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

rootmanifests67github.com__computational-morphogenomics-group__markermap.json

github.com__computational-morphogenomics-group__markermap.json273 linesDownload Raw Back to 67

1{2 "format": "oscr-script-manifest/1",3 "repository": "github.com/computational-morphogenomics-group/markermap",4 "url": "https://github.com/Computational-Morphogenomics-Group/MarkerMap.git",5 "host": "github.com",6 "commit": "f15cefe2b6737b3b0f1abf31182fe9ae6af8a980",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11  {12   "path": "LICENSE",13   "sha256": "504e433b7b01f8bac3e5f017d9a3ddb27c3f061c1a90dc2392c4d88e1982f27a",14   "language": "License",15   "lines": 21,16   "truncated": false,17   "block": 6,18   "row": 183119  },20  {21   "path": "README.md",22   "sha256": "b001377be5e51dc0a8e30aacce4c2408cfd6b6af9b10f3bfb12fd729106a2473",23   "language": "Text",24   "lines": 238,25   "truncated": false,26   "block": 8,27   "row": 1077328  },29  {30   "path": "notebooks/quick_start.ipynb",31   "sha256": "0643e0defdb23a9be4e4b91f2ff39cb9004f654f124b34e65042713757926d59",32   "language": "Jupyter",33   "lines": 96,34   "truncated": false,35   "block": 5,36   "row": 1666037  },38  {39   "path": "notebooks/quick_start_benchmark.ipynb",40   "sha256": "65cdb52afdaa31fd5f4e7a1e13d096a01cf4182ef9ea4c6acd99936a854522b0",41   "language": "Jupyter",42   "lines": 114,43   "truncated": false,44   "block": 5,45   "row": 1688246  },47  {48   "path": "notebooks/unmaintained/Array_of_Markers.ipynb",49   "sha256": "e1e917de8a64d2f0b72235402f0b66226601723b8b383cf1025985e180b8ee52",50   "language": "Jupyter",51   "lines": 317,52   "truncated": false,53   "block": 5,54   "row": 1761155  },56  {57   "path": "notebooks/unmaintained/CITE_seq.ipynb",58   "sha256": "e865fad170742c72212b5d8a4631071fc69b3c68465d5bf57c3456b540942d0d",59   "language": "Jupyter",60   "lines": 1820,61   "truncated": false,62   "block": 6,63   "row": 126064  },65  {66   "path": "notebooks/unmaintained/DemoSimpleInterface.ipynb",67   "sha256": "b02cbd668de4146e3842b1336fa667f5595fc3af9e0af7f8dcbbd6a3119191aa",68   "language": "Jupyter",69   "lines": 190,70   "truncated": false,71   "block": 5,72   "row": 1681573  },74  {75   "path": "notebooks/unmaintained/Mouse_Brain_Broad.ipynb",76   "sha256": "a6362561a886716a9aaa28001a9df307908c23dcefa2e91d1dc2ac93b317a877",77   "language": "Jupyter",78   "lines": 647,79   "truncated": false,80   "block": 6,81   "row": 101282  },83  {84   "path": "notebooks/unmaintained/Paul.ipynb",85   "sha256": "b263872fc562ef10b7a78cecb634907acb5e583038193b719f34534b8ad9db50",86   "language": "Jupyter",87   "lines": 652,88   "truncated": false,89   "block": 6,90   "row": 101791  },92  {93   "path": "notebooks/unmaintained/SummaryTable.ipynb",94   "sha256": "03c2b40f167f2d5792f25520de7b5486cc24a82d29a1509600d9cdaed1133d76",95   "language": "Jupyter",96   "lines": 160,97   "truncated": false,98   "block": 5,99   "row": 16731100  },101  {102   "path": "notebooks/unmaintained/Synthetic_Data.ipynb",103   "sha256": "f307808fb6c4d4cda7d8691fd6e59466ce4b83430392b3d4276880dcbdf51f35",104   "language": "Jupyter",105   "lines": 850,106   "truncated": false,107   "block": 6,108   "row": 1113109  },110  {111   "path": "notebooks/unmaintained/Zeisel.ipynb",112   "sha256": "e49dfdae52f485b15ae5fd07708d3f0f189171bbf83c9fc810114a080e60ccc9",113   "language": "Jupyter",114   "lines": 653,115   "truncated": false,116   "block": 6,117   "row": 1011118  },119  {120   "path": "scripts/Summary_Graphs.py",121   "sha256": "40c4ebc9c94444b45236380c9d491779dcaef617db6e41340e7910f380cf2a51",122   "language": "Python",123   "lines": 560,124   "truncated": false,125   "block": 7,126   "row": 4997127  },128  {129   "path": "scripts/benchmark_k.py",130   "sha256": "c8e6e81a5c4d7278ce219784a9b07f964a9a5b90871f8b3b5dfc549b1cb1023c",131   "language": "Python",132   "lines": 372,133   "truncated": false,134   "block": 7,135   "row": 4235136  },137  {138   "path": "scripts/display_results.py",139   "sha256": "e183855ccc3cd82218fc82371029d9d9fb562df92aba0f06dd401e286f287e30",140   "language": "Python",141   "lines": 137,142   "truncated": false,143   "block": 6,144   "row": 36847145  },146  {147   "path": "scripts/evaluate_reconstruction.py",148   "sha256": "ee5d714b7da88563f0f8635437f1e7d4e6d7229b3fd22220186394d54549c421",149   "language": "Python",150   "lines": 274,151   "truncated": false,152   "block": 7,153   "row": 1341154  },155  {156   "path": "scripts/quick_start.py",157   "sha256": "c35ba5c6fbe5a52e2b456aff7e45c45f91e613283ef0034c3804eafd90fa566c",158   "language": "Python",159   "lines": 70,160   "truncated": false,161   "block": 6,162   "row": 31922163  },164  {165   "path": "scripts/quick_start_benchmark.py",166   "sha256": "1c2eebc51010d70952f3d97aed20fb2060e2b5cac7db7bdd176eca0cee8ee466",167   "language": "Python",168   "lines": 84,169   "truncated": false,170   "block": 6,171   "row": 32932172  },173  {174   "path": "src/RankCorr/RankCorr-example.ipynb",175   "sha256": "3496c363332e4d080c57356a291db08571cf3442d046a3242a2ba9a6e4ecbaa0",176   "language": "Jupyter",177   "lines": 135,178   "truncated": false,179   "block": 5,180   "row": 16857181  },182  {183   "path": "src/RankCorr/__init__.py",184   "sha256": "b8149140af4f979aca7a5678624d4ca9aea968918632b848f8b24b12d077d1a7",185   "language": "Python",186   "lines": 1,187   "truncated": false,188   "block": 6,189   "row": 20495190  },191  {192   "path": "src/RankCorr/performance.py",193   "sha256": "1b4abf6f46dab64d02610823e05a00af9f03238da85f610378191c7ab64d81f7",194   "language": "Python",195   "lines": 262,196   "truncated": false,197   "block": 7,198   "row": 2442199  },200  {201   "path": "src/RankCorr/rocks.py",202   "sha256": "4aa2bc4cf6b7ba84a7af36e5c13aa1b14c837d2b1d14c7666edf78f34d449fcd",203   "language": "Python",204   "lines": 941,205   "truncated": false,206   "block": 7,207   "row": 11323208  },209  {210   "path": "src/markermap/other_models.py",211   "sha256": "a6ccd619de45655c1731878f38f8c854d9e6e4943bc73dc0ee0a1de3e22192d4",212   "language": "Python",213   "lines": 531,214   "truncated": false,215   "block": 7,216   "row": 9242217  },218  {219   "path": "src/markermap/smashpy_model.py",220   "sha256": "cf96a37a40aa7096540ede5c6a67194ededadcabe041683091686b3931911a24",221   "language": "Python",222   "lines": 181,223   "truncated": false,224   "block": 6,225   "row": 45054226  },227  {228   "path": "src/markermap/utils.py",229   "sha256": "c0a4e49ad5d4e9f72654bbabe0f57e6c036e08cccbea63e3aae59c0af11747fc",230   "language": "Python",231   "lines": 1336,232   "truncated": false,233   "block": 8,234   "row": 392235  },236  {237   "path": "src/markermap/vae_models.py",238   "sha256": "3c9a2ee15094158d8cc5514764d69b17017d13da593c9372ec40512caa23fcf1",239   "language": "Python",240   "lines": 1240,241   "truncated": false,242   "block": 8,243   "row": 53244  },245  {246   "path": "tests/test_benchmark.py",247   "sha256": "d4f06422aeecc71d21e7ff1a28ea9ed66b91c3afb8ce597bb39ca020afa12452",248   "language": "Python",249   "lines": 52,250   "truncated": false,251   "block": 6,252   "row": 32565253  },254  {255   "path": "tests/test_dataloaders.py",256   "sha256": "a40802960a16128263c4cada072aef9a5929aafb43758fd30d756082c3acb792",257   "language": "Python",258   "lines": 86,259   "truncated": false,260   "block": 6,261   "row": 36383262  },263  {264   "path": "tests/test_plots.py",265   "sha256": "4fedca94fb2133ec4ce25aa5c17f4a65187bf5caa62c85af16a6fdfc07afda30",266   "language": "Python",267   "lines": 106,268   "truncated": false,269   "block": 6,270   "row": 37730271  }272 ]273}