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Fixes to Monte Carlo chapter #744
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I just checked all the implementations, and as of now only the Factor implementation has a general Monte Carlo integrator that outside code uses to approximate pi. All other implementations combine both of those steps in the same function or code block intended to return pi. |
I think all implementations are fine as long as the radius is set at the I still need to look into it a bit more |
The Python version (and Coconut one, for that matter) simply define a keyword argument The choice is on you, but I'm ready to change the codes if needed. |
Just throwing in a note: It seems that the Monte-Carlo algorithm as described here only discusses simple sampling which works for these easy examples. I think it should at least be mentioned that such a thing exists and that therefore Monte-Carlo is not always that simple ☝️ |
Yeah, I agree with this. There are a bunch of monte carlo methods, but I haven't gotten around to them yet... Sorry! |
Absolutely no need to apologize. I was not meaning to critize anyone. I merely wanted to bring up that these kind of things exist and might be worth mentioning :) |
Feature Request
As described in #658, the Monte Carlo (MC) chapter is in a somewhat dire need of a rework
Description
Right now, several implementations in the MC chapter have been written with the specific intent of integrating pi, not for general-purpose MC integration.
This is because the text is somewhat ambiguous. It should clearly state that calculating the area of the circle is the same as finding an approximation for pi. It should also highlight that MC is general-purpose and can be used for more than calculating the area of a circle (this was why we had an
in_circle()
function that could be abstracted into an shape).Right now, it seems like we need to do the following:
For Algorithm Archive Developers
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