1: *> \brief \b DLATDF uses the LU factorization of the n-by-n matrix computed by sgetc2 and computes a contribution to the reciprocal Dif-estimate.
2: *
3: * =========== DOCUMENTATION ===========
4: *
5: * Online html documentation available at
6: * http://www.netlib.org/lapack/explore-html/
7: *
8: *> \htmlonly
9: *> Download DLATDF + dependencies
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11: *> [TGZ]</a>
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13: *> [ZIP]</a>
14: *> <a href="http://www.netlib.org/cgi-bin/netlibfiles.txt?format=txt&filename=/lapack/lapack_routine/dlatdf.f">
15: *> [TXT]</a>
16: *> \endhtmlonly
17: *
18: * Definition:
19: * ===========
20: *
21: * SUBROUTINE DLATDF( IJOB, N, Z, LDZ, RHS, RDSUM, RDSCAL, IPIV,
22: * JPIV )
23: *
24: * .. Scalar Arguments ..
25: * INTEGER IJOB, LDZ, N
26: * DOUBLE PRECISION RDSCAL, RDSUM
27: * ..
28: * .. Array Arguments ..
29: * INTEGER IPIV( * ), JPIV( * )
30: * DOUBLE PRECISION RHS( * ), Z( LDZ, * )
31: * ..
32: *
33: *
34: *> \par Purpose:
35: * =============
36: *>
37: *> \verbatim
38: *>
39: *> DLATDF uses the LU factorization of the n-by-n matrix Z computed by
40: *> DGETC2 and computes a contribution to the reciprocal Dif-estimate
41: *> by solving Z * x = b for x, and choosing the r.h.s. b such that
42: *> the norm of x is as large as possible. On entry RHS = b holds the
43: *> contribution from earlier solved sub-systems, and on return RHS = x.
44: *>
45: *> The factorization of Z returned by DGETC2 has the form Z = P*L*U*Q,
46: *> where P and Q are permutation matrices. L is lower triangular with
47: *> unit diagonal elements and U is upper triangular.
48: *> \endverbatim
49: *
50: * Arguments:
51: * ==========
52: *
53: *> \param[in] IJOB
54: *> \verbatim
55: *> IJOB is INTEGER
56: *> IJOB = 2: First compute an approximative null-vector e
57: *> of Z using DGECON, e is normalized and solve for
58: *> Zx = +-e - f with the sign giving the greater value
59: *> of 2-norm(x). About 5 times as expensive as Default.
60: *> IJOB .ne. 2: Local look ahead strategy where all entries of
61: *> the r.h.s. b is chosen as either +1 or -1 (Default).
62: *> \endverbatim
63: *>
64: *> \param[in] N
65: *> \verbatim
66: *> N is INTEGER
67: *> The number of columns of the matrix Z.
68: *> \endverbatim
69: *>
70: *> \param[in] Z
71: *> \verbatim
72: *> Z is DOUBLE PRECISION array, dimension (LDZ, N)
73: *> On entry, the LU part of the factorization of the n-by-n
74: *> matrix Z computed by DGETC2: Z = P * L * U * Q
75: *> \endverbatim
76: *>
77: *> \param[in] LDZ
78: *> \verbatim
79: *> LDZ is INTEGER
80: *> The leading dimension of the array Z. LDA >= max(1, N).
81: *> \endverbatim
82: *>
83: *> \param[in,out] RHS
84: *> \verbatim
85: *> RHS is DOUBLE PRECISION array, dimension (N)
86: *> On entry, RHS contains contributions from other subsystems.
87: *> On exit, RHS contains the solution of the subsystem with
88: *> entries acoording to the value of IJOB (see above).
89: *> \endverbatim
90: *>
91: *> \param[in,out] RDSUM
92: *> \verbatim
93: *> RDSUM is DOUBLE PRECISION
94: *> On entry, the sum of squares of computed contributions to
95: *> the Dif-estimate under computation by DTGSYL, where the
96: *> scaling factor RDSCAL (see below) has been factored out.
97: *> On exit, the corresponding sum of squares updated with the
98: *> contributions from the current sub-system.
99: *> If TRANS = 'T' RDSUM is not touched.
100: *> NOTE: RDSUM only makes sense when DTGSY2 is called by STGSYL.
101: *> \endverbatim
102: *>
103: *> \param[in,out] RDSCAL
104: *> \verbatim
105: *> RDSCAL is DOUBLE PRECISION
106: *> On entry, scaling factor used to prevent overflow in RDSUM.
107: *> On exit, RDSCAL is updated w.r.t. the current contributions
108: *> in RDSUM.
109: *> If TRANS = 'T', RDSCAL is not touched.
110: *> NOTE: RDSCAL only makes sense when DTGSY2 is called by
111: *> DTGSYL.
112: *> \endverbatim
113: *>
114: *> \param[in] IPIV
115: *> \verbatim
116: *> IPIV is INTEGER array, dimension (N).
117: *> The pivot indices; for 1 <= i <= N, row i of the
118: *> matrix has been interchanged with row IPIV(i).
119: *> \endverbatim
120: *>
121: *> \param[in] JPIV
122: *> \verbatim
123: *> JPIV is INTEGER array, dimension (N).
124: *> The pivot indices; for 1 <= j <= N, column j of the
125: *> matrix has been interchanged with column JPIV(j).
126: *> \endverbatim
127: *
128: * Authors:
129: * ========
130: *
131: *> \author Univ. of Tennessee
132: *> \author Univ. of California Berkeley
133: *> \author Univ. of Colorado Denver
134: *> \author NAG Ltd.
135: *
136: *> \date June 2016
137: *
138: *> \ingroup doubleOTHERauxiliary
139: *
140: *> \par Further Details:
141: * =====================
142: *>
143: *> This routine is a further developed implementation of algorithm
144: *> BSOLVE in [1] using complete pivoting in the LU factorization.
145: *
146: *> \par Contributors:
147: * ==================
148: *>
149: *> Bo Kagstrom and Peter Poromaa, Department of Computing Science,
150: *> Umea University, S-901 87 Umea, Sweden.
151: *
152: *> \par References:
153: * ================
154: *>
155: *> \verbatim
156: *>
157: *>
158: *> [1] Bo Kagstrom and Lars Westin,
159: *> Generalized Schur Methods with Condition Estimators for
160: *> Solving the Generalized Sylvester Equation, IEEE Transactions
161: *> on Automatic Control, Vol. 34, No. 7, July 1989, pp 745-751.
162: *>
163: *> [2] Peter Poromaa,
164: *> On Efficient and Robust Estimators for the Separation
165: *> between two Regular Matrix Pairs with Applications in
166: *> Condition Estimation. Report IMINF-95.05, Departement of
167: *> Computing Science, Umea University, S-901 87 Umea, Sweden, 1995.
168: *> \endverbatim
169: *>
170: * =====================================================================
171: SUBROUTINE DLATDF( IJOB, N, Z, LDZ, RHS, RDSUM, RDSCAL, IPIV,
172: $ JPIV )
173: *
174: * -- LAPACK auxiliary routine (version 3.7.0) --
175: * -- LAPACK is a software package provided by Univ. of Tennessee, --
176: * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
177: * June 2016
178: *
179: * .. Scalar Arguments ..
180: INTEGER IJOB, LDZ, N
181: DOUBLE PRECISION RDSCAL, RDSUM
182: * ..
183: * .. Array Arguments ..
184: INTEGER IPIV( * ), JPIV( * )
185: DOUBLE PRECISION RHS( * ), Z( LDZ, * )
186: * ..
187: *
188: * =====================================================================
189: *
190: * .. Parameters ..
191: INTEGER MAXDIM
192: PARAMETER ( MAXDIM = 8 )
193: DOUBLE PRECISION ZERO, ONE
194: PARAMETER ( ZERO = 0.0D+0, ONE = 1.0D+0 )
195: * ..
196: * .. Local Scalars ..
197: INTEGER I, INFO, J, K
198: DOUBLE PRECISION BM, BP, PMONE, SMINU, SPLUS, TEMP
199: * ..
200: * .. Local Arrays ..
201: INTEGER IWORK( MAXDIM )
202: DOUBLE PRECISION WORK( 4*MAXDIM ), XM( MAXDIM ), XP( MAXDIM )
203: * ..
204: * .. External Subroutines ..
205: EXTERNAL DAXPY, DCOPY, DGECON, DGESC2, DLASSQ, DLASWP,
206: $ DSCAL
207: * ..
208: * .. External Functions ..
209: DOUBLE PRECISION DASUM, DDOT
210: EXTERNAL DASUM, DDOT
211: * ..
212: * .. Intrinsic Functions ..
213: INTRINSIC ABS, SQRT
214: * ..
215: * .. Executable Statements ..
216: *
217: IF( IJOB.NE.2 ) THEN
218: *
219: * Apply permutations IPIV to RHS
220: *
221: CALL DLASWP( 1, RHS, LDZ, 1, N-1, IPIV, 1 )
222: *
223: * Solve for L-part choosing RHS either to +1 or -1.
224: *
225: PMONE = -ONE
226: *
227: DO 10 J = 1, N - 1
228: BP = RHS( J ) + ONE
229: BM = RHS( J ) - ONE
230: SPLUS = ONE
231: *
232: * Look-ahead for L-part RHS(1:N-1) = + or -1, SPLUS and
233: * SMIN computed more efficiently than in BSOLVE [1].
234: *
235: SPLUS = SPLUS + DDOT( N-J, Z( J+1, J ), 1, Z( J+1, J ), 1 )
236: SMINU = DDOT( N-J, Z( J+1, J ), 1, RHS( J+1 ), 1 )
237: SPLUS = SPLUS*RHS( J )
238: IF( SPLUS.GT.SMINU ) THEN
239: RHS( J ) = BP
240: ELSE IF( SMINU.GT.SPLUS ) THEN
241: RHS( J ) = BM
242: ELSE
243: *
244: * In this case the updating sums are equal and we can
245: * choose RHS(J) +1 or -1. The first time this happens
246: * we choose -1, thereafter +1. This is a simple way to
247: * get good estimates of matrices like Byers well-known
248: * example (see [1]). (Not done in BSOLVE.)
249: *
250: RHS( J ) = RHS( J ) + PMONE
251: PMONE = ONE
252: END IF
253: *
254: * Compute the remaining r.h.s.
255: *
256: TEMP = -RHS( J )
257: CALL DAXPY( N-J, TEMP, Z( J+1, J ), 1, RHS( J+1 ), 1 )
258: *
259: 10 CONTINUE
260: *
261: * Solve for U-part, look-ahead for RHS(N) = +-1. This is not done
262: * in BSOLVE and will hopefully give us a better estimate because
263: * any ill-conditioning of the original matrix is transfered to U
264: * and not to L. U(N, N) is an approximation to sigma_min(LU).
265: *
266: CALL DCOPY( N-1, RHS, 1, XP, 1 )
267: XP( N ) = RHS( N ) + ONE
268: RHS( N ) = RHS( N ) - ONE
269: SPLUS = ZERO
270: SMINU = ZERO
271: DO 30 I = N, 1, -1
272: TEMP = ONE / Z( I, I )
273: XP( I ) = XP( I )*TEMP
274: RHS( I ) = RHS( I )*TEMP
275: DO 20 K = I + 1, N
276: XP( I ) = XP( I ) - XP( K )*( Z( I, K )*TEMP )
277: RHS( I ) = RHS( I ) - RHS( K )*( Z( I, K )*TEMP )
278: 20 CONTINUE
279: SPLUS = SPLUS + ABS( XP( I ) )
280: SMINU = SMINU + ABS( RHS( I ) )
281: 30 CONTINUE
282: IF( SPLUS.GT.SMINU )
283: $ CALL DCOPY( N, XP, 1, RHS, 1 )
284: *
285: * Apply the permutations JPIV to the computed solution (RHS)
286: *
287: CALL DLASWP( 1, RHS, LDZ, 1, N-1, JPIV, -1 )
288: *
289: * Compute the sum of squares
290: *
291: CALL DLASSQ( N, RHS, 1, RDSCAL, RDSUM )
292: *
293: ELSE
294: *
295: * IJOB = 2, Compute approximate nullvector XM of Z
296: *
297: CALL DGECON( 'I', N, Z, LDZ, ONE, TEMP, WORK, IWORK, INFO )
298: CALL DCOPY( N, WORK( N+1 ), 1, XM, 1 )
299: *
300: * Compute RHS
301: *
302: CALL DLASWP( 1, XM, LDZ, 1, N-1, IPIV, -1 )
303: TEMP = ONE / SQRT( DDOT( N, XM, 1, XM, 1 ) )
304: CALL DSCAL( N, TEMP, XM, 1 )
305: CALL DCOPY( N, XM, 1, XP, 1 )
306: CALL DAXPY( N, ONE, RHS, 1, XP, 1 )
307: CALL DAXPY( N, -ONE, XM, 1, RHS, 1 )
308: CALL DGESC2( N, Z, LDZ, RHS, IPIV, JPIV, TEMP )
309: CALL DGESC2( N, Z, LDZ, XP, IPIV, JPIV, TEMP )
310: IF( DASUM( N, XP, 1 ).GT.DASUM( N, RHS, 1 ) )
311: $ CALL DCOPY( N, XP, 1, RHS, 1 )
312: *
313: * Compute the sum of squares
314: *
315: CALL DLASSQ( N, RHS, 1, RDSCAL, RDSUM )
316: *
317: END IF
318: *
319: RETURN
320: *
321: * End of DLATDF
322: *
323: END
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