Have a look at http://www.horsefish.net/ElementalFX/ if you want to see
some neat flash by one of the regulars here.
Ron
Dwayne Neckles wrote:
My god are you guys seriously talking about Flash here. I mean this is
so advanced. I feel like I gotta be a math whiz and a flash whiz ( an
unexpected combination ) to get all of this.
god bless you guys, meanwhile Ill be lurking figuring out how exactly
"biased random particle distribution" can be applied to flash..
ill send an fla if i get it figured out
goodness,
Dwayne
----Original Message Follows----
From: "clark slater" <[EMAIL PROTECTED]>
Reply-To: Flashcoders mailing list <flashcoders@chattyfig.figleaf.com>
To: "Flashcoders mailing list" <flashcoders@chattyfig.figleaf.com>
Subject: Re: [Flashcoders] Re: Biased Random Particle Distribution
Date: Sat, 27 May 2006 11:58:57 -0700
Thanks Ron,
I'm working on a dynamic portfolio component for a client and I've been
given static designs that I have to match.
The beginning of the portfolio has a couple hundred *tiny* icons that
appear
spread across the stage in a non overlapping random pattern. Thing is,
it's
not a normal distribution - with many more of the icons appearing to the
upper left (origin) of the stage...then spreading out in a random but
decreasingly dense pattern across the stage.
So it turned out that using the squared random value worked really
well in
this particular case. I was kind of surprised how well it works actually.
That link's a wonderful resource for these kind of things, thanks a
million.
Clark
On 5/27/06, Ron Wheeler <[EMAIL PROTECTED]> wrote:
I was surprised that the squaring gave you any kind of banding since it
should be a smooth bias.
I think that the log transformation will give you less of a bias toward
one side but I have not pulled out all my old stats and calculus books
to check this out.
It would seem that a normal distribution(cut in half and shifted) or a
Poisson might be what you are looking for.
What is the physical phenomenon are you trying to model?
http://mathworld.wolfram.com/topics/ContinuousDistributions.html has
more distributions that I ever knew existed.
It has a picture and formula for each one.
Ron
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