1*> \brief \b DLAPTM
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 DLAPTM( N, NRHS, ALPHA, D, E, X, LDX, BETA, B, LDB )
12*
13*       .. Scalar Arguments ..
14*       INTEGER            LDB, LDX, N, NRHS
15*       DOUBLE PRECISION   ALPHA, BETA
16*       ..
17*       .. Array Arguments ..
18*       DOUBLE PRECISION   B( LDB, * ), D( * ), E( * ), X( LDX, * )
19*       ..
20*
21*
22*> \par Purpose:
23*  =============
24*>
25*> \verbatim
26*>
27*> DLAPTM multiplies an N by NRHS matrix X by a symmetric tridiagonal
28*> matrix A and stores the result in a matrix B.  The operation has the
29*> form
30*>
31*>    B := alpha * A * X + beta * B
32*>
33*> where alpha may be either 1. or -1. and beta may be 0., 1., or -1.
34*> \endverbatim
35*
36*  Arguments:
37*  ==========
38*
39*> \param[in] N
40*> \verbatim
41*>          N is INTEGER
42*>          The order of the matrix A.  N >= 0.
43*> \endverbatim
44*>
45*> \param[in] NRHS
46*> \verbatim
47*>          NRHS is INTEGER
48*>          The number of right hand sides, i.e., the number of columns
49*>          of the matrices X and B.
50*> \endverbatim
51*>
52*> \param[in] ALPHA
53*> \verbatim
54*>          ALPHA is DOUBLE PRECISION
55*>          The scalar alpha.  ALPHA must be 1. or -1.; otherwise,
56*>          it is assumed to be 0.
57*> \endverbatim
58*>
59*> \param[in] D
60*> \verbatim
61*>          D is DOUBLE PRECISION array, dimension (N)
62*>          The n diagonal elements of the tridiagonal matrix A.
63*> \endverbatim
64*>
65*> \param[in] E
66*> \verbatim
67*>          E is DOUBLE PRECISION array, dimension (N-1)
68*>          The (n-1) subdiagonal or superdiagonal elements of A.
69*> \endverbatim
70*>
71*> \param[in] X
72*> \verbatim
73*>          X is DOUBLE PRECISION array, dimension (LDX,NRHS)
74*>          The N by NRHS matrix X.
75*> \endverbatim
76*>
77*> \param[in] LDX
78*> \verbatim
79*>          LDX is INTEGER
80*>          The leading dimension of the array X.  LDX >= max(N,1).
81*> \endverbatim
82*>
83*> \param[in] BETA
84*> \verbatim
85*>          BETA is DOUBLE PRECISION
86*>          The scalar beta.  BETA must be 0., 1., or -1.; otherwise,
87*>          it is assumed to be 1.
88*> \endverbatim
89*>
90*> \param[in,out] B
91*> \verbatim
92*>          B is DOUBLE PRECISION array, dimension (LDB,NRHS)
93*>          On entry, the N by NRHS matrix B.
94*>          On exit, B is overwritten by the matrix expression
95*>          B := alpha * A * X + beta * B.
96*> \endverbatim
97*>
98*> \param[in] LDB
99*> \verbatim
100*>          LDB is INTEGER
101*>          The leading dimension of the array B.  LDB >= max(N,1).
102*> \endverbatim
103*
104*  Authors:
105*  ========
106*
107*> \author Univ. of Tennessee
108*> \author Univ. of California Berkeley
109*> \author Univ. of Colorado Denver
110*> \author NAG Ltd.
111*
112*> \date December 2016
113*
114*> \ingroup double_lin
115*
116*  =====================================================================
117      SUBROUTINE DLAPTM( N, NRHS, ALPHA, D, E, X, LDX, BETA, B, LDB )
118*
119*  -- LAPACK test routine (version 3.7.0) --
120*  -- LAPACK is a software package provided by Univ. of Tennessee,    --
121*  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
122*     December 2016
123*
124*     .. Scalar Arguments ..
125      INTEGER            LDB, LDX, N, NRHS
126      DOUBLE PRECISION   ALPHA, BETA
127*     ..
128*     .. Array Arguments ..
129      DOUBLE PRECISION   B( LDB, * ), D( * ), E( * ), X( LDX, * )
130*     ..
131*
132*  =====================================================================
133*
134*     .. Parameters ..
135      DOUBLE PRECISION   ONE, ZERO
136      PARAMETER          ( ONE = 1.0D+0, ZERO = 0.0D+0 )
137*     ..
138*     .. Local Scalars ..
139      INTEGER            I, J
140*     ..
141*     .. Executable Statements ..
142*
143      IF( N.EQ.0 )
144     $   RETURN
145*
146*     Multiply B by BETA if BETA.NE.1.
147*
148      IF( BETA.EQ.ZERO ) THEN
149         DO 20 J = 1, NRHS
150            DO 10 I = 1, N
151               B( I, J ) = ZERO
152   10       CONTINUE
153   20    CONTINUE
154      ELSE IF( BETA.EQ.-ONE ) THEN
155         DO 40 J = 1, NRHS
156            DO 30 I = 1, N
157               B( I, J ) = -B( I, J )
158   30       CONTINUE
159   40    CONTINUE
160      END IF
161*
162      IF( ALPHA.EQ.ONE ) THEN
163*
164*        Compute B := B + A*X
165*
166         DO 60 J = 1, NRHS
167            IF( N.EQ.1 ) THEN
168               B( 1, J ) = B( 1, J ) + D( 1 )*X( 1, J )
169            ELSE
170               B( 1, J ) = B( 1, J ) + D( 1 )*X( 1, J ) +
171     $                     E( 1 )*X( 2, J )
172               B( N, J ) = B( N, J ) + E( N-1 )*X( N-1, J ) +
173     $                     D( N )*X( N, J )
174               DO 50 I = 2, N - 1
175                  B( I, J ) = B( I, J ) + E( I-1 )*X( I-1, J ) +
176     $                        D( I )*X( I, J ) + E( I )*X( I+1, J )
177   50          CONTINUE
178            END IF
179   60    CONTINUE
180      ELSE IF( ALPHA.EQ.-ONE ) THEN
181*
182*        Compute B := B - A*X
183*
184         DO 80 J = 1, NRHS
185            IF( N.EQ.1 ) THEN
186               B( 1, J ) = B( 1, J ) - D( 1 )*X( 1, J )
187            ELSE
188               B( 1, J ) = B( 1, J ) - D( 1 )*X( 1, J ) -
189     $                     E( 1 )*X( 2, J )
190               B( N, J ) = B( N, J ) - E( N-1 )*X( N-1, J ) -
191     $                     D( N )*X( N, J )
192               DO 70 I = 2, N - 1
193                  B( I, J ) = B( I, J ) - E( I-1 )*X( I-1, J ) -
194     $                        D( I )*X( I, J ) - E( I )*X( I+1, J )
195   70          CONTINUE
196            END IF
197   80    CONTINUE
198      END IF
199      RETURN
200*
201*     End of DLAPTM
202*
203      END
204