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Merged
agramfort merged 2 commits into from
Dec 10, 2012
Merged

init is only X and not X, active_set #3

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92f2b39
init is only X and not , active_set
joewalter Dec 10, 2012
4d09b84
avoid full matrix of zeros in _solver functions
joewalter Dec 10, 2012
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24 changes: 10 additions & 14 deletions mne/mixed_norm/optim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -175,22 +175,21 @@ def _mixed_norm_solver_prox(M, G, alpha, maxit=200, tol=1e-8, verbose=None,

if init is None:
X = 0.0
active_set = np.zeros(n_sources, dtype=np.bool)
R = M.copy()
if gram is not None:
R = np.dot(G.T, R)
else:
X, active_set = init
X = init
if gram is None:
R = M - np.dot(G[:, active_set], X)
R = M - np.dot(G, X)
else:
R = GTM - np.dot(gram[:, active_set], X)
R = GTM - np.dot(gram, X)

t = 1.0
Y = np.zeros((n_sources, n_times)) # FISTA aux variable
E = [] # track cost function

active_set = np.ones(n_sources, dtype=np.bool) # HACK
active_set = np.ones(n_sources, dtype=np.bool) # start with full AS

for i in xrange(maxit):
X0, active_set_0 = X, active_set # store previous values
Expand Down Expand Up @@ -231,14 +230,12 @@ def _mixed_norm_solver_cd(M, G, alpha, maxit=10000, tol=1e-8,
n_sensors, n_times = M.shape
n_sensors, n_sources = G.shape

if init is None:
X = np.zeros((n_sources, n_times))
else:
X, active_set = init
if init is not None:
init = init.T

clf = MultiTaskLasso(alpha=alpha / len(M), tol=tol, normalize=False,
fit_intercept=False, max_iter=maxit).fit(G, M,
coef_init=X.T)
coef_init=init)
X = clf.coef_.T
active_set = np.any(X, axis=1)
X = X[active_set]
Expand Down Expand Up @@ -325,7 +322,7 @@ def mixed_norm_solver(M, G, alpha, maxit=3000, tol=1e-8, verbose=None,
logger.info("Using proximal iterations")
l21_solver = _mixed_norm_solver_prox

init = None
X_init = None

if active_set_size is not None:
n_sensors, n_times = M.shape
Expand All @@ -336,7 +333,7 @@ def mixed_norm_solver(M, G, alpha, maxit=3000, tol=1e-8, verbose=None,
active_set = np.tile(active_set[:, None], [1, n_orient]).ravel()
for k in xrange(maxit):
X, as_, E = l21_solver(M, G[:, active_set], alpha,
maxit=maxit, tol=tol, init=init,
maxit=maxit, tol=tol, init=X_init,
n_orient=n_orient)
as_ = np.where(active_set)[0][as_]
gap, pobj, dobj, R = dgap_l21(M, G, X, as_, alpha, n_orient)
Expand All @@ -362,7 +359,6 @@ def mixed_norm_solver(M, G, alpha, maxit=3000, tol=1e-8, verbose=None,
idx_active_set = np.where(active_set)[0]
idx = np.searchsorted(idx_active_set, idx_old_active_set)
X_init[idx] = X
init = X_init, active_set[active_set == True]
if np.all(active_set_old == active_set):
logger.info('Convergence stopped (AS did not change) !')
break
Expand All @@ -373,7 +369,7 @@ def mixed_norm_solver(M, G, alpha, maxit=3000, tol=1e-8, verbose=None,
active_set[as_] = True
else:
X, active_set, E = l21_solver(M, G, alpha, maxit=maxit, tol=tol,
init=init, n_orient=n_orient)
init=X_init, n_orient=n_orient)

if (active_set.sum() > 0) and debias:
bias = compute_bias(M, G[:, active_set], X, n_orient=n_orient)
Expand Down