manifests/27/github.com__coencagli-lab__2025-naturecommunications-farzmahdi-et-al-code.json

{
 "format": "oscr-script-manifest/1",
 "repository": "github.com/coencagli-lab/2025-naturecommunications-farzmahdi-et-al-code",
 "url": "https://github.com/CoenCagli-Lab/2025-NatureCommunications-Farzmahdi-et-al-code",
 "host": "github.com",
 "commit": "bcc36d2a3a2f5cb4f02f1d844faafd58eac76eda",
 "license": "MIT",
 "license_confirmed_by": "license file LICENSE",
 "redistribution": "yes",
 "files": [
  {
   "path": "LICENSE",
   "sha256": "25e9c033733bcfa6746d5e41a6010a30811663f1a780f4ce5b3e2fc56e459e3c",
   "language": "License",
   "lines": 21,
   "truncated": false,
   "block": 22,
   "row": 14062
  },
  {
   "path": "README.md",
   "sha256": "ef87b9fb1e60b08a494fefbfa81f5012ca98f40b8f902cb8f1be22cf2aa4eae1",
   "language": "Text",
   "lines": 20,
   "truncated": false,
   "block": 24,
   "row": 387
  },
  {
   "path": "figure01.ipynb",
   "sha256": "2ec17994e7c4038a300151965fc476f6b24dc0dda00bbcabd208ecb709c6a035",
   "language": "Jupyter",
   "lines": 188,
   "truncated": false,
   "block": 22,
   "row": 12872
  },
  {
   "path": "figure02B.ipynb",
   "sha256": "a4d38311f87fc73acfb3efcc1062920b52bff13068a403c98b7bf41c8b129a53",
   "language": "Jupyter",
   "lines": 172,
   "truncated": false,
   "block": 22,
   "row": 12863
  },
  {
   "path": "figure03AD.ipynb",
   "sha256": "de7b5a24ee62c0694610185d1d4612a1e2b6712a42125d7772d331dfbb94f96e",
   "language": "Jupyter",
   "lines": 271,
   "truncated": false,
   "block": 22,
   "row": 13151
  },
  {
   "path": "figure03G.ipynb",
   "sha256": "91466457e9cafa221a44656d4a14235de7d8660faafd7772048d175e2871aae0",
   "language": "Jupyter",
   "lines": 147,
   "truncated": false,
   "block": 22,
   "row": 12884
  },
  {
   "path": "figure04A.m",
   "sha256": "6ee092b89575b92f23273dc063891f166914ca8de2ba9d6478bfce811308dce5",
   "language": "MATLAB",
   "lines": 394,
   "truncated": false,
   "block": 22,
   "row": 24298
  },
  {
   "path": "figure04B.m",
   "sha256": "aa55490f208ffcfa4e924471cd3ad2c076878be34d2f9c0371a61038181333cb",
   "language": "MATLAB",
   "lines": 214,
   "truncated": false,
   "block": 22,
   "row": 23084
  },
  {
   "path": "figure04B_anes136.m",
   "sha256": "392ee34f921efda9f00b52d89e071905e0de52f7dc92e8e166c9a6c67e5b29e6",
   "language": "MATLAB",
   "lines": 115,
   "truncated": false,
   "block": 22,
   "row": 21523
  },
  {
   "path": "figure04B_anes150.m",
   "sha256": "0e6aca85aa30dc1d76af2417932c26826a9cfb1c4e5c80b62b0408ba16866219",
   "language": "MATLAB",
   "lines": 109,
   "truncated": false,
   "block": 22,
   "row": 21477
  },
  {
   "path": "figure04B_nn2015.m",
   "sha256": "2f20390e452552b87894ed96d6734e93b074bf22df740cc252fdad92544f03f7",
   "language": "MATLAB",
   "lines": 158,
   "truncated": false,
   "block": 22,
   "row": 22687
  },
  {
   "path": "figure05.m",
   "sha256": "ae6d0ee487dbcbb48ccbb47e2340f57980e94005f91e11cac8f999d893bce6a4",
   "language": "MATLAB",
   "lines": 403,
   "truncated": false,
   "block": 22,
   "row": 24426
  },
  {
   "path": "figure06.ipynb",
   "sha256": "29c1ac2564cc5d4c33044342417e56fc77f7df3f6d3f6cc7cd9d7070d6cee425",
   "language": "Jupyter",
   "lines": 167,
   "truncated": false,
   "block": 22,
   "row": 12874
  },
  {
   "path": "figure06A.ipynb",
   "sha256": "ebea73f98b2a6e070a7fadd02f9d798a11caa98e880ad1ee47e7e445f47a8359",
   "language": "Jupyter",
   "lines": 98,
   "truncated": false,
   "block": 22,
   "row": 12660
  },
  {
   "path": "figure06B.ipynb",
   "sha256": "ccbd3e733ee896308b93043dba82be8e7ef89946c7e655e4d55bebdab8ff8034",
   "language": "Jupyter",
   "lines": 213,
   "truncated": false,
   "block": 22,
   "row": 13092
  },
  {
   "path": "figure06C.m",
   "sha256": "a51a2753872a3460414a1216f781ac7529fe9860c260b40da45025865e48793a",
   "language": "MATLAB",
   "lines": 344,
   "truncated": false,
   "block": 22,
   "row": 24169
  },
  {
   "path": "pairwise_gsm_model.ipynb",
   "sha256": "e0bb4e27233a8912bc657f36b7b787ad88c86444c74261b1527f72bc2ae465b2",
   "language": "Jupyter",
   "lines": 793,
   "truncated": false,
   "block": 22,
   "row": 13625
  },
  {
   "path": "pairwise_model_likelihood.ipynb",
   "sha256": "9dfe8ad2e817d535d14f280fb020fb261406b2ffdc58779621d442137408f8f8",
   "language": "Jupyter",
   "lines": 141,
   "truncated": false,
   "block": 22,
   "row": 12795
  },
  {
   "path": "test_natural_images.ipynb",
   "sha256": "e692c10c623d2e842985f9e0fe240ed9bb22768e50851bd3cc765ed0cee82ebf",
   "language": "Jupyter",
   "lines": 286,
   "truncated": false,
   "block": 22,
   "row": 13149
  },
  {
   "path": "train_noise_cov_mat.ipynb",
   "sha256": "2902126bf8024e029669eb4dbc8bbf2a8d3472ae914e32161da3f6103a1aa325",
   "language": "Jupyter",
   "lines": 320,
   "truncated": false,
   "block": 22,
   "row": 13230
  }
 ]
}