def __init__(self, value=None):
if value is None:
value = numpy.array([0.0, 0.0])
VectorHypothesis.__init__(self,
value=value,
n=2,
proposal=numpy.eye(2) * 0.1)
def __init__(
self,
grammar,
hypotheses,
rules=None,
load=None,
value=None,
proposal=None,
prior_shape=2.0,
prior_scale=1.0,
propose_n=1,
propose_step=0.1,
**kwargs
):
self.grammar = grammar
if load:
self.hypotheses = self.load_hypotheses(load)
else:
self.hypotheses = hypotheses
self.rules = [r for sublist in grammar.rules.values() for r in sublist]
if value is None:
value = [rule.p for rule in self.rules]
self.n = len(value)
self.propose_idxs = self.get_propose_idxs()
if proposal is None:
proposal = np.eye(len(self.propose_idxs))
VectorHypothesis.__init__(self, value=value, n=self.n, proposal=proposal)
self.prior_shape = prior_shape
self.prior_scale = prior_scale
self.propose_n = propose_n
self.propose_step = propose_step
# self.compute_prior()
self.update()
def __init__(self, grammar, hypotheses, rules=None, load=None, value=None,
prior_shape=2., prior_scale=1., propose_n=1, propose_step=.1,
**kwargs):
self.grammar = grammar
self.hypotheses = self.load_hypotheses(load) if load else hypotheses
self.rules = [r for sublist in grammar.rules.values() for r in sublist]
if value is None:
value = [rule.p for rule in self.rules]
self.n = len(value)
VectorHypothesis.__init__(self, value=value, n=self.n, **kwargs)
self.prior_shape = prior_shape
self.prior_scale = prior_scale
if int(self.n / 50) > propose_n:
propose_n = int(self.n / 50)
self.propose_n = propose_n
self.propose_step = propose_step
self.propose_idxs = self.get_propose_idxs()
self.compute_prior()
self.update()
def __init__(self, value=None):
if value is None: value = numpy.array([0.0, 0.0])
VectorHypothesis.__init__(self, value=value, N=2, proposal=numpy.eye(2)*0.1)
