Yes, you are right. I waited for 6 minutes to generate 3 workbooks. Is it possible to improve the speed without decreasing the ResultBlockSize?
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Decreasing ResultBlockSize doesn't speed it up, it slows it down because it has to create more workbooks. You can increase it safely up to 1,048,574
There is a DoEvents line whichyou can take out, but this will make it very difficult to interrupt the code should you find you've given it a task which is too big and so is taking too long.
Otherwise, there's not much to do to speed it up further.
So far you've been reluctant to say what you're going to do with these results, which could have a bearing on how/how quickly they can be produced.
edit: Taking DoEvents out speeds it up almost 10 times!
Chaotic Data without repetitions is not Chaotic
If a 6 column Row of numbers is one Chaotic Data Point, then 1234,65 is not the same as 1234,56
IMO, you are making your "Chaotic" Data Set very regulated.
http://sprott.physics.wisc.edu/cdg.htm
Attachment 28148
Like SamT says:
Quote:
IMO, you are making your "Chaotic" Data Set very regulated.
In my layman's terms, the best exmple of 'choas' is the classic butterfly effect.
Quote:
In chaos theory, the butterfly effect is the sensitive dependence on initial conditions in which a small change in one state of a deterministic nonlinear system can result in large differences in a later state.The term is closely associated with the work of mathematician and meteorologist Edward Lorenz. He noted that butterfly effect is derived from the metaphorical example of the details of a tornado (the exact time of formation, the exact path taken) being influenced by minor perturbations such as a distant butterfly flapping its wings several weeks earlier. Lorenz discovered the effect when he observed runs of his weather model with initial condition data that were rounded in a seemingly inconsequential manner. He noted that the weather model would fail to reproduce the results of runs with the unrounded initial condition data. A very small change in initial conditions had created a significantly different outcome.[1]
The idea that small causes may have large effects in weather was earlier recognized by French mathematician and engineer Henri Poincaré. American mathematician and philosopher Norbert Wiener also contributed to this theory. Edward Lorenz's work placed the concept of instability of the Earth's atmosphere onto a quantitative base and linked the concept of instability to the properties of large classes of dynamic systems which are undergoing nonlinear dynamics and deterministic chaos.[2]
Function Chaotic() As Long
'Returns 2 digit number
Randomize
Chaotic = CLong(Rnd() * 100)
End Function
'May be faster
Function Chaotic2() As Long
'Returns 2 digit number: final *100
Chaotic = CLong(Rnd(CInt(Right(CStr(CDble(Now)), 3) * -1) * 100))
End Function
SamT -- I would say that IMVVVHO is more of a Monte Carlo approach
I was thinking (again, it's been a long time for me) that testing a model through 1000's of iterations using an inputs of t-sub0 = 1.00001 and t-sub0 = 1.000011 to see the differences at the would be closer to the butterfly effect