def test_dom1(self):
u = np.matrix([[38], [500], [500]])
v = np.matrix([[39], [600], [600]])
self.assertTrue(mooproblem.dom1(u, v))
w = np.matrix([[38], [500], [450]])
self.assertFalse(mooproblem.dom1(u, w))
self.assertFalse(mooproblem.dom1(u, u))
def fnds(setp):
# This module performs the fast-non-dominated-sort described in Deb(2002).
# To run this module, enable the following line:
# from mop import dom
numsol = len(setp)
fronts = []
sp = []
fhold = []
nps = []
for p in range(numsol):
shold = []
nump = 0
for q in range(numsol):
if setp[p] != setp[q]:
if mop.dom1(setp[p].getfits(), setp[q].getfits()):
shold.append(setp[q])
if mop.dom1(setp[q].getfits(), setp[p].getfits()):
nump += 1
sp.append(shold)
nps.append(nump)
if nump == 0:
fhold.append(setp[p])
setp[p].updaterank(1)
fronts.append(fhold) # Pareto set
i = 0
while fronts[i] != []:
q = []
for j in range(numsol):
if setp[j] in fronts[i]:
for k in range(numsol):
if setp[k] in sp[j]:
nps[k] -= 1
if nps[k] == 0:
setp[k].updaterank(i + 2)
q.append(setp[k])
fronts.append(q)
i += 1
return setp, fronts
def finalapproxset(self):
# This function finds the final approximate set.
numsol = len(self.archive)
ndset = []
keys = [k for k, v in self.archive.items()]
for p in range(numsol):
np = 0
u = self.archive.get(keys[p])
for q in range(numsol):
v = self.archive.get(keys[q])
if u != v:
# If v dominates u, increase domination count
if mop.dom1(v.getfits(), u.getfits()):
np += 1
if np == 0:
ndset.append(u)
return ndset