def _get_networks_tag(self):
bs = BeautifulSoup()
networks_tag = bs.new_tag('networks')
for key in self.networks:
network_tag = bs.new_tag('network')
network_tag['sourceType'] = self.networks[key][1]['sourceType']
network_tag['source'] = self.networks[key][1]['source']
network_tag['targetType'] = self.networks[key][1]['targetType']
network_tag['target'] = self.networks[key][1]['target']
network_tag['id'] = key
network_tag['isDirected'] = dmlpu.unformat_prop(self.networks[key]['isDirected'])
network_tag['allowSelfLoops'] = dmlpu.unformat_prop(self.networks[key]['allowSelfLoops'])
network_tag['isBinary'] = dmlpu.unformat_prop(self.networks[key]['isBinary'])
e_l = self.networks[key].edge_list()
if self.networks[key]['isBinary']:
for i in range(len(e_l)):
network_tag.append(bs.new_tag('link', source=e_l[i][0], target=e_l[i][1]))
else:
for i in range(len(e_l)):
network_tag.append(bs.new_tag('link', source=e_l[i][0], target=e_l[i][1],
value=self.networks[key].es[i]['weight']))
networks_tag.append(network_tag)
return networks_tag
def _get_networks_tag(self):
bs = BeautifulSoup()
networks_tag = bs.new_tag('networks')
for key in self.networks:
network_tag = bs.new_tag('network')
network_tag['sourceType'] = self.networks[key].graph['sourceType']
network_tag['source'] = self.networks[key].graph['source']
network_tag['targetType'] = self.networks[key].graph['targetType']
network_tag['target'] = self.networks[key].graph['target']
network_tag['id'] = key
network_tag['isDirected'] = dmlpu.unformat_prop(
self.networks[key].graph['isDirected'])
network_tag['allowSelfLoops'] = dmlpu.unformat_prop(
self.networks[key].graph['allowSelfLoops'])
network_tag['isBinary'] = dmlpu.unformat_prop(
self.networks[key].graph['isBinary'])
if self.networks[key].graph['isBinary']:
for edge in self.networks[key].edges_iter(data=True):
network_tag.append(
bs.new_tag('link',
source=edge[0],
target=edge[1],
value=edge[2]['weight']))
else:
for edge in self.networks[key].edges_iter():
network_tag.append(
bs.new_tag('link', source=edge[0], target=edge[1]))
networks_tag.append(network_tag)
return networks_tag
def convert_to_dynetml(self, is_entire_file=False):
"""
Converts the graph to dynetml and returns a BeautifulSoup tag
:param is_entire_file: if True, wraps value as a soup. If False, returns the top tag
:type is_entire_file: bool
:return: bs4.element.Tag
:raise TypeError: if is_entire_file isn't a bool
"""
dmlpu.check_type(is_entire_file, 'is_entire_file', bool)
bs = BeautifulSoup(features='xml')
bs.append(bs.new_tag('MetaNetwork'))
for attr in self.attributes:
bs.MetaNetwork[attr] = dmlpu.unformat_prop(self.attributes[attr])
bs.MetaNetwork.append(dmlpu.get_property_identities_tag(self.propertyIdentities))
bs.MetaNetwork.append(bs.new_tag('properties'))
for key in self.properties:
prop_tag = bs.new_tag('property')
prop_tag['id'] = key
prop_tag['value'] = dmlpu.unformat_prop(self.properties[key])
bs.MetaNetwork.properties.append(prop_tag)
bs.MetaNetwork.append(bs.new_tag('nodes'))
for class_type in self.__node_tree:
for class_id in self.__node_tree[class_type]:
nodeclass_tag = bs.new_tag('nodeclass', type=class_type, id=class_id)
nodeclass_tag.append(dmlpu.get_property_identities_tag(self.__node_tree[class_type][class_id][0]))
for key in self.__node_tree[class_type][class_id][1]:
node_tag = bs.new_tag('node', id=key)
for attr in self.__node_tree[class_type][class_id][1][key][0]:
node_tag[attr] = dmlpu.unformat_prop(self.__node_tree[class_type][class_id][1][key][0][attr])
node_tag.append(dmlpu.get_properties_tag(self.__node_tree[class_type][class_id][1][key][1]))
nodeclass_tag.append(node_tag)
bs.MetaNetwork.nodes.append(nodeclass_tag)
networks_tag = self._get_networks_tag()
bs.MetaNetwork.networks.append(networks_tag)
if not is_entire_file:
bs = bs.MetaNetwork
return bs
def _get_networks_tag(self):
# bs = BeautifulSoup()
# networks_tag = bs.new_tag('networks')
# for key in self.networks:
# network_tag = bs.new_tag('network')
# network_tag['sourceType'] = self.networks[key][1]['sourceType']
# network_tag['source'] = self.networks[key][1]['source']
# network_tag['targetType'] = self.networks[key][1]['targetType']
# network_tag['target'] = self.networks[key][1]['target']
# network_tag['id'] = key
# network_tag['isDirected'] = dmlpu.unformat_prop(self.networks[key]['isDirected'])
# network_tag['allowSelfLoops'] = dmlpu.unformat_prop(self.networks[key]['allowSelfLoops'])
# network_tag['isBinary'] = dmlpu.unformat_prop(self.networks[key]['isBinary'])
#
# e_l = self.networks[key].edge_list()
# if self.networks[key]['isBinary']:
# for i in range(len(e_l)):
# network_tag.append(bs.new_tag('link', source=e_l[i][0], target=e_l[i][1]))
# else:
# for i in range(len(e_l)):
# network_tag.append(bs.new_tag('link', source=e_l[i][0], target=e_l[i][1],
# value=self.networks[key].es[i]['weight']))
#
# networks_tag.append(network_tag)
#
# return networks_tag
networks_tag = etree.Element('networks')
for key in self.networks:
network_tag = etree.SubElement(networks_tag, 'network', attrib={
'sourceType': self.networks[key][1]['sourceType'], 'source': self.networks[key][1]['source'],
'targetType': self.networks[key][1]['targetType'], 'target': self.networks[key][1]['target'],
'id': key, 'isDirected': dmlpu.unformat_prop(self.networks[key]['isDirected']),
'allowSelfLoops': dmlpu.unformat_prop(self.networks[key]['allowSelfLoops']),
'isBinary': dmlpu.unformat_prop(self.networks[key]['isBinary'])})
e_l = self.networks[key].edge_list()
if self.networks[key]['isBinary']:
for i in range(len(e_l)):
etree.SubElement(network_tag, 'link', attrib={'source': e_l[i][0], 'target': e_l[i][1]})
else:
for i in range(len(e_l)):
etree.SubElement(network_tag, 'link', attrib={'source': e_l[i][0], 'target': e_l[i][1],
'value': self.networks[key].es[i]['weight']})
return networks_tag
def _get_networks_tag(self):
"""Generates an :class:`lxml._Element` from the networks"""
# bs = BeautifulSoup()
# networks_tag = bs.new_tag('networks')
# for key in self.networks:
# network_tag = bs.new_tag('network')
# network_tag['sourceType'] = self.networks[key][0]['sourceType']
# network_tag['source'] = self.networks[key][0]['source']
# network_tag['targetType'] = self.networks[key][0]['targetType']
# network_tag['target'] = self.networks[key][0]['target']
# network_tag['id'] = key
# network_tag['isDirected'] = dmlpu.unformat_prop(self.networks[key][0]['isDirected'])
# network_tag['allowSelfLoops'] = dmlpu.unformat_prop(self.networks[key][0]['allowSelfLoops'])
# network_tag['isBinary'] = dmlpu.unformat_prop(self.networks[key][0]['isBinary'])
#
# if self.networks[key][0]['isBinary']:
# for edge in self.networks[key].edges_iter():
# network_tag.append(bs.new_tag('link', source=edge[0], target=edge[1]))
# else:
# for edge in self.networks[key].edges_iter(data=True):
# network_tag.append(bs.new_tag('link', source=edge[0], target=edge[1], value=edge[2]['weight']))
#
# networks_tag.append(network_tag)
#
# return networks_tag
networks_tag = etree.Element('networks')
for key in self.networks:
network_tag = etree.SubElement(networks_tag, 'network', attrib={
'sourceType': self.networks[key][0]['sourceType'], 'source': self.networks[key][0]['source'],
'targetType': self.networks[key][0]['targetType'], 'target': self.networks[key][0]['target'],
'id': key, 'isDirected': dmlpu.unformat_prop(self.networks[key][0]['isDirected']),
'allowSelfLoops': dmlpu.unformat_prop(self.networks[key][0]['allowSelfLoops']),
'isBinary': dmlpu.unformat_prop(self.networks[key][0]['isBinary'])})
if self.networks[key][0]['isBinary']:
for edge in self.networks[key].edges_iter():
etree.SubElement(network_tag, 'link', attrib={'source': edge[0], 'target': edge[1]})
else:
for edge in self.networks[key].edges_iter(data=True):
etree.SubElement(network_tag, 'link', attrib={'source': edge[0], 'target': edge[1],
'value': edge[2]['weight']})
return networks_tag
def _get_networks_tag(self):
bs = BeautifulSoup()
networks_tag = bs.new_tag('networks')
for key in self.networks:
network_tag = bs.new_tag('network')
network_tag['sourceType'] = self.networks[key][0]['sourceType']
network_tag['source'] = self.networks[key][0]['source']
network_tag['targetType'] = self.networks[key][0]['targetType']
network_tag['target'] = self.networks[key][0]['target']
network_tag['id'] = key
network_tag['isDirected'] = dmlpu.unformat_prop(self.networks[key][0]['isDirected'])
network_tag['allowSelfLoops'] = dmlpu.unformat_prop(self.networks[key][0]['allowSelfLoops'])
network_tag['isBinary'] = dmlpu.unformat_prop(self.networks[key][0]['isBinary'])
if self.networks[key][0]['isBinary']:
for edge in self.networks[key].edges_iter():
network_tag.append(bs.new_tag('link', source=edge[0], target=edge[1]))
else:
for edge in self.networks[key].edges_iter(data=True):
network_tag.append(bs.new_tag('link', source=edge[0], target=edge[1], value=edge[2]['weight']))
networks_tag.append(network_tag)
return networks_tag
def _get_networks_tag(self):
bs = BeautifulSoup()
networks_tag = bs.new_tag("networks")
for key in self.networks:
network_tag = bs.new_tag("network")
network_tag["sourceType"] = self.networks[key].graph["sourceType"]
network_tag["source"] = self.networks[key].graph["source"]
network_tag["targetType"] = self.networks[key].graph["targetType"]
network_tag["target"] = self.networks[key].graph["target"]
network_tag["id"] = key
network_tag["isDirected"] = dmlpu.unformat_prop(self.networks[key].graph["isDirected"])
network_tag["allowSelfLoops"] = dmlpu.unformat_prop(self.networks[key].graph["allowSelfLoops"])
network_tag["isBinary"] = dmlpu.unformat_prop(self.networks[key].graph["isBinary"])
if self.networks[key].graph["isBinary"]:
for edge in self.networks[key].edges_iter(data=True):
network_tag.append(bs.new_tag("link", source=edge[0], target=edge[1], value=edge[2]["weight"]))
else:
for edge in self.networks[key].edges_iter():
network_tag.append(bs.new_tag("link", source=edge[0], target=edge[1]))
networks_tag.append(network_tag)
return networks_tag
def convert_to_dynetml(self):
"""Return the dynamic meta-network as an :class:`lxml._Element`"""
# bs = BeautifulSoup(features='xml')
# bs.append(bs.new_tag('DynamicMetaNetwork'))
# for attr in self.attributes:
# bs.DynamicMetaNetwork[attr] = dmlpu.unformat_prop(self.attributes[attr])
#
# for mn in self.metanetworks:
# bs.DynamicMetaNetwork.append(mn.convert_to_dynetml())
#
# if not is_entire_file:
# bs = bs.DynamicMetaNetwork
#
# return bs
dmn = etree.Element('DynamicMetaNetwork')
for attr in self.attributes:
dmn.attrib[attr] = dmlpu.unformat_prop(self.attributes[attr])
for mn in self.metanetworks:
etree.SubElement(dmn, mn.convert_to_dynetml())
return dmn
def convert_to_dynetml(self, is_entire_file=False):
"""
Converts the dynamic meta network to a BeautifulSoup Tag and returns it
:param is_entire_file: If True, Tag will include XML wrapper code
:type is_entire_file: bool
:return: a BeautifulSoup Tag
:raise TypeError: if is_entire_file is not a bool
"""
if not isinstance(is_entire_file, bool):
raise TypeError('is_entire_file must be True or False')
bs = BeautifulSoup(features='xml')
bs.append(bs.new_tag('DynamicMetaNetwork'))
for attr in self.attributes:
bs.DynamicMetaNetwork[attr] = dmlpu.unformat_prop(self.attributes[attr])
for mn in self.metanetworks:
bs.DynamicMetaNetwork.append(mn.convert_to_dynetml())
if not is_entire_file:
bs = bs.DynamicMetaNetwork
return bs
def convert_to_dynetml(self):
"""Converts the graph to DyNetML and returns an :class:`lxml._Element`"""
# bs = BeautifulSoup(features='xml')
# bs.append(bs.new_tag('MetaNetwork'))
#
# for attr in self.attributes:
# bs.MetaNetwork[attr] = dmlpu.unformat_prop(self.attributes[attr])
#
# bs.MetaNetwork.append(dmlpu.get_property_identities_tag(self.propertyIdentities))
#
# bs.MetaNetwork.append(bs.new_tag('properties'))
# for key in self.properties:
# prop_tag = bs.new_tag('property')
# prop_tag['id'] = key
# prop_tag['value'] = dmlpu.unformat_prop(self.properties[key])
# bs.MetaNetwork.properties.append(prop_tag)
#
# bs.MetaNetwork.append(bs.new_tag('nodes'))
# for class_type in self.__node_tree:
# for class_id in self.__node_tree[class_type]:
# nodeclass_tag = bs.new_tag('nodeclass', type=class_type, id=class_id)
# nodeclass_tag.append(dmlpu.get_property_identities_tag(self.__node_tree[class_type][class_id][0]))
#
# for key in self.__node_tree[class_type][class_id][1]:
# node_tag = bs.new_tag('node', id=key)
# for attr in self.__node_tree[class_type][class_id][1][key][0]:
# node_tag[attr] = dmlpu.unformat_prop(self.__node_tree[class_type][class_id][1][key][0][attr])
# node_tag.append(dmlpu.get_properties_tag(self.__node_tree[class_type][class_id][1][key][1]))
# nodeclass_tag.append(node_tag)
#
# bs.MetaNetwork.nodes.append(nodeclass_tag)
#
# networks_tag = self._get_networks_tag()
# bs.MetaNetwork.networks.append(networks_tag)
#
# if not is_entire_file:
# bs = bs.MetaNetwork
#
# return bs
mn = etree.Element('MetaNetwork')
for attr in self.attributes:
mn.attrib[attr] = dmlpu.unformat_prop(self.attributes[attr])
etree.SubElement(mn, dmlpu.get_property_identities_tag(self.propertyIdentities))
properties_tag = etree.SubElement(mn, 'properties')
for key in self.properties:
prop_tag = etree.SubElement(properties_tag, 'property')
prop_tag.attrib['id'] = key
prop_tag['value'] = dmlpu.unformat_prop(self.properties[key])
nodes_tag = etree.SubElement(mn, 'nodes')
for class_type in self.__node_tree:
for class_id in self.__node_tree[class_type]:
nodeclass_tag = etree.SubElement(nodes_tag, 'nodeclass', attrib={'type': class_type, 'id': class_id})
etree.SubElement(nodeclass_tag,
dmlpu.get_property_identities_tag(self.__node_tree[class_type][class_id][0]))
etree.SubElement(mn, self._get_networks_tag())
return mn