def test_fix_tfill(self):
solution = sols.MultiSol(130, self.chrom, self.tfill, self.bpp)
testviolations = self.moop.rackcapacity(solution.getx(),
solution.gettfill())
self.moop.fixcoolingrack(testviolations, solution)
solution = coordarrays(solution)
fillviolations = self.moop.period_fill_limit(solution)
if fillviolations:
self.moop.fix_tfill(fillviolations, solution)
violations_left = self.moop.period_fill_limit(solution)
self.assertEqual(violations_left, [])
def test_openonebox(self):
solution = sols.MultiSol(0, self.chrom0, self.tfill0, self.bpp)
mooproblem.checkformismatch(solution)
violations = self.moop.rackcapacity(solution.getx(),
solution.gettfill())
for tv in range(len(violations)):
t = violations[tv][0]
self.moop.openonebox(t, solution)
out = StringIO()
mooproblem.checkformismatch(solution, out=out)
output = out.getvalue().strip()
self.assertEqual(output, '')
def setUp(self):
storedchrom = np.load('tests/chrom0.npz')
chrom = storedchrom[storedchrom.files[0]]
self.n = len(chrom)
storedtfill = np.load('tests/tfill0.npz')
tfill = storedtfill[storedtfill.files[0]]
cookies = coolcookies.makeobjects(self.n, 100, 'tests/Cookies1000.txt')
bpp = bp.BPP(self.n, 24, 300, cookies)
self.moop = mooproblem.MOCookieProblem(self.n, 24, 300, 8, cookies)
self.gen = moma.Generation(self.n, 100, 200, cookies, bpp, self.moop)
self.m = sols.MultiSol(0, chrom, tfill, bpp)
self.m = self.gen.moop.calcfeasibility(self.m)
def test_reduce(self):
# Create 10 solutions
for m in range(10):
tfill = self.gen.initialtfill()
newsol = sols.MultiSol(m, sample(range(24), 24), tfill, self.bpp)
newsol.updaterank(round(m / 2))
self.gen.archive[m] = newsol
# Test for normal reduction
self.gen.reduce(6)
self.assertEqual(len(self.gen.archive), 6)
# Recreate 10 solutions with different crowding distance values
for m in range(6):
self.gen.archive[m].updaterank(round(m / 5))
self.gen.archive[m].updatecd(m)
for m in range(4):
tfill = self.gen.initialtfill()
newsol = sols.MultiSol(m, sample(range(24), 24), tfill, self.bpp)
newsol.updaterank(round((m + 6) / 5))
newsol.updatecd(m + 6)
self.gen.archive[m + 6] = newsol
# Test for cd reduction
self.gen.reduce(6)
self.assertEqual(len(self.gen.archive), 6)
def test_approx(self):
# Create 100 solutions
self.gen.archive = {}
ids = sample(range(1000), 100)
for m in range(100):
tfill = self.gen.initialtfill()
newsol = sols.MultiSol(m, sample(range(24), 24), tfill, self.bpp)
newsol = self.gen.moop.calcfeasibility(newsol)
newsol = bp.coordarrays(newsol)
fits = self.gen.moop.calcfits(newsol)
newsol.updatefitvals(fits)
self.gen.archive[newsol.index] = newsol
ndset = self.gen.finalapproxset()
self.assertNotEqual(len(ndset), 0)
def addnewsol(self, newgenes):
# This function creates a new solution from an individual newgenes.
# Step 1: Make new solution
newsol = sols.MultiSol(self.idnum, newgenes[0], newgenes[1], self.bpp)
# Step 2: Check & Fix feasibility of solution
newsol = self.moop.calcfeasibility(newsol)
checkformismatch(newsol)
# Step 3: Calculate fitness values of solution
fits = self.moop.calcfits(newsol)
newsol.updatefitvals(fits)
self.updateid()
self.updatefe()
self.q.append(newsol)
self.archive[newsol.index] = newsol
def test_fixcoolingrack(self):
solution = sols.MultiSol(129, self.chrom, self.tfill, self.bpp)
testviolations = self.moop.rackcapacity(solution.getx(),
solution.gettfill())
self.moop.fixcoolingrack(testviolations, solution)
solution = coordarrays(solution)
# Make sure fixcoolingrack() fixed all violations
testviolations = self.moop.rackcapacity(solution.getx(),
solution.gettfill())
self.assertEqual(testviolations, [])
# Make sure it didn't create other constraint errors
self.moop.noreplacement(129, solution.getx())
tviolations = self.moop.timeconstraint(solution)
self.assertEqual(tviolations, [])
self.moop.calcfeasibility(solution)
def test_fittruncation(self):
# Create 20 solutions with cd-values
self.gen.archive = {}
for m in range(20):
tfill = self.gen.initialtfill()
newsol = sols.MultiSol(m, sample(range(24), 24), tfill, self.bpp)
newsol.updatefitvals([10, 50, 900])
newsol.updaterank(choice([1, 2]))
newsol.updatecd(choice(range(10)) / 10)
self.gen.archive[m] = newsol
approxset = [m for k, m in self.gen.archive.items() if m.getrank() == 1]
keys = [k for k, m in self.gen.archive.items() if m.getrank() == 1]
self.gen.fittruncation(keys, approxset, 5)
newapproxset = [m for k, m in self.gen.archive.items() if m.getrank() == 1]
self.assertEqual(len(newapproxset), 5)
def test_approx(self):
# Create 100 solutions
self.gen.archive = {}
ids = sample(range(1000), 100)
for m in range(100):
newsol = sols.MultiSol(ids[m], sample(range(10), 10),
np.zeros((10, 1), dtype=int), self.bpp)
newsol = self.gen.moop.calcfeasibility(newsol)
newsol.x, newsol.y, newsol.tfill = bp.coordarrays(
newsol.x, newsol.y, newsol.tfill)
fits = self.gen.moop.calcfits(newsol)
newsol.updatefitvals(fits)
self.gen.archive[newsol.index] = newsol
ndset = self.gen.finalapproxset()
self.assertNotEqual(len(ndset), 0)
def test_getvlrep(self):
solution = sols.MultiSol(8, self.chrom, self.tfill, self.bpp)
vlrep = solution.getvlrep()
self.assertTrue(vlrep)
vlrepi = solution.getvlrep(i=0)
self.assertEqual(vlrep[0], vlrepi)
def test_init(self):
solution = sols.MultiSol(8, self.chrom, self.tfill, self.bpp)
open = solution.getopenbins()
self.assertEqual(len(solution.vlrep), open)
self.assertEqual(np.sum(solution.getx()[open, :]), 0)