I sent some lasers through it to check the focus and everything worked as intended. I tried this a while back with v1.6 with a 5-element lens system. This is an interesting topic for me as well. But the combo "orthographic camera+planes" should pretty much model the new type of camera you need. The only other option I see is to write a dedicated new camera type but it would require to write code. It should be possible to do it indirectly: hit a plane with the laser, use an orthographic camera looking perpendicular to the plane, than use the Irradiance AOV if you want some numerical values or just check the normal rendered image for a qualitative evaluation I need the camera to be the surface that the light hits (or act like it at least). If the laser light lands on an external surface, the camera can see its effects as normal, but that's not what I need. "Hitting" the camera with a laser, either directly or after it passes through glass objects, does nothing. It needs to simulate an actual sensor surface that will register pixel illumination when directly struck by a laser (or other light source, but the laser is the most crucial). I believe it should also be nominated for a Pulitzer Prize.As part of this, I need the camera to act like a physical camera. > “This book has deservedly won an Academy Award. Jordan introduce the recipients, and at 2:12 Matt Pharr comes up and says "needless to say, when we started writing a book we never expected an Academy Award would be the end result of that effort" and thanks Donald Knuth for literate programming: Well, reality is even stranger than imagination: no computer program has won a Pulitzer prize, but this computer program won an Oscar! Here's a video of the awards ceremony, where Kristen Bell and Michael B. When Knuth came up with the term/idea of "literate programming" and the idea of programs as works of literature, in the paper ( ) he joked (I think?) that he hoped that, just as there are Pulitzer prizes for literature, there may oneĭay be Pulitzer prizes awarded to computer programs. To me the apparently obvious truth of this is up there with understanding that the iron that makes our blood red can only be formed in supernovae. Rendering is particularly beautiful in that it touches on so many fields, from pure maths, to applied maths and numerical methods, to physics, to human biology and perception, aesthetics, both low- and high-level programming concerns, even philosophy: if we can simulate visual reality to such high precision, it lends credence to the idea that we ourselves are simulated. Here's a wealth of recent research on all that: This isn't even scratching the surface of things like the Halton, Hammersley and Sobol sequences, the human visual response to different kinds of noise that makes blue noise preferable, etc. Does it work well for other numbers, and can it be extended to higher dimensions? Sure, there are some interesting things you can do. seashells and the distribution of sunflower seeds), in particular how it is in some sense (continued fraction) the "most irrational" number. Why does this work? Well, there's a lot of beautiful theory about phi (also relating to biology and nature, e.g. If you plot this sequence on a [0,1) number line, you'll see that it divides up the interval into finer pieces really nicely, magically keeping a good distance from all the previous values, without even knowing them! However, using actual proper random number generators has a very slow convergence rate, as the random numbers chosen will tend to clump on the other hand, if you just use a perfectly uniform distribution, you'll suffer from correlation problems.Ĭonsider a 1-D numerical integration problem, and instead of using rnd() to pick points in your integrand range, you start with some seed value in [0,1), and each time you need a new random number, you add phi-1 to the existing number and mod with 1.0 to get the new number. I'll try to give a small sample of that.īasically what you're doing in MC is estimating expected values (and thereby integrals: average height times base width equals area under the graph) using random numbers, to be roughly thought of as a rnd() function which gives you back a float in [0,1). I would say very close to the top is the amazing depth of sampling methods, in particular Quasi-Monte Carlo (QMC) methods.
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