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 1d agoView on Hugging Face
0likes5.4kdownloads
rootmanifestscegithub.com__kordinglab__neural_decoding.json
github.com__kordinglab__neural_decoding.json300 linesDownload Raw Back to ce
1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/kordinglab/neural_decoding",4 "url": "https://github.com/KordingLab/Neural_Decoding",5 "host": "github.com",6 "commit": "ed8e8f92027f92c18ebfd877ef28333da2e9646c",7 "license": "BSD-3-Clause",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11  {12   "path": "Example_format_data.ipynb",13   "sha256": "f949c96181384638596de6ed7ddff28e57e40603b482ec505f78a8a1918b8cb6",14   "language": "Jupyter",15   "lines": 83,16   "truncated": false,17   "block": 19,18   "row": 384219  },20  {21   "path": "Example_hyperparam_opt.ipynb",22   "sha256": "8a6e7c18b787933a654f53321f4476895754c810e5e4946e3c20148772842932",23   "language": "Jupyter",24   "lines": 558,25   "truncated": false,26   "block": 19,27   "row": 410728  },29  {30   "path": "Examples_all_decoders.ipynb",31   "sha256": "3f05c67182826c8a23c3d05fb6eb6b812cd570d7036ac0c0befdc714b80ec52a",32   "language": "Jupyter",33   "lines": 353,34   "truncated": false,35   "block": 19,36   "row": 399437  },38  {39   "path": "Examples_hippocampus/Example_format_data_hc.ipynb",40   "sha256": "ec0e8fd633c4ff238a1fe20dcd5ebb83a9812be842957b236633f3e6bec7fa9d",41   "language": "Jupyter",42   "lines": 86,43   "truncated": false,44   "block": 19,45   "row": 385046  },47  {48   "path": "Examples_hippocampus/Examples_decoders_hc.ipynb",49   "sha256": "e585cc09af2b9aef042ff01bb6e4c524978450ebb220caa4f47526c8c0c3e4dc",50   "language": "Jupyter",51   "lines": 275,52   "truncated": false,53   "block": 19,54   "row": 397155  },56  {57   "path": "Examples_hippocampus/Examples_kf_decoder_hc.ipynb",58   "sha256": "5744b8b8271a98850bf5893502a6844f4e97173f7914b8ed13305c0b96b5bebf",59   "language": "Jupyter",60   "lines": 222,61   "truncated": false,62   "block": 19,63   "row": 395364  },65  {66   "path": "Examples_hippocampus/Examples_naivebayes_decoder_hc.ipynb",67   "sha256": "328d01cff27a3a8e2f88274635f4b0103eb29bac0c91ba15ca8e6d48120b107e",68   "language": "Jupyter",69   "lines": 221,70   "truncated": false,71   "block": 19,72   "row": 395073  },74  {75   "path": "Examples_kf_decoder.ipynb",76   "sha256": "1bd9d9a26f31ecf5f5afef9d5427c359e76d009e2356db328d8c497be1d4d044",77   "language": "Jupyter",78   "lines": 215,79   "truncated": false,80   "block": 19,81   "row": 395782  },83  {84   "path": "LICENSE",85   "sha256": "0cbdbfa1694160e5ca687ec21dcd2200c41c92e73a75e3888d441592fcee1a90",86   "language": "License",87   "lines": 29,88   "truncated": false,89   "block": 19,90   "row": 427491  },92  {93   "path": "Neural_Decoding/__init__.py",94   "sha256": "687b82fc8d810593ebfb6cfecec28e1411b79f3e2c1d903df20708464f7aa5b0",95   "language": "Python",96   "lines": 4,97   "truncated": false,98   "block": 19,99   "row": 8812100  },101  {102   "path": "Neural_Decoding/decoders.py",103   "sha256": "d7b26438101b393e91a4d09726034e01d878470c69fe234f787839809b33730f",104   "language": "Python",105   "lines": 1685,106   "truncated": false,107   "block": 19,108   "row": 14590109  },110  {111   "path": "Neural_Decoding/metrics.py",112   "sha256": "ab9a2b88c1736809bc74471c63457a189c3f7acac388747c36b98a578910abb7",113   "language": "Python",114   "lines": 56,115   "truncated": false,116   "block": 19,117   "row": 9650118  },119  {120   "path": "Neural_Decoding/preprocessing_funcs.py",121   "sha256": "ec86d21e1880d7b6885503f6e2b61774f177df340b0647b448e2e8889f7323cb",122   "language": "Python",123   "lines": 119,124   "truncated": false,125   "block": 19,126   "row": 12092127  },128  {129   "path": "Paper_code/BayesDecoder_FullData.ipynb",130   "sha256": "e34fa6d5b76229485ab24cb04bc50136a80b48d3bd334af74fa1ba5c074aaefb",131   "language": "Jupyter",132   "lines": 362,133   "truncated": false,134   "block": 19,135   "row": 4012136  },137  {138   "path": "Paper_code/Ensemble_FullData.ipynb",139   "sha256": "5696da3dc826828791fdf04aa95811d9b7436682ac1a3cbc1b8088728e304cea",140   "language": "Jupyter",141   "lines": 161,142   "truncated": false,143   "block": 19,144   "row": 3959145  },146  {147   "path": "Paper_code/Hyperparameter_Sensitivity.ipynb",148   "sha256": "542453ba855971e113602130be07d40b1fbe6f6b57c8d6994f7415fba59755bb",149   "language": "Jupyter",150   "lines": 340,151   "truncated": false,152   "block": 19,153   "row": 3992154  },155  {156   "path": "Paper_code/KF_BinSize.ipynb",157   "sha256": "b88273d7dff470f5064e9f59758452d87ab9f5d8207f6624d8bc4524d5644e50",158   "language": "Jupyter",159   "lines": 451,160   "truncated": false,161   "block": 19,162   "row": 4060163  },164  {165   "path": "Paper_code/KF_DataAmt.ipynb",166   "sha256": "266d05b559f2077518c9b26e3850c791eaa8d10084b3a6afeddcd134db3f050e",167   "language": "Jupyter",168   "lines": 452,169   "truncated": false,170   "block": 19,171   "row": 4067172  },173  {174   "path": "Paper_code/KF_FewNeurons.ipynb",175   "sha256": "a6d4a77e1167ac5d286b4078086bdd1cfb6da1f3faa3be7fd182cbb13eae5c88",176   "language": "Jupyter",177   "lines": 448,178   "truncated": false,179   "block": 19,180   "row": 4063181  },182  {183   "path": "Paper_code/KF_FullData.ipynb",184   "sha256": "65f3dd8af2f97c0b0f5e5bb39ebee2b2ed0141f75a4c395dfb68844f1207abc0",185   "language": "Jupyter",186   "lines": 405,187   "truncated": false,188   "block": 19,189   "row": 4061190  },191  {192   "path": "Paper_code/ManyDecoders_BinSize.ipynb",193   "sha256": "214b561ae9fa3dc147ca9b77377d74cced754a22c2bf2f603d3bfad4e6d1f274",194   "language": "Jupyter",195   "lines": 677,196   "truncated": false,197   "block": 19,198   "row": 4096199  },200  {201   "path": "Paper_code/ManyDecoders_DataAmt.ipynb",202   "sha256": "5983ea88e53edd10d820db06e4bc71acc48d67c48749928158f532656d4aea11",203   "language": "Jupyter",204   "lines": 670,205   "truncated": false,206   "block": 19,207   "row": 4097208  },209  {210   "path": "Paper_code/ManyDecoders_FewNeurons.ipynb",211   "sha256": "3b438df9cf6408aaae19980860093e0412078c46882cab5ebe5596695a7598f9",212   "language": "Jupyter",213   "lines": 744,214   "truncated": false,215   "block": 19,216   "row": 4129217  },218  {219   "path": "Paper_code/ManyDecoders_FullData.ipynb",220   "sha256": "b1c317ea77aecb89ebada456d9c458edef76874cac5651aba6a8d77dd63f0b09",221   "language": "Jupyter",222   "lines": 710,223   "truncated": false,224   "block": 19,225   "row": 4128226  },227  {228   "path": "Paper_code/Plot_Results_BinSize.ipynb",229   "sha256": "c8c13702e22bb178cb687bd3500d4228e3e5529b788d5a396d0e57e9ef4df0e4",230   "language": "Jupyter",231   "lines": 212,232   "truncated": false,233   "block": 19,234   "row": 3979235  },236  {237   "path": "Paper_code/Plot_Results_FewNeurons.ipynb",238   "sha256": "b5d3b44947dea844ea90ef8609fa4003258a351c41b675bef5508c527ad08ae1",239   "language": "Jupyter",240   "lines": 94,241   "truncated": false,242   "block": 19,243   "row": 3861244  },245  {246   "path": "Paper_code/Plot_Results_FullData.ipynb",247   "sha256": "710b5257f444a0f91f3dbdbbf28f1e95547aa01db9769e06fe9f9ee91828a7d8",248   "language": "Jupyter",249   "lines": 499,250   "truncated": false,251   "block": 19,252   "row": 4086253  },254  {255   "path": "Paper_code/Plot_Results_Hyperparams.ipynb",256   "sha256": "dadfd6e7e1ba7bcf57b7da705d1b1e71f956fcbe2b5f02ac230d05a92e985397",257   "language": "Jupyter",258   "lines": 105,259   "truncated": false,260   "block": 19,261   "row": 3830262  },263  {264   "path": "Paper_code/Plot_Results_LimitedData.ipynb",265   "sha256": "8a490255b45d4fd8094349d667cb63dbcbc54ca35b13c45bdb0219cf8db868e0",266   "language": "Jupyter",267   "lines": 342,268   "truncated": false,269   "block": 19,270   "row": 4030271  },272  {273   "path": "README.md",274   "sha256": "15992d3f7d934862a3ce40799a6117bbf0efaf2c9a642afb400013eb9932a14a",275   "language": "Text",276   "lines": 160,277   "truncated": false,278   "block": 19,279   "row": 16191280  },281  {282   "path": "central_concepts_in_ML_for_decoding.ipynb",283   "sha256": "ed40e82cbe7612aa0c38bd483cb76b79b0472ca7cd9363de48e91c2b325e33b9",284   "language": "Jupyter",285   "lines": 691,286   "truncated": false,287   "block": 19,288   "row": 4095289  },290  {291   "path": "setup.py",292   "sha256": "645d8cf0a4c6c3928f4786953c10a157e5484ea55eab52411959cacce43e638e",293   "language": "Python",294   "lines": 43,295   "truncated": false,296   "block": 19,297   "row": 9580298  }299 ]300}