f06edf (dscal) (PDF version)
F06 (blas) Chapter Contents
F06 (blas) Chapter Introduction
NAG Library Manual
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NAG Library Routine Document
f06edf (dscal)
▸
▿
Contents
1
Purpose
2
Specification
3
Description
4
References
5
Arguments
6
Error Indicators and Warnings
7
Accuracy
8
Parallelism and Performance
9
Further Comments
10
Example
1
Purpose
f06edf (dscal)
multiplies a real vector by a real scalar.
2
Specification
Fortran Interface
Subroutine f06edf (
n
,
alpha
,
x
,
incx
)
Integer, Intent (In)
::
n
,
incx
Real (Kind=nag_wp), Intent (In)
::
alpha
Real (Kind=nag_wp), Intent (Inout)
::
x(*)
C Header Interface
#include nagmk26.h
void
f06edf_ (
const Integer *
n
,
const double *
alpha
,
double
x
[]
,
const Integer *
incx
)
The routine may be called by its BLAS name
dscal
.
3
Description
f06edf (dscal)
performs the operation
x
←
α
x
where
x
is an
n
-element real vector scattered with stride
incx
, and
α
is a real scalar.
4
References
Lawson C L, Hanson R J, Kincaid D R and Krogh F T (1979) Basic linear algebra supbrograms for Fortran usage
ACM Trans. Math. Software
5
308–325
5
Arguments
1:
n
– Integer
Input
On entry
:
n
, the number of elements in
x
.
2:
alpha
– Real (Kind=nag_wp)
Input
On entry
: the scalar
α
.
3:
x
*
– Real (Kind=nag_wp) array
Input/Output
Note:
the dimension of the array
x
must be at least
max
1
,
1
+
n
-
1
×
incx
.
On entry
: the
n
-element vector
x
.
x
i
must be stored in
x
1
+
i
-
1
×
incx
, for
i
=
1
,
2
,
…
,
n
.
Intermediate elements of
x
are not referenced.
On exit
: the vector
α
x
stored in the array elements used to supply the original vector
x
.
Intermediate elements of
x
are unchanged.
4:
incx
– Integer
Input
On entry
: the increment in the subscripts of
x
between successive elements of
x
.
Constraint
:
incx
>
0
.
6
Error Indicators and Warnings
None.
7
Accuracy
Not applicable.
8
Parallelism and Performance
f06edf (dscal)
is not threaded in any implementation.
9
Further Comments
None.
10
Example
None.
f06edf (dscal) (PDF version)
F06 (blas) Chapter Contents
F06 (blas) Chapter Introduction
NAG Library Manual
© The Numerical Algorithms Group Ltd, Oxford, UK. 2017