Louvain | A fast algorithm to find communities in large network | Machine Learning library
kandi X-RAY | Louvain Summary
kandi X-RAY | Louvain Summary
A fast algorithm to find communities in large network. Blondel V D, Guillaume J L, Lambiotte R, et al. Fast unfolding of communities in large networks[J]. Journal of Statistical Mechanics, 2008, 2008(10):155-168.
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Top functions reviewed by kandi - BETA
- The main entry point
- Rebuild the graph
- Initializes the graph
- Can be slow
- Try to move i
- Writes the output circle
- Writes the output cluster
- Add an edge
- Adds a global edge
- Adds a new edge
- Initialize the cluster
- Writes the output as JSON
- Get clone
Louvain Key Features
Louvain Examples and Code Snippets
Community Discussions
Trending Discussions on Louvain
QUESTION
Recently, I am reading the code of cuGraph. I notice that it is mentioned that Louvain and Katz algorithms support multi-GPU. However, when I read the C++ code of Louvain, I cannot find code that is related to multi-GPU. Specifically, according to a prior post, multi-GPU can be implemented by calling cudaSetDevice. I cannot find this function in the code of Louvain, however. Am I missing anything?
ANSWER
Answered 2021-May-28 at 00:11cuGraph supports multi-GPU by leveraging Dask. I encourage you to read the Dask cuGraph documentation that shows an example using PageRank.
For a Louvain example, I recommend looking at the docstring of the cugraph.dask.louvain function.
For completeness, under the hood cuGraph is using RAFT to manage underlying NCCL and UCX communication.
QUESTION
I have a problem with updating packages in conda. The list of my installed packages is:
...ANSWER
Answered 2021-Apr-14 at 20:26Channel pypi means that the package was installed with pip. You may need to upgrade it with pip as well
QUESTION
I have created a minimum spanning tree in which communities have been found using the Louvain method. I would now like to display the tree clearly, i.e., it would be great to have an overlap-free representation.
On the left is my current plot and on the right is a very nice example from Wang et al. (2017, JEIC), which is much clearer and mostly non-overlapping.
I wonder how it can be achieved to represent this tree more clearly, in particular it must be noted that this representation is only an MWE and the actual representation has much more observations.
MWE:
...ANSWER
Answered 2021-Apr-02 at 13:07First of all, your vertices are much larger than in the "nice" graph. I will use a smaller node size. But the main point is that you should specify the layout. A couple of options worth trying are layout_as_tree and layout_with_gem. Here is what I got.
QUESTION
I have created a simple minimum spanning tree and now have a data frame with columns 'from', 'to' and 'distance'.
Based on this, I found communities using the Louvain method, which I plotted. As far as I understand it, for clustering and plotting I need only the columns from and to, and the distance is not used.
How can I keep the communities I found, ideally each in a different color, but remove the box around the communities?
...ANSWER
Answered 2021-Mar-31 at 13:43The blobs around the groups can be turned off like this:
QUESTION
I'm reading tables from a website where one of the columns is university name and some of the names have special characters which are the following (but the names are written like I put them here, so is not a task I can fix by reading the web in a different way):
...ANSWER
Answered 2021-Mar-30 at 12:26As Deceze has commented, if the data is corrupted at source there is no guarantee that you can undo the corruption. However, using the data you provided we can make some progress.
Firstly, the vast majority of the strings in your list can be fixed by encoding as latin-1 and then decoding as UTF-8.
QUESTION
I am trying to implement Louvain clustering algorithm and use the following code:
...ANSWER
Answered 2020-Dec-20 at 20:09You can use nx.draw_networkx_labels. In your case:
QUESTION
I found a previous stackoverflow post that deals with a similar question that I have, but the answer there is not quite the same : Check which community a node belongs in louvain community detection
I created some data in R and then made a graph. After making the graph, I performed clustering on the graph. Now, suppose I have a list of people, I want to find out which cluster they belong to.
I understand that it is easy to manually inspect the data and find this out, however I think this would be very difficult to do if you had a big data set.
I have written the code below. Everything works until the last 2 lines where I try to find out which clusters do "John", "Peter" and "Tim" belong to:
...ANSWER
Answered 2020-Nov-26 at 00:16The membership of the vertices are held in $membership and the names of the vertices are in $names:
QUESTION
I want to subset anndata on basis of clusters, but i am not able to understand how to do it.
I am running scVelo pipeline, and in that i ran tl.louvain function to cluster cells on basis of louvain. I got around 32 clusters, of which cluster 2 and 4 is of my interest, and i have to run the pipeline further on these clusters only. (Initially i had the loom file which i read in scVelo, so i have now the anndata.)
I tried using adata.obs["louvain"] which gave me the cluster information, but i need to write a new anndata with only 2 clusters and process further.
Please help on how to subset anndata. Any help is highly appreciated. (Being very new to it, i am finding it difficult to get)
...ANSWER
Answered 2020-Oct-13 at 08:37If your adata.obs has a "louvain" column that I'd expect after running tl.louvain, you could do the subsetting as
adata[adata.obs["louvain"] == "2"]
if you want to obtain one cluster and
adata[adata.obs['louvain'].isin(['2', '4'])]
for obtaining cluster 2 & 4.
QUESTION
hello there is a json data as below.
...ANSWER
Answered 2020-Sep-07 at 12:22What you can do is to use the delete operator when parentID is equal to 0. This will delete the property from the object, hence not displaying it.
QUESTION
I try to use the Louvain Algorithm with a cypher projection:
...ANSWER
Answered 2020-Sep-01 at 11:57The Graph algorithms library is being deprecated. Please, try to use the new Graph Data Science library, which is the successor of the Graph Algorithms.
Using the GDS library, the syntax would look like:
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Install Louvain
You can use Louvain like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Louvain component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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