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.
05.6k
1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/lyambailey/opm_mnsbp",4 "url": "https://github.com/lyambailey/OPM_MNSBP",5 "host": "github.com",6 "commit": "b703004e1c69958174ff57de80fb59343d868240",7 "license": "BSD-3-Clause",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11 {12 "path": "LICENSE",13 "sha256": "02ff0aa6170d99f1d00e75de3a4f0e6dd6b0d033ecf848448f87e6892adeb3d6",14 "language": "License",15 "lines": 28,16 "truncated": false,17 "block": 6,18 "row": 196319 },20 {21 "path": "work/00_make_combined_ROI.py",22 "sha256": "4fe716ed825fc095cf88a0106320bb1e5a1edeb0b70f6cae41117703943699a0",23 "language": "Python",24 "lines": 54,25 "truncated": false,26 "block": 6,27 "row": 3058528 },29 {30 "path": "work/01_registrationPrep.py",31 "sha256": "da68144d754e44d5a5ff70d327b2b5000dcfd8cc6b045c330e1a347b7703d395",32 "language": "Python",33 "lines": 359,34 "truncated": false,35 "block": 7,36 "row": 458737 },38 {39 "path": "work/02_register.py",40 "sha256": "48ee430765282a9a3d92a8caf4ded0e0023c6d2ef23df68cd428185619056e7e",41 "language": "Python",42 "lines": 411,43 "truncated": false,44 "block": 7,45 "row": 581046 },47 {48 "path": "work/03_find_event_thresholds.ipynb",49 "sha256": "ab3db3c6acb2306876b49df455dea14e52f13a337805bddf37342dbbd233edf1",50 "language": "Jupyter",51 "lines": 103,52 "truncated": false,53 "block": 5,54 "row": 1656955 },56 {57 "path": "work/04_find_bad_channels.ipynb",58 "sha256": "94f042d881b9f13794572db74445f40dd47d1b3ca58018ac9552234eff1f0e42",59 "language": "Jupyter",60 "lines": 202,61 "truncated": false,62 "block": 5,63 "row": 1704164 },65 {66 "path": "work/05_sensor_preprocessing.py",67 "sha256": "4029946374ca6f2885ffbd9948f3ba9e379317fa2bfab7537638edb6653e59fe",68 "language": "Python",69 "lines": 498,70 "truncated": false,71 "block": 7,72 "row": 742573 },74 {75 "path": "work/06_find_bad_epochs.ipynb",76 "sha256": "893ec2280fd611b05268c80ffd6c783341d5c9ba46973aace1c439e369b3c3cc",77 "language": "Jupyter",78 "lines": 57,79 "truncated": false,80 "block": 5,81 "row": 1613182 },83 {84 "path": "work/07_compute_sensor_evoked_and_tfrs.py",85 "sha256": "60fa936a8fa497a216ed220ce6f8fe85276a52ff2b76623680dddbefe59f7f55",86 "language": "Python",87 "lines": 342,88 "truncated": false,89 "block": 7,90 "row": 546591 },92 {93 "path": "work/08_extract_label_evoked.py",94 "sha256": "4b6ac4b5225d5a2ddf5d23c707a17149ca714175f952bcaef8b067044e4d2d26",95 "language": "Python",96 "lines": 232,97 "truncated": false,98 "block": 7,99 "row": 864100 },101 {102 "path": "work/09_extract_label_tfrs.py",103 "sha256": "7e1e01e0efbe85b309c81572bd38d94d2b945e1051703cda01308298848f9593",104 "language": "Python",105 "lines": 333,106 "truncated": false,107 "block": 7,108 "row": 4882109 },110 {111 "path": "work/10_SEF_stats.r",112 "sha256": "587eda7b0c35a23319aaf1900ac56948544b70a194170140e608a953faae1cf6",113 "language": "R",114 "lines": 158,115 "truncated": false,116 "block": 8,117 "row": 3423118 },119 {120 "path": "work/11_mubeta_stats.r",121 "sha256": "7cb130f90ac6bf3d56e2f8860506a3ef147854f31fe20a2da7e1adec769650d6",122 "language": "R",123 "lines": 161,124 "truncated": false,125 "block": 8,126 "row": 3444127 },128 {129 "path": "work/12_plot_SEFs.ipynb",130 "sha256": "c13d0e8b46aedf09c04f5c3b70d4a0b26d1ed2965df3e678a4daaeacca9fbbf4",131 "language": "Jupyter",132 "lines": 342,133 "truncated": false,134 "block": 6,135 "row": 4136 },137 {138 "path": "work/13_plot_sens_tfrs.ipynb",139 "sha256": "cfa83224ddb9a9286401d7389380fb802624735755efdcd4ca26b9c0acadf20c",140 "language": "Jupyter",141 "lines": 251,142 "truncated": false,143 "block": 5,144 "row": 17378145 },146 {147 "path": "work/14_plot_label_tfrs.ipynb",148 "sha256": "174b5d500368b1579e708da9125472040179f6e11abb021a21550c0eed29b9c3",149 "language": "Jupyter",150 "lines": 223,151 "truncated": false,152 "block": 5,153 "row": 17280154 },155 {156 "path": "work/15_compute_snrs_SEF.py",157 "sha256": "c0a6ba3f1f19a3fa462e99328cb27f2fd04dc0a1aecece9049130a2c84e30ee2",158 "language": "Python",159 "lines": 235,160 "truncated": false,161 "block": 7,162 "row": 770163 },164 {165 "path": "work/16_plot_ROIs.py",166 "sha256": "b6bb4eed513a9ba04093292fe293a020371047beaa57e829f1cd823251489f6d",167 "language": "Python",168 "lines": 50,169 "truncated": false,170 "block": 6,171 "row": 28748172 }173 ]174}