Python best_constrained_pathの例

コード例 #1

ファイル: hypergraph_tests.py プロジェクト: pombredanne/PyDecode

def test_subgradient():
    for h in hypergraphs():
        w = utils.random_log_viterbi_potentials(h)
        constraints, edge = random_have_constraint(h)
        path = ph.best_path(h, w)
        match = constraints.check(path)
        if edge not in path:
            nt.assert_equal(match[0], "have")

        cpath = opt.best_constrained_path(h, w,
                                          constraints)
        assert edge in cpath

コード例 #2

ファイル: decipher.py プロジェクト: pombredanne/PyDecode

# 

# In[55]:

path = hyper.best_path(hyper1, potentials)
potentials.dot(path)


# Out[55]:

#     3.458035945892334

# In[56]:

import pydecode.optimization as opt
cpath = opt.best_constrained_path(hyper1, potentials, constraints)


# In[57]:

CipherFormat(hyper1, [cpath]).to_ipython()


# Out[57]:

#     <IPython.core.display.Image at 0x5381090>

# In[58]:

print potentials.dot(cpath)
constraints.check(cpath)

コード例 #3

ファイル: hmm.py プロジェクト: pombredanne/PyDecode

constraints =     cons.Constraints(hypergraph, [(cons_name(tag), 0) for tag in ["D", "V", "N"]]).build( 
                   build_constraints)


# This check fails because the tags do not agree.

# In[ ]:

print "check", constraints.check(path)


# Solve instead using subgradient.

# In[ ]:

gpath = opt.best_constrained_path(hypergraph, potentials, constraints)


# In[ ]:

import pydecode.lp as lp
hypergraph_lp = lp.HypergraphLP.make_lp(hypergraph, potentials)
hypergraph_lp.solve()
path = hypergraph_lp.path


# In[ ]:

# Output the path.
for edge in gpath.edges:
    print hypergraph.label(edge)