teneto
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Temporal Network Tools
Collecting issues relating to this issue. To be fixed for Version 0.6.
IIUC, this should be 4 time points, instead of 3. https://github.com/wiheto/teneto/blob/e7bfc4766738b1ef729528db3b7273492b4a7f60/test/communitydetection/test_communitydetection.py#L12-L13 `G` has the shape (6,6,4)
Hello! I get a problems when I run the following: ![屏幕截图 2021-09-02 114944](https://user-images.githubusercontent.com/62167117/131808466-edf98228-6d16-4282-ba33-caa6cb8476a0.png) In theory, I import a weighted network by the dataframe data. However, I get an unweighted network...
Running ```python import teneto as tnt import pandas as pd netin = {'i': [0,0,1,1], 'j': [1,2,2,2], 't': [100,101,102,103]} df = pd.DataFrame(data=netin) tnet = tnt.TemporalNetwork(from_df=df) print(tnet.T) ``` displays 104, even when...
Hi, I am getting the below error when running the following: !pip install teneto (on Google Cloud Platform JupyterLab in a Python 3 environment) from teneto import TemporalNetwork tnet =...
Considering preprocessing options like: [this](https://www.sciencedirect.com/science/article/pii/S1053811919303283?casa_token=j0kSj2EO3RwAAAAA:VIO_fZ0iVlXlj2S4D3NJmm_elH8kGdFtf8h-BzQf7Zlib7yDTcx1ZLOFK_FtdltftA4BjLwADA), prewhitening pror to deriving network connectivity for some methods may have advantages.
**Is your feature request related to a problem? Please describe.** Would it be possible to control the color of the temporal graph nodes when using tnet.plot()? For example give an...
If I try to load a relatively small network (~86980 edges) composed of three snapshots I get the following error: `MemoryError: Unable to allocate array with shape (110011, 110011, 3)...
**Is your feature request related to a problem? Please describe.** No, but it would make this tool easier for broad scale usage **Describe the solution you'd like** Currently, there are...
Copy pasting the first few lines of the tutorial https://teneto.readthedocs.io/en/latest/tutorial/networkrepresentation.html#temporalnetwork-object yields an error at `tnet.network.head()` because tnet created with `tnet.generatenetwork('rand_binomial',size=(5,3), prob=0.5)` is a Numpy `ndarray` and not a Pandas `DataFrame`....