def plot_discrete_distribution(distro, **options):
test_obj_subclass(distro, DictWrapper)
xs, ps = distro.sort_zip()
options = add_options_to_plot(options, label=distro.name)
plot(xs, ps, **options)
def __mod__(self, other):
test_obj_subclass(other, (DictWrapper))
d = copy.deepcopy(self.d)
for key, value in other:
if value == 0.0:
d[key] = 0.0
else:
d[key] %= value
return DictWrapper(d, self.name)
def __init__(self, prior, sample, likelihood):
test_obj_instance(prior, Pmf)
test_obj_instance(sample, list)
test_obj_subclass(likelihood, Likelihood)
self.prior = prior
self.sample = sample
self.likelihood = likelihood
self.posterior = deepcopy(prior)
self.posterior.name = 'posterior'
self._estimate_posterior()
def __init__(self, prior, sample, likelihood):
test_obj_instance(prior, Pmf)
test_obj_instance(sample, list)
test_obj_subclass(likelihood, Likelihood)
self.prior = prior
self.sample = sample
self.likelihood = likelihood
self.posterior = deepcopy(prior)
self.posterior.name = 'posterior'
self._estimate_posterior()
def is_subset(self, other):
test_obj_subclass(other, (DictWrapper))
if len(other) < len(self):
return False
if (not min(other.get_keys()) <= min(self.get_keys())) and (not max(self.get_keys()) <= max(min(other.get_keys()))):
return False
for val, freq in self.d.iteritems():
if other[val] == None:
continue
if freq > other[val]:
return False
return True
def plot_histogram(distro, **options):
test_obj_subclass(distro, DictWrapper)
xs, fs = distro.sort_zip()
width = min(differences_adj_elements(xs))
options = add_options_to_plot(options,
label=distro.name,
align='center',
edgecolor='blue',
width=width)
pyplot.bar(xs, fs, **options)
def __mul__(self, other):
test_obj_subclass(other, (DictWrapper))
d = copy.deepcopy(self.d)
for key, value in other:
d[key] *= value
return DictWrapper(d, self.name)
def __ge__(self, other):
test_obj_subclass(other, (DictWrapper))
return (self.d >= other.d)
def __cmp__(self, other):
test_obj_subclass(other, (DictWrapper))
return cmp(self.d, other.d)
def __init__(self, X, Y):
self.X = X
self.Y = Y
test_obj_subclass(self.X, RandomVariable)
test_obj_subclass(self.Y, RandomVariable)