Suffix Tries and Suffix Trees#

class sage.combinat.words.suffix_trees.DecoratedSuffixTree(w)[source]#

Bases: ImplicitSuffixTree

The decorated suffix tree of a word.

A decorated suffix tree of a word $w$ is the suffix tree of $w$ marked with the end point of all squares in the $w$.

The symbol $ is appended to w to ensure that each final state is a leaf of the suffix tree.

INPUT:

w – a finite word

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import DecoratedSuffixTree
sage: w = Word('0011001')
sage: DecoratedSuffixTree(w)
Decorated suffix tree of : 0011001$
sage: w = Word('0011001', '01')
sage: DecoratedSuffixTree(w)
Decorated suffix tree of : 0011001$

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import DecoratedSuffixTree
>>> w = Word('0011001')
>>> DecoratedSuffixTree(w)
Decorated suffix tree of : 0011001$
>>> w = Word('0011001', '01')
>>> DecoratedSuffixTree(w)
Decorated suffix tree of : 0011001$

ALGORITHM:

When using 'pair' as output, the squares are retrieved in linear time. The algorithm is an implementation of the one proposed in [DS2004].

square_vocabulary(output='pair')[source]#

Return the list of distinct squares of self.word.

Two types of outputs are available $pair$ and $word$. The algorithm is only truly linear if $output$ is set to $pair$. A pair is a tuple $(i, l)$ that indicates the factor self.word()[i:i+l]. The option 'word' return word objects.

INPUT:

output – (default: "pair") either "pair" or "word"

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import DecoratedSuffixTree
sage: w = Word('aabb')
sage: sorted(DecoratedSuffixTree(w).square_vocabulary())
[(0, 0), (0, 2), (2, 2)]
sage: w = Word('00110011010')
sage: sorted(DecoratedSuffixTree(w).square_vocabulary(output="word"))
[word: , word: 00, word: 00110011, word: 01100110, word: 1010, word: 11]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import DecoratedSuffixTree
>>> w = Word('aabb')
>>> sorted(DecoratedSuffixTree(w).square_vocabulary())
[(0, 0), (0, 2), (2, 2)]
>>> w = Word('00110011010')
>>> sorted(DecoratedSuffixTree(w).square_vocabulary(output="word"))
[word: , word: 00, word: 00110011, word: 01100110, word: 1010, word: 11]

class sage.combinat.words.suffix_trees.ImplicitSuffixTree(word)[source]#

Bases: SageObject

Construct the implicit suffix tree of a word w.

The suffix tree of a word w is a compactification of the suffix trie for w. The compactification removes all nodes that have exactly one incoming edge and exactly one outgoing edge. It consists of two components: a tree and a word. Thus, instead of labelling the edges by factors of w, we can labelled them by indices of the occurrence of the factors in w.

The following is a straightforward implementation of Ukkonen’s on-line algorithm for constructing the implicit suffix tree [Ukko1995]. It constructs the suffix tree for w[:i] from that of w[:i-1].

GENERAL IDEA. The suffix tree of w[:i+1] can be obtained from that of w[:i] by visiting each node corresponding to a suffix of w[:i] and modifying the tree by applying one of two rules (either append a new node to the tree, or split an edge into two). The “active state” is the node where the algorithm begins and the “suffix link” carries us to the next node that needs to be dealt with.

TREE. The tree is modelled as an automaton, which is stored as a dictionary of dictionaries: it is keyed by the nodes of the tree, and the corresponding dictionary is keyed by pairs $(i,j)$ of integers representing the word w[i-1:j]. This makes it faster to look up a particular transition beginning at a specific node.

STATES/NODES. The states will always be -1, 0, 1, …, n. The state -1 is special and is only used for the purposes of the algorithm. All transitions map -1 to 0, so this information is not explicitly stored in the transition function.

EXPLICIT/IMPLICIT NODES. By definition, some of the nodes will not be states, but merely locations along an edge; these are called implicit nodes. A node r (implicit or explicit) is referenced as a pair (s,(k,p)) where s is an ancestor of r and w[k-1:p] is the word read by transitioning from s to r in the suffix trie. A reference pair is canonical if s is the closest ancestor of r.

SUFFIX LINK. The algorithm makes use of a map from (some) nodes to other nodes, called the suffix link. This is stored as a dictionary.

ACTIVE STATE. We store as ._active_state the active state of the tree, the state where the algorithm will begin when processing the next letter.

RUNNING TIME. The running time and storage space of the algorithm is linear in the length of the word w (whereas for a suffix tree it is quadratic).

REFERENCES:

[Ukko1995]

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: w = Words("aco")("cacao")
sage: t = ImplicitSuffixTree(w); t
Implicit Suffix Tree of the word: cacao
sage: ababb = Words([0,1])([0,1,0,1,1])
sage: s = ImplicitSuffixTree(ababb); s
Implicit Suffix Tree of the word: 01011

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> w = Words("aco")("cacao")
>>> t = ImplicitSuffixTree(w); t
Implicit Suffix Tree of the word: cacao
>>> ababb = Words([Integer(0),Integer(1)])([Integer(0),Integer(1),Integer(0),Integer(1),Integer(1)])
>>> s = ImplicitSuffixTree(ababb); s
Implicit Suffix Tree of the word: 01011

LZ_decomposition()[source]#

Return a list of index of the beginning of the block of the Lempel-Ziv decomposition of self.word

The Lempel-Ziv decomposition is the factorisation $u_1...u_k$ of a word $w=x_1...x_n$ such that $u_i$ is the longest prefix of $u_i...u_k$ that has an occurrence starting before $u_i$ or a letter if this prefix is empty.

OUTPUT:

Return a list iB of index such that the blocks of the decomposition are self.word()[iB[k]:iB[k+1]]

EXAMPLES:

Sage

sage: w = Word('abababb')
sage: T = w.suffix_tree()
sage: T.LZ_decomposition()
[0, 1, 2, 6, 7]
sage: w = Word('abaababacabba')
sage: T = w.suffix_tree()
sage: T.LZ_decomposition()
[0, 1, 2, 3, 6, 8, 9, 11, 13]
sage: w = Word([0, 0, 0, 1, 1, 0, 1])
sage: T = w.suffix_tree()
sage: T.LZ_decomposition()
[0, 1, 3, 4, 5, 7]
sage: w = Word('0000100101')
sage: T = w.suffix_tree()
sage: T.LZ_decomposition()
[0, 1, 4, 5, 9, 10]

Python

>>> from sage.all import *
>>> w = Word('abababb')
>>> T = w.suffix_tree()
>>> T.LZ_decomposition()
[0, 1, 2, 6, 7]
>>> w = Word('abaababacabba')
>>> T = w.suffix_tree()
>>> T.LZ_decomposition()
[0, 1, 2, 3, 6, 8, 9, 11, 13]
>>> w = Word([Integer(0), Integer(0), Integer(0), Integer(1), Integer(1), Integer(0), Integer(1)])
>>> T = w.suffix_tree()
>>> T.LZ_decomposition()
[0, 1, 3, 4, 5, 7]
>>> w = Word('0000100101')
>>> T = w.suffix_tree()
>>> T.LZ_decomposition()
[0, 1, 4, 5, 9, 10]

active_state()[source]#

Return the active state of the suffix tree.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words([0,1,2])
sage: t = ImplicitSuffixTree(W([0,1,0,1,2]))
sage: t.active_state()
(0, (6, 6))

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words([Integer(0),Integer(1),Integer(2)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(2)]))
>>> t.active_state()
(0, (6, 6))

edge_iterator()[source]#

Return an iterator over the edges of the suffix tree.

The edge from $u$ to $v$ labelled by $(i,j)$ is yielded as the tuple $(u,v,(i,j))$.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: sorted( ImplicitSuffixTree(Word("aaaaa")).edge_iterator() )
[(0, 1, (0, None))]
sage: sorted( ImplicitSuffixTree(Word([0,1,0,1])).edge_iterator() )
[(0, 1, (0, None)), (0, 2, (1, None))]
sage: sorted( ImplicitSuffixTree(Word()).edge_iterator() )
[]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> sorted( ImplicitSuffixTree(Word("aaaaa")).edge_iterator() )
[(0, 1, (0, None))]
>>> sorted( ImplicitSuffixTree(Word([Integer(0),Integer(1),Integer(0),Integer(1)])).edge_iterator() )
[(0, 1, (0, None)), (0, 2, (1, None))]
>>> sorted( ImplicitSuffixTree(Word()).edge_iterator() )
[]

factor_iterator(n=None)[source]#

Generate distinct factors of self.

INPUT:

n – an integer, or None.

OUTPUT:

If n is an integer, returns an iterator over all distinct factors of length n. If n is None, returns an iterator generating all distinct factors.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator() )
[word: , word: a, word: ac, word: aca, word: acao, word: ao, word: c, word: ca, word: cac, word: caca, word: cacao, word: cao, word: o]
sage: sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator(1) )
[word: a, word: c, word: o]
sage: sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator(2) )
[word: ac, word: ao, word: ca]
sage: sorted( ImplicitSuffixTree(Word([0,0,0])).factor_iterator() )
[word: , word: 0, word: 00, word: 000]
sage: sorted( ImplicitSuffixTree(Word([0,0,0])).factor_iterator(2) )
[word: 00]
sage: sorted( ImplicitSuffixTree(Word([0,0,0])).factor_iterator(0) )
[word: ]
sage: sorted( ImplicitSuffixTree(Word()).factor_iterator() )
[word: ]
sage: sorted( ImplicitSuffixTree(Word()).factor_iterator(2) )
[]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator() )
[word: , word: a, word: ac, word: aca, word: acao, word: ao, word: c, word: ca, word: cac, word: caca, word: cacao, word: cao, word: o]
>>> sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator(Integer(1)) )
[word: a, word: c, word: o]
>>> sorted( ImplicitSuffixTree(Word("cacao")).factor_iterator(Integer(2)) )
[word: ac, word: ao, word: ca]
>>> sorted( ImplicitSuffixTree(Word([Integer(0),Integer(0),Integer(0)])).factor_iterator() )
[word: , word: 0, word: 00, word: 000]
>>> sorted( ImplicitSuffixTree(Word([Integer(0),Integer(0),Integer(0)])).factor_iterator(Integer(2)) )
[word: 00]
>>> sorted( ImplicitSuffixTree(Word([Integer(0),Integer(0),Integer(0)])).factor_iterator(Integer(0)) )
[word: ]
>>> sorted( ImplicitSuffixTree(Word()).factor_iterator() )
[word: ]
>>> sorted( ImplicitSuffixTree(Word()).factor_iterator(Integer(2)) )
[]

leftmost_covering_set()[source]#

Compute the leftmost covering set of square pairs in self.word(). Return a square as a pair (i,l) designating factor self.word()[i:i+l].

A leftmost covering set is a set such that the leftmost occurrence $(j,l)$ of a square in self.word() is covered by a pair $(i,l)$ in the set for all types of squares. We say that $(j,l)$ is covered by $(i,l)$ if $(i,l)$ (i+1,l), ldots, (j,l)` are all squares.

The set is returned in the form of a list P such that P[i] contains all the lengths of squares starting at i in the set. The lists P[i] are sorted in decreasing order.

The algorithm used is described in [DS2004].

EXAMPLES:

Sage

sage: w = Word('abaabaabbaaabaaba')
sage: T = w.suffix_tree()
sage: T.leftmost_covering_set()
[[6], [6], [2], [], [], [], [], [2], [], [], [6, 2], [], [], [], [], [], []]
sage: w = Word('abaca')
sage: T = w.suffix_tree()
sage: T.leftmost_covering_set()
[[], [], [], [], []]
sage: T = Word('aaaaa').suffix_tree()
sage: T.leftmost_covering_set()
[[4, 2], [], [], [], []]

Python

>>> from sage.all import *
>>> w = Word('abaabaabbaaabaaba')
>>> T = w.suffix_tree()
>>> T.leftmost_covering_set()
[[6], [6], [2], [], [], [], [], [2], [], [], [6, 2], [], [], [], [], [], []]
>>> w = Word('abaca')
>>> T = w.suffix_tree()
>>> T.leftmost_covering_set()
[[], [], [], [], []]
>>> T = Word('aaaaa').suffix_tree()
>>> T.leftmost_covering_set()
[[4, 2], [], [], [], []]

number_of_factors(n=None)[source]#

Count the number of distinct factors of self.word().

INPUT:

n – an integer, or None.

OUTPUT:

If n is an integer, returns the number of distinct factors of length n. If n is None, returns the total number of distinct factors.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: t = ImplicitSuffixTree(Word([1,2,1,3,1,2,1]))
sage: t.number_of_factors()
22
sage: t.number_of_factors(1)
3
sage: t.number_of_factors(9)
0
sage: t.number_of_factors(0)
1

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> t = ImplicitSuffixTree(Word([Integer(1),Integer(2),Integer(1),Integer(3),Integer(1),Integer(2),Integer(1)]))
>>> t.number_of_factors()
22
>>> t.number_of_factors(Integer(1))
3
>>> t.number_of_factors(Integer(9))
0
>>> t.number_of_factors(Integer(0))
1

Sage

sage: t = ImplicitSuffixTree(Word("cacao"))
sage: t.number_of_factors()
13
sage: list(map(t.number_of_factors, range(10)))
[1, 3, 3, 3, 2, 1, 0, 0, 0, 0]

Python

>>> from sage.all import *
>>> t = ImplicitSuffixTree(Word("cacao"))
>>> t.number_of_factors()
13
>>> list(map(t.number_of_factors, range(Integer(10))))
[1, 3, 3, 3, 2, 1, 0, 0, 0, 0]

Sage

sage: t = ImplicitSuffixTree(Word("c"*1000))
sage: t.number_of_factors()
1001
sage: t.number_of_factors(17)
1
sage: t.number_of_factors(0)
1

Python

>>> from sage.all import *
>>> t = ImplicitSuffixTree(Word("c"*Integer(1000)))
>>> t.number_of_factors()
1001
>>> t.number_of_factors(Integer(17))
1
>>> t.number_of_factors(Integer(0))
1

Sage

sage: ImplicitSuffixTree(Word()).number_of_factors()
1

Python

>>> from sage.all import *
>>> ImplicitSuffixTree(Word()).number_of_factors()
1

Sage

sage: blueberry = ImplicitSuffixTree(Word("blueberry"))
sage: blueberry.number_of_factors()
43
sage: list(map(blueberry.number_of_factors, range(10)))
[1, 6, 8, 7, 6, 5, 4, 3, 2, 1]

Python

>>> from sage.all import *
>>> blueberry = ImplicitSuffixTree(Word("blueberry"))
>>> blueberry.number_of_factors()
43
>>> list(map(blueberry.number_of_factors, range(Integer(10))))
[1, 6, 8, 7, 6, 5, 4, 3, 2, 1]

plot(word_labels=False, layout='tree', tree_root=0, tree_orientation='up', vertex_colors=None, edge_labels=True, *args, **kwds)[source]#

Return a Graphics object corresponding to the transition graph of the suffix tree.

INPUT:

word_labels – boolean (default: False) if False, labels the edges by pairs $(i, j)$; if True, labels the edges by word[i:j].
layout – (default: 'tree')
tree_root – (default: 0)
tree_orientation – (default: 'up')
vertex_colors – (default: None)
edge_labels – (default: True)

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: ImplicitSuffixTree(Word('cacao')).plot(word_labels=True)              # needs sage.graphs sage.plot
Graphics object consisting of 23 graphics primitives
sage: ImplicitSuffixTree(Word('cacao')).plot(word_labels=False)             # needs sage.graphs sage.plot
Graphics object consisting of 23 graphics primitives

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> ImplicitSuffixTree(Word('cacao')).plot(word_labels=True)              # needs sage.graphs sage.plot
Graphics object consisting of 23 graphics primitives
>>> ImplicitSuffixTree(Word('cacao')).plot(word_labels=False)             # needs sage.graphs sage.plot
Graphics object consisting of 23 graphics primitives

process_letter(letter)[source]#

Modify the current implicit suffix tree producing the implicit suffix tree for self.word() + letter.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: w = Words("aco")("cacao")
sage: t = ImplicitSuffixTree(w[:-1]); t
Implicit Suffix Tree of the word: caca
sage: t.process_letter(w[-1]); t
Implicit Suffix Tree of the word: cacao

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> w = Words("aco")("cacao")
>>> t = ImplicitSuffixTree(w[:-Integer(1)]); t
Implicit Suffix Tree of the word: caca
>>> t.process_letter(w[-Integer(1)]); t
Implicit Suffix Tree of the word: cacao

Sage

sage: W = Words([0,1])
sage: s = ImplicitSuffixTree(W([0,1,0,1])); s
Implicit Suffix Tree of the word: 0101
sage: s.process_letter(W([1])[0]); s
Implicit Suffix Tree of the word: 01011

Python

>>> from sage.all import *
>>> W = Words([Integer(0),Integer(1)])
>>> s = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1)])); s
Implicit Suffix Tree of the word: 0101
>>> s.process_letter(W([Integer(1)])[Integer(0)]); s
Implicit Suffix Tree of the word: 01011

show(word_labels=None, *args, **kwds)[source]#

Display the output of plot().

INPUT:

word_labels – (default: None) if False, labels the edges by pairs $(i, j)$; if True, labels the edges by word[i:j].

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: w = Words("cao")("cacao")
sage: t = ImplicitSuffixTree(w)
sage: t.show(word_labels=True)                                              # needs sage.plot
sage: t.show(word_labels=False)                                             # needs sage.plot

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> w = Words("cao")("cacao")
>>> t = ImplicitSuffixTree(w)
>>> t.show(word_labels=True)                                              # needs sage.plot
>>> t.show(word_labels=False)                                             # needs sage.plot

states()[source]#

Return the states (explicit nodes) of the suffix tree.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words([0,1,2])
sage: t = ImplicitSuffixTree(W([0,1,0,1,2]))
sage: t.states()
[0, 1, 2, 3, 4, 5, 6, 7]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words([Integer(0),Integer(1),Integer(2)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(2)]))
>>> t.states()
[0, 1, 2, 3, 4, 5, 6, 7]

suffix_link(state)[source]#

Evaluate the suffix link map of the implicit suffix tree on state.

Note that the suffix link is not defined for all states.

The suffix link of a state $x'$ that corresponds to the suffix $x$ is defined to be -1 is $x'$ is the root (0) and $y'$ otherwise, where $y'$ is the state corresponding to the suffix x[1:].

INPUT:

state – a state

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words([0,1,2])
sage: t = ImplicitSuffixTree(W([0,1,0,1,2]))
sage: t.suffix_link(3)
5
sage: t.suffix_link(5)
0
sage: t.suffix_link(0)
-1
sage: t.suffix_link(-1)
Traceback (most recent call last):
    ...
TypeError: there is no suffix link from -1

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words([Integer(0),Integer(1),Integer(2)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(2)]))
>>> t.suffix_link(Integer(3))
5
>>> t.suffix_link(Integer(5))
0
>>> t.suffix_link(Integer(0))
-1
>>> t.suffix_link(-Integer(1))
Traceback (most recent call last):
    ...
TypeError: there is no suffix link from -1

suffix_walk(edge, l)[source]#

Return the state of “w” if the input state is “aw”.

If the input state (edge, l) is path labeled “aw” with “a” a letter, the output is the state which is path labeled “w”.

INPUT:

edge – the edge containing the state
l – the string-depth of the state on edge (l>0)

OUTPUT:

Return ("explicit", end_node) if the state of w is an explicit state and ("implicit", edge, d) is obtained by reading d letters on edge.

EXAMPLES:

Sage

sage: T = Word('00110111011').suffix_tree()
sage: T.suffix_walk((0, 5), 1)
('explicit', 0)
sage: T.suffix_walk((7, 3), 1)
('implicit', (9, 4), 1)

Python

>>> from sage.all import *
>>> T = Word('00110111011').suffix_tree()
>>> T.suffix_walk((Integer(0), Integer(5)), Integer(1))
('explicit', 0)
>>> T.suffix_walk((Integer(7), Integer(3)), Integer(1))
('implicit', (9, 4), 1)

to_digraph(word_labels=False)[source]#

Return a DiGraph object of the transition graph of the suffix tree.

INPUT:

word_labels – boolean (default: False) if False, labels the edges by pairs $(i, j)$; if True, labels the edges by word[i:j].

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words([0,1,2])
sage: t = ImplicitSuffixTree(W([0,1,0,1,2]))
sage: t.to_digraph()                                                        # needs sage.graphs
Digraph on 8 vertices

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words([Integer(0),Integer(1),Integer(2)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(2)]))
>>> t.to_digraph()                                                        # needs sage.graphs
Digraph on 8 vertices

to_explicit_suffix_tree()[source]#

Convert self to an explicit suffix tree.

It is obtained by processing an end of string letter as if it were a regular letter, except that no new leaf nodes are created (thus, the only thing that happens is that some implicit nodes become explicit).

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: w = Words("aco")("cacao")
sage: t = ImplicitSuffixTree(w)
sage: t.to_explicit_suffix_tree()

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> w = Words("aco")("cacao")
>>> t = ImplicitSuffixTree(w)
>>> t.to_explicit_suffix_tree()

Sage

sage: W = Words([0,1])
sage: s = ImplicitSuffixTree(W([0,1,0,1,1]))
sage: s.to_explicit_suffix_tree()

Python

>>> from sage.all import *
>>> W = Words([Integer(0),Integer(1)])
>>> s = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(1)]))
>>> s.to_explicit_suffix_tree()

transition_function(word, node=0)[source]#

Return the node obtained by starting from node and following the edges labelled by the letters of word.

OUTPUT:

("explicit", end_node) if we end at end_node, or ("implicit", edge, d) if we end $d$ spots along an edge.

INPUT:

word – a word
node – (default: 0) starting node

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words([0,1,2])
sage: t = ImplicitSuffixTree(W([0,1,0,1,2]))
sage: t.transition_function(W([0,1,0]))
('implicit', (3, 1), 1)
sage: t.transition_function(W([0,1,2]))
('explicit', 4)
sage: t.transition_function(W([0,1,2]), 5)
('explicit', 2)
sage: t.transition_function(W([0,1]), 5)
('implicit', (5, 2), 2)

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words([Integer(0),Integer(1),Integer(2)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0),Integer(1),Integer(2)]))
>>> t.transition_function(W([Integer(0),Integer(1),Integer(0)]))
('implicit', (3, 1), 1)
>>> t.transition_function(W([Integer(0),Integer(1),Integer(2)]))
('explicit', 4)
>>> t.transition_function(W([Integer(0),Integer(1),Integer(2)]), Integer(5))
('explicit', 2)
>>> t.transition_function(W([Integer(0),Integer(1)]), Integer(5))
('implicit', (5, 2), 2)

transition_function_dictionary()[source]#

Return the transition function as a dictionary of dictionaries.

The format is consistent with the input format for DiGraph.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree
sage: W = Words("aco")
sage: t = ImplicitSuffixTree(W("cac"))
sage: t.transition_function_dictionary()
{0: {1: (0, None), 2: (1, None)}}

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree
>>> W = Words("aco")
>>> t = ImplicitSuffixTree(W("cac"))
>>> t.transition_function_dictionary()
{0: {1: (0, None), 2: (1, None)}}

Sage

sage: W = Words([0,1])
sage: t = ImplicitSuffixTree(W([0,1,0]))
sage: t.transition_function_dictionary()
{0: {1: (0, None), 2: (1, None)}}

Python

>>> from sage.all import *
>>> W = Words([Integer(0),Integer(1)])
>>> t = ImplicitSuffixTree(W([Integer(0),Integer(1),Integer(0)]))
>>> t.transition_function_dictionary()
{0: {1: (0, None), 2: (1, None)}}

trie_type_dict()[source]#

Return a dictionary in a format compatible with that of the suffix trie transition function.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree, SuffixTrie
sage: W = Words("ab")
sage: t = ImplicitSuffixTree(W("aba"))
sage: d = t.trie_type_dict()
sage: len(d)
5
sage: d                     # random
{(4, word: b): 5, (0, word: a): 4, (0, word: b): 3, (5, word: a): 1, (3, word: a): 2}

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree, SuffixTrie
>>> W = Words("ab")
>>> t = ImplicitSuffixTree(W("aba"))
>>> d = t.trie_type_dict()
>>> len(d)
5
>>> d                     # random
{(4, word: b): 5, (0, word: a): 4, (0, word: b): 3, (5, word: a): 1, (3, word: a): 2}

uncompactify()[source]#

Return the tree obtained from self by splitting edges so that they are labelled by exactly one letter.

The resulting tree is isomorphic to the suffix trie.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import ImplicitSuffixTree, SuffixTrie
sage: abbab = Words("ab")("abbab")
sage: s = SuffixTrie(abbab)
sage: t = ImplicitSuffixTree(abbab)
sage: t.uncompactify().is_isomorphic(s.to_digraph())                        # needs sage.graphs
True

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import ImplicitSuffixTree, SuffixTrie
>>> abbab = Words("ab")("abbab")
>>> s = SuffixTrie(abbab)
>>> t = ImplicitSuffixTree(abbab)
>>> t.uncompactify().is_isomorphic(s.to_digraph())                        # needs sage.graphs
True

word()[source]#: Return the word whose implicit suffix tree this is.

class sage.combinat.words.suffix_trees.SuffixTrie(word)[source]#

Bases: SageObject

Construct the suffix trie of the word w.

The suffix trie of a finite word w is a data structure representing the factors of w. It is a tree whose edges are labelled with letters of w, and whose leafs correspond to suffixes of w.

This is a straightforward implementation of Algorithm 1 from [Ukko1995]. It constructs the suffix trie of w[:i] from that of w[:i-1].

A suffix trie is modelled as a deterministic finite-state automaton together with the suffix_link map. The set of states corresponds to factors of the word (below we write x’ for the state corresponding to x); these are always 0, 1, …. The state 0 is the initial state, and it corresponds to the empty word. For the purposes of the algorithm, there is also an auxiliary state -1. The transition function t is defined as:

t(-1,a) = 0 for all letters a; and
t(x',a) = y' for all x',y' \in Q such that y = xa,

and the suffix link function is defined as:

suffix_link(0) = -1;
suffix_link(x') = y', if x = ay for some letter a.

REFERENCES:

[Ukko1995]

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cacao")
sage: t = SuffixTrie(w); t
Suffix Trie of the word: cacao

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cacao")
>>> t = SuffixTrie(w); t
Suffix Trie of the word: cacao

Sage

sage: e = Words("ab")()
sage: t = SuffixTrie(e); t
Suffix Trie of the word:
sage: t.process_letter("a"); t
Suffix Trie of the word: a
sage: t.process_letter("b"); t
Suffix Trie of the word: ab
sage: t.process_letter("a"); t
Suffix Trie of the word: aba

Python

>>> from sage.all import *
>>> e = Words("ab")()
>>> t = SuffixTrie(e); t
Suffix Trie of the word:
>>> t.process_letter("a"); t
Suffix Trie of the word: a
>>> t.process_letter("b"); t
Suffix Trie of the word: ab
>>> t.process_letter("a"); t
Suffix Trie of the word: aba

active_state()[source]#

Return the active state of the suffix trie.

This is the state corresponding to the word as a suffix of itself.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cacao")
sage: t = SuffixTrie(w)
sage: t.active_state()
8

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cacao")
>>> t = SuffixTrie(w)
>>> t.active_state()
8

Sage

sage: u = Words([0,1])([0,1,1,0,1,0,0,1])
sage: s = SuffixTrie(u)
sage: s.active_state()
22

Python

>>> from sage.all import *
>>> u = Words([Integer(0),Integer(1)])([Integer(0),Integer(1),Integer(1),Integer(0),Integer(1),Integer(0),Integer(0),Integer(1)])
>>> s = SuffixTrie(u)
>>> s.active_state()
22

final_states()[source]#

Return the set of final states of the suffix trie.

These are the states corresponding to the suffixes of self.word(). They are obtained be repeatedly following the suffix link from the active state until we reach 0.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cacao")
sage: t = SuffixTrie(w)
sage: t.final_states() == Set([8, 9, 10, 11, 12, 0])
True

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cacao")
>>> t = SuffixTrie(w)
>>> t.final_states() == Set([Integer(8), Integer(9), Integer(10), Integer(11), Integer(12), Integer(0)])
True

has_suffix(word)[source]#

Return True if and only if word is a suffix of self.word().

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cacao")
sage: t = SuffixTrie(w)
sage: [t.has_suffix(w[i:]) for i in range(w.length()+1)]
[True, True, True, True, True, True]
sage: [t.has_suffix(w[:i]) for i in range(w.length()+1)]
[True, False, False, False, False, True]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cacao")
>>> t = SuffixTrie(w)
>>> [t.has_suffix(w[i:]) for i in range(w.length()+Integer(1))]
[True, True, True, True, True, True]
>>> [t.has_suffix(w[:i]) for i in range(w.length()+Integer(1))]
[True, False, False, False, False, True]

node_to_word(state=0)[source]#

Return the word obtained by reading the edge labels from 0 to state.

INPUT:

state – (default: 0) a state

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("abc")("abcba")
sage: t = SuffixTrie(w)
sage: t.node_to_word(10)
word: abcba
sage: t.node_to_word(7)
word: abcb

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("abc")("abcba")
>>> t = SuffixTrie(w)
>>> t.node_to_word(Integer(10))
word: abcba
>>> t.node_to_word(Integer(7))
word: abcb

plot(layout='tree', tree_root=0, tree_orientation='up', vertex_colors=None, edge_labels=True, *args, **kwds)[source]#

Return a Graphics object corresponding to the transition graph of the suffix trie.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: SuffixTrie(Word("cacao")).plot()                                      # needs sage.plot
Graphics object consisting of 38 graphics primitives

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> SuffixTrie(Word("cacao")).plot()                                      # needs sage.plot
Graphics object consisting of 38 graphics primitives

process_letter(letter)[source]#

Modify self to produce the suffix trie for self.word() + letter.

Note

letter must occur within the alphabet of the word.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("ab")("ababba")
sage: t = SuffixTrie(w); t
Suffix Trie of the word: ababba
sage: t.process_letter("a"); t
Suffix Trie of the word: ababbaa

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("ab")("ababba")
>>> t = SuffixTrie(w); t
Suffix Trie of the word: ababba
>>> t.process_letter("a"); t
Suffix Trie of the word: ababbaa

show(*args, **kwds)[source]#

Display the output of plot().

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cac")
sage: t = SuffixTrie(w)
sage: t.show()                                                              # needs sage.plot

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cac")
>>> t = SuffixTrie(w)
>>> t.show()                                                              # needs sage.plot

states()[source]#

Return the states of the automaton defined by the suffix trie.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words([0,1])([0,1,1])
sage: t = SuffixTrie(w)
sage: t.states()
[0, 1, 2, 3, 4]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words([Integer(0),Integer(1)])([Integer(0),Integer(1),Integer(1)])
>>> t = SuffixTrie(w)
>>> t.states()
[0, 1, 2, 3, 4]

Sage

sage: u = Words("aco")("cacao")
sage: s = SuffixTrie(u)
sage: s.states()
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]

Python

>>> from sage.all import *
>>> u = Words("aco")("cacao")
>>> s = SuffixTrie(u)
>>> s.states()
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]

suffix_link(state)[source]#

Evaluate the suffix link map of the suffix trie on state.

Note that the suffix link map is not defined on -1.

INPUT:

state – a state

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cacao")
sage: t = SuffixTrie(w)
sage: list(map(t.suffix_link, range(13)))
[-1, 0, 3, 0, 5, 1, 7, 2, 9, 10, 11, 12, 0]
sage: t.suffix_link(0)
-1

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cacao")
>>> t = SuffixTrie(w)
>>> list(map(t.suffix_link, range(Integer(13))))
[-1, 0, 3, 0, 5, 1, 7, 2, 9, 10, 11, 12, 0]
>>> t.suffix_link(Integer(0))
-1

to_digraph()[source]#

Return a DiGraph object of the transition graph of the suffix trie.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("cao")("cac")
sage: t = SuffixTrie(w)
sage: d = t.to_digraph(); d                                                 # needs sage.graphs
Digraph on 6 vertices
sage: d.adjacency_matrix()                                                  # needs sage.graphs sage.modules
[0 1 0 1 0 0]
[0 0 1 0 0 0]
[0 0 0 0 1 0]
[0 0 0 0 0 1]
[0 0 0 0 0 0]
[0 0 0 0 0 0]

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("cao")("cac")
>>> t = SuffixTrie(w)
>>> d = t.to_digraph(); d                                                 # needs sage.graphs
Digraph on 6 vertices
>>> d.adjacency_matrix()                                                  # needs sage.graphs sage.modules
[0 1 0 1 0 0]
[0 0 1 0 0 0]
[0 0 0 0 1 0]
[0 0 0 0 0 1]
[0 0 0 0 0 0]
[0 0 0 0 0 0]

transition_function(node, word)[source]#

Return the state reached by beginning at node and following the arrows in the transition graph labelled by the letters of word.

INPUT:

node – a node
word – a word

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words([0,1])([0,1,0,1,1])
sage: t = SuffixTrie(w)
sage: all(t.transition_function(u, letter) == v
....:     for (u, letter), v in t._transition_function.items())
True

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words([Integer(0),Integer(1)])([Integer(0),Integer(1),Integer(0),Integer(1),Integer(1)])
>>> t = SuffixTrie(w)
>>> all(t.transition_function(u, letter) == v
...     for (u, letter), v in t._transition_function.items())
True

word()[source]#

Return the word whose suffix tree this is.

EXAMPLES:

Sage

sage: from sage.combinat.words.suffix_trees import SuffixTrie
sage: w = Words("abc")("abcba")
sage: t = SuffixTrie(w)
sage: t.word()
word: abcba
sage: t.word() == w
True

Python

>>> from sage.all import *
>>> from sage.combinat.words.suffix_trees import SuffixTrie
>>> w = Words("abc")("abcba")
>>> t = SuffixTrie(w)
>>> t.word()
word: abcba
>>> t.word() == w
True