
  1367. dlaset_("G", n, n, &c_b72, &c_b76, &v[v_offset], ldv);
  1368. }
  1369. if (wntuf) {
  1370. dlaset_("G", n, &c__1, &c_b72, &c_b72, &work[1], n)
  1371. ;
  1372. dlaset_("G", m, n, &c_b72, &c_b76, &u[u_offset], ldu);
  1373. }
  1374. i__1 = *n;
  1375. for (p = 1; p <= i__1; ++p) {
  1376. iwork[p] = p;
  1377. /* L5001: */
  1378. }
  1379. if (rowprm) {
  1380. i__1 = *n + *m - 1;
  1381. for (p = *n + 1; p <= i__1; ++p) {
  1382. iwork[p] = p - *n;
  1383. /* L5002: */
  1384. }
  1385. }
  1386. if (conda) {
  1387. rwork[1] = -1.;
  1388. }
  1389. rwork[2] = -1.;
  1390. return 0;
  1391. }
  1392. if (rwork[1] > big / sqrt((doublereal) (*m))) {
  1393. /* matrix by 1/sqrt(M) if too large entry detected */
  1394. d__1 = sqrt((doublereal) (*m));
  1395. dlascl_("G", &c__0, &c__0, &d__1, &c_b76, m, n, &a[a_offset], lda,
  1396. &ierr);
  1397. ascaled = TRUE_;
  1398. }
  1399. i__1 = *m - 1;
  1400. dlaswp_(n, &a[a_offset], lda, &c__1, &i__1, &iwork[*n + 1], &c__1);
  1401. }
  1402. /* norms overflows during the QR factorization. The SVD procedure should */
  1403. /* have its own scaling to save the singular values from overflows and */
  1404. /* underflows. That depends on the SVD procedure. */
  1405. if (! rowprm) {
  1406. rtmp = dlange_("M", m, n, &a[a_offset], lda, rdummy);
  1407. if (rtmp != rtmp || rtmp * 0. != 0.) {
  1408. *info = -8;
  1409. i__1 = -(*info);
  1410. xerbla_("DGESVDQ", &i__1, (ftnlen)7);
  1411. return 0;
  1412. }
  1413. if (rtmp > big / sqrt((doublereal) (*m))) {
  1414. /* matrix by 1/sqrt(M) if too large entry detected */
  1415. d__1 = sqrt((doublereal) (*m));
  1416. dlascl_("G", &c__0, &c__0, &d__1, &c_b76, m, n, &a[a_offset], lda,
  1417. &ierr);
  1418. ascaled = TRUE_;
  1419. }
  1420. }
  1421. /* A * P = Q * [ R ] */
  1422. /* [ 0 ] */
  1423. i__1 = *n;
  1424. for (p = 1; p <= i__1; ++p) {
  1425. iwork[p] = 0;
  1426. /* L1963: */
  1427. }
  1428. i__1 = *lwork - *n;
  1429. dgeqp3_(m, n, &a[a_offset], lda, &iwork[1], &work[1], &work[*n + 1], &
  1430. i__1, &ierr);
  1431. /* If the user requested accuracy level allows truncation in the */
  1432. /* computed upper triangular factor, the matrix R is examined and, */
  1433. /* if possible, replaced with its leading upper trapezoidal part. */
  1434. epsln = dlamch_("E");
  1435. sfmin = dlamch_("S");
  1436. /* SMALL = SFMIN / EPSLN */
  1437. nr = *n;
  1438. if (accla) {
  1439. /* Standard absolute error bound suffices. All sigma_i with */
  1440. /* sigma_i < N*EPS*||A||_F are flushed to zero. This is an */
  1441. /* aggressive enforcement of lower numerical rank by introducing a */
  1442. /* backward error of the order of N*EPS*||A||_F. */
  1443. nr = 1;
  1444. rtmp = sqrt((doublereal) (*n)) * epsln;
  1445. i__1 = *n;
  1446. for (p = 2; p <= i__1; ++p) {
  1447. if ((d__2 = a[p + p * a_dim1], abs(d__2)) < rtmp * (d__1 = a[
  1448. a_dim1 + 1], abs(d__1))) {
  1449. goto L3002;
  1450. }
  1451. ++nr;
  1452. /* L3001: */
  1453. }
  1454. L3002:
  1455. ;
  1456. } else if (acclm) {
  1457. /* Sudden drop on the diagonal of R is used as the criterion for being */
  1458. /* close-to-rank-deficient. The threshold is set to EPSLN=DLAMCH('E'). */
  1459. /* [[This can be made more flexible by replacing this hard-coded value */
  1460. /* with a user specified threshold.]] Also, the values that underflow */
  1461. /* will be truncated. */
  1462. nr = 1;
  1463. i__1 = *n;
  1464. for (p = 2; p <= i__1; ++p) {
  1465. if ((d__2 = a[p + p * a_dim1], abs(d__2)) < epsln * (d__1 = a[p -
  1466. 1 + (p - 1) * a_dim1], abs(d__1)) || (d__3 = a[p + p *
  1467. a_dim1], abs(d__3)) < sfmin) {
  1468. goto L3402;
  1469. }
  1470. ++nr;
  1471. /* L3401: */
  1472. }
  1473. L3402:
  1474. ;
  1475. } else {
  1476. /* obvious case of zero pivots. */
  1477. /* R(i,i)=0 => R(i:N,i:N)=0. */
  1478. nr = 1;
  1479. i__1 = *n;
  1480. for (p = 2; p <= i__1; ++p) {
  1481. if ((d__1 = a[p + p * a_dim1], abs(d__1)) == 0.) {
  1482. goto L3502;
  1483. }
  1484. ++nr;
  1485. /* L3501: */
  1486. }
  1487. L3502:
  1488. if (conda) {
  1489. /* Estimate the scaled condition number of A. Use the fact that it is */
  1490. /* the same as the scaled condition number of R. */
  1491. dlacpy_("U", n, n, &a[a_offset], lda, &v[v_offset], ldv);
  1492. /* Only the leading NR x NR submatrix of the triangular factor */
  1493. /* is considered. Only if NR=N will this give a reliable error */
  1494. /* bound. However, even for NR < N, this can be used on an */
  1495. /* expert level and obtain useful information in the sense of */
  1496. /* perturbation theory. */
  1497. i__1 = nr;
  1498. for (p = 1; p <= i__1; ++p) {
  1499. rtmp = dnrm2_(&p, &v[p * v_dim1 + 1], &c__1);
  1500. d__1 = 1. / rtmp;
  1501. dscal_(&p, &d__1, &v[p * v_dim1 + 1], &c__1);
  1502. /* L3053: */
  1503. }
  1504. if (! (lsvec || rsvec)) {
  1505. dpocon_("U", &nr, &v[v_offset], ldv, &c_b76, &rtmp, &work[1],
  1506. &iwork[*n + iwoff], &ierr);
  1507. } else {
  1508. dpocon_("U", &nr, &v[v_offset], ldv, &c_b76, &rtmp, &work[*n
  1509. + 1], &iwork[*n + iwoff], &ierr);
  1510. }
  1511. sconda = 1. / sqrt(rtmp);
  1512. /* For NR=N, SCONDA is an estimate of SQRT(||(R^* * R)^(-1)||_1), */
  1513. /* N^(-1/4) * SCONDA <= ||R^(-1)||_2 <= N^(1/4) * SCONDA */
  1514. /* See the reference [1] for more details. */
  1515. }
  1516. }
  1517. if (wntur) {
  1518. n1 = nr;
  1519. } else if (wntus || wntuf) {
  1520. n1 = *n;
  1521. } else if (wntua) {
  1522. n1 = *m;
  1523. }
  1524. if (! (rsvec || lsvec)) {
  1525. /* ....................................................................... */
  1526. /* ....................................................................... */
  1527. if (rtrans) {
  1528. /* the upper triangle of [A] to zero. */
  1529. i__1 = f2cmin(*n,nr);
  1530. for (p = 1; p <= i__1; ++p) {
  1531. i__2 = *n;
  1532. for (q = p + 1; q <= i__2; ++q) {
  1533. a[q + p * a_dim1] = a[p + q * a_dim1];
  1534. if (q <= nr) {
  1535. a[p + q * a_dim1] = 0.;
  1536. }
  1537. /* L1147: */
  1538. }
  1539. /* L1146: */
  1540. }
  1541. dgesvd_("N", "N", n, &nr, &a[a_offset], lda, &s[1], &u[u_offset],
  1542. ldu, &v[v_offset], ldv, &work[1], lwork, info);
  1543. } else {
  1544. if (nr > 1) {
  1545. i__1 = nr - 1;
  1546. i__2 = nr - 1;
  1547. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &a[a_dim1 + 2],
  1548. lda);
  1549. }
  1550. dgesvd_("N", "N", &nr, n, &a[a_offset], lda, &s[1], &u[u_offset],
  1551. ldu, &v[v_offset], ldv, &work[1], lwork, info);
  1552. }
  1553. } else if (lsvec && ! rsvec) {
  1554. /* ....................................................................... */
  1555. /* ......................................................................."""""""" */
  1556. if (rtrans) {
  1557. /* vectors of R */
  1558. i__1 = nr;
  1559. for (p = 1; p <= i__1; ++p) {
  1560. i__2 = *n;
  1561. for (q = p; q <= i__2; ++q) {
  1562. u[q + p * u_dim1] = a[p + q * a_dim1];
  1563. /* L1193: */
  1564. }
  1565. /* L1192: */
  1566. }
  1567. if (nr > 1) {
  1568. i__1 = nr - 1;
  1569. i__2 = nr - 1;
  1570. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &u[(u_dim1 << 1) +
  1571. 1], ldu);
  1572. }
  1573. /* vectors overwrite [U](1:NR,1:NR) as transposed. These */
  1574. /* will be pre-multiplied by Q to build the left singular vectors of A. */
  1575. i__1 = *lwork - *n;
  1576. dgesvd_("N", "O", n, &nr, &u[u_offset], ldu, &s[1], &u[u_offset],
  1577. ldu, &u[u_offset], ldu, &work[*n + 1], &i__1, info);
  1578. i__1 = nr;
  1579. for (p = 1; p <= i__1; ++p) {
  1580. i__2 = nr;
  1581. for (q = p + 1; q <= i__2; ++q) {
  1582. rtmp = u[q + p * u_dim1];
  1583. u[q + p * u_dim1] = u[p + q * u_dim1];
  1584. u[p + q * u_dim1] = rtmp;
  1585. /* L1120: */
  1586. }
  1587. /* L1119: */
  1588. }
  1589. } else {
  1590. dlacpy_("U", &nr, n, &a[a_offset], lda, &u[u_offset], ldu);
  1591. if (nr > 1) {
  1592. i__1 = nr - 1;
  1593. i__2 = nr - 1;
  1594. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &u[u_dim1 + 2],
  1595. ldu);
  1596. }
  1597. /* vectors overwrite [U](1:NR,1:NR) */
  1598. i__1 = *lwork - *n;
  1599. dgesvd_("O", "N", &nr, n, &u[u_offset], ldu, &s[1], &u[u_offset],
  1600. ldu, &v[v_offset], ldv, &work[*n + 1], &i__1, info);
  1601. /* R. These will be pre-multiplied by Q to build the left singular */
  1602. /* vectors of A. */
  1603. }
  1604. /* (M x NR) or (M x N) or (M x M). */
  1605. if (nr < *m && ! wntuf) {
  1606. i__1 = *m - nr;
  1607. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &u[nr + 1 + u_dim1], ldu);
  1608. if (nr < n1) {
  1609. i__1 = n1 - nr;
  1610. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &u[(nr + 1) * u_dim1
  1611. + 1], ldu);
  1612. i__1 = *m - nr;
  1613. i__2 = n1 - nr;
  1614. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[nr + 1 + (nr +
  1615. 1) * u_dim1], ldu);
  1616. }
  1617. }
  1618. /* The Q matrix from the first QRF is built into the left singular */
  1619. /* vectors matrix U. */
  1620. if (! wntuf) {
  1621. i__1 = *lwork - *n;
  1622. dormqr_("L", "N", m, &n1, n, &a[a_offset], lda, &work[1], &u[
  1623. u_offset], ldu, &work[*n + 1], &i__1, &ierr);
  1624. }
  1625. if (rowprm && ! wntuf) {
  1626. i__1 = *m - 1;
  1627. dlaswp_(&n1, &u[u_offset], ldu, &c__1, &i__1, &iwork[*n + 1], &
  1628. c_n1);
  1629. }
  1630. } else if (rsvec && ! lsvec) {
  1631. /* ....................................................................... */
  1632. /* ....................................................................... */
  1633. if (rtrans) {
  1634. i__1 = nr;
  1635. for (p = 1; p <= i__1; ++p) {
  1636. i__2 = *n;
  1637. for (q = p; q <= i__2; ++q) {
  1638. v[q + p * v_dim1] = a[p + q * a_dim1];
  1639. /* L1166: */
  1640. }
  1641. /* L1165: */
  1642. }
  1643. if (nr > 1) {
  1644. i__1 = nr - 1;
  1645. i__2 = nr - 1;
  1646. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &v[(v_dim1 << 1) +
  1647. 1], ldv);
  1648. }
  1649. /* vectors not computed */
  1650. if (wntvr || nr == *n) {
  1651. i__1 = *lwork - *n;
  1652. dgesvd_("O", "N", n, &nr, &v[v_offset], ldv, &s[1], &u[
  1653. u_offset], ldu, &u[u_offset], ldu, &work[*n + 1], &
  1654. i__1, info);
  1655. i__1 = nr;
  1656. for (p = 1; p <= i__1; ++p) {
  1657. i__2 = nr;
  1658. for (q = p + 1; q <= i__2; ++q) {
  1659. rtmp = v[q + p * v_dim1];
  1660. v[q + p * v_dim1] = v[p + q * v_dim1];
  1661. v[p + q * v_dim1] = rtmp;
  1662. /* L1122: */
  1663. }
  1664. /* L1121: */
  1665. }
  1666. if (nr < *n) {
  1667. i__1 = nr;
  1668. for (p = 1; p <= i__1; ++p) {
  1669. i__2 = *n;
  1670. for (q = nr + 1; q <= i__2; ++q) {
  1671. v[p + q * v_dim1] = v[q + p * v_dim1];
  1672. /* L1104: */
  1673. }
  1674. /* L1103: */
  1675. }
  1676. }
  1677. dlapmt_(&c_false, &nr, n, &v[v_offset], ldv, &iwork[1]);
  1678. } else {
  1679. /* [!] This is simple implementation that augments [V](1:N,1:NR) */
  1680. /* by padding a zero block. In the case NR << N, a more efficient */
  1681. /* way is to first use the QR factorization. For more details */
  1682. /* how to implement this, see the " FULL SVD " branch. */
  1683. i__1 = *n - nr;
  1684. dlaset_("G", n, &i__1, &c_b72, &c_b72, &v[(nr + 1) * v_dim1 +
  1685. 1], ldv);
  1686. i__1 = *lwork - *n;
  1687. dgesvd_("O", "N", n, n, &v[v_offset], ldv, &s[1], &u[u_offset]
  1688. , ldu, &u[u_offset], ldu, &work[*n + 1], &i__1, info);
  1689. i__1 = *n;
  1690. for (p = 1; p <= i__1; ++p) {
  1691. i__2 = *n;
  1692. for (q = p + 1; q <= i__2; ++q) {
  1693. rtmp = v[q + p * v_dim1];
  1694. v[q + p * v_dim1] = v[p + q * v_dim1];
  1695. v[p + q * v_dim1] = rtmp;
  1696. /* L1124: */
  1697. }
  1698. /* L1123: */
  1699. }
  1700. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  1701. }
  1702. } else {
  1703. dlacpy_("U", &nr, n, &a[a_offset], lda, &v[v_offset], ldv);
  1704. if (nr > 1) {
  1705. i__1 = nr - 1;
  1706. i__2 = nr - 1;
  1707. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &v[v_dim1 + 2],
  1708. ldv);
  1709. }
  1710. /* vectors stored in U(1:NR,1:NR) */
  1711. if (wntvr || nr == *n) {
  1712. i__1 = *lwork - *n;
  1713. dgesvd_("N", "O", &nr, n, &v[v_offset], ldv, &s[1], &u[
  1714. u_offset], ldu, &v[v_offset], ldv, &work[*n + 1], &
  1715. i__1, info);
  1716. dlapmt_(&c_false, &nr, n, &v[v_offset], ldv, &iwork[1]);
  1717. } else {
  1718. /* [!] This is simple implementation that augments [V](1:NR,1:N) */
  1719. /* by padding a zero block. In the case NR << N, a more efficient */
  1720. /* way is to first use the LQ factorization. For more details */
  1721. /* how to implement this, see the " FULL SVD " branch. */
  1722. i__1 = *n - nr;
  1723. dlaset_("G", &i__1, n, &c_b72, &c_b72, &v[nr + 1 + v_dim1],
  1724. ldv);
  1725. i__1 = *lwork - *n;
  1726. dgesvd_("N", "O", n, n, &v[v_offset], ldv, &s[1], &u[u_offset]
  1727. , ldu, &v[v_offset], ldv, &work[*n + 1], &i__1, info);
  1728. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  1729. }
  1730. /* vectors of A. */
  1731. }
  1732. } else {
  1733. /* ....................................................................... */
  1734. /* ....................................................................... */
  1735. if (rtrans) {
  1736. if (wntvr || nr == *n) {
  1737. /* vectors of R**T */
  1738. i__1 = nr;
  1739. for (p = 1; p <= i__1; ++p) {
  1740. i__2 = *n;
  1741. for (q = p; q <= i__2; ++q) {
  1742. v[q + p * v_dim1] = a[p + q * a_dim1];
  1743. /* L1169: */
  1744. }
  1745. /* L1168: */
  1746. }
  1747. if (nr > 1) {
  1748. i__1 = nr - 1;
  1749. i__2 = nr - 1;
  1750. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &v[(v_dim1 <<
  1751. 1) + 1], ldv);
  1752. }
  1753. /* singular vectors of R**T stored in [U](1:NR,1:NR) as transposed */
  1754. i__1 = *lwork - *n;
  1755. dgesvd_("O", "A", n, &nr, &v[v_offset], ldv, &s[1], &v[
  1756. v_offset], ldv, &u[u_offset], ldu, &work[*n + 1], &
  1757. i__1, info);
  1758. i__1 = nr;
  1759. for (p = 1; p <= i__1; ++p) {
  1760. i__2 = nr;
  1761. for (q = p + 1; q <= i__2; ++q) {
  1762. rtmp = v[q + p * v_dim1];
  1763. v[q + p * v_dim1] = v[p + q * v_dim1];
  1764. v[p + q * v_dim1] = rtmp;
  1765. /* L1116: */
  1766. }
  1767. /* L1115: */
  1768. }
  1769. if (nr < *n) {
  1770. i__1 = nr;
  1771. for (p = 1; p <= i__1; ++p) {
  1772. i__2 = *n;
  1773. for (q = nr + 1; q <= i__2; ++q) {
  1774. v[p + q * v_dim1] = v[q + p * v_dim1];
  1775. /* L1102: */
  1776. }
  1777. /* L1101: */
  1778. }
  1779. }
  1780. dlapmt_(&c_false, &nr, n, &v[v_offset], ldv, &iwork[1]);
  1781. i__1 = nr;
  1782. for (p = 1; p <= i__1; ++p) {
  1783. i__2 = nr;
  1784. for (q = p + 1; q <= i__2; ++q) {
  1785. rtmp = u[q + p * u_dim1];
  1786. u[q + p * u_dim1] = u[p + q * u_dim1];
  1787. u[p + q * u_dim1] = rtmp;
  1788. /* L1118: */
  1789. }
  1790. /* L1117: */
  1791. }
  1792. if (nr < *m && ! wntuf) {
  1793. i__1 = *m - nr;
  1794. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &u[nr + 1 +
  1795. u_dim1], ldu);
  1796. if (nr < n1) {
  1797. i__1 = n1 - nr;
  1798. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &u[(nr + 1) *
  1799. u_dim1 + 1], ldu);
  1800. i__1 = *m - nr;
  1801. i__2 = n1 - nr;
  1802. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[nr + 1
  1803. + (nr + 1) * u_dim1], ldu);
  1804. }
  1805. }
  1806. } else {
  1807. /* vectors of R**T */
  1808. /* [[The optimal ratio N/NR for using QRF instead of padding */
  1809. /* with zeros. Here hard coded to 2; it must be at least */
  1810. /* two due to work space constraints.]] */
  1811. /* OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0) */
  1812. /* OPTRATIO = MAX( OPTRATIO, 2 ) */
  1813. optratio = 2;
  1814. if (optratio * nr > *n) {
  1815. i__1 = nr;
  1816. for (p = 1; p <= i__1; ++p) {
  1817. i__2 = *n;
  1818. for (q = p; q <= i__2; ++q) {
  1819. v[q + p * v_dim1] = a[p + q * a_dim1];
  1820. /* L1199: */
  1821. }
  1822. /* L1198: */
  1823. }
  1824. if (nr > 1) {
  1825. i__1 = nr - 1;
  1826. i__2 = nr - 1;
  1827. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &v[(v_dim1
  1828. << 1) + 1], ldv);
  1829. }
  1830. i__1 = *n - nr;
  1831. dlaset_("A", n, &i__1, &c_b72, &c_b72, &v[(nr + 1) *
  1832. v_dim1 + 1], ldv);
  1833. i__1 = *lwork - *n;
  1834. dgesvd_("O", "A", n, n, &v[v_offset], ldv, &s[1], &v[
  1835. v_offset], ldv, &u[u_offset], ldu, &work[*n + 1],
  1836. &i__1, info);
  1837. i__1 = *n;
  1838. for (p = 1; p <= i__1; ++p) {
  1839. i__2 = *n;
  1840. for (q = p + 1; q <= i__2; ++q) {
  1841. rtmp = v[q + p * v_dim1];
  1842. v[q + p * v_dim1] = v[p + q * v_dim1];
  1843. v[p + q * v_dim1] = rtmp;
  1844. /* L1114: */
  1845. }
  1846. /* L1113: */
  1847. }
  1848. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  1849. /* (M x N1), i.e. (M x N) or (M x M). */
  1850. i__1 = *n;
  1851. for (p = 1; p <= i__1; ++p) {
  1852. i__2 = *n;
  1853. for (q = p + 1; q <= i__2; ++q) {
  1854. rtmp = u[q + p * u_dim1];
  1855. u[q + p * u_dim1] = u[p + q * u_dim1];
  1856. u[p + q * u_dim1] = rtmp;
  1857. /* L1112: */
  1858. }
  1859. /* L1111: */
  1860. }
  1861. if (*n < *m && ! wntuf) {
  1862. i__1 = *m - *n;
  1863. dlaset_("A", &i__1, n, &c_b72, &c_b72, &u[*n + 1 +
  1864. u_dim1], ldu);
  1865. if (*n < n1) {
  1866. i__1 = n1 - *n;
  1867. dlaset_("A", n, &i__1, &c_b72, &c_b72, &u[(*n + 1)
  1868. * u_dim1 + 1], ldu);
  1869. i__1 = *m - *n;
  1870. i__2 = n1 - *n;
  1871. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[*n
  1872. + 1 + (*n + 1) * u_dim1], ldu);
  1873. }
  1874. }
  1875. } else {
  1876. /* singular vectors of R */
  1877. i__1 = nr;
  1878. for (p = 1; p <= i__1; ++p) {
  1879. i__2 = *n;
  1880. for (q = p; q <= i__2; ++q) {
  1881. u[q + (nr + p) * u_dim1] = a[p + q * a_dim1];
  1882. /* L1197: */
  1883. }
  1884. /* L1196: */
  1885. }
  1886. if (nr > 1) {
  1887. i__1 = nr - 1;
  1888. i__2 = nr - 1;
  1889. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &u[(nr + 2)
  1890. * u_dim1 + 1], ldu);
  1891. }
  1892. i__1 = *lwork - *n - nr;
  1893. dgeqrf_(n, &nr, &u[(nr + 1) * u_dim1 + 1], ldu, &work[*n
  1894. + 1], &work[*n + nr + 1], &i__1, &ierr);
  1895. i__1 = nr;
  1896. for (p = 1; p <= i__1; ++p) {
  1897. i__2 = *n;
  1898. for (q = 1; q <= i__2; ++q) {
  1899. v[q + p * v_dim1] = u[p + (nr + q) * u_dim1];
  1900. /* L1144: */
  1901. }
  1902. /* L1143: */
  1903. }
  1904. i__1 = nr - 1;
  1905. i__2 = nr - 1;
  1906. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &v[(v_dim1 <<
  1907. 1) + 1], ldv);
  1908. i__1 = *lwork - *n - nr;
  1909. dgesvd_("S", "O", &nr, &nr, &v[v_offset], ldv, &s[1], &u[
  1910. u_offset], ldu, &v[v_offset], ldv, &work[*n + nr
  1911. + 1], &i__1, info);
  1912. i__1 = *n - nr;
  1913. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &v[nr + 1 +
  1914. v_dim1], ldv);
  1915. i__1 = *n - nr;
  1916. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &v[(nr + 1) *
  1917. v_dim1 + 1], ldv);
  1918. i__1 = *n - nr;
  1919. i__2 = *n - nr;
  1920. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &v[nr + 1 + (
  1921. nr + 1) * v_dim1], ldv);
  1922. i__1 = *lwork - *n - nr;
  1923. dormqr_("R", "C", n, n, &nr, &u[(nr + 1) * u_dim1 + 1],
  1924. ldu, &work[*n + 1], &v[v_offset], ldv, &work[*n +
  1925. nr + 1], &i__1, &ierr);
  1926. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  1927. /* (M x NR) or (M x N) or (M x M). */
  1928. if (nr < *m && ! wntuf) {
  1929. i__1 = *m - nr;
  1930. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &u[nr + 1 +
  1931. u_dim1], ldu);
  1932. if (nr < n1) {
  1933. i__1 = n1 - nr;
  1934. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &u[(nr +
  1935. 1) * u_dim1 + 1], ldu);
  1936. i__1 = *m - nr;
  1937. i__2 = n1 - nr;
  1938. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[nr
  1939. + 1 + (nr + 1) * u_dim1], ldu);
  1940. }
  1941. }
  1942. }
  1943. }
  1944. } else {
  1945. if (wntvr || nr == *n) {
  1946. dlacpy_("U", &nr, n, &a[a_offset], lda, &v[v_offset], ldv);
  1947. if (nr > 1) {
  1948. i__1 = nr - 1;
  1949. i__2 = nr - 1;
  1950. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &v[v_dim1 + 2],
  1951. ldv);
  1952. }
  1953. /* singular vectors of R stored in [U](1:NR,1:NR) */
  1954. i__1 = *lwork - *n;
  1955. dgesvd_("S", "O", &nr, n, &v[v_offset], ldv, &s[1], &u[
  1956. u_offset], ldu, &v[v_offset], ldv, &work[*n + 1], &
  1957. i__1, info);
  1958. dlapmt_(&c_false, &nr, n, &v[v_offset], ldv, &iwork[1]);
  1959. /* (M x NR) or (M x N) or (M x M). */
  1960. if (nr < *m && ! wntuf) {
  1961. i__1 = *m - nr;
  1962. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &u[nr + 1 +
  1963. u_dim1], ldu);
  1964. if (nr < n1) {
  1965. i__1 = n1 - nr;
  1966. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &u[(nr + 1) *
  1967. u_dim1 + 1], ldu);
  1968. i__1 = *m - nr;
  1969. i__2 = n1 - nr;
  1970. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[nr + 1
  1971. + (nr + 1) * u_dim1], ldu);
  1972. }
  1973. }
  1974. } else {
  1975. /* is then N1 (N or M) */
  1976. /* [[The optimal ratio N/NR for using LQ instead of padding */
  1977. /* with zeros. Here hard coded to 2; it must be at least */
  1978. /* two due to work space constraints.]] */
  1979. /* OPTRATIO = ILAENV(6, 'DGESVD', 'S' // 'O', NR,N,0,0) */
  1980. /* OPTRATIO = MAX( OPTRATIO, 2 ) */
  1981. optratio = 2;
  1982. if (optratio * nr > *n) {
  1983. dlacpy_("U", &nr, n, &a[a_offset], lda, &v[v_offset], ldv);
  1984. if (nr > 1) {
  1985. i__1 = nr - 1;
  1986. i__2 = nr - 1;
  1987. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &v[v_dim1
  1988. + 2], ldv);
  1989. }
  1990. /* singular vectors of R stored in [U](1:NR,1:NR) */
  1991. i__1 = *n - nr;
  1992. dlaset_("A", &i__1, n, &c_b72, &c_b72, &v[nr + 1 + v_dim1]
  1993. , ldv);
  1994. i__1 = *lwork - *n;
  1995. dgesvd_("S", "O", n, n, &v[v_offset], ldv, &s[1], &u[
  1996. u_offset], ldu, &v[v_offset], ldv, &work[*n + 1],
  1997. &i__1, info);
  1998. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  1999. /* singular vectors of A. The leading N left singular vectors */
  2000. /* are in [U](1:N,1:N) */
  2001. /* (M x N1), i.e. (M x N) or (M x M). */
  2002. if (*n < *m && ! wntuf) {
  2003. i__1 = *m - *n;
  2004. dlaset_("A", &i__1, n, &c_b72, &c_b72, &u[*n + 1 +
  2005. u_dim1], ldu);
  2006. if (*n < n1) {
  2007. i__1 = n1 - *n;
  2008. dlaset_("A", n, &i__1, &c_b72, &c_b72, &u[(*n + 1)
  2009. * u_dim1 + 1], ldu);
  2010. i__1 = *m - *n;
  2011. i__2 = n1 - *n;
  2012. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[*n
  2013. + 1 + (*n + 1) * u_dim1], ldu);
  2014. }
  2015. }
  2016. } else {
  2017. dlacpy_("U", &nr, n, &a[a_offset], lda, &u[nr + 1 +
  2018. u_dim1], ldu);
  2019. if (nr > 1) {
  2020. i__1 = nr - 1;
  2021. i__2 = nr - 1;
  2022. dlaset_("L", &i__1, &i__2, &c_b72, &c_b72, &u[nr + 2
  2023. + u_dim1], ldu);
  2024. }
  2025. i__1 = *lwork - *n - nr;
  2026. dgelqf_(&nr, n, &u[nr + 1 + u_dim1], ldu, &work[*n + 1], &
  2027. work[*n + nr + 1], &i__1, &ierr);
  2028. dlacpy_("L", &nr, &nr, &u[nr + 1 + u_dim1], ldu, &v[
  2029. v_offset], ldv);
  2030. if (nr > 1) {
  2031. i__1 = nr - 1;
  2032. i__2 = nr - 1;
  2033. dlaset_("U", &i__1, &i__2, &c_b72, &c_b72, &v[(v_dim1
  2034. << 1) + 1], ldv);
  2035. }
  2036. i__1 = *lwork - *n - nr;
  2037. dgesvd_("S", "O", &nr, &nr, &v[v_offset], ldv, &s[1], &u[
  2038. u_offset], ldu, &v[v_offset], ldv, &work[*n + nr
  2039. + 1], &i__1, info);
  2040. i__1 = *n - nr;
  2041. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &v[nr + 1 +
  2042. v_dim1], ldv);
  2043. i__1 = *n - nr;
  2044. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &v[(nr + 1) *
  2045. v_dim1 + 1], ldv);
  2046. i__1 = *n - nr;
  2047. i__2 = *n - nr;
  2048. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &v[nr + 1 + (
  2049. nr + 1) * v_dim1], ldv);
  2050. i__1 = *lwork - *n - nr;
  2051. dormlq_("R", "N", n, n, &nr, &u[nr + 1 + u_dim1], ldu, &
  2052. work[*n + 1], &v[v_offset], ldv, &work[*n + nr +
  2053. 1], &i__1, &ierr);
  2054. dlapmt_(&c_false, n, n, &v[v_offset], ldv, &iwork[1]);
  2055. /* (M x NR) or (M x N) or (M x M). */
  2056. if (nr < *m && ! wntuf) {
  2057. i__1 = *m - nr;
  2058. dlaset_("A", &i__1, &nr, &c_b72, &c_b72, &u[nr + 1 +
  2059. u_dim1], ldu);
  2060. if (nr < n1) {
  2061. i__1 = n1 - nr;
  2062. dlaset_("A", &nr, &i__1, &c_b72, &c_b72, &u[(nr +
  2063. 1) * u_dim1 + 1], ldu);
  2064. i__1 = *m - nr;
  2065. i__2 = n1 - nr;
  2066. dlaset_("A", &i__1, &i__2, &c_b72, &c_b76, &u[nr
  2067. + 1 + (nr + 1) * u_dim1], ldu);
  2068. }
  2069. }
  2070. }
  2071. }
  2072. }
  2073. /* The Q matrix from the first QRF is built into the left singular */
  2074. /* vectors matrix U. */
  2075. if (! wntuf) {
  2076. i__1 = *lwork - *n;
  2077. dormqr_("L", "N", m, &n1, n, &a[a_offset], lda, &work[1], &u[
  2078. u_offset], ldu, &work[*n + 1], &i__1, &ierr);
  2079. }
  2080. if (rowprm && ! wntuf) {
  2081. i__1 = *m - 1;
  2082. dlaswp_(&n1, &u[u_offset], ldu, &c__1, &i__1, &iwork[*n + 1], &
  2083. c_n1);
  2084. }
  2085. /* ... end of the "full SVD" branch */
  2086. }
  2087. /* Check whether some singular values are returned as zeros, e.g. */
  2088. /* due to underflow, and update the numerical rank. */
  2089. p = nr;
  2090. for (q = p; q >= 1; --q) {
  2091. if (s[q] > 0.) {
  2092. goto L4002;
  2093. }
  2094. --nr;
  2095. /* L4001: */
  2096. }
  2097. L4002:
  2098. /* singular values are set to zero. */
  2099. if (nr < *n) {
  2100. i__1 = *n - nr;
  2101. dlaset_("G", &i__1, &c__1, &c_b72, &c_b72, &s[nr + 1], n);
  2102. }
  2103. /* values. */
  2104. if (ascaled) {
  2105. d__1 = sqrt((doublereal) (*m));
  2106. dlascl_("G", &c__0, &c__0, &c_b76, &d__1, &nr, &c__1, &s[1], n, &ierr);
  2107. }
  2108. if (conda) {
  2109. rwork[1] = sconda;
  2110. }
  2111. rwork[2] = (doublereal) (p - nr);
  2112. /* exact zeros in DGESVD() applied to the (possibly truncated) */
  2113. /* full row rank triangular (trapezoidal) factor of A. */
  2114. *numrank = nr;
  2115. return 0;
  2116. /* End of DGESVDQ */
  2117. } /* dgesvdq_ */