Commit d0fc4754 authored by Tiago Peixoto's avatar Tiago Peixoto
Browse files

test_inference_mcmc: Simplify statistics

parent 9566e946
Pipeline #206 failed with stage
in 4651 minutes and 40 seconds
......@@ -116,7 +116,7 @@ for directed in [True, False]:
for i, c in enumerate(cs):
if c != "gibbs":
mcmc_args=dict(beta=1, c=c, niter=20 if c != numpy.inf else 200)
mcmc_args=dict(beta=1, c=c, niter=20)
else:
mcmc_args=dict(beta=1, niter=20)
if i == 0:
......@@ -129,8 +129,8 @@ for directed in [True, False]:
hists[c] = mcmc_equilibrate(state,
mcmc_args=mcmc_args,
gibbs=c=="gibbs",
wait=10000,
nbreaks=40,
wait=4000,
nbreaks=5,
verbose=(1, "c = %s " % str(c)) if verbose else False,
history=True)
......@@ -143,14 +143,15 @@ for directed in [True, False]:
pass
Ss1 = array(list(zip(*hists[c1]))[0])
Ss2 = array(list(zip(*hists[c2]))[0])
# add very small normal noise, to solve discreetness issue
# add very small normal noise, to solve discreteness issue
Ss1 += numpy.random.normal(0, 1e-6, len(Ss1))
Ss2 += numpy.random.normal(0, 1e-6, len(Ss2))
D, p = scipy.stats.ks_2samp(Ss1, Ss2)
D_c = 1.63 * sqrt((len(Ss1) + len(Ss2)) / (len(Ss1) * len(Ss2)))
if verbose:
print("directed:", directed, "c1:", c1, "c2:", c2,
"D", D, "p-value:", p)
if p < .001:
"D:", D, "D_c:", D_c, "p-value:", p)
if p < .01:
print(("Warning, distributions for directed=%s (c1, c2) = " +
"(%s, %s) are not the same, with a p-value: %g (D=%g)") %
(str(directed), str(c1), str(c2), p, D))
......
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