Team Ai
Datasetpublic

OpenScientificCodeRegistry/Database

Open Scientific Code Registry (OSCR): the authors' scripts The code published by the authors of open-access neuroscience papers, as found and verified by Open Scientific Code Registry (OSCR). Each file is here exactly as it is at the source, at the verified commit, under the license of its repository. 421,275 unique files (3,782 MB of text) from 8,849 repositories, in 24 Parquet block(s). Only files whose repository's license allows redistribution, confirmed by the repository's… See the full description on the dataset page: https://huggingface.co/datasets/OpenScientificCodeRegistry/Database.

sourceHugging Faceotherupdated 2d agoView on Hugging Face
0likes5.6kdownloads
github.com__ugolomoio__dibima-eegsr.json264 linesDownload Raw Back to 82
1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/ugolomoio/dibima-eegsr",4 "url": "https://github.com/UgoLomoio/DiBiMa-EEGSR.git",5 "host": "github.com",6 "commit": "8a666bdf5d8af48d8cf7b657f2e7afa2d03f9093",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11  {12   "path": "LICENSE",13   "sha256": "81b6d724a881b7c1798ddb4928a2800df69ab971a4664db93518108902b04b5e",14   "language": "License",15   "lines": 21,16   "truncated": false,17   "block": 6,18   "row": 146719  },20  {21   "path": "README.md",22   "sha256": "2a74c5e0d959d9e22d0bfa4ac17c599cb08120b21c2ceca366a375c78cc932e9",23   "language": "Text",24   "lines": 97,25   "truncated": false,26   "block": 8,27   "row": 995228  },29  {30   "path": "ablations.py",31   "sha256": "2d7635cd2587a85a3a24beff5e3003a0b35b943065321850f740139643f8d6b2",32   "language": "Python",33   "lines": 739,34   "truncated": false,35   "block": 7,36   "row": 1144637  },38  {39   "path": "ablations_diff_mamba.py",40   "sha256": "15800ca4ee4969a91fc6b62070a79a5df858f5a3fbb5fb44e344e8826d1edf79",41   "language": "Python",42   "lines": 329,43   "truncated": false,44   "block": 7,45   "row": 681546  },47  {48   "path": "ablations_mambadim.py",49   "sha256": "5d8c1951a496608245715f3247ae99fc2a9dbecc8dab7fcc6b2474e9ab31975d",50   "language": "Python",51   "lines": 524,52   "truncated": false,53   "block": 7,54   "row": 969155  },56  {57   "path": "analyze_topo.py",58   "sha256": "20dd004281f9dc42d6904990ea0e0939dc6aa9064233aaa0e24240980a342a4d",59   "language": "Python",60   "lines": 354,61   "truncated": false,62   "block": 7,63   "row": 804964  },65  {66   "path": "app.py",67   "sha256": "0b38b1add4621174db9bb29c8123d5038e5ced0a0b6702aa1e87f3f419bc6603",68   "language": "Python",69   "lines": 185,70   "truncated": false,71   "block": 6,72   "row": 4512473  },74  {75   "path": "compare_maser_topomap.py",76   "sha256": "d3130a36600790894b5b36801825ed9c7085d5d4f92d3f85549704e9c8fb1bcd",77   "language": "Python",78   "lines": 395,79   "truncated": false,80   "block": 7,81   "row": 596882  },83  {84   "path": "compare_to_maser.py",85   "sha256": "d1f48093d7d4609567fe96a7ebabeebe66a8f50a828c86e2c5eb34632e5bda95",86   "language": "Python",87   "lines": 315,88   "truncated": false,89   "block": 7,90   "row": 556791  },92  {93   "path": "diffusion_conditioning_ablations.py",94   "sha256": "0c5445da377d2d91b91c9ccc94638369a103a58dbd235b93247089755dd7e29c",95   "language": "Python",96   "lines": 646,97   "truncated": false,98   "block": 7,99   "row": 10785100  },101  {102   "path": "downstream_task/explain.py",103   "sha256": "a0f3aaa93a1b2dae9518cfb28b704267274262313fa859addb803f81397c6b72",104   "language": "Python",105   "lines": 291,106   "truncated": false,107   "block": 7,108   "row": 5135109  },110  {111   "path": "downstream_task/metrics.py",112   "sha256": "0837d3dd640be81ee3dd5e48f6b0d9df04ee72d2de276b733dc04e0d1ee2a39e",113   "language": "Python",114   "lines": 144,115   "truncated": false,116   "block": 6,117   "row": 39967118  },119  {120   "path": "downstream_task/metrics_class.py",121   "sha256": "729b4ab910b73758a6ab16fa61d4f55a13f46f37d3f7fc7ab2621d6d4d7dbe16",122   "language": "Python",123   "lines": 141,124   "truncated": false,125   "block": 6,126   "row": 42468127  },128  {129   "path": "downstream_task/resnet50.py",130   "sha256": "ea315da6f633f8e0badc3bbedabe03544eb1de5c788d79f7e2131883f4b6b145",131   "language": "Python",132   "lines": 166,133   "truncated": false,134   "block": 6,135   "row": 43306136  },137  {138   "path": "downstream_task/test.py",139   "sha256": "fe117ddd8b812caef57c7f6461c30198b1b7130f62e9a776e4a48a992ef7f68f",140   "language": "Python",141   "lines": 237,142   "truncated": false,143   "block": 7,144   "row": 3850145  },146  {147   "path": "downstream_task/train.py",148   "sha256": "4e0e9ac8349884abe3ae31fd1e7dcf7c21d20f94439dde5a1145e0676ab067d6",149   "language": "Python",150   "lines": 228,151   "truncated": false,152   "block": 7,153   "row": 4083154  },155  {156   "path": "downstream_task/utils_class.py",157   "sha256": "5f4eb7d0602f3436c9f2e5c9d1dff32d836144527d849bfba7390f484a322596",158   "language": "Python",159   "lines": 174,160   "truncated": false,161   "block": 6,162   "row": 45449163  },164  {165   "path": "eeg_fid.py",166   "sha256": "d0fafcfeb7560a15f5ea785f13b7055a0d66f15acb30b1e378e9526568ff5075",167   "language": "Python",168   "lines": 205,169   "truncated": false,170   "block": 7,171   "row": 1598172  },173  {174   "path": "explain_super_resolution.py",175   "sha256": "0a092a3deadce600afcb13238ea843faeb390d8821c09cd897536ad50458719d",176   "language": "Python",177   "lines": 257,178   "truncated": false,179   "block": 7,180   "row": 3589181  },182  {183   "path": "metrics.py",184   "sha256": "d5238e230f143456cec71d3fe16670c509096223166888343ca02149f7fefdc4",185   "language": "Python",186   "lines": 404,187   "truncated": false,188   "block": 7,189   "row": 6473190  },191  {192   "path": "models.py",193   "sha256": "5d0d400f0d42ad3d68b80af446774afadef79533a5a3c0bbf26cf864366b6c15",194   "language": "Python",195   "lines": 1206,196   "truncated": false,197   "block": 8,198   "row": 237199  },200  {201   "path": "ssi.py",202   "sha256": "7c704f9c67de23944cb4f4e698e68722889d796b9069ac48bc66d1562d657fde",203   "language": "Python",204   "lines": 82,205   "truncated": false,206   "block": 6,207   "row": 36086208  },209  {210   "path": "test.py",211   "sha256": "787793079b5f6090314aa930135adb7c469e19b3a058e9bee6dc1cf83e63e3f2",212   "language": "Python",213   "lines": 372,214   "truncated": false,215   "block": 7,216   "row": 7665217  },218  {219   "path": "train.py",220   "sha256": "f767a73ec2e21cb8d7b7c37c4e3d8028bdac8ab9169598da7c370133db58fe3a",221   "language": "Python",222   "lines": 484,223   "truncated": false,224   "block": 7,225   "row": 9364226  },227  {228   "path": "utils.py",229   "sha256": "9a50c659fc902c041095bdcc726ba55e23ae3078fed39afaa55ee8cf1804c8cf",230   "language": "Python",231   "lines": 1120,232   "truncated": false,233   "block": 8,234   "row": 3235  },236  {237   "path": "visualize.py",238   "sha256": "752c2866c8f03defa42af64532e31b472e05ffa525abf5cb6731c86ac847bf0b",239   "language": "Python",240   "lines": 316,241   "truncated": false,242   "block": 7,243   "row": 4064244  },245  {246   "path": "visualize_input.ipynb",247   "sha256": "82c836ed6e79b19ab16ad41bc715e1d9f90dedd5fac4b06abd6e1adb04b7115d",248   "language": "Jupyter",249   "lines": 462,250   "truncated": false,251   "block": 6,252   "row": 797253  },254  {255   "path": "visualize_signal.py",256   "sha256": "f1a864a33183896fd6faee8ba1702915e151e38df946365357dbca0a0a7081b8",257   "language": "Python",258   "lines": 137,259   "truncated": false,260   "block": 6,261   "row": 42398262  }263 ]264}