From: David Dailey <ddailey@zoominternet.net>

Date: Tue, 4 Dec 2012 20:58:29 -0500

To: <steve@fenestra.com>

Cc: <www-svg@w3.org>, "'Eric Elder'" <ericjelder@gmail.com>

Message-ID: <002301cdd28c$05c51970$114f4c50$@net>

Date: Tue, 4 Dec 2012 20:58:29 -0500

To: <steve@fenestra.com>

Cc: <www-svg@w3.org>, "'Eric Elder'" <ericjelder@gmail.com>

Message-ID: <002301cdd28c$05c51970$114f4c50$@net>

I wish my thoughts were more in the midst of it at the moment, so perhaps it was a bad time to raise the issue. In the HTML-WG, an ill-formulated idea was prone to evoke derision, slanderous IRC's and intensely juvenile behavior for which no known antidote short of senility is known. The SVG community tends to be a bit more forgiving, thankfully. I will try to resurrect some of the conceptual threads that underlay my admittedly unsubstantiated conclusion, but all that I can recall for now is that when one plays within the rich constructional framework provided by declarative randomness together with <replicate> one wants a way to a) remember values that have been generated during one pass so that they might be reused in a next iteration and b) many aspects of scene generation are correlated in ways that invite declarative syntax, but which to date have eluded our simple conceptualization of what that syntax might be. I think, alas, one sort of has to play with replicate and random to get a sense of what I'm talking about, and for many people this would be tantamount to some sort of ideological blasphemy -- sort of like when Dada came to Zurich. I'll try to be more concrete in later post, and I will try to complete said post within a finite number of months. I'm not being sarcastic, really, just realistic. Regards D -----Original Message----- From: Steve Schafer [mailto:steve@fenestra.com] Sent: Tuesday, December 04, 2012 1:27 PM To: David Dailey Cc: www-svg@w3.org; 'Eric Elder' Subject: Re: covariation and declarative randomness RE: Re (2): Turing completeness and syntactic elegance; On Tue, 4 Dec 2012 07:29:10 -0500, you wrote: >What we'd like to be able to add in, and welcome suggestions for how to >do it, is to be able to control the amount of covariation between two >random variables --- for example as the y position of trees varies we >might also want their brightness to increase (but with a fixed >coefficient of correlation). It is the co-dependency of random >variables for which we are trying to craft a declarative solution. Can you give some concrete examples? I'm not sure I understand what kinds of covariance you're looking for. There is quite a bit of literature covering joint probability distributions of random variables, with all manner of combinations of correlation and independence. I'm reasonably confident that any useful joint probability distribution can be specified in terms of functions of a finite number of independent, uniformly-distributed random variables. That is, given a set A, B, C, etc. of variables of interest (that may be involved in various degrees of correlation and dependence), and a set a, b, c, etc. of independent random variables, you should be able to write: A = f1(a, b, c, ...) B = f2(a, b, c, ...) C = f3(a, b, c, ...) ... If you do it right, then some of the parameters in the functions f1, f2, etc. could serve as the "knobs" that a non-technical user would be able to tweak to vary the effect. How you would go about that is left as an exercise for the reader. ;-) -Steve SchaferReceived on Wednesday, 5 December 2012 01:59:00 GMT

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