Maxime Lucas
Maxime Lucas
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...
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`....
We could add that with the group size as argument. This would go in `xgi/classes/function.py`?
Running ```python HH = xgi.Hypergraph([{1, 2, 3}, {4}, {5, 6}, {6, 7, 8}]) xgi.degree_counts(HH) ``` outputs `[0, 7, 1]`. It is even our test: https://github.com/ComplexGroupInteractions/xgi/blob/c262f406cf13e3d51e7b40e5534fbfcca223caff/tests/classes/test_function.py#L58). But node 4 does not...
Right now `xgi.unique_edge_sizes(H)` returns the existing the unique edge sizes in the hypergraph, but does not count them. It would be nice to have an easy way to compute a...
Because `cleanup()` uses HyperGraph specific methods and functions: `XGIError: Cannot remove_edges_from to SimplicialComplex, use remove_simplices_from instead`
Right now they are here https://xgi.readthedocs.io/en/latest/api/stats/xgi.stats.edgestats.html in a non-compact way. It would be nice to have them there as a list, and in the docs of methods like `filterby()`.
As a result, `H.degree(order=2)` works, but the argument `order` is not in the docs.
For example, `edge_lc` should be changed to `dyad_lw`.
Add an easy way to plot grid, triangular, and other regular lattices with a natural layout.