Timeline for Efficiently generating n-D Gaussian random fields
Current License: CC BY-SA 3.0
7 events
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| Dec 17, 2021 at 16:49 | comment | added | lorenzop | OK thanks, so it is simply the field "resolution" and the "size" parameter won't affect the physical dimensions of your field. Then, probably my question changes into: what is the physical size of the system considered in your example? Specifically, how can I map the returned list (field) to actual space coordinates? | |
| Dec 17, 2021 at 16:41 | comment | added | J. M.'s missing motivation | @lorenzo, the size argument just specifies the number of points taken in each dimension; for instance, GaussianRandomField[256, 2] should return a list with dimensions {256, 256}. | |
| Dec 17, 2021 at 16:37 | comment | added | lorenzop | Great answer! I only have one question: when you input size=256, what does it correspond in the physical space? Basically my question amounts to: what is the "physical" size of the system? Hope it is clear what I mean, thanks! | |
| Feb 11, 2013 at 3:54 | history | bounty awarded | CommunityBot | ||
| Sep 3, 2012 at 15:17 | vote | accept | chris | ||
| Aug 31, 2012 at 13:07 | history | edited | J. M.'s missing motivation | CC BY-SA 3.0 | added 169 characters in body |
| Aug 28, 2012 at 7:10 | history | answered | J. M.'s missing motivation | CC BY-SA 3.0 |