Create basic anisotropic field by scaling the cartesian axes to have the same length

[Leguark]

• [x] Check which functions read X_r Y_r

  • only interpolator seems to care

• [x] Check which functions read grid rescaled

  • self.grid.regular_grid.values_r is nowhere used
  • self.grid.regular_grid.values_r is used in Solutions.compute_marching_cubes_regurlar_grid and in regular grid for dx_dy_dz rescaled

• [x] Add a X_c Y_c column for the actual input data

• [ ] Visually inspect the impact that this feature has in each individual model. At least in the map2loop model

• [x] Refactor X_r or values_r to values_r or values_c, standing for rescaling or computing

• [x] Find the transform from prism to cube

  • Average between the 3 axis regular grid
  • Find the factor for each axis
  • Extent c should be the same on the 3 directions and the range the diagonal of this cube

~- [ ] It has to be a function that define the anisotropic field so be can set it once and that is used as we call for it. This can be seen as a fourth dimension that add distance between points. The scaling of this 4th dimension unit vector will rule how much we penalize the sparsity/density (for local anisotropy)~ -> #523