def proj(self, w, index, eps=consts.TOLERANCE, max_iter=100):
"""The projection operator of a constraint that corresponds to the
function with the given index.
From the interface "MultiblockProjectionOperator".
Parameters
----------
w : List of numpy arrays. The weight vectors.
index : Non-negative integer. Which variable the step is for.
"""
prox = self._prox[index]
proj = self._c[index]
if len(proj) == 1 and len(prox) == 0:
proj_w = proj[0].proj(w[index], eps=eps, max_iter=max_iter)
elif len(proj) == 2 and len(prox) == 0:
from parsimony.algorithms.proximal \
import DykstrasProjectionAlgorithm
combo = DykstrasProjectionAlgorithm(eps=eps,
max_iter=max_iter, min_iter=1)
proj_w = combo.run(proj, w[index])
else:
proj_w = self.prox(w, index, eps=eps, max_iter=max_iter)
return proj_w
def proj(self, w, index, eps=consts.TOLERANCE, max_iter=100):
"""The projection operator of a constraint that corresponds to the
function with the given index.
From the interface "MultiblockProjectionOperator".
Parameters
----------
w : List of numpy arrays. The weight vectors.
index : Non-negative integer. Which variable the step is for.
"""
prox = self._prox[index]
proj = self._c[index]
if len(proj) == 1 and len(prox) == 0:
proj_w = proj[0].proj(w[index], eps=eps, max_iter=max_iter)
elif len(proj) == 2 and len(prox) == 0:
from parsimony.algorithms.proximal \
import DykstrasProjectionAlgorithm
combo = DykstrasProjectionAlgorithm(eps=eps,
max_iter=max_iter, min_iter=1)
proj_w = combo.run(proj, w[index])
else:
proj_w = self.prox(w, index, eps=eps, max_iter=max_iter)
return proj_w
def proj(self, w, index, eps=consts.TOLERANCE, max_iter=100):
"""The projection operator of a constraint that corresponds to the
function with the given index.
From the interface "MultiblockProjectionOperator".
Parameters
----------
w : list of numpy arrays
The weight vectors.
index : int
Non-negative integer. Which variable the projection is for.
"""
prox = self._p[index]
proj = self._c[index]
# We have no penalties with projection operators:
if len(prox) == 0 and len(proj) == 0:
proj_w = w[index] # Do nothing!
# There is one projection operator and no proximal operators:
elif len(proj) == 1 and len(prox) == 0:
proj_w = proj[0].proj(w[index], eps=eps, max_iter=max_iter)
# There are two projection operators and no proximal operators:
elif len(proj) == 2 and len(prox) == 0:
from parsimony.algorithms.proximal \
import DykstrasProjectionAlgorithm
combo = DykstrasProjectionAlgorithm(eps=eps,
max_iter=max_iter,
min_iter=1)
proj_w = combo.run(proj, w[index])
# There are no constraints, but one or two proximal operators, or any
# number of constraints and any number of proximal oeprators:
else:
proj_w = self.prox(w, index, eps=eps, max_iter=max_iter)
return proj_w
def proj(self, w, index, eps=consts.TOLERANCE, max_iter=100):
"""The projection operator of a constraint that corresponds to the
function with the given index.
From the interface "MultiblockProjectionOperator".
Parameters
----------
w : list of numpy arrays
The weight vectors.
index : int
Non-negative integer. Which variable the projection is for.
"""
prox = self._p[index]
proj = self._c[index]
# We have no penalties with projection operators:
if len(prox) == 0 and len(proj) == 0:
proj_w = w[index] # Do nothing!
# There is one projection operator and no proximal operators:
elif len(proj) == 1 and len(prox) == 0:
proj_w = proj[0].proj(w[index], eps=eps, max_iter=max_iter)
# There are two projection operators and no proximal operators:
elif len(proj) == 2 and len(prox) == 0:
from parsimony.algorithms.proximal \
import DykstrasProjectionAlgorithm
combo = DykstrasProjectionAlgorithm(eps=eps,
max_iter=max_iter, min_iter=1)
proj_w = combo.run(proj, w[index])
# There are no constraints, but one or two proximal operators, or any
# number of constraints and any number of proximal oeprators:
else:
proj_w = self.prox(w, index, eps=eps, max_iter=max_iter)
return proj_w