pyFM.refine.zoomout

Functions

mesh_zoomout_refine(FM_12, mesh1, mesh2[, ...])

Refine a functional map between meshes with ZoomOut.

mesh_zoomout_refine_p2p(p2p_21, mesh1, ...)

Refine a functional map between meshes with ZoomOut.

zoomout_iteration(FM_12, evects1, evects2[, ...])

Performs an iteration of ZoomOut.

zoomout_refine(FM_12, evects1, evects2[, ...])

Refine a functional map with ZoomOut.
pyFM.refine.zoomout.zoomout_iteration(FM_12, evects1, evects2, step=1, A2=None, n_jobs=1)

Performs an iteration of ZoomOut.

Parameters:

  • FM_12 – (k2,k1) Functional map from evects1[:,:k1] to evects2[:,:k2]

  • evects1 –

    (n1,k1’) eigenvectors on source shape with k1’ >= k1 + step.

    Can be a subsample of the original ones on the first dimension.

  • evects2 –

    (n2,k2’) eigenvectors on target shape with k2’ >= k2 + step.

    Can be a subsample of the original ones on the first dimension.

  • step (int) – step of increase of dimension.

  • A2 –

    (n2,n2) sparse area matrix on target mesh, for vertex to vertex computation.

    If specified, the eigenvectors can’t be subsampled !

Returns:

FM_zo – zoomout-refined functional map

Return type:

np.ndarray

pyFM.refine.zoomout.zoomout_refine(FM_12, evects1, evects2, nit=10, step=1, A2=None, subsample=None, return_p2p=False, n_jobs=1, verbose=False)

Refine a functional map with ZoomOut. Supports subsampling for each mesh, different step size, and approximate nearest neighbor.

Parameters:

  • eigvects1 – (n1,k1) eigenvectors on source shape with k1 >= K + nit

  • eigvects2 – (n2,k2) eigenvectors on target shape with k2 >= K + nit

  • FM_12 – (K,K) Functional map from from shape 1 to shape 2

  • nit (int) – number of iteration of zoomout

  • step – increase in dimension at each Zoomout Iteration

  • A2 – (n2,n2) sparse area matrix on target mesh.

  • subsample (tuple or iterable of size 2) –

    Each gives indices of vertices to sample

    for faster optimization. If not specified, no subsampling is done.

  • return_p2p (bool) – if True returns the vertex to vertex map.

Returns:

  • FM_12_zo (np.ndarray) – zoomout-refined functional map from basis 1 to 2

  • p2p_21_zo (np.ndarray) – only if return_p2p is set to True - the refined pointwise map from basis 2 to basis 1

pyFM.refine.zoomout.mesh_zoomout_refine(FM_12, mesh1, mesh2, nit=10, step=1, subsample=None, return_p2p=False, n_jobs=1, verbose=False)

Refine a functional map between meshes with ZoomOut. Supports subsampling for each mesh, different step size, and approximate nearest neighbor.

Parameters:

  • mesh1 (TriMesh) – Source mesh

  • mesh2 (TriMesh) – Target mesh

  • FM – (K,K) Functional map between

  • nit (int) – number of iteration of zoomout

  • step – increase in dimension at each Zoomout Iteration

  • A2 – (n2,n2) sparse area matrix on target mesh.

  • subsample (int or tuple or iterable of size 2) –

    Each gives indices of vertices so sample

    for faster optimization. If not specified, no subsampling is done.

  • return_p2p (bool) – if True returns the vertex to vertex map.

Returns:

  • FM_zo (zoomout-refined functional map)

  • p2p (only if return_p2p is set to True - the refined pointwise map)

pyFM.refine.zoomout.mesh_zoomout_refine_p2p(p2p_21, mesh1, mesh2, k_init, nit=10, step=1, subsample=None, return_p2p=False, n_jobs=1, p2p_on_sub=False, verbose=False)

Refine a functional map between meshes with ZoomOut. Supports subsampling for each mesh, different step size, and approximate nearest neighbor.

Parameters:

  • mesh1 (TriMesh) – Source mesh

  • mesh2 (TriMesh) – Target mesh

  • FM – (K,K) Functional map between

  • nit (int) – number of iteration of zoomout

  • step – increase in dimension at each Zoomout Iteration

  • A2 – (n2,n2) sparse area matrix on target mesh.

  • subsample (int or tuple or iterable of size 2) –

    Each gives indices of vertices so sample

    for faster optimization. If not specified, no subsampling is done.

  • return_p2p (bool) – if True returns the vertex to vertex map.

Returns:

  • FM_zo (np.ndarray) – zoomout-refined functional map

  • p2p (np.ndarray) – only if return_p2p is set to True - the refined pointwise map