def pt_DFS(v):
global G, reached
S = Stack()
if reached[v] == 0:
reached[v] = 1
S.Push(v)
while S.IsNotEmpty():
v = S.Pop()
for w in G.adj_nodes(v):
if reached[w] == 0:
reached[w] = 1
S.Push(w)
def strongly_planar(e0, Att):
# We now come to the heart of the planarity test: procedure strongly_planar.
# It takes a tree edge e0=(x,y) and tests whether the segment S(e0) is
# strongly planar.
# If successful it returns (in Att) the ordered list of attachments of S(e0)
# (excluding x); high DFS-numbers are at the front of the list.
# In alpha it records the placement of the subsegments.
#
# strongly_planar operates in three phases.
# It first constructs the cycle C(e0) underlying the segment S(e0).
# It then constructs the interlacing graph for the segments emanating >from the
# spine of the cycle.
# If this graph is non-bipartite then the segment S(e0) is non-planar.
# If it is bipartite then the segment is planar.
# In this case the third phase checks whether the segment is strongly planar
# and, if so, computes its list of attachments.
global G, alpha, dfsnum, parent
#--------------------------------------------------------------
# DETERMINE THE CYCLE C(e0)
# We determine the cycle "C(e0)" by following first edges until a back
# edge is encountered.
# |wk| will be the last node on the tree path and |w0|
# is the destination of the back edge.
x = source(e0)
y = target(e0)
e = G.first_adj_edge(y)
wk = y
while dfsnum[target(e)] > dfsnum[wk]: # e is a tree edge
wk = target(e)
e = G.first_adj_edge(wk)
w0 = target(e)
#--------------------------------------------------------------
#--------------------------------------------------------------
# PROCESS ALL EDGES LEAVING THE SPINE
# The second phase of |strongly_planar| constructs the connected
# components of the interlacing graph of the segments emananating
# from the the spine of the cycle "C(e0)".
# We call a connected component a "block".
# For each block we store the segments comprising its left and
# right side (lists |Lseg| and |Rseg| contain the edges defining
# these segments) and the ordered list of attachments of the segments
# in the block;
# lists |Latt| and |Ratt| contain the DFS-numbers of the attachments;
# high DFS-numbers are at the front of the list.
#
# We process the edges leaving the spine of "S(e0)" starting at
# node |wk| and working backwards.
# The interlacing graph of the segments emanating from
# the cycle is represented as a stack |S| of blocks.
w = wk
S = Stack()
while w != x:
count = 0
for e in G.adj_edges(w):
count = count + 1
if count != 1: # no action for first edge
# TEST RECURSIVELY
# Let "e" be any edge leaving the spine.
# We need to test whether "S(e)" is strongly planar
# and if so compute its list |A| of attachments.
# If "e" is a tree edge we call our procedure recursively
# and if "e" is a back edge then "S(e)" is certainly strongly
# planar and |target(e)| is the only attachment.
# If we detect non-planarity we return false and free
# the storage allocated for the blocks of stack |S|.
A = List()
if dfsnum[w] < dfsnum[target(e)]:
# tree edge
if not (strongly_planar(e, A)):
while S.IsNotEmpty():
S.Pop()
return 0
else:
A.append(dfsnum[target(e)]) # a back edge
# UPDATE STACK |S| OF ATTACHMENTS
# The list |A| contains the ordered list of attachments
# of segment "S(e)".
# We create an new block consisting only of segment "S(e)"
# (in its L-part) and then combine this block with the
# topmost block of stack |S| as long as there is interlacing.
# We check for interlacing with the L-part.
# If there is interlacing then we flip the two sides of the
# topmost block.
# If there is still interlacing with the left side then the
# interlacing graph is non-bipartite and we declare the graph
# non-planar (and also free the storage allocated for the
# blocks).
# Otherwise we check for interlacing with the R-part.
# If there is interlacing then we combine |B| with the topmost
# block and repeat the process with the new topmost block.
# If there is no interlacing then we push block |B| onto |S|.
B = block(e, A)
while 1:
if B.left_interlace(S): (S.contents[-1]).flip()
if B.left_interlace(S):
del B
while S.IsNotEmpty():
S.Pop()
return 0
if B.right_interlace(S): B.combine(S.Pop())
else: break
S.Push(B)
# PREPARE FOR NEXT ITERATION
# We have now processed all edges emanating from vertex |w|.
# Before starting to process edges emanating from vertex
# |parent[w]| we remove |parent[w]| from the list of attachments
# of the topmost
# block of stack |S|.
# If this block becomes empty then we pop it from the stack and
# record the placement for all segments in the block in array
# |alpha|.
while (S.IsNotEmpty()
and (S.contents[-1]).clean(dfsnum[parent[w]], alpha, dfsnum)):
S.Pop()
w = parent[w]
#--------------------------------------------------------------
#--------------------------------------------------------------
# TEST STRONG PLANARITY AND COMPUTE Att
# We test the strong planarity of the segment "S(e0)".
# We know at this point that the interlacing graph is bipartite.
# Also for each of its connected components the corresponding block
# on stack |S| contains the list of attachments below |x|.
# Let |B| be the topmost block of |S|.
# If both sides of |B| have an attachment above |w0| then
# "S(e0)" is not strongly planar.
# We free the storage allocated for the blocks and return false.
# Otherwise (cf. procedure |add_to_Att|) we first make sure that
# the right side of |B| attaches only to |w0| (if at all) and then
# add the two sides of |B| to the output list |Att|.
# We also record the placements of the subsegments in |alpha|.
Att.clear()
while S.IsNotEmpty():
B = S.Pop()
if (not (B.empty_Latt()) and not (B.empty_Ratt())
and B.head_of_Latt() > dfsnum[w0]
and B.head_of_Ratt() > dfsnum[w0]):
del B
while S.IsNotEmpty():
S.Pop()
return 0
B.add_to_Att(Att, dfsnum[w0], alpha, dfsnum)
del B
# Let's not forget that "w0" is an attachment
# of "S(e0)" except if w0 = x.
if w0 != x: Att.append(dfsnum[w0])
return 1
def TreeCoords(G, root, orientation):
S = Stack()
visited = {}
d = {}
leaves = []
number_of_leaves = 0
height = 0
nodes = {}
children = {}
father = {}
for v in G.vertices:
visited[v] = 0
visited[root] = 1
S.Push(root)
d[root] = 0
nodes[0] = []
children[root] = []
father[root] = None
while S.IsNotEmpty():
v = S.Pop()
if orientation=="vertical":
nodes[d[v]].insert(0,v)
if v!=root: children[father[v]].insert(0,v)
else:
nodes[d[v]].append(v)
if v!=root: children[father[v]].append(v)
isleaf = 1
for w in G.InOutNeighbors(v):
if visited[w] == 0:
isleaf = 0
visited[w] = 1
d[w] = d[v] + 1
children[w] = []
father[w] = v
if d[w]>height:
height = d[w]
nodes[height] = []
S.Push(w)
if isleaf:
number_of_leaves = number_of_leaves + 1
if orientation=="vertical":
leaves.insert(0,v)
else:
leaves.append(v)
# Test whether the graph is connected and
# acyclic.(=test whether the graph is a tree)
for v in G.vertices:
if visited[v]==0:
showwarning("Warning",
"Graph is not a tree,\n"
"not connected !!!")
return 0
ch_len = len(children[v])
if v!=root: ch_len = ch_len + 1
if ch_len<len(G.InOutNeighbors(v)):
showwarning("Warning",
"Graph is not a tree,\n"
"contains cycles !!!")
return 0
if number_of_leaves<=19:
dist1 = 50
else:
dist1 = 900 / (number_of_leaves-1)
if height+1<=19:
dist2 = 50
else:
dist2 = 900 / height
if dist1<25 or dist2<30:
showwarning("Warning",
"Tree-Layout not possible,\n"
"the tree is too large !!!")
return 0
Coord1 = {}
Coord2 = {}
i = 0
for v in leaves:
Coord1[v] = 50 + i * dist1
Coord2[v] = 50 + d[v] * dist2
i = i + 1
i = height - 1
while i>=0:
for v in nodes[i]:
if children[v]!=[]:
Coord2[v] = 50 + d[v] * dist2
if len(children[v])==1:
Coord1[v] = Coord1[children[v][0]]
else:
Coord1[v] = ( Coord1[children[v][0]] +
(Coord1[children[v][-1]] -
Coord1[children[v][0]]) / 2)
i=i-1
if orientation=="vertical":
G.xCoord=Coord1
G.yCoord=Coord2
else:
G.xCoord=Coord2
G.yCoord=Coord1
return 1
