sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d45249758bb819d1432caa790713fbf077f86bb1e760f84ed6e8015c9756ddc1 | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Inverters(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/inverters",
"n_nodes": 29,
"n_edges": 33,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
d537f4801f42b1cf2ddd73fe0d623fb8563ed61fb56c56b5cd6202b32c75e66a | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Lawschool(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/lawschool",
"n_nodes": 10,
"n_edges": 21,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
d5ed9e29d57b6e4db563bb2ae67946cbd9a5eb195830d0f0c1fbb69113c0c3b7 | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Disputed1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/disputed1",
"n_nodes": 11,
"n_edges": 11,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
e8f7134f367ba86636bd0036e564390127828bed521c186033f4bafa47d33949 | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Disputed4(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/disputed4",
"n_nodes": 23,
"n_edges": 29,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
f15ff00823d8ff9416bb85916657b89bf64ab782a442913f12c209afac7737ae | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Grounding(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/grounding",
"n_nodes": 36,
"n_edges": 45,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
f86fdf3ef51478c78be91565774eb40574bfb8634b13aee6f6ae45eb0e322292 | Python | 356 | 15 | from .._base import BaseExampleModel, BIFMixin
class Ecosystem(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/ecosystem",
"n_nodes": 13,
"n_edges": 12,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
14c95299436ff27274e4f25381eaf39253d1f9983b122a3132aaa3bdf107aa0f | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Navigation(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/navigation",
"n_nodes": 4,
"n_edges": 3,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
1771615a557cc6883720c71934a8f381d4d063575ae510d709e158b846a64fb7 | Python | 357 | 20 | import sys
class ConsoleOutputRedirect:
"""Wrapper to redirect stdout or stderr"""
def __init__(self, fp):
self.fp = fp
def write(self, s):
self.fp.write(s)
def writelines(self, lines):
self.fp.writelines(lines)
def flush(self):
self.fp.flush()
stdout_redirect... |
44d3e470a7b09343193eb89f03339781ab5e16d769ea9a582c9247a92b895292 | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Pneumonia(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/pneumonia",
"n_nodes": 62,
"n_edges": 171,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
6c06942429daa763d0df8e351a091a9985fa28d386055fee2ed2977ece2fb9ba | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Enrollment(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/enrollment",
"n_nodes": 8,
"n_edges": 7,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
8ab841ed901b2ba0d0db7e5d5e7cb4ac865c1603dd7285cfced37eb1ec9f560b | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Simulation(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/simulation",
"n_nodes": 4,
"n_edges": 3,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
8ecee0b6a839e430a029fad20861dfb7c92df7a418a385585ad93d3816582e76 | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Augmenting(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/augmenting",
"n_nodes": 6,
"n_edges": 6,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
a051c7bd399b2c4d8e84678514d316dc63547373f8feadbd5c24c8eb75d093e7 | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Sallyclark(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/sallyclark",
"n_nodes": 6,
"n_edges": 5,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
b8779a3ec5183dde4d81fab5477fdb18914644ff30c18b2bf3461ff2e235506b | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Bankruptcy(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/bankruptcy",
"n_nodes": 9,
"n_edges": 8,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
d048e9683c358fd6fd01c31a1820e2cb4d59192cea2ca6e6a732a6569d8d8fba | Python | 357 | 15 | from .._base import BaseExampleModel, BIFMixin
class Compaction(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/compaction",
"n_nodes": 6,
"n_edges": 5,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
0a19c23aa1314ecd8567aca4e9f76f568a34a5fde9dae1d6740a88d2fee3696c | Python | 358 | 15 | from .._base import BaseExampleModel, BIFMixin
class Safespeeds(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/safespeeds",
"n_nodes": 9,
"n_edges": 15,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
511c61cb328f0791303374a3edb5c5a8f59a4b3779ff84b00ec61ef55e0d4614 | Python | 358 | 17 | from .._base import BaseExampleModel, DAGMixin
class Confounding(DAGMixin, BaseExampleModel):
"""
References
----------
- :footcite:t:`acid_decampos_1996`
"""
_tags = {
"name": "dagitty/confounding",
"n_nodes": 5,
"n_edges": 7,
"is_parameterized": False,
}
... |
c80de812b273cbb91943378c25fe143538a344eae214c8f60f2319a7f1b207f5 | Python | 358 | 15 | from .._base import BaseExampleModel, BIFMixin
class Crimescene(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/crimescene",
"n_nodes": 9,
"n_edges": 13,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
001af0ee20162de108ae50d322d0e5c584ad09021d088c723c166b3a7acd7863 | Python | 359 | 10 | """
Swin Transformer-Base baseline using timm.
"""
from .common import TimmClassifier
class SwinTransformerBaseClassifier(TimmClassifier):
def __init__(self, num_classes: int = 8, pretrained: bool = True, model_name: str = "swin_base_patch4_window7_224"):
super().__init__(model_name=model_name, num_class... |
18ac7caeff38a985ab1127d44ab2b2d9885ec0bb23ec174b1fc616c0b3ec4d4d | Python | 359 | 16 | import torch
def get_default() -> str:
"""Get default `accelerator` for :class:`lightning.pytorch.Trainer`.
Returns
-------
accelerator : str
Will be ``'gpu'`` if :func:`torch.cuda.is_available`
is ``True``, and ``'cpu'`` if not.
"""
if torch.cuda.is_available():
retur... |
1dbc94c06155ab8731344123c36086b056c20a1df60bf89abe379057803a4775 | Python | 359 | 16 | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
def main():
for line in sys.stdin:
print(line.replace(" ", "").replace("|", " ").strip())
... |
39a8e01f00f344b20f2c481e7990d87d48a6e48fe3ed441360291271640f2805 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Resilience(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/resilience",
"n_nodes": 36,
"n_edges": 52,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
690035668aedd94ea319fb548f86f517715b66e70fff883aa0fe841d299625f2 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Volleyball(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/volleyball",
"n_nodes": 14,
"n_edges": 18,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
71240ea607cbb0e2a76a10a42b14edb38ba6940c53038f3b0feb7793e97dfa12 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Tastingtea(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/tastingtea",
"n_nodes": 17,
"n_edges": 72,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
7e070cdc40584435bad3be3971d319848b78865cd8b18c4823057980ac573099 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Charleston(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/charleston",
"n_nodes": 24,
"n_edges": 35,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
93a2a309d739890f664cdbd52cb1e396db0b0003191c6d47e6adb7a890072810 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Earthquake(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/earthquake",
"n_nodes": 40,
"n_edges": 77,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
c99ea43f0db4f38829149ba34a00dc0255259d82dabd48f7b5fc17b506ee623c | Python | 359 | 6 | """Dynamic segmentation with CID attribution (extends dynamic_segmentation)."""
from tasks.dynamic_segmentation_CID.dynamic_segmentation_CID_task import DynamicSegmentationCIDTask
from tasks.dynamic_segmentation_CID.run_CID import run_dynamic_segmentation_CID_training
__all__ = ["DynamicSegmentationCIDTask", "ru... |
e3419af4aa1dc6ac6232e4bf08008c4ddedf9610c7504ab84f26b1fb665febe1 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Blockchain(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/blockchain",
"n_nodes": 12,
"n_edges": 13,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
e4e6792b46d22acc0614c6cf780b0f002c8eae3f0af248f568bec210ffff3f80 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Propellant(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/propellant",
"n_nodes": 49,
"n_edges": 48,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
f4e9b62ef72069d247348c00b7cc7852019e1d6fe7735c790b8273115deff8d9 | Python | 359 | 15 | from .._base import BaseExampleModel, BIFMixin
class Megacities(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/megacities",
"n_nodes": 18,
"n_edges": 17,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
fdfcdec6395a02e3c19dad0211db43deaaacca18f9c39f04335c9b0318dc66d7 | Python | 359 | 16 | from pgmpy.datasets._base import BaseCovarianceDataset
class Goldberg(BaseCovarianceDataset):
_tags = {
"name": "goldberg",
"n_variables": 6,
"n_samples": 645,
"is_continuous": True,
}
base_url = "real/goldberg"
data_url = "data/goldberg.cov.txt"
ground_truth_url ... |
070ef9b33000ad58b8bdd93511b28391ab2882c597f5f4c9da20e90f18148369 | Python | 360 | 11 | from ._de_utils import adjusted_nearest_neighbors
from ._marker_classifier import _gaussian_process_classifier
from ._niche_de_core import _niche_de_core
from ._results_dataclass import DifferentialExpressionResults
__all__ = [
"_niche_de_core",
"adjusted_nearest_neighbors",
"_gaussian_process_classifier",... |
138da62765e76e7776d894ca6777e7c509e5711d615538cc681fff7e9b9b96e1 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Medicaltest(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/medicaltest",
"n_nodes": 3,
"n_edges": 2,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
1dd354e36922c7021715dcf44175264acd84153264815676b86d06b249ca6342 | Python | 360 | 12 | """Testing End 2 End."""
from pathlib import Path
from moosez import moose
data = Path(__file__).parent / "data"
def test_basic_e2e(tmp_path) -> None:
min_ct_throat = data / "CT_enhance_pet_1446_neck_slice.nii.gz"
moose(input_data=str(min_ct_throat),
model_names="clin_ct_organs",
output_di... |
205e4502c53d49f1ccbd0a83f315c028453294ab1723d40f3f4b7d8bfa79f7d5 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Salmonella1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/salmonella1",
"n_nodes": 7,
"n_edges": 5,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
2fe049a896e540d9c452550bfc73ab14b9c0fb9e0cdd02986acfcc769ad75de1 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Algorithms3(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/algorithms3",
"n_nodes": 4,
"n_edges": 3,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
503c47b089e52df08551f1114c0fcd0b39240f27db6ee8d4af94d2f2f48be061 | Python | 360 | 15 | from .._base import BaseExampleModel, ContinuousMixin
class Algal2(ContinuousMixin, BaseExampleModel):
_tags = {
"name": "bnrep/algal2",
"n_nodes": 9,
"n_edges": 9,
"is_parameterized": True,
"is_discrete": False,
"is_continuous": True,
"is_hybrid": False,
... |
79a824706b48b6f75e52d587381afba1728ae875d6dc4aa12a182a5fb071aaf4 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Phdarticles(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/phdarticles",
"n_nodes": 6,
"n_edges": 4,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
99bdf22ea9897e830beec86f4b8980df88706873ee921c0f799aeac47b379460 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Onlinerisk(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/onlinerisk",
"n_nodes": 84,
"n_edges": 109,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}... |
a048a94d6754a9b17648d938b98cae1d3166120551c7a3496dab90b297e7fc9a | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Rockquality(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/rockquality",
"n_nodes": 9,
"n_edges": 8,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
a2a18e5385fabdc48833a996b1b1aaaba59c06d94dfd2f995b3bb0569b8a0cc2 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Algorithms4(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/algorithms4",
"n_nodes": 4,
"n_edges": 4,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
a80e1440f8f53613f27a4ebb455e5f8f6afbeb1f88ae3c78c1a22f6200d3c9a0 | Python | 360 | 17 | from .._base import BaseExampleModel, DAGMixin
class Thoemmes2013(DAGMixin, BaseExampleModel):
"""
References
----------
- :footcite:t:`thoemmes_2013`
"""
_tags = {
"name": "dagitty/thoemmes_2013",
"n_nodes": 13,
"n_edges": 14,
"is_parameterized": False,
}
... |
a872b178d6d578c8b0fbdba2900ea5bbf14bc4902737818d964e17eec39156c6 | Python | 360 | 15 | from .._base import BaseExampleModel, BIFMixin
class Fundraising(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/fundraising",
"n_nodes": 8,
"n_edges": 8,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}
... |
5549ec002f0a207b01155b659194cc5683fc0bd0eb04e7a5a209c977981189d2 | Python | 361 | 18 | from pgmpy.datasets._base import BaseCovarianceDataset
class Dropouts(BaseCovarianceDataset):
_tags = {
"name": "dropouts",
"n_variables": 8,
"n_samples": 159,
"is_continuous": True,
}
base_url = "real/dropouts"
data_url = "data/dropouts.cov.txt"
ground_truth_url... |
9a5ba2455863a8e2677091dc8e02de02abe20bc49600c7135c1e7030019982a7 | Python | 361 | 15 | from .._base import BaseExampleModel, BIFMixin
class Gonorrhoeae(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/gonorrhoeae",
"n_nodes": 10,
"n_edges": 9,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
}... |
9d65ee19cb67ca9921bfa58dd9cd3ccc047df25329eee3aa01be74f520949fba | Python | 361 | 10 | from typing import NamedTuple
class _DRVI_MODULE_KEYS(NamedTuple):
# per-split decoder scale logits before aggregation, consumed by the interpretability mixin.
# Value is a tensor of shape ``(*, n_split, n_genes)`` in inspect mode, else ``None``.
PX_UNAGGREGATED_PARAMS_KEY: str = "px_unaggregated_params"
... |
d02a783d8ec44ffde216331e7c15a62207a204f6e6c94127b6adb15e9e28a308 | Python | 361 | 9 | try:
from beartype.claw import beartype_this_package
except ModuleNotFoundError:
# `beartype` is declared by no runtime dependency of this package — it is
# a dev-group extra of the root project, which is the only reason these
# scripts ever imported. The claw is an enhancement, not a precondition.
... |
d264ee456be03257e05cf293bdef459a52eb48f07d8891ddb3a168bd50ca08cc | Python | 361 | 6 | from ._base import BaseGraphicalIdentification, BaseFormulaIdentification # isort: skip # noqa: E402
from .adjustment import Adjustment
from .frontdoor import Frontdoor
from .probability_expression import ProbabilityExpressionTree
__all__ = ["BaseGraphicalIdentification", "BaseFormulaIdentification", "Adjustment", "... |
eba8feddb9e858eb4ded654bf303de484c9732b2a58ebff179828365b80e2d58 | Python | 361 | 12 | """
Cell type specific gene selection.
"""
import numpy as np
import pandas as pd
import scanpy as sc
def ctg(adata_sc, cluster_label):
sc.tl.rank_genes_groups(adata_sc, groupby=cluster_label, use_raw=False)
markers_df = pd.DataFrame(adata_sc.uns["rank_genes_groups"]["names"]).iloc[0:150, :]
return list(n... |
eeb57fa0f802c815ffef05c1f38e99fca1842caea3e231d56b98972ed9ae51be | Python | 361 | 10 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .wav2vec import * # noqa
from .wav2vec2 import * # noqa
from .wav2vec2_asr import * # noqa
from .wav2vec2_laser import * # noqa
from ... |
049c08445233919a42c686a0f69567e82b8086519d137da80c0eb11d6be19d04 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Ropesegment(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/ropesegment",
"n_nodes": 11,
"n_edges": 10,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
08738cd6dab29e0a67a4d9a574ba3a93102066f771adc4c5d7002c48486cbcad | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class GDIpathway1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/GDIpathway1",
"n_nodes": 28,
"n_edges": 31,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
1521f62cb3f95c79653cc4751c2ce876cefec2b6e71229f2294e83f438583ffb | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class GDIpathway2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/GDIpathway2",
"n_nodes": 28,
"n_edges": 31,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
1cddd2ff90788a1914e6b8db318ec02405b1bfd32954846b811d81a08ae448be | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Realestate1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/realestate1",
"n_nodes": 27,
"n_edges": 77,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
2c8ae80d2a906a0b017f98aec37704031927528b3d05c88f8f772a31297609a7 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Kosterhavet(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/kosterhavet",
"n_nodes": 38,
"n_edges": 63,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
3074d9f55905f0c4d57dc52f6b400060f99def2c4550f3762984acb2190a7d5b | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Greencredit(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/greencredit",
"n_nodes": 10,
"n_edges": 12,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
336a24119cb452b82309593a8d0f4476f0b3113c8b481d11692591f0c1321b8e | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Polymorphic(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/polymorphic",
"n_nodes": 22,
"n_edges": 21,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
5aae0a1952ba30769731b035c9ffa5af1816b92f78c4c543976792db2a2d9db2 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Salmonella2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/salmonella2",
"n_nodes": 10,
"n_edges": 10,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
6153b037e55af034c735752d8db08d89d7809e1484bb167672fbbeba11b23d0e | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class BOPfailure2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/BOPfailure2",
"n_nodes": 46,
"n_edges": 45,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
6fb9f94387afdadda1bf1d80ee9a72a45fbbacb70db24635e0de33f583f60389 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Macrophytes(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/macrophytes",
"n_nodes": 15,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
7fd5220b2ced9ec0591f307772ffa6fef92d1f923f6c31098e0a987eede918f9 | Python | 362 | 15 | from .._base import BaseExampleModel, ContinuousMixin
class Stocks(ContinuousMixin, BaseExampleModel):
_tags = {
"name": "bnrep/stocks",
"n_nodes": 13,
"n_edges": 23,
"is_parameterized": True,
"is_discrete": False,
"is_continuous": True,
"is_hybrid": False,
... |
b996d93354d7b3457cdeefe85f51595f71370ea83f9cad427b90f1aa6f739630 | Python | 362 | 12 | from __future__ import annotations
from pathlib import Path
from typing import Any
def build(setup_kwargs: dict[str, Any]):
assert setup_kwargs["name"] == "extended-project"
assert setup_kwargs["version"] == "1.2.3"
dynamic_module = Path(__file__).parent / "extended_project" / "built.py"
dynamic_mod... |
b9a62f1b7293e5b30e43364288295baf2cf0c6fb5a6ae52c50a826e190b9999c | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Realestate2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/realestate2",
"n_nodes": 27,
"n_edges": 81,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
b9f0306dae9e749c53b58b4a33acb2d39ca68d7b7b06488edae2d775241c0ce5 | Python | 362 | 19 | """Module providing utilities for brenda_references"""
from .utils import (
CachingMiddleware,
abbreviate_bacteria,
entities_in_dataset,
fuzzy_find_all,
jaccard_similarity,
ratio,
)
__all__ = [
"CachingMiddleware",
"abbreviate_bacteria",
"entities_in_dataset",
"fuzzy_find_all",... |
c5a5b9ad43ef25bd7ef1661429a7c1a91ec6d87c7ccfb8c8cf4ff118259748f1 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class Realestate3(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/realestate3",
"n_nodes": 27,
"n_edges": 69,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
c7d9dba9dba1bcd49086a674684ec75b76aeb57c665e537e0f4cb35b43dad3af | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class BOPfailure3(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/BOPfailure3",
"n_nodes": 28,
"n_edges": 27,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
eee30f2bd4712fb624a92e8d9291fa5bc9bb0b6c31e95e48f734dfd2b4b81916 | Python | 362 | 15 | from .._base import BaseExampleModel, BIFMixin
class BOPfailure1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/BOPfailure1",
"n_nodes": 30,
"n_edges": 29,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
687aaec305893cc568307ccde64e4caf513af1d234c478799018b73d740e7aba | Python | 363 | 15 | from .._base import BaseExampleModel, BIFMixin
class Tubercolosis(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/tubercolosis",
"n_nodes": 5,
"n_edges": 4,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
b40ab4cf186d57e1ee78efdbf1a916dc1c71334dfbac3013f150b3ef1b3a9e63 | Python | 363 | 15 | from .._base import BaseExampleModel, BIFMixin
class Foodallergy3(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/foodallergy3",
"n_nodes": 8,
"n_edges": 8,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
db9ca096735ca966c715681c596a4f62d6a48e221ddf0ef87a532d02763ca14e | Python | 363 | 15 | from .._base import BaseExampleModel, BIFMixin
class Foodallergy2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/foodallergy2",
"n_nodes": 8,
"n_edges": 8,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
f934d0c611fed90a20025f7b09bde3cf6135615343a79bc0744169a9d34d1107 | Python | 363 | 15 | from .._base import BaseExampleModel, BIFMixin
class Trajectories(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/trajectories",
"n_nodes": 5,
"n_edges": 9,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
484b4d039fb93750743cce88763091bd1588817e6478ddd569189a4a2ce67045 | Python | 364 | 15 | from .._base import BaseExampleModel, BIFMixin
class Foodallergy1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/foodallergy1",
"n_nodes": 8,
"n_edges": 12,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
a748a22c6f8b0b8f4206b59e0ca9958df0386b863be57f49b396f0078612b4c1 | Python | 364 | 15 | from .._base import BaseExampleModel, ContinuousMixin
class Lexical(ContinuousMixin, BaseExampleModel):
_tags = {
"name": "bnrep/lexical",
"n_nodes": 8,
"n_edges": 14,
"is_parameterized": True,
"is_discrete": False,
"is_continuous": True,
"is_hybrid": False,... |
d7a3754b54a44b0f5340904e5fef203c237c617dcb4a448240ef566bf999c094 | Python | 364 | 11 | import cv2
def sobel_cam(img):
gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
grad_x = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=3)
grad_y = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=3)
abs_grad_x = cv2.convertScaleAbs(grad_x)
abs_grad_y = cv2.convertScaleAbs(grad_y)
grad = cv2.addWeighted(abs_grad_... |
ee6bd5654ae5032eb95f5d186ebb3d3b95b2ebc0d9185ac419e62ade92e17e0b | Python | 364 | 15 | from .._base import BaseExampleModel, BIFMixin
class Windturbine(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/windturbine",
"n_nodes": 122,
"n_edges": 123,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
f57be06f58bdfadc81242796b084f1a75241a52a615cbec59d09d07b4fe9a3f3 | Python | 364 | 15 | from .._base import BaseExampleModel, BIFMixin
class Mountaingoat(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/mountaingoat",
"n_nodes": 7,
"n_edges": 12,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
180cba96cfdd2f307099021e0bf30615371d84cab9fb34e814f142e709d9ab55 | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Fingermarks2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/fingermarks2",
"n_nodes": 12,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
2f7001c036ebb07172c9afcfa2a63be17cce88cc92816b0694d1a41730d8932a | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Humanitarian(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/humanitarian",
"n_nodes": 21,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
5465e619a0a81da96f0f5a2c9585e376ecdd72b0d00ce4441b9cfbf0532c8ba6 | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Fingermarks1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/fingermarks1",
"n_nodes": 12,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
5fb7e749ca28d9225d7d2f1393035ad52a11da1b7f0568f902c2473b02c3a87d | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Nuclearwaste(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/nuclearwaste",
"n_nodes": 10,
"n_edges": 11,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
769eba6f3dff97641286f70f35dbdccfdb77c24c7f42c5ba94a507953a4d615f | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Arcticwaters(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/arcticwaters",
"n_nodes": 46,
"n_edges": 59,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
905f751760b9075402980475417d0f6ebb2314af5d369013f8ed53e97796bb46 | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Electrolysis(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/electrolysis",
"n_nodes": 16,
"n_edges": 18,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
aeb1f1c5e3184321907dace74644467fdaea2b623791c12a7fd323b38ef52297 | Python | 365 | 16 | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
def main():
for line in sys.stdin:
print(" ".join(list(line.strip().replace(" ", "|"))) + "... |
fa606760f3e45988c79ec43b839d397bcdf61ee61f4d01b35ac413e4f5c0e42d | Python | 365 | 15 | from .._base import BaseExampleModel, BIFMixin
class Gasexplosion(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/gasexplosion",
"n_nodes": 18,
"n_edges": 23,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
1249c9cb4c430163f755ae1f03a8a1fb1acf8ae3f890edd53e31f0aecd9bfafc | Python | 366 | 14 | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Legacy entry point. Use fairseq_cli/train.py or fairseq-train instead.
"""
from fairseq_cli.train import cli_mai... |
15577fd19a221b104f5ce71fcb86769514be9b5c53aa4aa2dda559b413672084 | Python | 366 | 15 | from .._base import BaseExampleModel, BIFMixin
class Perioperative(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/perioperative",
"n_nodes": 5,
"n_edges": 4,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
62c3a843a41dc45eb5627d8162f09a4b637188a20bc445e251808a1ead3a2879 | Python | 366 | 14 | METRIC_CV_CELL = "cv_cell"
METRIC_CV_GENE = "cv_gene"
METRIC_DIFF_EXP = "diff_exp"
METRIC_CALIBRATION = "calibration"
METRIC_ZERO_FRACTION = "zero_fraction"
DEFAULT_DE_N_TOP_GENES = 2
DEFAULT_DE_P_VAL_THRESHOLD = 0.001
DEFAULT_DE_N_TOP_GENES_OVERLAP = 100
DATA_VAR_RAW = "Raw"
UNS_NAME_RGG_RAW = "rank_genes_groups_ra... |
76b59c5272ba47e607846266cccfb0bca150003c89573ef862ea1e22a97b6899 | Python | 366 | 15 | from .._base import BaseExampleModel, BIFMixin
class Agropastoral5(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/agropastoral5",
"n_nodes": 5,
"n_edges": 4,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
80437e7db9d844bcdf21e0fd7a3e405102ffed294d5f297ee46e448a1778cc1a | Python | 366 | 15 | from .._base import BaseExampleModel, BIFMixin
class Twinframework(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/twinframework",
"n_nodes": 7,
"n_edges": 7,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
8ac7d2e05aac91b587dd130404d3d029c0c748e32dd3d9ed1d6c55d6b2fb97cb | Python | 366 | 15 | from .._base import BaseExampleModel, BIFMixin
class Softwarelogs1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/softwarelogs1",
"n_nodes": 5,
"n_edges": 5,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
0d8b2955c752d3118de5069486447297b4402636d3c29362b2721bf04a3b42a9 | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Agropastoral2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/agropastoral2",
"n_nodes": 11,
"n_edges": 17,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
3c1b05084f3ae9aa3a47874c370a2f4a953b628bad1df06cba59bf0c94531e4f | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Agropastoral3(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/agropastoral3",
"n_nodes": 11,
"n_edges": 15,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
4ab6ce9cca1bd3e1593544e4238d7398a84567eb639fdf4bc58c79407764a887 | Python | 368 | 15 | from .._base import BaseExampleModel, ContinuousMixin
class Turbine2(ContinuousMixin, BaseExampleModel):
_tags = {
"name": "bnrep/turbine2",
"n_nodes": 16,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": False,
"is_continuous": True,
"is_hybrid": Fal... |
5212146afa8c1a15482fdddbdc81776aeaf20bb690076dbc261690cc67fdb212 | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Airegulation2(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/airegulation2",
"n_nodes": 19,
"n_edges": 36,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
645a4ff0796db2382c47cb8a63b825c7d51fef2d3d05925e6cfa2d61137345fd | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Dustexplosion(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/dustexplosion",
"n_nodes": 26,
"n_edges": 32,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
8437b7a65363646e5ecb27e3b4b433790e4f1f89a582dc766177e9eeed1b06e7 | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Agropastoral4(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/agropastoral4",
"n_nodes": 21,
"n_edges": 14,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
84fbd0ede34705226f850248761b92628e456ec980d2a3b3884e7d860c16d878 | Python | 368 | 15 | from .._base import BaseExampleModel, ContinuousMixin
class Turbine1(ContinuousMixin, BaseExampleModel):
_tags = {
"name": "bnrep/turbine1",
"n_nodes": 16,
"n_edges": 20,
"is_parameterized": True,
"is_discrete": False,
"is_continuous": True,
"is_hybrid": Fal... |
855c0c05d29ab28b3efb25e976e3c6547ec303c1648f5cdccd531ff87d06d9ba | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Airegulation1(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/airegulation1",
"n_nodes": 22,
"n_edges": 42,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
93a77a9fbabca3742b654745b59a9c37dcf147ac71e15b5c603e78ae14f2e027 | Python | 368 | 12 | import os
from tractseg.experiments.base_legacy.peak_reg_legacy import Config as PeakRegConfig
#Name of original exp: Peaks20_12g90g270g_ALLoss
class Config(PeakRegConfig):
EXP_NAME = os.path.basename(__file__).split(".")[0]
LOSS_WEIGHT = 10
LOSS_WEIGHT_LEN = 400 # nr of epochs
CLASSES = "All" ... |
9c1d13bbf88eb06958fb4eca5dcd1b4e0d4eeb9781561e2fe4b1c25203234224 | Python | 368 | 15 | from .._base import BaseExampleModel, BIFMixin
class Softwarelogs4(BIFMixin, BaseExampleModel):
_tags = {
"name": "bnrep/softwarelogs4",
"n_nodes": 14,
"n_edges": 21,
"is_parameterized": True,
"is_discrete": True,
"is_continuous": False,
"is_hybrid": False,
... |
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