def test_further(self):
np.set_printoptions(suppress=True, precision=6)
# X = np.linspace(0, 1, 4, dtype=float)[:, None]
X = np.array([0.1, 0.2, 0.3, 0.4])[:, None]
BP_tf = tf.placeholder(dtype=float_type, shape=[])
eZ0_tf = tf.placeholder(dtype=float_type, shape=(X.shape[0], X.shape[0]*3))
pZ0 = np.array([[0.7, 0.3], [0.1, 0.9], [0.5, 0.5], [0.85, 0.15]])
eZ0 = pZ_construction_singleBP.expand_pZ0(pZ0)
BP = 0.2
pZ = tf.Session().run(pZ_construction_singleBP.make_matrix(X, BP_tf, eZ0_tf), feed_dict={BP_tf: BP, eZ0_tf: eZ0})
print('pZ0', pZ0)
print('eZ0', eZ0)
print('pZ', pZ)
for r, c in zip(range(0, X.shape[0]), range(0, X.shape[0]*3, 3)):
print(r, c)
print(X[r], pZ[r, c:c+3], pZ0[r, :])
if(X[r] > BP): # after branch point should be prior
assert np.allclose(pZ[r, c+1:c+3], pZ0[r, :], atol=1e-6), 'must be the same! %s-%s' % (str(pZ[r, c:c+3]), str(pZ0[r, :]))
else:
assert np.allclose(pZ[r, c:c+3], np.array([1., 0., 0.]), atol=1e-6), 'must be the same! %s-%s' % (str(pZ[r, c:c+3]), str(np.array([1., 0., 0.])))
# from matplotlib import pyplot as plt
# plt.ion()
# plt.matshow(pZ)
eZ0z = pZ_construction_singleBP.expand_pZ0Zeros(pZ0)
r = pZ_construction_singleBP.expand_pZ0PureNumpyZeros(eZ0z, BP, X)
assert np.allclose(r, pZ, atol=1e-5)
# try another
pZ = tf.Session().run(pZ_construction_singleBP.make_matrix(X, BP_tf, eZ0_tf), feed_dict={BP_tf: 0.3, eZ0_tf: eZ0})
r = pZ_construction_singleBP.expand_pZ0PureNumpyZeros(eZ0z, 0.3, X)
assert np.allclose(r, pZ, atol=1e-5)
def test_pZ(self):
np.set_printoptions(suppress=True, precision=2)
X = np.linspace(0, 1, 4, dtype=float)[:, None]
X = np.sort(X, 0)
BP_tf = tf.placeholder(settings.tf_float, shape=[])
eZ0_tf = tf.placeholder(settings.tf_float,
shape=(X.shape[0], X.shape[0] * 3))
pZ0 = np.array([[0.7, 0.3], [0.1, 0.9], [0.5, 0.5], [1, 0]])
eZ0 = pZ_construction_singleBP.expand_pZ0(pZ0)
for BP in [0, 0.2, 0.5, 1]:
print('========== BP %.2f ===========' % BP)
pZ = tf.Session().run(pZ_construction_singleBP.make_matrix(
X, BP, eZ0_tf),
feed_dict={
BP_tf: BP,
eZ0_tf: eZ0
})
print('pZ0', pZ0)
print('eZ0', eZ0)
print('pZ', pZ)
for r, c in zip(range(0, X.shape[0]), range(0, X.shape[0] * 3, 3)):
print(X[r], pZ[r, c:c + 3], pZ0[r, :])
if (X[r] > BP): # after branch point should be prior
self.assertTrue(
np.allclose(pZ[r, c + 1:c + 3], pZ0[r, :],
atol=1e-6), 'must be the same! %s-%s' %
(str(pZ[r, c:c + 3]), str(pZ0[r, :])))
else:
self.assertTrue(
np.allclose(pZ[r, c:c + 3],
np.array([1., 0., 0.]),
atol=1e-6), 'must be the same! %s-%s' %
(str(pZ[r, c:c + 3]), str(pZ0[r, :])))
def test_further(self):
np.set_printoptions(suppress=True, precision=6)
# X = np.linspace(0, 1, 4, dtype=float)[:, None]
X = np.array([0.1, 0.2, 0.3, 0.4])[:, None]
with tf.compat.v1.Session():
BP_tf = tf.compat.v1.placeholder(dtype=gpflow.default_float(),
shape=[])
eZ0_tf = tf.compat.v1.placeholder(dtype=gpflow.default_float(),
shape=(X.shape[0],
X.shape[0] * 3))
pZ0 = np.array([[0.7, 0.3], [0.1, 0.9], [0.5, 0.5], [0.85, 0.15]])
eZ0 = pZ_construction_singleBP.expand_pZ0(pZ0)
BP = 0.2
pZ = tf.compat.v1.Session().run(
pZ_construction_singleBP.make_matrix(X, BP_tf, eZ0_tf),
feed_dict={
BP_tf: BP,
eZ0_tf: eZ0
},
)
print("pZ0", pZ0)
print("eZ0", eZ0)
print("pZ", pZ)
for r, c in zip(range(0, X.shape[0]), range(0, X.shape[0] * 3, 3)):
print(r, c)
print(X[r], pZ[r, c:c + 3], pZ0[r, :])
if X[r] > BP: # after branch point should be prior
assert np.allclose(
pZ[r, c + 1:c + 3], pZ0[r, :],
atol=1e-6), "must be the same! %s-%s" % (
str(pZ[r, c:c + 3]),
str(pZ0[r, :]),
)
else:
assert np.allclose(
pZ[r, c:c + 3], np.array([1.0, 0.0, 0.0]),
atol=1e-6), "must be the same! %s-%s" % (
str(pZ[r, c:c + 3]),
str(np.array([1.0, 0.0, 0.0])),
)
eZ0z = pZ_construction_singleBP.expand_pZ0Zeros(pZ0)
r = pZ_construction_singleBP.expand_pZ0PureNumpyZeros(eZ0z, BP, X)
assert np.allclose(r, pZ, atol=1e-5)
# try another
pZ = tf.compat.v1.Session().run(
pZ_construction_singleBP.make_matrix(X, BP_tf, eZ0_tf),
feed_dict={
BP_tf: 0.3,
eZ0_tf: eZ0
},
)
r = pZ_construction_singleBP.expand_pZ0PureNumpyZeros(eZ0z, 0.3, X)
assert np.allclose(r, pZ, atol=1e-5)
def test_pZ(self):
np.set_printoptions(suppress=True, precision=2)
X = np.linspace(0, 1, 4, dtype=float)[:, None]
X = np.sort(X, 0)
with tf.compat.v1.Session():
BP_tf = tf.compat.v1.placeholder(gpflow.default_float(), shape=[])
eZ0_tf = tf.compat.v1.placeholder(gpflow.default_float(),
shape=(X.shape[0],
X.shape[0] * 3))
pZ0 = np.array([[0.7, 0.3], [0.1, 0.9], [0.5, 0.5], [1, 0]])
eZ0 = pZ_construction_singleBP.expand_pZ0(pZ0)
for BP in [0, 0.2, 0.5, 1]:
print("========== BP %.2f ===========" % BP)
pZ = tf.compat.v1.Session().run(
pZ_construction_singleBP.make_matrix(X, BP, eZ0_tf),
feed_dict={
BP_tf: BP,
eZ0_tf: eZ0
},
)
print("pZ0", pZ0)
print("eZ0", eZ0)
print("pZ", pZ)
for r, c in zip(range(0, X.shape[0]),
range(0, X.shape[0] * 3, 3)):
print(X[r], pZ[r, c:c + 3], pZ0[r, :])
if X[r] > BP: # after branch point should be prior
self.assertTrue(
np.allclose(pZ[r, c + 1:c + 3],
pZ0[r, :],
atol=1e-6),
"must be the same! %s-%s" %
(str(pZ[r, c:c + 3]), str(pZ0[r, :])),
)
else:
self.assertTrue(
np.allclose(pZ[r, c:c + 3],
np.array([1.0, 0.0, 0.0]),
atol=1e-6),
"must be the same! %s-%s" %
(str(pZ[r, c:c + 3]), str(pZ0[r, :])),
)