Python networkx.read_graphml方法代碼示例

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def read_graph(self, subgraph_file=None):
        if subgraph_file is None:
            subraph_file = self.context_graph_file
        logging.info("Writing graph.")
        # write the graph out
        file_format = subgraph_file.split(".")[-1]
        if file_format == "graphml":
            return nx.read_graphml(subgraph_file)
        elif file_format == "gml":
            return nx.read_gml(subgraph_file)
        elif file_format == "gexf":
            return nx.read_gexf(subgraph_file)
        elif file_format == "net":
            return nx.read_pajek(subgraph_file)
        elif file_format == "yaml":
            return nx.read_yaml(subgraph_file)
        elif file_format == "gpickle":
            return nx.read_gpickle(subgraph_file)
        else:
            logging.warning("File format not found, returning empty graph.")
        return nx.MultiDiGraph() 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def load_graphml(self,filename):
        warnings.warn("The load_graphml function is deprecated and "
                      "will be removed in version 2.0.0. "
                      "Use NX.READ_GRAPHML function instead.",
                      FutureWarning,
                      stacklevel=8
                      )

        self.G = nx.read_graphml(filename)
        attEdges = {}
        for k in self.G.edges():
            attEdges[k] = {"BW": 1, "PR": 1}
        nx.set_edge_attributes(self.G, values=attEdges)
        attNodes = {}
        for k in self.G.nodes():
            attNodes[k] = {"IPT": 1}
        nx.set_node_attributes(self.G, values=attNodes)
        for k in self.G.nodes():
            self.nodeAttributes[k] = self.G.node[k] #it has "id" att. TODO IMPROVE 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def read_graphml_with_position(filename):
	"""Read a graph in GraphML format with position
	"""
	G = nx.read_graphml(filename)
 
	# rearrage node attributes x, y as position for networkx
	pos = dict() # A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2.
	node_and_x = nx.get_node_attributes(G, 'x')
	node_and_y = nx.get_node_attributes(G, 'y')
 
	for node in node_and_x:
		x = node_and_x[node]
		y = node_and_y[node]
		pos[node] = (x, y)
 
	# add node attribute `pos` to G
	nx.set_node_attributes(G, 'pos', pos)
 
	return G 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def read_graphml_with_position(cls, filename):
        """Read a graph in GraphML format with position
        """
        G = nx.read_graphml(filename)

        # rearrage node attributes x, y as position for networkx
        pos = dict() # A dictionary with nodes as keys and positions as values. Positions should be sequences of length 2.
        node_and_x = nx.get_node_attributes(G, 'x')
        node_and_y = nx.get_node_attributes(G, 'y')

        for node in node_and_x:
            x = node_and_x[node]
            y = node_and_y[node]
            pos[node] = (x, y)

        # add node attribute `pos` to G
        nx.set_node_attributes(G, 'pos', pos)

        return G 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_read_attribute_graphml(self):
        G=self.attribute_graph
        H=nx.read_graphml(self.attribute_fh)
        assert_equal(sorted(G.nodes(True)),sorted(H.nodes(data=True)))
        ge=sorted(G.edges(data=True))
        he=sorted(H.edges(data=True))
        for a,b in zip(ge,he):
            assert_equal(a,b)
        self.attribute_fh.seek(0)

        I=nx.parse_graphml(self.attribute_data)
        assert_equal(sorted(G.nodes(True)),sorted(I.nodes(data=True)))
        ge=sorted(G.edges(data=True))
        he=sorted(I.edges(data=True))
        for a,b in zip(ge,he):
            assert_equal(a,b) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_default_attribute(self):
        G=nx.Graph()
        G.add_node(1,label=1,color='green')
        G.add_path([0,1,2,3])
        G.add_edge(1,2,weight=3)
        G.graph['node_default']={'color':'yellow'}
        G.graph['edge_default']={'weight':7}
        fh = io.BytesIO()
        nx.write_graphml(G,fh)
        fh.seek(0)
        H=nx.read_graphml(fh,node_type=int)
        assert_equal(sorted(G.nodes()),sorted(H.nodes()))
        assert_equal(
            sorted(sorted(e) for e in G.edges()),
            sorted(sorted(e) for e in H.edges()))
        assert_equal(G.graph,H.graph) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_unicode(self):
        G = nx.Graph()
        try: # Python 3.x
            name1 = chr(2344) + chr(123) + chr(6543)
            name2 = chr(5543) + chr(1543) + chr(324)
            node_type=str
        except ValueError: # Python 2.6+
            name1 = unichr(2344) + unichr(123) + unichr(6543)
            name2 = unichr(5543) + unichr(1543) + unichr(324)
            node_type=unicode
        G.add_edge(name1, 'Radiohead', attr_dict={'foo': name2})
        fd, fname = tempfile.mkstemp()
        nx.write_graphml(G, fname)
        H = nx.read_graphml(fname,node_type=node_type)
        assert_equal(G.adj, H.adj)
        os.close(fd)
        os.unlink(fname) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def load_graph(self, file):
        """
        Loads a .graphml file containing the architecture, discards unnecessary information and relabels the nodes.

        :param file: GraphML file containing the architecture
        :return: sanitised graph object
        """
        graph = nx.read_graphml(file)
        mapping = {}
        for node in graph.nodes():
            label = graph.node[node].pop("label", "NaN")
            mapping[node] = label
        graph = nx.relabel_nodes(graph, mapping)
        for node in graph.nodes():
            graph.node[node].pop("x", None)
            graph.node[node].pop("y", None)

        return graph 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_read_attribute_graphml(self):
        G = self.attribute_graph
        H = nx.read_graphml(self.attribute_fh)
        assert_nodes_equal(G.nodes(True), sorted(H.nodes(data=True)))
        ge = sorted(G.edges(data=True))
        he = sorted(H.edges(data=True))
        for a, b in zip(ge, he):
            assert_equal(a, b)
        self.attribute_fh.seek(0)

        I = nx.parse_graphml(self.attribute_data)
        assert_equal(sorted(G.nodes(True)), sorted(I.nodes(data=True)))
        ge = sorted(G.edges(data=True))
        he = sorted(I.edges(data=True))
        for a, b in zip(ge, he):
            assert_equal(a, b) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_directed_edge_in_undirected(self):
        s = """<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
         http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
  <graph id="G">
    <node id="n0"/>
    <node id="n1"/>
    <node id="n2"/>
    <edge source="n0" target="n1"/>
    <edge source="n1" target="n2" directed='true'/>
  </graph>
</graphml>"""
        fh = io.BytesIO(s.encode('UTF-8'))
        assert_raises(nx.NetworkXError, nx.read_graphml, fh)
        assert_raises(nx.NetworkXError, nx.parse_graphml, s) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_undirected_edge_in_directed(self):
        s = """<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
         http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
  <graph id="G" edgedefault='directed'>
    <node id="n0"/>
    <node id="n1"/>
    <node id="n2"/>
    <edge source="n0" target="n1"/>
    <edge source="n1" target="n2" directed='false'/>
  </graph>
</graphml>"""
        fh = io.BytesIO(s.encode('UTF-8'))
        assert_raises(nx.NetworkXError, nx.read_graphml, fh)
        assert_raises(nx.NetworkXError, nx.parse_graphml, s) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_multigraph_keys(self):
        # Test that reading multigraphs uses edge id attributes as keys
        s = """<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://graphml.graphdrawing.org/xmlns
         http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd">
  <graph id="G" edgedefault="directed">
    <node id="n0"/>
    <node id="n1"/>
    <edge id="e0" source="n0" target="n1"/>
    <edge id="e1" source="n0" target="n1"/>
  </graph>
</graphml>
"""
        fh = io.BytesIO(s.encode('UTF-8'))
        G = nx.read_graphml(fh)
        expected = [("n0", "n1", "e0"), ("n0", "n1", "e1")]
        assert_equal(sorted(G.edges(keys=True)), expected)
        fh.seek(0)
        H = nx.parse_graphml(s)
        assert_equal(sorted(H.edges(keys=True)), expected) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_write_read_attribute_numeric_type_graphml(self):
        from xml.etree.ElementTree import parse

        G = self.attribute_numeric_type_graph
        fh = io.BytesIO()
        self.writer(G, fh, infer_numeric_types=True)
        fh.seek(0)
        H = nx.read_graphml(fh)
        fh.seek(0)

        assert_nodes_equal(G.nodes(), H.nodes())
        assert_edges_equal(G.edges(), H.edges())
        assert_edges_equal(G.edges(data=True), H.edges(data=True))
        self.attribute_numeric_type_fh.seek(0)

        xml = parse(fh)
        # Children are the key elements, and the graph element
        children = xml.getroot().getchildren()
        assert_equal(len(children), 3)

        keys = [child.items() for child in children[:2]]

        assert_equal(len(keys), 2)
        assert_in(('attr.type', 'double'), keys[0])
        assert_in(('attr.type', 'double'), keys[1]) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_more_multigraph_keys(self):
        """Writing keys as edge id attributes means keys become strings.
        The original keys are stored as data, so read them back in
        if `make_str(key) == edge_id`
        This allows the adjacency to remain the same.
        """
        G = nx.MultiGraph()
        G.add_edges_from([('a', 'b', 2), ('a', 'b', 3)])
        fd, fname = tempfile.mkstemp()
        self.writer(G, fname)
        H = nx.read_graphml(fname)
        assert_true(H.is_multigraph())
        assert_edges_equal(G.edges(keys=True), H.edges(keys=True))
        assert_equal(G._adj, H._adj)
        os.close(fd)
        os.unlink(fname) 

# 需要導入模塊: import networkx [as 別名]
# 或者: from networkx import read_graphml [as 別名]
def test_numpy_float32(self):
        try:
            import numpy as np
        except:
            return
        wt = np.float32(3.4)
        G = nx.Graph([(1, 2, {'weight': wt})])
        fd, fname = tempfile.mkstemp()
        self.writer(G, fname)
        H = nx.read_graphml(fname, node_type=int)
        assert_equal(G.edges, H.edges)
        wtG = G[1][2]['weight']
        wtH = H[1][2]['weight']
        assert_almost_equal(wtG, wtH, places=6)
        assert_equal(type(wtG), np.float32)
        assert_equal(type(wtH), float)
        os.close(fd)
        os.unlink(fname)