jinhongjung/pyrwr

Python Implementation for Random Walk with Restart (RWR)

pyrwr's Issues

How to implement this algorithim to anomaly detection

Hi
Is there any guides regarding How to implement this algorithim to anomaly detection

Does the input file of the undirected graph need to have reverse edges？

Does the input file of the undirected graph need to have reverse edges?
like，
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Python implementation of BePI

Thank you for this great resource. Are there plans to integrate a python version of the "BePI" algorithm , which allows for fast and memory efficient RWR? RE: https://datalab.snu.ac.kr/bepi/resources/bepiSIGMOD2017.pdf

Thank you!

Test issue

The shape of the input matrix should be n by n

In your code or function : "row_normalize()" as well as other functions, the shape of the function's input matrix should be the same in rows and columns. If the number of rows doesn't match up with that of its columns, we will get error from the function "np.dot()".

If the assumption is that "the matrix.shape[0] == matrix.shape[1]", then why bother to set:
m, n = self.A.shape ? It's really redundant and misleading.

I think that the code can be simplified.

How to print out the random walk steps while doing pagerank ?

How to print out the random walk steps while doing pagerank ?

unweighted RWR

I have tried to RWR without weight. However, in "utils/reader.py",  "weighted" is directly defined as True and so   even if my edges are unweighted,    "A = csr_matrix((np.ones(len(K), (I, J), shape=A.shape)))"  gives error due to lack of weight. I solved the problem by giving  them all same weight as default 1. In fact, it may be solved directly "utils/reader.py". weights argumant may be added as weights default True.

reader.txt

Error found when trying to execute rwr.read_graph(input_graph, graph_type)

I was trying to execute train_WGCN.py from this repository this error appeared. I execute the code through Anaconda environment.

My setup:

Operating System: Windows 10
Conda version: 4.10.3
Python version: 3.6.13

Using backend: pytorch
Traceback (most recent call last):
  File "train_WGCN.py", line 79, in <module>
    structural_info = compute_structural_infot(args.dataset, args.directed, args.dijkstra_k, args.in_out_ratio,args.restart_rate,args.in_out_peak)
  File "D:\Git\WGCN_Graph-Convolutional-Networks-with-Weighted-Structural-Features\utils_structural.py", line 50, in compute_structural_infot
    rwr.read_graph(input_graph, graph_type)
  File "E:\anaconda3\envs\wgcn\lib\site-packages\pyrwr-1.0.0-py3.6.egg\pyrwr\pyrwr.py", line 25, in read_graph
    self.A, self.base = reader.read_graph(input_path, graph_type)
  File "E:\anaconda3\envs\wgcn\lib\site-packages\pyrwr-1.0.0-py3.6.egg\utils\reader.py", line 77, in read_graph
    X = np.loadtxt(path, dtype=float, comments='#')
  File "E:\anaconda3\envs\wgcn\lib\site-packages\numpy\lib\npyio.py", line 968, in loadtxt
    fh = np.lib._datasource.open(fname, 'rt', encoding=encoding)
  File "E:\anaconda3\envs\wgcn\lib\site-packages\numpy\lib\_datasource.py", line 269, in open
    return ds.open(path, mode, encoding=encoding, newline=newline)
  File "E:\anaconda3\envs\wgcn\lib\site-packages\numpy\lib\_datasource.py", line 623, in open
    raise IOError("%s not found." % path)
OSError: data\cora_ml\out1_graph_edges_rwr.txt not found.

The error shows that rwr.read_graph(input_graph, graph_type) function is not successfully executed.

What might be the problem? Thanks in advance

the dimension of r doesn't match the number of nodes in PPI

I changed the network in the example to my network. I split it with Tab separator and saved it as txt file, which contains 17662 nodes, but the output r length is 101243544.Below is my code and txt file, could you please tell me where the problem is. Thank you so much!

Update requirements.txt

Hi,

I see that you hardcoded the package versions for requirements.txt. Have you tested on newer versions? I cannot downgrade to the package versions you suggest in my environment. It would be good to have compatibility with the latest versions of numpy and scipy.

Inclusion of SimRank, SimRank, VertexSim, RoleSim, PageSim

As noted in abhishekmaha23/RoleSim-Python#2 there are other Link predictions out there, and this repo seemed to have some of the best algorithms. Is it possible to include them in this repo?