def graph_visualize(G, args):
import networkx as nx
import numpy as np
# ???????????????????????????
pos = nx.spring_layout(G)
# ?????? ????????????????????
plt.figure()
nx.draw_networkx(G, pos, with_labels=False, alpha=0.4,font_size=0.0,node_size=10)
plt.savefig(args.directory+"/graph/graph.png")
nx.write_gml(G, args.directory+"/graph/graph.gml")
# ??????
plt.figure()
degree_sequence=sorted(nx.degree(G).values(),reverse=True)
dmax=max(degree_sequence)
dmin =min(degree_sequence)
kukan=range(0,dmax+2)
hist, kukan=np.histogram(degree_sequence,kukan)
plt.plot(hist,"o-")
plt.xlabel('degree')
plt.ylabel('frequency')
plt.grid()
plt.savefig(args.directory+'/graph/degree_hist.png')
python类write_gml()的实例源码
def run(self):
logging.info("Grabbing Filling Metrics")
self.metricsCollector()
logging.info("Loading Reference")
self.loadReference()
logging.info("Removing Poorly Supported Edges")
self.cleanGraph()
logging.info("Outputting new contigs")
self.outputContigs()
logging.info("Finished!")
#g = nx.Graph()
#for i in self.subGraphs:
#for n in i.nodes():
#g.add_node(n)
#for e in i.edges():
#g.add_edge(*e)
#nx.write_gml(g,"output.gml")
def run(self):
logging.info("Grabbing Filling Metrics")
self.metricsCollector()
logging.info("Loading Reference")
self.loadReference()
logging.info("Removing Poorly Supported Edges")
self.cleanGraph()
logging.info("Outputting new contigs")
self.outputContigs()
logging.info("Finished!")
#g = nx.Graph()
#for i in self.subGraphs:
#for n in i.nodes():
#g.add_node(n)
#for e in i.edges():
#g.add_edge(*e)
#nx.write_gml(g,"output.gml")
def __output__(self, projectstructure, output=None):
_graphoutput = super(Directedgraph, self).__output__(projectstructure)
if output is None:
raise ValueError('output file be specified for Multipgraph output')
else:
networkx.write_gml(_graphoutput, output)
return True # TODO inconsistent return json object vs true
def visualize(G, savename, savegml):
pos = nx.spring_layout(G) # ???????????????????????????
nx.draw(G, pos, with_labels=True,alpha=0.3,font_size=0.0,node_size=10) # ?????? ????????????????????
plt.savefig(savename+".png")
plt.show()
if savegml:
nx.write_gml(G,savename+".gml")
def merge_node(path,new_path):
g = nx.read_gml(path)
nodes = [n for n,d in g.out_degree().items() if d==1]
for node in nodes:
if not node in g.nodes():
continue
if g.in_degree(node) != 1:
continue
p = g.successors(node)
#print p
#dict = g.in_degree(p)
#print dict[p]
#print g.in_degree(p)[p[0]]
if g.in_degree(p)[p[0]] == 1:
text1 = g.node[node]["text"]
text1 = remove_last_jump(text1)
text2 = g.node[p[0]]["text"]
#print text1
#print text2
new_text = text1 + ',' + text2
#print new_text
nns = g.successors(p[0])
g.node[node]["text"] = new_text
for n in nns:
g.add_edge(node, n)
g.remove_node(p[0])
nx.write_gml(g, new_path)
return nx.number_of_nodes(g)
def dag(recipe_folder, config, packages="*", format='gml', hide_singletons=False):
"""
Export the DAG of packages to a graph format file for visualization
"""
dag, name2recipes = utils.get_dag(utils.get_recipes(recipe_folder, packages), config)
if hide_singletons:
for node in nx.nodes(dag):
if dag.degree(node) == 0:
dag.remove_node(node)
if format == 'gml':
nx.write_gml(dag, sys.stdout.buffer)
elif format == 'dot':
write_dot(dag, sys.stdout)
elif format == 'txt':
subdags = sorted(map(sorted, nx.connected_components(dag.to_undirected())))
subdags = sorted(subdags, key=len, reverse=True)
singletons = []
for i, s in enumerate(subdags):
if len(s) == 1:
singletons += s
continue
print("# subdag {0}".format(i))
subdag = dag.subgraph(s)
recipes = [
recipe for package in nx.topological_sort(subdag)
for recipe in name2recipes[package]]
print('\n'.join(recipes) + '\n')
if not hide_singletons:
print('# singletons')
recipes = [recipe for package in singletons for recipe in
name2recipes[package]]
print('\n'.join(recipes) + '\n')
def extract_intra_function_cfg(name):
for seg in Segments():
if SegName(seg) == ".text":
#functions = Functions(seg)
#for func_ea in functions:
func_ea = here()
cfg = nx.DiGraph()
tmp_bbs = []
#flag FC_PREDS is to get the backward info
for bb in FlowChart(get_func(func_ea), flags=FC_PREDS):
#check if we have already met this bb
flag = True
for tmp_bb in tmp_bbs:
if tmp_bb.startEA == bb.startEA:
bb = tmp_bb
flag = False
if flag:
tmp_bbs.append(bb)
cfg.add_node(bb.startEA)
preds = bb.preds()
succs = bb.succs()
if preds:
for preds_block in preds:
#check if we have already met this bb
flag = True
for tmp_bb in tmp_bbs:
if tmp_bb.startEA == preds_block.startEA:
preds_block = tmp_bb
flag = False
if flag:
tmp_bbs.append(preds_block)
cfg.add_edge(preds_block.startEA, bb.startEA)
if succs:
for succs_block in preds:
#check if we have already met this bb
flag = True
for tmp_bb in tmp_bbs:
if tmp_bb.startEA == succs_block.startEA:
succs_block = tmp_bb
flag = False
if flag:
tmp_bbs.append(succs_block)
cfg.add_edge(bb.startEA, succs_block.startEA)
nx.write_gml(cfg, "C:\\Users\\Xu Zhengzi\\Desktop\\tt\\second.gml")
return cfg
def read_gml(path, relabel=False):
"""Read graph in GML format from path.
Parameters
----------
path : filename or filehandle
The filename or filehandle to read from.
relabel : bool, optional
If True use the GML node label attribute for node names otherwise use
the node id.
Returns
-------
G : MultiGraph or MultiDiGraph
Raises
------
ImportError
If the pyparsing module is not available.
See Also
--------
write_gml, parse_gml
Notes
-----
Requires pyparsing: http://pyparsing.wikispaces.com/
The GML specification says that files should be ASCII encoded, with any
extended ASCII characters (iso8859-1) appearing as HTML character entities.
References
----------
GML specification:
http://www.infosun.fim.uni-passau.de/Graphlet/GML/gml-tr.html
Examples
--------
>>> G=nx.path_graph(4)
>>> nx.write_gml(G,'test.gml')
>>> H=nx.read_gml('test.gml')
"""
lines = (unescape(line.decode('ascii')) for line in path)
G = parse_gml(lines, relabel=relabel)
return G
def pyparse_gml():
"""A pyparsing tokenizer for GML graph format.
This is not intended to be called directly.
See Also
--------
write_gml, read_gml, parse_gml
"""
try:
from pyparsing import \
Literal, CaselessLiteral, Word, Forward,\
ZeroOrMore, Group, Dict, Optional, Combine,\
ParseException, restOfLine, White, alphas, alphanums, nums,\
OneOrMore,quotedString,removeQuotes,dblQuotedString, Regex
except ImportError:
try:
from matplotlib.pyparsing import \
Literal, CaselessLiteral, Word, Forward,\
ZeroOrMore, Group, Dict, Optional, Combine,\
ParseException, restOfLine, White, alphas, alphanums, nums,\
OneOrMore,quotedString,removeQuotes,dblQuotedString, Regex
except:
raise ImportError('pyparsing not found',
'http://pyparsing.wikispaces.com/')
lbrack = Literal("[").suppress()
rbrack = Literal("]").suppress()
pound = ("#")
comment = pound + Optional( restOfLine )
integer = Word(nums+'-').setParseAction(lambda s,l,t:[ int(t[0])])
real = Regex(r"[+-]?\d+\.\d*([eE][+-]?\d+)?").setParseAction(
lambda s,l,t:[ float(t[0]) ])
dblQuotedString.setParseAction( removeQuotes )
key = Word(alphas,alphanums+'_')
value_atom = (real | integer | Word(alphanums) | dblQuotedString)
value = Forward() # to be defined later with << operator
keyvalue = Group(key+value)
value << (value_atom | Group( lbrack + ZeroOrMore(keyvalue) + rbrack ))
node = Group(Literal("node") + lbrack + Group(OneOrMore(keyvalue)) + rbrack)
edge = Group(Literal("edge") + lbrack + Group(OneOrMore(keyvalue)) + rbrack)
creator = Group(Literal("Creator")+ Optional( restOfLine ))
version = Group(Literal("Version")+ Optional( restOfLine ))
graphkey = Literal("graph").suppress()
graph = Dict (Optional(creator)+Optional(version)+\
graphkey + lbrack + ZeroOrMore( (node|edge|keyvalue) ) + rbrack )
graph.ignore(comment)
return graph
def write_gml(G, path):
"""
Write the graph G in GML format to the file or file handle path.
Parameters
----------
path : filename or filehandle
The filename or filehandle to write. Filenames ending in
.gz or .gz2 will be compressed.
See Also
--------
read_gml, parse_gml
Notes
-----
GML specifications indicate that the file should only use
7bit ASCII text encoding.iso8859-1 (latin-1).
This implementation does not support all Python data types as GML
data. Nodes, node attributes, edge attributes, and graph
attributes must be either dictionaries or single stings or
numbers. If they are not an attempt is made to represent them as
strings. For example, a list as edge data
G[1][2]['somedata']=[1,2,3], will be represented in the GML file
as::
edge [
source 1
target 2
somedata "[1, 2, 3]"
]
Examples
---------
>>> G=nx.path_graph(4)
>>> nx.write_gml(G,"test.gml")
Filenames ending in .gz or .bz2 will be compressed.
>>> nx.write_gml(G,"test.gml.gz")
"""
for line in generate_gml(G):
line += '\n'
path.write(line.encode('ascii', 'xmlcharrefreplace'))
# fixture for nose tests
