def add_next_dominators(list_of_next_dominators: list,
args: argparse.ArgumentParser):
"""
Description: Add next dominators to connected dominating set
Args:
list_of_next_dominators (list): A list with next dominators
Returns:
-
"""
import graph as g
# Sort list of next dominators by how important are
sorted_list_of_next_dominators = sorted(list_of_next_dominators.items(),
key=operator.itemgetter(1))
# Add next dominators until DS be connected
for node in sorted_list_of_next_dominators:
connected_dominating_set[node[0]] = node[1]
g.add_node(node[0], False)
add_dominator_to_all_nodes(node[0])
remove_nodes_from_dominatees([node[0]])
write_message(args, "[+] Add to DS node with name {}".format(node[0]),
"INFO")
connectivity_list = check_connectivity(
dict_of_objects[list(connected_dominating_set.keys())[0]], [],
connected_dominating_set)
if len(
set(connectivity_list) & set(list(dict_of_objects.keys()))
) == len(connected_dominating_set) and all_dominees_have_dominators():
break
def draw_graph(counter_total, counter_lives, counter_deaths, n=20):
"""Draw graph of survival depending on sequence.
Parameters:
counter_total - Counter object with total number of sequences
counter_lives - Counter object with number of sequences without death date
counter_deaths - Counter object with number of sequences with death date
n - specifies how many of the sequences with highest death rate should be printed to output. If set to 0 then all sequences will be printed
"""
print 'Creating graph'
node_labels = {}
edge_labels = {}
graph = nx.DiGraph()
graph.add_node(0)
node_labels[0] = 'End'
i = 1
for k, v in counter_total.most_common(n) if n else counter_total.most_common():
lastI = 0
for medicine in reversed(k.split(';')):
graph.add_edge(i, lastI)
edge_labels[(i, lastI)] = medicine
lastI = i
i += 1
node_labels[lastI] = '{0}%'.format(100 * counter_deaths[k] / v)
print 'Graph created'
layout = nx.graphviz_layout(graph)
print 'Graph layout created'
nx.draw(graph, pos = layout, hold = True, node_color = 'w', node_size = 1000)
nx.draw_networkx_labels(graph, layout, labels = node_labels)
nx.draw_networkx_edge_labels(graph, layout, edge_labels = edge_labels)
plt.show()
def amr_2_graph(sentence, graph):
if sentence[0] != '(' or sentence[-1] != ')':
raise Exception("Error: Initial and closing character should be parenthesis.")
sentence = sentence[1:-1]
if re.search('([^:)(]*)([:)(].*)', sentence):
root, sentence = re.search('([^:)(]*)([:)(].*)', sentence).group(1, 2)
else:
root = sentence
sentence = ""
graph.add_node(root)
while sentence.find(':') >= 0:
terminal = False
argument, sentence = re.search('(:[^ ]+) ?(.*)', sentence).group(1, 2)
child_node = None
if sentence[0] == '(':
subgraph, sentence = find_closing_parenthesis(sentence)
child_node = amr_2_graph(subgraph, graph)
else:
child_node, sentence = re.search('([^ ]+) ?(:.*)?', sentence).group(1, 2)
if not sentence: sentence = ""
terminal = True
graph.add_edge(root, child_node, argument, terminal=terminal)
return root
def toDOT(self, label=''):
"""
Convert a Structure object to a graph image via DOT. This is useful
for visualizing the functional groups that make up the databases. The
output is a string containing a graph in DOT format, which can be
passed to graphviz to produce an image; neato is recommended.
Atoms are visualized as vertices in the outputted graph. Vertices are
labeled with the atom type(s) of each corresponding atom. Labeled atoms
('\*', '\*1', etc.) are color-coded, with a unique color for each label.
Bonds are indicated with edges; multiple bonds are represented by
multiple edges between the same pair of vertices. The edge line style is
used to denote further semantic information: dashed lines indicate
optional higher-order bonds, while dotted lines indicate benzene bonds.
"""
import pydot
graph = pydot.Dot(size='5,4', rankdir='LR',
graph_type='graph', simplify=True, fontsize='8',
overlap='true', dpi='85',center="True")
# List of atoms (vertices)
for i, atom in enumerate(self.atoms()):
# Generate vertex label from atom type labels
label = ','.join([atomType.label for atomType in atom._atomType])
# Labeled atoms are color coded
color = 'black'
if atom.label != '':
colors = {'*': 'red', '*1': 'red', '*2': 'green', '*3': 'blue', '*4': 'yellow', '*5': 'purple', '*6': 'orange', '*7': 'magenta', '*8': 'cyan'}
color = colors[atom.label]
# Create and add vertex to graph
node = pydot.Node(str(i+1), label=label, color=color, fontcolor=color)
graph.add_node(node)
# List of bonds (edges)
for i, bond in enumerate(self.bonds()):
index1 = self.atoms().index(bond.atoms[0])
index2 = self.atoms().index(bond.atoms[1])
single = False; double = False; triple = False; benzene = False
for type in bond._bondType:
if type.order == 1: single = True
if type.order == 2: double = True
if type.order == 3: triple = True
if type.order == 1.5: benzene = True
label = []
if single: label.append('S')
if double: label.append('D')
if triple: label.append('T')
if benzene: label.append('B')
label = ','.join(label)
# Create and add edge to graph
edge = pydot.Edge(str(index1+1), str(index2+1), label=label, len='2')
graph.add_edge(edge)
return graph
def test_depth_first():
graph = Graph()
A = graph.add_node('A')
B = graph.add_node('B')
C = graph.add_node('C')
D = graph.add_node('D')
E = graph.add_node('E')
F = graph.add_node('F')
G = graph.add_node('G')
H = graph.add_node('H')
graph.add_edge(A,B)
graph.add_edge(A,D)
graph.add_edge(D,E)
graph.add_edge(D,H)
graph.add_edge(D,F)
graph.add_edge(B,C)
graph.add_edge(C,G)
output = graph.depth_first(A)
assert output[0] == A
assert output[1] == B
assert output[2] == C
assert output[3] == G
assert output[4] == D
assert output[5] == E
assert output[6] == H
assert output[7] == F
def add_API_nodes(name):
""" Queries the API for a list of related nodes from the current_node and
their relationships to be added to the database.
The process is multithreaded."""
add_node(name)
start_time = time.time()
all_links = get_top_links(name)
if all_links is None:
return None
# avoids stupid quotations breaking queries
all_links = [
link for link in all_links if not contains_quotes(link["title"])
]
threads = []
for link in all_links:
#print link
q = Queue()
print link
try:
link["name"] = link.pop("title")
link.pop("ns")
except:
pass
if not node_exists(link):
print 'node does not exist '
add = lambda x: add_node(x)
q.put(add)
# otherwise always add relationship
edge = lambda x, y, z: add_edge(x, y, z)
q.put(edge)
t = threading.Thread(target=process, args=(q, name, link))
threads.append(t)
t.start()
[thread.join() for thread in threads]
print "--- adding nodes took %s seconds ---" % (time.time() - start_time)
return True
def load_nodes(graph):
with open(AUTHORS_FILE,'r') as f:
line = f.readline()
while line != "":
line = line[len("#index "):] # remove index prefix from line
a_id = line.strip() # 1st line (stripped) is author's index
line = f.readline() # read next line
line = line[len("#n "):] # remove name prefix from line
if line.strip() == "": # make sure name isn't empty
line = "<empty_" + a_id + ">"
name = line.strip() # 2nd line (stripped) is author's name
auth = author.Author(int(a_id), name) # create author and
graph.add_node(auth) # add it to the graph
#if graph.number_of_nodes() % 100000 == 0:
# print graph.number_of_nodes()
while line.strip() != "": # ignore additional author details and read next line
line = f.readline()
line = f.readline()
def load_nodes(graph):
with open(AUTHORS_FILE, 'r') as f:
line = f.readline()
while line != "":
line = line[len("#index "):] # remove index prefix from line
a_id = line.strip() # 1st line (stripped) is author's index
line = f.readline() # read next line
line = line[len("#n "):] # remove name prefix from line
if line.strip() == "": # make sure name isn't empty
line = "<empty_" + a_id + ">"
name = line.strip() # 2nd line (stripped) is author's name
auth = author.Author(int(a_id), name) # create author and
graph.add_node(auth) # add it to the graph
#if graph.number_of_nodes() % 100000 == 0:
# print graph.number_of_nodes()
while line.strip(
) != "": # ignore additional author details and read next line
line = f.readline()
line = f.readline()
def test_breadth_first():
graph = Graph()
a = graph.add_node('a')
b = graph.add_node('b')
c = graph.add_node('c')
d = graph.add_node('d')
e = graph.add_node('e')
f = graph.add_node('f')
g = graph.add_node('g')
h = graph.add_node('h')
i = graph.add_node('i')
k = graph.add_node('k')
graph.add_edge(a, b)
graph.add_edge(a, c)
graph.add_edge(a,e)
graph.add_edge(b, d)
graph.add_edge(c, f)
graph.add_edge(c, b)
graph.add_edge(e,g)
graph.add_edge(f,h)
graph.add_edge(g,h)
graph.add_edge(f,i)
graph.add_edge(h,k)
graph.add_edge(i,k)
assert len(graph.breadth_first(a)) == 10
breadth = graph.breadth_first(a)
assert breadth[0].value == 'a'
assert breadth[1].value == 'b'
assert breadth[2].value == 'c'
assert breadth[3].value == 'e'
assert breadth[4].value == 'd'
assert breadth[5].value == 'f'
assert breadth[6].value == 'g'
assert breadth[7].value == 'h'
assert breadth[8].value == 'i'
assert breadth[9].value == 'k'
def test_graph():
# check for successful input
graph = Graph()
a = graph.add_node('a')
assert a.value == 'a'
b = graph.add_node('b')
c = graph.add_node('c')
d = graph.add_node('d')
e = graph.add_node('e')
f = graph.add_node('f')
# check the get_nodes function
assert graph.get_nodes()[0].value == 'a'
assert graph.get_nodes()[1].value == 'b'
assert graph.get_nodes()[5].value == 'f'
# check if the add_edges and get_neighbors are working properly
graph.add_edge(a, c)
graph.add_edge(a, d)
graph.add_edge(b, c)
graph.add_edge(b, f)
graph.add_edge(c, a)
graph.add_edge(c, b)
graph.add_edge(c, e)
graph.add_edge(d, a)
graph.add_edge(d, e)
graph.add_edge(e, c)
graph.add_edge(e, d)
graph.add_edge(e, f)
graph.add_edge(f, b)
graph.add_edge(f, e)
assert graph.get_neighbors(a)[0].node.value == 'c'
assert graph.get_neighbors(a)[1].node.value == 'd'
# testing the size method
assert graph.size()==6
# check for empty graph
graph2 = Graph()
assert graph2.get_nodes() == None
def add_dominatee_to_CDS(args: argparse.ArgumentParser):
"""
Description: Add dominatee to CDS
Args:
args (obj): An object with all user input arguments
Returns:
- or ERROR_CODE
"""
import graph as g
sequense_size = 1
next_node = 0
nodes_list = []
_add_dominatee = False
while not _add_dominatee:
try:
nodes_list = [get_list_of_dominatees()[next_node][0]]
except Exception as err:
write_message(args, err, "ERROR")
next_node = 0
sequense_size += 1
if sequense_size > 1:
for i in range(int(args.k)):
if next_node < len(get_list_of_dominatees()):
nodes_list = find_sequense_nodes(nodes_list,
get_list_of_dominatees())
if next_node >= len(get_list_of_dominatees()) or sequense_size > int(
args.k):
next_node = 0
sequense_size += 1
if sequense_size > int(args.k):
write_message(
args, "Input file with name {} cannot create {}-{} CDS",
"INFO")
return
dom_list = []
for node in nodes_list:
if len(dict_of_objects[node].get_dominators()) >= int(
args.k) - sequense_size + 1:
dom_list.append(node)
if len(dom_list) >= int(args.k):
break
for node in dom_list:
_add_dominatee = True
connected_dominating_set[node] = 1
add_dominator_to_all_nodes(node)
remove_nodes_from_dominatees([node])
g.add_node(node)
next_node += 1
if sequense_size > int(args.k):
write_message(
args, "This input network cannot create {}-{}-MCDS".format(
args.k, args.m), "INFO")
return -1
def find_MCDS(args: argparse.ArgumentParser):
"""
Description: Minimize existing connected dominating set (CDS)
Args:
-
Returns:
-
"""
import graph
write_message(args,
"[!] CDS created. Need to minimize CDS and create MCDS",
"INFO")
write_message(args, "[!] Start to minimize CDS", "INFO")
counter = 0
pbar = tqdm(total=len(connected_dominating_set), initial=counter)
while counter < len(connected_dominating_set) and len(
connected_dominating_set) > 1:
# Remove dominator from DS to find out if it needs
key = list(connected_dominating_set.items())[counter][0]
value = connected_dominating_set.pop(key)
write_message(args, "[!] Try to remove node with name {}".format(key),
"INFO")
# Check if every dominatee has dominator
all_nodes = []
if int(args.algorithm) == 1 or int(args.algorithm) == 2:
# for key1 in tqdm(connected_dominating_set):
for key1 in connected_dominating_set:
all_nodes = all_nodes + dict_of_objects[key1].get_N_of_u()
if key1 not in all_nodes:
all_nodes.append(key1)
if int(args.algorithm) == 2:
# for node in tqdm(dict_of_objects):
for node in dict_of_objects:
node_obj = dict_of_objects[node]
if key in node_obj.get_dominators():
node_obj.add_temp_dominator(key)
node_obj.get_dominators().remove(key)
# Check if DS is connected without dominator
connectivity_list = check_connectivity(
dict_of_objects[list(connected_dominating_set.keys())[0]], [],
connected_dominating_set)
all_nodes = dict_of_objects[list(connected_dominating_set.keys())
[0]].remove_duplicate(all_nodes)
if not len(set(connectivity_list) & set(connected_dominating_set)
) == len(connected_dominating_set) or not len(
set(all_nodes)
& set(dict_of_objects)) == len(dict_of_objects):
connected_dominating_set[key] = value
write_message(
args,
"[!] Node with name {} cannot be removed because CDS will disconnected"
.format(key), "INFO")
counter += 1
pbar.update(1)
else:
write_message(
args, "[-] Node with name {} removed from CDS".format(key),
"INFO")
message = "New CDS with out node {} is [%s]" % ", ".join(
[a for a in connected_dominating_set])
message = message.format(key)
write_message(args, message, "DEBUG")
if int(args.algorithm) == 2:
# for node in tqdm(dict_of_objects):
for node in dict_of_objects:
node_obj = dict_of_objects[node]
if key in node_obj.get_temp_dominators():
node_obj.get_dominators().append(key)
node_obj.delete_temp_dominator(key)
node_obj.clear_temp_dominators()
else:
import graph as g
g.remove_node(key)
write_message(
args, "Try to remove dominator from neighbor for all nodes...",
"INFO")
# for node in tqdm(dict_of_objects):
for node in dict_of_objects:
node_obj = dict_of_objects[node]
try:
node_obj.get_dominators().remove(key)
node_obj.add_temp_dominator(key)
except Exception:
pass
write_message(
args,
"Check if network is connected without node {}".format(key),
"INFO")
if all_dominators_have_k_dominators(int(
args.k)) and all_dominees_have_m_dominators(int(
args.m)) and g._is_k_connected(args):
# for node in tqdm(dict_of_objects):
for node in dict_of_objects:
node_obj = dict_of_objects[node]
node_obj.clear_temp_dominators()
write_message(
args, "[-] Node with name {} removed from CDS".format(key),
"INFO")
else:
connected_dominating_set[key] = value
# for node in tqdm(dict_of_objects):
for node in dict_of_objects:
node_obj = dict_of_objects[node]
if key in node_obj.get_temp_dominators():
node_obj.get_dominators().append(key)
node_obj.delete_temp_dominator(key)
node_obj.clear_temp_dominators()
g.add_node(key)
add_dominator_to_all_nodes(key)
write_message(
args,
"[!] Node with name {} cannot be removed because CDS will disconnected"
.format(key), "INFO")
counter += 1
pbar.update(1)
pbar.close()
import graph
from collections import namedtuple
import re, sys
infile = sys.argv[1]
infile = open(infile, "r")
graph = graph.Graph()
for i, line in enumerate(infile):
if i == 1:
s = line.split(', ')
if i > 2:
nodes = graph.get_nodes()
words = line.split()
if words[0] not in graph.get_nodes():
graph.add_node(words[0])
elif words[1] not in graph.get_nodes():
graph.add_node(words[1])
graph.add_edge(int(words[0]), int(words[1]), int(words[2]))
print(graph.get_nodes())
graph.dijkstra(1, 10)
map = osmapi.OsmApi().Map(-3.9524, 38.9531 , -3.8877, 39.0086)
for map_dict in map:
# Selecionamos las vías
list_nodes = []
if map_dict['type'] == 'way':
if 'highway' in map_dict['data']['tag'] and map_dict['data']['tag']['highway'] in ['trunk', 'residential', 'pedestrian']:
way_dict = osmapi.OsmApi().WayGet(map_dict['data']['id'])
list_nodes.append(way_dict['nd'])
for i, node in enumerate(list_nodes):
if not graph.node_exist(node):
if i == 0:
node_aux = osmapi.OsmApi().NodeGet(node)
node_dic = {'lat' : node_aux['lat'], 'lon' : node_aux['lon'], 'id' : node_aux['id'], 'edges' : []}
graph.add_node(node_dic)
else:
node_aux = osmapi.OsmApi().NodeGet(node)
node_dic = {'lat' : node_aux['lat'], 'lon' : node_aux['lon'], 'id' : node_aux['id'], 'edges': []}
graph.add_node(node_dic)
graph.add_edge(list_nodes[i], list_nodes[i-1], 0)
graph.add_edge(list_nodes[i-1], list_nodes[i], 0)
else:
if i != 0:
graph.add_edge(list_nodes[i], list_nodes[i-1], 0)
graph.add_edge(list_nodes[i-1], list_nodes[i], 0)
# Impresión de las aristas de los nodos.
for i, node in enumerate(list_nodes):
print("[nodo]",node,"->", graph.nodes[node]['edges'])
if 'highway' in map_dict['data']['tag'] and map_dict['data']['tag'][
'highway'] in ['trunk', 'residential', 'pedestrian']:
way_dict = osmapi.OsmApi().WayGet(map_dict['data']['id'])
list_nodes.append(way_dict['nd'])
for i, node in enumerate(list_nodes):
if not graph.node_exist(node):
if i == 0:
node_aux = osmapi.OsmApi().NodeGet(node)
node_dic = {
'lat': node_aux['lat'],
'lon': node_aux['lon'],
'id': node_aux['id'],
'edges': []
}
graph.add_node(node_dic)
else:
node_aux = osmapi.OsmApi().NodeGet(node)
node_dic = {
'lat': node_aux['lat'],
'lon': node_aux['lon'],
'id': node_aux['id'],
'edges': []
}
graph.add_node(node_dic)
graph.add_edge(list_nodes[i], list_nodes[i - 1], 0)
graph.add_edge(list_nodes[i - 1], list_nodes[i], 0)
else:
if i != 0:
graph.add_edge(list_nodes[i], list_nodes[i - 1], 0)
