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Extend lengthscale tip #476

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merged 5 commits into from
Sep 26, 2022
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Extend lengthscale tip #476

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ad05748
Extend lengthscale tip
Sep 26, 2022
d5bd514
Tweak docstring
Sep 26, 2022
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Merge branch 'master' into wct/docs-improvement
willtebbutt Sep 26, 2022
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Pluralise title of tip
Sep 26, 2022
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Merge in master'
Sep 26, 2022
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9 changes: 7 additions & 2 deletions docs/src/userguide.md
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Expand Up @@ -8,7 +8,7 @@ For example, a squared exponential kernel is created by
k = SqExponentialKernel()
```

!!! tip "How do I set the lengthscale?"
!!! tip "How do I set the lengthscale(s)?"
Instead of having lengthscale(s) for each kernel we use [`Transform`](@ref) objects which act on the inputs before passing them to the kernel. Note that the transforms such as [`ScaleTransform`](@ref) and [`ARDTransform`](@ref) _multiply_ the input by a scale factor, which corresponds to the _inverse_ of the lengthscale.
For example, a lengthscale of 0.5 is equivalent to premultiplying the input by 2.0, and you can create the corresponding kernel in either of the following equivalent ways:
```julia
Expand All @@ -19,7 +19,12 @@ For example, a squared exponential kernel is created by
```julia
k = with_lengthscale(SqExponentialKernel(), 0.5)
```
[`with_lengthscale`](@ref) also works with vector-valued lengthscales for ARD.
[`with_lengthscale`](@ref) also works with vector-valued lengthscales for multiple-dimensional inputs, and is equivalent to pre-composing with an [`ARDTransform`](@ref):
```julia
length_scales = [1.0, 2.0]
k = with_lengthscale(SqExponentialKernel(), length_scales)
k = SqExponentialKernel() ∘ ARDTransform(1 ./ length_scales)
```
Check the [Input Transforms](@ref input_transforms) page for more details.

!!! tip "How do I set the kernel variance?"
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