def test_mm():
np.random.seed(0)
import distributions
N = 100
data = np.zeros(N, dtype=np.float32)
MODEL = distributions.conjugate.nich
data[::2] = -1
data[1::2] = 1
f = mixmodel.Feature(data, MODEL)
f.hps = MODEL.HP(0.0, 1.0, 1.0, 1.0)
mm = mixmodel.MixtureModel(N, {'f1' : f})
rng = None
# random init
grp = {}
for i, g in enumerate(np.random.permutation(np.arange(N) % 10)):
if g not in grp:
grp[g] = mm.create_group(rng)
mm.add_entity_to_group(grp[g], i)
print mm.score()
for i in range(10):
gibbs.gibbs_sample(mm, rng)
print mm.score()
assert_equal(irm.util.count(mm.get_assignments()).values(), [50, 50])
def test_mm():
np.random.seed(0)
import distributions
N = 100
data = np.zeros(N, dtype=np.float32)
MODEL = distributions.conjugate.nich
data[::2] = -1
data[1::2] = 1
f = mixmodel.Feature(data, MODEL)
f.hps = MODEL.HP(0.0, 1.0, 1.0, 1.0)
mm = mixmodel.MixtureModel(N, {'f1': f})
rng = None
# random init
grp = {}
for i, g in enumerate(np.random.permutation(np.arange(N) % 10)):
if g not in grp:
grp[g] = mm.create_group(rng)
mm.add_entity_to_group(grp[g], i)
print mm.score()
for i in range(10):
gibbs.gibbs_sample(mm, rng)
print mm.score()
assert_equal(irm.util.count(mm.get_assignments()).values(), [50, 50])
def test_format(self):
fr = FR(factors)
sample = gibbs_sample(fr, 100, 0)
self.assertEqual(type(sample), type(('foo', 'barr')))
self.assertEqual(len(sample), 100)
for s in sample:
self.assertEqual(len(s), 100)
for x in s:
self.assertEqual(x in [0, 1], True)
def test_format(self):
fr = FR(factors)
sample = gibbs_sample(fr,100,0)
self.assertEqual(type(sample),type(('foo','barr')))
self.assertEqual(len(sample),100)
for s in sample:
self.assertEqual(len(s),100)
for x in s:
self.assertEqual(x in [0,1],True)
from gPy.Variables import declare_variable
from gPy.Parameters import Factor
from gibbs import gibbs_sample
from gPy.Models import FR
for i in range(10):
for j in range(10):
declare_variable((i,j),binvals)
x=1
y=5
data = [
x, # 0,0
y, # 0,1
y, # 1,0
x # 1,1
]
factors = []
for i in range(10):
for j in range(10):
factors.append(Factor(((i,j),((i+1)%10,j)),data))
factors.append(Factor(((i,j),(i,(j+1)%10)),data))
fr = FR(factors)
sample = gibbs_sample(fr,100,0)
cPickle.dump(sample,open(sys.argv[1],'w'))
binvals = (0, 1)
from gPy.Variables import declare_variable
from gPy.Parameters import Factor
from gibbs import gibbs_sample
from gPy.Models import FR
for i in range(10):
for j in range(10):
declare_variable((i, j), binvals)
x = 1
y = 5
data = [
x, # 0,0
y, # 0,1
y, # 1,0
x # 1,1
]
factors = []
for i in range(10):
for j in range(10):
factors.append(Factor(((i, j), ((i + 1) % 10, j)), data))
factors.append(Factor(((i, j), (i, (j + 1) % 10)), data))
fr = FR(factors)
sample = gibbs_sample(fr, 100, 0)
cPickle.dump(sample, open(sys.argv[1], 'w'))
