F06EWF (DSCTR) (PDF version)
F06 Chapter Contents
F06 Chapter Introduction
NAG Library Manual
NAG Library Routine Document
F06EWF (DSCTR)
Note:
before using this routine, please read the Users' Note for your implementation to check the interpretation of
bold italicised
terms and other implementation-dependent details.
▸
▿
Contents
1
Purpose
2
Specification
3
Description
4
References
5
Parameters
6
Error Indicators and Warnings
7
Accuracy
8
Parallelism and Performance
9
Further Comments
10
Example
1 Purpose
F06EWF (DSCTR) scatters the elements of a sparse real vector
x
stored in compressed form, into a real vector
y
in full storage form.
2 Specification
SUBROUTINE F06EWF (
NZ
,
X
,
INDX
,
Y
)
INTEGER
NZ, INDX(*)
REAL (KIND=nag_wp)
X(*), Y(*)
The routine may be called by its BLAS name
dsctr
.
3 Description
F06EWF (DSCTR) scatters the elements of a vector
x
, stored in compressed form, into a vector,
y
, in full storage form.
4 References
Dodson D S, Grimes R G and Lewis J G (1991) Sparse extensions to the Fortran basic linear algebra subprograms
ACM Trans. Math. Software
17
253–263
5 Parameters
1:
NZ
– INTEGER
Input
On entry
: the number of nonzeros in the sparse vector
x
.
2:
X
*
– REAL (KIND=nag_wp) array
Input
Note:
the dimension of the array
X
must be at least
max
1
,
NZ
.
On entry
: the nonzero elements of the sparse vector
x
.
3:
INDX
*
– INTEGER array
Input
Note:
the dimension of the array
INDX
must be at least
max
1
,
NZ
.
On entry
:
INDX
i
must contain the index of
X
i
in the sparse vector
x
, for
i
=
1
,
2
,
…
,
NZ
.
Constraint
: the indices must be distinct.
4:
Y
*
– REAL (KIND=nag_wp) array
Output
Note:
the dimension of the array
Y
must be at least
max
k
INDX
k
.
On exit
: the vector
y
. Only elements corresponding to indices in
INDX
are altered.
6 Error Indicators and Warnings
None.
7 Accuracy
Not applicable.
8 Parallelism and Performance
Not applicable.
9 Further Comments
None.
10 Example
None.
F06EWF (DSCTR) (PDF version)
F06 Chapter Contents
F06 Chapter Introduction
NAG Library Manual
© The Numerical Algorithms Group Ltd, Oxford, UK. 2015