def testMinimumSpanningTree():
sd = np.random.randint(1, 999)
N = 150
makeCanvas(size=[7, 7])
G = randomNodes(N, .1, NodeColor='black', NodeSize=.05, seed=sd)
complete(G)
t0 = time()
Krus = KruskalMinTree(G, modify=False)
print("Kruskal: {:.3f} seconds".format(time() - t0))
#print(Krus)
empty(G)
G.addEdges(Krus)
G.drawNodes()
G.drawLines()
makeCanvas(size=[7, 7])
G = randomNodes(N, .1, NodeColor='black', NodeSize=.05, seed=sd)
complete(G)
t0 = time()
Prim = PrimMinTree(G, modify=False)
print("Prim: {:.3f} seconds".format(time() - t0))
#print(Prim)
empty(G)
G.addEdges(Prim)
G.drawNodes()
G.drawLines()
#testMinimumSpanningTree()
def testDijkstrasAlgorithmVisualizer():
#G = flowerSnarkGraph(NodeSize=.2)
#DijkstraVisualizer(G,start=7,text=False)
N = 15
G = randomNodes(N,1,NodeSize=.15,TextSize=1.7)
G.Mat = connectedGraph(N,prob=.1)
DijkstraVisualizer(G,start=0,text=True)
def unitDiskGraph(N,
f,
d,
xlim=[-2.8, 2.8],
ylim=[-2.8, 2.8],
seed=None,
**kwargs):
G = randomNodes(N, f, xlim=xlim, ylim=ylim, seed=seed, **kwargs)
for i in range(N):
for j in range(i):
if dist(G.pos[i], G.pos[j]) < d:
G.addEdges(i, j)
return G
def testStronglyConnected():
G = randomNodes(10, .5, NodeSize=.2, TextSize=1.5, seed=44345)
G.addEdges([8, 3, 6, 4, 1, 1, 7, 9, 7, 2, 2, 9, 2, 4, 7],
[3, 6, 4, 8, 4, 7, 5, 7, 2, 0, 6, 0, 9, 3, 4],
directed=True)
makeCanvas()
G.drawNodes()
G.drawText()
G.drawArrows()
S = stronglyConnected(G)
color = ['pink', 'cornflowerblue', 'khaki', 'lightgreen', 'violet']
ctr = 0
for i in S:
for j in i:
G.colors[j] = color[ctr]
ctr += 1
G.drawNodes()
from Graphs import *
from DijkstrasAlgorithm import dijkstra
from RandomPoints import randomNodes
G = randomNodes(14, .5, NodeSize=.2, seed=44345)
G.addEdges([8, 3, 6, 4, 1, 1, 7, 9, 7, 2, 2, 9, 2, 5, 10, 0, 11, 4, 12, 1],
[3, 6, 4, 8, 4, 7, 5, 7, 2, 0, 6, 0, 9, 10, 0, 11, 3, 12, 8, 13],
directed=False)
makeCanvas()
G.drawNodes()
G.drawText()
D = maskDist(G)
M = np.zeros([G.size, G.size])
for n in range(10):
x = dijkstra(D, n)
x = x[1]
used = []
for i in x:
for j in range(len(i) - 1):
if [i[j], i[j + 1]] not in used:
used.append([i[j], i[j + 1]])
for x in used:
M[x[0], x[1]] += 1
M[x[1], x[0]] += 1
print(M)
# Draw the connections
if len(P) > 1:
G.addEdges([O[-1]], [O[-2]])
if directed == False:
G.addEdges([O[-2]], [O[-1]])
# Check if we've reached the place where we started
if end == P[0]:
P.append(cur)
G.addEdges([O[0]], [O[-1]])
if directed == False:
G.addEdges([O[-1]], [O[0]])
break
return O
makeCanvas(size=[12, 12])
#np.random.seed(17)
G = randomNodes(20, .3)
G.texts = [i for i in range(20)]
G.tscales = [2] * 20
G.radii = [.06] * 20
G.drawNodes()
c = convexHull(G, directed=True)
print(c)
G.drawLines()
from Graphs import *
from RandomPoints import randomNodes
G = randomNodes(10, .5, NodeSize=.2, TextSize=1.5, seed=44345)
G.addEdges([8, 3, 4, 1, 1, 7, 9, 7, 2, 2, 9, 2, 4, 7, 8, 2],
[3, 6, 8, 4, 7, 5, 7, 2, 0, 6, 0, 9, 3, 4, 6, 8],
directed=True)
def mergeNode(a, b, G):
A = [i for i in range(len(G.texts)) if G.texts[i] == str(a)][0]
B = [i for i in range(len(G.texts)) if G.texts[i] == str(b)][0]
x = np.mean([G.pos[A][0], G.pos[B][0]])
y = np.mean([G.pos[A][1], G.pos[B][1]])
G.Mat[A, :] += G.Mat[B, :]
G.Mat[:, A] += G.Mat[:, B]
G.delNode(B)
G.pos[A] = [x, y]
def mergeNodes(L, G, name=None):
L.sort()
for i in range(len(L) - 1):
mergeNode(L[0], L[i + 1], G)
if name != None:
G.texts[L[0]] = name