Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-06-29 Thread ryanm

No web site is configured at this address.

   Yeah, my wife lost the credit card and had to get it replaced, and I 
forgot to update the host. :-P


   It should be back up tomorrow afternoon.

ryanm 


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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-06-29 Thread Latcho

No web site is configured at this address.

Ron Wheeler wrote:
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 
To: "Flashcoders mailing list" 
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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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-28 Thread Ron Wheeler
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 
To: "Flashcoders mailing list" 
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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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread Dwayne Neckles
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 
To: "Flashcoders mailing list" 
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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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread clark slater

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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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread clark slater

Thanks Weldon - yeah I was tempted by the ease of a large switch statement
relying on probability ranges but one of my many resolutions for this year
is to improve my elementary maths and solve problems like this like a grown
up =80)

Clark
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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread Ron Wheeler

Chi-Squared also looks interesting.

Ron

clark slater wrote:

Hi Ron,

Thanks for jumping into this thread amongst the tumbleweeds. Yes, I 
suspect
something logarithmic could work but don't know where to start. I am 
trying

to distribute 1000 particles randomly in a rectangular distribution area,
with a bias towards one side of the rectangle.

Clark


On 5/26/06, Ron Wheeler <[EMAIL PROTECTED]> wrote:


Would a formula based on logarithms give you what you want as well?
You were not very specific about what you wanted the distribution to
look like.

Ron
clark slater wrote:
> Here I go answering my own question.
>
> To make it more dense toward the origin, use {x,y} = {random[]^2,
> random[]^2}--squaring the independently generated numbers
> (random[]*random[]
> won't work). The result is a distribution with a sharp cusp at the
> origin--the probability is a maximum there, and has a discontinuous
> derivative. You can use higher powers for narrower (and sharper)
> distributions.
>
> Damn useful I say!
> ___
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> To change your subscription options or search the archive:
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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread Ron Wheeler
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


clark slater wrote:

Hi Ron,

Thanks for jumping into this thread amongst the tumbleweeds. Yes, I 
suspect
something logarithmic could work but don't know where to start. I am 
trying

to distribute 1000 particles randomly in a rectangular distribution area,
with a bias towards one side of the rectangle.

Clark


On 5/26/06, Ron Wheeler <[EMAIL PROTECTED]> wrote:


Would a formula based on logarithms give you what you want as well?
You were not very specific about what you wanted the distribution to
look like.

Ron
clark slater wrote:
> Here I go answering my own question.
>
> To make it more dense toward the origin, use {x,y} = {random[]^2,
> random[]^2}--squaring the independently generated numbers
> (random[]*random[]
> won't work). The result is a distribution with a sharp cusp at the
> origin--the probability is a maximum there, and has a discontinuous
> derivative. You can use higher powers for narrower (and sharper)
> distributions.
>
> Damn useful I say!
> ___
> Flashcoders@chattyfig.figleaf.com
> To change your subscription options or search the archive:
> http://chattyfig.figleaf.com/mailman/listinfo/flashcoders
>
> Brought to you by Fig Leaf Software
> Premier Authorized Adobe Consulting and Training
> http://www.figleaf.com
> http://training.figleaf.com
>
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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-27 Thread Weldon MacDonald

from a practical standpoint, something like this should work, it's
difficult to be sure at 5:30 in the AM.

get a random number from 1 - 10
var ranNum:Number = random(10)+1;
now if ranNum is less than 4 pick a random position within x of the origin
if ranNum is 6-8 select a random point within x + delta x
If ranNum is 9 - 10 select a random point from the entire range.
By playing with the ranges I used here you will get more or less
intensity near the origin. If this is too coarse, make ranNum a bigger
range and add more regions.
You could set this up in one tidy finction, it's less interesting than
the math, but it should get the job done.

On 5/27/06, clark slater <[EMAIL PROTECTED]> wrote:

Hi Ron,

Thanks for jumping into this thread amongst the tumbleweeds. Yes, I suspect
something logarithmic could work but don't know where to start. I am trying
to distribute 1000 particles randomly in a rectangular distribution area,
with a bias towards one side of the rectangle.

Clark


On 5/26/06, Ron Wheeler <[EMAIL PROTECTED]> wrote:
>
> Would a formula based on logarithms give you what you want as well?
> You were not very specific about what you wanted the distribution to
> look like.
>
> Ron
> clark slater wrote:
> > Here I go answering my own question.
> >
> > To make it more dense toward the origin, use {x,y} = {random[]^2,
> > random[]^2}--squaring the independently generated numbers
> > (random[]*random[]
> > won't work). The result is a distribution with a sharp cusp at the
> > origin--the probability is a maximum there, and has a discontinuous
> > derivative. You can use higher powers for narrower (and sharper)
> > distributions.
> >
> > Damn useful I say!
> > ___
> > Flashcoders@chattyfig.figleaf.com
> > To change your subscription options or search the archive:
> > http://chattyfig.figleaf.com/mailman/listinfo/flashcoders
> >
> > Brought to you by Fig Leaf Software
> > Premier Authorized Adobe Consulting and Training
> > http://www.figleaf.com
> > http://training.figleaf.com
> >
> >
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--
Weldon MacDonald
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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-26 Thread clark slater

Hi Ron,

Thanks for jumping into this thread amongst the tumbleweeds. Yes, I suspect
something logarithmic could work but don't know where to start. I am trying
to distribute 1000 particles randomly in a rectangular distribution area,
with a bias towards one side of the rectangle.

Clark


On 5/26/06, Ron Wheeler <[EMAIL PROTECTED]> wrote:


Would a formula based on logarithms give you what you want as well?
You were not very specific about what you wanted the distribution to
look like.

Ron
clark slater wrote:
> Here I go answering my own question.
>
> To make it more dense toward the origin, use {x,y} = {random[]^2,
> random[]^2}--squaring the independently generated numbers
> (random[]*random[]
> won't work). The result is a distribution with a sharp cusp at the
> origin--the probability is a maximum there, and has a discontinuous
> derivative. You can use higher powers for narrower (and sharper)
> distributions.
>
> Damn useful I say!
> ___
> Flashcoders@chattyfig.figleaf.com
> To change your subscription options or search the archive:
> http://chattyfig.figleaf.com/mailman/listinfo/flashcoders
>
> Brought to you by Fig Leaf Software
> Premier Authorized Adobe Consulting and Training
> http://www.figleaf.com
> http://training.figleaf.com
>
>
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Re: [Flashcoders] Re: Biased Random Particle Distribution

2006-05-26 Thread Ron Wheeler

Would a formula based on logarithms give you what you want as well?
You were not very specific about what you wanted the distribution to 
look like.


Ron
clark slater wrote:

Here I go answering my own question.

To make it more dense toward the origin, use {x,y} = {random[]^2,
random[]^2}--squaring the independently generated numbers 
(random[]*random[]

won't work). The result is a distribution with a sharp cusp at the
origin--the probability is a maximum there, and has a discontinuous
derivative. You can use higher powers for narrower (and sharper)
distributions.

Damn useful I say!
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[Flashcoders] Re: Biased Random Particle Distribution

2006-05-26 Thread clark slater

Here I go answering my own question.

To make it more dense toward the origin, use {x,y} = {random[]^2,
random[]^2}--squaring the independently generated numbers (random[]*random[]
won't work). The result is a distribution with a sharp cusp at the
origin--the probability is a maximum there, and has a discontinuous
derivative. You can use higher powers for narrower (and sharper)
distributions.

Damn useful I say!
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