def test_05(self):
lmbda = 1e-1
Nit = 10
opts = cbpdndl.ConvBPDNDictLearn.Options(
{
'MaxMainIter': Nit,
'AccurateDFid': True,
'CBPDN': {
'RelaxParam': 1.0,
'AutoRho': {
'Enabled': False
}
},
'CCMOD': {
'RelaxParam': 1.0,
'AutoRho': {
'Enabled': False
}
}
},
dmethod='cns')
bs = cbpdndl.ConvBPDNDictLearn(self.D0,
self.S,
lmbda,
opt=opts,
dmethod='cns')
Ds = bs.solve()
optp = prlcnscdl.ConvBPDNDictLearn_Consensus.Options({
'MaxMainIter': Nit,
'CBPDN': {
'RelaxParam': 1.0
},
'CCMOD': {
'RelaxParam': 1.0
}
})
bp = prlcnscdl.ConvBPDNDictLearn_Consensus(self.D0,
self.S,
lmbda,
opt=optp,
nproc=2)
Dp = bp.solve()
assert np.linalg.norm(Ds - Dp) < 1e-7
assert np.abs(
bs.getitstat().ObjFun[-1] - bp.getitstat().ObjFun[-1] < 1e-7)
def par_csc(input_, d_size, lmbda, Iter, visualize=False):
D0 = np.random.uniform(-1.0, 1.0, d_size)
opt = prlcnscdl.ConvBPDNDictLearn_Consensus.Options({
'Verbose': True,
'MaxMainIter': Iter,
'CBPDN': {
'rho': 50.0 * lmbda + 0.5
},
'CCMOD': {
'rho': 1.0,
'ZeroMean': True
}
})
d = prlcnscdl.ConvBPDNDictLearn_Consensus(D0, input_, lmbda, opt, nproc=12)
D1 = d.solve()
print("ConvBPDNDictLearn solve time: %.2fs" % d.timer.elapsed('solve'))
if visualize:
plot_2([util.tiledict(D0.squeeze()),
util.tiledict(D1.squeeze())],
["initial dictionary", "learned dictionary"])
return d, D1, d.getcoef()
def test_04(self):
N = 16
Nc = 3
Nd = 5
M = 4
K = 3
D0 = np.random.randn(Nd, Nd, Nc, M)
S = np.random.randn(N, N, Nc, K)
lmbda = 1e-1
opt = prlcnscdl.ConvBPDNDictLearn_Consensus.Options(
{'MaxMainIter': 10})
try:
b = prlcnscdl.ConvBPDNDictLearn_Consensus(D0,
S,
lmbda,
opt=opt,
nproc=2)
b.solve()
except Exception as e:
print(e)
assert 0
"""
Set regularization parameter and options for dictionary learning solver.
"""
lmbda = 0.2
opt = prlcnscdl.ConvBPDNDictLearn_Consensus.Options({'Verbose': True,
'MaxMainIter': 200,
'CBPDN': {'rho': 50.0*lmbda + 0.5},
'CCMOD': {'rho': 1.0, 'ZeroMean': True}})
"""
Create solver object and solve.
"""
d = prlcnscdl.ConvBPDNDictLearn_Consensus(D0, sh, lmbda, opt)
D1 = d.solve()
print("ConvBPDNDictLearn_Consensus solve time: %.2fs" %
d.timer.elapsed('solve'))
"""
Display initial and final dictionaries.
"""
D1 = D1.squeeze()
fig = plot.figure(figsize=(14, 7))
plot.subplot(1, 2, 1)
plot.imview(util.tiledict(D0), title='D0', fig=fig)
plot.subplot(1, 2, 2)
plot.imview(util.tiledict(D1), title='D1', fig=fig)
