Marco Musy

you can use ``` mesh.decimate(n=20000, method="pro") ``` Another option is to interpolate back the data with ``` decimated_mesh.interpolate_data_from(original_mesh, n=3) ``` ps: i edited the examples in the links.

How big is the mesh? the interpolate_data seems to do it fast on 500k points mesh. Anyways I have updated the `decimate` method and split ii in 3 different methods:...

This looks fantastic, thanks a lot Louis for the contribution! I added your script as an example here https://github.com/marcomusy/vedo/blob/master/examples/other/fast_simpl.py related: #1003 #1007

@Louis-Pujol Would you mind opening PR to correct the doc string? @raphaelsulzer I hope this can help addressing your case!

Hi, can you update to the latest vedo? ``` pip install vedo -U ``` then you need to change ``` numberOfDivisions -> number_of_divisions xyShift -> xyshift addScalarBar3D -> add_scalarbar3d ```...

Sorry I think you are right it's a genuine bug!

Thanks for reporting!

sorry for leaving this one behind, but I could not find a way to reproduce the issue - would be cool if you could upload a mesh example a code...

hi, what happens if you reset it outside of the constructor: ``` nkx = Mesh("nkx.ply") # nkx.pointdata.remove("RGB") # also try this nkx.color("green5").alpha(0.5) nkx ```

There might be something wrong with the normals (?) in the original mesh. This seems to work for me: ```py import vedo from vedo.applications import FreeHandCutPlotter msh = vedo.Volume(vedo.dataurl+'embryo.tif').isosurface().color('gold', 0.25)...