Given an undirected graph in which each node has a Cartesian coordinate in space that has the general shape of a tree, is there an algorithm to convert the graph into a tree, and find the appropriate root node?
Note that our definition of a "tree" requires that branches do not diverge from parent nodes at acute angles.
See the example graphs below. How do we find the red node?
here is a suggestion on how to solve your problem.
prerequisites
- notation:
g
graph, g.v
graph vertices
v,w,z
: individual vertices
e
: individual edge
n
: number of vertices
- any combination of an undirected tree g and a given node g.v uniquely determines a directed tree with root g.v (provable by induction)
idea
- complement the edges of
g
by orientations in the directed tree implied by g
and the yet-to-be-found root node by local computations at the nodes of g
.
- these orientations will represent child-parent-relationsships between nodes (
v -> w
: v
child, w
parent).
- the completely marked tree will contain a sole node with outdegree 0, which is the desired root node. you might end up with 0 or more than one root node.
algorithm
assumes standard representation of the graph/tree structure (eg adjacency list)
- all vertices in
g.v
are marked initially as not visited, not finished.
visit all vertices in arbitrary sequence. skip nodes marked as 'finished'.
let v
be the currently visited vertex.
- 2.1 sweep through all edges linking
v
clockwise starting with a randomly chosen e_0
in the order of the edges' angle with e_0
.
2.2. orient adjacent edges e_1=(v,w_1), e_2(v,w_2)
, that enclose an acute angle.
adjacent: wrt being ordered according to the angle they enclose with e_0
.
[ note: the existence of such a pair is not guaranteed, see 2nd comment and last remark. if no angle is acute, proceed at 2. with next node. ]
2.2.1 the orientations of edges e_1, e_2
are known:
w_1 -> v -> w_2
: impossible, as a grandparent-child-segment would enclose an acute angle
w_1 <- v <- w_2
: impossible, same reason
w_1 <- v -> w_2
: impossible, there are no nodes with outdegree >1 in a tree
w_1 -> v <- w_2
:
only possible pair of orientations. e_1, e_2
might have been oriented before. if the previous orientation violates the current assignment, the problem instance has no solution.
2.2.2 this assignment implies a tree structure on the subgraphs induced by all vertices reachable from w_1
(w_2
) on a path not comprising e_1 (
e_2`). mark all vertices in both induced subtrees as finished
[ note: the subtree structure might violate the angle constraints. in this case the problem has no solution. ]
2.3 mark v
visited. after completing steps 2.2 at vertex v
, check the number nc
of edges connecting that have not yet been assigned an orientation.
if you have not yet found a root node, your problem instance is ambiguous:
orient the remaining unoriented edges at will.
remarks
termination:
each node is visited at max 4 times:
- once per step 2
- at max twice per step 2.2.2
- at max once per step 2.3
correctness:
- all edges enclosing an acute angle are oriented per step 2.2.1
complexity (time):
- visiting every node: O(n);
the clockwise sweep through all edges connecting a given vertex requires these edges to be sorted.
thus you need O( sum_i=1..m ( k_i * lg k_i ) )
at m <= n
vertices under the constraint sum_i=1..m k_i = n
.
in total this requires O ( n * lg n)
, as sum_i=1..m ( k_i * lg k_i ) <= n * lg n
given sum_i=1..m k_i = n
for any m <= n
(provable by applying lagrange optimization).
[ note: if your trees have a degree bounded by a constant, you theoretically sort in constant time at each node affected; grand total in this case: O(n)
]
subtree marking:
each node in the graph is visited at max 2 times by this procedure if implemented as a dfs. thus a grand total of O(n)
for the invocation of this subroutine.
in total: O(n * lg n)
complexity (space):
O(n)
for sorting (with vertex-degree not constant-bound).
problem is probably ill-defined:
- multiple solutions: e.g. steiner tree
- no solution: e.g. graph shaped like a double-tipped arrow (<->)
A simple solution would be to define a 2d rectangle around the red node or the center of your node and compute each node with a moore curve. A moore curve is a space-filling curve, more over a special version of a hilbert curve where the start and end vertex is the same and the coordinate is in the middle of the 2d rectangle. In generell your problem looks like a discrete addressing space problem.