def _sampleAVG(avg, size): """ Simplified pipeline """ C = cactus.Cactus(avg) NC = normalized.NormalizedCactus(C) OC = oriented.OrientedCactus(NC) H = cycleCover.initialHistory(OC) return sampleGraphCycles.sample(H, size)
def main():
G = avg.randomEulerianGraph(10)
C = cactus.Cactus(G)
NC = normalized.NormalizedCactus(C)
BC = balancedCactus.BalancedCactus(NC)
OC = oriented.OrientedCactus(BC)
H = cycleCover.initialHistory(OC)
assert areUnitFlows(X.cycle for X in H.parent)
def main():
G = avg.randomNearEulerianGraph(10)
C = cactus.Cactus(G)
N = normalized.NormalizedCactus(C)
B = balanced.BalancedCactus(N)
O = oriented.OrientedCactus(B)
print C
print '>>>>>>>>>>>>>>>>>>>>>>'
print "\n".join(map(str, extractGraphModules(O).values()))
def main():
G = avg.randomEulerianGraph(10)
C = cactus.Cactus(G)
N = normalizedCactus.NormalizedCactus(C)
orientedCactus = oriented.OrientedCactus(N)
print orientedCactus
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
res = sample(cycleCover.initialHistory(orientedCactus), 20)[-1]
print res
res.validate()
def main():
graph = avg.randomNearEulerianGraph(10)
C = cactus.Cactus(graph)
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
print C
print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>'
NC = normalized.NormalizedCactus(C)
print NC
BC = BalancedCactus(NC)
print BC
print BC.graphError()
def main(): G = avg.randomEulerianGraph(10) C = cactus.Cactus(G) N = normalized.NormalizedCactus(C) O = orientedCactus.OrientedCactus(N) print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>' print O print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>' CH = cycleCover.initialHistory(O) print CH print '>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>' N = random.choice(O.nets) NH = createNewHistory(CH, CH.netHistories[N]) NH.validate()
def main():
graph = avg.randomNearEulerianGraph(10)
C = cactus.Cactus(graph)
NC = normalized.NormalizedCactus(C)
BC = balanced.BalancedCactus(NC)
OC = oriented.OrientedCactus(BC)
H = cycleCover.initialHistory(OC)
H.validate()
print H
c = H.rearrangementCost()
FH = flattenGraph(H)
print FH
print FH.cactus.telomeres
FH.validate()
def main():
options = _parseOptions()
sampleGraphCycles.TEMPERATURE = options.temp
if options.dir is not None:
if not os.path.exists(options.dir):
os.mkdir(options.dir)
os.chdir(options.dir)
if options.index is None:
## Initial graph construction
G = _parseGraph(options)
B = balancedAVG.BalancedAVG(G)
C = cactus.Cactus(B)
pickle.dump(C, open('CACTUS', "wb"))
else:
H = None
if options.debug:
## Picking up from where we started
OC = pickle.load(open('CACTUS_%i' % options.index))
random.setstate(pickle.load(open("STATE_%i" % options.index)))
elif options.cont:
## Picking up from where we stopped
OC = pickle.load(open('CACTUS_%i' % options.index))
## Going through all the histories to the last in file
file= open('HISTORIES_%i' % (options.index))
while True:
try:
H = pickle.load(file)
except:
break
file.close()
else:
## Just moving from there
pickle.dump(random.getstate(), open("STATE_%i" % options.index, "wb"))
C = pickle.load(open('CACTUS'))
## Sampling possible cactus
NC = normalized.NormalizedCactus(C)
if debug.RATIO_TO_OFFSET:
BC = balancedCactus.BalancedCactus(NC)
else:
BC = NC
OC = oriented.OrientedCactus(BC)
## Saving sampled cactus
pickle.dump(OC, open('CACTUS_%i' % options.index, "wb"))
# Moving into historical space
if options.integer:
debug.INTEGER_HISTORY = True
if H is None:
H = cycleCover.initialHistory(OC)
FH = flattened.flattenGraph(H)
S = FH.simplifyStubsAndTrivials()
F = S.removeLowRatioEvents(debug.RATIO_CUTOFF)
O = ordered.OrderedHistory(F)
# Preparing file for progressive write
if options.cont:
stats_file = open("HISTORY_STATS_%li" % options.index, "a")
pickle_file = open('HISTORIES_%i' % options.index, "ab")
braney_file = gzip.open("HISTORIES_%i.braney" % options.index, "a")
else:
stats_file = open("HISTORY_STATS_%li" % options.index, "w")
pickle_file = open('HISTORIES_%i' % options.index, "wb")
braney_file = gzip.open("HISTORIES_%i.braney" % options.index, "w")
stats_file.write("%s\n" % H.stats())
#pickle.dump(H, pickle_file)
braney_file.write("%s\n" % O.braneyText(0, H.rearrangementCost()))
#tree_file = open("HISTORY_TREES_%li" % options.index, "w")
#tree_file.write("%s\n" % O.newick())
tree_file = None
# Sampling
for i in range(options.size):
H2 = copy.copy(H)
# Shuffle events
for event in list(H.parent):
H2.correctSchedulingError(event)
H = H2
stats_file.write("%s\n" % H.stats())
FH = flattened.flattenGraph(H)
S = FH.simplifyStubsAndTrivials()
F = S.removeLowRatioEvents(debug.RATIO_CUTOFF)
O = ordered.OrderedHistory(F)
braney_file.write("%s\n" % O.braneyText(i+1, H.rearrangementCost()))
# Cleaning up
stats_file.close()
pickle_file.close()
braney_file.close()
#tree_file.close()
## Removing temp file
if os.path.exists("STATE_%i" % options.index):
os.remove("STATE_%i" % options.index)