graphkit-learn/py-graph/utils/graphfiles.py

import networkx as nx
   
def loadCT(filename):
    """load data from .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, the last parameter in which is the label of the node, representing a chemical element @Q what are the first 3 numbers?
        0.0000    0.0000    0.0000 C
        0.0000    0.0000    0.0000 O
      1  3  1  1 <- each line describes an edge, the first two numbers represent two nodes of the edge, the last number represents the label. @Q what are the 3th numbers?
      2  3  1  1
    """
    content = open(filename).read().splitlines()
    G = nx.Graph(name=str(content[0])) # 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])

    for i in range(0, nb_nodes):
        tmp = content[i + 2].split(" ")
        tmp = [x for x in tmp if x != '']
        G.add_node(i, label=tmp[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, label=int(tmp[3]))
    return G


def loadGXL(filename):
    import networkx as nx
    import xml.etree.ElementTree as ET

    tree = ET.parse(filename)
    root = tree.getroot()
    index = 0
    G = nx.Graph()
    dic={}
    for node in root.iter('node'):
        label = node.find('attr')[0].text
        dic[node.attrib['id']] = index
        G.add_node(index, id=node.attrib['id'], label=label)
        index += 1
        
    for edge in root.iter('edge'):
        label = edge.find('attr')[0].text
        G.add_edge(dic[edge.attrib['from']], dic[edge.attrib['to']], label=label)
    return G
 
def loadDataset(filename):
    """load file list of the dataset.
    """
    from os.path import dirname, splitext

    dirname_dataset = dirname(filename)
    extension = splitext(filename)[1][1:]
    data = []
    y = []
    if(extension == "ds"):
        content = open(filename).read().splitlines()
        for i in range(0, len(content)):
            tmp = content[i].split(' ')
            data.append(loadCT(dirname_dataset + '/' + tmp[0].replace('#', '', 1))) # remove the '#'s in file names
            y.append(float(tmp[1]))
    elif(extension == "cxl"):
        import xml.etree.ElementTree as ET

        tree = ET.parse(filename)
        root = tree.getroot()
        data = []
        y = []
        for graph in root.iter('print'):
            mol_filename = graph.attrib['file']
            mol_class = graph.attrib['class']
            data.append(loadGXL(dirname_dataset + '/' + mol_filename))
            y.append(mol_class)

    return data, y