In the Bplus.Math.perlin() function, you can customize coordinate transformations (e.x. to make the noise wrap around), or supply a custom curve for the interpolants (defaults to smootherstep()).
In the Fields.PerlinField struct, this customization is missing. It would need to be supported from within the DSL, so the best route is to let the user specify the coordinate transform as an AbstractField{NIn, NIn, F}. And specify the interpolation curve as an AbstractField{1, 1, F}.
An analytical gradient for PerlinField (see #15 ) gets more difficult to work out after adding this feature, but should still be achievable since each of these sub-fields can already tell you their own derivative. If an analytical gradient is added to PerlinField before this issue is done, then this one should be re-labeled to SIZE:medium and remove the good first issue as well.
In the
Bplus.Math.perlin()function, you can customize coordinate transformations (e.x. to make the noise wrap around), or supply a custom curve for the interpolants (defaults tosmootherstep()).In the
Fields.PerlinFieldstruct, this customization is missing. It would need to be supported from within the DSL, so the best route is to let the user specify the coordinate transform as anAbstractField{NIn, NIn, F}. And specify the interpolation curve as anAbstractField{1, 1, F}.An analytical gradient for
PerlinField(see #15 ) gets more difficult to work out after adding this feature, but should still be achievable since each of these sub-fields can already tell you their own derivative. If an analytical gradient is added toPerlinFieldbefore this issue is done, then this one should be re-labeled toSIZE:mediumand remove thegood first issueas well.