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quadtree_boundary

quadtree_boundary(CH, A)

"Boundary of a quadtree

Returns indeces of cells that fall on the boundary (defined as cells that have no neighbor in at least one direction)

Parameters:

Name Type Description Default
CH numpy int array

Matrix of child indeces (-1 if leaf node)

 required
A scipy sparse.csr_matrix

Sparse node adjacency matrix, where a value of a in the (i,j) entry means that node j is to the a-th direction of i (a=1: left; a=2: right; a=3: bottom; a=4: top).

 required

Returns:

Name Type Description
children_boundary list

Indeces into CH and A of cells that are both boundary cells and leaf nodes in the tree
other_boundary list

All boundary cells regardless of leaf status

See Also

initialize_quadtree, quadtree_children.

Notes

This only works in 2D quadtrees.

Examples:

TODO

Source code in src/gpytoolbox/quadtree_boundary.py 
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def quadtree_boundary(CH,A):
    """"Boundary of a quadtree

    Returns indeces of cells that fall on the boundary (defined as cells that have no neighbor in at least one direction)

    Parameters
    ----------
    CH : numpy int array
        Matrix of child indeces (-1 if leaf node)
    A : scipy sparse.csr_matrix
        Sparse node adjacency matrix, where a value of a in the (i,j) entry means that node j is to the a-th direction of i (a=1: left;  a=2: right;  a=3: bottom;  a=4: top).

    Returns
    -------
    children_boundary : list
        Indeces into CH and A of cells that are both boundary cells and leaf nodes in the tree
    other_boundary : list
        All boundary cells regardless of leaf status

    See Also
    --------
    initialize_quadtree, quadtree_children.

    Notes
    -----
    This only works in 2D quadtrees.

    Examples
    --------
    TODO 
    """
    # Returns indeces of cells that fall on the boundary (defined as cells that
    # have no neighbor in at least one direction)
    #
    # Inputs:
    #   CH #nodes by 4 matrix of child indeces (-1 if leaf node)
    #   A #nodes by #nodes sparse adjacency matrix, where a value of a in the
    #       (i,j) entry means that node j is to the a-th direction of i
    #       (a=1: left;  a=2: right;  a=3: bottom;  a=4: top).
    #
    # Outputs:
    #   children_boundary is a list of indeces to CH and A of cells that are 
    #       both boundary cells and leaf nodes in the tree
    #   other_boundary is a list of all boundary cells regardless of parenthood 
    #
    #
    #

    children_boundary = []
    other_boundary = []
    for i in range(A.shape[0]):
        # go over possible direction
        for j in range(1,5):
            # is there a neighbor in this direction?
            j_neighbors = (A[i,:]==j).sum(axis=1).squeeze()
            #print(j_neighbors)
            if j_neighbors==0:
                other_boundary.append(i)
                if CH[i,0]==-1:
                    children_boundary.append(i)
                break

    # # Get uniques
    # children_boundary = list(set(children_boundary))
    # other_boundary = list(set(other_boundary))
    return children_boundary, other_boundary