diff options
Diffstat (limited to 'Wrappers/Python')
| -rwxr-xr-x | Wrappers/Python/ccpi/optimisation/algorithms/FISTA.py | 39 |
1 files changed, 4 insertions, 35 deletions
diff --git a/Wrappers/Python/ccpi/optimisation/algorithms/FISTA.py b/Wrappers/Python/ccpi/optimisation/algorithms/FISTA.py index d509621..3f285be 100755 --- a/Wrappers/Python/ccpi/optimisation/algorithms/FISTA.py +++ b/Wrappers/Python/ccpi/optimisation/algorithms/FISTA.py @@ -59,35 +59,18 @@ class FISTA(Algorithm): if opt is None: opt = {'tol': 1e-4} -# self.tol = opt['tol'] if 'tol' in opt.keys() else 1e-4 -# memopt = opt['memopt'] if 'memopt' in opt.keys() else False -# self.memopt = memopt - - # initialization -# if memopt: self.y = x_init.copy() self.x_old = x_init.copy() self.x = x_init.copy() self.u = x_init.copy() -# else: -# self.x_old = x_init.copy() -# self.y = x_init.copy() - - #timing = numpy.zeros(max_iter) - #criter = numpy.zeros(max_iter) - - + + self.invL = 1/f.L self.t_old = 1 def update(self): - # algorithm loop - #for it in range(0, max_iter): - -# if self.memopt: - # u = y - invL*f.grad(y) - # store the result in x_old + self.f.gradient(self.y, out=self.u) self.u.__imul__( -self.invL ) self.u.__iadd__( self.y ) @@ -96,26 +79,12 @@ class FISTA(Algorithm): self.t = 0.5*(1 + numpy.sqrt(1 + 4*(self.t_old**2))) - # y = x + (t_old-1)/t*(x-x_old) self.x.subtract(self.x_old, out=self.y) self.y.__imul__ ((self.t_old-1)/self.t) self.y.__iadd__( self.x ) self.x_old.fill(self.x) - self.t_old = self.t - - -# else: -# u = self.y - self.invL*self.f.gradient(self.y) -# -# self.x = self.g.proximal(u,self.invL) -# -# self.t = 0.5*(1 + numpy.sqrt(1 + 4*(self.t_old**2))) -# -# self.y = self.x + (self.t_old-1)/self.t*(self.x-self.x_old) -# -# self.x_old = self.x.copy() -# self.t_old = self.t + self.t_old = self.t def update_objective(self): self.loss.append( self.f(self.x) + self.g(self.x) )
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