vector * number
8. number * point
9. point * number
10. complex * complex
11. colour * colour
12. colour * number
13. number * colour
--
David Rutten
david@mcneel.com
Seattle, WA…
Added by David Rutten at 10:39pm on November 12, 2010
circles that can be populated (for each radius size) is set as an integer (or slider)
(ie. radius 1.5 = 10 , radius 3= 6, radius 6 = 6, radius 9=4)
Conditions are:
1) Each of the circle has a radius of influence,
Radius of influence = double the radius of the circle)
(3, 6, 12, 18)
2) Any overlapping circles in either: Radius of influence or the Circles are removed so that
No circles overlap.
3) There must also be 4 circles set at the corner points of the grid - These must be circles with a radius of 3 or 6
If you can do that I will be amazed as i've been trying for weeks! :(
Ive attached a sketch of what im looking for…
ggle A
7. Toggle A
8. Toggle 2
9. Toggle 3
10. Toggle A
11. Toggle A
12. Toggle 3
I was thinking to use somehow slider and animate option....but without luck
Any idea would be appreciated…
h i get 5 points (kinkos), Lets say 0,1,2,3,4,...But all segments are of different sizes,..that is, I know the distance between 0 & 1 is 2 units,Distance btw 1 & 2 = 3 unitsDistance btw 2 & 3 = 1 unitDistance btw 3 & 4 = 4units,..How do i do this division,. Could anyone help please,..Thank you…
)
3. KeyError(1417,)
4. KeyError(1417,)
5. KeyError(1417,)
6. KeyError(1417,)
7. KeyError(1417,)
8. KeyError(1417,)
9. KeyError(1417,)
10. KeyError(1417,)
11.......
i tried different weather file but also same result. it seems i have same problem. the file am working on is the radiation file i took from the examples . whats seems to be the problem?
thank you for your time…
t, let's talk about randomness. Randomness is a problem in computing because digital computers are deterministic. If you give them the exact same instructions they always end up with the exact same result. It turns out to be mathematically impossible to generate true random numbers using a digital computer, but it is fairly easy to generate pseudo-random numbers. This is actually not bad news as pseudo-random numbers -unlike real random numbers- can be generated again and again and you'll end up with the same random numbers every time. Being able to get the same random numbers on demand increases the reliability of these number sequences which in turn makes them easier to use.
Pseudo-random numbers are numbers that have certain characteristics. Note that when we talk about random numbers we are really talking about numbers. Plural. It's easy to generate only a single one, as xkcd so eloquently put it:
So what are these characteristics that define pseudo-randomness? Without being actually correct, I can sum them up as follows:
The sequence of generated numbers should never repeat itself*
The numbers in the sequence ought to be spread evenly across the numeric domain**
There are a lot of different algorithms out there, some better than others, some faster than others, some solving very specific problems while others are more generic. The generator used in Grasshopper is the standard Microsoft .NET Random, based on Donald Knuth's subtractive algorithm.
So let's imagine we want random integers between 0 and 10. What would a bad random sequence look like?
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 (about as bad as it gets)
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 (not random at all)
1 3 2 5 3 9 1 2 4 2 5 1 1 2 8 1 5 2 3 4 (too many low numbers)
2 8 4 6 0 9 8 2 4 8 6 4 2 2 5 1 4 8 6 2 (too many even numbers)
So what about good sequences? Well, here's a few:
6 9 1 2 0 4 2 8 5 7 2 9 1 9 2 5 3 1 9 2 (sure, why not)
6 2 5 3 4 1 9 7 8 0 2 1 6 4 5 8 9 5 0 9 (looks about right)
1 8 5 2 3 4 5 7 9 5 2 1 0 2 1 0 9 7 6 4 (I suppose)
9 0 6 4 8 3 1 5 2 7 6 1 4 6 0 1 9 7 5 6 (whatever)
There are a lot of valid pseudo-random sequences. (Seriously, loads). So even if we have a good pseudo-random generator we may be given a random sequence that isn't entirely to our liking. The shorter the sequence we need, the more likely it is that statistical aberrations invalidate that particular sequence for us. What we need is some control over the generator so we don't just get a repeatable sequence, but a repeatable sequence we actually like.
Enter seed values. The random generator requires a seed value before it can generate a random sequence. These seed values are always integers, and they can be any valid 32-bit integer. Every unique seed value results in the same sequence. Every time.
Unfortunately there is no clear relationship between seeds and sequences. Changing the seed value from 5 to 6 will result in a completely difference random sequence, and two sequences that are very similar may well have to wildly different seeds. There is therefore no way to guess a good seed value, it is completely trial-and-error. Also because of this extremely discontinuous nature, you cannot use tools like Galapagos to optimize a seed value.
If you are looking for a pseudo-random sequence which has custom characteristics, you may well end up having to write your own generator algorithm. Ask questions about this on the Grasshopper main forum or the VB/C# forum.
Conclusion: Seed values are integers that define the exact sequence of pseudo-random numbers, but there's no way of knowing ahead of time what sequence it will be and there's no way of tweaking a sequence by slightly changing the seed. Even the tiniest change in seed value will result in a radically different random sequence.
--
David Rutten
david@mcneel.com
Poprad, Slovakia
* This is not actually possible. A finite amount of numbers always repeats itself eventually.
** This should only be true for long enough sequences, short sequences are allowed to cluster their values somewhat.
Interesting links for further reading:
Coding Horror: Computers are Louse Random Number Generators
StackOverflow: When do random numbers start repeating?…
Added by David Rutten at 9:52am on October 20, 2012