I have this problem in Fortran where I need to generate a sequence of random numbers (precisely, 729 random numbers between 1 and 1000) and to do I use the intrinsic function random_number().
The problem, of course, is that it returns pseudorandom numbers and it happens to often that I get same values repeated. I'm not an expert in programming with Fortran, but how can I get 729 unique random numbers without repetitions? Can someone help me?
Here you go
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ cat the_chosen.f90
Program possibly_homework
Use, Intrinsic :: iso_fortran_env, Only : wp => real64
Implicit None( Type, External )
Integer, Parameter :: from = 1000
Integer, Parameter :: to_choose = 729
Real( wp ) :: rand
Integer, Dimension( : ), Allocatable :: the_many
Integer, Dimension( : ), Allocatable :: the_chosen
Integer :: the_chosen_one
Integer :: unit
Integer :: i
Allocate( the_many( 1:from ) )
the_many = [ ( i, i = 1, from ) ]
Allocate( the_chosen( 1:0 ) )
Do i = 1, to_choose
Call Random_number( rand )
the_chosen_one = 1 + Int( Size( the_many ) * rand )
the_chosen = [ the_chosen, the_many( the_chosen_one ) ]
the_many = [ the_many( :the_chosen_one - 1 ), the_many( the_chosen_one + 1: ) ]
End Do
Open( newunit = unit, file = 'the_chosen.dat' )
Do i = 1, Size( the_chosen )
Write( unit, '( i0, t20, i0 )' ) i, the_chosen( i )
End Do
Close( unit )
End Program possibly_homework
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ gfortran --version
GNU Fortran (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ gfortran -std=f2018 -Wall -Wextra -fcheck=all -O -g the_chosen.f90 -o the_chosen
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ ./the_chosen
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ head the_chosen.dat
1 303
2 916
3 414
4 452
5 116
6 962
7 392
8 675
9 153
10 458
ijb#LAPTOP-GUG8KQ9I:~/work/stack$ sort +1 -n the_chosen.dat | awk '{ print $2 }' | uniq -D
ijb#LAPTOP-GUG8KQ9I:~/work/stack$
This shows how you can in an inelegant way solve your problem.
program p
implicit none
integer, parameter :: n = 10
logical :: a(n) = .false.
integer b(n), cnt
real x
cnt = 1
do
call random_number(x)
b(cnt) = n * x + 1
if (.not. a(b(cnt))) then
if (b(cnt) > n) cycle
a(b(cnt)) = .true.
cnt = cnt + 1
if (cnt > n) exit
end if
end do
print '(*(1X,I0))', b
end program p
Order not important (as per Marta's question at How to remove random rows from a matrix in Fortran90 ). No shuffle required.
program test
implicit none
integer Nmax, Nsample, Nchoose
logical start
logical, allocatable :: mask(:)
integer cnt, i
real r
Nmax = 10 ! or 1000
Nsample = 7 ! or 729
start = .false.
Nchoose = Nsample
if ( Nsample > Nmax / 2 ) then
start = .true. ! go for the SMALLER likelihood of already taken
Nchoose = Nmax - Nsample
end if
allocate ( mask(Nmax) )
mask = start
cnt = 0
call random_seed()
do while ( cnt < Nchoose )
call random_number( r )
i = 1 + r * Nmax
if ( mask(i) .eqv. start ) then
mask(i) = .not. mask(i)
cnt = cnt + 1
end if
end do
do i = 1, Nmax
if ( mask(i) ) write( *, * ) i
end do
end program test
Related
I am new to fortran and I am trying to write code using random data instead of binned data in x, y, z as shown in my sample code.
implicit real*8(a-h,o-z)
dimension rm(4),rp1(4),rip1(4),rp2(4),rip2(4),rp3(4),rip3(4),
d rn(4),u1(4),u2(4),u3(4)
do ix= 1000,25000,1000
x = ix/1000000.
do iy= 1000,25000,1000
y = iy/100000.
do iz= 1,1000,25
z = iz/10000.
a=(x**2+y**2)/z
b=x*y*z
c=x*y**2+y*z**2+z*x**2
fr=(a*b)/c
if(fr.ge.0.05.and.fr.le.23)then
write(40,*)x,y,x,fr
else
endif
end do
end do
end do
stop
How to convert such code having binned data to a code using random draws.
As an example binned data here means possible fixed values of x are {1000/1000000.,2000/1000000., .....,25000/1000000.} i.e. 25 possible values in range {.001, .025} but they are not random values
In case of random values 25 points will be drawn from the range {.001, .025} randomly.
This my assumption about doing the analysis with random draws(previously I was not familiar with this ).
Something like
ian#eris:~/work/stack$ cat data.f90
Program random_data
Use, Intrinsic :: iso_fortran_env, Only : wp => real64
Implicit None
Real( wp ), Parameter :: min_rand = 0.001_wp
Real( wp ), Parameter :: max_rand = 0.025_wp
Integer, Parameter :: n_samples = 25
Real( wp ) :: x, y, z
Real( wp ) :: a, b, c
Real( wp ) :: fr
Integer :: i_sample
Do i_sample = 1, n_samples
Call Random_number( x )
Call Random_number( y )
Call Random_number( z )
x = x * ( max_rand - min_rand ) + min_rand
y = y * ( max_rand - min_rand ) + min_rand
z = z * ( max_rand - min_rand ) + min_rand
a=(x**2+y**2)/z
b=x*y*z
c=x*y**2+y*z**2+z*x**2
fr=(a*b)/c
If( fr >= 0.05_wp .And. fr <= 23.0_wp )Then
Write( 40, * ) x, y, x, fr
Endif
End Do
End Program random_data
ian#eris:~/work/stack$ gfortran-10 -Wall -Wextra -fcheck=all -std=f2008 -g -finit-real=snan data.f90
ian#eris:~/work/stack$ ./a.out;more fort.40
more: stat of fort.40 failed: No such file or directory
Unfortunately none of the random numbers in this run produced an output that lay in the desired range - however I did test it with 2500 samples and then a couple did.
I abstracted some code from a much larger coding project I'm working on. The code has an OMP parallel do loop which scales well with processor number when compiled with gfortran but badly when compiled with Intel. With gfortran, the code takes 18 seconds to run with 1 processor and 5 seconds to run with 4 processors. With Intel it takes 7 seconds to run with 1 processor and 14 seconds to run with 4 processors. I don't understand what's going on here. The code is below.
MODULE test
TYPE walker
DOUBLE PRECISION, DIMENSION(:,:), ALLOCATABLE :: R
END TYPE walker
TYPE walkerlist
INTEGER :: nwlkr
TYPE(walker), DIMENSION(:), ALLOCATABLE :: W
END TYPE walkerlist
CONTAINS
FUNCTION step( dTau, nelec, ndim ) RESULT ( dR )
DOUBLE PRECISION, INTENT(IN) :: dTau
INTEGER, INTENT(IN) :: nelec, ndim
DOUBLE PRECISION :: dR(ndim,nelec), rand1, rand2, N2DTau
INTEGER :: d, k
DOUBLE PRECISION, PARAMETER :: twopi = 8.d0 * atan(1.d0)
N2DTau = -2 * dTau
DO k = 1, nelec
DO d = 1, ndim
CALL RANDOM_NUMBER(rand1)
CALL RANDOM_NUMBER(rand2)
dR(d,k) = SQRT( N2DTau * LOG( rand1 ) ) * COS( twopi * rand2 )
END DO
END DO
END FUNCTION step
END MODULE test
PROGRAM walk
USE test
TYPE(walkerlist), TARGET :: Wl
DOUBLE PRECISION :: dTau
INTEGER :: istp, i, t1, t2, clock_rate, clock_max
Wl % nwlkr = 10000
ALLOCATE( Wl % W ( Wl % nwlkr ) )
DO i = 1, Wl % nwlkr
ALLOCATE( Wl % W(i) % R(3,2) )
END DO
dTau = 0.001
CALL SYSTEM_CLOCK ( t1, clock_rate, clock_max )
!$OMP PARALLEL DO SHARED( W ) DEFAULT( FIRSTPRIVATE )
DO i = 1, Wl % nwlkr
DO istp = 1, 4000
Wl % W(i) % R = Wl % W(i) % R + step( dTau, 2, 3 )
END DO
END DO
!$OMP END PARALLEL DO
CALL SYSTEM_CLOCK ( t2, clock_rate, clock_max )
Print*, "time:", REAL ( t2 - t1 ) / REAL ( clock_rate )
END PROGRAM walk
The issue was the random_number calls, where I'm guessing the threads were sharing seeds. I solved it by instead using the random number generating function ran.
rand1 = ran(s)
rand2 = ran(s)
Ran lets you input the seed s, which I made thread_private and of the save type. Ran changes the seed only for ifort and not gfortran, so I can't use it for the latter. Ran also sometimes outputs 0, which I personally need to always check for and discard. I also need to Ensure all threads start with a different seed.
I'm new to parallel programming, and I'm currently working on optimizing a code that works with electromagnetic calculations.
Analyzing how the program works, I realized that 85% of the time spent on execution is about solving a linear equation.
I studied a little bit of openmp but I have no idea how to parallelize a nested loop like this.
Any idea?
Thank you in advance. Follow the code below
Subroutine GaussEqSolver_Sym(n,ma,a,b,ep,kwji)
!------------------------------------------------------------------
! Solve sysmmetric linear equation ax=b by using Gauss elimination.
! If kwji=1, no solution;if kwji=0,has solution
! Input--n,ma,a(ma,n),b(n),ep,
! Output--b,kwji
!------------------------------------------------------------------
implicit real*8 (a-h,o-z)
dimension a(ma,n),b(n),m(n+1)
do 10 i=1,n
10 m(i)=i
do 120 k=1,n
p=0.0
do 20 i=k,n
do 20 j=k,n
if(dabs(a(i,j)).gt.dabs(p)) then
p=a(i,j)
io=i
jo=j
endif
20 continue
if(dabs(p)-ep) 30,30,35
30 kwji=1
return
35 continue
if(jo.eq.k) go to 45
do 40 i=1,n
t=a(i,jo)
a(i,jo)=a(i,k)
a(i,k)=t
40 continue
j=m(k)
m(k)=m(jo)
m(jo)=j
45 if(io.eq.k) go to 55
do 50 j=k,n
t=a(io,j)
a(io,j)=a(k,j)
a(k,j)=t
50 continue
t=b(io)
b(io)=b(k)
b(k)=t
55 p=1./p
in=n-1
if(k.eq.n) go to 65
do 60 j=k,in
60 a(k,j+1)=a(k,j+1)*p
65 b(k)=b(k)*p
if(k.eq.n) go to 120
do 80 i=k,in
do 70 j=k,in
70 a(i+1,j+1)=a(i+1,j+1)-a(i+1,k)*a(k,j+1)
80 b(i+1)=b(i+1)-a(i+1,k)*b(k)
120 continue
do 130 i1=2,n
i=n+1-i1
do 130 j=i,in
130 b(i)=b(i)-a(i,j+1)*b(j+1)
do 140 k=1,n
i=m(k)
140 a(1,i)=b(k)
do 150 k=1,n
150 b(k)=a(1,k)
kwji=0
return
end
If you are interested in performance you should be using LAPACK. To illustrate this I have written a simple driver program that compares the speed of the code you provided with calling DSYSV, the LAPACK routine that solves a set of linear equations for a symmetric, "double precision" matrix. The code and results are below, but in summary LAPACK varies from being 3.3 times faster than the Fortran, to 725 times faster. Note this is probably not an optimised LAPACK library, it is whatever comes with the Mint Linux I have installed on my laptop. Anyway, details below
ian#eris:~/work/stack$ cat solve.f90
Subroutine GaussEqSolver_Sym(n,ma,a,b,ep,kwji)
!------------------------------------------------------------------
! Solve sysmmetric linear equation ax=b by using Gauss elimination.
! If kwji=1, no solution;if kwji=0,has solution
! Input--n,ma,a(ma,n),b(n),ep,
! Output--b,kwji
!------------------------------------------------------------------
implicit real*8 (a-h,o-z)
dimension a(ma,n),b(n),m(n+1)
do 10 i=1,n
10 m(i)=i
do 120 k=1,n
p=0.0
do 20 i=k,n
do 20 j=k,n
if(dabs(a(i,j)).gt.dabs(p)) then
p=a(i,j)
io=i
jo=j
endif
20 continue
if(dabs(p)-ep) 30,30,35
30 kwji=1
return
35 continue
if(jo.eq.k) go to 45
do 40 i=1,n
t=a(i,jo)
a(i,jo)=a(i,k)
a(i,k)=t
40 continue
j=m(k)
m(k)=m(jo)
m(jo)=j
45 if(io.eq.k) go to 55
do 50 j=k,n
t=a(io,j)
a(io,j)=a(k,j)
a(k,j)=t
50 continue
t=b(io)
b(io)=b(k)
b(k)=t
55 p=1./p
in=n-1
if(k.eq.n) go to 65
do 60 j=k,in
60 a(k,j+1)=a(k,j+1)*p
65 b(k)=b(k)*p
if(k.eq.n) go to 120
do 80 i=k,in
do 70 j=k,in
70 a(i+1,j+1)=a(i+1,j+1)-a(i+1,k)*a(k,j+1)
80 b(i+1)=b(i+1)-a(i+1,k)*b(k)
120 continue
do 130 i1=2,n
i=n+1-i1
do 130 j=i,in
130 b(i)=b(i)-a(i,j+1)*b(j+1)
do 140 k=1,n
i=m(k)
140 a(1,i)=b(k)
do 150 k=1,n
150 b(k)=a(1,k)
kwji=0
return
end
Program solve_eqns
Use, Intrinsic :: iso_fortran_env, Only : wp => real64, li => int64
Implicit None
Real( wp ), Dimension( :, : ), Allocatable :: a, a_copy
Real( wp ), Dimension( : ), Allocatable :: b
Real( wp ), Dimension( : ), Allocatable :: x_lap, x_for
Real( wp ), Dimension( : ), Allocatable :: work
Real( wp ) :: time_lap, time_for
Integer, Dimension( : ), Allocatable :: pivots
Integer :: i
Integer :: n, nb = 64 ! hack value for nb - should use ilaenv
Integer :: error
Integer( li ) :: start, finish, rate
Write( *, * ) 'n ?'
Read ( *, * ) n
Allocate( a( 1:n, 1:n ) )
Allocate( b( 1:n ) )
Allocate( pivots( 1:n ) )
! Set up matrix
Call Random_number( a )
a = a - 0.5_wp
! Make A symmetric
a = 0.5_wp * ( a + Transpose( a ) )
! Add n to diagonal of A to avoid any nasty condition numbers
Do i = 1, n
a( i, i ) = a( i, i ) + n
End Do
! And keep a back up of A
a_copy = a
! RHS
Call Random_number( b )
! Solve with LAPACK
x_lap = b
Allocate( work( 1:n * nb ) )
Call system_clock( start, rate )
Call dsysv( 'U', n, 1, a, Size( a, dim = 1 ), pivots, &
x_lap, Size( x_lap, Dim = 1 ), work, Size( work ), error )
Call system_clock( finish, rate )
time_lap = Real( finish - start, Kind( time_lap ) ) / rate
! Restore A
a = a_copy
Write( *, * ) 'Errors for LAPACK', error, Maxval( Abs( Matmul( a, x_lap ) - b ) )
Write( *, * ) 'Time for LAPACK', time_lap
! Solve with Fortran
x_for = b
Call system_clock( start, rate )
Call GaussEqSolver_Sym( Size( a, Dim = 2 ), Size( a, Dim = 1 ), a, x_for, Epsilon( a ), error )
Call system_clock( finish, rate )
time_for = Real( finish - start, Kind( time_for ) ) / rate
! Restore A
a = a_copy
Write( *, * ) 'Errors for Fortran', error, Maxval( Abs( Matmul( a, x_for ) - b ) )
Write( *, * ) 'Time_For for Fortran', time_for
Write( *, * ) 'Max difference in solutions', Maxval( Abs( x_lap - x_for ) )
Write( *, * ) 'LAPACK is ', time_for / time_lap, ' times quicker than the Fortran'
End Program solve_eqns
ian#eris:~/work/stack$ gfortran --version
GNU Fortran (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
ian#eris:~/work/stack$ gfortran -O3 solve.f90 -llapack
ian#eris:~/work/stack$ ./a.out
n ?
100
Errors for LAPACK 0 4.4408920985006262E-016
Time for LAPACK 1.5952670000000000E-003
Errors for Fortran 0 9.9920072216264089E-016
Time_For for Fortran 5.3095140000000004E-003
Max difference in solutions 8.6736173798840355E-018
LAPACK is 3.3282917530419676 times quicker than the Fortran
ian#eris:~/work/stack$ ./a.out
n ?
1000
Errors for LAPACK 0 1.3322676295501878E-015
Time for LAPACK 3.9014976000000000E-002
Errors for Fortran 0 4.9960036108132044E-015
Time_For for Fortran 1.9314730620000000
Max difference in solutions 4.7704895589362195E-018
LAPACK is 49.505940026722044 times quicker than the Fortran
ian#eris:~/work/stack$ ./a.out
n ?
5000
Errors for LAPACK 0 4.3298697960381105E-015
Time for LAPACK 1.2611959250000000
Errors for Fortran 0 1.3322676295501878E-014
Time_For for Fortran 913.76959534100001
Max difference in solutions 2.7647155398380363E-018
LAPACK is 724.52628273517462 times quicker than the Fortran
I'm trying to implement a modified Dijkstra's algorithm to find the shortest path with highest weighted value between all nodes of an undirected graph.
My problem is that I don't know how to properly change my original Fortran code (that finds the minimum path with the lowest weight value). I would like to ask if you could help me with ideas to revise this code, mainly the subroutines find_nearest and update_mind, as well the code to run all over the nodes.
c ***************************************************************************
subroutine dijkstra (nmols, matrixS)
implicit none
include 'COMMONP.dat'
integer nmols, i, j, k1, k2, step, md, mv
logical connected(nmols)
integer, parameter :: i4_huge = 2147483647
dimension mind(nmolsp), ohd(nmolsp, nmolsp)
c
ohd(1:nmols,1:nmols) = i4_huge
c
do i = 1, nmols
ohd(i,i) = 0
end do
c
c Loading the weighted matrix
c
do 14 k1 = 1, nmols
do 15 k2 = 1, nmols
if matrixS(k1,k2).ne.0 then
ohd(k1,k2) = matrixS(k1,k2)
15 continue
14 continue
c
c carry out the algorithm
c start out with only node 1 connected to the tree.
c
do 33 node = 1, nmols
connected(1:nmols) = .false.
connected(node) = .true.
c
c initialize the minimum distance to the one-step distance
c
mind(1:nmols) = ohd(node,1:nmols)
c
c attach one more node on each interaction
do step = 1, nmols
call find_nearest (nmols, mind, connected, md, mv)
if ( mv == -1 ) then
write ( *, '(a)' ) ' '
write ( *, '(a)' ) 'DIJKSTRA_DISTANCE - Warning!'
write ( *, '(a)' ) ' Search terminated early.'
write ( *, '(a)' ) ' Graph might not be connected.'
return
end if
c
c Mark this node as connected
c
connected(mv) = .true.
c
c Having determined the minimum distance to node MV, see
c what is the highest weighted path to other nodes.
c
call update_mind ( nmols, connected, ohd, mv, mind )
end do
! Print the results.
!
write ( *, '(a)' ) ' '
write ( *, '(a)' ) ' Minimum path from node i:'
write ( *, '(a)' ) ' '
do i = 1, nmols
write ( *, '(2x,i2,2x,i2)' ) i, mind(i)
end do
33 continue
!
stop
end
c ***************************************************************************
subroutine find_nearest (nmols, mind, connected, md, mv)
implicit none
integer ( kind = 4 ) nmols
logical ( kind = 4 ) connected(nmols)
integer ( kind = 4 ) d
integer ( kind = 4 ) i
integer ( kind = 4 ), parameter :: i4_huge = 2147483647
integer ( kind = 4 ) mind(nmols)
integer ( kind = 4 ) v
d = i4_huge
v = -1
do i = 1, nmols
if ( .not. connected(i) .and. mind(i) < d ) then
d = mind(i)
v = i
end if
end do
return
end
c ***************************************************************************
subroutine update_mind ( nmols, connected, ohd, mv, mind )
implicit none
integer ( kind = 4 ) nmols
logical ( kind = 4 ) connected(nmols)
integer ( kind = 4 ) i
integer ( kind = 4 ), parameter :: i4_huge = 2147483647
integer ( kind = 4 ) mind(nmols)
integer ( kind = 4 ) mv
integer ( kind = 4 ) ohd(nmols,nmols)
do i = 1, nmols
if ( .not. connected(i) ) then
c
if ( ohd(mv,i) < i4_huge ) then
if ( mind(mv) + ohd(mv,i) < mind(i) ) then
mind(i) = mind(mv) + ohd(mv,i)
end if
end if
end if
end do
return
end
c
The following code just generates a simple triple of random numbers:
program testrand
integer, parameter :: nz = 160, nf = 160, nlt = 90
real :: tmpidx(3)
integer :: idxarr(3), idx1, idx2, idx3, seed_size, ticks
integer, allocatable :: seed(:)
call random_seed(size=seed_size)
allocate(seed(seed_size))
call system_clock(count=ticks)
seed = ticks+37*(/(i-1, i=1,seed_size)/)
call random_seed(put=seed)
deallocate(seed)
call random_number(tmpidx)
idxarr = tmpidx * (/nz, nf, nlt/)
idx1 = max(1,idxarr(1))
idx2 = max(1,idxarr(2))
idx3 = max(1,idxarr(3))
print *,idx1, idx2, idx3
end program
I compile this with gfortran and run a few times and I get:
> gfortran testrand.f90
> ./a.out
74 98 86
> ./a.out
113 3 10
> ./a.out
44 104 27
Looks pretty random. Now I compile with PGI Fortran and run a few times:
> pgf90 testrand.f90
> ./a.out
1 1 1
> ./a.out
1 1 1
> ./a.out
1 1 1
Of course, there's no way to be completely sure, but I suspect this is not random. :) Anyone know what is going on here? Anyone know the right way to get random numbers with PGI Fortran?
Somehow, PGI does not implement system_clock as in GNU compilers. I do not know why, I found it recently by doing similar stuff like you.
To see what I am talking about, just print ticks after calling system_clock. Chances are that you get 0 all the time with PGI and varying numbers with GNU compilers. To solve your problem, you can adapt the code bellow. It is a slightly modified version of a code that you can get at GNU fortran web site
program testrand
use iso_fortran_env, only: int64
integer, parameter :: nz = 160, nf = 160, nlt = 90
real :: tmpidx(3)
integer :: idxarr(3), idx1, idx2, idx3, seed_size, ticks
integer, allocatable :: seed(:)
call random_seed(size=seed_size)
allocate(seed(seed_size))
! call system_clock(count=ticks)
! seed = ticks+37*(/(i-1, i=1,seed_size)/)
! call random_seed(put=seed)
!
! deallocate(seed)
call init_random_seed()
call random_number(tmpidx)
idxarr = tmpidx * (/nz, nf, nlt/)
idx1 = max(1,idxarr(1))
idx2 = max(1,idxarr(2))
idx3 = max(1,idxarr(3))
print *,idx1, idx2, idx3
contains
!
subroutine init_random_seed()
implicit none
integer, allocatable :: seed(:)
integer :: i, n, istat, dt(8), pid
integer(int64) :: t
integer, parameter :: un=703
call random_seed(size = n)
allocate(seed(n))
! First try if the OS provides a random number generator
open(unit=un, file="/dev/urandom", access="stream", &
form="unformatted", action="read", status="old", iostat=istat)
if (istat == 0) then
read(un) seed
close(un)
else
! The PID is
! useful in case one launches multiple instances of the same
! program in parallel.
call system_clock(t)
if (t == 0) then
call date_and_time(values=dt)
t = (dt(1) - 1970) * 365_int64 * 24 * 60 * 60 * 1000 &
+ dt(2) * 31_int64 * 24 * 60 * 60 * 1000 &
+ dt(3) * 24_int64 * 60 * 60 * 1000 &
+ dt(5) * 60 * 60 * 1000 &
+ dt(6) * 60 * 1000 + dt(7) * 1000 &
+ dt(8)
end if
pid = getpid()
t = ieor( t, int(pid, kind(t)) )
do i = 1, n
seed(i) = lcg(t)
end do
end if
call random_seed(put=seed)
!print*, "optimal seed = ", seed
end subroutine init_random_seed
!
function lcg(s)
integer :: lcg
integer(int64), intent(in out) :: s
if (s == 0) then
s = 104729
else
s = mod(s, 4294967296_int64)
end if
s = mod(s * 279470273_int64, 4294967291_int64)
lcg = int(mod(s, int(huge(0), 8)), kind(0))
end function lcg
!
!this option is especially used for pgf90 to provide a getpid() function
!> #brief Returns the process ID of the current process
!! #todo write the actual code, for now returns a fixed value
!<
function getpid()result(pid)
integer pid
pid = 53 !just a prime number, no special meaning
end function getpid
end program