def reconstruct(f,tree,tau,minfrac,maxfrac):
randomize_folder_size(tree,minfrac,maxfrac)
fshifted = (f[0,:] - tau) % 1.0
tree_intervals = np.array([node.lbound for node in tree.leaves()])
indices = np.digitize(fshifted,tree_intervals) - 1
fy = np.zeros([tree.size,1])
fcts = np.zeros(np.shape(fy))
for (i,idx) in enumerate(indices):
fcts[idx,0] += 1.0
n = fcts[idx,0]
fy[idx,0] = ((n-1)/n)*fy[idx,0]+(1/n)*f[1,i]
cl = tree.char_library()
coeffs,iters = lb.l1_bregman(cl[indices,:],fy[indices,:],1,threshold=1e-6,verbose=False)
shiftedy = cl.dot(coeffs).ravel()
shiftedx = tree_intervals
nx = (shiftedx + tau) % 1.0
sorted_ind = nx[0:tree.size].argsort()
y = shiftedy[sorted_ind]
y = np.hstack([y[-1],y[-1],y])
x = nx.copy()[0:tree.size]
x.sort()
x = np.hstack([[0.0],x,[1.0]])
return x,y,coeffs
def reconstruct_l2(f,tree,minfrac,maxfrac,alpha=1.0,suppress_warnings=True):
randomize_folder_size(tree,minfrac,maxfrac)
tree_intervals = np.array([node.lbound for node in tree.leaves()])
indices = np.digitize(f[0,:],tree_intervals) - 1
fy = np.zeros([tree.size])
fcts = np.zeros(np.shape(fy))
for (i,idx) in enumerate(indices):
fcts[idx] += 1.0
n = fcts[idx]
fy[idx] = ((n-1)/n)*fy[idx]+(1/n)*f[1,i]
active_indices = np.where(fcts>0)[0]
#print active_indices
cl = tree.char_library(alpha)
if suppress_warnings:
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
alphas,active_vars,coef_path = sklm.lars_path(cl[active_indices,:],
fy[active_indices,:],
method='lasso',max_iter=2000)
else:
alphas,active_vars,coef_path = sklm.lars_path(cl[active_indices,:],
fy[active_indices,:],method='lasso',
max_iter=2000)
return tree_intervals, fy, alphas, active_vars, coef_path, active_indices