919 lines
35 KiB
Python
919 lines
35 KiB
Python
# Copyright (C) 2008-2019 by
|
|
# Aric Hagberg <hagberg@lanl.gov>
|
|
# Dan Schult <dschult@colgate.edu>
|
|
# Pieter Swart <swart@lanl.gov>
|
|
# All rights reserved.
|
|
# BSD license.
|
|
#
|
|
# Authors: Salim Fadhley
|
|
# Aric Hagberg (hagberg@lanl.gov)
|
|
"""
|
|
*******
|
|
GraphML
|
|
*******
|
|
Read and write graphs in GraphML format.
|
|
|
|
This implementation does not support mixed graphs (directed and unidirected
|
|
edges together), hyperedges, nested graphs, or ports.
|
|
|
|
"GraphML is a comprehensive and easy-to-use file format for graphs. It
|
|
consists of a language core to describe the structural properties of a
|
|
graph and a flexible extension mechanism to add application-specific
|
|
data. Its main features include support of
|
|
|
|
* directed, undirected, and mixed graphs,
|
|
* hypergraphs,
|
|
* hierarchical graphs,
|
|
* graphical representations,
|
|
* references to external data,
|
|
* application-specific attribute data, and
|
|
* light-weight parsers.
|
|
|
|
Unlike many other file formats for graphs, GraphML does not use a
|
|
custom syntax. Instead, it is based on XML and hence ideally suited as
|
|
a common denominator for all kinds of services generating, archiving,
|
|
or processing graphs."
|
|
|
|
http://graphml.graphdrawing.org/
|
|
|
|
Format
|
|
------
|
|
GraphML is an XML format. See
|
|
http://graphml.graphdrawing.org/specification.html for the specification and
|
|
http://graphml.graphdrawing.org/primer/graphml-primer.html
|
|
for examples.
|
|
"""
|
|
import warnings
|
|
from collections import defaultdict
|
|
|
|
try:
|
|
from xml.etree.cElementTree import Element, ElementTree
|
|
from xml.etree.cElementTree import tostring, fromstring
|
|
except ImportError:
|
|
try:
|
|
from xml.etree.ElementTree import Element, ElementTree
|
|
from xml.etree.ElementTree import tostring, fromstring
|
|
except ImportError:
|
|
pass
|
|
|
|
try:
|
|
import lxml.etree as lxmletree
|
|
except ImportError:
|
|
lxmletree = None
|
|
|
|
import networkx as nx
|
|
from networkx.utils import open_file, make_str
|
|
|
|
__all__ = ['write_graphml', 'read_graphml', 'generate_graphml',
|
|
'write_graphml_xml', 'write_graphml_lxml',
|
|
'parse_graphml', 'GraphMLWriter', 'GraphMLReader']
|
|
|
|
|
|
@open_file(1, mode='wb')
|
|
def write_graphml_xml(G, path, encoding='utf-8', prettyprint=True,
|
|
infer_numeric_types=False):
|
|
"""Write G in GraphML XML format to path
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
path : file or string
|
|
File or filename to write.
|
|
Filenames ending in .gz or .bz2 will be compressed.
|
|
encoding : string (optional)
|
|
Encoding for text data.
|
|
prettyprint : bool (optional)
|
|
If True use line breaks and indenting in output XML.
|
|
infer_numeric_types : boolean
|
|
Determine if numeric types should be generalized.
|
|
For example, if edges have both int and float 'weight' attributes,
|
|
we infer in GraphML that both are floats.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.path_graph(4)
|
|
>>> nx.write_graphml(G, "test.graphml")
|
|
|
|
Notes
|
|
-----
|
|
It may be a good idea in Python2 to convert strings to unicode
|
|
before giving the graph to write_gml. At least the strings with
|
|
either many characters to escape.
|
|
|
|
This implementation does not support mixed graphs (directed
|
|
and unidirected edges together) hyperedges, nested graphs, or ports.
|
|
"""
|
|
writer = GraphMLWriter(encoding=encoding, prettyprint=prettyprint,
|
|
infer_numeric_types=infer_numeric_types)
|
|
writer.add_graph_element(G)
|
|
writer.dump(path)
|
|
|
|
|
|
@open_file(1, mode='wb')
|
|
def write_graphml_lxml(G, path, encoding='utf-8', prettyprint=True,
|
|
infer_numeric_types=False):
|
|
"""Write G in GraphML XML format to path
|
|
|
|
This function uses the LXML framework and should be faster than
|
|
the version using the xml library.
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
path : file or string
|
|
File or filename to write.
|
|
Filenames ending in .gz or .bz2 will be compressed.
|
|
encoding : string (optional)
|
|
Encoding for text data.
|
|
prettyprint : bool (optional)
|
|
If True use line breaks and indenting in output XML.
|
|
infer_numeric_types : boolean
|
|
Determine if numeric types should be generalized.
|
|
For example, if edges have both int and float 'weight' attributes,
|
|
we infer in GraphML that both are floats.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.path_graph(4)
|
|
>>> nx.write_graphml_lxml(G, "fourpath.graphml") # doctest: +SKIP
|
|
|
|
Notes
|
|
-----
|
|
This implementation does not support mixed graphs (directed
|
|
and unidirected edges together) hyperedges, nested graphs, or ports.
|
|
"""
|
|
writer = GraphMLWriterLxml(path, graph=G, encoding=encoding,
|
|
prettyprint=prettyprint,
|
|
infer_numeric_types=infer_numeric_types)
|
|
writer.dump()
|
|
|
|
|
|
def generate_graphml(G, encoding='utf-8', prettyprint=True):
|
|
"""Generate GraphML lines for G
|
|
|
|
Parameters
|
|
----------
|
|
G : graph
|
|
A networkx graph
|
|
encoding : string (optional)
|
|
Encoding for text data.
|
|
prettyprint : bool (optional)
|
|
If True use line breaks and indenting in output XML.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.path_graph(4)
|
|
>>> linefeed = chr(10) # linefeed = \n
|
|
>>> s = linefeed.join(nx.generate_graphml(G)) # doctest: +SKIP
|
|
>>> for line in nx.generate_graphml(G): # doctest: +SKIP
|
|
... print(line)
|
|
|
|
Notes
|
|
-----
|
|
This implementation does not support mixed graphs (directed and unidirected
|
|
edges together) hyperedges, nested graphs, or ports.
|
|
"""
|
|
writer = GraphMLWriter(encoding=encoding, prettyprint=prettyprint)
|
|
writer.add_graph_element(G)
|
|
for line in str(writer).splitlines():
|
|
yield line
|
|
|
|
|
|
@open_file(0, mode='rb')
|
|
def read_graphml(path, node_type=str, edge_key_type=int):
|
|
"""Read graph in GraphML format from path.
|
|
|
|
Parameters
|
|
----------
|
|
path : file or string
|
|
File or filename to write.
|
|
Filenames ending in .gz or .bz2 will be compressed.
|
|
|
|
node_type: Python type (default: str)
|
|
Convert node ids to this type
|
|
|
|
edge_key_type: Python type (default: int)
|
|
Convert graphml edge ids to this type as key of multi-edges
|
|
|
|
|
|
Returns
|
|
-------
|
|
graph: NetworkX graph
|
|
If no parallel edges are found a Graph or DiGraph is returned.
|
|
Otherwise a MultiGraph or MultiDiGraph is returned.
|
|
|
|
Notes
|
|
-----
|
|
Default node and edge attributes are not propagated to each node and edge.
|
|
They can be obtained from `G.graph` and applied to node and edge attributes
|
|
if desired using something like this:
|
|
|
|
>>> default_color = G.graph['node_default']['color'] # doctest: +SKIP
|
|
>>> for node, data in G.nodes(data=True): # doctest: +SKIP
|
|
... if 'color' not in data:
|
|
... data['color']=default_color
|
|
>>> default_color = G.graph['edge_default']['color'] # doctest: +SKIP
|
|
>>> for u, v, data in G.edges(data=True): # doctest: +SKIP
|
|
... if 'color' not in data:
|
|
... data['color']=default_color
|
|
|
|
This implementation does not support mixed graphs (directed and unidirected
|
|
edges together), hypergraphs, nested graphs, or ports.
|
|
|
|
For multigraphs the GraphML edge "id" will be used as the edge
|
|
key. If not specified then they "key" attribute will be used. If
|
|
there is no "key" attribute a default NetworkX multigraph edge key
|
|
will be provided.
|
|
|
|
Files with the yEd "yfiles" extension will can be read but the graphics
|
|
information is discarded.
|
|
|
|
yEd compressed files ("file.graphmlz" extension) can be read by renaming
|
|
the file to "file.graphml.gz".
|
|
|
|
"""
|
|
reader = GraphMLReader(node_type=node_type, edge_key_type=edge_key_type)
|
|
# need to check for multiple graphs
|
|
glist = list(reader(path=path))
|
|
if len(glist) == 0:
|
|
# If no graph comes back, try looking for an incomplete header
|
|
header = b'<graphml xmlns="http://graphml.graphdrawing.org/xmlns">'
|
|
path.seek(0)
|
|
old_bytes = path.read()
|
|
new_bytes = old_bytes.replace(b'<graphml>', header)
|
|
glist = list(reader(string=new_bytes))
|
|
if len(glist) == 0:
|
|
raise nx.NetworkXError('file not successfully read as graphml')
|
|
return glist[0]
|
|
|
|
|
|
def parse_graphml(graphml_string, node_type=str):
|
|
"""Read graph in GraphML format from string.
|
|
|
|
Parameters
|
|
----------
|
|
graphml_string : string
|
|
String containing graphml information
|
|
(e.g., contents of a graphml file).
|
|
|
|
node_type: Python type (default: str)
|
|
Convert node ids to this type
|
|
|
|
Returns
|
|
-------
|
|
graph: NetworkX graph
|
|
If no parallel edges are found a Graph or DiGraph is returned.
|
|
Otherwise a MultiGraph or MultiDiGraph is returned.
|
|
|
|
Examples
|
|
--------
|
|
>>> G = nx.path_graph(4)
|
|
>>> linefeed = chr(10) # linefeed = \n
|
|
>>> s = linefeed.join(nx.generate_graphml(G))
|
|
>>> H = nx.parse_graphml(s)
|
|
|
|
Notes
|
|
-----
|
|
Default node and edge attributes are not propagated to each node and edge.
|
|
They can be obtained from `G.graph` and applied to node and edge attributes
|
|
if desired using something like this:
|
|
|
|
>>> default_color = G.graph['node_default']['color'] # doctest: +SKIP
|
|
>>> for node, data in G.nodes(data=True): # doctest: +SKIP
|
|
... if 'color' not in data:
|
|
... data['color']=default_color
|
|
>>> default_color = G.graph['edge_default']['color'] # doctest: +SKIP
|
|
>>> for u, v, data in G.edges(data=True): # doctest: +SKIP
|
|
... if 'color' not in data:
|
|
... data['color']=default_color
|
|
|
|
This implementation does not support mixed graphs (directed and unidirected
|
|
edges together), hypergraphs, nested graphs, or ports.
|
|
|
|
For multigraphs the GraphML edge "id" will be used as the edge
|
|
key. If not specified then they "key" attribute will be used. If
|
|
there is no "key" attribute a default NetworkX multigraph edge key
|
|
will be provided.
|
|
|
|
"""
|
|
reader = GraphMLReader(node_type=node_type)
|
|
# need to check for multiple graphs
|
|
glist = list(reader(string=graphml_string))
|
|
if len(glist) == 0:
|
|
# If no graph comes back, try looking for an incomplete header
|
|
header = '<graphml xmlns="http://graphml.graphdrawing.org/xmlns">'
|
|
new_string = graphml_string.replace('<graphml>', header)
|
|
glist = list(reader(string=new_string))
|
|
if len(glist) == 0:
|
|
raise nx.NetworkXError('file not successfully read as graphml')
|
|
return glist[0]
|
|
|
|
|
|
class GraphML(object):
|
|
NS_GRAPHML = "http://graphml.graphdrawing.org/xmlns"
|
|
NS_XSI = "http://www.w3.org/2001/XMLSchema-instance"
|
|
# xmlns:y="http://www.yworks.com/xml/graphml"
|
|
NS_Y = "http://www.yworks.com/xml/graphml"
|
|
SCHEMALOCATION = \
|
|
' '.join(['http://graphml.graphdrawing.org/xmlns',
|
|
'http://graphml.graphdrawing.org/xmlns/1.0/graphml.xsd'])
|
|
|
|
try:
|
|
chr(12345) # Fails on Py!=3.
|
|
unicode = str # Py3k's str is our unicode type
|
|
long = int # Py3K's int is our long type
|
|
except ValueError:
|
|
# Python 2.x
|
|
pass
|
|
|
|
types = [(int, "integer"), # for Gephi GraphML bug
|
|
(str, "yfiles"), (str, "string"), (unicode, "string"),
|
|
(int, "int"), (long, "long"),
|
|
(float, "float"), (float, "double"),
|
|
(bool, "boolean")]
|
|
|
|
# These additions to types allow writing numpy types
|
|
try:
|
|
import numpy as np
|
|
except:
|
|
pass
|
|
else:
|
|
# prepend so that python types are created upon read (last entry wins)
|
|
types = [(np.float64, "float"), (np.float32, "float"),
|
|
(np.float16, "float"), (np.float_, "float"),
|
|
(np.int, "int"), (np.int8, "int"),
|
|
(np.int16, "int"), (np.int32, "int"),
|
|
(np.int64, "int"), (np.uint8, "int"),
|
|
(np.uint16, "int"), (np.uint32, "int"),
|
|
(np.uint64, "int"), (np.int_, "int"),
|
|
(np.intc, "int"), (np.intp, "int"),
|
|
] + types
|
|
|
|
xml_type = dict(types)
|
|
python_type = dict(reversed(a) for a in types)
|
|
|
|
# This page says that data types in GraphML follow Java(TM).
|
|
# http://graphml.graphdrawing.org/primer/graphml-primer.html#AttributesDefinition
|
|
# true and false are the only boolean literals:
|
|
# http://en.wikibooks.org/wiki/Java_Programming/Literals#Boolean_Literals
|
|
convert_bool = {
|
|
# We use data.lower() in actual use.
|
|
'true': True, 'false': False,
|
|
# Include integer strings for convenience.
|
|
'0': False, 0: False,
|
|
'1': True, 1: True
|
|
}
|
|
|
|
|
|
class GraphMLWriter(GraphML):
|
|
def __init__(self, graph=None, encoding="utf-8", prettyprint=True,
|
|
infer_numeric_types=False):
|
|
try:
|
|
import xml.etree.ElementTree
|
|
except ImportError:
|
|
msg = 'GraphML writer requires xml.elementtree.ElementTree'
|
|
raise ImportError(msg)
|
|
self.myElement = Element
|
|
|
|
self.infer_numeric_types = infer_numeric_types
|
|
self.prettyprint = prettyprint
|
|
self.encoding = encoding
|
|
self.xml = self.myElement("graphml",
|
|
{'xmlns': self.NS_GRAPHML,
|
|
'xmlns:xsi': self.NS_XSI,
|
|
'xsi:schemaLocation': self.SCHEMALOCATION})
|
|
self.keys = {}
|
|
self.attributes = defaultdict(list)
|
|
self.attribute_types = defaultdict(set)
|
|
|
|
if graph is not None:
|
|
self.add_graph_element(graph)
|
|
|
|
def __str__(self):
|
|
if self.prettyprint:
|
|
self.indent(self.xml)
|
|
s = tostring(self.xml).decode(self.encoding)
|
|
return s
|
|
|
|
def attr_type(self, name, scope, value):
|
|
"""Infer the attribute type of data named name. Currently this only
|
|
supports inference of numeric types.
|
|
|
|
If self.infer_numeric_types is false, type is used. Otherwise, pick the
|
|
most general of types found across all values with name and scope. This
|
|
means edges with data named 'weight' are treated separately from nodes
|
|
with data named 'weight'.
|
|
"""
|
|
if self.infer_numeric_types:
|
|
types = self.attribute_types[(name, scope)]
|
|
|
|
try:
|
|
chr(12345) # Fails on Py<3.
|
|
local_long = int # Py3's int is Py2's long type
|
|
local_unicode = str # Py3's str is Py2's unicode type
|
|
except ValueError:
|
|
# Python 2.x
|
|
local_long = long
|
|
local_unicode = unicode
|
|
|
|
if len(types) > 1:
|
|
if str in types:
|
|
return str
|
|
elif local_unicode in types:
|
|
return local_unicode
|
|
elif float in types:
|
|
return float
|
|
elif local_long in types:
|
|
return local_long
|
|
else:
|
|
return int
|
|
else:
|
|
return list(types)[0]
|
|
else:
|
|
return type(value)
|
|
|
|
def get_key(self, name, attr_type, scope, default):
|
|
keys_key = (name, attr_type, scope)
|
|
try:
|
|
return self.keys[keys_key]
|
|
except KeyError:
|
|
new_id = "d%i" % len(list(self.keys))
|
|
self.keys[keys_key] = new_id
|
|
key_kwargs = {"id": new_id,
|
|
"for": scope,
|
|
"attr.name": name,
|
|
"attr.type": attr_type}
|
|
key_element = self.myElement("key", **key_kwargs)
|
|
# add subelement for data default value if present
|
|
if default is not None:
|
|
default_element = self.myElement("default")
|
|
default_element.text = make_str(default)
|
|
key_element.append(default_element)
|
|
self.xml.insert(0, key_element)
|
|
return new_id
|
|
|
|
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:
|
|
msg = 'GraphML writer does not support %s as data values.'
|
|
raise nx.NetworkXError(msg % element_type)
|
|
keyid = self.get_key(name, self.xml_type[element_type], scope, default)
|
|
data_element = self.myElement("data", key=keyid)
|
|
data_element.text = make_str(value)
|
|
return data_element
|
|
|
|
def add_attributes(self, scope, xml_obj, data, default):
|
|
"""Appends attribute data to edges or nodes, and stores type information
|
|
to be added later. See add_graph_element.
|
|
"""
|
|
for k, v in data.items():
|
|
self.attribute_types[(make_str(k), scope)].add(type(v))
|
|
self.attributes[xml_obj].append([k, v, scope, default.get(k)])
|
|
|
|
def add_nodes(self, G, graph_element):
|
|
default = G.graph.get('node_default', {})
|
|
for node, data in G.nodes(data=True):
|
|
node_element = self.myElement("node", id=make_str(node))
|
|
self.add_attributes("node", node_element, data, default)
|
|
graph_element.append(node_element)
|
|
|
|
def add_edges(self, G, graph_element):
|
|
if G.is_multigraph():
|
|
for u, v, key, data in G.edges(data=True, keys=True):
|
|
edge_element = self.myElement("edge", source=make_str(u),
|
|
target=make_str(v),
|
|
id=make_str(key))
|
|
default = G.graph.get('edge_default', {})
|
|
self.add_attributes("edge", edge_element, data, default)
|
|
graph_element.append(edge_element)
|
|
else:
|
|
for u, v, data in G.edges(data=True):
|
|
edge_element = self.myElement("edge", source=make_str(u),
|
|
target=make_str(v))
|
|
default = G.graph.get('edge_default', {})
|
|
self.add_attributes("edge", edge_element, data, default)
|
|
graph_element.append(edge_element)
|
|
|
|
def add_graph_element(self, G):
|
|
"""
|
|
Serialize graph G in GraphML to the stream.
|
|
"""
|
|
if G.is_directed():
|
|
default_edge_type = 'directed'
|
|
else:
|
|
default_edge_type = 'undirected'
|
|
|
|
graphid = G.graph.pop('id', None)
|
|
if graphid is None:
|
|
graph_element = self.myElement("graph",
|
|
edgedefault=default_edge_type)
|
|
else:
|
|
graph_element = self.myElement("graph",
|
|
edgedefault=default_edge_type,
|
|
id=graphid)
|
|
default = {}
|
|
data = {k: v for (k, v) in G.graph.items()
|
|
if k not in ['node_default', 'edge_default']}
|
|
self.add_attributes("graph", graph_element, data, default)
|
|
self.add_nodes(G, graph_element)
|
|
self.add_edges(G, graph_element)
|
|
|
|
# self.attributes contains a mapping from XML Objects to a list of
|
|
# data that needs to be added to them.
|
|
# We postpone processing in order to do type inference/generalization.
|
|
# See self.attr_type
|
|
for (xml_obj, data) in self.attributes.items():
|
|
for (k, v, scope, default) in data:
|
|
xml_obj.append(self.add_data(make_str(k),
|
|
self.attr_type(k, scope, v),
|
|
make_str(v), scope, default))
|
|
self.xml.append(graph_element)
|
|
|
|
def add_graphs(self, graph_list):
|
|
""" Add many graphs to this GraphML document. """
|
|
for G in graph_list:
|
|
self.add_graph_element(G)
|
|
|
|
def dump(self, stream):
|
|
if self.prettyprint:
|
|
self.indent(self.xml)
|
|
document = ElementTree(self.xml)
|
|
document.write(stream, encoding=self.encoding, xml_declaration=True)
|
|
|
|
def indent(self, elem, level=0):
|
|
# in-place prettyprint formatter
|
|
i = "\n" + level * " "
|
|
if len(elem):
|
|
if not elem.text or not elem.text.strip():
|
|
elem.text = i + " "
|
|
if not elem.tail or not elem.tail.strip():
|
|
elem.tail = i
|
|
for elem in elem:
|
|
self.indent(elem, level + 1)
|
|
if not elem.tail or not elem.tail.strip():
|
|
elem.tail = i
|
|
else:
|
|
if level and (not elem.tail or not elem.tail.strip()):
|
|
elem.tail = i
|
|
|
|
|
|
class IncrementalElement(object):
|
|
"""Wrapper for _IncrementalWriter providing an Element like interface.
|
|
|
|
This wrapper does not intend to be a complete implementation but rather to
|
|
deal with those calls used in GraphMLWriter.
|
|
"""
|
|
|
|
def __init__(self, xml, prettyprint):
|
|
self.xml = xml
|
|
self.prettyprint = prettyprint
|
|
|
|
def append(self, element):
|
|
self.xml.write(element, pretty_print=self.prettyprint)
|
|
|
|
|
|
class GraphMLWriterLxml(GraphMLWriter):
|
|
def __init__(self, path, graph=None, encoding='utf-8', prettyprint=True,
|
|
infer_numeric_types=False):
|
|
self.myElement = lxmletree.Element
|
|
|
|
self._encoding = encoding
|
|
self._prettyprint = prettyprint
|
|
self.infer_numeric_types = infer_numeric_types
|
|
|
|
self._xml_base = lxmletree.xmlfile(path, encoding=encoding)
|
|
self._xml = self._xml_base.__enter__()
|
|
self._xml.write_declaration()
|
|
|
|
# We need to have a xml variable that support insertion. This call is
|
|
# used for adding the keys to the document.
|
|
# We will store those keys in a plain list, and then after the graph
|
|
# element is closed we will add them to the main graphml element.
|
|
self.xml = []
|
|
self._keys = self.xml
|
|
self._graphml = self._xml.element(
|
|
'graphml',
|
|
{
|
|
'xmlns': self.NS_GRAPHML,
|
|
'xmlns:xsi': self.NS_XSI,
|
|
'xsi:schemaLocation': self.SCHEMALOCATION
|
|
})
|
|
self._graphml.__enter__()
|
|
self.keys = {}
|
|
self.attribute_types = defaultdict(set)
|
|
|
|
if graph is not None:
|
|
self.add_graph_element(graph)
|
|
|
|
def add_graph_element(self, G):
|
|
"""
|
|
Serialize graph G in GraphML to the stream.
|
|
"""
|
|
if G.is_directed():
|
|
default_edge_type = 'directed'
|
|
else:
|
|
default_edge_type = 'undirected'
|
|
|
|
graphid = G.graph.pop('id', None)
|
|
if graphid is None:
|
|
graph_element = self._xml.element('graph',
|
|
edgedefault=default_edge_type)
|
|
else:
|
|
graph_element = self._xml.element('graph',
|
|
edgedefault=default_edge_type,
|
|
id=graphid)
|
|
|
|
# gather attributes types for the whole graph
|
|
# to find the most general numeric format needed.
|
|
# Then pass through attributes to create key_id for each.
|
|
graphdata = {k: v for k, v in G.graph.items()
|
|
if k not in ('node_default', 'edge_default')}
|
|
node_default = G.graph.get('node_default', {})
|
|
edge_default = G.graph.get('edge_default', {})
|
|
# Graph attributes
|
|
for k, v in graphdata.items():
|
|
self.attribute_types[(make_str(k), "graph")].add(type(v))
|
|
for k, v in graphdata.items():
|
|
element_type = self.xml_type[self.attr_type(k, "graph", v)]
|
|
self.get_key(make_str(k), element_type, "graph", None)
|
|
# Nodes and data
|
|
for node, d in G.nodes(data=True):
|
|
for k, v in d.items():
|
|
self.attribute_types[(make_str(k), "node")].add(type(v))
|
|
for node, d in G.nodes(data=True):
|
|
for k, v in d.items():
|
|
T = self.xml_type[self.attr_type(k, "node", v)]
|
|
self.get_key(make_str(k), T, "node", node_default.get(k))
|
|
# Edges and data
|
|
if G.is_multigraph():
|
|
for u, v, ekey, d in G.edges(keys=True, data=True):
|
|
for k, v in d.items():
|
|
self.attribute_types[(make_str(k), "edge")].add(type(v))
|
|
for u, v, ekey, d in G.edges(keys=True, data=True):
|
|
for k, v in d.items():
|
|
T = self.xml_type[self.attr_type(k, "edge", v)]
|
|
self.get_key(make_str(k), T, "edge", edge_default.get(k))
|
|
else:
|
|
for u, v, d in G.edges(data=True):
|
|
for k, v in d.items():
|
|
self.attribute_types[(make_str(k), "edge")].add(type(v))
|
|
for u, v, d in G.edges(data=True):
|
|
for k, v in d.items():
|
|
T = self.xml_type[self.attr_type(k, "edge", v)]
|
|
self.get_key(make_str(k), T, "edge", edge_default.get(k))
|
|
|
|
# Now add attribute keys to the xml file
|
|
for key in self.xml:
|
|
self._xml.write(key, pretty_print=self._prettyprint)
|
|
|
|
# The incremental_writer writes each node/edge as it is created
|
|
incremental_writer = IncrementalElement(self._xml, self._prettyprint)
|
|
with graph_element:
|
|
self.add_attributes('graph', incremental_writer, graphdata, {})
|
|
self.add_nodes(G, incremental_writer) # adds attributes too
|
|
self.add_edges(G, incremental_writer) # adds attributes too
|
|
|
|
def add_attributes(self, scope, xml_obj, data, default):
|
|
"""Appends attribute data."""
|
|
for k, v in data.items():
|
|
data_element = self.add_data(make_str(k),
|
|
self.attr_type(make_str(k), scope, v),
|
|
make_str(v), scope, default.get(k))
|
|
xml_obj.append(data_element)
|
|
|
|
def __str__(self):
|
|
return object.__str__(self)
|
|
|
|
def dump(self):
|
|
self._graphml.__exit__(None, None, None)
|
|
self._xml_base.__exit__(None, None, None)
|
|
|
|
|
|
# Choose a writer function for default
|
|
if lxmletree is None:
|
|
write_graphml = write_graphml_xml
|
|
else:
|
|
write_graphml = write_graphml_lxml
|
|
|
|
|
|
class GraphMLReader(GraphML):
|
|
"""Read a GraphML document. Produces NetworkX graph objects."""
|
|
|
|
def __init__(self, node_type=str, edge_key_type=int):
|
|
try:
|
|
import xml.etree.ElementTree
|
|
except ImportError:
|
|
msg = 'GraphML reader requires xml.elementtree.ElementTree'
|
|
raise ImportError(msg)
|
|
self.node_type = node_type
|
|
self.edge_key_type = edge_key_type
|
|
self.multigraph = False # assume multigraph and test for multiedges
|
|
self.edge_ids = {} # dict mapping (u,v) tuples to id edge attributes
|
|
|
|
def __call__(self, path=None, string=None):
|
|
if path is not None:
|
|
self.xml = ElementTree(file=path)
|
|
elif string is not None:
|
|
self.xml = fromstring(string)
|
|
else:
|
|
raise ValueError("Must specify either 'path' or 'string' as kwarg")
|
|
(keys, defaults) = self.find_graphml_keys(self.xml)
|
|
for g in self.xml.findall("{%s}graph" % self.NS_GRAPHML):
|
|
yield self.make_graph(g, keys, defaults)
|
|
|
|
def make_graph(self, graph_xml, graphml_keys, defaults, G=None):
|
|
# set default graph type
|
|
edgedefault = graph_xml.get("edgedefault", None)
|
|
if G is 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 doesn't support hyperedges")
|
|
# add nodes
|
|
for node_xml in graph_xml.findall("{%s}node" % self.NS_GRAPHML):
|
|
self.add_node(G, node_xml, graphml_keys, defaults)
|
|
# 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():
|
|
G = nx.DiGraph(G)
|
|
else:
|
|
G = nx.Graph(G)
|
|
nx.set_edge_attributes(G, values=self.edge_ids, name='id')
|
|
|
|
return G
|
|
|
|
def add_node(self, G, node_xml, graphml_keys, defaults):
|
|
"""Add a node to the graph.
|
|
"""
|
|
# warn on finding unsupported ports tag
|
|
ports = node_xml.find("{%s}port" % self.NS_GRAPHML)
|
|
if ports is not None:
|
|
warnings.warn("GraphML port tag not supported.")
|
|
# find the node by id and cast it to the appropriate type
|
|
node_id = self.node_type(node_xml.get("id"))
|
|
# get data/attributes for node
|
|
data = self.decode_data_elements(graphml_keys, node_xml)
|
|
G.add_node(node_id, **data)
|
|
# get child nodes
|
|
if node_xml.attrib.get('yfiles.foldertype') == 'group':
|
|
graph_xml = node_xml.find("{%s}graph" % self.NS_GRAPHML)
|
|
self.make_graph(graph_xml, graphml_keys, defaults, G)
|
|
|
|
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':
|
|
msg = "directed=false edge found in directed graph."
|
|
raise nx.NetworkXError(msg)
|
|
if (not G.is_directed()) and directed == 'true':
|
|
msg = "directed=true edge found in undirected graph."
|
|
raise nx.NetworkXError(msg)
|
|
|
|
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:
|
|
# self.edge_ids is used by `make_graph` method for non-multigraphs
|
|
self.edge_ids[source, target] = edge_id
|
|
try:
|
|
edge_id = self.edge_key_type(edge_id)
|
|
except ValueError: # Could not convert.
|
|
pass
|
|
else:
|
|
edge_id = data.get('key')
|
|
|
|
if G.has_edge(source, target):
|
|
# mark this as a multigraph
|
|
self.multigraph = True
|
|
|
|
# Use add_edges_from to avoid error with add_edge when `'key' in data`
|
|
G.add_edges_from([(source, target, edge_id, data)])
|
|
|
|
def decode_data_elements(self, graphml_keys, obj_xml):
|
|
"""Use the key information to decode the data XML if present."""
|
|
data = {}
|
|
for data_element in obj_xml.findall("{%s}data" % self.NS_GRAPHML):
|
|
key = data_element.get("key")
|
|
try:
|
|
data_name = graphml_keys[key]['name']
|
|
data_type = graphml_keys[key]['type']
|
|
except KeyError:
|
|
raise nx.NetworkXError("Bad GraphML data: no key %s" % key)
|
|
text = data_element.text
|
|
# assume anything with subelements is a yfiles extension
|
|
if text is not None and len(list(data_element)) == 0:
|
|
if data_type == bool:
|
|
# Ignore cases.
|
|
# http://docs.oracle.com/javase/6/docs/api/java/lang/
|
|
# Boolean.html#parseBoolean%28java.lang.String%29
|
|
data[data_name] = self.convert_bool[text.lower()]
|
|
else:
|
|
data[data_name] = data_type(text)
|
|
elif len(list(data_element)) > 0:
|
|
# Assume yfiles as subelements, try to extract node_label
|
|
node_label = None
|
|
for node_type in ['ShapeNode', 'SVGNode', 'ImageNode']:
|
|
pref = "{%s}%s/{%s}" % (self.NS_Y, node_type, self.NS_Y)
|
|
geometry = data_element.find("%sGeometry" % pref)
|
|
if geometry is not None:
|
|
data['x'] = geometry.get('x')
|
|
data['y'] = geometry.get('y')
|
|
if node_label is None:
|
|
node_label = data_element.find("%sNodeLabel" % pref)
|
|
if node_label is not None:
|
|
data['label'] = node_label.text
|
|
|
|
# check all the different types of edges avaivable in yEd.
|
|
for e in ['PolyLineEdge', 'SplineEdge', 'QuadCurveEdge',
|
|
'BezierEdge', 'ArcEdge']:
|
|
pref = "{%s}%s/{%s}" % (self.NS_Y, e, self.NS_Y)
|
|
edge_label = data_element.find("%sEdgeLabel" % pref)
|
|
if edge_label is not None:
|
|
break
|
|
|
|
if edge_label is not None:
|
|
data['label'] = edge_label.text
|
|
return data
|
|
|
|
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." % 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 pytest
|
|
def setup_module(module):
|
|
import pytest
|
|
xml.etree.ElementTree = pytest.importorskip('xml.etree.ElementTree')
|
|
|
|
|
|
# fixture for pytest
|
|
def teardown_module(module):
|
|
import os
|
|
try:
|
|
os.unlink('test.graphml')
|
|
except:
|
|
pass
|