Addition of coauthorship dataset #180
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toponetx/datasets/graph.py
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| cochains = np.load(DIR / "150250_cochains.npy", allow_pickle=True) | ||
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| simplices = [] | ||
| for dim in list(range(len(cochains)))[::-1]: |
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No need to explicitly construct a list, use the step parameter of range:
| for dim in list(range(len(cochains)))[::-1]: | |
| for dim in range(len(cochains) - 1, -1, -1): |
toponetx/datasets/graph.py
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| li = list(cochains[dim].keys()) | ||
| simplices += [list(l) for l in li] |
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No need to explicitly construct the list here, you are only iterating over its values, which you can do with the iterator you have in the first place:
| li = list(cochains[dim].keys()) | |
| simplices += [list(l) for l in li] | |
| simplices += [list(l) for l in cochains[dim].keys()] |
toponetx/datasets/graph.py
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| sc = SimplicialComplex(simplices) | ||
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| for i in range(len(cochains)): | ||
| dic = {tuple(sorted(list(k))): v for k, v in cochains[i].items()} |
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Again, explicit list construction is not necessary, sorted happily works on an iterable:
| dic = {tuple(sorted(list(k))): v for k, v in cochains[i].items()} | |
| dic = {tuple(sorted(k)): v for k, v in cochains[i].items()} |
Codecov Report
@@ Coverage Diff @@
## main #180 +/- ##
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+ Coverage 77.18% 77.29% +0.11%
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Files 22 22
Lines 2402 2414 +12
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+ Hits 1854 1866 +12
Misses 548 548
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| References | ||
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| [SNN20] Stefania Ebli, Michael Defferrard and Gard Spreemann. |
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I do no think the description of the dataset is clear enough.
- What is the dimension of the SC?
- What is the problem exactly ? Can you describe the training pairs in more details
- Can you provide a brief statistics about the dataset?
toponetx/datasets/graph.py
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| - the number of citations attributed to the given collaborations of k authors. | ||
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| """ | ||
| cochains = np.load(DIR / "150250_cochains.npy", allow_pickle=True) |
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Can you change the name of the file?
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Agreed, let's choose one name for this dataset and stick to it:
"coauthorship", then "coauthorship.npy" and the variable itself can be called coauthorship
| @@ -9,7 +10,9 @@ | |||
| from toponetx.algorithms.spectrum import hodge_laplacian_eigenvectors | |||
| from toponetx.transform.graph_to_simplicial_complex import graph_2_clique_complex | |||
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| __all__ = ["karate_club"] | |||
| __all__ = ["karate_club", "coauthorship"] | |||
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I am not sure the addition of this dataset to graph is justified, maybe it needs a different file all together. Can you justify your choice for graph? other people might not find it intuitive anyway,
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Yes, can you suggest a name for the file?
I'll be away for a week, I can fix the code based on the comments when I'm back.
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I have fixed the changes suggested above. However please advise about where to place it. The dataset originates from a citation graph which is why I placed it in graph.py first, but it is already pre-processed as a simplicial complex and therefore I agree graph.py may not be ideal place. But I'm not sure where it should be placed. |
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@USFCA-MSDS we need to merge this to allow the challenge's participant @Hellsegga to move forward with their submission. |
This is the dataset used in the Simplicial Neural Networks paper (https://arxiv.org/abs/2010.03633). I'd like to include it here to be able to use it in my implementation in TopoModelX (pyt-team/TopoModelX#98). It can hopefully be useful to test other methods as well.