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/s-m-sys/mix_with_saps",4 "url": "https://github.com/s-m-sys/mix_with_SAPs",5 "host": "github.com",6 "commit": "f69e99bfce1e3170a6d1cffe58dd431841b30140",7 "license": "GPL-3.0",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11 {12 "path": "Figures_and_data/Figure_1_a_initial_distribution/imageGen.ipynb",13 "sha256": "a2ff796d310680b10be858f32366fd237edf30421a2222b4458ec04f265f1bba",14 "language": "Jupyter",15 "lines": 57,16 "truncated": false,17 "block": 14,18 "row": 1487619 },20 {21 "path": "Figures_and_data/Figure_3_RT_snapshots/Fig_3_a/imageGen.ipynb",22 "sha256": "44d46fc81e278941b80a072be88ad80fc8680e7e9b1251eafef1f44ffaf500bb",23 "language": "Jupyter",24 "lines": 68,25 "truncated": false,26 "block": 14,27 "row": 1489828 },29 {30 "path": "Figures_and_data/Figure_3_RT_snapshots/Fig_3_b/act_particle_loci_cmap_from_active_data.ipynb",31 "sha256": "45cd45ef7393ff5d4668600d375a5b9a71edcf3a1ded3f9dd31c62ca78eedf91",32 "language": "Jupyter",33 "lines": 106,34 "truncated": false,35 "block": 14,36 "row": 1500137 },38 {39 "path": "Figures_and_data/Figure_4/Fig_4_a_traj/trajectory_plots.ipynb",40 "sha256": "8d3a642a592e0625bf8a11b2b6a2f4a445e069b6ac07bdefa411434429b79fd5",41 "language": "Jupyter",42 "lines": 79,43 "truncated": false,44 "block": 14,45 "row": 1498346 },47 {48 "path": "Figures_and_data/Figure_4/Fig_4_b_kde/kde_passive_RT.ipynb",49 "sha256": "9c239a13e55f97cfad81994312c0b464f453c6f14d0b154f3e997486a6d69207",50 "language": "Jupyter",51 "lines": 70,52 "truncated": false,53 "block": 14,54 "row": 1489755 },56 {57 "path": "Figures_and_data/Figure_5/Trained/imageGen.ipynb",58 "sha256": "c1cb99661b26c288584f38f6cb334ead52822a98dffc8c7bea60171938934c7e",59 "language": "Jupyter",60 "lines": 62,61 "truncated": false,62 "block": 14,63 "row": 1486564 },65 {66 "path": "Figures_and_data/Figure_5/non-Trained/imageGen.ipynb",67 "sha256": "c1cb99661b26c288584f38f6cb334ead52822a98dffc8c7bea60171938934c7e",68 "language": "Jupyter",69 "lines": 62,70 "truncated": false,71 "block": 14,72 "row": 1486573 },74 {75 "path": "Figures_and_data/Figure_6/Fig_6_a_i/act_particle_loci_cmap_from_act_data.ipynb",76 "sha256": "6e89f6b2ca615338f288fe17c5a4fa12636d2773473776e61c06264522bdbc30",77 "language": "Jupyter",78 "lines": 102,79 "truncated": false,80 "block": 14,81 "row": 1500482 },83 {84 "path": "Figures_and_data/Figure_6/Fig_6_a_ii/act_particle_loci_cmap_from_act_data.ipynb",85 "sha256": "df5a92bce9c1038636e09089483dd6efb8edcbaadff916cbc1f4e78f3d7e69c6",86 "language": "Jupyter",87 "lines": 96,88 "truncated": false,89 "block": 14,90 "row": 1497991 },92 {93 "path": "Figures_and_data/Figure_6/Fig_6_b/traj_active_from_data.ipynb",94 "sha256": "e27fb790ef3d7d1a662e954c5cb75e6055cfd5f53a624c20fdc8126cb01b925d",95 "language": "Jupyter",96 "lines": 84,97 "truncated": false,98 "block": 14,99 "row": 15074100 },101 {102 "path": "Figures_and_data/Figure_6/Fig_6_c_inset/consolidated_mean_curves_RTP.ipynb",103 "sha256": "c558c9ddfb1aaa3724b85572596c96e8f428534ee667ffcbf8ccf262fb38207a",104 "language": "Jupyter",105 "lines": 35,106 "truncated": false,107 "block": 14,108 "row": 14805109 },110 {111 "path": "Figures_and_data/Figure_6/Fig_6_c_main/plotting_graphs_with_band.ipynb",112 "sha256": "75c0b8bddd9857f549e8d93dc9ba0794f36663046968a8cb2907293f4481c6bd",113 "language": "Jupyter",114 "lines": 203,115 "truncated": false,116 "block": 14,117 "row": 15591118 },119 {120 "path": "Figures_and_data/Figure_7/dist_fit.m",121 "sha256": "56cc07450c4746aa801f34cfb2ffef0e2ae968540b2d8ba9d97a9d8d0a09baa4",122 "language": "MATLAB",123 "lines": 50,124 "truncated": false,125 "block": 14,126 "row": 21251127 },128 {129 "path": "Figures_and_data/Figure_8/Fig_8_a/quiver_colour_plots.ipynb",130 "sha256": "bd42cab7b72c70eebb0ad52ec0ccf2491ebecad59b6074defd46f5e4988ccd68",131 "language": "Jupyter",132 "lines": 81,133 "truncated": false,134 "block": 14,135 "row": 15017136 },137 {138 "path": "Figures_and_data/Figure_8/Fig_8_b/quiver_colour_plots.ipynb",139 "sha256": "15ee71ab5ea89d4c8f82a1354df6090ee1320e43aa7eb7917388d25efc379188",140 "language": "Jupyter",141 "lines": 84,142 "truncated": false,143 "block": 14,144 "row": 15024145 },146 {147 "path": "Figures_and_data/Figure_8/Fig_8_c/Ridge_plot_from_data.ipynb",148 "sha256": "6a412b7dbffc664b7e220ac8a4753b5a9627ee3093b96d16c87303c8844786d8",149 "language": "Jupyter",150 "lines": 57,151 "truncated": false,152 "block": 14,153 "row": 14910154 },155 {156 "path": "Figures_and_data/Figure_9/Consolidated_figs_delta_fixed_gamma_varying.ipynb",157 "sha256": "b07bd547ed0f03e8426a3fa96fdc14cfa0cbf62c7a6c1327f9dc3c86519c51d4",158 "language": "Jupyter",159 "lines": 94,160 "truncated": false,161 "block": 14,162 "row": 14981163 },164 {165 "path": "LICENSE",166 "sha256": "3972dc9744f6499f0f9b2dbf76696f2ae7ad8af9b23dde66d6af86c9dfb36986",167 "language": "License",168 "lines": 674,169 "truncated": false,170 "block": 1,171 "row": 2235172 },173 {174 "path": "README.md",175 "sha256": "7edf29ce3083d5092a824fc89e17e42d0484b9d310c5082a2ac94ce22b2d0ac7",176 "language": "Text",177 "lines": 112,178 "truncated": false,179 "block": 16,180 "row": 7473181 },182 {183 "path": "Test_run/mixing.c",184 "sha256": "b1b05a32eece7c09ce0385c1c4c88e51d9bac5ad5665a82a8faa46c0adaa2b2a",185 "language": "C",186 "lines": 191,187 "truncated": false,188 "block": 14,189 "row": 237190 },191 {192 "path": "Test_run/test_run.ipynb",193 "sha256": "fc27bb6d0d5f6de662bee9ffa5f2bbddd108e22dc827c8bcf52c05f768605650",194 "language": "Jupyter",195 "lines": 391,196 "truncated": false,197 "block": 14,198 "row": 16264199 },200 {201 "path": "Training/PYTHON_C_MIXING_v1.ipynb",202 "sha256": "8906cdfb430a25e6e10056268fd43a03d41625297c39dfd929d07675c481f9d3",203 "language": "Jupyter",204 "lines": 391,205 "truncated": false,206 "block": 14,207 "row": 16284208 },209 {210 "path": "Training/mixing.c",211 "sha256": "b1b05a32eece7c09ce0385c1c4c88e51d9bac5ad5665a82a8faa46c0adaa2b2a",212 "language": "C",213 "lines": 191,214 "truncated": false,215 "block": 14,216 "row": 237217 }218 ]219}