def test_prox_binarsity_range(self):
"""...Test ProxBinarsity deals with range correctly
"""
np.random.seed(2093)
coeffs = np.random.randn(10)
# put a very high strength that will push the penalized coefficients
# to zero
l_binarsity = 1e2
blocks_start = [1]
blocks_length = [3]
prox_range = (3, 7)
prox = ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length, range=prox_range)
start_penalized_coeff = prox_range[0] + blocks_start[0]
end_penalized_coeff = prox_range[0] + blocks_start[0] + blocks_length[0]
self.assertTrue(all(prox.call(coeffs)
[start_penalized_coeff:end_penalized_coeff] == 0))
def test_ProxBinarsity_n_blocks(self):
"""...Test parameter n_blocks
"""
l_binarsity = 0.5
blocks_start = [0, 3, 8, 34]
blocks_length = [3, 5, 2, 23]
prox = ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
self.assertEqual(prox.n_blocks, 4)
def test_ProxBinarsity(self):
"""...Test of ProxBinarsity
"""
coeffs = self.coeffs.copy()
l_binarsity = 0.5
t = 1.7
out = np.array([0., 0., 0., -0.72681389, -0.72681389, 0.4845426,
0.4845426, 0.4845426, 0., 0.])
blocks_start = [0, 3, 8]
blocks_length = [3, 5, 2]
prox = ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
val = 0
for j, d_j in enumerate(blocks_length):
start = blocks_start[j]
val += np.abs(coeffs[start + 1:start + d_j]
- coeffs[start:start + d_j - 1]).sum()
val *= l_binarsity
self.assertAlmostEqual(prox.value(coeffs), val, delta=1e-15)
assert_almost_equal(prox.call(coeffs, step=t), out, decimal=7)
def test_ProxBinarsity_penalty_parameters_setting(self):
"""...Test ProxBinarsity parameters setting
"""
l_binarsity = 0.5
blocks_start = [0, 3, 8]
blocks_length = [3, 5]
msg = '^``blocks_start`` and ``blocks_length`` must have the same size$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
blocks_start = [0, 3, 8]
blocks_length = [4, 5, 1]
msg = '^blocks must not overlap$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
# test not overlapping but not penalizing all coefficients either
blocks_start = [0, 3, 8]
blocks_length = [2, 2, 2]
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
blocks_start = [0, 8, 3]
blocks_length = [1, 1, 1]
msg = '^``block_start`` must be sorted$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
blocks_start = [0, 3, 8]
blocks_length = [-3, 5, 2]
msg = '^all blocks must be of positive size$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
blocks_start = [0, -3, 8]
blocks_length = [3, 5, 2]
msg = '^all blocks must have positive starting indices$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
blocks_start = [0, 3, 8]
blocks_length = [3, 5, 2]
prox = ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length)
msg = '^blocks_length and blocks_start must have the same size$'
with self.assertRaisesRegex(ValueError, msg):
prox.blocks_length = np.array([3, 5, 2, 3], dtype=np.uint64)
blocks_start = [0, 4, 8]
blocks_length = [3, 3, 10]
msg = '^last block is not within the range \[0, end-start\)$'
with self.assertRaisesRegex(ValueError, msg):
ProxBinarsity(strength=l_binarsity, blocks_start=blocks_start,
blocks_length=blocks_length, range=(0, 17))
proxs = [
ProxZero(),
ProxPositive(),
ProxL2Sq(strength=s),
ProxL1(strength=s),
ProxElasticNet(strength=s, ratio=0.5),
ProxSlope(strength=s),
ProxTV(strength=s),
ProxEquality(range=(25, 40)),
ProxL1w(strength=s, weights=0.1 * np.arange(50, dtype=np.double)),
ProxGroupL1(strength=2 * s,
blocks_start=np.arange(0, 50, 10),
blocks_length=10 * np.ones((5, ))),
ProxBinarsity(strength=s,
blocks_start=np.arange(0, 50, 10),
blocks_length=10 * np.ones((5, )))
]
fig, _ = plt.subplots(3, 4, figsize=(16, 12), sharey=True, sharex=True)
fig.axes[0].stem(x)
fig.axes[0].set_title("original vector", fontsize=16)
fig.axes[0].set_xlim((-1, 51))
fig.axes[0].set_ylim((a, b))
for i, prox in enumerate(proxs):
fig.axes[i + 1].stem(prox.call(x))
fig.axes[i + 1].set_title(prox.name, fontsize=16)
fig.axes[i + 1].set_xlim((-1, 51))
fig.axes[i + 1].set_ylim((a, b))