Carl McBride: Slight tidy up.

2007-11-13T12:31:25Z

Slight tidy up.

← Older revision		Revision as of 14:31, 13 November 2007
Line 1:		Line 1:
	{{Source}}		{{Source}}
	[[Random number]] ~~generators~~ usually provide numbers ~~with~~ a uniform (flat)		[[Random_numbers \|Random number generators]] usually provide numbers having a uniform (flat)
	distribution. ~~Sometimes~~ it is desirable to generate numbers with some		distribution. However, sometimes it is desirable to generate numbers with some
	other distributions. ~~The~~ Gaussian (normal) distribution is of paramount ~~imporance~~.		other distributions. For example, the [[Gaussian distribution \|Gaussian (normal) distribution]] is of paramount importance.
	==Fortran 90 implementation==		==Fortran 90 implementation==
	This Fortran 90 ~~implementation~~ is adapted from Ref. 1, based on an algorithm from the Numerical Recipes collection, Ref. 2. The function '''ran()''' calls a ~~[[Random_numbers \| randon~~ number generator]]:		This Fortran 90 function is adapted from Ref. 1, based on an algorithm from the Numerical Recipes collection (Ref. 2). The function '''ran()''' calls a random number generator:
	<small><pre>		<small><pre>
	! Returns random numbers distributed following a Gaussian with		! Returns random numbers distributed following a Gaussian with
Line 35:		Line 35:
	==References==		==References==
	# Daan Frenkel and Berend Smit "Understanding Molecular Simulation: From Algorithms to Applications" p. 411 Academic Press (1996)		# Daan Frenkel and Berend Smit "Understanding Molecular Simulation: From Algorithms to Applications" p. 411 Academic Press (1996)
	# [http://www.nr.com Numerical Recipes]		# [http://www.nr.com Numerical Recipes (Third Edition) website ]

	[[category: random numbers]]		[[category: random numbers]]
	[[category: computer simulation techniques]]		[[category: computer simulation techniques]]

Dduque: New page: {{Source}} Random number generators usually provide numbers with a uniform (flat) distribution. Sometimes it is desirable to generate numbers with some other distributions. The Gaussia...

2007-11-13T12:22:36Z

New page: {{Source}} Random number generators usually provide numbers with a uniform (flat) distribution. Sometimes it is desirable to generate numbers with some other distributions. The Gaussia...

New page

{{Source}}
[[Random number]] generators usually provide numbers with a uniform (flat)
distribution. Sometimes it is desirable to generate numbers with some
other distributions. The Gaussian (normal) distribution is of paramount imporance.
==Fortran 90 implementation==
This Fortran 90 implementation is adapted from Ref. 1, based on an algorithm from the Numerical Recipes collection, Ref. 2. The function '''ran()''' calls a [[Random_numbers | randon number generator]]:
<small><pre>
! Returns random numbers distributed following a Gaussian with
! unit variance

function gauss()

implicit none

real gauss

real v1,v2,r

real ranmar

do
v1=2.0*ranmar()-1.0
v2=2.0*ranmar()-1.0
r=v1*v1+v2*v2
if(r.lt.1.0) exit
enddo

gauss=v1*sqrt(-2.0*log(r)/r)

return

end function gauss
</pre></small>

==References==
# Daan Frenkel and Berend Smit "Understanding Molecular Simulation: From Algorithms to Applications" p. 411 Academic Press (1996)
# [http://www.nr.com Numerical Recipes]

[[category: random numbers]]
[[category: computer simulation techniques]]

Numbers with a Gaussian distribution - Revision history

Carl McBride: Slight tidy up.

Dduque: New page: {{Source}} Random number generators usually provide numbers with a uniform (flat) distribution. Sometimes it is desirable to generate numbers with some other distributions. The Gaussia...