LAPACK 3.12.0 LAPACK: Linear Algebra PACKage
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slahilb.f
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1*> \brief \b SLAHILB
2*
3* =========== DOCUMENTATION ===========
4*
5* Online html documentation available at
6* http://www.netlib.org/lapack/explore-html/
7*
8* Definition:
9* ===========
10*
11* SUBROUTINE SLAHILB( N, NRHS, A, LDA, X, LDX, B, LDB, WORK, INFO)
12*
13* .. Scalar Arguments ..
14* INTEGER N, NRHS, LDA, LDX, LDB, INFO
15* .. Array Arguments ..
16* REAL A(LDA, N), X(LDX, NRHS), B(LDB, NRHS), WORK(N)
17* ..
18*
19*
20*> \par Purpose:
21* =============
22*>
23*> \verbatim
24*>
25*> SLAHILB generates an N by N scaled Hilbert matrix in A along with
26*> NRHS right-hand sides in B and solutions in X such that A*X=B.
27*>
28*> The Hilbert matrix is scaled by M = LCM(1, 2, ..., 2*N-1) so that all
29*> entries are integers. The right-hand sides are the first NRHS
30*> columns of M * the identity matrix, and the solutions are the
31*> first NRHS columns of the inverse Hilbert matrix.
32*>
33*> The condition number of the Hilbert matrix grows exponentially with
34*> its size, roughly as O(e ** (3.5*N)). Additionally, the inverse
35*> Hilbert matrices beyond a relatively small dimension cannot be
36*> generated exactly without extra precision. Precision is exhausted
37*> when the largest entry in the inverse Hilbert matrix is greater than
38*> 2 to the power of the number of bits in the fraction of the data type
39*> used plus one, which is 24 for single precision.
40*>
41*> In single, the generated solution is exact for N <= 6 and has
42*> small componentwise error for 7 <= N <= 11.
43*> \endverbatim
44*
45* Arguments:
46* ==========
47*
48*> \param[in] N
49*> \verbatim
50*> N is INTEGER
51*> The dimension of the matrix A.
52*> \endverbatim
53*>
54*> \param[in] NRHS
55*> \verbatim
56*> NRHS is INTEGER
57*> The requested number of right-hand sides.
58*> \endverbatim
59*>
60*> \param[out] A
61*> \verbatim
62*> A is REAL array, dimension (LDA, N)
63*> The generated scaled Hilbert matrix.
64*> \endverbatim
65*>
66*> \param[in] LDA
67*> \verbatim
68*> LDA is INTEGER
69*> The leading dimension of the array A. LDA >= N.
70*> \endverbatim
71*>
72*> \param[out] X
73*> \verbatim
74*> X is REAL array, dimension (LDX, NRHS)
75*> The generated exact solutions. Currently, the first NRHS
76*> columns of the inverse Hilbert matrix.
77*> \endverbatim
78*>
79*> \param[in] LDX
80*> \verbatim
81*> LDX is INTEGER
82*> The leading dimension of the array X. LDX >= N.
83*> \endverbatim
84*>
85*> \param[out] B
86*> \verbatim
87*> B is REAL array, dimension (LDB, NRHS)
88*> The generated right-hand sides. Currently, the first NRHS
89*> columns of LCM(1, 2, ..., 2*N-1) * the identity matrix.
90*> \endverbatim
91*>
92*> \param[in] LDB
93*> \verbatim
94*> LDB is INTEGER
95*> The leading dimension of the array B. LDB >= N.
96*> \endverbatim
97*>
98*> \param[out] WORK
99*> \verbatim
100*> WORK is REAL array, dimension (N)
101*> \endverbatim
102*>
103*> \param[out] INFO
104*> \verbatim
105*> INFO is INTEGER
106*> = 0: successful exit
107*> = 1: N is too large; the data is still generated but may not
108*> be not exact.
109*> < 0: if INFO = -i, the i-th argument had an illegal value
110*> \endverbatim
111*
112* Authors:
113* ========
114*
115*> \author Univ. of Tennessee
116*> \author Univ. of California Berkeley
117*> \author Univ. of Colorado Denver
118*> \author NAG Ltd.
119*
120*> \ingroup single_lin
121*
122* =====================================================================
123 SUBROUTINE slahilb( N, NRHS, A, LDA, X, LDX, B, LDB, WORK, INFO)
124*
125* -- LAPACK test routine --
126* -- LAPACK is a software package provided by Univ. of Tennessee, --
127* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
128*
129* .. Scalar Arguments ..
130 INTEGER N, NRHS, LDA, LDX, LDB, INFO
131* .. Array Arguments ..
132 REAL A(LDA, N), X(LDX, NRHS), B(LDB, NRHS), WORK(N)
133* ..
134*
135* =====================================================================
136* .. Local Scalars ..
137 INTEGER TM, TI, R
138 INTEGER M
139 INTEGER I, J
140* ..
141* .. Parameters ..
142* NMAX_EXACT the largest dimension where the generated data is
143* exact.
144* NMAX_APPROX the largest dimension where the generated data has
145* a small componentwise relative error.
146 INTEGER NMAX_EXACT, NMAX_APPROX
147 parameter(nmax_exact = 6, nmax_approx = 11)
148* ..
149* .. External Functions
150 EXTERNAL slaset
151 INTRINSIC real
152* ..
153* .. Executable Statements ..
154*
155* Test the input arguments
156*
157 info = 0
158 IF (n .LT. 0 .OR. n .GT. nmax_approx) THEN
159 info = -1
160 ELSE IF (nrhs .LT. 0) THEN
161 info = -2
162 ELSE IF (lda .LT. n) THEN
163 info = -4
164 ELSE IF (ldx .LT. n) THEN
165 info = -6
166 ELSE IF (ldb .LT. n) THEN
167 info = -8
168 END IF
169 IF (info .LT. 0) THEN
170 CALL xerbla('SLAHILB', -info)
171 RETURN
172 END IF
173 IF (n .GT. nmax_exact) THEN
174 info = 1
175 END IF
176*
177* Compute M = the LCM of the integers [1, 2*N-1]. The largest
178* reasonable N is small enough that integers suffice (up to N = 11).
179 m = 1
180 DO i = 2, (2*n-1)
181 tm = m
182 ti = i
183 r = mod(tm, ti)
184 DO WHILE (r .NE. 0)
185 tm = ti
186 ti = r
187 r = mod(tm, ti)
188 END DO
189 m = (m / ti) * i
190 END DO
191*
192* Generate the scaled Hilbert matrix in A
193 DO j = 1, n
194 DO i = 1, n
195 a(i, j) = real(m) / (i + j - 1)
196 END DO
197 END DO
198*
199* Generate matrix B as simply the first NRHS columns of M * the
200* identity.
201 CALL slaset('Full', n, nrhs, 0.0, real(m), b, ldb)
202*
203* Generate the true solutions in X. Because B = the first NRHS
204* columns of M*I, the true solutions are just the first NRHS columns
205* of the inverse Hilbert matrix.
206 work(1) = n
207 DO j = 2, n
208 work(j) = ( ( (work(j-1)/(j-1)) * (j-1 - n) ) /(j-1) )
209 \$ * (n +j -1)
210 END DO
211*
212 DO j = 1, nrhs
213 DO i = 1, n
214 x(i, j) = (work(i)*work(j)) / (i + j - 1)
215 END DO
216 END DO
217*
218 END
219
subroutine slahilb(n, nrhs, a, lda, x, ldx, b, ldb, work, info)
SLAHILB
Definition slahilb.f:124
subroutine xerbla(srname, info)
Definition cblat2.f:3285
subroutine slaset(uplo, m, n, alpha, beta, a, lda)
SLASET initializes the off-diagonal elements and the diagonal elements of a matrix to given values.
Definition slaset.f:110