def lpdf(rv, sample, **kwargs):
"""
Return the probability (density) that random variable `rv`, returned by
a call to one of the sampling routines of this class takes value `sample`
"""
if not is_rv(rv):
raise TypeError('rv not recognized as a random variable', rv)
if is_raw_rv(rv):
dist_name = rstreams.rv_dist_name(rv)
pdf = rstreams.pdfs[dist_name]
return pdf(rv.owner, sample, kwargs)
else:
#TODO: infer from the ancestors of v what distribution it
# has.
raise NotImplementedError(rv)
def normal_get_sigma(v):
# look in uniform_sampler to see the positions of these things
if v.owner and rv_dist_name(v) == "normal":
return v.owner.inputs[3]
raise TypeError
def uniform_get_high(v):
# look in uniform_sampler to see the positions of these things
if v.owner and rv_dist_name(v) == "uniform":
return v.owner.inputs[3]
raise TypeError
def qlognormal_get_round(v):
# look in uniform_sampler to see the positions of these things
if v.owner and rv_dist_name(v) == "quantized_lognormal":
return v.owner.inputs[4]
raise TypeError
def normal_get_sigma(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == "normal":
return v.owner.inputs[3]
raise ValueError("v is not a normal draw", v)
def uniform_get_high(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == "uniform":
return v.owner.inputs[3]
raise ValueError("v is not a uniform draw", v)
def quantized_lognormal_get_round(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == "quantized_lognormal":
return v.owner.inputs[4]
raise ValueError("v is not a quantized_lognormal draw", v)
def quantized_lognormal_get_sigma(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'quantized_lognormal':
return v.owner.inputs[3]
raise ValueError('v is not a quantized_lognormal draw', v)
def lognormal_get_mu(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'lognormal':
return v.owner.inputs[2]
raise ValueError('v is not a lognormal draw', v)
def uniform_get_low(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'uniform':
return v.owner.inputs[2]
raise ValueError('v is not a uniform draw', v)
def quantized_lognormal_get_round(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'quantized_lognormal':
return v.owner.inputs[4]
raise ValueError('v is not a quantized_lognormal draw', v)
def lognormal_get_sigma(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'lognormal':
return v.owner.inputs[3]
raise ValueError('v is not a lognormal draw', v)
def uniform_get_high(v):
# look in uniform_sampler to see the positions of these things
if rv_dist_name(v) == 'uniform':
return v.owner.inputs[3]
raise ValueError('v is not a uniform draw', v)