Function parameter documentation #304
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Good PR! Added a few minor comments, but I basically think this can be merged. We can always make further improvements to the docs in the future as people start using the function parameters!
An aside:
It seems the terminology "class" or "subclass" is used a few locations throughout the documentation to describe parameter distributions both relating to function parameters, but also in general. I think it would be good to be a bit more precise to refer to these as abstract types and structs. That said, I think it's best to discuss and make those changes in a separate PR.
| ``` | ||
| We plot 4 samples of this distribution. Samples are taken over the (30-dimensional) degrees of freedom, and then we apply the `transform_unconstrained_to_costrained` map to (i) build the function distribution, (ii) evaluate it on the numerical grid, and (iii) constrain the output with our prescribed bounds. | ||
| ```@example snip_fun | ||
| shape = [length(pp) for pp in points] |
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could ndims be used here instead to illustrate the usage of that method?
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the functional parameter ndims only gives the total number of eval points, where as here for plotting we need the breakdown of # eval points per dimension. It might be worth storing this grid-shape internally however, for future use in reshaping. I'll create a separate issue, I presume it is obtainable from the GRF package.
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I have appended this into #282
function distribution docs run show(parameter_distribution) format updated from review
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I've also created an issue for the terminology #308 |
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bors r+ |
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Purpose
Fixes #300
Addresses GRF docs part of #282
NB this is merely documenting what is currently implemented, improvements to the API will come soon.
Content
constraintkeyword to fixbase.show()bug with function distributionsshow(parameter_distribution)during tests to appease codecovGaussianRandomFieldInterfaceobject and samples.Relevant docs section found here and here.