define N 1200
	set x=1,$N
	# dummy call to get ws dimensioned right
	get_hist x v ws -.5 .5 .02
	set ws=ws*0
	erase
	window 1 1 1 1

	set y=x*0
	limits 0 $N -.7 0.7
	box
	ptype 1 1
	# generate a lot of points to uniformly cover -0.5 to 0.5
	# -and- at the same time do averages of 10 samples => pseudo-gaussian
	do i=1,10 {
		set t=random($N)-0.5
		set y=y+t
		# keep plotting the uniform points
		points x t
		get_hist t v w -.5 .5 .02
		set ws=ws+w
	}
	echo  * Uniformly Distributed between -0.5 and 0.5 *
	toplabel  * Uniformly Distributed between -0.5 and 0.5 *
	# use call to "cursor" in order to pause
#	cursor
	# prepare and plot the pseudo gaussian points
	set y=.02+y/10
	lweight 3
	ctype red
	connect x y
	ctype default
	lweight 1
	define ave (sum(y)/$N)
	define rms (sqrt(sum(y*y)/$N))
	define err ($rms/sqrt($N))
	echo rms=sigma= $rms
	echo average= $ave +- $err
	echo
	echo * red: averages of 10 random points *

#	print noise_file { y }

# 	cursor

	erase
	ctype default
	limits x y
	box
	connect x y
	set s=abs(x-450)<40?.06:0
	ctype red
#	cursor
	lweight 3
	connect x s
	lweight 1
	set ynew=y
	ctype 0
#	cursor
        erase
	box
	limits x ynew
	erase
	box
	connect x ynew
	stats ynew ave sig kur
	echo ...
	echo stats ynew ave sig kur
	echo ave=$ave    sigma=$sig
	echo ...
	echo vecminmax ynew mn mx
	vecminmax ynew mn mx
	echo min=$mn   max=$mx
	echo

#	print data.2 {ynew}