sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a7db9aba1a22c23eddc4463ed14d6cad80a22c696677919459f2114336421cef | Python | 409 | 16 | '''
Python Client for MyGene.Info services
'''
# import alwayslist helper function here in case users
# still use "from mygene import alwayslist"
from biothings_client import alwayslist, get_client
__version__ = '3.2.2'
class MyGeneInfo(get_client('gene', instance=False)):
def __init__(self):
super(MyGe... |
ef8af766dada7156f5f6bda1bd05fa7315b8cba0b86ad6bb3d16e3c8f5150a1c | Python | 409 | 6 |
from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_no_specular_iteration=4'] = lambda: ModelCommitment(identifier='alexnet_no_specular_iteration=4', activations_model=get_model('... |
1d4e71070224af05637de1d266879d15725a981ef462cb867b1142aaef256ca1 | Python | 410 | 19 | import pandas as pd
split = pd.read_csv('/data2/whr/czl/TwiBot22-baselines/datasets/cresci-2015/split.csv')
user = pd.read_csv('./user_feature.csv')
user_list = list(user['id'])
del_list = []
for i,r in split.iterrows():
if r[0] not in user_list:
del_list.append(i)
print(len(del_list))
split.drop(inde... |
510ab66bafc3dfa59effebc87c556ddbbdbf2deecbe810b6c25e1e572a5698d1 | Python | 410 | 13 | from avpenet.data.audio_preprocessing import AudioPreprocessor, AudioAugmenter
from avpenet.data.visual_preprocessing import VisualPreprocessor, VisualAugmenter
from avpenet.data.dataset import PainDataset, build_dataloader, mixup_batch
__all__ = [
"AudioPreprocessor",
"AudioAugmenter",
"VisualPreprocessor... |
c3734867d4628e293b12770a5d6b93e4812bdf0969c483229683115850713570 | Python | 410 | 9 | from PUMI.utils import rpn_model
import numpy as np
clf = rpn_model(file='../data_in/rpn_model.json') # Load scikit-learn model
np.random.seed(42) # Set seed for random number generator for reproducibility
X = np.random.rand(7503, 7503) # Generate random matrix of size 7503x7503
output = clf.predict(X) # Let the ... |
c64e71d08141d20c970c18ba0a707855e71ec3aa676220dd05bd63972806e634 | Python | 410 | 19 | import pandas as pd
split = pd.read_csv('/data2/whr/czl/TwiBot22-baselines/datasets/cresci-2017/split.csv')
user = pd.read_csv('./user_feature.csv')
user_list = list(user['id'])
del_list = []
for i,r in split.iterrows():
if r[0] not in user_list:
del_list.append(i)
print(len(del_list))
split.drop(inde... |
105a49bd7ee4b12e5f2cfb02a45cf63df0018bbdd4fb871acf89166130f65522 | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p9_s1')
assert model.identifier == 'jem_imagenet_p0p9_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
3fc4f51f8c769f7bb4726423ca5dc5675328d4e7a2a8fbc668a6eb8e81b57c33 | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p1_s1')
assert model.identifier == 'jem_imagenet_p0p1_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
44f5b2747764c6fac8551072e29b401273bf4a2b5b70a670ab78ae38db089216 | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p3_s1')
assert model.identifier == 'jem_imagenet_p0p3_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
4b6a3336c7c39dd14fd426f7c338f1c90879ffb06f40f02e99c98c9980b88c58 | Python | 411 | 19 | import pandas as pd
split = pd.read_csv('/data2/whr/czl/TwiBot22-baselines/datasets/midterm-2018/split.csv')
user = pd.read_csv('./user_feature.csv')
user_list = list(user['id'])
del_list = []
for i,r in split.iterrows():
if r[0] not in user_list:
del_list.append(i)
print(len(del_list))
split.drop(ind... |
777e6bf7bac924bb4eca2b2ca26c72fa9fb889dd75c7ae192baa1daa2a833f6b | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p8_s1')
assert model.identifier == 'jem_imagenet_p0p8_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
d4627224e9c0a6831d819d58785ff187c361d5bb1d578dbd7813b7f10bae59b9 | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p5_s1')
assert model.identifier == 'jem_imagenet_p0p5_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
ef5baaf69e55533881be7c90657e1e8ae1185d096ceae77aa6fcebcf1eafcf58 | Python | 411 | 9 | from brainscore_vision import load_model
def test_load_model():
model = load_model('jem_imagenet_p0p0_s1')
assert model.identifier == 'jem_imagenet_p0p0_s1'
# Brain-Score reads 'logits' from the last registered leaf module: it must be the 1000-way classifier
activations_model = model.activations_model... |
82b09f2abba4121fa3156ae0bb2743c4d98fd65e66f8f7c24debcfa71c841dde | Python | 412 | 16 | import numpy as np
from brainscore_core import Metric
from brainscore_vision.metrics import Score
class Accuracy(Metric):
def __call__(self, source, target) -> Score:
values = source == target
center = np.mean(values)
error = np.std(values)
score = Score(center)
score.att... |
167e6aace995cd277e29cf4cd47e84604ed56d38d56ffd606f38e8ab8bae84e5 | Python | 413 | 17 | from .schnet import RANGESchNet, StandardRANGESchNet
from .painn import RANGEPaiNN, StandardRANGEPaiNN
from .so3krates import RANGESo3krates, StandardRANGESo3krates
from .mace import RANGEMACE, StandardRANGEMACE
__all__ = [
"RANGESchNet",
"RANGEPaiNN",
"RANGESo3krates",
"RANGEMACE",
"StandardRANG... |
202c17eceedc60d3ccdb6d52b5daca2f95a3a9b6376a6df7b799cb3a9ef2c0fd | Python | 413 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['Hojin_Jang_ResNet50_Strong_blur'] = lambda: ModelCommitment(identifier='Hojin_Jang_ResNet50_Strong_blur', activations_model=get_mode... |
67e288686cab43c6d182132d85da29cd0a23032454ebf1d4fafed99508d08cad | Python | 413 | 19 | #!/usr/bin/env python3
# coding: utf-8
import json
import nrn_validation as V
V.override_defaults_from_args()
# dendrite geometry: all 100 µm long, 1 µm diameter.
geom = [(0, 1), (200, 1)]
model = V.VModel()
model.add_soma(12.6157)
model.add_dendrite("dend", geom)
model.add_iclamp(5, 80, 0.3, to="dend")
data = V.r... |
98b952a5a49425874c754249d8da1898f34423d9f77445c78548005e19c4a3b6 | Python | 413 | 25 | #!/usr/bin/env python
"""
Read a MAF from standard input and print the fraction of gap columns in
each block.
usage: %prog < maf > out
"""
import sys
import bx.align.maf
def main():
for m in bx.align.maf.Reader(sys.stdin):
gaps = 0
for col in m.column_iter():
if "-" in col:
... |
996c96e458cff694691d40fba279170e902445ffb834c91f07d98957d7a6fd1b | Python | 413 | 6 |
from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_no_variation_iteration=4'] = lambda: ModelCommitment(identifier='alexnet_no_variation_iteration=4', activations_model=get_model... |
b75d7809b92b9a2aa45da6afc7983b38ee7674b764b5ff94fff07942a60842f2 | Python | 413 | 21 | import warnings
from typing import Literal
import torch_geometric
def warn(message: str) -> None:
if torch_geometric.is_compiling():
return
warnings.warn(message)
def filterwarnings(
action: Literal['default', 'error', 'ignore', 'always', 'module', 'once'],
message: str,
) -> None:
if ... |
26856d40ea80ae40bf84ee01f157092807c8c883d2445d592a67e073019c89d3 | Python | 414 | 18 | # Generated by Django 4.2.15 on 2024-12-29 19:08
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("quality_control", "0005_qualitysettings_match_empty"),
]
operations = [
migrations.RenameField(
model_name="qualitysettings",
... |
2ea7b913fd58ca9b8cf4e03dd04c72805570e0e3140f1d93b8e50c3f02cdf676 | Python | 414 | 12 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# from .sam import Sam
from .sam_model import Sam
from .image_encoder import ImageEncoderViT
from .mask_decoder import Mas... |
52733e1966466f5bc0a0897d0eda58e5aa0d0b9d533e27008b53dc63b62fb275 | Python | 414 | 13 | from analognas.search_spaces import config_space
from analognas.evaluators import XGBoostEvaluator
from analognas.search_algorithms import EAOptimizer, Worker
CS = config_space('CIFAR-10')
surrogate = XGBoostEvaluator(model_type="XGBRanker", load_weight=True)
optimizer = EAOptimizer()
worker = Worker(CS, eval=surrog... |
5fbc0a513c6af69f608238808efddca08387deaf8bd356fe98df00d17b3158ea | Python | 414 | 26 | # -*- coding: utf-8 -*-
"""TODO"""
class SyncBuffer:
"""TODO"""
def __init__(self, mpicomm):
"""TODO"""
self._mpicomm = mpicomm
def sync(self):
"""TODO"""
pass
def push(self, delay, size):
"""TODO"""
pass
def pop(self, delay, size):
"""TO... |
c7e25840caba0e3fe9ac903eed784a26becd0948196613cf804c71bf118c4515 | Python | 414 | 13 | """
get data from different dataloader
"""
import importlib
def get_data(args):
loader_name = args['dataloader']['loader_name'].lower()
# _, data_name = path.rsplit('/', maxsplit=1)
module = importlib.import_module('dataloader.' + loader_name)
data_loader = getattr(module, 'get_data_loader')
train... |
38dac17f4f8a8f112124502fae7c63a012bfc0722e14cf2e364b77ac24d3c63f | Python | 415 | 12 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from allauth.account.adapter import DefaultAccountAdapter
from django.conf import settings
from django.http import HttpResponseRedirect
class DefaultAccountAdapterEx(DefaultAccountAdapter):
def respond_email_verification_sent(self, request, use... |
451cff9984a5e5e57cf874d13683bf3e9c806b21dd4a491cb63edc26bffe22ea | Python | 415 | 14 | default_dict = {
"model": "Model",
"agegroup": "AgeGroup",
"emptystring": "",
"simulation": "Simulation",
"flowmodel": "FlowModel",
"compartmentalmodel": "CompartmentaModel",
"modelfile": "model.h",
"infectionstatefile": "infection_state.h",
"parameterspacefile": "parameter_space.h",... |
dd94552f5b1ce482102cf5b61ab0fafa5178fe756748ba3b4815b8adf68e30b0 | Python | 415 | 20 | """ Utilities used for unit tests """
import numpy as np
def return_na_check(data):
"""Helper function for tests to check if the data returned is a
numpy array and that the imputed data has no NaN's.
Parameters
----------
data: numpy.ndarray
Data to impute.
Returns
-------... |
76f71da17289de5f205402882678595f94f4a52c1b6bf0c8eb2341254d69ea77 | Python | 416 | 14 | """
get data from different dataloader
"""
import importlib
def get_data(args):
# 大写变小写
path = args['dataloader']['path'].lower()
_, data_name = path.rsplit('/', maxsplit=1)
module = importlib.import_module('dataloader.'+data_name)
data_loader = getattr(module, 'get_data_loader')
train_loader,... |
91a0349877e64de613191d3a415600805a5d1d4dff36962048d64b99fd6611e3 | Python | 417 | 22 | from __future__ import print_function
import sys,time
import sys
sys.path.append("../../")
import jieba
import jieba.posseg as pseg
jieba.enable_parallel(4)
url = sys.argv[1]
content = open(url,"rb").read()
t1 = time.time()
words = list(pseg.cut(content))
t2 = time.time()
tm_cost = t2-t1
log_f = open("1.log","w")
l... |
da9bbb4e973a8ce0e9d12df202eb470970a340703b3b2ddd1c83d7b3569dc923 | Python | 417 | 15 | import scipy
def integrate_from_min_lag_index(target, x_axis, index=0):
"""
Integrate the jacobian from the minimum lag index to the end of the lags.
"""
return scipy.integrate.simpson(target[..., index:], x=x_axis[index:], axis=-1)
def map_col(x, index, block_size=1000):
if x.startswith("g1"):
... |
df035c2611d9e5718a16e257d31208eee61da55a861517948069d7f48b5bc665 | Python | 417 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['Zejin_Lu_dvd_s_imagenet_resnet50'] = lambda: ModelCommitment(identifier='Zejin_Lu_dvd_s_imagenet_resnet50', activations_model=get_mo... |
f503be5cb7a8e2a6a0b057bac7ba13444219040fc8cd1657e077f66878b44596 | Python | 417 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['Zejin_Lu_dvd_p_imagenet_resnet50'] = lambda: ModelCommitment(identifier='Zejin_Lu_dvd_p_imagenet_resnet50', activations_model=get_mo... |
fd41fbdbd9a345e66a2bf73e8fb62bd7f1b7f74f5ceda07b09849c8c946b9d39 | Python | 417 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['Zejin_Lu_dvd_b_imagenet_resnet50'] = lambda: ModelCommitment(identifier='Zejin_Lu_dvd_b_imagenet_resnet50', activations_model=get_mo... |
009e50c957cfffc60d53a41004e2848dac97de92e8aa41d52d6479437717faa1 | Python | 418 | 19 | from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score
metrics = {
"Acc": accuracy_score,
"Pre": precision_score,
"Rec": recall_score,
"MiF": f1_score,
"AUC": roc_auc_score,
# "Auc":
}
def evaluate_on_all_metrics(y_true, y_pred):
ret = {}
f... |
4119bcb51098e6aa72966a2a8c99f2bea530fa7c11776741c8c5b51a3b892f19 | Python | 419 | 18 | # Copyright (c) OpenMMLab. All rights reserved.
def add_prefix(inputs, prefix):
"""Add prefix for dict.
Args:
inputs (dict): The input dict with str keys.
prefix (str): The prefix to add.
Returns:
dict: The dict with keys updated with ``prefix``.
"""
outputs = dict()
... |
6f9d091c722036a33eac2ae767eea2a5fdf940c6f47a5710f9b044a64067f252 | Python | 419 | 12 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from .sam import Sam
from .image_encoder import ImageEncoderViT
from .mask_decoder import MaskDecoder
from .prompt_encoder... |
9a1af58a7d90b635856127db08c02d706f53c3ca8bec717906f9576d5ab7abdc | Python | 419 | 10 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['evresnet_50_4_no_mapping'] = lambda: ModelCommitment(
identifier='evresnet_50_4_no_mapping',
activations_model=get_model('evresn... |
f34fa024931cf42a1198af2dcfdd3654f5cd9c142fa82c53e99537c8fe96c313 | Python | 419 | 18 | # Generated by Django 3.2.12 on 2022-03-14 10:51
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0051_auto_20220220_1824"),
]
operations = [
migrations.AlterField(
model_name="cloudstorage",
name="speci... |
fe0d3d63bcc44c4545abd114042b5bee6653df2ff06d16702e96b3015f1a3375 | Python | 419 | 25 | '''Zennit top-level __init__.'''
from . import attribution
from . import canonizers
from . import cmap
from . import composites
from . import core
from . import image
from . import layer
from . import rules
from . import torchvision
from . import types
__all__ = [
'attribution',
'canonizers',
'cmap',
... |
6659178dabfe904dda1d217358f76a9cb7ba160cf3b86bd32ae0e48ced19c4be | Python | 420 | 11 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from hydra import initialize_config_module
from hydra.core.global_hydra import GlobalHydra
if not GlobalHydra.instance().... |
b6fc445dec30a7a8e0cba1c7a99467c583e05703420be47c67cd3959adf48be6 | Python | 420 | 17 | # Generated by Django 4.2.6 on 2024-01-09 09:55
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0077_auto_20231121_1952"),
]
operations = [
migrations.AlterField(
model_name="cloudstorage",
name="credent... |
bd2a35beeb9e048d1d322d7b55f0a1731ffd225f77cf70745d798d8acfc773ba | Python | 420 | 10 | from .doubly_robust import AIPW, PropensityFeatureStandardization, WeightedStandardization
from .ipw import IPW
from .overlap_weights import OverlapWeights
from .standardization import Standardization, StratifiedStandardization
from .marginal_outcome import MarginalOutcomeEstimator
from .matching import Matching, Prope... |
5ab55e4f9bf302fb1fc2b501ce6504b65df3e0f12c6fa6e1d89be7df81d677e5 | Python | 421 | 6 |
from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_less_variation_iteration=1'] = lambda: ModelCommitment(identifier='alexnet_less_variation_iteration=1', activations_model=get_m... |
bb243bae4fcd5b49f194efcedb720050dd89f3d721b85cf18dbdfe89332fa6f5 | Python | 421 | 21 | """# Input values dialog
A basic example of a user input dialog.
This will pause code execution until the user responds.
# { width=50% }
```python linenums="1"
from magicgui.widgets import request_values
vals = request_values(
age=int,
name={"annotation"... |
c4397f50519ea2cf31940895dd9363e6e31ee921af55e861e29eb52155a4742a | Python | 421 | 6 |
from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_less_variation_iteration=2'] = lambda: ModelCommitment(identifier='alexnet_less_variation_iteration=2', activations_model=get_m... |
d350103191b53c48af96ea960fbae22c6d9b2616ed260d7960a18016088d544a | Python | 421 | 6 |
from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['alexnet_less_variation_iteration=4'] = lambda: ModelCommitment(identifier='alexnet_less_variation_iteration=4', activations_model=get_m... |
e0bc3c44438c37e32c41162bd904c3c8c95f40e1ae8d32c72552ac24152dabc5 | Python | 421 | 9 | import os
import numpy as np
working_dir = os.path.abspath(os.path.dirname(__file__))
dirs30 = np.genfromtxt(os.path.join(working_dir, "dirs30.csv"), delimiter=",")
dirs256 = np.genfromtxt(os.path.join(working_dir, "dirs256.csv"), delimiter=",")
dirs10000 = np.genfromtxt(os.path.join(working_dir, "dirs10000.csv"), de... |
7038d930ece09c27ae536b96600af8f829c1996dcf133e4f6d6039cea940226e | Python | 422 | 13 | import subprocess
import shlex
import numpy as np
ref_reflectances = list(np.round(np.array([0.2, 0.4, 0.6]), 1))
test_reflectances = list(np.array([0.05,0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]))
command = 'blender --background --python render_testset.py --python-use-system-env ' \
f'-- --filename tes... |
301cd3df501e775d41c798a4b9bbd1bdfbcd9afb8d7efafec4fe114a4b3c42c7 | Python | 423 | 17 | #!/usr/bin/env python
"""
This is the base class for a HAL functionality. Typically these
are provided by a module to other modules that want to use some
of the hardware that the module controls.
Hazen 04/17
"""
from PyQt5 import QtCore
class HalFunctionality(QtCore.QObject):
"""
Base class for a functionali... |
51f0b0adf948666723ff069a75eff7a0667c7842b8fd746ec7f02b905c6366d9 | Python | 423 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_tiny_imagenet1k_HAND'] = lambda: ModelCommitment(
identifier='convnext_tiny_imagenet1k_HAND',
activations_model=g... |
5e2d949e5f6474d0c347672174200dc9b29cdfd4afb4a9e7fb1c3a9b1c9c763e | Python | 423 | 19 | # -*- coding: utf-8 -*-
"""TODO"""
from core.spiking_group import NodeDistributionMode, SpikingGroup
class McNeuronGroup(SpikingGroup):
"""TODO"""
def __init__(self, n, m, mode=NodeDistributionMode.AUTO):
"""TODO"""
super().__init__(n, mode)
if self.evolve_locally:
self.... |
8f5b2200f11e3cd060f80acbbbfd8d5f5d07209a0b6c2684b14763688700701f | Python | 423 | 18 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from django.apps import AppConfig
class ConsensusConfig(AppConfig):
name = "cvat.apps.consensus"
def ready(self) -> None:
from cvat.apps.iam.permissions import load_app_iam_rules
load_app_iam_rules(self)
# Requir... |
bff9deae0e42e409e9c064254dfa73f55b51d6ef8b373ce692778df9d9e71e56 | Python | 423 | 8 | from .propensity_metrics import weighted_roc_auc_error, expected_roc_auc_error
from .propensity_metrics import weighted_roc_curve_error, expected_roc_curve_error
from .propensity_metrics import ici_error
from .weight_metrics import covariate_balancing_error
from .weight_metrics import covariate_imbalance_count_error
fr... |
ce249e8f345e16ecdc3333df49f97362f51ac9b42a7a735e578bb210f97bda1d | Python | 423 | 10 | from diffxpy.stats.stats import hypergeom_test
from diffxpy.stats.stats import likelihood_ratio_test
from diffxpy.stats.stats import wald_test
from diffxpy.stats.stats import wald_test_chisq
from diffxpy.stats.stats import two_coef_z_test
from diffxpy.stats.stats import mann_whitney_u_test
from diffxpy.stats.stats impo... |
af70c3a952db59148478548caf2bae6687b8c8d7777c6f822dacebf6dbfbaa13 | Python | 424 | 15 | import torch
from .base_distance import BaseDistance
class DotProductSimilarity(BaseDistance):
def __init__(self, **kwargs):
super().__init__(is_inverted=True, **kwargs)
assert self.is_inverted
def compute_mat(self, query_emb, ref_emb):
return torch.matmul(query_emb, ref_emb.t())
... |
ebc73fa1b3a0c3342a907e41eef440b4d3af09e6d254e705cd964a6d4c8d5c09 | Python | 424 | 12 | import pytest
import brainscore_vision
@pytest.mark.travis_slow
def test_barlow_twins_custom():
model = brainscore_vision.load_model('barlow_twins_custom')
assert model.identifier == 'barlow_twins_custom'
# AssertionError: No registrations found for resnet18_random
# ⚡ master ~/vision python -m brainscore_v... |
80677b8822dba314a9303f1507faf85e6b8e83d242cfc63b9c6d49537edf5770 | Python | 425 | 16 | """# Self reference magicgui widgets
Widgets created with magicgui can reference themselves, and use the widget API.
"""
from magicgui import magicgui
@magicgui(auto_call=True, width={"max": 800, "min": 100}, x={"widget_type": "Slider"})
def function(width=400, x: int = 50):
"""Example function."""
# the wi... |
9a7eeca38ac29dda51d78f759f03b1d8c2a5f5c8f5278bcaf79ca8ad3d41f8c3 | Python | 425 | 7 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['hmax'] = lambda: ModelCommitment(identifier='hmax',
activations_model=get... |
eaae7c6573d425b227bf5453a2651f4c09f198c3c0857306b49a9cedc93a56d4 | Python | 425 | 12 | import numpy as np
yeo7_colors = np.array([[0, 0, 0, 255],
[0, 118, 14, 255],
[230, 148, 34, 255],
[205, 62, 78, 255],
[120, 18, 134, 255],
[220, 248, 164, 255],
[70, 130, 180... |
9a3958ba363d513da8a6b835bf65610ed46b3d4ed328e3518422aeb97c5544c2 | Python | 426 | 19 | #!/usr/bin/env python3
# coding: utf-8
import json
import nrn_validation as V
V.override_defaults_from_args()
# dendrite geometry: 200 µm long, diameter 1 µm to 0.4 µm.
geom = [(0, 1.0), (200, 0.4)]
model = V.VModel()
model.add_soma(12.6157)
model.add_dendrite("taper", geom)
model.add_iclamp(5, 80, 0.3, to="taper")... |
a6c9722562d5b46f19746b3326f142c5d9637e2bf6918d357807a7eceb728066 | Python | 426 | 8 |
# median ca_conc in the mitochondria for a sim, control and lemt1
ca_freq_concs = {1: [0.6889664920152534, 1.985134951642442], # 1Hz
2: [1.3935457542367056, 3.9876974385223063], # 2Hz
5: [3.5070601316523886, 10.024326115413015], # 5Hz
10: [7.009985908144186, 20.00345... |
9b3b7646055590027f8f5960c2c5ab65c00249bd0c23721a9fa82ffd0ad58206 | Python | 427 | 17 | #!/usr/bin/env python3
# This script is included in documentation. Adapt line numbers if touched.
import glob
import pandas
import seaborn
results = glob.glob("result_mpi_*.csv")
df_list = []
for result in results:
df_list.append(pandas.read_csv(result))
df = pandas.concat(df_list, ignore_index=True)
seaborn.re... |
c8d8eb649610b2d51f138481a89617a3dcb61106465121dcb1c2f23affc84c30 | Python | 427 | 15 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
from .build_sam import (
build_sam,
build_sam_vit_h,
build_sam_vit_l,
build_sam_vit_b,
sam_model_regis... |
f2ea1d13ef6d0a8e169bade9b49ed0c87860a42cc8f4db358c8724585910236d | Python | 427 | 14 | # myelinfccoupling/__init__.py
"""
Python companion library for the Myelin–FC coupling analysis.
Core modules:
- config: configuration / options
- io: loading edges/nodes tables
- model: regression + dominance analysis (global, rsn_pairs, nodewise)
- binning: myelin-binned modeling and FC–predictor correlations
... |
488ebb27a5606658b805928308f1de5ad91041c23d6116be128039e51f5ed371 | Python | 428 | 19 | import tensorflow_probability
import antspynet
import ants
t1 = ants.image_read("t1name_here.nii.gz")
t2 = ants.image_read("t2name_here.nii.gz")
t1t2 = list()
t1t2.append(t1)
t1t2.append(t2)
t1t2_probability_mask = antspynet.brain_extraction(t1t2, modality='t1t2infant', verbose=True)
t1t2_mask = ants.threshold_im... |
ccbed57e0a9016f5f5d1f766ce89b0e5532eafabc0649e9afbdfd002aa8de9f9 | Python | 429 | 12 | import unittest
import base
class Test(base.BaseScriptTest, unittest.TestCase):
command_line = "./scripts/out_to_chain.py ./test_data/epo_tests/epo_547_hs_mm_12way_mammals_65.out --chrsizes ./test_data/epo_tests/hg19.chrom.sizes ./test_data/epo_tests/mm9.chrom.sizes"
output_stdout = base.TestFile(filename=".... |
dcaada1cbcbde4fc541ab3e69354fd0df8d7ac997876096fce15e0501e227e50 | Python | 429 | 18 | from ._version import get_versions
from .matlab import import_matlab_result
from .structures import PLSInputs, PLSResults
from .types import behavioral_pls, meancentered_pls, pls_regression
__version__ = get_versions()["version"]
del get_versions
__all__ = [
"__version__",
"behavioral_pls",
"meancentered_... |
bfa34b7fc0006e3ba75828e1337e4a03cfc82860c59df45b19512348c8fcaef1 | Python | 430 | 18 | # Generated by Django 4.2.15 on 2024-11-05 14:22
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("quality_control", "0004_qualitysettings_point_size_base"),
]
operations = [
migrations.AddField(
model_name="qualitysettings",
... |
fee544d2f7d19b838eddaecca93b6850c1bade31e8c4707d0edfb4ef39f4f5a9 | Python | 430 | 17 | from setuptools import setup, find_packages
setup(
name='Energy_Landscape_Analysis',
version='0.0.1',
packages=find_packages(),
install_requires=[ #Installed automatically : https://packaging.python.org/ja/latest/discussions/install-requires-vs-requirements/
"numpy",
"matplotlib",
... |
50e07174b8dfcf232da350519c38d48937e3b12cf4f2454636d95e47b2b1a2df | Python | 431 | 19 | from typing import Literal
from argclz import argument
from .cli_model import ModelOptions
__all__ = [
'BEHAVIOR_COVARIANT',
'GLMOptions'
]
BEHAVIOR_COVARIANT = Literal['pos', 'speed', 'lick_rate', 'acceleration']
class GLMOptions(ModelOptions):
var_type: BEHAVIOR_COVARIANT = argument(
'-V', '-... |
d645a44c848d31527c352399a64ecbe9c645313ee2785a50034bcf7c5ea31181 | Python | 432 | 14 | # Copyright (C) 2021-2022 Intel Corporation
#
# SPDX-License-Identifier: MIT
from rest_framework.routers import DefaultRouter
from .views import InvitationViewSet, MembershipViewSet, OrganizationViewSet
router = DefaultRouter(trailing_slash=False)
router.register("organizations", OrganizationViewSet)
router.register... |
93d24a5fd090d578c2bf5565b96ea5ec06f6a921f4b297b6f94ec6336b998345 | Python | 433 | 13 | # If files are moved, data in the db files might have to be updated
from pathlib import Path
from benedict import benedict
folder = "//lebnas1.epfl.ch/microsc125/deep_events/data/original_data/event_data"
db_files = list(Path(folder).rglob(r'event_db.yaml'))
print(len(db_files))
for file in db_files:
db_dict = b... |
b8184c73ee448ecafa894d3183070e9a2bef0523ec141cd0e02b0bccb60e4198 | Python | 433 | 20 | # -*- coding: utf-8 -*-
"""TODO"""
simulation_timestep = 1e-3
simulation_mindelay = 8
simulation_min_distributed_size = 16
# Error codes:
# -1: Cannot write/open logger logfile.
class SimulationDelayTooSmallException(Exception):
"""TODO"""
def __init__(self, message="Axonal delay can not be shorter than ... |
595da1c8f8bcd1e5446d9b1e2e88f32a15732da63979c25f678a3a36fcaaa4bd | Python | 434 | 18 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import numpy as np
def is_current_report_data(report_data: object) -> bool:
return isinstance(report_data, dict) and "groups" in report_data
def array_safe_divide(a: np.ndarray, b: np.ndarray) -> np.ndarray:
"Scalar (element-wise) array ... |
9bcae38eddb663fc009b2da20ed60134f37edbdea6a1329a5837c166eb05efdd | Python | 434 | 13 | #!/usr/local/bin/python3
from pipeline import experiment, pupil
import logging
import datajoint as dj
## database logging code
logging.basicConfig(level=logging.ERROR)
logging.getLogger('datajoint.connection').setLevel(logging.DEBUG)
if hasattr(dj.connection, 'query_log_max_length'):
dj.connection.query_log_max_l... |
a30f573d9a4843deacc24acee7bb6c93f1509710baf9384e1680112a86cf88e5 | Python | 434 | 14 | from neuralib.util.utils import ensure_dir
from rscvp.atlas.main_roi_atlas import RoiAtlasOptions
from rscvp.util.io import RSCVP_CACHE_DIRECTORY
from rscvp.util.util_demo import run_demo
class ExampleRun(RoiAtlasOptions):
SOURCE_ROOT = ensure_dir(RSCVP_CACHE_DIRECTORY) / 'rscvp_dataset' / 'analysis' / 'hist'
... |
309ec5ef10415de83f41fadbdb31f0a8b70af2f72a10665c4b9e367de68b32e0 | Python | 435 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_tiny_imagenet1k_HAND_PS'] = lambda: ModelCommitment(
identifier='convnext_tiny_imagenet1k_HAND_PS',
activations_m... |
4b96029d71cfc2115c3d3dd7b93e4dc33ca90f816294f991619ca8a9045c0ad9 | Python | 435 | 16 | #!/usr/bin/env python
"""
Mad City Labs (voltage controlled) Z stage functionality.
Hazen 05/17
"""
import storm_control.sc_hardware.baseClasses.voltageZModule as voltageZModule
class MCLVoltageZ(voltageZModule.VoltageZ):
"""
This is a Mad City Labs stage in analog control mode.
"""
def __init__(sel... |
55e9b55ac64df5862e584dd9fb3826f7b16e0c036a727b17ca7ec7768a2e1483 | Python | 435 | 20 | # Generated by Django 2.1.3 on 2019-02-05 17:08
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("dataset_repo", "0002_auto_20190123_1305"),
]
replaces = [("git", "0003_gitdata_lfs")]
operations = [
migrations.AddField(
m... |
6101ca7d113c80079fe1cabe937bb6fc30de608e65ab0aecbf8180a663b0e371 | Python | 435 | 18 | # Copyright (c) DP Technology.
# 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 . import UnicoreDataset
class NumSamplesDataset(UnicoreDataset):
def __getitem__(self, index):
... |
890b019a84e0d1c6a67307cba670ad29a77008df37b7c789b556ae9fbabc69a1 | Python | 435 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_tiny_imagenet1k_TA_GELU'] = lambda: ModelCommitment(
identifier='convnext_tiny_imagenet1k_TA_GELU',
activations_m... |
9f17671591538159b1b87f09edf8ede57e134019debe2885d465c87cac460e53 | Python | 435 | 13 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
class GreedyAtlas(ExternalToolWrapper):
def __init__(self,binary_path= None, **kwargs):
super().__init__(binary_path, **kwargs)
def compute_deformation_fields(self,xml_file,parsed_file):
arguments=[
'-f',xml_file,... |
b62c888c607bb7f08227c6556b24604fa69bbe750b46ca9861bacbed48184c7e | Python | 435 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_tiny_imagenet1k_HANDsum'] = lambda: ModelCommitment(
identifier='convnext_tiny_imagenet1k_HANDsum',
activations_m... |
ddbe88e8b4e529be1471d3b2c02419aecc1288cb35a272e01816fafe79048c00 | Python | 435 | 9 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['convnext_tiny_imagenet1k_GELU_PS'] = lambda: ModelCommitment(
identifier='convnext_tiny_imagenet1k_GELU_PS',
activations_m... |
d3f8f7bc5fbf19a78c47f0c842e4ab7e842f90615b067fb3c880f91c0e023234 | Python | 436 | 16 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class PatchMixLoss(nn.Module):
""" Refer to models/ast.py for the code of patch mixing
"""
def __init__(self, criterion):
super().__init__()
self.criterion = criterion
def forward(self, pred, y_a, y_... |
6c9459e0b6c3c033f7d8fcd505c9a6453c69eb772f91548c7edcf988555f4f9c | Python | 437 | 22 | from scipy import stats
import numpy as np
from .base import Distribution
class Exponential(Distribution):
"""Exponential Prior.
Parameters
----------
beta : scalar or ndarray
Scale of distribution.
"""
def __init__(self, beta):
self._beta = np.asarray(beta)
self.di... |
f137a3fa4139e651af2b676cc9268a30fbd443f3dd40811bef9f445bb921f7bc | Python | 437 | 18 | """
nelpy.io
========
This is the nelpy IO module.
"""
# TODO: add file IO utils such as mkdir, getwd, load, save, glob, etc.
# also possibly have examples and support for Jagular
# also add hdf5 support, especially for pandas
from . import brian, hc3, hc11, hc18, matlab, miniscopy, neo, neuralynx
# from . import j... |
02fa914c7e9a91e69ecfaed5c0b73e16a0c1063a494c7f922e959694b4ec1190 | Python | 438 | 18 | # Generated by Django 3.2.15 on 2022-10-11 09:02
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("webhooks", "0002_alter_webhookdelivery_status_code"),
]
operations = [
migrations.AlterField(
model_name="webhookdelivery",
... |
2916fac1d491cc58f8cdc9d579a412b4ab90fa9f9672c736c43932c1bcd75e03 | Python | 439 | 17 | # Generated by Django 4.2.1 on 2023-07-26 11:22
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0074_alter_labeledimage_source_alter_labeledshape_source_and_more"),
]
operations = [
migrations.AddField(
model_name="... |
6fba82c2ee7e36b3602926ab7c4c31929b1cd55490a50dc069ea092fb2f32b0b | Python | 439 | 31 | #!/bin/env python
import numpy as np
import sys
inp = sys.argv[1]
lines = np.loadtxt(inp,dtype=int,usecols=(0,4),unpack=False)
nstates = np.max(lines[:,1])+1
index = []
for s in range(nstates):
index.append([])
for line in lines:
iframe, st = line
index[st].append(iframe)
i = 0
for idx in index:
print "... |
3ec000144676467ce752e33c7740330dadae9d878f9108e0edc923dee650ca3c | Python | 440 | 18 | import requests
def send_request(url: str, payload: list[dict]) -> list[dict]:
response = requests.post(url, json=payload)
response.raise_for_status()
return response.json()
payload = [
{
"text_output": "### Instruction: Write a short story about a robot "
"learning to feel emotions.... |
5ac8677cd91a2c3098dd4d90086873cb5c8d6631f12da22d9e58ea8b590017e3 | Python | 440 | 5 | from brainscore_vision import model_registry
from brainscore_vision.model_helpers.brain_transformation import ModelCommitment
from .model import get_model, get_layers
model_registry['deit3_base_patch16_224_fb_in22k_ft_in1k'] = lambda: ModelCommitment(identifier='deit3_base_patch16_224_fb_in22k_ft_in1k', activations_mo... |
5b78d1761928bf1e00cbb3e266a95fd9bb34ccac433fa731b9886eafa951f769 | Python | 441 | 18 | # Generated by Django 4.2.21 on 2025-06-22 11:13
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("engine", "0090_asset_content_size_data_content_size"),
]
operations = [
migrations.AddField(
model_name="profile",
... |
8d1c2177cfc385cf22ce67d3007fddb0bc9801b6526c224aadb82224fa06d9aa | Python | 441 | 12 | from sklearn.metrics import accuracy_score, roc_auc_score, f1_score, precision_score, recall_score
def metrics(y: list, pred: list):
print("ACC: {}".format(accuracy_score(y, pred)))
print("ROC: {}".format(roc_auc_score(y, pred)))
print("F1: {}".format(f1_score(y, pred)))
print("Precision: {}".format... |
f2f7ff36cb84df4bbb278d90aae0d11f2b51e56965d09261d632c0fdc383381f | Python | 441 | 9 | import os
import ClearMap.Settings as settings
filename = os.path.join(settings.ClearMapPath, 'Test/Data/ImageAnalysis/cfos-substack.tif');
import ClearMap.Visualization.Plot as plt
import ClearMap.IO as io
data = io.readData(filename, z = (0,26));
import ClearMap.ImageProcessing.BackgroundRemoval as bgr
dataBGR = bgr.... |
f93a1fe13543266d5054a0d8844194e3969432e00699ba0c9685bb5b95be8b8e | Python | 441 | 11 | """
Label preprocessing script
Converts raw labels to binary classification labels
"""
import pandas as pd
df = pd.read_csv('labels_raw.csv')
# Column name: '癫痫控制标签(1有0无)' means 'Epilepsy Control Label (1=yes, 0=no)'
# Convert: 2 -> 1 (epilepsy), others -> 0 (no epilepsy)
df['label'] = df['癫痫控制标签(1有0无)'].appl... |
faba47a6b5a15faaf945fbab1432265895f445e7d56920b5d3573d6649b41c7e | Python | 441 | 15 | #!/usr/bin/env python3
import sys,re
out=[]
in_block=False
for line in sys.stdin:
# The replacement of name: has to be done only in figure and container blocks
if line.startswith(".. figure::") or line.startswith(".. container::"):
in_block=True
elif line.strip()=="":
in_block=False
if ... |
026f68eee3c44d93e8d62268108ddae507825939259607d28c6467b8bac22df5 | Python | 442 | 19 | import requests
def send_request(url: str, payload: list[dict]) -> list[dict]:
response = requests.post(url, json=payload)
response.raise_for_status()
return response.json()
payload = [
{
"power_input": "19 3 10 11 14 3 3 4 4 9 39 27 12 5 20 20 38 39 41 61 "
"52 31 43 31",
"p... |
259ec86d2a5e6f7d338b4f248584a4ad249906a9701637e8e09970572a8f89b4 | Python | 442 | 23 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from .caching import UpdatePolicy
from .common import (
FrameAnnotations,
MediaDownloadPolicy,
MediaElement,
Sample,
UnsupportedDatasetError,
)
from .task_dataset import TaskDataset
__all__ = [
"FrameAnnotations",
"MediaD... |
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