def realign(self, x, dx, y, dy):
if 'viterbi_path' not in self.io_files['input']:
path = self.model.getViterbiPath(self.table)
if 'viterbi_path' in self.io_files['output']:
with Open(self.io_files['output']['viterbi_path.js'], 'w') as f:
json.dump(jsonize(path), f, indent=4)
else:
path = dejsonize_struct(
json.load(Open(self.io_files['input']['viterbi_path'])),
(
list,
(
tuple,
int,
(tuple, int),
(tuple, int),
lambda x: LogNum(x, False))))
X = ""
Y = ""
A = ""
for (state, (_x, _y), (_dx, _dy), _) in path:
X += self.X[_x - _dx:_x] + ('-' * (max(_dx, _dy) - _dx))
Y += self.Y[_y - _dy:_y] + ('-' * (max(_dx, _dy) - _dy))
A += self.model.states[state].getChar() * max(_dx, _dy)
return [(self.X_name, X), ("viterbi annotation of " + self.X_name +
" and " + self.Y_name, A),
(self.Y_name, Y)]
def realign(self, x, dx, y, dy):
if 'viterbi_path' not in self.io_files['input']:
path = self.model.getViterbiPath(self.table)
if 'viterbi_path' in self.io_files['output']:
with Open(self.io_files['output']['viterbi_path.js'],
'w') as f:
json.dump(jsonize(path), f, indent=4)
else:
path = dejsonize_struct(
json.load(Open(self.io_files['input']['viterbi_path'])),
(list, (tuple, int, (tuple, int),
(tuple, int), lambda x: LogNum(x, False))))
X = ""
Y = ""
A = ""
for (state, (_x, _y), (_dx, _dy), _) in path:
X += self.X[_x - _dx:_x] + ('-' * (max(_dx, _dy) - _dx))
Y += self.Y[_y - _dy:_y] + ('-' * (max(_dx, _dy) - _dy))
A += self.model.states[state].getChar() * max(_dx, _dy)
return [
(self.X_name, X),
("viterbi annotation of " + self.X_name + " and " + self.Y_name,
A), (self.Y_name, Y)
]
def computeViterbiTable(self):
if 'viterbi' not in self.io_files['input']:
for state in self.model.states:
if isinstance(state, ClassifierState):
emission_table = SequenceTablePrecompute(
state.clf, self.positionGenerator, self.X, self.Y, state.ann_x, state.ann_y
)
emission_table.compute()
state.set_emission_table(emission_table)
self.table = self.model.getViterbiTable(
self.X, 0, len(self.X),
self.Y, 0, len(self.Y),
positionGenerator=self.positionGenerator
)
x = jsonize(self.table)
if 'viterbi' in self.io_files['output']:
with Open(self.io_files['output']['viterbi'], 'w') as f:
json.dump(x, f, indent=4)
else:
self.table = dejsonize_struct(
json.load(Open(self.io_files['input']['viterbi'])),
(
list,
(
dict,
int,
(
dict,
(tuple, int),
(
tuple,
lambda x: LogNum(x, False),
int)))))
def computeViterbiTable(self):
if 'viterbi' not in self.io_files['input']:
for state in self.model.states:
if isinstance(state, ClassifierState):
emission_table = SequenceTablePrecompute(
state.clf, self.positionGenerator, self.X, self.Y,
state.ann_x, state.ann_y)
emission_table.compute()
state.set_emission_table(emission_table)
self.table = self.model.getViterbiTable(
self.X,
0,
len(self.X),
self.Y,
0,
len(self.Y),
positionGenerator=self.positionGenerator)
x = jsonize(self.table)
if 'viterbi' in self.io_files['output']:
with Open(self.io_files['output']['viterbi'], 'w') as f:
json.dump(x, f, indent=4)
else:
self.table = dejsonize_struct(
json.load(Open(self.io_files['input']['viterbi'])),
(list, (dict, int,
(dict, (tuple, int),
(tuple, lambda x: LogNum(x, False), int)))))
