example of differential geometry tools in slam

# Authors: Guillaume Auzias <guillaume.auzias@univ-amu.fr>

# License: MIT
# sphinx_gallery_thumbnail_number = 2

importation of slam modules

import slam.io as sio
import slam.sulcal_depth as sdepth

loading an examplar mesh and corresponding texture

mesh_file = "../examples/data/example_mesh.gii"
texture_file = "../examples/data/example_texture.gii"
mesh = sio.load_mesh(mesh_file)

compute the depth potential function

dpf = sdepth.depth_potential_function(mesh)

Calculating vertex normals .... Please wait
Finished calculating vertex normals
Calculating curvature tensors ... Please wait
Finished Calculating curvature tensors
Calculating Principal Components ... Please wait
Finished Calculating principal components
  Computing Laplacian
    Computing mesh weights of type fem
    -edge length threshold needed for  0  values =  0.0  %
    -number of Nan in weights:  0  =  0.0  %
    -number of Negative values in weights:  936  =  6.706792777300086  %
    -nb Nan in Laplacian :  0
    -nb Inf in Laplacian :  0

compute the dpf_star

dpf_star = sdepth.dpf_star(mesh)

Calculating vertex normals .... Please wait
Finished calculating vertex normals
Calculating curvature tensors ... Please wait
Finished Calculating curvature tensors
Calculating Principal Components ... Please wait
Finished Calculating principal components
  Computing Laplacian
    Computing mesh weights of type conformal
    -edge length threshold needed for  0  values =  0.0  %
    -number of Nan in weights:  0  =  0.0  %
    -number of Negative values in weights:  936  =  6.706792777300086  %
    -nb Nan in Laplacian :  0
    -nb Inf in Laplacian :  0

VISUALIZATION USING plotly

import slam.plot as splt

display_settings = {}
display_settings['colorbar_label'] = 'dpf_star'
mesh_data = {}
mesh_data['vertices'] = mesh.vertices
mesh_data['faces'] = mesh.faces
mesh_data['title'] = 'dpf_star'
intensity_data = {}
intensity_data['values'] = dpf_star[0]
intensity_data["mode"] = "vertex"
fig = splt.plot_mesh(
    mesh_data=mesh_data,
    intensity_data=intensity_data,
    display_settings=display_settings)
fig.show()
fig