diff options
Diffstat (limited to 'python/src/hypergraph.pxi')
| -rw-r--r-- | python/src/hypergraph.pxi | 56 |
1 files changed, 50 insertions, 6 deletions
diff --git a/python/src/hypergraph.pxi b/python/src/hypergraph.pxi index b210f440..5b675531 100644 --- a/python/src/hypergraph.pxi +++ b/python/src/hypergraph.pxi @@ -10,25 +10,39 @@ cdef class Hypergraph: if self.rng != NULL: del self.rng + cdef MT19937* _rng(self): + if self.rng == NULL: + self.rng = new MT19937() + return self.rng + def viterbi(self): + """hg.viterbi() -> String for the best hypothesis in the hypergraph.""" cdef vector[WordID] trans hypergraph.ViterbiESentence(self.hg[0], &trans) return unicode(GetString(trans).c_str(), 'utf8') def viterbi_trees(self): + """hg.viterbi_trees() -> (f_tree, e_tree) + f_tree: Source tree for the best hypothesis in the hypergraph. + e_tree: Target tree for the best hypothesis in the hypergraph. + """ f_tree = unicode(hypergraph.ViterbiFTree(self.hg[0]).c_str(), 'utf8') e_tree = unicode(hypergraph.ViterbiETree(self.hg[0]).c_str(), 'utf8') return (f_tree, e_tree) def viterbi_features(self): + """hg.viterbi_features() -> SparseVector with the features corresponding + to the best derivation in the hypergraph.""" cdef SparseVector fmap = SparseVector.__new__(SparseVector) fmap.vector = new FastSparseVector[weight_t](hypergraph.ViterbiFeatures(self.hg[0])) return fmap def viterbi_joshua(self): + """hg.viterbi_joshua() -> Joshua representation of the best derivation.""" return unicode(hypergraph.JoshuaVisualizationString(self.hg[0]).c_str(), 'utf8') def kbest(self, size): + """hg.kbest(size) -> List of k-best hypotheses in the hypergraph.""" cdef kbest.KBestDerivations[vector[WordID], kbest.ESentenceTraversal]* derivations = new kbest.KBestDerivations[vector[WordID], kbest.ESentenceTraversal](self.hg[0], size) cdef kbest.KBestDerivations[vector[WordID], kbest.ESentenceTraversal].Derivation* derivation cdef unsigned k @@ -41,6 +55,7 @@ cdef class Hypergraph: del derivations def kbest_trees(self, size): + """hg.kbest_trees(size) -> List of k-best trees in the hypergraph.""" cdef kbest.KBestDerivations[vector[WordID], kbest.FTreeTraversal]* f_derivations = new kbest.KBestDerivations[vector[WordID], kbest.FTreeTraversal](self.hg[0], size) cdef kbest.KBestDerivations[vector[WordID], kbest.FTreeTraversal].Derivation* f_derivation cdef kbest.KBestDerivations[vector[WordID], kbest.ETreeTraversal]* e_derivations = new kbest.KBestDerivations[vector[WordID], kbest.ETreeTraversal](self.hg[0], size) @@ -59,6 +74,7 @@ cdef class Hypergraph: del e_derivations def kbest_features(self, size): + """hg.kbest_trees(size) -> List of k-best feature vectors in the hypergraph.""" cdef kbest.KBestDerivations[FastSparseVector[weight_t], kbest.FeatureVectorTraversal]* derivations = new kbest.KBestDerivations[FastSparseVector[weight_t], kbest.FeatureVectorTraversal](self.hg[0], size) cdef kbest.KBestDerivations[FastSparseVector[weight_t], kbest.FeatureVectorTraversal].Derivation* derivation cdef SparseVector fmap @@ -74,10 +90,9 @@ cdef class Hypergraph: del derivations def sample(self, unsigned n): + """hg.sample(n) -> Sample of n hypotheses from the hypergraph.""" cdef vector[hypergraph.Hypothesis]* hypos = new vector[hypergraph.Hypothesis]() - if self.rng == NULL: - self.rng = new MT19937() - hypergraph.sample_hypotheses(self.hg[0], n, self.rng, hypos) + hypergraph.sample_hypotheses(self.hg[0], n, self._rng(), hypos) cdef unsigned k try: for k in range(hypos.size()): @@ -85,10 +100,32 @@ cdef class Hypergraph: finally: del hypos - def intersect(self, Lattice lat): + def sample_trees(self, unsigned n): + """hg.sample_trees(n) -> Sample of n trees from the hypergraph.""" + cdef vector[string]* trees = new vector[string]() + hypergraph.sample_trees(self.hg[0], n, self._rng(), trees) + cdef unsigned k + try: + for k in range(trees.size()): + yield unicode(trees[0][k].c_str(), 'utf8') + finally: + del trees + + def intersect(self, inp): + """hg.intersect(Lattice/string): Intersect the hypergraph with the provided reference.""" + cdef Lattice lat + if isinstance(inp, Lattice): + lat = <Lattice> inp + elif isinstance(inp, basestring): + lat = Lattice(inp) + else: + raise TypeError('cannot intersect hypergraph with %s' % type(inp)) return hypergraph.Intersect(lat.lattice[0], self.hg) def prune(self, beam_alpha=0, density=0, **kwargs): + """hg.prune(beam_alpha=0, density=0): Prune the hypergraph. + beam_alpha: use beam pruning + density: use density pruning""" cdef hypergraph.EdgeMask* preserve_mask = NULL if 'csplit_preserve_full_word' in kwargs: preserve_mask = new hypergraph.EdgeMask(self.hg.edges_.size()) @@ -98,10 +135,16 @@ cdef class Hypergraph: del preserve_mask def lattice(self): # TODO direct hg -> lattice conversion in cdec - cdef str plf = hypergraph.AsPLF(self.hg[0], True).c_str() + """hg.lattice() -> Lattice corresponding to the hypergraph.""" + cdef bytes plf = hypergraph.AsPLF(self.hg[0], True).c_str() return Lattice(eval(plf)) + def plf(self): + """hg.plf() -> Lattice PLF representation corresponding to the hypergraph.""" + return bytes(hypergraph.AsPLF(self.hg[0], True).c_str()) + def reweight(self, weights): + """hg.reweight(SparseVector/DenseVector): Reweight the hypergraph with a new vector.""" if isinstance(weights, SparseVector): self.hg.Reweight((<SparseVector> weights).vector[0]) elif isinstance(weights, DenseVector): @@ -130,6 +173,7 @@ cdef class Hypergraph: return self.hg.NumberOfPaths() def inside_outside(self): + """hg.inside_outside() -> SparseVector with inside-outside scores for each feature.""" cdef FastSparseVector[prob_t]* result = new FastSparseVector[prob_t]() cdef prob_t z = hypergraph.InsideOutside(self.hg[0], result) result[0] /= z @@ -218,7 +262,7 @@ cdef class HypergraphNode: property cat: def __get__(self): if self.node.cat_: - return TDConvert(-self.node.cat_) + return str(TDConvert(-self.node.cat_).c_str()) def __richcmp__(HypergraphNode x, HypergraphNode y, int op): if op == 2: # == |