PQ-Trees

This module implements PQ-Trees and methods to help recognise Interval Graphs. It is used by is_interval.

Author:

  • Nathann Cohen
class sage.graphs.pq_trees.P(seq)

Bases: sage.graphs.pq_trees.PQ

A P-Tree is a PQ-Tree whose children are not ordered (they can be permuted in any way)

set_contiguous(v)

Updates self so that its sets containing v are contiguous for any admissible permutation of its subtrees.

This function also ensures, whenever possible, that all the sets containing v are located on an interval on the right side of the ordering.

INPUT:

  • v – an element of the ground set

OUTPUT:

According to the cases :

  • (EMPTY, ALIGNED) if no set of the tree contains an occurrence of v
  • (FULL, ALIGNED) if all the sets of the tree contain v
  • (PARTIAL, ALIGNED) if some (but not all) of the sets contain v, all of which are aligned to the right of the ordering at the end when the function ends
  • (PARTIAL, UNALIGNED) if some (but not all) of the sets contain v, though it is impossible to align them all to the right

In any case, the sets containing v are contiguous when this function ends. If there is no possibility of doing so, the function raises a ValueError exception.

EXAMPLE:

Ensuring the sets containing 0 are continuous:

sage: from sage.graphs.pq_trees import P, Q
sage: p = P([[0,3], [1,2], [2,3], [2,4], [4,0],[2,8], [2,9]])
sage: p.set_contiguous(0)
(1, True)
sage: print p
('P', [{1, 2}, {2, 3}, {2, 4}, {8, 2}, {9, 2}, ('P', [{0, 3}, {0, 4}])])

Impossible situation:

sage: p = P([[0,1], [1,2], [2,3], [3,0]])
sage: p.set_contiguous(0)
(1, True)
sage: p.set_contiguous(1)
(1, True)
sage: p.set_contiguous(2)
(1, True)
sage: p.set_contiguous(3)
Traceback (most recent call last):
...
ValueError: Impossible
class sage.graphs.pq_trees.PQ(seq)

This class implements the PQ-Tree, used for the recognition of Interval Graphs, or equivalently for matrices having the so-caled “consecutive ones property”.

Briefly, we are given a collection \(C=S_1, ..., S_n\) of sets on a common ground set \(X\), and we would like to reorder the elements of \(C\) in such a way that for every element \(x\in X\) such that \(x\in S_i\) and \(x\in S_j\), \(i<j\), we have \(x\in S_l\) for all \(i<l<j\). This property could also be rephrased as : the sets containing \(x\) are an interval.

To achieve it, we will actually compute ALL the orderings satisfying such constraints using the structure of PQ-Tree, by adding the constraints one at a time.

  • At first, there is no constraint : all the permutations are allowed. We will then build a tree composed of one node linked to all the sets in our collection (his children). As we want to remember that all the permutations of his children are allowed, we will label it with “P”, making it a P-Tree.

  • We are now picking an element \(x \in X\), and we want to ensure that all the elements \(C_x\) containing it are contiguous. We can remove them from their tree \(T_1\), create a second tree \(T_2\) whose only children are the \(C_x\), and attach this \(T_2\) to \(T_1\). We also make this new tree a \(P-Tree\), as all the elements of \(C_x\) can be permuted as long as they stay close to each other. Obviously, the whole tree \(T_2\) can be prmuter with the other children of \(T_1\) in any way – it does not impair the fact that the sequence of the children will ensure the sets containing \(x\) are contiguous.

  • We would like to repeat the same procedure for \(x' \in X\), but we are now encountering a problem : there may be sets containing both \(x'\) and \(x\), along with others containing only \(x\) or only \(x'\). We can permute the sets containing only \(x'\) together, or the sets containing both \(x\) and \(x'\) together, but we may NOT permute all the sets containing \(x'\) together as this may break the relationship between the sets containing \(x\). We need \(Q\)-Trees. A \(Q\)-Tree is a tree whose children are ordered, even though their order could be reversed (if the children of a \(Q\)-Tree are \(c_1c_2 ... c_k\), we can change it to \(c_k ... c_2c_1\)). We can now express all the orderings satisfying our two constraints the following way :

    • We create a tree \(T_1\) gathering all the elements not containing \(x\) nor \(x'\), and make it a \(P-Tree\)

    • We create 3 \(P\)-Trees \(T_{x, x'}, T_x, T_{x'}\), which respectively have for children the elements or our collection containing

      • both \(x\) and \(x'\)
      • only \(x\)
      • only \(x'\)
    • To ensure our constraints on both elements, we create a \(Q\)-tree \(T_2\) whose children are in order \(T_x, T_{x, x'}, T_{x'}\)

    • We now make this \(Q\)-Tree \(T_2\) a children of the \(P\)-Tree \(T_1\)

Using these two types of tree, and exploring the different cases of intersection, it is possible to represent all the possible permutations of our sets satisfying or constraints, or to prove that no such ordering exists. This is the whole purpose of this class and this algorithm, and is explained with more details in many places, for example in the following document from Hajiaghayi [Haj].

REFERENCES:

[Haj]M. Hajiaghayi http://www-math.mit.edu/~hajiagha/pp11.ps

AUTHOR : Nathann Cohen

cardinality()

Returns the number of children of self

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: p = Q([[1,2], [2,3], P([[2,4], [2,8], [2,9]])])
sage: p.cardinality()
3
flatten()

Returns a flattened copy of self

If self has only one child, we may as well consider its child’s children, as self encodes no information. This method recursively “flattens” trees having only on PQ-tree child, and returns it.

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: p = Q([P([[2,4], [2,8], [2,9]])])
sage: p.flatten()
('P', [{2, 4}, {8, 2}, {9, 2}])
is_P()

Tests whether self is a \(P\)-Tree

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: P([[0,1],[2,3]]).is_P()
True
sage: Q([[0,1],[2,3]]).is_P()
False
is_Q()

Tests whether self is a \(Q\)-Tree

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: Q([[0,1],[2,3]]).is_Q()
True
sage: P([[0,1],[2,3]]).is_Q()
False
ordering()

Returns the current ordering given by listing the leaves from left to right.

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: p = Q([[1,2], [2,3], P([[2,4], [2,8], [2,9]])])
sage: p.ordering()
[{1, 2}, {2, 3}, {2, 4}, {8, 2}, {9, 2}]
reverse()

Recursively reverses self and its children

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: p = Q([[1,2], [2,3], P([[2,4], [2,8], [2,9]])])
sage: p.ordering()
[{1, 2}, {2, 3}, {2, 4}, {8, 2}, {9, 2}]
sage: p.reverse()
sage: p.ordering()
[{9, 2}, {8, 2}, {2, 4}, {2, 3}, {1, 2}]
simplify(v, left=False, right=False)

Returns a simplified copy of self according to the element v

If self is a partial P-tree for v, we would like to restrict the permutations of its children to permutations keeping the children containing v contiguous. This function also “locks” all the elements not containing v inside a \(P\)-tree, which is useful when one want to keep the elements containing v on one side (which is the case when this method is called).

INPUT:

  • left, right (booleans) – whether v is aligned to the right or to the left
  • v`– an element of the ground set

OUTPUT:

If self is a \(Q\)-Tree, the sequence of its children is returned. If self is a \(P\)-tree, 2 \(P\)-tree are returned, namely the two \(P\)-tree defined above and restricting the permutations, in the order implied by left, right (if right =True, the second \(P\)-tree will be the one gathering the elements containing v, if left=True, the opposite).

Note

This method is assumes that self is partial for v, and aligned to the side indicated by left, right.

EXAMPLES:

A \(P\)-Tree

sage: from sage.graphs.pq_trees import P, Q
sage: p = P([[2,4], [1,2], [0,8], [0,5]])
sage: p.simplify(0, right = True)
[('P', [{2, 4}, {1, 2}]), ('P', [{0, 8}, {0, 5}])]

A \(Q\)-Tree

sage: q = Q([[2,4], [1,2], [0,8], [0,5]])
sage: q.simplify(0, right = True)
[{2, 4}, {1, 2}, {0, 8}, {0, 5}]
split(v)

Returns the subsequences of children containing and not containing v

INPUT:

  • v – an element of the ground set

OUTPUT:

Two lists, the first containing the children of self containing v, and the other containing the other children.

Note

This command is meant to be used on a partial tree, once it has be “set continuous” on an element v and aligned it to the right. Hence, none of the list should be empty (an exception is raised if that happens, as it would reveal a bug in the algorithm) and the sum contains + does_not_contain should be equal to the sequence of children of self.

EXAMPLE:

sage: from sage.graphs.pq_trees import P, Q
sage: p = Q([[1,2], [2,3], P([[2,4], [2,8], [2,9]])])
sage: p.reverse()
sage: contains, does_not_contain = p.split(1)
sage: contains
[{1, 2}]
sage: does_not_contain
[('P', [{9, 2}, {8, 2}, {2, 4}]), {2, 3}]
sage: does_not_contain + contains == p._children
True
class sage.graphs.pq_trees.Q(seq)

Bases: sage.graphs.pq_trees.PQ

A Q-Tree is a PQ-Tree whose children are ordered up to reversal

set_contiguous(v)

Updates self so that its sets containing v are contiguous for any admissible permutation of its subtrees.

This function also ensures, whenever possible, that all the sets containing v are located on an interval on the right side of the ordering.

INPUT:

  • v – an element of the ground set

OUTPUT:

According to the cases :

  • (EMPTY, ALIGNED) if no set of the tree contains an occurrence of v
  • (FULL, ALIGNED) if all the sets of the tree contain v
  • (PARTIAL, ALIGNED) if some (but not all) of the sets contain v, all of which are aligned to the right of the ordering at the end when the function ends
  • (PARTIAL, UNALIGNED) if some (but not all) of the sets contain v, though it is impossible to align them all to the right

In any case, the sets containing v are contiguous when this function ends. If there is no possibility of doing so, the function raises a ValueError exception.

EXAMPLE:

Ensuring the sets containing 0 are continuous:

sage: from sage.graphs.pq_trees import P, Q
sage: q = Q([[2,3], Q([[3,0],[3,1]]), Q([[4,0],[4,5]])])
sage: q.set_contiguous(0)
(1, False)
sage: print q
('Q', [{2, 3}, {1, 3}, {0, 3}, {0, 4}, {4, 5}])

Impossible situation:

sage: p = Q([[0,1], [1,2], [2,0]])
sage: p.set_contiguous(0)
Traceback (most recent call last):
...
ValueError: Impossible
sage.graphs.pq_trees.flatten(x)

x.__init__(...) initializes x; see help(type(x)) for signature

sage.graphs.pq_trees.new_P(liste)

x.__init__(...) initializes x; see help(type(x)) for signature

sage.graphs.pq_trees.new_Q(liste)

x.__init__(...) initializes x; see help(type(x)) for signature

sage.graphs.pq_trees.reorder_sets(sets)

Reorders a collection of sets such that each element appears on an interval.

Given a collection of sets \(C = S_1,...,S_k\) on a ground set \(X\), this function attempts to reorder them in such a way that \(\forall x \in X\) and \(i<j\) with \(x\in S_i, S_j\), then \(x\in S_l\) for every \(i<l<j\) if it exists.

INPUT:

  • sets - a list of instances of list, Set or set

ALGORITHM:

PQ-Trees

EXAMPLE:

There is only one way (up to reversal) to represent contiguously the sequence ofsets \(\{i-1, i, i+1\}\):

sage: from sage.graphs.pq_trees import reorder_sets
sage: seq = [Set([i-1,i,i+1]) for i in range(1,15)]

We apply a random permutation:

sage: p = Permutations(len(seq)).random_element()
sage: seq = [ seq[p(i+1)-1] for i in range(len(seq)) ]
sage: ordered = reorder_sets(seq)
sage: if not 0 in ordered[0]:
...      ordered = ordered.reverse()
sage: print ordered
[{0, 1, 2}, {1, 2, 3}, {2, 3, 4}, {3, 4, 5}, {4, 5, 6}, {5, 6, 7}, {8, 6, 7}, {8, 9, 7}, {8, 9, 10}, {9, 10, 11}, {10, 11, 12}, {11, 12, 13}, {12, 13, 14}, {13, 14, 15}]
sage.graphs.pq_trees.set_contiguous(tree, x)

x.__init__(...) initializes x; see help(type(x)) for signature

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