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directed_graph.py
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directed_graph.py
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from compas.datastructures.network import Network
from compas_fab.fab.geometry import Frame, Transformation
from compas.geometry.elements import Line
from compas.geometry import distance_point_point
from collections import deque
import random as r
from graphviz import Digraph
from heap import Heap
import random
import operator
r.seed(1)
__author__ = 'Augusto Gandia'
__copyright__ = 'Copyright 2018, Gramazio Kohler Research - ETH Zurich'
__license__ = 'MIT'
__email__ = '[email protected]'
def setup(rawData):
cities = list()
#Create and return sorted data in list
data = list()
for line in rawData:
item = list()
temp = line.split()
item.extend([temp[0],temp[1],int(temp[2])])
cities.extend([temp[0],temp[1]])
data.append(item)
return sorted(data, key=operator.itemgetter(2)),sorted(set(cities))
def depth_first_tree(adjacency, root):
"""Construct a spanning tree using a depth-first search.
Parameters
----------
adjacency : dict
An adjacency dictionary.
root : hashable
The identifier of the root node.
Returns
-------
list
List of nodes in depth-first order.
dict
Dictionary of predecessors for each of the nodes.
list
The depth-first paths.
"""
adjacency = {key: set(nbrs) for key, nbrs in iter(adjacency.items())}
tovisit = [root]
visited = set()
ordering = []
predecessors = {}
paths = [[root]]
#if there are nodes in tovisit
while tovisit:
# pop the last added element from the stack
node = tovisit.pop()
if node not in visited:
# add node to last path
paths[-1].append(node)
# mark the node as visited
visited.add(node)
ordering.append(node)
# add the unvisited nbrs to the stack
nodes = adjacency [node] - visited
# if there still not visited nbrs
if nodes:
for child in nodes:
predecessors[child] = node
else:
paths.append([])
tovisit.extend(nodes)
if not len(paths[-1]):
del paths[-1]
return ordering, predecessors, paths
def breadth_first_tree(adjacency, root):
tovisit = deque([root])
visited = set([root])
ordering = [root]
predecessors = {}
paths = []
while tovisit:
node = tovisit.popleft()
for nbr in adjacency[node]:
if nbr not in visited:
predecessors[nbr]=node
tovisit.append(nbr)
visited.add(nbr)
ordering.append(nbr)
else:
path = [node]
while path[-1] in predecessors:
path.append(predecessors[path[-1]])
paths.append(list(reversed(path)))
return ordering, predecessors, paths
def init(E):
nodes = {}
for e in E:
nodes[e] = None
return nodes
def find(nodes, U):
if U not in nodes:
print('Find failed: ' + str(U) + ' not found')
return None
if nodes[U] == None:
return U
return find(nodes,nodes[U])
def union(nodes,U0,U1):
U1_temp = find(nodes,U1)
U0_temp = find(nodes,U0)
if U1_temp == None or U0_temp == None:
failed = []
if U0_temp == None:
failed.append(U0)
if U1_temp == None:
failed.append(U1)
print('\nUnion failed: Element(s) ' + str(failed) + ' not found\n')
return None
if U0_temp != U1_temp:
nodes[U0_temp] = U1_temp
return U1_temp
# Method to perform Kruskal's Algorithm
def kruskal(data,cities):
distance = 0
result = list()
cities = init(cities)
for edge in range(len(data)):
path = data.pop(0)
#If the two cities in the path do not have the same
#canonical representative, join them together, then
#add path to result and calculate distance
if find(cities,path[0]) != find(cities,path[1]):
union(cities, path[0],path[1])
result.append(path[0])
result.append(path[1])
result.append(path[2])
distance += path[2]
return result,distance
def midpoint_point_point(a, b):
return [0.5 * (a[0] + b[0]),
0.5 * (a[1] + b[1]),
0.5 * (a[2] + b[2])]
def midpoint_line(line):
return midpoint_point_point(*line)
def vertex_neighbours(self,key):
"""Return the neighbours of a vertex."""
return list(self.halfedge[key])
def edge_connected_edges(self, u, v):
edges = []
for nbr in vertex_neighbours(self,u):
if nbr in self.edge[u]:
edges.append((u, nbr))
else:
edges.append((nbr, u))
for nbr in vertex_neighbours(self,v):
if nbr in self.edge[v]:
edges.append((v, nbr))
else:
edges.append((nbr, v))
return edges
def delete_vertex(self, key): #This could be removed in newer versions of compas
for nbr in self.vertex_neighbours(key):
del self.halfedge[key][nbr]
del self.halfedge[nbr][key]
if key in self.edge and nbr in self.edge[key]:
del self.edge[key][nbr]
else:
del self.edge[nbr][key]
del self.vertex[key]
del self.halfedge[key]
del self.edge[key]
class ToleranceNetwork(Network):
"""multiple networks for tolerance analysis of spatial structures """
def __init__(self, edges_joint, edges_beam, ordered_beams, weights_list):
super(ToleranceNetwork, self).__init__()
input_dict = {'edges_joint': edges_joint, 'edges_beam': edges_beam, 'ordered_beams': ordered_beams}
self.attributes.update(input_dict)
self.generate_vertices()
self.generate_joint_edges()
self.store_connectivity_in_member_edges()
self.generate_topology_network(weights_list)
self.MST_Kruskal()
#self.draw_MST_Kruskal()
def MST_Kruskal(self):
#Adjacency dictionary for COMPAS deph_first_tree
adjacency_dictionary=self.topology_network.adjacency_dictionary
#Sort
r = []
#Iterate nodes
for n in adjacency_dictionary:
parent_weight = self.topology_network.get_vertex_attribute(n, 'weight')
#Iterate neighbours of each node
for nbr in adjacency_dictionary[n]:
child_weight = self.topology_network.get_vertex_attribute(nbr, 'weight')
parent = [str(nbr), str(n), parent_weight]
child = [str(n), str(nbr), child_weight]
if parent_weight > child_weight:
r.append(parent)
if child in r:
r.remove(child)
else:
r.append(child)
if parent in r:
r.remove(parent)
r = sorted(r, key=operator.itemgetter(2))
data = r
cities = map(str, self.topology_network.vertices())
result,distance = kruskal(data,cities)
self.result=result
# print self.result, distance
#Remove duplicates
assembly_sequence=[]
#for step in self.result[1:][::3]:
for step in self.result:
#skip weights and remove multiple connections to add beam
if isinstance(step, str) and step not in assembly_sequence:
assembly_sequence.append(step)
self.assembly_sequence = assembly_sequence
def draw_MST_Kruskal(self):
#adjacency_dictionary
adjacency_dictionary=self.topology_network.adjacency_dictionary
#color convention
color="/rdbu8/"
#setup
directed_graph=Digraph(format='png')
directed_graph.attr(ranksep='7', resolution='80', lheight='1000', lwidth='2000', smoothing='true')#, bgcolor='transparent')
root=self.assembly_sequence[0]
#add Root
directed_graph.node(root, fontsize='60', width='3', fixedsize='true', shape='circle', label='Beam '+str(root), style='filled', color=color+str(1))#label='beam '+str(root) #Brewer colors http://graphviz.org/doc/info/colors.html#brewer
#add nodes and edges returned from assembly sequence
for n in self.assembly_sequence:
weight=self.topology_network.get_vertex_attribute(int(n), 'weight')
directed_graph.node(n, fontsize='60', width='3', fixedsize='true', shape='circle', label='Beam '+str(n), style='filled', color=color+str(weight))#, color='transparent')
weighted_edges=[self.result[int(i):int(i) + 3] for i in range(0, len(self.result), 3)]
for e in weighted_edges:
directed_graph.edge(e[0],e[1], headlabel=str(e[2]), labeldistance='6', fontsize='60', arrowsize='3')#, fontcolor=color+str(int(weight)))
directed_graph.render(filename = 'C:/Users/gandiaa/Documents/projects/tolerance_analysis/connectivity_graph', cleanup=True)
"""
#adjacency_dictionary
adjacency_dictionary=self.topology_network.adjacency_dictionary
#set root
root=str(self.paths[0][0])
#setup
directed_graph=Digraph(format='png')#format='png')
directed_graph.attr(ranksep='7', resolution='80', lheight='1000', lwidth='2000', smoothing='true', bgcolor='transparent')
#color convention
color="/rdbu8/"
#add Root
#directed_graph.node(root, fontsize='60', width='3', fixedsize='true', shape='circle', label='Beam '+str(root), style='filled', color=color+str(1))#label='beam '+str(root) #Brewer colors http://graphviz.org/doc/info/colors.html#brewer
#add nodes and edges returned from breadth_first tree
added_edges=[]
for tree in self.paths:
level=int(len(tree)-1)
node=str(tree[level])
color_by_weight=self.topology_network.get_vertex_attribute(int(node), 'weight')
directed_graph.node(node, fontsize='60', width='3', fixedsize='true', shape='circle', label='Beam '+str(node), style='filled', color='transparent')# color=color+str(color_by_weight))#width='0.5', fixedsize='true', label='beam '+str(node)#Brewer colors http://graphviz.org/doc/info/colors.html#brewer
if len(tree) != 1:
parent=str(tree[len(tree)-2])
child=str(tree[len(tree)-1])
i=self.paths.index(tree)-1
weight=self.breadth_first_weighted_edges[i].split(' ')[2]
directed_graph.edge(parent,child, headlabel=str(weight), labeldistance='6', fontsize='60', arrowsize='3')#, fontcolor=color+str(int(weight)))
added_edges.append((parent,child))
#add not selected edges
for ordered_node in self.ordering:
for connected_node in adjacency_dictionary[ordered_node]:
ordered_node=str(ordered_node)
connected_node=str(connected_node)
if (ordered_node,connected_node) not in added_edges and (connected_node,ordered_node) not in added_edges:
weight=self.topology_network.get_vertex_attribute(int(connected_node), 'weight')
directed_graph.edge(ordered_node,connected_node,constraint='false', color='grey80')
added_edges.append((ordered_node,connected_node))
counter=0
for key in self.assembly_sequence:
#for node in list(directed_graph)[3:]:
for node in directed_graph.body:
key = str(key)
if node.startswith('\t%s [' % key):
weight=self.topology_network.get_vertex_attribute(int(key), 'weight')
index=directed_graph.body.index(node)
directed_graph.body[index]=directed_graph.body[index].replace('style=filled', 'style=filled,color="/rdbu8/'+str(weight)+'"')
#directed_graph.render(filename = 'C:/Users/gandiaa/Documents/projects/tolerance_analysis/connectivity_graph_'+str(counter), cleanup=True)
counter+=1
#render
#directed_graph.render(filename = 'C:/Users/gandiaa/Documents/projects/tolerance_analysis/connectivity_graph', cleanup=True)
"""
def generate_vertices(self):
#add in network, vertices of edge beams
for index in range(len(self.attributes ['edges_beam'])):
#add edge vertex u
position = self.attributes ['edges_beam'][index][0]
u=self.add_vertex(attr_dict={'x': position[0], 'y' : position[1], 'z' : position[2], 'vertex_type': 'member'})
#add edge vertex v
position = self.attributes ['edges_beam'][index][1]
v=self.add_vertex(attr_dict={'x': position[0], 'y' : position[1], 'z' : position[2], 'vertex_type': 'member'})
#add attribute edge type and asociate beam
neighbours_member_edges=[]
self.add_edge(u,v, {'edge_type': 'member','beam': self.attributes ['ordered_beams'][index], 'u_coordinate':self.vertex_coordinates(u), 'v_coordinate': self.vertex_coordinates(v), 'neighbours_member_edges': neighbours_member_edges})
def generate_joint_edges(self):
store_beam_u=[]
store_beam_v=[]
for edge_joint in range (len(self.attributes['edges_joint'])):
joint_u=self.attributes ['edges_joint'][edge_joint][0]
joint_v=self.attributes ['edges_joint'][edge_joint][1]
for u,v,attr in self.edges(data=True):
beam_u=attr['u_coordinate']
beam_v=attr['v_coordinate']
if distance_point_point(joint_u,beam_u) < 50:
joint_new_vertex_u=[]
joint_new_vertex_u.append(u)
if distance_point_point(joint_u,beam_v) < 50:
joint_new_vertex_u=[]
joint_new_vertex_u.append(v)
if distance_point_point(joint_v,beam_u) < 50:
joint_new_vertex_v=[]
joint_new_vertex_v.append(u)
if distance_point_point(joint_v,beam_v) < 50:
joint_new_vertex_v=[]
joint_new_vertex_v.append(v)
store_beam_u.append(joint_new_vertex_u[0])
store_beam_v.append(joint_new_vertex_v[0])
for iterate in range(len(store_beam_v)):
self.add_edge(store_beam_u[iterate], store_beam_v[iterate], {'edge_type': 'joint','beam': None})
def store_connectivity_in_member_edges(self):
#store connectivity in joint edges
for u,v,attr in self.edges(data=True):#181
if attr['edge_type']=='joint':
connected_joint_edges_list=edge_connected_edges(self,u,v) #per beam edge a list of connected joint edges
prev_list=[]
#filter connected joint edges and store connected member edges
for joint_edge in connected_joint_edges_list:
if self.get_edge_attribute(joint_edge[0],joint_edge[1],'edge_type')=='member':
prev_list.append((joint_edge[0],joint_edge[1]))
#get existing neighbours from first edge
first_edge_neighbours=self.get_edge_attribute(prev_list[0][0],prev_list[0][1],'neighbours_member_edges')
first_edge_neighbours.append(prev_list[1])
#get existing neighbours from second edge
sec_edge_neighbours=self.get_edge_attribute(prev_list[1][0],prev_list[1][1],'neighbours_member_edges')
sec_edge_neighbours.append(prev_list[0])
def generate_topology_network(self, weights_list):
#this "topology network" is an inversion of the "geometry_network" by turning beams into vertices
self.topology_network=TopologyNetwork(self, weights_list)
class TopologyNetwork(Network):
def __init__(self, geometry_network, weights_list):
super(TopologyNetwork, self).__init__()
input_dict = {'edges': geometry_network.edges(data=True)}
self.attributes.update(input_dict)
self.invert_network(weights_list)
def invert_network(self, weights_list):
#to translate from member being an edge to member being a vertex
#only the u value of each member is used and divided by 2.
#thus it turns from being (u=0,u=2,u=4...) to (u=0,u=1,u=2...)
#iter member edges of geometry network
for u,v,attr in self.attributes['edges']:
if attr['edge_type']=='member':
#get midpoint for each member edge of geometry network
beam_edge_mid=midpoint_line((attr['u_coordinate'],attr['v_coordinate']))
#create new vertex and use as coordinate the midpoint of u and v
self.add_vertex(attr_dict={'x': beam_edge_mid[0], 'y' : beam_edge_mid[1], 'z' : beam_edge_mid[2]})#add beam_vertex
#create adjacency dictionary
adjacency_dict={}
for u,v,attr in self.attributes['edges']:
if attr['edge_type']=='member':
temp_connected_vertex=[]
#iter connected member edges of geometry network
for connected_vertices in attr['neighbours_member_edges']:
#store connected member as its u value divided by 2
temp_connected_vertex.append(connected_vertices[0]/2)
adjacency_dict[u/2]=temp_connected_vertex
#prepare adjacency dictionary for COMPAS traverse
self.adjacency_dictionary=adjacency_dict
#add adjacency and weight attribute to vertices
for u, attr in self.vertices(data=True):
self.set_vertex_attribute(u,'weight', weights_list[u])
self.set_vertex_attribute(u,'connected_vertices', adjacency_dict[u])
if __name__ == "__main__":
temp_frames_array = []