def checkAAAParticleWeights(sp, seed):
if inParallel() and "make_suff_stat_bernoulli" in sp and backend_name(
) == "puma":
raise SkipTest(
"The Lite SPs in Puma interface is not thread-safe, and make_suff_stat_bernoulli comes from Lite."
)
if "dir_cat" in sp and backend_name() == 'puma':
raise SkipTest(
"Dirichlet categorical in Puma does not accept objects parameter. Issue #340"
)
ripl = get_ripl(seed=seed)
ripl.assume("a", "1.0")
# bogus labelled directives, so the infer step can forget them
ripl.predict("nil", label="f")
ripl.predict("nil", label="pid")
predictions = collectSamples(ripl,
"pid",
infer="""\
(do (resample 10)
(forget 'pid)
(forget 'f)
(assume f %s f)
(predict (f) pid)
(observe (f) true obs1)
(observe (f) true obs2)
(resample 1)
(forget 'obs2)
(forget 'obs1))""" % sp)
ans = [(False, .25), (True, .75)]
return reportKnownDiscrete(ans, predictions)
def testInvWishartPrior4(seed):
# Confirm that as dof increases, the elements of a Wishart obey the
# central limit theorem.
if inParallel() and backend_name() == "puma":
raise SkipTest("The Lite SPs in Puma interface is not thread-safe, and wishart comes from Lite.")
ripl = get_ripl(seed=seed)
ripl.assume("s", "(scale_matrix 10000 (id_matrix 3))")
ripl.assume("m", "(inv_wishart s 10000)")
ripl.predict("(lookup m (pair 0 1))", label="prediction")
predictions = collectSamples(ripl, "prediction")
return reportKnownGaussian(0, 0.01, predictions)
def testInvWishartPrior2(seed):
# Confirm that the diagonal elements of an inverse Wishart are an
# inverse Gamma distribution.
if inParallel() and backend_name() == "puma":
raise SkipTest("The Lite SPs in Puma interface is not thread-safe, and wishart comes from Lite.")
ripl = get_ripl(seed=seed)
ripl.assume("s", "(matrix (array (array 2 -1) (array -1 3)))")
ripl.assume("m", "(inv_wishart s 4.2)")
ripl.predict("(lookup m (pair 1 1))", label="prediction")
predictions = collectSamples(ripl, "prediction")
cdf = scipy.stats.invgamma(a=1.6, scale=1.5).cdf
return reportKnownContinuous(cdf, predictions)
def testWishartPrior1(seed):
# Confirm that the diagonal elements of a Wishart are a chi-squared
# distribution.
if inParallel() and backend_name() == "puma":
raise SkipTest("The Lite SPs in Puma interface is not thread-safe, and wishart comes from Lite.")
ripl = get_ripl(seed=seed)
ripl.assume("s", "(matrix (array (array 2 -1) (array -1 3)))")
ripl.assume("m", "(wishart s 5)")
ripl.predict("(lookup m (pair 0 0))", label="prediction")
predictions = collectSamples(ripl, "prediction")
cdf = scipy.stats.chi2(df=5, scale=2).cdf
return reportKnownContinuous(cdf, predictions)
def checkMakeBetaBernoulli1(maker, hyper, seed):
if rejectionSampling() and hyper == "(normal 10.0 1.0)":
raise SkipTest(
"Too slow. Tightening the rejection bound is Issue #468.")
if inParallel() and "make_suff_stat_bernoulli" in maker and backend_name(
) == "puma":
raise SkipTest(
"The Lite SPs in Puma interface is not thread-safe, and make_suff_stat_bernoulli comes from Lite."
)
ripl = get_ripl(seed=seed)
ripl.assume("a", hyper)
ripl.assume("f", "(%s a a)" % maker)
ripl.predict("(f)", label="pid")
for _ in range(20):
ripl.observe("(f)", "true")
predictions = collectSamples(ripl, "pid")
ans = [(False, .25), (True, .75)]
return reportKnownDiscrete(ans, predictions)
def checkMakeBetaBernoulli4(maker, seed):
if inParallel() and "make_suff_stat_bernoulli" in maker and backend_name(
) == "puma":
raise SkipTest(
"The Lite SPs in Puma interface is not thread-safe, and make_suff_stat_bernoulli comes from Lite."
)
ripl = get_ripl(seed=seed)
ripl.assume("a", "(normal 10.0 1.0)")
ripl.assume("f", """
(if (lt a 10.0)
({0} a a)
({0} a a))""".format(maker))
ripl.predict("(f)", label="pid")
for _ in range(20):
ripl.observe("(f)", "true")
predictions = collectSamples(ripl, "pid")
ans = [(False, .25), (True, .75)]
return reportKnownDiscrete(ans, predictions)