def mtvsolverbis(Hurstaest_init, yij, varyj, nj, j1, j2,
mask, max_iter=100, init=None,
prox_max_iter=5000, tol=1e-4, call_back=None, verbose=1,
l=1, l1_ratio=0, wtype=1, lipschitz_constant=0):
"""
This function yields the total energy of the Tv penalyzation
"""
# shape of image box
alpha = 1
flat_mask = mask.ravel()
volume_shape = mask.shape
H_size = len(Hurstaest_init)
if lipschitz_constant == 0:
lipschitz_constant = H_size * lipschitz_constant_gradf(j1,j2,varyj, nj, wtype)
#init["z"] = Hurst_init.copy()
#init["t"] = 1
#ini["stepsize"] = 1 / lipschitz_constant
def total_energy(estimation):
return fbis(estimation, yij, varyj, nj, j1, j2, wtype) + l * tv(_unmask(estimation[:H_size / 2],
mask))
def unmaskvec(estimation):
return _unmask(estimation, mask)
def maskvec(estimation):
return estimation[flat_mask]
def f1_grad(estimation):
return gradfbis(estimation, yij, varyj, nj, j1, j2, wtype)
def f2_prox(estimation, stepsize, dgap_tol, init):
lenw = len(estimation)
Hurst = estimation[lenw / 2:]
init = unmaskvec(init[:lenw / 2]) if not init is None else init
out, info = _prox_tvl1(unmaskvec(Hurst),
weight=(l + 1.e-6) * stepsize, l1_ratio=l1_ratio,
dgap_tol=dgap_tol, init=init,
max_iter=prox_max_iter, fista = False,
verbose=verbose)
#pdb.set_trace()
return np.concatenate((maskvec(out.ravel()),estimation[lenw / 2:])), info
w, obj, init = mfista(
f1_grad, f2_prox, total_energy, lipschitz_constant, H_size,
dgap_factor=(.1 + l1_ratio) ** 2, tol=tol, init=init, verbose=verbose,
max_iter=max_iter, callback=None)
return w, obj, init
def mtvsolver(Hurst_init, aest, yij, varyj, nj, j1, j2,
mask, max_iter=100, init=None,
prox_max_iter=5000, tol=1e-4, call_back=None, verbose=1,
l=1, l1_ratio=0,lipschitz_constant=0, wtype=1):
"""
This function yields the total energy of the Tv penalyzation
"""
# shape of image box
alpha = 1
flat_mask = mask.ravel()
volume_shape = mask.shape
H_size = len(Hurst_init)
if lipschitz_constant == 0:
lipschitz_constant = lipschitz_constant_gradf(j1,j2,varyj, nj, wtype)
#init["z"] = Hurst_init.copy()
#init["t"] = 1
#ini["stepsize"] = 1 / lipschitz_constant
def total_energy(x):
return l2_loss(x, aest, yij, varyj, nj, j1, j2, wtype) + l * tv(_unmask(x,mask))
def unmaskvec(w):
return _unmask(w, mask)
def maskvec(w):
return w[flat_mask]
def f1_grad(x):
return grad_l2_loss(x, aest, yij, varyj, nj, j1, j2, wtype)
def f2_prox(w, stepsize, dgap_tol, init):
out, info = _prox_tvl1(unmaskvec(w),
weight= (l + 1.e-6) * stepsize, l1_ratio=l1_ratio,
dgap_tol=dgap_tol, init=unmaskvec(init),
max_iter=prox_max_iter, fista = False,
verbose=verbose)
return maskvec(out.ravel()), info
w, obj, init = mfista(
f1_grad, f2_prox, total_energy, lipschitz_constant, H_size,
dgap_factor=(.1 + l1_ratio) ** 2, tol=tol, init=init, verbose=verbose,
max_iter=max_iter, callback=None)
return w, obj, init
def mtvsolver(Hurst_init, aest, yij, varyj, nj, j1, j2,
mask, max_iter=100, init=None,
prox_max_iter=5000, tol=1e-4, call_back=None, verbose=1,
l=1, l1_ratio=0,lipschitz_constant=0, wtype=1):
"""
This function yields the total energy of the Tv penalyzation
"""
# shape of image box
alpha = 1
flat_mask = mask.ravel()
volume_shape = mask.shape
H_size = len(Hurst_init)
if lipschitz_constant == 0:
lipschitz_constant = lipschitz_constant_gradf(j1,j2,varyj, nj, wtype)
#init["z"] = Hurst_init.copy()
#init["t"] = 1
#ini["stepsize"] = 1 / lipschitz_constant
def total_energy(x):
return f(x, aest, yij, varyj, nj, j1, j2, wtype) + l * tv(_unmask(x,mask))
def unmaskvec(w):
return _unmask(w, mask)
def maskvec(w):
return w[flat_mask]
def f1_grad(x):
return gradf(x, aest, yij, varyj, nj, j1, j2, wtype)
def f2_prox(w, stepsize, dgap_tol, init):
out, info = _prox_tvl1(unmaskvec(w),
weight= (l + 1.e-6) * stepsize, l1_ratio=l1_ratio,
dgap_tol=dgap_tol, init=unmaskvec(init),
max_iter=prox_max_iter, fista = False,
verbose=verbose)
#pdb.set_trace()
return maskvec(out.ravel()), info
w, obj, init = mfista(
f1_grad, f2_prox, total_energy, lipschitz_constant, H_size,
dgap_factor=(.1 + l1_ratio) ** 2, tol=tol, init=init, verbose=verbose,
max_iter=max_iter, callback=None)
return w, obj, init
def tv_welch_solver(Hurst_init, aest, log2frq, log2pwr,
mask, max_iter=100, init=None,
prox_max_iter=5000, tol=1e-4, call_back=None, verbose=1,
l=1, l1_ratio=0,lipschitz_constant=0, consider_fBm=False):
"""
This function yields the total energy of the Tv penalyzation
"""
# shape of image box
flat_mask = mask.ravel()
volume_shape = mask.shape
H_size = len(Hurst_init)
if lipschitz_constant==0:
lipschitz_constant = lipschitz_constant_grad_welch_square_loss(log2frq, consider_fBm=consider_fBm)
def total_energy(x):
return welch_squared_loss(x, aest, log2frq, log2pwr, compute_energy=True, compute_grad=False, consider_fBm=consider_fBm)
def unmaskvec(w):
return _unmask(w, mask)
def maskvec(w):
return w[flat_mask]
def f1_grad(x):
return welch_squared_loss(x, aest,log2frq, log2pwr, compute_energy=False, compute_grad=True, consider_fBm=consider_fBm)
def f2_prox(w, stepsize, dgap_tol, init):
out, info = _prox_tvl1(unmaskvec(w),
weight= (l + 1.e-6) * stepsize, l1_ratio=l1_ratio,
dgap_tol=dgap_tol, init=unmaskvec(init),
max_iter=prox_max_iter, fista = False,
verbose=verbose)
return maskvec(out.ravel()), info
w, obj, init = mfista(
f1_grad, f2_prox, total_energy, lipschitz_constant, H_size,
dgap_factor=(.1 + l1_ratio) ** 2, tol=tol, init=init, verbose=verbose,
max_iter=max_iter, callback=None)
return w, obj, init
def tv_welch_solver(Hurst_init,
aest,
log2frq,
log2pwr,
mask,
max_iter=100,
init=None,
prox_max_iter=5000,
tol=1e-4,
call_back=None,
verbose=1,
l=1,
l1_ratio=0,
lipschitz_constant=0,
consider_fBm=False):
"""
This function yields the total energy of the Tv penalyzation
"""
# shape of image box
flat_mask = mask.ravel()
volume_shape = mask.shape
H_size = len(Hurst_init)
if lipschitz_constant == 0:
lipschitz_constant = lipschitz_constant_grad_welch_square_loss(
log2frq, consider_fBm=consider_fBm)
def total_energy(x):
return welch_squared_loss(x,
aest,
log2frq,
log2pwr,
compute_energy=True,
compute_grad=False,
consider_fBm=consider_fBm)
def unmaskvec(w):
return _unmask(w, mask)
def maskvec(w):
return w[flat_mask]
def f1_grad(x):
return welch_squared_loss(x,
aest,
log2frq,
log2pwr,
compute_energy=False,
compute_grad=True,
consider_fBm=consider_fBm)
def f2_prox(w, stepsize, dgap_tol, init):
out, info = _prox_tvl1(unmaskvec(w),
weight=(l + 1.e-6) * stepsize,
l1_ratio=l1_ratio,
dgap_tol=dgap_tol,
init=unmaskvec(init),
max_iter=prox_max_iter,
fista=False,
verbose=verbose)
return maskvec(out.ravel()), info
w, obj, init = mfista(f1_grad,
f2_prox,
total_energy,
lipschitz_constant,
H_size,
dgap_factor=(.1 + l1_ratio)**2,
tol=tol,
init=init,
verbose=verbose,
max_iter=max_iter,
callback=None)
return w, obj, init
