Re: Randomu in 5.2? Not working

[landsman(at)stars.gsfc.nasa.gov (Wayne Landsman)]

In article <7edl5u$7kd@netline.jpl.nasa.gov>, "Mathew Yeates" <mathew@fugue.jpl.nasa.gov> writes...
>Hi-
> 
>We just went from 5.1 to 5.2 and I'm noticing different behavior.
>Here's my 5.2 session
>IDL> res=randomu(a,1) ; set seed using system clock
>IDL> print,res
>0.415999
> 
>I then exit IDL and start a new session..... and get the same result!
> 
>I verified that this does not happen when I use 5.1.

Mathew,

      The behavour of RANDOMU has changed three times since V4.0.1, and each
new version has introduced a bug of some sort.   Below is a summary of the
sordid history of RANDOMU problems that I've pieced together from previous 
posts to comp.lang.idl-pvwave, and from information from Pat Broos.      
Corrections welcome.

--Wayne Landsman                           landsman@mpb.gsfc.nasa.gov 


 V4.0.1:     No problems?

 V5.0:     RANDOMU could yield a non-random distribution if two programs
	   using RANDOMU are interleaved.    For example, in the program 
	   demo.pro given at the bottom of this message, the command
	   demo,/breakit will show a significant excess in the distribution
	   of random numbers between 0 and 0.03.

 V5.1:       A *negative* seed value must be specified if you want to preserve
           the same "random" sequence 

              IDL> seed = 2 & print, randomu(seed, 3)
                    0.0594004     0.982075     0.358593
              IDL> seed = 2 & print, randomu(seed, 3)
                    0.831999     0.303037     0.506712

                                   but 

               IDL>  seed = -2 & print, randomu(seed, 3)
                      0.342299     0.402381     0.307838
               IDL> seed = -2 & print, randomu(seed, 3)
                      0.342299     0.402381     0.307838

              This isn't necessarily a bug, but it means that RANDOMU works
              differently in V5.1 than in all other IDL versions.

 V5.1.1 and V5.2:  The seed variable is now initialized to the same value at the
              start of each session rather than the system clock.   Thus, Monte
              Carlo simulations from different IDL sessions, might yield 
              decidedly unrandom results.    Perhaps more insidious, only the
              first call to RANDOMU is initialized inside a program.    Thus, if
              one calls the following program test.pro multiple times, you will
              see that the "random" vector is simply the vector on the previous
              call, shifted by one.

PRO test
print, randomu(seed)
print, randomu(seed,6)
return
end

       For this last problem, Pat suggests using the following wrapper program
       to RANDOMU to store the seed value in a common block.

FUNCTION random, n1, n2, n3, NEW_SEED=new_seed, _EXTRA=extra

COMMON random_seed, seed

if keyword_set(new_seed) then seed = long(new_seed)

case n_params() of
     0: return, randomu(seed,          _EXTRA=extra)
     1: return, randomu(seed,n1,       _EXTRA=extra)
     2: return, randomu(seed,n1,n2,    _EXTRA=extra)
     3: return, randomu(seed,n1,n2,n3, _EXTRA=extra)
endcase

end

************************************************************************

FUNCTION lib_random

return, randomu(other_seed,1)
end


PRO demo, x, BREAK_IT=break_it

; Type demo,/breakit to see the "non-random" distribution that can result in
; V5.0.   Works correctly in earlier and later IDL versions

x = fltarr(100000)

for ii = 0L, n_elements(x)-1 do begin
  x(ii) = randomu(seed,1)

  if keyword_set(break_it) then dummy = lib_random()
endfor

h = histogram( x, MIN=0.0, BIN=0.01 )
plot, h, PSYM=10
print, h
return
end