def test_reference(self):
true, data = self.generate_data()
model = DPMixtureModel(3, 100, 100, 1)
model.seed = 1
model.load_ref(array(true))
r = model.fit(data, verbose=True)
diffs = {}
for i in gen_mean:
diffs[i] = np.abs(r.mus[i]-gen_mean[i])
assert(np.vdot(diffs[i], diffs[i]) < 1)
model.load_ref(r)
r = model.fit(data, verbose=True)
diffs = {}
for i in gen_mean:
diffs[i] = np.abs(r.mus[i]-gen_mean[i])
assert(np.vdot(diffs[i], diffs[i]) < 1)
def testRefernce(self):
print "starting mcmc"
true, data = self.generate_data()
m = data.mean(0)
s = data.std(0)
# true_mean = {}
# for i in gen_mean:
# true_mean[i] = (gen_mean[i]-m)/s
model = DPMixtureModel(3, 100, 100, 1)
model.seed = 1
model.load_ref(array(true))
start = time()
r = model.fit(data, verbose=True)
end = time() - start
diffs = {}
# print 'r.mus:', r.mus
for i in gen_mean:
# diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
diffs[i] = np.abs(r.mus[i] - gen_mean[i])
# print i, gen_mean[i],r.mus[i], diffs[i],
# np.vdot(diffs[i],diffs[i])
assert np.vdot(diffs[i], diffs[i]) < 1
# print diffs
print "MCMC fitting took %0.3f" % (end)
model.load_ref(r)
start = time()
r = model.fit(data, verbose=True)
end = time() - start
diffs = {}
# print 'r.mus:', r.mus
for i in gen_mean:
# diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
diffs[i] = np.abs(r.mus[i] - gen_mean[i])
# print i, gen_mean[i],r.mus[i], diffs[i],
# np.vdot(diffs[i],diffs[i])
assert np.vdot(diffs[i], diffs[i]) < 1
def testRefernce(self):
print "starting mcmc"
true, data = self.generate_data()
m = data.mean(0)
s = data.std(0)
# true_mean = {}
# for i in gen_mean:
# true_mean[i] = (gen_mean[i]-m)/s
model = DPMixtureModel(3,100,100,1)
model.seed = 1
model.load_ref(array(true))
start = time()
r = model.fit(data, verbose=True)
end = time() - start
diffs = {}
#print 'r.mus:', r.mus
for i in gen_mean:
#diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
diffs[i] = np.abs(r.mus[i]-gen_mean[i])
#print i, gen_mean[i],r.mus[i], diffs[i], np.vdot(diffs[i],diffs[i])
assert( np.vdot(diffs[i],diffs[i]) < 1)
#print diffs
print 'MCMC fitting took %0.3f' % (end)
model.load_ref(r)
start = time()
r = model.fit(data, verbose=True)
end = time() - start
diffs = {}
#print 'r.mus:', r.mus
for i in gen_mean:
#diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
diffs[i] = np.abs(r.mus[i]-gen_mean[i])
#print i, gen_mean[i],r.mus[i], diffs[i], np.vdot(diffs[i],diffs[i])
assert( np.vdot(diffs[i],diffs[i]) < 1)
