LAPACK  3.6.1
LAPACK: Linear Algebra PACKage
subroutine derrls ( character*3  PATH,
integer  NUNIT 
)

DERRLS

Purpose: 
 DERRLS tests the error exits for the DOUBLE PRECISION least squares
 driver routines (DGELS, SGELSS, SGELSY, SGELSD).
Parameters
[in]PATH
          PATH is CHARACTER*3
          The LAPACK path name for the routines to be tested.
[in]NUNIT
          NUNIT is INTEGER
          The unit number for output.
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date
November 2015

Definition at line 57 of file derrls.f.

57 *
58 * -- LAPACK test routine (version 3.6.0) --
59 * -- LAPACK is a software package provided by Univ. of Tennessee, --
60 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
61 * November 2015
62 *
63 * .. Scalar Arguments ..
64  CHARACTER*3 path
65  INTEGER nunit
66 * ..
67 *
68 * =====================================================================
69 *
70 * .. Parameters ..
71  INTEGER nmax
72  parameter ( nmax = 2 )
73 * ..
74 * .. Local Scalars ..
75  CHARACTER*2 c2
76  INTEGER info, irnk
77  DOUBLE PRECISION rcond
78 * ..
79 * .. Local Arrays ..
80  INTEGER ip( nmax )
81  DOUBLE PRECISION a( nmax, nmax ), b( nmax, nmax ), s( nmax ),
82  $ w( nmax )
83 * ..
84 * .. External Functions ..
85  LOGICAL lsamen
86  EXTERNAL lsamen
87 * ..
88 * .. External Subroutines ..
89  EXTERNAL alaesm, chkxer, dgels, dgelsd, dgelss, dgelsy
90 * ..
91 * .. Scalars in Common ..
92  LOGICAL lerr, ok
93  CHARACTER*32 srnamt
94  INTEGER infot, nout
95 * ..
96 * .. Common blocks ..
97  COMMON / infoc / infot, nout, ok, lerr
98  COMMON / srnamc / srnamt
99 * ..
100 * .. Executable Statements ..
101 *
102  nout = nunit
103  WRITE( nout, fmt = * )
104  c2 = path( 2: 3 )
105  a( 1, 1 ) = 1.0d+0
106  a( 1, 2 ) = 2.0d+0
107  a( 2, 2 ) = 3.0d+0
108  a( 2, 1 ) = 4.0d+0
109  ok = .true.
110 *
111  IF( lsamen( 2, c2, 'LS' ) ) THEN
112 *
113 * Test error exits for the least squares driver routines.
114 *
115 * DGELS
116 *
117  srnamt = 'DGELS '
118  infot = 1
119  CALL dgels( '/', 0, 0, 0, a, 1, b, 1, w, 1, info )
120  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
121  infot = 2
122  CALL dgels( 'N', -1, 0, 0, a, 1, b, 1, w, 1, info )
123  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
124  infot = 3
125  CALL dgels( 'N', 0, -1, 0, a, 1, b, 1, w, 1, info )
126  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
127  infot = 4
128  CALL dgels( 'N', 0, 0, -1, a, 1, b, 1, w, 1, info )
129  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
130  infot = 6
131  CALL dgels( 'N', 2, 0, 0, a, 1, b, 2, w, 2, info )
132  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
133  infot = 8
134  CALL dgels( 'N', 2, 0, 0, a, 2, b, 1, w, 2, info )
135  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
136  infot = 10
137  CALL dgels( 'N', 1, 1, 0, a, 1, b, 1, w, 1, info )
138  CALL chkxer( 'DGELS ', infot, nout, lerr, ok )
139 *
140 * DGELSS
141 *
142  srnamt = 'DGELSS'
143  infot = 1
144  CALL dgelss( -1, 0, 0, a, 1, b, 1, s, rcond, irnk, w, 1, info )
145  CALL chkxer( 'DGELSS', infot, nout, lerr, ok )
146  infot = 2
147  CALL dgelss( 0, -1, 0, a, 1, b, 1, s, rcond, irnk, w, 1, info )
148  CALL chkxer( 'DGELSS', infot, nout, lerr, ok )
149  infot = 3
150  CALL dgelss( 0, 0, -1, a, 1, b, 1, s, rcond, irnk, w, 1, info )
151  CALL chkxer( 'DGELSS', infot, nout, lerr, ok )
152  infot = 5
153  CALL dgelss( 2, 0, 0, a, 1, b, 2, s, rcond, irnk, w, 2, info )
154  CALL chkxer( 'DGELSS', infot, nout, lerr, ok )
155  infot = 7
156  CALL dgelss( 2, 0, 0, a, 2, b, 1, s, rcond, irnk, w, 2, info )
157  CALL chkxer( 'DGELSS', infot, nout, lerr, ok )
158 *
159 * DGELSY
160 *
161  srnamt = 'DGELSY'
162  infot = 1
163  CALL dgelsy( -1, 0, 0, a, 1, b, 1, ip, rcond, irnk, w, 10,
164  $ info )
165  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
166  infot = 2
167  CALL dgelsy( 0, -1, 0, a, 1, b, 1, ip, rcond, irnk, w, 10,
168  $ info )
169  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
170  infot = 3
171  CALL dgelsy( 0, 0, -1, a, 1, b, 1, ip, rcond, irnk, w, 10,
172  $ info )
173  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
174  infot = 5
175  CALL dgelsy( 2, 0, 0, a, 1, b, 2, ip, rcond, irnk, w, 10,
176  $ info )
177  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
178  infot = 7
179  CALL dgelsy( 2, 0, 0, a, 2, b, 1, ip, rcond, irnk, w, 10,
180  $ info )
181  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
182  infot = 12
183  CALL dgelsy( 2, 2, 1, a, 2, b, 2, ip, rcond, irnk, w, 1, info )
184  CALL chkxer( 'DGELSY', infot, nout, lerr, ok )
185 *
186 * DGELSD
187 *
188  srnamt = 'DGELSD'
189  infot = 1
190  CALL dgelsd( -1, 0, 0, a, 1, b, 1, s, rcond, irnk, w, 10, ip,
191  $ info )
192  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
193  infot = 2
194  CALL dgelsd( 0, -1, 0, a, 1, b, 1, s, rcond, irnk, w, 10, ip,
195  $ info )
196  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
197  infot = 3
198  CALL dgelsd( 0, 0, -1, a, 1, b, 1, s, rcond, irnk, w, 10, ip,
199  $ info )
200  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
201  infot = 5
202  CALL dgelsd( 2, 0, 0, a, 1, b, 2, s, rcond, irnk, w, 10, ip,
203  $ info )
204  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
205  infot = 7
206  CALL dgelsd( 2, 0, 0, a, 2, b, 1, s, rcond, irnk, w, 10, ip,
207  $ info )
208  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
209  infot = 12
210  CALL dgelsd( 2, 2, 1, a, 2, b, 2, s, rcond, irnk, w, 1, ip,
211  $ info )
212  CALL chkxer( 'DGELSD', infot, nout, lerr, ok )
213  END IF
214 *
215 * Print a summary line.
216 *
217  CALL alaesm( path, ok, nout )
218 *
219  RETURN
220 *
221 * End of DERRLS
222 *
lsamen
logical function lsamen(N, CA, CB)
LSAMEN
Definition: lsamen.f:76
alaesm
subroutine alaesm(PATH, OK, NOUT)
ALAESM
Definition: alaesm.f:65
dgelsd
subroutine dgelsd(M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, WORK, LWORK, IWORK, INFO)
DGELSD computes the minimum-norm solution to a linear least squares problem for GE matrices ...
Definition: dgelsd.f:211
chkxer
subroutine chkxer(SRNAMT, INFOT, NOUT, LERR, OK)
Definition: cblat2.f:3199
dgelss
subroutine dgelss(M, N, NRHS, A, LDA, B, LDB, S, RCOND, RANK, WORK, LWORK, INFO)
DGELSS solves overdetermined or underdetermined systems for GE matrices
Definition: dgelss.f:174
dgels
subroutine dgels(TRANS, M, N, NRHS, A, LDA, B, LDB, WORK, LWORK, INFO)
DGELS solves overdetermined or underdetermined systems for GE matrices
Definition: dgels.f:185
dgelsy
subroutine dgelsy(M, N, NRHS, A, LDA, B, LDB, JPVT, RCOND, RANK, WORK, LWORK, INFO)
DGELSY solves overdetermined or underdetermined systems for GE matrices
Definition: dgelsy.f:206

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