def TestBansal():
G = syn.InitRandom(10, makeInt=True)
WG = G.copy()
WG.remove_edges_from([(u, v) for (u, v, d) in WG.edges(data=True)
if d['weight'] < 0.0])
viz.DrawGraph(WG, title='original')
print("Trying Bansal")
ban = bansal.BansalSolver(WG)
components = ban.run()
labels = dict()
ci = 1
for component in components:
for v in component:
labels[v] = ci
ci = ci + 1
E = seg.GetLabelEnergy(G, labels)
print("Bansal energy is " + str(E))
L = seg.GetLabelsAtThreshold(G, theta=0)
E = seg.GetLabelEnergy(G, L)
print("CC at zero is " + str(E))
thresh, minE = seg.FindMinEnergyThreshold(G)
print("CC min is " + str(minE))
plt.show()
print("Done")
def FindBestThreshold(NG, RG, WCLabels):
edgeWeights = [(u, v, w) for (u, v, w) in NG.edges(data='weight')]
sortedEdges = sorted(edgeWeights, reverse=True, key=lambda edge: edge[2])
bestL = WCLabels.copy()
bestE = seg.GetLabelEnergy(RG, bestL)
bestT = sortedEdges[0][2] + DELTA_TOLERANCE
print("E = " + str(bestE) + " from T = " + str(bestT))
for e in sortedEdges:
t = e[2] - DELTA_TOLERANCE
L = seg.GetLabelsAtThreshold(NG, theta=t)
lowerL = WCLabels.copy()
for n in lowerL:
lowerL[n] = L[lowerL[n]]
lowerE = seg.GetLabelEnergy(RG, lowerL)
if lowerE < bestE:
bestE = lowerE
bestL = lowerL.copy()
bestT = t
print("E = " + str(bestE) + " from T = " + str(bestT))
return bestL, bestE, bestT
def Minimize(G, width, theta=None, minType=None):
if minType is None:
minType = 'kl' # kl (heurestic) or lp
if theta is None:
theta = 0.5 # Used to round the result (note.. if all results are integer already that tells us its optimal for sure (I think))
ExportGraph(G, width)
cmd = "graphCluster -n " + str(len(G)) + " -c " + minType
print(cmd)
os.system(cmd)
edgeLabels = ImportEdgeLabels(width)
# label the nodes
lg = G.copy()
for (u, v, d) in lg.edges(data=True):
d['weight'] = edgeLabels[(u, v)]
lg.remove_edges_from([(u, v) for (u, v, d) in lg.edges(data=True)
if d['weight'] >= theta])
nodeLabels = {
node: color
for color, comp in enumerate(nx.connected_components(lg))
for node in comp
}
minE = seg.GetLabelEnergy(G, nodeLabels)
return nodeLabels, minE
def TestKruskal():
#np.random.seed(1)
WG = syn.InitRandom(10, 1, False)
viz.DrawGraph(WG, title='original')
# Get the labeling at threshold 0 and calculate energy
L = seg.GetLabelsAtThreshold(WG, theta=0)
E = seg.GetLabelEnergy(WG, L)
print("Energy at zero is " + str(E))
viz.DrawGraph(WG, labels=LG, title='original')
# Find the best threshold and check it
thresh, minE = seg.FindMinEnergyThreshold(WG)
print("Minimum energy at " + str(thresh) + " is " + str(minE))
# check to see if that's correct
L = seg.GetLabelsAtThreshold(WG, theta=thresh)
E2 = seg.GetLabelEnergy(WG, L)
print("Energy check: " + str(E2))
viz.DrawGraph(WG, labels=LG, title='bestThresh')
plt.show()
def Minimize(WG, nodeType=None):
if nodeType is None:
nodeType = 'CC'
#print("DsnNode: Minimizing...")
param = dict()
param['nodeType'] = nodeType
if nodeType == 'CC':
thresh, minE = seg.FindMinEnergyThreshold(WG)
#print("WS Min Energy: " + str(minE) + " @ t=" + str(thresh))
param['threshold'] = thresh
L = seg.GetLabelsAtThreshold(WG, theta=thresh)
#E2 = seg.GetLabelEnergy(WG, L)
#print("Energy check: " + str(minE) + " verse " + str(E2))
elif nodeType == 'WC':
WC = seg.GetWatershedGraph(WG)
thresh, minE = seg.FindMinEnergyThreshold(WC, eval=WG)
#print("WS Min Energy: " + str(minE) + " @ t=" + str(thresh))
param['threshold'] = thresh
L = seg.GetLabelsAtThreshold(WC, theta=thresh)
#E2 = seg.GetLabelEnergy(WG, L)
#print("Energy check: " + str(E2))
elif nodeType == 'WS': # fixed threshold WC
WC = seg.GetWatershedGraph(WG)
param['threshold'] = 0.0
L = seg.GetLabelsAtThreshold(WC, theta=0.0)
minE = seg.GetLabelEnergy(WG, L)
#print("Energy check: " + str(E2))
#print("DsnNode: Done")
return L, minE, param