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September 29, 2023 03:30
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I made a networkx network and a DGL network. They match :) I am pleased.
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| # The DGL network has sentence encoded JSON for node features. | |
| In [26]: g | |
| Out[26]: | |
| [Graph(num_nodes=27770, num_edges=352807, | |
| ndata_schemes={'x': Scheme(shape=(384,), dtype=torch.float64)} | |
| edata_schemes={})] | |
| # The networkx network parsed the records and has inidividual fields for analysis | |
| In [27]: G | |
| Out[27]: <networkx.classes.digraph.DiGraph at 0x14fe5c4c0> | |
| # Do the two networks match? | |
| In [28]: G.number_of_nodes(), G.number_of_edges() | |
| Out[28]: (27770, 352807) | |
| # For our next trick, the DGLGraph gets labels... |
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| { | |
| "Authors": "Paul S. Aspinwall", | |
| "Comments": "82 pages, 8 figures, LaTeX2e, TASI99, refs added and some typos fixed", | |
| "Date": "Sat, 1 Jan 2000 00:02:31 GMT", | |
| "From": "Paul S. Aspinwall", | |
| "Paper": "hep-th/0001001", | |
| "Published": 946684800, | |
| "Report-no": "DUKE-CGTP-00-01", | |
| "Title": "Compactification, Geometry and Duality: N=2", | |
| "file_id": 1001, | |
| "sequential_id": 0 | |
| } |
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