sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
f74a3c66ab3457995d0dd5be6440263e492a6469e1702193891cbe3d60d783f7 | Python | 276 | 15 |
""" Custom layers for networks """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
import torch.nn as nn
class IdLayer(nn.Module):
""" Identity layer """
def __init__(self):
super().__init__()
def forward(self, x):
return x
|
7eb3ea064805e37df1f41943597e06801d10d94bb19505481598b0151b65d848 | Python | 278 | 7 | from .cascade_mask_rcnn_mvitv2_t_3x import model, dataloader, optimizer, lr_multiplier, train
model.backbone.bottom_up.depth = 16
model.backbone.bottom_up.last_block_indexes = (0, 2, 13, 15)
train.init_checkpoint = "detectron2://ImageNetPretrained/mvitv2/MViTv2_S_in1k.pyth"
|
d3243ee7713fc17b8ceb2ddfff52298e3fda7f2d22bd354ec405dc626991b3cd | Python | 278 | 10 | # type: ignore
__submodules__ = ["hook", "run", "args"]
# <AUTOGEN_INIT>
import lazy_loader
__getattr__, __dir__, __all__ = lazy_loader.attach_stub(__name__, __file__)
__all__ = ["ArgumentGroups", "ArgumentParserArgs", "SnakebidsConfig", "app", "hookimpl"]
# </AUTOGEN_INIT>
|
d8cb0ad8af24ffa5213135be8303913e83bb395893786d89837aa44d136e6441 | Python | 279 | 12 | """LaMAR scripts package."""
# Import main functions to make them available at package level
from lamareg.scripts.lamar import lamareg
from lamareg.scripts import synthseg, coregister, apply_warp
__all__ = [
'lamareg',
'synthseg',
'coregister',
'apply_warp',
] |
274ad14429ae4bb31c2351669b967561856d079d47db4e4567f33644ec36419e | Python | 280 | 16 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 16:45:14 2016
@author: Federico Barabas
"""
from pyqtgraph.Qt import QtGui
from ringfinder.ringFinder import Gollum
if __name__ == '__main__':
app = QtGui.QApplication([])
win = Gollum()
win.show()
app.exec_()
|
3883359dfc5b7f5bb3af82fb4fb7570be90f55d742aa2707233dca7eeced87d2 | Python | 282 | 8 | #cp ./testVersion.py $HOME/testVersion.py
#singularity exec https://depot.galaxyproject.org/singularity/python:3.9--1 "python" "./testVersion.py"
#3.9.5 | packaged by conda-forge | (default, Jun 19 2021, 00:32:32)
#[GCC 9.3.0]
#!/usr/bin/env python3
import sys
print (sys.version)
|
3a42e2eea5042be4a57520948a6df0ad024c50e2e6dab8e10a4251517709cb82 | Python | 284 | 12 | from music21 import *
import random
keyDetune = []
for i in range(0, 127):
keyDetune.append(random.randint(-30, 30))
sBach = corpus.parse('bach/bwv7.7')
sBach.show('text')
sBach[0].show('text')
#svn checkout http://music21.googlecode.com/svn/trunk/ music21-read-only |
9efa2bd756f64336b45df2062cfbd6e83dfae20cf510b3a2c5bed4d0030f366b | Python | 286 | 12 | from nilearn import plotting
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib
matplotlib.use("Agg")
# 3D surface
# requires `snakemake.input.surf`
fig = plotting.plot_surf(snakemake.input.surf, view="dorsal")
fig.savefig(snakemake.output.png)
|
23aed6b8c1dac129299a7aafa5120f0460df89224be8ab9c816a6010785e4e5d | Python | 291 | 10 | try:
import torch
except ImportError:
raise ImportError # Torch is not installed. Please install through https://pytorch.org/get-started/locally/
from .data import DataProcess
from .train import Trainer
from .predict import Predict
from .unet3d import UNet3D
from .losses import *
|
43202ed6f89114cfab910e0eb7b9fa39494c9488ab87c11547aaa38b03b703bc | Python | 291 | 6 | reads = bnp.open('F:/tk/TK9_1_22FFLLLT3_AGAGAACCTA-GGTTATGCTA_L005__1.fq.gz').read()
print(reads)
collectReads = bnp.open('Z:/Download/rnafusion/data/fastq/SRR31089076_1.fastq.gz').read()
print(reads)
gc_content = np.mean((reads.sequence == "C") | (reads.sequence == "G"))
print(gc_content)
|
621d638274b584e5653ee4c2eaf161e44e21c204627b6b5d82d71eafc7fed259 | Python | 292 | 13 | from setuptools import setup, find_packages
setup(
name='taming-transformers',
version='0.0.1',
description='Taming Transformers for High-Resolution Image Synthesis',
packages=find_packages(),
install_requires=[
'torch',
'numpy',
'tqdm',
],
)
|
b1384e975dff77c19505da0300ce9fc71fd1e2f9fc7283c393ccd58416ed91d6 | Python | 293 | 9 | from lightning.pytorch.callbacks import Callback
from chemprop.utils.registry import ClassRegistry
CallbackRegistry = ClassRegistry[Callback]()
from .interpret import MyersonExplainerCallback # noqa: E402 # avoid circular import
__all__ = ["CallbackRegistry", "MyersonExplainerCallback"]
|
fa7327dd713c7dd7a4c899074c5faf9c274c5b34ab0343e54056bf8651cc5612 | Python | 296 | 12 | from nilearn import plotting
import matplotlib.pyplot as plt
import matplotlib
matplotlib.use("Agg")
display = plotting.plot_anat(snakemake.input.flo, display_mode="ortho", dim=-0.5)
display.add_contours(snakemake.params.ref, colors="r")
display.savefig(snakemake.output.png)
display.close()
|
5d7780cf0167b00257555a760f72f019eae72d1c762e848c023764dfb2288fd1 | Python | 298 | 13 | # Module 'rand'
# Don't use unless you want compatibility with C's rand()!
import whrandom
def srand(seed):
whrandom.seed(seed%256, seed/256%256, seed/65536%256)
def rand():
return int(whrandom.random() * 32768.0) % 32768
def choice(seq):
return seq[rand() % len(seq)]
|
16b30b88cad3b197ef278aecba1175a3fe9074ecc2e85abae20942ea1026a4a9 | Python | 302 | 12 | from .registry import ClassRegistry, Factory
from .utils import EnumMapping, create_and_call_object, make_mol, parallel_execute, pretty_shape
__all__ = [
"ClassRegistry",
"Factory",
"EnumMapping",
"make_mol",
"pretty_shape",
"create_and_call_object",
"parallel_execute",
]
|
1fd696f64008166f1a0dac6d21a9a2190777bb3f83c7e19129bcafd057db7a6c | Python | 307 | 16 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 24 16:45:14 2016
@author: Federico Barabas
"""
from pyqtgraph.Qt import QtGui
from ringfinder.ringFinderDeveloper import GollumDeveloper
if __name__ == '__main__':
app = QtGui.QApplication([])
win = GollumDeveloper()
win.show()
app.exec_()
|
fb898ad9ded8561266e3e37f8e95e7f76b389c6dcf06b66fd04c85e4e8c55ed9 | Python | 308 | 11 | import math
combo = { }
for i in range(1,101):
print "%f" % ( math.fmod (100, i ) )
for j in range(1,101):
roll= i+j
#print "%d" % ( roll )
combo.setdefault( roll, 0 )
combo[roll] += 1
for n in range(2,201):
print "%d %.2f%%" % ( n, combo[n]/math.pi )
|
1bde2ecd91446bbf45e3de9bdbfbb0193d5a4044c2a491d3567779901a0e9cc3 | Python | 310 | 7 | # Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_pointrend_config
from .mask_head import PointRendMaskHead, ImplicitPointRendMaskHead
from .semantic_seg import PointRendSemSegHead
from .color_augmentation import ColorAugSSDTransform
from . import roi_heads as _ # only registration
|
8b4793d2c0a4c40a98ec7094bbce74bb7e513d6a41d727ab08e075fdc38085bd | Python | 314 | 16 | import torch
import os
import numpy as np
import random
class Config:
device = 'cuda' if torch.cuda.is_available() else 'cpu'
def seed_everything(seed):
random.seed(seed)
os.environ['PYTHONHASHSEED'] = str(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
|
fa015d248400bed81ab30a2311ee8d859cac3076cf783b5f1d289380f16a6e6d | Python | 314 | 16 | import ystockquote
ticker = 'GOOG'
start = '20080101'
end = '20080523'
data = ystockquote.get_historical_prices(ticker, start, end)
closing_prices = [x[4] for x in data][1:]
closing_prices.reverse()
fh = open('data.txt', 'w')
for closing_price in closing_prices:
fh.write(closing_price + '\n')
fh.close()
|
064802ec0564913a840f4274450ab74d97eaef81d7b28f40b37918e7e4c1f774 | Python | 315 | 10 | try:
import torch
except ImportError:
raise ImportError # Torch is not installed. Please install through https://pytorch.org/get-started/locally/
from .data import DataProcess
from .train import Trainer
from .predict import Predict
from .multi_output_unet3d import MultiOutputUnet3D
from .losses import *
|
02b8c85cb7286eb20945d6f42f8fac9a6883e50119b49e57b6470ca714f5da29 | Python | 316 | 16 | import click
from ..._cli.utils import OrderedClickGroup
from .ilastik import ilastik_cmd_group
@click.group(
name="classify",
cls=OrderedClickGroup,
help="Perform pixel classification to extract probabilities",
)
def classify_cmd_group():
pass
classify_cmd_group.add_command(ilastik_cmd_group)
|
2ecf3cdc74608c017cf3d7fc73496e4df1a91bb3e5a69c73e717f8ab2bc50c0c | Python | 318 | 14 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .densepose_cse_base import DensePoseCSEBaseSampler
from .densepose_uniform import DensePoseUniformSampler
class DensePoseCSEUniformSampler(DensePoseCSEBaseSampler, DensePoseUniformSampler):
"""
Uniform Sampler for CSE
"""
pass
|
6417b16b3b9e8a63e3c427334248afd5dbb9a67b2a960dd402303ebc29d87dc5 | Python | 318 | 7 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
# Alignment collection and per-alignment data structures.
|
7e1d32872e9da53194d554e150c28a6da70b04da9956ccc14d6e55952c5ccd37 | Python | 318 | 5 | from sklearn.metrics import accuracy_score, precision_recall_fscore_support
def classification_metrics(y_true, y_pred):
p,r,f,_ = precision_recall_fscore_support(y_true,y_pred,average='macro',zero_division=0)
return {'accuracy':accuracy_score(y_true,y_pred),'precision_macro':p,'recall_macro':r,'macro_f1':f}
|
37f28a6870c1ef48d2db18d72ae2a47856014ff995a0c2587f5c1935ea17ed40 | Python | 320 | 22 | import time
import fluidsynth
fs = fluidsynth.Synth()
fs.start()
sfid = fs.sfload("example.sf2")
fs.program_select(0, sfid, 0, 0)
fs.noteon(0, 60, 30)
fs.noteon(0, 67, 30)
fs.noteon(0, 76, 30)
time.sleep(1.0)
fs.noteoff(0, 60)
fs.noteoff(0, 67)
fs.noteoff(0, 76)
time.sleep(1.0)
fs.delete()
|
c804366c5c207ac1cdd80ccb629cebb547a0bf957cba351ca721c3696f94a860 | Python | 320 | 13 |
#!/usr/bin/env python
"""
# Author: MD Istiaq Ansari
# File Name: __init__.py
# Description:
"""
__author__ = "MD Istiaq Ansari"
__email__ = "istiaq@ucf.edu"
from .trainer import train_SPIDER
from .utils import Cal_Spatial_Net, Stats_Spatial_Net, mclust_R, pseudo_spot_generation, Cal_knn_expression, Cal_Spatial_Net
|
02e42b4cd0036779058f170a6c26f648ddaf5ed0a2ce6102ff871230c1984c57 | Python | 321 | 9 | # Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_tridentnet_config
from .trident_backbone import (
TridentBottleneckBlock,
build_trident_resnet_backbone,
make_trident_stage,
)
from .trident_rpn import TridentRPN
from .trident_rcnn import TridentRes5ROIHeads, TridentStandardROIHeads... |
752b7bf5a2f3810823c5d62e78f6579a26363d3d49296bcfc464517ddf0f7bef | Python | 321 | 7 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
# Read/feature counting and grouped-count format conversion.... |
48c67e46672cb7ca2a4602e1eb10678a0d0a431eda665b41bf0bf460a63444fe | Python | 322 | 14 | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_ite... |
7db763c56fe2fb3f0baf332ff92d986232cb730012755b12ce753931eaca8606 | Python | 322 | 14 | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_ite... |
82f1b3e0d6dfcdccace7afc720b26fec9285fc5435a50db498e55701e30cbe4e | Python | 322 | 12 | from .cascade_mask_rcnn_swin_b_in21k_50ep import (
dataloader,
lr_multiplier,
model,
train,
optimizer,
)
model.backbone.bottom_up.embed_dim = 192
model.backbone.bottom_up.num_heads = [6, 12, 24, 48]
train.init_checkpoint = "detectron2://ImageNetPretrained/swin/swin_large_patch4_window7_224_22k.pth... |
8f5cbb5d73b1a4c0e1975f29518f205e4850a95639fd295a0ada5d04428a88e1 | Python | 322 | 5 | from nnunetv2.training.nnUNetTrainer.variants.data_augmentation.nnUNetTrainerNoMirroring import nnUNetTrainer_onlyMirror01
from nnunetv2.training.nnUNetTrainer.variants.data_augmentation.nnUNetTrainerDA5 import nnUNetTrainerDA5
class nnUNetTrainer_onlyMirror01_DA5(nnUNetTrainer_onlyMirror01, nnUNetTrainerDA5):
pas... |
191d8dedf07650b8e0a0e0f4474d1488d14087f6e1987b3a526c602bfa5f2dba | Python | 323 | 6 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from . import register_point_annotations
from .config import add_point_sup_config
from .dataset_mapper import PointSupDatasetMapper
from .mask_head import MaskRCNNConvUpsamplePointSupHead
from .point_utils import get_point_coords_from_point_annotati... |
43d197ed9307b6e59a2b8420b4f4b3983b3987598d254906665cab370401d288 | Python | 323 | 14 | from .mask_rcnn_R_101_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... |
64fb998e08b833d138664f3eb2dbfcd590631fb525f7f88b8b0d7df82909e0a8 | Python | 323 | 11 | """Functions for computing null models."""
__all__ = [
'alexander_bloch', 'vazquez_rodriguez', 'vasa',
'hungarian', 'baum', 'cornblath', 'burt2018', 'burt2020', 'moran'
]
from neuromaps.nulls.nulls import (
alexander_bloch, vazquez_rodriguez, vasa, hungarian, baum, cornblath,
burt2018, burt2020, moran... |
c4c8b1044b343e6a73b26043b36da583d4dae9c2460cbe9b8c514920ac47226d | Python | 323 | 14 | from .mask_rcnn_R_50_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter //= 2 # 100ep -> 50ep
lr_multiplier.scheduler.milestones = [
milestone // 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... |
cb0e6532af97912b2139d8a8a65fd2a8710f433ae53a8355199150ea2729b4d7 | Python | 323 | 14 | from .mask_rcnn_R_101_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = train.max_it... |
7f079b94a28c66b918a71e06c62980900958cef5449482571d0858e1b49d1c1e | Python | 324 | 8 | from .cascade_mask_rcnn_mvitv2_t_3x import model, dataloader, optimizer, lr_multiplier, train
model.backbone.bottom_up.depth = 24
model.backbone.bottom_up.last_block_indexes = (1, 4, 20, 23)
model.backbone.bottom_up.drop_path_rate = 0.4
train.init_checkpoint = "detectron2://ImageNetPretrained/mvitv2/MViTv2_B_in1k.py... |
82027ddc6d1cc6b0e4d72c80886e0d001ee2f2ef12fd1f415332dca73db7f0e9 | Python | 328 | 10 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from . import (
custom_typing,
logging_control,
)
from .optional_imports import requires_package
from .remove_oechem import without_oechem_backend
from .system_probe import log_syste... |
2a9449efa6299da6cefc30d4a6af26a50a658bc50267fc4d0713d3bc32c95cda | Python | 329 | 10 | """
CASCADE — Criticality Avalanche Spike Cross-platform Analysis Detection Engine
A modular Python pipeline for analysing multi-electrode array (MEA) recordings
from multiple manufacturers.
"""
__version__ = "0.8.0"
__author__ = "Forbes Avila, Jin Kim, Jong-Chan Park, Hyun-Su Lee, Sun-Hyun Park"
__license__ = "Apach... |
65507cacd4e7fac62a1914bb496459a2d138048d58d36b948d1da0c232d15d50 | Python | 329 | 22 |
""" Modes """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
from enum import IntEnum
class ExecModes(IntEnum):
""" Modes for execution """
TRAIN = 1
TEST = 2
TRAIN_TEST = 3
TUNE = 4
class DataModes(IntEnum):
""" Modes for data """
TRAIN = 1
VALIDATION = 2
TE... |
ebda380c8afd228390c1244a01c4ef7e0de0bfb67b2d792347eb945540f5047f | Python | 329 | 12 | try:
import torch
except ImportError:
raise ImportError # Torch is not installed. Please install through https://pytorch.org/get-started/locally/
from .data import DataProcess
from .train import Trainer
from .predict import Predict
from .unet import Unet
from .attention_unet import AttentionUnet
from .losses i... |
c62adad3476e28e7650abce44c4d280871748a3550f457ddb72b06c12c4139a6 | Python | 330 | 9 | # noqa: D100
import toml
# This file reads the pyproject.toml and prints out the
# dependencies and dev dependencies.
# It is located in tests/ folder so as not to pollute the root repo.
c = toml.load("pyproject.toml")
print("\n".join(c["project"]["dependencies"]))
print("\n".join(c["project"]["optional-dependencies"]... |
6fc05344849f50245b71ceb6b520da841d901c700100b214b8b05999911c3d2c | Python | 332 | 10 | # Copyright (c) Facebook, Inc. and its affiliates.
from .config import add_panoptic_deeplab_config
from .dataset_mapper import PanopticDeeplabDatasetMapper
from .panoptic_seg import (
PanopticDeepLab,
INS_EMBED_BRANCHES_REGISTRY,
build_ins_embed_branch,
PanopticDeepLabSemSegHead,
PanopticDeepLabInsE... |
15781846eb3551c4f9ba34ca3ad98d205623503eaf15c723b7d250341f07a9c3 | Python | 333 | 14 | from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... |
6647f4209bc69ea2caa1c37db00f005245a0873d11c2cbaf7401c822b4ba9ffb | Python | 333 | 14 | from .mask_rcnn_regnetx_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 2 # 100ep -> 200ep
lr_multiplier.scheduler.milestones = [
milestone * 2 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... |
804ca0910179116badb027f842c42b9302093cabadf95db2c499d25b052183af | Python | 333 | 14 | from .mask_rcnn_regnety_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... |
b8596d544e9827c3e305712e79007078e49154698f5c2812f09828cb83c20675 | Python | 333 | 14 | from .mask_rcnn_regnetx_4gf_dds_FPN_100ep_LSJ import (
dataloader,
lr_multiplier,
model,
optimizer,
train,
)
train.max_iter *= 4 # 100ep -> 400ep
lr_multiplier.scheduler.milestones = [
milestone * 4 for milestone in lr_multiplier.scheduler.milestones
]
lr_multiplier.scheduler.num_updates = tr... |
161555d06a580d8be0a6ee1e058f1aae27a9bb8c9f5abab8ac12fbd58c149eac | Python | 336 | 11 | # Copyright (c) Facebook, Inc. and its affiliates.
from .build import build_lr_scheduler, build_optimizer, get_default_optimizer_params
from .lr_scheduler import (
LRMultiplier,
LRScheduler,
WarmupCosineLR,
WarmupMultiStepLR,
WarmupParamScheduler,
)
__all__ = [k for k in globals().keys() if not k.s... |
1d50701e00830645c3e8ff6a6405c1745de9aa6f539e4eff9a4a9c47987a2bfd | Python | 337 | 11 | from typing import Sequence
from hsnn.core.types import SpikeEvents, SpikeTrains
def assert_recording(recording: SpikeEvents | SpikeTrains) -> None:
if isinstance(recording, dict):
return
if isinstance(recording, Sequence) and len(recording) == 2:
return
raise TypeError(f"invalid argument... |
ab9fc30426675b580ccacf45ea231bf7b4521d4c6059eb00100f090e1abbcd90 | Python | 337 | 8 | from ..common.train import train
from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_c4 import model
model.backbone.freeze_at = 2
train.init_checkpoint = "detectron2://ImageNetPretraine... |
d1b2cf21adfb8db2cd55ac9c231b9a779f7fb8dfa6713bbccce08cbb36037b2a | Python | 338 | 25 | from enum import Enum
__all__ = ["NeuronClass", "SynapseClass", "Projection", "SynEvent"]
class NeuronClass(Enum):
EXC = 1
INH = 2
class SynapseClass(Enum):
PLASTIC = 1
FIXED = 2
class Projection(Enum):
FF = 1
E2I = 2
I2E = 3
FB = 4
E2E = 5
class SynEvent(Enum):
ON_PRE = ... |
775488a0b01fab9f82add9d9ee93a87870cce09813a7270d26bb65ea3c9f3d0b | Python | 340 | 7 | import pandas as pd
from sklearn.model_selection import train_test_split
def stratified_split(df, seed=42):
train, tmp = train_test_split(df, test_size=0.20, random_state=seed, stratify=df['fine_intent'])
val, test = train_test_split(tmp, test_size=0.50, random_state=seed, stratify=tmp['fine_intent'])
retu... |
bc4e9dc6a494b1d324a791793b04d2e5c17e7e415b573ba93107e7984f96b2cc | Python | 340 | 10 | from . import (array_operations, mesh_elements, mesh_correspondence,
mesh_cluster, mesh_creation, mesh_operations, mesh_io)
__all__ = ['array_operations',
'mesh_elements',
'mesh_correspondence',
'mesh_operations',
'mesh_creation',
'mesh_cluster',
... |
65f5289fed24aa23582906b82a7650cb4f4f134a4b8f536c384f453c6fa6af85 | Python | 341 | 15 | """Constants for the reuse annotation-table pipeline."""
from __future__ import annotations
__all__ = [
"TABLE_NAMES",
"REUSE_SUBDIR",
"DEFAULT_DURATION",
"DEFAULT_OFFSET",
]
TABLE_NAMES = ("hfb_annotations", "png_label_metrics", "neuron_information")
REUSE_SUBDIR = "reuse"
DEFAULT_DURATION = 200.0
D... |
ccd1d127fc00cdbd9aa53892b5d566f5da873c4759e2fb66dd4f622ec08abb5e | Python | 342 | 13 | #!/usr/bin/env python
#
# Copyright (c) 2018 10X Genomics, Inc. All rights reserved.
#
MULTI_REFS_PREFIX = "multi"
# Constants for metasamples
GENE_EXPRESSION_LIBRARY_TYPE = "Gene Expression"
VDJ_LIBRARY_TYPE = "VDJ"
ATACSEQ_LIBRARY_TYPE = "Peaks"
ATACSEQ_LIBRARY_DERIVED_TYPE = "Motifs"
DEFAULT_LIBRARY_TYPE = GENE_EX... |
741021efa7fe75b86e27b9ff59c3027e1e70a744400bf9776bcd5a5c329d39b1 | Python | 343 | 13 | import os
import pathlib
from importlib import resources
from openfecli.parameters.output_dir import get_dir
def test_get_output_dir():
with resources.as_file(resources.files("openfe.tests")) as dir_path:
out_dir = get_dir(dir_path, None)
assert isinstance(out_dir, pathlib.Path)
assert o... |
e5511cdfd6775e8b38dd660393f774637827f6e4242864867052a6dc6b59fb53 | Python | 343 | 14 | # Copyright (c) Facebook, Inc. and its affiliates.
from itertools import count
from detectron2.config import LazyCall as L
from .dir1.dir1_a import dir1a_dict, dir1a_str
dir1a_dict.a = "modified"
# modification above won't affect future imports
from .dir1.dir1_b import dir1b_dict, dir1b_str
lazyobj = L(count)(x=d... |
7d7be89c98c9c6e2dc5aa19d08c8999f0fc4c9b2bba40c6769409d16ae35d3bc | Python | 345 | 15 | from importlib.metadata import version
__version__ = version(__name__)
from . import spatially_variable
from . import plotting
from . import preprocess
from . import spatially_variable as sv
from . import plotting as pl
from . import preprocess as pp
__all__ = [
"preprocess", "plotting", "spatially_variable",... |
b633ca2401f8733bb3bc27ac8315d50cfdf18708b8b277872fc72bfe0d0eac69 | Python | 345 | 13 | """
Denoising module for image restoration using CARE (CSBDeep).
This module provides functions for denoising calcium imaging data before
segmentation to improve detection quality.
"""
from .pipeline import denoising_pipeline, run_denoising_and_post_processing
__all__ = [
'denoising_pipeline',
'run_denoising... |
a65539097c1ea287e2b7135e51f29429a0d169ccae9830db280e3ec221376dc7 | Python | 346 | 16 | # Generated by Django 4.2 on 2024-11-12 09:30
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("abx_app", "0003_remove_resultsabx_condition_root"),
]
operations = [
migrations.RemoveField(
model_name="resultsabx",
name="tas... |
f2c181682dd4f58880b5ed4b98b469547ed449688aed1007229ba7c07957f8a5 | Python | 346 | 16 | # Generated by Django 4.2 on 2024-11-13 12:32
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("abx_app", "0007_alter_user_epsilon_dim_1_plus"),
]
operations = [
migrations.RemoveField(
model_name="user",
name="epsilon_dim_... |
4818fed258cf788aa4148e7fc7c5d43ca6865fe2ff9b9f5346ea1926f0017dca | Python | 347 | 10 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
# File:
from . import catalog as _UNUSED # register the handler
from .detection_checkpoint import DetectionCheckpointer
from fvcore.common.checkpoint import Checkpointer, PeriodicCheckpointer
__all__ = ["Checkpointer", "PeriodicCheckpointer"... |
b65b5419ce06e00facea7db1b62158146912c7ad60e75b58817702e1ff6ea49a | Python | 348 | 8 | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_fpn import model
from ..common.train import train
model.backbone.bottom_up.freeze_at = 2
train.init_checkpoint = "detectron2://ImageN... |
8ee74346c74834c6fed2f51defec46e8b67f2818ce136f74c53473691fd4a807 | Python | 350 | 13 | from __future__ import annotations
import jinja2
from colorama import Fore
from jinja2.ext import Extension
class ColoramaExtension(Extension):
"""Include colorama foreground colors in the global environment."""
def __init__(self, env: jinja2.Environment):
super().__init__(env)
env.globals["... |
2545e180213e2087b99f2c87c3187fe017c80bd8c3ff1137d9482bb39fb9a640 | Python | 352 | 17 | from abc import ABC, abstractmethod
from typing import TypeVar
import numpy as np
import torch
V = TypeVar("V", np.ndarray, torch.Tensor)
class DecompositionHandler(ABC):
@abstractmethod
def transform_coordinate(self, data_flat: V) -> V:
pass
@abstractmethod
def inverse_coordinate(self, coo... |
5e0c1c1686f91aa66f1bc67f1439db310382e469cc57e546b654e795aaa85260 | Python | 356 | 18 | #!/usr/bin/env python
#
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
"""Read environment variables."""
from __future__ import annotations
import os
def product():
"""Return the value of the environment variable TENX_PRODUCT if it exists.
or "tenxranger" otherwise.
"""
return os.g... |
bedaf0fa423b5e7095b825f17ff049b9fe29b527ba7bb1dc7f6ada92a1614108 | Python | 359 | 16 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from openfe.utils import requires_package
@requires_package("no_such_package_hopefully")
def the_answer():
return 42
def test_requires_decorator():
with pytest.rai... |
f4f00a939b26011494e73b845108d8443c7583b685cca700c4b96e6f472951c4 | Python | 359 | 11 | # Copyright (c) Facebook, Inc. and its affiliates.
from detectron2.config import LazyConfig
# equivalent to relative import
dir1a_str, dir1a_dict = LazyConfig.load_rel("dir1_a.py", ("dir1a_str", "dir1a_dict"))
dir1b_str = dir1a_str + "_from_b"
dir1b_dict = dir1a_dict
# Every import is a reload: not modified by other... |
e0bfe9c285e5fc7ae2b06e82313c40f0ba5edbc25dc586f0ce063654e638a67c | Python | 360 | 16 | # Generated by Django 4.2 on 2024-11-12 09:12
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("abx_app", "0002_rename_indices_miss_resultsabx_first_stim"),
]
operations = [
migrations.RemoveField(
model_name="resultsabx",
... |
3a8563118a133943e73a5b9a7dde920c22b93c5ac44ac74bcb95f8825dd7e1c1 | Python | 361 | 8 | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco_keypoint import dataloader
from ..common.models.keypoint_rcnn_fpn import model
from ..common.train import train
model.backbone.bottom_up.freeze_at = 2
train.init_checkpoint = "detect... |
4da6b5c117891c5f2e1148a41292da07c266a748bf087d3a1321c59d1ddee10d | Python | 362 | 19 | # operation flags
OP_ASSIGN = 'OP_ASSIGN'
OP_DELETE = 'OP_DELETE'
OP_APPLY = 'OP_APPLY'
SC_LOCAL = 1
SC_GLOBAL = 2
SC_FREE = 3
SC_CELL = 4
SC_UNKNOWN = 5
CO_OPTIMIZED = 0x0001
CO_NEWLOCALS = 0x0002
CO_VARARGS = 0x0004
CO_VARKEYWORDS = 0x0008
CO_NESTED = 0x0010
CO_GENERATOR = 0x0020
CO_GENERATOR_ALLOW... |
8abd8fb6aae06337e1ea087c44bf855411c189315115b66eeb2339819082a99f | Python | 362 | 9 | import WORC.classification.fitandscore
import WORC.classification.SearchCV
import WORC.classification.AdvancedSampler
import WORC.classification.construct_classifier
import WORC.classification.metrics
import WORC.classification.parameter_optimization
import WORC.classification.crossval
import WORC.classification.trainc... |
cf804c7f25b6a88fdf56c7c3c92aa4793675311b899fd0887549d4cb020616bd | Python | 362 | 15 | import torch.nn as nn
from braindecode import models
class Model (nn.Module):
def __init__(self):
super(Model, self).__init__()
self.core = models.SyncNet(
n_outputs=40,
n_chans=128,
n_times=440,
sfreq=1000,
input_window_seconds=0.44,
)
def forward(self... |
b0d63652d6631eed326c981a967e14d8175d4cfdf1973583cde95ec828564751 | Python | 363 | 17 | # Generated by Django 4.2 on 2024-11-12 09:08
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
("abx_app", "0001_initial"),
]
operations = [
migrations.RenameField(
model_name="resultsabx",
old_name="indices_miss",
... |
f7767479f1a22647c29c3be90a034e00f991e2cd42d7c27a64ce2cd4c98c8554 | Python | 363 | 13 | import pandas as pd
def make_result_tables(
rows: list[dict],
candidate_rows: list[dict],
importance_rows: list[dict],
) -> dict[str, pd.DataFrame]:
return {
"model_performance": pd.DataFrame(rows),
"candidate_model_selection": pd.DataFrame(candidate_rows),
"permutation_importa... |
34169465d130006b7786f4dfe1b16cba44e93b252cd12747addc36726a696ee3 | Python | 364 | 9 | from datetime import datetime
import logging
import os
from pathlib import Path
LOG_DIR = Path(os.getenv("CHEMPROP_LOG_DIR", "chemprop_logs"))
LOG_LEVELS = {0: logging.INFO, 1: logging.DEBUG, -1: logging.WARNING, -2: logging.ERROR}
NOW = datetime.now().strftime("%Y-%m-%dT%H-%M-%S")
CHEMPROP_TRAIN_DIR = Path(os.getenv(... |
dee31ff277135ab229d24cb06e6e9c5c6115a757abb2db39519b7da4fbc42d6f | Python | 365 | 17 | """VAE-based molecular generation."""
from nfml.generate.sample import generate_molecules
from nfml.generate.mol_db import (
add_to_mol_db,
dedupe_against_source,
merge_into_mol_db,
save_generated_mols,
)
__all__ = [
"generate_molecules",
"add_to_mol_db",
"dedupe_against_source",
"merg... |
b4d4c671ff1703ae68c358513d7d5da51883df655145d6c1efce49cdf02bd165 | Python | 366 | 8 | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco_panoptic_separated import dataloader
from ..common.models.panoptic_fpn import model
from ..common.train import train
model.backbone.bottom_up.freeze_at = 2
train.init_checkpoint = "d... |
4bd8bd677a23cb4a009d6b7ee78e8c513f67a25405cce80a1760dea0c56bfd7d | Python | 367 | 15 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
import logging
def verbosity_to_level(verbosity) -> int:
if verbosity is not None:
if verbosity == 0:
return logging.WARNING
elif verbosity == 1:
return logging.INFO
elif verbosity >= 2:
r... |
4657ba4975b6b91eee3e1dabaee014b419e277952269430192c338479a2c221c | Python | 369 | 13 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
def add_point_sup_config(cfg):
"""
Add config for point supervision.
"""
# Use point annotation
cfg.INPUT.POINT_SUP = False
# Sample only part of points in each iteration.
# Default: 0, use all a... |
38e999a2dfe569cd5a7058a800fa8ade0492335c1d64a99ed008392c7061dac3 | Python | 370 | 11 | try:
import torch
except ImportError:
raise ImportError # Torch is not installed. Please install through https://pytorch.org/get-started/locally/
from .data import DataProcess
from .train import Trainer
from .predict import Predict
from .multi_output_nested_unet import MultiOutputNestedUNet
from .multi_output_... |
ff4de4fe23f96dbc2adfb97429b37249fa3f48365717c192aecac039efd203c3 | Python | 370 | 8 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
# Post-run visualization: output config, plotting, and gene-... |
9bb48a2d7259ff148297d3247c68c9d88c5171298e69e418d45ae831823ea86c | Python | 372 | 19 | from setuptools import setup, find_packages
setup(
name="filament_processing",
version="0.1",
packages=find_packages(),
install_requires=[
# List dependencies here
"open3d",
"numpy",
"scipy",
"scikit-image",
"pandas",
"mrcfile",
"ipykernel... |
5600c3e8478b1021223ec7b0adb8b96dc21db5cf46a6845e94ec1f0ed89c697a | Python | 374 | 19 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .frame_selector import (
FrameSelectionStrategy,
RandomKFramesSelector,
FirstKFramesSelector,
LastKFramesSelector,
FrameTsList,
FrameSelector,
)
from .video_keyframe_dataset import (
VideoKeyframeDataset,
video_list... |
a964abd71ea0db293703a12cb937b5c1ab7b67abea6dbf488fb99746efa92ce1 | Python | 375 | 13 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from torch import nn
def initialize_module_params(module: nn.Module) -> None:
for name, param in module.named_parameters():
if "bias" in name:
nn.init.constant_(param, 0)
elif "weight" in name:
nn.init.kaimi... |
78838ffeefc3dfe065f0d667ec2613d26b7abf62344222fb44c98d7e6dfcb2e7 | Python | 376 | 13 | from typing import Union, Tuple, List
import numpy as np
import torch
def no_resampling_hack(
data: Union[torch.Tensor, np.ndarray],
new_shape: Union[Tuple[int, ...], List[int], np.ndarray],
current_spacing: Union[Tuple[float, ...], List[float], np.ndarray],
new_spacing: Union[Tuple[f... |
46074dc422c8957cba74c43b9f44ba2ba89e369270738117eeeb6e54fef4dd9f | Python | 377 | 19 | import os
import pathlib
import click
from plugcli.params import NOT_PARSED, MultiStrategyGetter, Option
def get_dir(user_input, context):
dir_path = pathlib.Path(user_input)
return dir_path
OUTPUT_DIR = Option(
"-o",
"--output-dir",
help="Path to the output directory. ",
getter=get_dir,
... |
8832aae254306dc016329bf0a16a8eb04d185432904cb5bc6c7276adab294529 | Python | 377 | 14 |
def define_env(env):
@env.macro
def spades_version():
try:
lines = open("VERSION").readlines()
version = lines[0].strip()
# FIXME: dirty hack for current VERSION file
if version.find("dev") != -1:
version = "3.4.2"
return vers... |
3e357c8bf71347a9a7b90893cc58aaa684a784892f94669fde49d801cc132d42 | Python | 381 | 12 | from setuptools import setup
exec(open("cshift/__version__.py").read())
setup(
name="cshift",
version=__version__,
description="A tool to perform cluster enrichment/depletion analyses",
author="Noam Teyssier",
author_email="Noam.Teyssier@ucsf.edu",
packages=["cshift"],
install_requires=["nu... |
ecd95cff406ef1013c84ca21a24a384a5357a4d0bf672162badfaba705ecbfe8 | Python | 386 | 12 | from pathlib import Path
from omegaconf import DictConfig, OmegaConf
SAMPLES_DIR = Path(__file__).parents[1] / 'samples'
config = DictConfig(OmegaConf.load(SAMPLES_DIR / 'data_ops.yaml'))
def get_data(name: str) -> list:
arguments = OmegaConf.to_container(config[name])
assert isinstance(arguments, dict)
... |
038870300c903358d384bb670d7f2f34db5426f5cad430704867e05a49d3ef23 | Python | 388 | 12 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from . import _rfe_utils
from .equil_rfe_methods import (
RelativeHybridTopologyProtocol,
RelativeHybridTopologyProtocolResult,
RelativeHybridTopologyProtocolUnit,
)
from .equil_... |
29004d3df1a489748dd1d4a941dcdee4953acd12afda988b221bcb1987dc1a14 | Python | 389 | 16 | """
WSGI config for config project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/4.2/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault("DJANGO_SETTIN... |
50a4b6538c4d418b0df314fe60dfadeb1e91ea843df621f8e1430e3f891f2c32 | Python | 389 | 16 | """
ASGI config for config project.
It exposes the ASGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/4.2/howto/deployment/asgi/
"""
import os
from django.core.asgi import get_asgi_application
os.environ.setdefault("DJANGO_SETTIN... |
77dc953bba7b2c7c2fd872e519b8cb84f10d23dfb349e12dc3097aa07896795a | Python | 390 | 16 | #return lists of columns available
def get_available_columns( input_filename ):
rval = []
elems = []
file_in = open(input_filename, 'r')
oneline = file_in.readline()
if oneline :
elems = oneline.split('\t')
file_in.close()
ncol = len(elems)
while ncol > 0:
rval.app... |
b8125fa635e6a8599c2b953991f880f03d828f785bb65cf46cb7b8b400f6c7c7 | Python | 391 | 18 | # Generated by Django 4.2 on 2024-12-27 02:01
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('abx_app', '0018_user_is_not_fixate'),
]
operations = [
migrations.AlterField(
model_name='user',
name='is_not_fixate',... |
c3bbe2c48a69e6510d42cd444b6b6f431c7139363887a7665fdd60421cda6dba | Python | 391 | 16 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .chart import DensePoseChartLoss
from .chart_with_confidences import DensePoseChartWithConfidenceLoss
from .cse import DensePoseCseLoss
from .registry import DENSEPOSE_LOSS_REGISTRY
__all__ = [
"DensePoseChartLoss",
"DensePoseChartWithCon... |
f8fd5c070524d515cc09c90928a8a800e5662e5a19f9917ac6d6767f225c03e1 | Python | 391 | 7 | """AccuSNV downstream analysis: the stages run after accusnv.accusnv's candidate calling.
snv.py is the shared kernel (data structures, reference/GFF parsing, filters, state
rebuild) used by every stage below it:
annotate (stage 2) -> recombination / dnds / generate_dashboard / tree_building
Each stage is runnable as ... |
338011eec3c4b399c81bbe4b07743b0af74bc3b22c51bc47ef781890eeba5e1c | Python | 392 | 18 | # Generated by Django 4.2 on 2025-01-09 11:56
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('abx_app', '0022_alter_user_is_fixate'),
]
operations = [
migrations.AddField(
model_name='user',
name='miss_eye_positi... |
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