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/jaydu1/causarray",4 "url": "https://github.com/jaydu1/causarray",5 "host": "github.com",6 "commit": "14d482803af83879330625e27ed64c49a9b0b9e0",7 "license": "MIT",8 "license_confirmed_by": "license file LICENSE",9 "redistribution": "yes",10 "files": [11 {12 "path": "LICENSE",13 "sha256": "e3314494081832d2f874ab2ed00d69ef4704a3649746c1845a62457456f684d8",14 "language": "License",15 "lines": 21,16 "truncated": false,17 "block": 10,18 "row": 605919 },20 {21 "path": "README.md",22 "sha256": "9de36ac880729a6777f556cec339a9492d42fdcb3e8c1c574fce16f4f6d0e5d6",23 "language": "Text",24 "lines": 150,25 "truncated": false,26 "block": 10,27 "row": 1994728 },29 {30 "path": "causarray/DR_estimation.py",31 "sha256": "236c221853bfd712b06c4256a0c39e4d797e6ad9b9d38ec39682e1f08d2c974b",32 "language": "Python",33 "lines": 1068,34 "truncated": false,35 "block": 10,36 "row": 1749037 },38 {39 "path": "causarray/DR_inference.py",40 "sha256": "6b8f4b76545180872571e4263678d7acb586c2d9638d48c0017569f0d8c27079",41 "language": "Python",42 "lines": 201,43 "truncated": false,44 "block": 10,45 "row": 1396746 },47 {48 "path": "causarray/DR_learner.py",49 "sha256": "806accc82a7d61a699ea6fe14ed9b514d2ba60af2607412ba51f23f9602a0809",50 "language": "Python",51 "lines": 1257,52 "truncated": false,53 "block": 10,54 "row": 1759155 },56 {57 "path": "causarray/__about__.py",58 "sha256": "91447944015cec709e8aa7655f7e9d64e1e4508e7023a57fe3746911c0fc6fed",59 "language": "Python",60 "lines": 1,61 "truncated": false,62 "block": 3,63 "row": 1735264 },65 {66 "path": "causarray/__init__.py",67 "sha256": "0698867252c758322cd773da9fffe9213987aab7a5ed5ac9842d2312f752849e",68 "language": "Python",69 "lines": 43,70 "truncated": false,71 "block": 10,72 "row": 1159973 },74 {75 "path": "causarray/diagnostics.py",76 "sha256": "87b753660ff4e7e838c1910e6b1f28e0be51f3d4523dca448baa6960f9e2a050",77 "language": "Python",78 "lines": 628,79 "truncated": false,80 "block": 10,81 "row": 1698682 },83 {84 "path": "causarray/gcate.py",85 "sha256": "012ce0263e92605699d5e30c0f1c0c92a1eea0bec127cfa1fcbda70a479e9de1",86 "language": "Python",87 "lines": 646,88 "truncated": false,89 "block": 10,90 "row": 1709291 },92 {93 "path": "causarray/gcate_glm.py",94 "sha256": "d2d1671c867e3d8db46b6f835be15abc097f3d5e2678b634e15c118951d7b76f",95 "language": "Python",96 "lines": 453,97 "truncated": false,98 "block": 10,99 "row": 16419100 },101 {102 "path": "causarray/gcate_likelihood.py",103 "sha256": "91c631e31952746e953fbdbc76c2ab5fcdb339e3f61305711e9f9847f6d4d508",104 "language": "Python",105 "lines": 279,106 "truncated": false,107 "block": 10,108 "row": 15409109 },110 {111 "path": "causarray/gcate_opt.py",112 "sha256": "7ed49bea741cfc407ece570f7de5cb388124750ac6baf18708596789349cf062",113 "language": "Python",114 "lines": 461,115 "truncated": false,116 "block": 10,117 "row": 16587118 },119 {120 "path": "causarray/nb_glm_fast.py",121 "sha256": "4e449043de702c73ef06fd73dc23b12308f1dc4814ac37aa05e168f30559c482",122 "language": "Python",123 "lines": 506,124 "truncated": false,125 "block": 10,126 "row": 16588127 },128 {129 "path": "causarray/utils.py",130 "sha256": "a669eba1c4e2c8ad204bed66a37bf10db4d4a6d8801940bd2d887a6863426aa7",131 "language": "Python",132 "lines": 339,133 "truncated": false,134 "block": 10,135 "row": 15503136 },137 {138 "path": "docs/source/conf.py",139 "sha256": "c24e86f42e725d84a662bbf09bb248f0cf453488218d2bb311d154766b13f8c2",140 "language": "Python",141 "lines": 180,142 "truncated": false,143 "block": 10,144 "row": 14147145 },146 {147 "path": "docs/source/tutorial/SCARF/SCARF-py.ipynb",148 "sha256": "bc6ef5233eb0781d63310ee7bfb13b07cf39a23a2fdc49149413986e3cbd3d05",149 "language": "Jupyter",150 "lines": 1154,151 "truncated": false,152 "block": 10,153 "row": 5943154 },155 {156 "path": "docs/source/tutorial/SCARF/prep_scarf_data.py",157 "sha256": "db3617241800d068d473331ae1c91a8ec1e1d61825471aa9f31000c9faf749e4",158 "language": "Python",159 "lines": 125,160 "truncated": false,161 "block": 10,162 "row": 14152163 },164 {165 "path": "docs/source/tutorial/case_control/1_preprocess_sea_ad.py",166 "sha256": "170d62b0554788c463d4856c01f735912eea69fb37e27ea45a3464a65e9d054c",167 "language": "Python",168 "lines": 176,169 "truncated": false,170 "block": 10,171 "row": 14654172 },173 {174 "path": "docs/source/tutorial/case_control/sea_ad_case_control.ipynb",175 "sha256": "0055964083135ee103404a5268c184cfa54e65ae990bf2998e8e05ca3c6acf29",176 "language": "Jupyter",177 "lines": 263,178 "truncated": false,179 "block": 10,180 "row": 5630181 },182 {183 "path": "docs/source/tutorial/perturbseq/perturbseq-py.ipynb",184 "sha256": "8c597aaaba70917a11f5f2ee3bf37cff5917412420e3f3f823e001442b68311e",185 "language": "Jupyter",186 "lines": 334,187 "truncated": false,188 "block": 10,189 "row": 5759190 },191 {192 "path": "docs/source/tutorial/perturbseq/perturbseq-r.Rmd",193 "sha256": "eb0a09802bd24fda0113e99ed66d951bee470ea4d49733670160a2866e591240",194 "language": "R",195 "lines": 393,196 "truncated": false,197 "block": 10,198 "row": 18817199 },200 {201 "path": "docs/source/tutorial/replogle/1_prep_tutorial_data.py",202 "sha256": "004b81fcd21580b9ec504ba0832c62352a1a79927c189ce3ec987664970629f6",203 "language": "Python",204 "lines": 184,205 "truncated": false,206 "block": 10,207 "row": 14886208 },209 {210 "path": "docs/source/tutorial/replogle/2_estimate_r.py",211 "sha256": "b1d642db1b570a6dba98892896572dc1d5f8d4201fdfbb55a63e38defdfad0ac",212 "language": "Python",213 "lines": 21,214 "truncated": false,215 "block": 10,216 "row": 11112217 },218 {219 "path": "docs/source/tutorial/replogle/3_run_batch.py",220 "sha256": "61fcc81dc87cb53676ca2276de4e70ff3392c1bf9292a49b98e402f598d34133",221 "language": "Python",222 "lines": 35,223 "truncated": false,224 "block": 10,225 "row": 11745226 },227 {228 "path": "docs/source/tutorial/replogle/4_cache_propensity_batch.py",229 "sha256": "a5f078f12088f8da0d909d1b4e7b1a07a0e2ea8dc76f19c954b4aa65e5ed0298",230 "language": "Python",231 "lines": 422,232 "truncated": false,233 "block": 10,234 "row": 16413235 },236 {237 "path": "docs/source/tutorial/replogle/5_refit_propensity.py",238 "sha256": "f5ccf0c57f903464dba71aa9772c38a1e238720c90bd3e5d8138e4cddfc2f0bc",239 "language": "Python",240 "lines": 140,241 "truncated": false,242 "block": 10,243 "row": 14721244 },245 {246 "path": "docs/source/tutorial/replogle/replogle-py.ipynb",247 "sha256": "5cf26be95bab82f9b1dc18b586667b2209fbd47c5133b19bc97d552d31d3e086",248 "language": "Jupyter",249 "lines": 639,250 "truncated": false,251 "block": 10,252 "row": 5874253 },254 {255 "path": "paper/AD/GO.R",256 "sha256": "965dcb2b0b5169a49b93e66cee82382384a59ae1bdcb32086874acd847ffe882",257 "language": "R",258 "lines": 81,259 "truncated": false,260 "block": 10,261 "row": 18277262 },263 {264 "path": "paper/AD/Plot.ipynb",265 "sha256": "0f9945201c9bbd7d344a6901e49693b6742aee5cb468fd1d46e26208efebb146",266 "language": "Jupyter",267 "lines": 528,268 "truncated": false,269 "block": 10,270 "row": 5798271 },272 {273 "path": "paper/ROSMAP-AD/1-preprocess.R",274 "sha256": "0ea0a447d5725c5f7eac60d902f610ac100175870de09f618bd7bfe58c5f1212",275 "language": "R",276 "lines": 157,277 "truncated": false,278 "block": 10,279 "row": 18405280 },281 {282 "path": "paper/ROSMAP-AD/1-preprocess.ipynb",283 "sha256": "6a7f5f04f76554063dca5a4a4281548a03d43cbc50807c4ed6ec9ee302bca21e",284 "language": "Jupyter",285 "lines": 160,286 "truncated": false,287 "block": 10,288 "row": 5222289 },290 {291 "path": "paper/ROSMAP-AD/2-DE.R",292 "sha256": "b0158aad8cab1829e60c9aab26112931706b30d5ddb4e70e82505d44147284e6",293 "language": "R",294 "lines": 180,295 "truncated": false,296 "block": 10,297 "row": 18508298 },299 {300 "path": "paper/ROSMAP-AD/3-GO.R",301 "sha256": "ad568801d7e31457ce4791bdc4ae8fc0f810b7e0fdaa62a87251576d7a720f78",302 "language": "R",303 "lines": 168,304 "truncated": false,305 "block": 10,306 "row": 18516307 },308 {309 "path": "paper/ROSMAP-AD/4-CATE.py",310 "sha256": "c70b9e0fba016d114c34038154ca5ef6db990ed430ccf1d7bb31011799326df3",311 "language": "Python",312 "lines": 99,313 "truncated": false,314 "block": 10,315 "row": 12556316 },317 {318 "path": "paper/ROSMAP-AD/run.sh",319 "sha256": "6b4954f2fed755851c6caaa8cf59227cc59bd64c561b7b5e1c14bad1d4130c8e",320 "language": "Shell",321 "lines": 14,322 "truncated": false,323 "block": 10,324 "row": 19118325 },326 {327 "path": "paper/SEA-AD/1-preprocess.R",328 "sha256": "1e337cb6c445c46924ef706e0ff48489c32b2d28ab7ff14c19ec72168d6ec23c",329 "language": "R",330 "lines": 67,331 "truncated": false,332 "block": 10,333 "row": 18125334 },335 {336 "path": "paper/SEA-AD/1-preprocess.py",337 "sha256": "12b992f24c67a122809331bd23855c54c6dede796670b3c79f4156e0263fbde8",338 "language": "Python",339 "lines": 144,340 "truncated": false,341 "block": 10,342 "row": 13226343 },344 {345 "path": "paper/SEA-AD/2-DE.R",346 "sha256": "f1eeffacae76efb2e0d1ee73574dcc2f6d1ddf75dab7faafc8f31beae0863e57",347 "language": "R",348 "lines": 199,349 "truncated": false,350 "block": 10,351 "row": 18558352 },353 {354 "path": "paper/SEA-AD/3-GO.R",355 "sha256": "72184dc1d196fb292730fe31186fef3e3c028ac0038058dd097cda448dd1d075",356 "language": "R",357 "lines": 180,358 "truncated": false,359 "block": 10,360 "row": 18535361 },362 {363 "path": "paper/SEA-AD/run.sh",364 "sha256": "8ae065bf0a6c7dd4c6ca3e86064f35abd5ed592c697dc7dfc488d60748b3659b",365 "language": "Shell",366 "lines": 17,367 "truncated": false,368 "block": 10,369 "row": 19225370 },371 {372 "path": "paper/methods/R_functions.R",373 "sha256": "122e7906ed53bf2327b16fa1cd1ad983d0a85bf9beab5de480c9b4d41b1f3ec0",374 "language": "R",375 "lines": 576,376 "truncated": false,377 "block": 10,378 "row": 18832379 },380 {381 "path": "paper/methods/causarray/DR_estimation.py",382 "sha256": "b4f01281293a210c16c738c23568a42e8ef4d9250805475fa45409d6a8cd4c49",383 "language": "Python",384 "lines": 330,385 "truncated": false,386 "block": 10,387 "row": 15707388 },389 {390 "path": "paper/methods/causarray/DR_inference.py",391 "sha256": "abf14828d646ac3bf5524bffbc7dc1a7a67422ce26b5ab3011efbf18a9d9e82b",392 "language": "Python",393 "lines": 195,394 "truncated": false,395 "block": 10,396 "row": 13818397 },398 {399 "path": "paper/methods/causarray/DR_learner.py",400 "sha256": "701fce20949a0d51975b6f5b5f5f2da3387c7d2d3f5ca1ae3fa77faa1c23ea14",401 "language": "Python",402 "lines": 324,403 "truncated": false,404 "block": 10,405 "row": 15596406 },407 {408 "path": "paper/methods/causarray/__about__.py",409 "sha256": "d66a6d13342285b772aaaccc81d9ecfe3e5918af60cfb851d9bb2003f4e78cee",410 "language": "Python",411 "lines": 1,412 "truncated": false,413 "block": 10,414 "row": 9603415 },416 {417 "path": "paper/methods/causarray/__init__.py",418 "sha256": "6d3c82cfd118dcd55c7056f8ef6c3b82a331ae689d06cc4766396c7cc6b03ec9",419 "language": "Python",420 "lines": 21,421 "truncated": false,422 "block": 10,423 "row": 10406424 },425 {426 "path": "paper/methods/causarray/gcate.py",427 "sha256": "a0e46ef650ef53a0067f75b961bbfd58cfa5381925cb06797008b428a6dc710c",428 "language": "Python",429 "lines": 246,430 "truncated": false,431 "block": 10,432 "row": 15175433 },434 {435 "path": "paper/methods/causarray/gcate_glm.py",436 "sha256": "862f5ffbb1f72d9ed4eccbdf1943e97bf7d7134f584a813e69401b91bf648dbe",437 "language": "Python",438 "lines": 266,439 "truncated": false,440 "block": 10,441 "row": 15237442 },443 {444 "path": "paper/methods/causarray/gcate_likelihood.py",445 "sha256": "b2bb36aa5dae121827dfceb0d65112e3513f19bd042874f9603216fb6e580de7",446 "language": "Python",447 "lines": 143,448 "truncated": false,449 "block": 10,450 "row": 13644451 },452 {453 "path": "paper/methods/causarray/gcate_opt.py",454 "sha256": "de5c45bee503a417408406a98c12f6413cef755c1fc384fd0f6eca624c26f2fa",455 "language": "Python",456 "lines": 294,457 "truncated": false,458 "block": 10,459 "row": 15494460 },461 {462 "path": "paper/methods/causarray/utils.py",463 "sha256": "11ed01ebae84b381b46bc21e378d29097ab4e338a963435bf9acdce106efd74f",464 "language": "Python",465 "lines": 246,466 "truncated": false,467 "block": 10,468 "row": 14546469 },470 {471 "path": "paper/methods/cinemaot.py",472 "sha256": "906379c420f698186473d7f9407b3153cb0b3392a5166c190aa32dc2724df0fa",473 "language": "Python",474 "lines": 136,475 "truncated": false,476 "block": 10,477 "row": 13505478 },479 {480 "path": "paper/methods/cinemaot/__init__.py",481 "sha256": "c883a2f2effc5c8966d8ced740ea925dbbf2c2f8cb3568e475a0930010061e92",482 "language": "Python",483 "lines": 3,484 "truncated": false,485 "block": 10,486 "row": 9855487 },488 {489 "path": "paper/methods/cinemaot/benchmark.py",490 "sha256": "3e4be01de4ff7b999891af2f92fa4159c8c8bc34292bcb796bf8605677269ab4",491 "language": "Python",492 "lines": 293,493 "truncated": false,494 "block": 10,495 "row": 15684496 },497 {498 "path": "paper/methods/cinemaot/cinemaot.py",499 "sha256": "5b6e67f79b033bf3f3d4d88a9692b20dac434c898b7655555bd94dc46cf9e4a1",500 "language": "Python",501 "lines": 545,502 "truncated": false,503 "block": 10,504 "row": 16967505 },506 {507 "path": "paper/methods/cinemaot/sinkhorn_knopp.py",508 "sha256": "5ff271280dda8da950c701f3b242edddfd8ea68ede59800c49c7cce951124595",509 "language": "Python",510 "lines": 171,511 "truncated": false,512 "block": 10,513 "row": 13877514 },515 {516 "path": "paper/methods/cinemaot/utils.py",517 "sha256": "4fe9dc36c110e5acec3cee795031d3b44b3588906957d37af099a3f19498464c",518 "language": "Python",519 "lines": 286,520 "truncated": false,521 "block": 10,522 "row": 16084523 },524 {525 "path": "paper/methods/metrics.py",526 "sha256": "a1451883b27102815cb0dfcf5c4403e1f395eac21bc0b96c270ce0a0aaf320ab",527 "language": "Python",528 "lines": 307,529 "truncated": false,530 "block": 10,531 "row": 15463532 },533 {534 "path": "paper/perturbseq/1-preprocess.R",535 "sha256": "05366257701506222bc5ab86fd0478f39d86bb703453dac56d09f0f59bb31b7b",536 "language": "R",537 "lines": 14,538 "truncated": false,539 "block": 10,540 "row": 17877541 },542 {543 "path": "paper/perturbseq/2-DE.R",544 "sha256": "1fb555348f5b23c0bd188fe9c03d93977920fa99e999293e63b73987f89d9f6d",545 "language": "R",546 "lines": 197,547 "truncated": false,548 "block": 10,549 "row": 18522550 },551 {552 "path": "paper/perturbseq/3-GO.R",553 "sha256": "d3b711f87f77529b7abc993f3989ce29237406692ec831568926bf2ec2dbc8bb",554 "language": "R",555 "lines": 225,556 "truncated": false,557 "block": 10,558 "row": 18578559 },560 {561 "path": "paper/perturbseq/Plot.ipynb",562 "sha256": "ab79b011696d258f675519747858c233323d9fdd121cab442dd43753d7af9283",563 "language": "Jupyter",564 "lines": 432,565 "truncated": false,566 "block": 10,567 "row": 5742568 },569 {570 "path": "paper/perturbseq/run.sh",571 "sha256": "a07516f3cd09d3e5806c97222c276881f12e9fd8f26c97751653d81d1189bdef",572 "language": "Shell",573 "lines": 11,574 "truncated": false,575 "block": 10,576 "row": 19053577 },578 {579 "path": "paper/simu_nb/Plot.ipynb",580 "sha256": "58deb72b1b8a9fed806c9cdf532f7ccbb312c95334f4906f3567f5fdd6c61560",581 "language": "Jupyter",582 "lines": 246,583 "truncated": false,584 "block": 10,585 "row": 5565586 },587 {588 "path": "paper/simu_nb/simu_nb.sh",589 "sha256": "48abbd8bb4333b2334583aadac7c4e9a3fcc602523dcda04620e2f216b5801f5",590 "language": "Shell",591 "lines": 13,592 "truncated": false,593 "block": 10,594 "row": 19160595 },596 {597 "path": "paper/simu_nb/simu_nb_data.R",598 "sha256": "b6a0f195b3756ab03bfeccde94a2b514e157d46e7b24601ab81b7141f2b81194",599 "language": "R",600 "lines": 100,601 "truncated": false,602 "block": 10,603 "row": 18275604 },605 {606 "path": "paper/simu_nb/simu_nb_fit.R",607 "sha256": "41ffc908a44add586d48c824fb1dd6a1a21683949564d9da0a377f01fd711787",608 "language": "R",609 "lines": 180,610 "truncated": false,611 "block": 10,612 "row": 18526613 },614 {615 "path": "paper/simu_nb/simu_nb_plot.py",616 "sha256": "5e1a60549620acae852a5aed9f4cc81db5e961eaf5f63f7d512e1ee25bf4b889",617 "language": "Python",618 "lines": 233,619 "truncated": false,620 "block": 10,621 "row": 15021622 },623 {624 "path": "paper/simu_poi/Plot.ipynb",625 "sha256": "5e1334abfa8bae5e2f553c356c4ced422c76ce7e6cef10eca37be24cb77300a1",626 "language": "Jupyter",627 "lines": 300,628 "truncated": false,629 "block": 10,630 "row": 5624631 },632 {633 "path": "paper/simu_poi/simu_poi.sh",634 "sha256": "a752f8fd809aec5434158287bbeb6a18fb8365922ab262b6c718bcfb37e7f8cd",635 "language": "Shell",636 "lines": 10,637 "truncated": false,638 "block": 10,639 "row": 19084640 },641 {642 "path": "paper/simu_poi/simu_poi_data.py",643 "sha256": "bc2d6740d24237c57f4b5742546942594e7f5b64555f76f06634dd5c10927f1d",644 "language": "Python",645 "lines": 176,646 "truncated": false,647 "block": 10,648 "row": 13864649 },650 {651 "path": "paper/simu_poi/simu_poi_fit.R",652 "sha256": "b909cc47da6c806a4ca9c7d18a6c6cd6807b063c0eebd593fafb5d094f8a41a1",653 "language": "R",654 "lines": 181,655 "truncated": false,656 "block": 10,657 "row": 18546658 },659 {660 "path": "paper/simu_poi/simu_poi_plot.py",661 "sha256": "e6502926dcda4cc4f82fba7dce170a0ff2bd5cbe07fbeb1831cf53775edacb4c",662 "language": "Python",663 "lines": 204,664 "truncated": false,665 "block": 10,666 "row": 14570667 },668 {669 "path": "tests/test_DR_learner.py",670 "sha256": "d817e103b3151541099ac92c920c4979d47a2d747c888435ae46c51fdae8c453",671 "language": "Python",672 "lines": 199,673 "truncated": false,674 "block": 10,675 "row": 14949676 },677 {678 "path": "tests/test_batch_fitting.py",679 "sha256": "7bf7fc0af5ee20077d711dd4c9b3412efb16a403a7c460f36daa562788e8f535",680 "language": "Python",681 "lines": 525,682 "truncated": false,683 "block": 10,684 "row": 16758685 },686 {687 "path": "tests/test_deconfounding.py",688 "sha256": "79b24b1a8160aa9d62ecd28a889370ebcc61b6b343dff3df6bf3214463add996",689 "language": "Python",690 "lines": 123,691 "truncated": false,692 "block": 10,693 "row": 13500694 },695 {696 "path": "tests/test_diagnostics.py",697 "sha256": "df6eecae8f401ab2b7fd439975242c46df122470caffcd704809039e874be11d",698 "language": "Python",699 "lines": 155,700 "truncated": false,701 "block": 10,702 "row": 13705703 },704 {705 "path": "tests/test_estimate_r.py",706 "sha256": "76e7416e6412ae00d0fe75e72b52dc43d5699410653c71ace6225726f86a1a0a",707 "language": "Python",708 "lines": 25,709 "truncated": false,710 "block": 10,711 "row": 11029712 },713 {714 "path": "tests/test_gcate.py",715 "sha256": "e88b5089a7bad69c8e7897d3e8b6c3e0f96b9c874819dd23b4ef1a64a37f9903",716 "language": "Python",717 "lines": 128,718 "truncated": false,719 "block": 10,720 "row": 13412721 },722 {723 "path": "tests/test_gcate_convergence.py",724 "sha256": "56946ebabc608eb6833650f64c8f5a5193e01dac298b6c53c80f3099eb8732b1",725 "language": "Python",726 "lines": 362,727 "truncated": false,728 "block": 10,729 "row": 16109730 },731 {732 "path": "tests/test_inference_comprehensive.py",733 "sha256": "37cdfdbbf307647ffcd5dd179790e5720f9976a41933ca4da5efcfcd5b606a27",734 "language": "Python",735 "lines": 791,736 "truncated": false,737 "block": 10,738 "row": 17337739 },740 {741 "path": "tests/test_likelihood_kernels.py",742 "sha256": "b287042413182d8bcc7a5a9bc19d1c5187d7c0a820a6cc8ed44487d15771276c",743 "language": "Python",744 "lines": 62,745 "truncated": false,746 "block": 10,747 "row": 12337748 },749 {750 "path": "tests/test_nb_glm_fast.py",751 "sha256": "21811f4c6894784011b9c5f5ef49707d9f6c41e372e589f351b9067c55649594",752 "language": "Python",753 "lines": 521,754 "truncated": false,755 "block": 10,756 "row": 16710757 },758 {759 "path": "tests/test_nb_glm_integration.py",760 "sha256": "448e8acd81408dacb1d0e35590c85304fe450e2dd9c7e3cf20ec1b8ddc7b0032",761 "language": "Python",762 "lines": 356,763 "truncated": false,764 "block": 10,765 "row": 16095766 },767 {768 "path": "tests/test_propensity.py",769 "sha256": "ca6c38c1e0622e4e33e0215339a29d61b89875b4e90a919a1dd87b7da8e407a9",770 "language": "Python",771 "lines": 687,772 "truncated": false,773 "block": 10,774 "row": 17028775 },776 {777 "path": "tests/test_review_regressions.py",778 "sha256": "e901a109a8dad92d9f1c4d5ed42402948bde0d283febd1fcbef0b6addd3ba0c6",779 "language": "Python",780 "lines": 147,781 "truncated": false,782 "block": 10,783 "row": 14232784 },785 {786 "path": "tests/test_small_arm_inference.py",787 "sha256": "9c0122b118041799766bf769758eef851243ca13957c9b30dda490d8bf4549d4",788 "language": "Python",789 "lines": 320,790 "truncated": false,791 "block": 10,792 "row": 16122793 },794 {795 "path": "tests/test_structured_glm.py",796 "sha256": "e3ab52a51540719598086016c4a476e3131892f4478a0865dea38cae7d931d4e",797 "language": "Python",798 "lines": 104,799 "truncated": false,800 "block": 10,801 "row": 13802802 }803 ]804}