{ "format": "oscr-script-manifest/1", "repository": "github.com/nih-megcore/megnet", "url": "http://github.com/nih-megcore/MegNet", "host": "github.com", "commit": "6148992041fb9c32c1902c9c486f31515d475616", "license": "BSD-3-Clause", "license_confirmed_by": "license file LICENSE", "redistribution": "yes", "files": [ { "path": "LICENSE", "sha256": "d2084d7604a1786b1184977be478ad2455d8d4a884b55f6d0a9fe9202779759b", "language": "License", "lines": 29, "truncated": false, "block": 6, "row": 2016 }, { "path": "MEGnet/__init__.py", "sha256": "526b282f88303f36f72a285166c33c7d0319eea25db22e2c03bd31f1fc41c7f2", "language": "Python", "lines": 3, "truncated": false, "block": 12, "row": 3307 }, { "path": "MEGnet/label_ICA_components.py", "sha256": "ac7b82665b0a7f220055e24f78b001edf268102e0ba5a3a38a66107774ae5d64", "language": "Python", "lines": 89, "truncated": false, "block": 6, "row": 40375 }, { "path": "MEGnet/megnet_init.py", "sha256": "e58a3856a6b73ed42586121c6123e791f9cc11cf1756e5598f24711c8b40434a", "language": "Python", "lines": 82, "truncated": false, "block": 12, "row": 8859 }, { "path": "MEGnet/megnet_qc_plots.py", "sha256": "7523b0882d931a8cebdfe6c6ade2858bc3ba1b03ab8c1d8a4ffee820db3b1774", "language": "Python", "lines": 141, "truncated": false, "block": 12, "row": 16188 }, { "path": "MEGnet/megnet_utilities.py", "sha256": "11fad6b8b81d91825e62d2e507643703f28067b2f8fc5a00da5dc2222842ab57", "language": "Python", "lines": 423, "truncated": false, "block": 7, "row": 9462 }, { "path": "MEGnet/prep_inputs/ICA.ipynb", "sha256": "2ed02187b25b09338cd5c18d6ae05182a2a52b0d2a87daeed04cfa1ca221af98", "language": "Jupyter", "lines": 323, "truncated": false, "block": 6, "row": 39 }, { "path": "MEGnet/prep_inputs/ICA.py", "sha256": "ba1c65170b1001a02e0cf15951e744f811a1bce95b21a46b38f50ccd4e40efa4", "language": "Python", "lines": 989, "truncated": false, "block": 12, "row": 22424 }, { "path": "MEGnet/prep_inputs/assess_predictions.py", "sha256": "5d55a948a3a30790a13fbd79013d2420c6a08b79bedde99a4c0459817f75032e", "language": "Python", "lines": 211, "truncated": false, "block": 7, "row": 1115 }, { "path": "MEGnet/prep_inputs/assess_predictions_pkl.py", "sha256": "647b2da6d92529303d32641ca22c6794196a2a6de971919dc10295a69fd005d9", "language": "Python", "lines": 128, "truncated": false, "block": 12, "row": 13427 }, { "path": "MEGnet/prep_inputs/augmentation_generator.py", "sha256": "fd01ec4c0e932257302a435fc59aa901a776e226769e650e290b96bc50546e13", "language": "Python", "lines": 90, "truncated": false, "block": 12, "row": 11266 }, { "path": "MEGnet/prep_inputs/build_save_dframe_nparrs_inputs.py", "sha256": "965eb3616ecc6431458b732f46ccbdb90c28c0cff09e866eb90bc8a42539b9b9", "language": "Python", "lines": 455, "truncated": false, "block": 12, "row": 20003 }, { "path": "MEGnet/prep_inputs/build_save_dframe_pkl_inputs.py", "sha256": "31bc20cfade95f44d86811cdc53233ca19f5c9b56f0546fb991a7df7925cce1b", "language": "Python", "lines": 523, "truncated": false, "block": 12, "row": 20489 }, { "path": "MEGnet/prep_inputs/convert_hcp_ica.py", "sha256": "181f40de36839fef1c97b0ff5a9d0a8ff1b903fb6309e8d5962173f24deb2a32", "language": "Python", "lines": 163, "truncated": false, "block": 6, "row": 42637 }, { "path": "MEGnet/prep_inputs/convert_keras_model.sh", "sha256": "159d091b504936321d175871e808d3ce6cdaafe4ac71b5235971a48385a70f96", "language": "Shell", "lines": 172, "truncated": false, "block": 13, "row": 5737 }, { "path": "MEGnet/prep_inputs/cvSplits.py", "sha256": "9bfa3a2ff3139d592d705e3f73e399ecda82a2479f382624ba71c28fcec6d879", "language": "Python", "lines": 269, "truncated": false, "block": 7, "row": 1539 }, { "path": "MEGnet/prep_inputs/extras/inside_loop_testing.py", "sha256": "204b66bcbeb7dc76964f68328607a950c526ccfc61026cd4001f457f542e371f", "language": "Python", "lines": 185, "truncated": false, "block": 7, "row": 139 }, { "path": "MEGnet/prep_inputs/extras/new_train_model_modlayers.py", "sha256": "17ec2ce40a76bf0850b2e0693b7453edb8f18734dcd67c0a3568789a6eae4c51", "language": "Python", "lines": 583, "truncated": false, "block": 7, "row": 8711 }, { "path": "MEGnet/prep_inputs/extras/new_train_model_modlayers_allinfrozen.py", "sha256": "dee5c429aa857db25e769264eda9bec206bbb79f6417d6cab933424b5d5e218d", "language": "Python", "lines": 583, "truncated": false, "block": 7, "row": 8723 }, { "path": "MEGnet/prep_inputs/new_train_model.py", "sha256": "5937de118a9f9214fb83df066f6497a91c47ad3fd1a1c12458b8e72df1023460", "language": "Python", "lines": 338, "truncated": false, "block": 7, "row": 5163 }, { "path": "MEGnet/prep_inputs/new_train_model_pkl.py", "sha256": "041cc4dd84f2aba414abbfc0e1cc59db998b6199e02b9916886880257b4fc867", "language": "Python", "lines": 253, "truncated": false, "block": 12, "row": 17173 }, { "path": "MEGnet/prep_inputs/new_train_model_pkl_cmdline.py", "sha256": "66b41b3fcdd487df563c5d34ddd1eb4bb93d6d14a2821a3e1b34063a45cfbc92", "language": "Python", "lines": 138, "truncated": false, "block": 12, "row": 12584 }, { "path": "MEGnet/prep_inputs/tests/test_ica2input.py", "sha256": "8d907d38e04197c8cb819d81724b3b829a72b130f5f5af5ab411667b7a8f9019", "language": "Python", "lines": 186, "truncated": false, "block": 12, "row": 15853 }, { "path": "MEGnet/tests/test_ica_model_weights.py", "sha256": "a42203ee45890270c6f9c89b86e937d16a0fde4da301bb62f99378f26e94f6b3", "language": "Python", "lines": 89, "truncated": false, "block": 12, "row": 10107 }, { "path": "MEGnet/tests/test_megnet_init.py", "sha256": "c78e4a36382b7e0d6d35dbcab8d403f6a9c28064b882d8590120f4b9f7182ab7", "language": "Python", "lines": 55, "truncated": false, "block": 12, "row": 8479 }, { "path": "README.md", "sha256": "33fc24809396bd9d8468bf2f1323ea0028f97a77127c1c3c204a750428188776", "language": "Text", "lines": 41, "truncated": false, "block": 13, "row": 6329 } ] }