""" Utilities function to manage graph files
"""
from os.path import dirname, splitext
[docs]def loadCT(filename):
"""load data from a Chemical Table (.ct) file.
Notes
------
a typical example of data in .ct is like this:
3 2 <- number of nodes and edges
0.0000 0.0000 0.0000 C <- each line describes a node (x,y,z + label)
0.0000 0.0000 0.0000 C
0.0000 0.0000 0.0000 O
1 3 1 1 <- each line describes an edge : to, from, bond type, bond stereo
2 3 1 1
Check `CTFile Formats file <https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=10&ved=2ahUKEwivhaSdjsTlAhVhx4UKHczHA8gQFjAJegQIARAC&url=https%3A%2F%2Fwww.daylight.com%2Fmeetings%2Fmug05%2FKappler%2Fctfile.pdf&usg=AOvVaw1cDNrrmMClkFPqodlF2inS>`__
for detailed format discription.
"""
import networkx as nx
from os.path import basename
g = nx.Graph()
with open(filename) as f:
content = f.read().splitlines()
g = nx.Graph(
name = str(content[0]),
filename = basename(filename)) # set name of the graph
tmp = content[1].split(" ")
if tmp[0] == '':
nb_nodes = int(tmp[1]) # number of the nodes
nb_edges = int(tmp[2]) # number of the edges
else:
nb_nodes = int(tmp[0])
nb_edges = int(tmp[1])
# patch for compatibility : label will be removed later
for i in range(0, nb_nodes):
tmp = content[i + 2].split(" ")
tmp = [x for x in tmp if x != '']
g.add_node(i, atom=tmp[3].strip(),
label=[item.strip() for item in tmp[3:]],
attributes=[item.strip() for item in tmp[0:3]])
for i in range(0, nb_edges):
tmp = content[i + g.number_of_nodes() + 2].split(" ")
tmp = [x for x in tmp if x != '']
g.add_edge(int(tmp[0]) - 1, int(tmp[1]) - 1,
bond_type=tmp[2].strip(),
label=[item.strip() for item in tmp[2:]])
return g
[docs]def loadGXL(filename):
from os.path import basename
import networkx as nx
import xml.etree.ElementTree as ET
tree = ET.parse(filename)
root = tree.getroot()
index = 0
g = nx.Graph(filename=basename(filename), name=root[0].attrib['id'])
dic = {} # used to retrieve incident nodes of edges
for node in root.iter('node'):
dic[node.attrib['id']] = index
labels = {}
for attr in node.iter('attr'):
labels[attr.attrib['name']] = attr[0].text
if 'chem' in labels:
labels['label'] = labels['chem']
labels['atom'] = labels['chem']
g.add_node(index, **labels)
index += 1
for edge in root.iter('edge'):
labels = {}
for attr in edge.iter('attr'):
labels[attr.attrib['name']] = attr[0].text
if 'valence' in labels:
labels['label'] = labels['valence']
labels['bond_type'] = labels['valence']
g.add_edge(dic[edge.attrib['from']], dic[edge.attrib['to']], **labels)
return g
[docs]def saveGXL(graph, filename, method='default', node_labels=[], edge_labels=[], node_attrs=[], edge_attrs=[]):
if method == 'default':
gxl_file = open(filename, 'w')
gxl_file.write("<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n")
gxl_file.write("<!DOCTYPE gxl SYSTEM \"http://www.gupro.de/GXL/gxl-1.0.dtd\">\n")
gxl_file.write("<gxl xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n")
if 'name' in graph.graph:
name = str(graph.graph['name'])
else:
name = 'dummy'
gxl_file.write("<graph id=\"" + name + "\" edgeids=\"false\" edgemode=\"undirected\">\n")
for v, attrs in graph.nodes(data=True):
gxl_file.write("<node id=\"_" + str(v) + "\">")
for l_name in node_labels:
gxl_file.write("<attr name=\"" + l_name + "\"><int>" +
str(attrs[l_name]) + "</int></attr>")
for a_name in node_attrs:
gxl_file.write("<attr name=\"" + a_name + "\"><float>" +
str(attrs[a_name]) + "</float></attr>")
gxl_file.write("</node>\n")
for v1, v2, attrs in graph.edges(data=True):
gxl_file.write("<edge from=\"_" + str(v1) + "\" to=\"_" + str(v2) + "\">")
for l_name in edge_labels:
gxl_file.write("<attr name=\"" + l_name + "\"><int>" +
str(attrs[l_name]) + "</int></attr>")
for a_name in edge_attrs:
gxl_file.write("<attr name=\"" + a_name + "\"><float>" +
str(attrs[a_name]) + "</float></attr>")
gxl_file.write("</edge>\n")
gxl_file.write("</graph>\n")
gxl_file.write("</gxl>")
gxl_file.close()
elif method == 'benoit':
import xml.etree.ElementTree as ET
root_node = ET.Element('gxl')
attr = dict()
attr['id'] = str(graph.graph['name'])
attr['edgeids'] = 'true'
attr['edgemode'] = 'undirected'
graph_node = ET.SubElement(root_node, 'graph', attrib=attr)
for v in graph:
current_node = ET.SubElement(graph_node, 'node', attrib={'id': str(v)})
for attr in graph.nodes[v].keys():
cur_attr = ET.SubElement(
current_node, 'attr', attrib={'name': attr})
cur_value = ET.SubElement(cur_attr,
graph.nodes[v][attr].__class__.__name__)
cur_value.text = graph.nodes[v][attr]
for v1 in graph:
for v2 in graph[v1]:
if (v1 < v2): # Non oriented graphs
cur_edge = ET.SubElement(
graph_node,
'edge',
attrib={
'from': str(v1),
'to': str(v2)
})
for attr in graph[v1][v2].keys():
cur_attr = ET.SubElement(
cur_edge, 'attr', attrib={'name': attr})
cur_value = ET.SubElement(
cur_attr, graph[v1][v2][attr].__class__.__name__)
cur_value.text = str(graph[v1][v2][attr])
tree = ET.ElementTree(root_node)
tree.write(filename)
elif method == 'gedlib':
# reference: https://github.com/dbblumenthal/gedlib/blob/master/data/generate_molecules.py#L22
# pass
gxl_file = open(filename, 'w')
gxl_file.write("<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n")
gxl_file.write("<!DOCTYPE gxl SYSTEM \"http://www.gupro.de/GXL/gxl-1.0.dtd\">\n")
gxl_file.write("<gxl xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n")
gxl_file.write("<graph id=\"" + str(graph.graph['name']) + "\" edgeids=\"true\" edgemode=\"undirected\">\n")
for v, attrs in graph.nodes(data=True):
gxl_file.write("<node id=\"_" + str(v) + "\">")
gxl_file.write("<attr name=\"" + "chem" + "\"><int>" + str(attrs['chem']) + "</int></attr>")
gxl_file.write("</node>\n")
for v1, v2, attrs in graph.edges(data=True):
gxl_file.write("<edge from=\"_" + str(v1) + "\" to=\"_" + str(v2) + "\">")
gxl_file.write("<attr name=\"valence\"><int>" + str(attrs['valence']) + "</int></attr>")
# gxl_file.write("<attr name=\"valence\"><int>" + "1" + "</int></attr>")
gxl_file.write("</edge>\n")
gxl_file.write("</graph>\n")
gxl_file.write("</gxl>")
gxl_file.close()
elif method == 'gedlib-letter':
# reference: https://github.com/dbblumenthal/gedlib/blob/master/data/generate_molecules.py#L22
# and https://github.com/dbblumenthal/gedlib/blob/master/data/datasets/Letter/HIGH/AP1_0000.gxl
gxl_file = open(filename, 'w')
gxl_file.write("<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n")
gxl_file.write("<!DOCTYPE gxl SYSTEM \"http://www.gupro.de/GXL/gxl-1.0.dtd\">\n")
gxl_file.write("<gxl xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n")
gxl_file.write("<graph id=\"" + str(graph.graph['name']) + "\" edgeids=\"false\" edgemode=\"undirected\">\n")
for v, attrs in graph.nodes(data=True):
gxl_file.write("<node id=\"_" + str(v) + "\">")
gxl_file.write("<attr name=\"x\"><float>" + str(attrs['attributes'][0]) + "</float></attr>")
gxl_file.write("<attr name=\"y\"><float>" + str(attrs['attributes'][1]) + "</float></attr>")
gxl_file.write("</node>\n")
for v1, v2, attrs in graph.edges(data=True):
gxl_file.write("<edge from=\"_" + str(v1) + "\" to=\"_" + str(v2) + "\"/>\n")
gxl_file.write("</graph>\n")
gxl_file.write("</gxl>")
gxl_file.close()
[docs]def loadSDF(filename):
"""load data from structured data file (.sdf file).
Notes
------
A SDF file contains a group of molecules, represented in the similar way as in MOL format.
Check `here <http://www.nonlinear.com/progenesis/sdf-studio/v0.9/faq/sdf-file-format-guidance.aspx>`__ for detailed structure.
"""
import networkx as nx
from os.path import basename
from tqdm import tqdm
import sys
data = []
with open(filename) as f:
content = f.read().splitlines()
index = 0
pbar = tqdm(total=len(content) + 1, desc='load SDF', file=sys.stdout)
while index < len(content):
index_old = index
g = nx.Graph(name=content[index].strip()) # set name of the graph
tmp = content[index + 3]
nb_nodes = int(tmp[:3]) # number of the nodes
nb_edges = int(tmp[3:6]) # number of the edges
for i in range(0, nb_nodes):
tmp = content[i + index + 4]
g.add_node(i, atom=tmp[31:34].strip())
for i in range(0, nb_edges):
tmp = content[i + index + g.number_of_nodes() + 4]
tmp = [tmp[i:i + 3] for i in range(0, len(tmp), 3)]
g.add_edge(
int(tmp[0]) - 1, int(tmp[1]) - 1, bond_type=tmp[2].strip())
data.append(g)
index += 4 + g.number_of_nodes() + g.number_of_edges()
while content[index].strip() != '$$$$': # seperator
index += 1
index += 1
pbar.update(index - index_old)
pbar.update(1)
pbar.close()
return data
[docs]def loadMAT(filename, extra_params):
"""Load graph data from a MATLAB (up to version 7.1) .mat file.
Notes
------
A MAT file contains a struct array containing graphs, and a column vector lx containing a class label for each graph.
Check README in `downloadable file <http://mlcb.is.tuebingen.mpg.de/Mitarbeiter/Nino/WL/>`__ for detailed structure.
"""
from scipy.io import loadmat
import numpy as np
import networkx as nx
data = []
content = loadmat(filename)
order = extra_params['am_sp_al_nl_el']
# print(content)
# print('----')
for key, value in content.items():
if key[0] == 'l': # class label
y = np.transpose(value)[0].tolist()
# print(y)
elif key[0] != '_':
# print(value[0][0][0])
# print()
# print(value[0][0][1])
# print()
# print(value[0][0][2])
# print()
# if len(value[0][0]) > 3:
# print(value[0][0][3])
# print('----')
# if adjacency matrix is not compressed / edge label exists
if order[1] == 0:
for i, item in enumerate(value[0]):
# print(item)
# print('------')
g = nx.Graph(name=i) # set name of the graph
nl = np.transpose(item[order[3]][0][0][0]) # node label
# print(item[order[3]])
# print()
for index, label in enumerate(nl[0]):
g.add_node(index, atom=str(label))
el = item[order[4]][0][0][0] # edge label
for edge in el:
g.add_edge(
edge[0] - 1, edge[1] - 1, bond_type=str(edge[2]))
data.append(g)
else:
from scipy.sparse import csc_matrix
for i, item in enumerate(value[0]):
# print(item)
# print('------')
g = nx.Graph(name=i) # set name of the graph
nl = np.transpose(item[order[3]][0][0][0]) # node label
# print(nl)
# print()
for index, label in enumerate(nl[0]):
g.add_node(index, atom=str(label))
sam = item[order[0]] # sparse adjacency matrix
index_no0 = sam.nonzero()
for col, row in zip(index_no0[0], index_no0[1]):
# print(col)
# print(row)
g.add_edge(col, row)
data.append(g)
# print(g.edges(data=True))
return data, y
[docs]def loadTXT(filename):
"""Load graph data from a .txt file.
Notes
------
The graph data is loaded from separate files.
Check README in `downloadable file <http://tiny.cc/PK_MLJ_data>`__, 2018 for detailed structure.
"""
# import numpy as np
import networkx as nx
from os import listdir
from os.path import dirname, basename
def get_label_names(frm):
"""Get label names from DS_label_readme.txt file.
"""
def get_names_from_line(line):
"""Get names of labels/attributes from a line.
"""
str_names = line.split('[')[1].split(']')[0]
names = str_names.split(',')
names = [attr.strip() for attr in names]
return names
label_names = {'node_labels': [], 'node_attrs': [],
'edge_labels': [], 'edge_attrs': []}
content_rm = open(frm).read().splitlines()
for line in content_rm:
line = line.strip()
if line.startswith('Node labels:'):
label_names['node_labels'] = get_names_from_line(line)
elif line.startswith('Node attributes:'):
label_names['node_attrs'] = get_names_from_line(line)
elif line.startswith('Edge labels:'):
label_names['edge_labels'] = get_names_from_line(line)
elif line.startswith('Edge attributes:'):
label_names['edge_attrs'] = get_names_from_line(line)
return label_names
# get dataset name.
dirname_dataset = dirname(filename)
filename = basename(filename)
fn_split = filename.split('_A')
ds_name = fn_split[0].strip()
# load data file names
for name in listdir(dirname_dataset):
if ds_name + '_A' in name:
fam = dirname_dataset + '/' + name
elif ds_name + '_graph_indicator' in name:
fgi = dirname_dataset + '/' + name
elif ds_name + '_graph_labels' in name:
fgl = dirname_dataset + '/' + name
elif ds_name + '_node_labels' in name:
fnl = dirname_dataset + '/' + name
elif ds_name + '_edge_labels' in name:
fel = dirname_dataset + '/' + name
elif ds_name + '_edge_attributes' in name:
fea = dirname_dataset + '/' + name
elif ds_name + '_node_attributes' in name:
fna = dirname_dataset + '/' + name
elif ds_name + '_graph_attributes' in name:
fga = dirname_dataset + '/' + name
elif ds_name + '_label_readme' in name:
frm = dirname_dataset + '/' + name
# this is supposed to be the node attrs, make sure to put this as the last 'elif'
elif ds_name + '_attributes' in name:
fna = dirname_dataset + '/' + name
# get labels and attributes names.
if 'frm' in locals():
label_names = get_label_names(frm)
else:
label_names = {'node_labels': [], 'node_attrs': [],
'edge_labels': [], 'edge_attrs': []}
content_gi = open(fgi).read().splitlines() # graph indicator
content_am = open(fam).read().splitlines() # adjacency matrix
content_gl = open(fgl).read().splitlines() # graph labels
# create graphs and add nodes
data = [nx.Graph(name=str(i),
node_labels=label_names['node_labels'],
node_attrs=label_names['node_attrs'],
edge_labels=label_names['edge_labels'],
edge_attrs=label_names['edge_attrs']) for i in range(0, len(content_gl))]
if 'fnl' in locals():
content_nl = open(fnl).read().splitlines() # node labels
for idx, line in enumerate(content_gi):
# transfer to int first in case of unexpected blanks
data[int(line) - 1].add_node(idx)
labels = [l.strip() for l in content_nl[idx].split(',')]
data[int(line) - 1].nodes[idx]['atom'] = str(int(labels[0])) # @todo: this should be removed after.
if data[int(line) - 1].graph['node_labels'] == []:
for i, label in enumerate(labels):
l_name = 'label_' + str(i)
data[int(line) - 1].nodes[idx][l_name] = label
data[int(line) - 1].graph['node_labels'].append(l_name)
else:
for i, l_name in enumerate(data[int(line) - 1].graph['node_labels']):
data[int(line) - 1].nodes[idx][l_name] = labels[i]
else:
for i, line in enumerate(content_gi):
data[int(line) - 1].add_node(i)
# add edges
for line in content_am:
tmp = line.split(',')
n1 = int(tmp[0]) - 1
n2 = int(tmp[1]) - 1
# ignore edge weight here.
g = int(content_gi[n1]) - 1
data[g].add_edge(n1, n2)
# add edge labels
if 'fel' in locals():
content_el = open(fel).read().splitlines()
for idx, line in enumerate(content_el):
labels = [l.strip() for l in line.split(',')]
n = [int(i) - 1 for i in content_am[idx].split(',')]
g = int(content_gi[n[0]]) - 1
data[g].edges[n[0], n[1]]['bond_type'] = labels[0] # @todo: this should be removed after.
if data[g].graph['edge_labels'] == []:
for i, label in enumerate(labels):
l_name = 'label_' + str(i)
data[g].edges[n[0], n[1]][l_name] = label
data[g].graph['edge_labels'].append(l_name)
else:
for i, l_name in enumerate(data[g].graph['edge_labels']):
data[g].edges[n[0], n[1]][l_name] = labels[i]
# add node attributes
if 'fna' in locals():
content_na = open(fna).read().splitlines()
for idx, line in enumerate(content_na):
attrs = [a.strip() for a in line.split(',')]
g = int(content_gi[idx]) - 1
data[g].nodes[idx]['attributes'] = attrs # @todo: this should be removed after.
if data[g].graph['node_attrs'] == []:
for i, attr in enumerate(attrs):
a_name = 'attr_' + str(i)
data[g].nodes[idx][a_name] = attr
data[g].graph['node_attrs'].append(a_name)
else:
for i, a_name in enumerate(data[g].graph['node_attrs']):
data[g].nodes[idx][a_name] = attrs[i]
# add edge attributes
if 'fea' in locals():
content_ea = open(fea).read().splitlines()
for idx, line in enumerate(content_ea):
attrs = [a.strip() for a in line.split(',')]
n = [int(i) - 1 for i in content_am[idx].split(',')]
g = int(content_gi[n[0]]) - 1
data[g].edges[n[0], n[1]]['attributes'] = attrs # @todo: this should be removed after.
if data[g].graph['edge_attrs'] == []:
for i, attr in enumerate(attrs):
a_name = 'attr_' + str(i)
data[g].edges[n[0], n[1]][a_name] = attr
data[g].graph['edge_attrs'].append(a_name)
else:
for i, a_name in enumerate(data[g].graph['edge_attrs']):
data[g].edges[n[0], n[1]][a_name] = attrs[i]
# load y
y = [int(i) for i in content_gl]
return data, y
[docs]def loadDataset(filename, filename_y=None, extra_params=None):
"""Read graph data from filename and load them as NetworkX graphs.
Parameters
----------
filename : string
The name of the file from where the dataset is read.
filename_y : string
The name of file of the targets corresponding to graphs.
extra_params : dict
Extra parameters only designated to '.mat' format.
Return
------
data : List of NetworkX graph.
y : List
Targets corresponding to graphs.
Notes
-----
This function supports following graph dataset formats:
'ds': load data from .ds file. See comments of function loadFromDS for a example.
'cxl': load data from Graph eXchange Language file (.cxl file). See
`here <http://www.gupro.de/GXL/Introduction/background.html>`__ for detail.
'sdf': load data from structured data file (.sdf file). See
`here <http://www.nonlinear.com/progenesis/sdf-studio/v0.9/faq/sdf-file-format-guidance.aspx>`__
for details.
'mat': Load graph data from a MATLAB (up to version 7.1) .mat file. See
README in `downloadable file <http://mlcb.is.tuebingen.mpg.de/Mitarbeiter/Nino/WL/>`__
for details.
'txt': Load graph data from a special .txt file. See
`here <https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets>`__
for details. Note here filename is the name of either .txt file in
the dataset directory.
"""
extension = splitext(filename)[1][1:]
if extension == "ds":
data, y = loadFromDS(filename, filename_y)
elif extension == "cxl":
import xml.etree.ElementTree as ET
dirname_dataset = dirname(filename)
tree = ET.parse(filename)
root = tree.getroot()
data = []
y = []
for graph in root.iter('graph'):
mol_filename = graph.attrib['file']
mol_class = graph.attrib['class']
data.append(loadGXL(dirname_dataset + '/' + mol_filename))
y.append(mol_class)
elif extension == 'xml':
data, y = loadFromXML(filename, extra_params)
elif extension == "sdf":
# import numpy as np
from tqdm import tqdm
import sys
data = loadSDF(filename)
y_raw = open(filename_y).read().splitlines()
y_raw.pop(0)
tmp0 = []
tmp1 = []
for i in range(0, len(y_raw)):
tmp = y_raw[i].split(',')
tmp0.append(tmp[0])
tmp1.append(tmp[1].strip())
y = []
for i in tqdm(range(0, len(data)), desc='ajust data', file=sys.stdout):
try:
y.append(tmp1[tmp0.index(data[i].name)].strip())
except ValueError: # if data[i].name not in tmp0
data[i] = []
data = list(filter(lambda a: a != [], data))
elif extension == "mat":
data, y = loadMAT(filename, extra_params)
elif extension == 'txt':
data, y = loadTXT(filename)
# print(len(y))
# print(y)
# print(data[0].nodes(data=True))
# print('----')
# print(data[0].edges(data=True))
# for g in data:
# print(g.nodes(data=True))
# print('----')
# print(g.edges(data=True))
return data, y
[docs]def loadFromXML(filename, extra_params):
import xml.etree.ElementTree as ET
if extra_params:
dirname_dataset = extra_params
else:
dirname_dataset = dirname(filename)
tree = ET.parse(filename)
root = tree.getroot()
data = []
y = []
for graph in root.iter('graph'):
mol_filename = graph.attrib['file']
mol_class = graph.attrib['class']
data.append(loadGXL(dirname_dataset + '/' + mol_filename))
y.append(mol_class)
return data, y
[docs]def loadFromDS(filename, filename_y):
"""Load data from .ds file.
Possible graph formats include:
'.ct': see function loadCT for detail.
'.gxl': see dunction loadGXL for detail.
Note these graph formats are checked automatically by the extensions of
graph files.
"""
dirname_dataset = dirname(filename)
data = []
y = []
content = open(filename).read().splitlines()
extension = splitext(content[0].split(' ')[0])[1][1:]
if filename_y is None or filename_y == '':
if extension == 'ct':
for i in range(0, len(content)):
tmp = content[i].split(' ')
# remove the '#'s in file names
data.append(
loadCT(dirname_dataset + '/' + tmp[0].replace('#', '', 1)))
y.append(float(tmp[1]))
elif extension == 'gxl':
for i in range(0, len(content)):
tmp = content[i].split(' ')
# remove the '#'s in file names
data.append(
loadGXL(dirname_dataset + '/' + tmp[0].replace('#', '', 1)))
y.append(float(tmp[1]))
else: # y in a seperate file
if extension == 'ct':
for i in range(0, len(content)):
tmp = content[i]
# remove the '#'s in file names
data.append(
loadCT(dirname_dataset + '/' + tmp.replace('#', '', 1)))
elif extension == 'gxl':
for i in range(0, len(content)):
tmp = content[i]
# remove the '#'s in file names
data.append(
loadGXL(dirname_dataset + '/' + tmp.replace('#', '', 1)))
content_y = open(filename_y).read().splitlines()
# assume entries in filename and filename_y have the same order.
for item in content_y:
tmp = item.split(' ')
# assume the 3rd entry in a line is y (for Alkane dataset)
y.append(float(tmp[2]))
return data, y
[docs]def saveDataset(Gn, y, gformat='gxl', group=None, filename='gfile', xparams=None):
"""Save list of graphs.
"""
import os
dirname_ds = os.path.dirname(filename)
if dirname_ds != '':
dirname_ds += '/'
os.makedirs(dirname_ds, exist_ok=True)
if xparams is not None and 'graph_dir' in xparams:
graph_dir = xparams['graph_dir'] + '/'
os.makedirs(graph_dir, exist_ok=True)
else:
graph_dir = dirname_ds
if group == 'xml' and gformat == 'gxl':
kwargs = {'method': xparams['method']} if xparams is not None else {}
with open(filename + '.xml', 'w') as fgroup:
fgroup.write("<?xml version=\"1.0\"?>")
fgroup.write("\n<!DOCTYPE GraphCollection SYSTEM \"http://www.inf.unibz.it/~blumenthal/dtd/GraphCollection.dtd\">")
fgroup.write("\n<GraphCollection>")
for idx, g in enumerate(Gn):
fname_tmp = "graph" + str(idx) + ".gxl"
saveGXL(g, graph_dir + fname_tmp, **kwargs)
fgroup.write("\n\t<graph file=\"" + fname_tmp + "\" class=\"" + str(y[idx]) + "\"/>")
fgroup.write("\n</GraphCollection>")
fgroup.close()
if __name__ == '__main__':
# ### Load dataset from .ds file.
# # .ct files.
# ds = {'name': 'Alkane', 'dataset': '../../datasets/Alkane/dataset.ds',
# 'dataset_y': '../../datasets/Alkane/dataset_boiling_point_names.txt'}
# Gn, y = loadDataset(ds['dataset'], filename_y=ds['dataset_y'])
## ds = {'name': 'Acyclic', 'dataset': '../../datasets/acyclic/dataset_bps.ds'} # node symb
## Gn, y = loadDataset(ds['dataset'])
## ds = {'name': 'MAO', 'dataset': '../../datasets/MAO/dataset.ds'} # node/edge symb
## Gn, y = loadDataset(ds['dataset'])
## ds = {'name': 'PAH', 'dataset': '../../datasets/PAH/dataset.ds'} # unlabeled
## Gn, y = loadDataset(ds['dataset'])
# print(Gn[1].nodes(data=True))
# print(Gn[1].edges(data=True))
# print(y[1])
# # .gxl file.
# ds = {'name': 'monoterpenoides',
# 'dataset': '../../datasets/monoterpenoides/dataset_10+.ds'} # node/edge symb
# Gn, y = loadDataset(ds['dataset'])
# print(Gn[1].nodes(data=True))
# print(Gn[1].edges(data=True))
# print(y[1])
# ### Convert graph from one format to another.
# # .gxl file.
# import networkx as nx
# ds = {'name': 'monoterpenoides',
# 'dataset': '../../datasets/monoterpenoides/dataset_10+.ds'} # node/edge symb
# Gn, y = loadDataset(ds['dataset'])
# y = [int(i) for i in y]
# print(Gn[1].nodes(data=True))
# print(Gn[1].edges(data=True))
# print(y[1])
# # Convert a graph to the proper NetworkX format that can be recognized by library gedlib.
# Gn_new = []
# for G in Gn:
# G_new = nx.Graph()
# for nd, attrs in G.nodes(data=True):
# G_new.add_node(str(nd), chem=attrs['atom'])
# for nd1, nd2, attrs in G.edges(data=True):
# G_new.add_edge(str(nd1), str(nd2), valence=attrs['bond_type'])
## G_new.add_edge(str(nd1), str(nd2))
# Gn_new.append(G_new)
# print(Gn_new[1].nodes(data=True))
# print(Gn_new[1].edges(data=True))
# print(Gn_new[1])
# filename = '/media/ljia/DATA/research-repo/codes/others/gedlib/tests_linlin/generated_datsets/monoterpenoides/gxl/monoterpenoides'
# xparams = {'method': 'gedlib'}
# saveDataset(Gn, y, gformat='gxl', group='xml', filename=filename, xparams=xparams)
# save dataset.
# ds = {'name': 'MUTAG', 'dataset': '../../datasets/MUTAG/MUTAG.mat',
# 'extra_params': {'am_sp_al_nl_el': [0, 0, 3, 1, 2]}} # node/edge symb
# Gn, y = loadDataset(ds['dataset'], extra_params=ds['extra_params'])
# saveDataset(Gn, y, group='xml', filename='temp/temp')
# test - new way to add labels and attributes.
# dataset = '../../datasets/SYNTHETICnew/SYNTHETICnew_A.txt'
# dataset = '../../datasets/Fingerprint/Fingerprint_A.txt'
# dataset = '../../datasets/Letter-med/Letter-med_A.txt'
# dataset = '../../datasets/AIDS/AIDS_A.txt'
# dataset = '../../datasets/ENZYMES_txt/ENZYMES_A_sparse.txt'
# Gn, y_all = loadDataset(dataset)
pass