Python networkx.NetworkXError() Examples

def _spectral(A, dim=2):
    # Input adjacency matrix A
    # Uses dense eigenvalue solver from numpy
    try:
        import numpy as np
    except ImportError:
        raise ImportError("spectral_layout() requires numpy: http://scipy.org/ ")
    try:
        nnodes,_=A.shape
    except AttributeError:
        raise nx.NetworkXError(\
            "spectral() takes an adjacency matrix as input")

    # form Laplacian matrix
    # make sure we have an array instead of a matrix
    A=np.asarray(A)
    I=np.identity(nnodes,dtype=A.dtype)
    D=I*np.sum(A,axis=1) # diagonal of degrees
    L=D-A

    eigenvalues,eigenvectors=np.linalg.eig(L)
    # sort and keep smallest nonzero
    index=np.argsort(eigenvalues)[1:dim+1] # 0 index is zero eigenvalue
    return np.real(eigenvectors[:,index]) 

def predecessors_iter(self, n, t=None):
        """Return an iterator over predecessors nodes of n at time t (optional).

        Parameters
        ----------
        n : node
            Nodes can be, for example, strings or numbers.
            Nodes must be hashable (and not None) Python objects.
        t : snapshot id (default=None)
            If None will be returned the presence of the interaction on the flattened graph.


        """
        try:
            if t is None:
                return iter(self._pred[n])
            else:
                return iter([i for i in self._pred[n] if self.__presence_test(i, n, t)])
        except KeyError:
            raise nx.NetworkXError("The node %s is not in the graph." % (n,)) 

def test_relabel_duplicate(self):
        data = """
graph
[
	label	""
	directed	1
	node
	[
		id	0
		label	"same"
	]
	node
	[
		id	1
		label	"same"
	]
]
"""
        fh = io.BytesIO(data.encode('UTF-8'))
        fh.seek(0)
        assert_raises(
            nx.NetworkXError, nx.read_gml, fh, label='label') 

def _remove_history(self, h):
        try:
            predecessors = self._graph.predecessors(h)
            successors = self._graph.successors(h)

            for p,s in itertools.product(predecessors, successors):
                self._graph.add_edge(p, s)

            self._graph.remove_node(h)
        except networkx.NetworkXError:
            pass

        self._leaves.discard(h)
        self._twigs.discard(h)
        hh = h()
        if hh is not None:
            hh.demote() 

def test_directed_edge_in_undirected(self):
        s="""<?xml version="1.0" encoding="UTF-8"?>
<gexf xmlns="http://www.gexf.net/1.1draft" version="1.1">
    <graph mode="static" defaultedgetype="undirected">
        <nodes>
            <node id="0" label="Hello" />
            <node id="1" label="Word" />
        </nodes>
        <edges>
            <edge id="0" source="0" target="1" type="directed"/>
        </edges>
    </graph>
</gexf>
"""
        fh = io.BytesIO(s.encode('UTF-8'))
        assert_raises(nx.NetworkXError,nx.read_gexf,fh) 

def test_key_error(self):
        s="""<?xml version="1.0" encoding="UTF-8"?>
<gexf xmlns="http://www.gexf.net/1.1draft" version="1.1">
    <graph mode="static" defaultedgetype="directed">
        <nodes>
            <node id="0" label="Hello">
              <attvalues>
                <attvalue for='0' value='1'/>
              </attvalues>
            </node>
            <node id="1" label="Word" />
        </nodes>
        <edges>
            <edge id="0" source="0" target="1" type="undirected"/>
        </edges>
    </graph>
</gexf>
"""
        fh = io.BytesIO(s.encode('UTF-8'))
        assert_raises(nx.NetworkXError,nx.read_gexf,fh) 

def test_is_weighted(self):
        G = nx.Graph()
        assert_false(nx.is_weighted(G))

        G = nx.path_graph(4)
        assert_false(nx.is_weighted(G))
        assert_false(nx.is_weighted(G, (2, 3)))

        G.add_node(4)
        G.add_edge(3, 4, weight=4)
        assert_false(nx.is_weighted(G))
        assert_true(nx.is_weighted(G, (3, 4)))

        G = nx.DiGraph()
        G.add_weighted_edges_from([('0', '3', 3), ('0', '1', -5), ('1', '0', -5),
                                     ('0', '2', 2), ('1', '2', 4),
                                     ('2', '3', 1)])
        assert_true(nx.is_weighted(G))
        assert_true(nx.is_weighted(G, ('1', '0')))

        G = G.to_undirected()
        assert_true(nx.is_weighted(G))
        assert_true(nx.is_weighted(G, ('1', '0')))

        assert_raises(nx.NetworkXError, nx.is_weighted, G, (1, 2)) 

def test_info_digraph(self):
        G=nx.DiGraph(name='path_graph(5)')
        G.add_path([0,1,2,3,4])
        info=nx.info(G)
        expected_graph_info='\n'.join(['Name: path_graph(5)',
                                       'Type: DiGraph',
                                       'Number of nodes: 5',
                                       'Number of edges: 4',
                                       'Average in degree:   0.8000',
                                       'Average out degree:   0.8000'])
        assert_equal(info,expected_graph_info)

        info=nx.info(G,n=1)
        expected_node_info='\n'.join(
            ['Node 1 has the following properties:',
             'Degree: 2',
             'Neighbors: 2'])
        assert_equal(info,expected_node_info)

        assert_raises(nx.NetworkXError,nx.info,G,n=-1) 

def __init__(self, data=None, **attr):
            self.node_dict_factory = ndf = self.node_dict_factory
            self.adjlist_dict_factory = self.adjlist_dict_factory
            self.edge_attr_dict_factory = self.edge_attr_dict_factory

            self.graph = {}   # dictionary for graph attributes
            self.node = ndf()  # empty node attribute dict
            self.adj = ndf()  # empty adjacency dict
            # attempt to load graph with data
            if data is not None:
                if isinstance(data, OrderedGraph):
                    try:
                        nx.convert.from_dict_of_dicts(
                            data.adj,
                            create_using=self,
                            multigraph_input=data.is_multigraph()
                        )
                        self.graph = data.graph.copy()
                        self.node.update((n,d.copy()) for n,d in data.node.items())
                    except:
                        raise nx.NetworkXError("Input is not a correct NetworkX graph.")
                else:
                    nx.convert.to_networkx_graph(data, create_using=self) 

def test_iterators(self):
        G=self.G()
        G.add_edges_from([('A', 'B'), ('A', 'C'), ('B', 'D'), 
                          ('C', 'B'), ('C', 'D')])
        G.add_nodes_from('GJK')
        assert_equal(sorted(G.nodes_iter()),
                     ['A', 'B', 'C', 'D', 'G', 'J', 'K'])
        assert_edges_equal(G.edges_iter(),
        [('A', 'B'), ('A', 'C'), ('B', 'D'), ('C', 'B'), ('C', 'D')])

        assert_equal(sorted([v for k,v in G.degree_iter()]),
                     [0, 0, 0, 2, 2, 3, 3])
        assert_equal(sorted(G.degree_iter(),key=str),
                     [('A', 2), ('B', 3), ('C', 3), ('D', 2), 
                      ('G', 0), ('J', 0), ('K', 0)])
        assert_equal(sorted(G.neighbors_iter('A')),['B', 'C'])
        assert_raises(nx.NetworkXError,G.neighbors_iter,'X')
        G.clear()
        assert_equal(nx.number_of_nodes(G),0)
        assert_equal(nx.number_of_edges(G),0) 

def neighbors_iter(self, n, t=None):
        """Return an iterator over all neighbors of node n at time t.

        Parameters
        ----------
        n : node
           A node in the graph
        t : snapshot id (default=None)
            If None will be returned an iterator over the neighbors of the node on the flattened graph.

        Examples
        --------
        >>> import dynetx as dn
        >>> G = dn.DynGraph()
        >>> G.add_path([0,1,2,3], t=0)
        >>> [n for n in G.neighbors_iter(0, t=0)]
        [1]
        """
        try:
            if t is None:
                return iter(self._adj[n])
            else:
                return iter([i for i in self._adj[n] if self.__presence_test(n, i, t)])
        except KeyError:
            raise nx.NetworkXError("The node %s is not in the graph." % (n,)) 

def _transitive_rel(self, ns, id, rel_fun, rel_types, target=None):
        source = (ns, id)
        visited = {source}
        queue = deque([(source,
                        rel_fun(*source, rel_types))])
        while queue:
            parent, children = queue[0]
            try:
                child = next(children)
                if target and child == target:
                    return [target]
                if child not in visited:
                    visited.add(child)
                    queue.append((child,
                                  rel_fun(*child, rel_types)))
            except networkx.NetworkXError as e:
                logger.debug(e)
                return []
            except StopIteration:
                queue.popleft()
        return list(visited - {source}) 

def successors_iter(self, n, t=None):
        """
        Return an iterator over successor nodes of n at time t (optional).

        Parameters
        ----------
        n : node
            Nodes can be, for example, strings or numbers.
            Nodes must be hashable (and not None) Python objects.
        t : snapshot id (default=None)
            If None will be returned the presence of the interaction on the flattened graph.

        """
        try:
            if t is None:
                return iter(self._succ[n])
            else:
                return iter([i for i in self._succ[n] if self.__presence_test(n, i, t)])
        except KeyError:
            raise nx.NetworkXError("The node %s is not in the graph." % (n,)) 

def test_is_negatively_weighted(self):
        G = nx.Graph()
        assert_false(nx.is_negatively_weighted(G))

        G.add_node(1)
        G.add_nodes_from([2, 3, 4, 5])
        assert_false(nx.is_negatively_weighted(G))

        G.add_edge(1, 2, weight=4)
        assert_false(nx.is_negatively_weighted(G, (1, 2)))

        G.add_edges_from([(1, 3), (2, 4), (2, 6)])
        G[1][3]['color'] = 'blue'
        assert_false(nx.is_negatively_weighted(G))
        assert_false(nx.is_negatively_weighted(G, (1, 3)))

        G[2][4]['weight'] = -2
        assert_true(nx.is_negatively_weighted(G, (2, 4)))
        assert_true(nx.is_negatively_weighted(G))

        G = nx.DiGraph()
        G.add_weighted_edges_from([('0', '3', 3), ('0', '1', -5), ('1', '0', -2),
                                   ('0', '2', 2), ('1', '2', -3), ('2', '3', 1)])
        assert_true(nx.is_negatively_weighted(G))
        assert_false(nx.is_negatively_weighted(G, ('0', '3')))
        assert_true(nx.is_negatively_weighted(G, ('1', '0')))

        assert_raises(nx.NetworkXError, nx.is_negatively_weighted, G, (1, 4)) 

def find_graphml_keys(self, graph_element):
        """Extracts all the keys and key defaults from the xml.
        """
        graphml_keys = {}
        graphml_key_defaults = {}
        for k in graph_element.findall("{%s}key" % self.NS_GRAPHML):
            attr_id = k.get("id")
            attr_type=k.get('attr.type')
            attr_name=k.get("attr.name")
            yfiles_type=k.get("yfiles.type")
            if yfiles_type is not None:
                attr_name = yfiles_type
                attr_type = 'yfiles'
            if attr_type is None:
                attr_type = "string"
                warnings.warn("No key type for id %s. Using string"%attr_id)
            if attr_name is None:
                raise nx.NetworkXError("Unknown key for id %s in file."%attr_id)
            graphml_keys[attr_id] = {
                "name":attr_name,
                "type":self.python_type[attr_type],
                "for":k.get("for")}
            # check for "default" subelement of key element
            default=k.find("{%s}default" % self.NS_GRAPHML)
            if default is not None:
                graphml_key_defaults[attr_id]=default.text
        return graphml_keys,graphml_key_defaults

# fixture for nose tests 

def test_edges_data(self):
        G=self.K3
        assert_equal(sorted(G.edges(data=True)),
                     [(0,1,{}),(0,2,{}),(1,0,{}),(1,2,{}),(2,0,{}),(2,1,{})])
        assert_equal(sorted(G.edges(0,data=True)),[(0,1,{}),(0,2,{})])
        assert_raises((KeyError,networkx.NetworkXError), G.neighbors,-1) 

def test_freeze(self):
        G=nx.freeze(self.G)
        assert_equal(G.frozen,True)
        assert_raises(nx.NetworkXError, G.add_node, 1)
        assert_raises(nx.NetworkXError, G.add_nodes_from, [1])
        assert_raises(nx.NetworkXError, G.remove_node, 1)
        assert_raises(nx.NetworkXError, G.remove_nodes_from, [1])
        assert_raises(nx.NetworkXError, G.add_edge, 1,2)
        assert_raises(nx.NetworkXError, G.add_edges_from, [(1,2)])
        assert_raises(nx.NetworkXError, G.remove_edge, 1,2)
        assert_raises(nx.NetworkXError, G.remove_edges_from, [(1,2)])
        assert_raises(nx.NetworkXError, G.clear) 

def add_data(self, name, element_type, value,
                 scope="all",
                 default=None):
        """
        Make a data element for an edge or a node. Keep a log of the
        type in the keys table.
        """
        if element_type not in self.xml_type:
            raise nx.NetworkXError('GraphML writer does not support '
                                   '%s as data values.'%element_type)
        key_id = self.get_key(name, self.xml_type[element_type], scope, default)
        data_element = Element("data", key=key_id)
        data_element.text = make_str(value)
        return data_element 

def test_nonexistent_nodes(self):
        G = nx.complete_graph(5)
        assert_raises(nx.NetworkXError, nx.common_neighbors, G, 5, 4)
        assert_raises(nx.NetworkXError, nx.common_neighbors, G, 4, 5)
        assert_raises(nx.NetworkXError, nx.common_neighbors, G, 5, 6) 

def test_in_edges(self):
        G=self.K3
        assert_equal(sorted(G.in_edges()),
                     [(0,1),(0,2),(1,0),(1,2),(2,0),(2,1)])
        assert_equal(sorted(G.in_edges(0)),[(1,0),(2,0)])
        assert_raises((KeyError,networkx.NetworkXError), G.in_edges,-1)
        G.add_edge(0,1,2)
        assert_equal(sorted(G.in_edges()),
                     [(0,1),(0,1),(0,2),(1,0),(1,2),(2,0),(2,1)])
        assert_equal(sorted(G.in_edges(0,keys=True)),[(1,0,0),(2,0,0)]) 

def test_successors(self):
        G=self.K3
        assert_equal(sorted(G.successors(0)),[1,2])
        assert_raises((KeyError,networkx.NetworkXError), G.successors,-1) 

def add_edge(self, G, edge_element, graphml_keys):
        """Add an edge to the graph.
        """
        # warn on finding unsupported ports tag
        ports=edge_element.find("{%s}port" % self.NS_GRAPHML)
        if ports is not None:
            warnings.warn("GraphML port tag not supported.")

        # raise error if we find mixed directed and undirected edges
        directed = edge_element.get("directed")
        if G.is_directed() and directed=='false':
            raise nx.NetworkXError(\
                "directed=false edge found in directed graph.")
        if (not G.is_directed()) and directed=='true':
            raise nx.NetworkXError(\
                "directed=true edge found in undirected graph.")

        source = self.node_type(edge_element.get("source"))
        target = self.node_type(edge_element.get("target"))
        data = self.decode_data_elements(graphml_keys, edge_element)
        # GraphML stores edge ids as an attribute
        # NetworkX uses them as keys in multigraphs too if no key
        # attribute is specified
        edge_id = edge_element.get("id")
        if edge_id:
            data["id"] = edge_id
        if G.has_edge(source,target):
            # mark this as a multigraph
            self.multigraph=True
        if edge_id is None:
            # no id specified, try using 'key' attribute as id
            edge_id=data.pop('key',None)
        G.add_edge(source, target, key=edge_id, **data) 

def make_graph(self, graph_xml, graphml_keys, defaults):
        # set default graph type
        edgedefault = graph_xml.get("edgedefault", None)
        if edgedefault=='directed':
            G=nx.MultiDiGraph()
        else:
            G=nx.MultiGraph()
        # set defaults for graph attributes
        G.graph['node_default']={}
        G.graph['edge_default']={}
        for key_id,value in defaults.items():
            key_for=graphml_keys[key_id]['for']
            name=graphml_keys[key_id]['name']
            python_type=graphml_keys[key_id]['type']
            if key_for=='node':
                G.graph['node_default'].update({name:python_type(value)})
            if key_for=='edge':
                G.graph['edge_default'].update({name:python_type(value)})
        # hyperedges are not supported
        hyperedge=graph_xml.find("{%s}hyperedge" % self.NS_GRAPHML)
        if hyperedge is not None:
            raise nx.NetworkXError("GraphML reader does not support hyperedges")
        # add nodes
        for node_xml in graph_xml.findall("{%s}node" % self.NS_GRAPHML):
            self.add_node(G, node_xml, graphml_keys)
        # add edges
        for edge_xml in graph_xml.findall("{%s}edge" % self.NS_GRAPHML):
            self.add_edge(G, edge_xml, graphml_keys)
        # add graph data
        data = self.decode_data_elements(graphml_keys, graph_xml)
        G.graph.update(data)

        # switch to Graph or DiGraph if no parallel edges were found.
        if not self.multigraph:
            if G.is_directed():
                return nx.DiGraph(G)
            else:
                return nx.Graph(G)
        else:
            return G 

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) 

def decode_attr_elements(self, gexf_keys, obj_xml):
        # Use the key information to decode the attr XML
        attr = {}
        # look for outer "<attvalues>" element
        attr_element=obj_xml.find("{%s}attvalues" % self.NS_GEXF)
        if attr_element is not None:
            # loop over <attvalue> elements
            for a in attr_element.findall("{%s}attvalue" % self.NS_GEXF):
                key = a.get('for') # for is required
                try: # should be in our gexf_keys dictionary
                    title=gexf_keys[key]['title']
                except KeyError:
                    raise nx.NetworkXError("No attribute defined for=%s"%key)
                atype=gexf_keys[key]['type']
                value=a.get('value')
                if atype=='boolean':
                    value=self.convert_bool[value]
                else:
                    value=self.python_type[atype](value)
                if gexf_keys[key]['mode']=='dynamic':
                    # for dynamic graphs use list of three-tuples
                    # [(value1,start1,end1), (value2,start2,end2), etc]
                    ttype = self.timeformat
                    start=self.python_type[ttype](a.get('start'))
                    end=self.python_type[ttype](a.get('end'))
                    if title in attr:
                        attr[title].append((value,start,end))
                    else:
                        attr[title]=[(value,start,end)]
                else:
                    # for static graphs just assign the value
                    attr[title] = value
        return attr 

def __call__(self, stream):
        self.xml = ElementTree(file=stream)
        g=self.xml.find("{%s}graph" % self.NS_GEXF)
        if g is not None:
            return self.make_graph(g)
        # try all the versions
        for version in self.versions:
            self.set_version(version)
            g=self.xml.find("{%s}graph" % self.NS_GEXF)
            if g is not None:
                return self.make_graph(g)
        raise nx.NetworkXError("No <graph> element in GEXF file") 

def set_version(self,version):
        d=self.versions.get(version)
        if d is None:
            raise nx.NetworkXError('Unknown GEXF version %s'%version)
        self.NS_GEXF = d['NS_GEXF']
        self.NS_VIZ = d['NS_VIZ']
        self.NS_XSI = d['NS_XSI']
        self.SCHEMALOCATION = d['NS_XSI']
        self.VERSION=d['VERSION']
        self.version=version

#        register_namespace('viz', d['NS_VIZ']) 

def test_hyperedge_error(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">
  <key id="d0" for="node" attr.name="color" attr.type="string">
    <default>yellow</default>
  </key>
  <key id="d1" for="edge" attr.name="weight" attr.type="double"/>
  <graph id="G" edgedefault="directed">
    <node id="n0">
      <data key="d0">green</data>
    </node>
    <node id="n1"/>
    <node id="n2">
      <data key="d0">blue</data>
    </node>
    <hyperedge id="e0" source="n0" target="n2">
       <endpoint node="n0"/>
       <endpoint node="n1"/>
       <endpoint node="n2"/>
    </hyperedge>
  </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)

    # remove test until we get the "name" issue sorted
    # https://networkx.lanl.gov/trac/ticket/544 

def test_key_error(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">
  <key id="d0" for="node" attr.name="color" attr.type="string">
    <default>yellow</default>
  </key>
  <key id="d1" for="edge" attr.name="weight" attr.type="double"/>
  <graph id="G" edgedefault="directed">
    <node id="n0">
      <data key="d0">green</data>
    </node>
    <node id="n1"/>
    <node id="n2">
      <data key="d0">blue</data>
    </node>
    <edge id="e0" source="n0" target="n2">
      <data key="d2">1.0</data>
    </edge>
  </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) 

def plot_path(self, frm_node, to_node, levels=1, add_to_exsting=False):
        """Plot shortest path between two nodes"""
        try:
            path = nx.shortest_path(self.dataG, frm_node, to_node)
        except nx.NetworkXNoPath as e:
            tkm.showerror("No path", str(e))
            return
        except nx.NetworkXError as e:
            tkm.showerror("Node not in graph", str(e))
            return

        graph = self.dataG.subgraph(self._neighbors(path,levels=levels))

        if add_to_exsting:
            self._plot_additional(graph.nodes())
        else:
            self.clear()
            self._plot_graph(graph)

        # Mark the path
        if levels > 0 or add_to_exsting:
            for u, v in zip(path[:-1], path[1:]):
                u_disp = self._find_disp_node(u)
                v_disp = self._find_disp_node(v)
                for key, value in self.dispG.edge[u_disp][v_disp].items():
                    self.mark_edge(u_disp, v_disp, key)