Python networkx.parse_adjlist() Examples

The following are 2 code examples of networkx.parse_adjlist(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module networkx , or try the search function .
Example #1
Source File: graph_reader.py    From nmp_qc with MIT License 5 votes vote down vote up 
def create_graph_enzymes(file):
    
    f = open(file, 'r')
    lines = f.read().splitlines()
    f.close()
    
    # get the indices of the vertext, adj list and class
    idx_vertex = lines.index("#v - vertex labels")
    idx_adj_list = lines.index("#a - adjacency list")
    idx_clss = lines.index("#c - Class")
    
    # node label    
    vl = [int(ivl) for ivl in lines[idx_vertex+1:idx_adj_list]]
    
    adj_list = lines[idx_adj_list+1:idx_clss]
    sources = list(range(1,len(adj_list)+1))

    for i in range(len(adj_list)):
        if not adj_list[i]:
            adj_list[i] = str(sources[i])
        else:
            adj_list[i] = str(sources[i])+","+adj_list[i]

    g = nx.parse_adjlist(adj_list, nodetype=int, delimiter=",")
    
    for i in range(1, g.number_of_nodes()+1):
        g.node[i]['labels'] = np.array(vl[i-1])
    
    c = int(lines[idx_clss+1])
    
    return g, c
Example #2
Source File: utils.py    From Recycler with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def get_fastg_digraph(fastg_name):
    """ scans through fastg headers as an adjacency list
        builds and returns a nx directed graph using adjacencies
        note: no connections are created between each node and its 
        rc node - we need to take care to maintain these 
    """
    lines = []
    fp = open(fastg_name, 'r')
    for name,seq,qual in readfq(fp):
        name = re.sub('[:,]'," ", name[:-1])
        lines.append(name)
    G = nx.DiGraph()
    return nx.parse_adjlist(lines, create_using=G)