def lagrange_prox(self, X, lipschitz=1, lagrange=None):
lagrange = svd_atom.lagrange_prox(self, X, lipschitz, lagrange)
self.X = X
U, D, V = self.SVD
D_soft_thresholded = D - projl1(D, lagrange/lipschitz)
keepD = D_soft_thresholded > 0
self.SVD = U[:,keepD], D_soft_thresholded[keepD], V[keepD]
c = self.conjugate
c.SVD = self.SVD
self._X = np.dot(U[:,keepD], D_soft_thresholded[keepD][:,np.newaxis] * V[keepD])
return self.X
def bound_prox(self, X, lipschitz=1, bound=None):
bound = svd_atom.bound_prox(self, X, lipschitz, bound)
self.X = X
U, D, V = self.SVD
D_projected = projl1(D, self.bound)
keepD = D_projected > 0
# store the projected X -- or should we keep original?
self.SVD = U[:,keepD], D_projected[keepD], V[keepD]
c = self.conjugate
c.SVD = self.SVD
self._X = np.dot(U[:,keepD], D_projected[keepD][:,np.newaxis] * V[keepD])
return self.X