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)