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halfedge_edge_map

halfedge_edge_map(F, assume_manifold=True)

Computes unique edge indices, and a unique map from halfedges to edges, as well as its inverse. There is no particular ordering convention for edges. Boundary edges are guaranteed to be oriented as in F.

The ordering convention for halfedges is the following: [halfedge opposite vertex 0, halfedge opposite vertex 1, halfedge opposite vertex 2]

Parameters:

Name Type Description Default
F (m,3) numpy int array

face index list of a triangle mesh

 required
assume_manifold bool, optional (default True)

if this is true, will assume that F is manifold, and thus every edge can be incident to at most two halfedges. The algorithm is very slow if this is False.

 True

Returns:

Name Type Description
he (m,3,2) numpy int array

halfedge list as per above conventions
E (e,2) numpy int array

indices of edges into the vertex array
he_to_E (m,3) numpy int array

index map from he to corresponding row in E
E_to_he (e,2,2) numpy int array of list of m (k,2) numpy int arrays

if assume_manifold, (e,2,2) index map from e to corresponding row and col in he for two halfedges (or -1 if only one halfedge exists); if not assume_manifold, python list with m entries of (k,2) arrays, where k is however many halfedges are adjacent to each edge.

Examples:

TODO

Source code in src/gpytoolbox/halfedge_edge_map.py 
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def halfedge_edge_map(F, assume_manifold=True):
    """Computes unique edge indices, and a unique map from halfedges to edges,
    as well as its inverse.
    There is no particular ordering convention for edges.
    Boundary edges are guaranteed to be oriented as in F.

    The ordering convention for halfedges is the following:
    [halfedge opposite vertex 0,
     halfedge opposite vertex 1,
     halfedge opposite vertex 2]

    Parameters
    ----------
    F : (m,3) numpy int array
        face index list of a triangle mesh
    assume_manifold : bool, optional (default True)
        if this is true, will assume that F is manifold, and thus every edge can 
        be incident to at most two halfedges.
        The algorithm is very slow if this is False.

    Returns
    -------
    he : (m,3,2) numpy int array
        halfedge list as per above conventions
    E : (e,2) numpy int array
        indices of edges into the vertex array
    he_to_E : (m,3) numpy int array
        index map from he to corresponding row in E
    E_to_he : (e,2,2) numpy int array of list of m (k,2) numpy int arrays
        if assume_manifold, (e,2,2) index map from e to corresponding row and
        col in he for two halfedges (or -1 if only one halfedge exists);
        if not assume_manifold, python list with m entries of (k,2) arrays,
        where k is however many halfedges are adjacent to each edge. 

    Examples
    --------
    TODO

    """

    m = F.shape[0]
    assert m > 0
    assert F.shape[1] == 3

    he = halfedges(F)
    flat_he = np.concatenate([he[:,0,:],he[:,1,:],he[:,2,:]], axis=0)
    sorted_he = np.sort(flat_he, axis=1)
    unique_he, unique_indices, unique_count = np.unique(sorted_he, axis=0,
        return_index=True, return_counts=True)

    # Boundary edges come first, in order to preserve their orientation.
    bdry_E_to_flat_he = unique_indices[unique_count==1]
    n_b = bdry_E_to_flat_he.shape[0]
    bdry_E = flat_he[bdry_E_to_flat_he,:]

    # Interior edges come after.
    interior_E_to_first_flat_he = unique_indices[unique_count>1]
    n_i = interior_E_to_first_flat_he.shape[0]
    interior_E = flat_he[interior_E_to_first_flat_he,:]

    # Construct edges array
    E = np.concatenate([bdry_E,interior_E], axis=0)
    assert E.shape == unique_he.shape

    # Construct the E_to_he map
    def unflat_he(flat_he):
        return np.stack((flat_he%m, flat_he//m), axis=-1)
    if assume_manifold:
        E_to_he = np.full((E.shape[0],2,2), -1, dtype=F.dtype)
        if n_b>0:
            E_to_he[0:n_b,0,:] = unflat_he(bdry_E_to_flat_he)
        if n_i>0:
            E_to_he[n_b:(n_b+n_i),0,:] = \
            unflat_he(array_correspondence(interior_E,flat_he,axis=1))
            E_to_he[n_b:(n_b+n_i),1,:] = \
            unflat_he(array_correspondence(interior_E,np.flip(flat_he, axis=-1),axis=1))
    else:
        E_to_he = []
        bdry_E_to_he = unflat_he(bdry_E_to_flat_he)
        for e in range(n_b):
            E_to_he.append(bdry_E_to_he[e,:][None,:])
        for e in range(n_b, (n_b+n_i)):
            flat_he_inds = np.nonzero((E[e,:][None,:]==flat_he).all(axis=-1) |
                (np.flip(E[e,:],axis=-1)[None,:]==flat_he).all(axis=-1))[0]
            E_to_he.append(unflat_he(flat_he_inds))

    # Construct the he_to_E map
    he_to_E = np.full(F.shape, -1, dtype=F.dtype)
    if assume_manifold:
        he_r = E_to_he[:,:,0].flatten()
        he_c = E_to_he[:,:,1].flatten()
        es_to_put = np.stack((np.arange(E_to_he.shape[0]),np.arange(E_to_he.shape[0])), axis=-1).flatten()
        valid = he_r >= 0
        he_to_E[he_r[valid], he_c[valid]] = es_to_put[valid]
    else:
        for e in range(len(E_to_he)):
            he_to_E[E_to_he[e][:,0], E_to_he[e][:,1]] = e
    assert not np.any(he_to_E == -1)

    return he, E, he_to_E, E_to_he