def __init__(self, **kwargs):
LOTHypothesis.__init__(self,
grammar=grammar,
maxnodes=400,
display='lambda from_seq: %s',
**kwargs)
def __init__(self,
grammar=None,
display="lambda C, lex_, x: %s",
**kwargs): # lexicon, x arg, context
LOTHypothesis.__init__(self,
grammar=grammar,
display=display,
**kwargs)
def __init__(self, **kwargs):
self.start_counts = {}
LOTHypothesis.__init__(self,
grammar=grammar,
maxnodes=400,
display='lambda : %s',
**kwargs)
def __init__(self, constant_sd=1.0, fit_only_once=True, **kwargs):
"""
:param constant_sd: The SD of our constants in the prior
:param fit_only_once: Do we fit multiple times or just take the first?
"""
LOTHypothesis.__init__(self, grammar, display='lambda x,'+','.join(CONSTANT_NAMES)+": %s", **kwargs)
self.constant_sd=constant_sd # also the prior SD
self.parameters = self.sample_constants()
self.fit_only_once = fit_only_once
def __init__(self,
grammar,
value=None,
f=None,
proposal_function=None,
**kwargs):
LOTHypothesis.__init__(self,
grammar,
proposal_function=proposal_function,
**kwargs)
if value is None: self.set_value(grammar.generate('WORD'), f)
else: self.set_value(value, f)
def __init__(self, **kwargs):
LOTHypothesis.__init__(self,
grammar=grammar,
maxnodes=400,
display="lambda C: %s",
**kwargs)
if 'sp' in kwargs:
self.use_size_principle = kwargs['sp']
else:
self.use_size_principle = False
def __init__(self, constant_sd=1.0, fit_only_once=True, **kwargs):
"""
:param constant_sd: The SD of our constants in the prior
:param fit_only_once: Do we fit multiple times or just take the first?
"""
LOTHypothesis.__init__(self,
grammar,
display='lambda x,' + ','.join(CONSTANT_NAMES) +
": %s",
**kwargs)
self.constant_sd = constant_sd # also the prior SD
self.parameters = self.sample_constants()
self.fit_only_once = fit_only_once
def __init__(self, grammar=None, **kwargs):
LOTHypothesis.__init__(self, grammar, display='lambda : %s', **kwargs)
def __init__(self, grammar=grammar, **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, args=["x"], **kwargs)
def __init__(self, grammar=None, display="lambda C, lex_, x: %s", **kwargs): # lexicon, x arg, context
LOTHypothesis.__init__(self, grammar=grammar, display=display, **kwargs)
def __init__(self, **kwargs):
LOTHypothesis.__init__(self, grammar, **kwargs)
def __init__(self, constant_sd=1.0, **kwargs):
LOTHypothesis.__init__(self, grammar, args=['x']+CONSTANT_NAMES, **kwargs)
self.CONSTANT_VALUES = numpy.zeros(NCONSTANTS)
self.constant_sd=constant_sd
def __init__(self, *args, **kwargs):
LOTHypothesis.__init__(self,
grammar,
display='lambda x,y: %s',
**kwargs)
super(CRHypothesis, self).__init__(*args, **kwargs)
def __init__(self, grammar=grammar, **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, display="lambda x : %s", maxnodes=150, **kwargs)
def __init__(self, grammar=None, display="lambda recurse_: %s", **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, display=display, **kwargs)
def __init__(self, ALPHA=0.9, **kwargs):
LOTHypothesis.__init__(self, grammar, **kwargs)
self.ALPHA = ALPHA
def __init__(self, grammar, value=None, alpha=0.9, domain=100, **kwargs):
LOTHypothesis.__init__(self, grammar, value=value, args=[], **kwargs)
self.grammar = grammar
self.alpha = alpha
self.domain = domain
self.value_set = None
def __init__(self, grammar, domain=100, noise=0.9, args=['n'], **kwargs):
LOTHypothesis.__init__(self, grammar, args=args, **kwargs)
self.domain = domain
self.noise = noise
def __init__(self, value=None, alpha=0.99, baserate=0.5):
LOTHypothesis.__init__(self, grammar, value=value, display='lambda S, x: %s', alpha=alpha, baserate=baserate)
def __init__(self, value=None, alpha=0.99, baserate=0.5):
LOTHypothesis.__init__(self, grammar, value=value, args=['S', 'x'], alpha=alpha, baserate=baserate)
def __init__(self, grammar=grammar, **kwargs):
LOTHypothesis.__init__(self, grammar, display='lambda C : %s', maxnodes=200, **kwargs)
# self.outlier = -100 # for MultinomialLikelihoodLog
self.alphabet_size = len(TERMINALS)
def __init__(self, **kwargs):
LOTHypothesis.__init__(self, grammar, display="lambda x,y: %s", **kwargs)
def __init__(self, grammar, alpha=0.9, domain=100, **kwargs):
LOTHypothesis.__init__(self, grammar, args=[], **kwargs)
self.alpha = alpha
self.domain = domain
def __init__(self, grammar=None, **kwargs):
LOTHypothesis.__init__(self, grammar, display="lambda : %s", **kwargs)
self.outlier = -1000 # for MultinomialLikelihood
def __init__(self, grammar=None, value=None, domain=100, **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, value=value, display="lambda : %s", **kwargs)
self.domain = domain
def __init__(self, **kwargs):
LOTHypothesis.__init__(self, grammar, **kwargs)
def __init__(self, grammar=None, **kwargs):
LOTHypothesis.__init__(self, grammar, args=[''], **kwargs)
def __init__(self, *args, **kwargs ):
LOTHypothesis.__init__(self, grammar, display='lambda x,y: %s', **kwargs)
super(CRHypothesis, self).__init__(*args, **kwargs)
def __init__(self, grammar, value=None, f=None, proposal_function=None, **kwargs):
LOTHypothesis.__init__(self,grammar,proposal_function=proposal_function, **kwargs)
if value is None: self.set_value(grammar.generate('WORD'), f)
else: self.set_value(value, f)
def __init__(self, grammar=None, value=None, domain=100, **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, value=value, args=[], **kwargs)
self.domain = domain
def __init__(self, grammar, value=None, alpha=0.9, domain=100, **kwargs):
LOTHypothesis.__init__(self, grammar, value=value, args=[], **kwargs)
self.alpha = alpha
self.domain = domain
self.value_set = None
def __init__(self, **kwargs ):
LOTHypothesis.__init__(self, grammar, args=['x', 'y'], **kwargs)
def __init__(self, **kwargs):
LOTHypothesis.__init__(self,
grammar=grammar,
display="lambda x: %s",
**kwargs)
def __init__(self, grammar=grammar, **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, args=['x'], **kwargs)
def __init__(self, grammar=None, **kwargs):
LOTHypothesis.__init__(self, grammar, display='lambda : %s', **kwargs)
self.outlier = -1000 # for MultinomialLikelihood
def __init__(self, value=None, base_facts="", **kwargs):
self.base_facts = base_facts # must be set before initializer
LOTHypothesis.__init__(self, grammar, value=value, args=None, **kwargs)
def __init__(self, grammar=None, display="lambda recurse_: %s", **kwargs):
LOTHypothesis.__init__(self, grammar=grammar, display=display, **kwargs)
def __init__(self, grammar=None, **kwargs):
LOTHypothesis.__init__(self, grammar, display='lambda : %s', **kwargs)
def __init__(self, **kwargs):
LOTHypothesis.__init__(self,
grammar=grammar,
display='''def algo(x): \n%s\n return x''',
**kwargs)
