sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
66e57a8c759d0445f3b9ee43be2db1197001e269fb27005b7c9e9fe2a1f3c46f | Python | 2,133 | 54 | import tensorflow as tf
import numpy as np
from pdb import set_trace
BATCH_SIZE = 10
def get_dataset():
fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
return (train_images, train_labels), (test_images, test_labels)
de... |
434fec59d185b53f6d911d6115a7bf602a39993884f9265323f181b18d92ae68 | Python | 2,134 | 69 | OVERALL_SIZE_CANO_TEST_SET = 16505
def get_tissue_groups(name):
import sys
sys.path.insert(0, ".")
from modular_splicing.gtex_data.experiments import tissue_groups
return getattr(tissue_groups, name)
def get_path(name):
import sys
sys.path.insert(0, ".")
from modular_splicing.gtex_data... |
b94963082ef4bc2173ec887375f390048c9db604e43e199500726d4da9a99967 | Python | 2,134 | 61 | import functools
@functools.lru_cache(maxsize=1)
def torchvision_vit_available() -> bool:
"""Checks if Vision Transformer (ViT) models are available in torchvision.
This function checks if the `vision_transformer` module is available in torchvision,
which requires torchvision version >= 0.12. It also han... |
ce6c2f8816b27b236ba54e2b93fe7eb016218ae50ebbae239fef82d5238c3226 | Python | 2,134 | 72 | """Functional performance-regression smoke tests."""
from __future__ import annotations
from types import FrameType
import torch
from torch import nn
import torchlens as tl
import torchlens.utils.introspection as introspection
class TenLayerMlp(nn.Module):
"""Ten-layer MLP for stack-introspection smoke tests.... |
50583a634c3136dcbbb565466fed9ce0f90dee1f14823d305c19f66c72240228 | Python | 2,135 | 68 | import sys, os
from collections import defaultdict
from functools import wraps
import brian2.numpy_ as np
from brian2.units.fundamentalunits import (
Quantity, fail_for_dimension_mismatch, is_dimensionless, DIMENSIONLESS)
from brian2.core.variables import VariableView
@wraps(np.concatenate)
def concatenate(arrays... |
6245ab5c4eddbb0a9c2cffbfbd305b4786719c07f8bea1c649df2ad60428ec44 | Python | 2,135 | 77 | from pathlib import Path
import pandas as pd
from anndata import AnnData
def positions(
adata: AnnData,
position_filepath: Path | str,
scale_filepath: Path | str,
quality: str = "low",
copy: bool = False,
) -> AnnData | None:
"""\
Adding spatial information into the Anndata object
Pa... |
e1f4cf286661be7730f9505db3b2912108e989364d4fe082cae586f4f1f914bb | Python | 2,135 | 86 | '''
http://pymolwiki.org/index.php/cgo_arrow
(c) 2013 Thomas Holder, Schrodinger Inc.
License: BSD-2-Clause
'''
from pymol import cmd, cgo, CmdException
def cgo_arrow(atom1='pk1', atom2='pk2', radius=0.5, gap=0.0, hlength=-1, hradius=-1,
color='blue red', name='', state=0):
'''
DESCRIPTION
C... |
1f9f0280c13fa9238f4d92ce1b4f30160ad04b58f7e29bcdc0c3eb9138f7124e | Python | 2,136 | 67 | # We use the same API as https://github.com/rwightman/pytorch-image-models/blob/v0.6.11/timm/models/layers/patch_embed.py
# But we use nn.Linear instead of Conv2d and it's about 8x faster.
from functools import partial
import torch.nn as nn
from einops import rearrange
from torch import _assert
from torch.nn.modules.... |
b66942ea6bf3328606ba47b7e1530b06e60adf8f56c1dbf2faec32523675f342 | Python | 2,136 | 61 | # fix problems with pythons terrible import system
import os
import sys
file_dir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(os.path.join(file_dir, '..'))
import prob2020.console.randomization_test as rt
import numpy as np
def test_ctnnb1_hotmaps_main():
opts = {'input': os.path.join(file_dir, '... |
ff7862e347683241855bf2e8eb4cc610a16365b68754f23c23072c92180d0648 | Python | 2,136 | 92 | #!/usr/bin/env python3
from __future__ import annotations
import re
import ghapi.all
from rich import print
from rich.syntax import Syntax
ENTRY = re.compile(
r"""
Suggested \s changelog \s entry:
.*
```rst
\s*
(.*?)
\s*
```
""",
re.DOTALL | re.VERBOSE,
)
print()
api = ghapi.al... |
658c538c62a32d2770425488e2f1e25af60e68df9128a23612c3cd164e958a14 | Python | 2,137 | 86 | from typing import Optional, Union
from anndata import AnnData
import pandas as pd
def stack_3d_plot(
adata: AnnData,
slides,
cmap="viridis",
slide_col="sample_id",
use_label=None,
gene_symbol=None,
) -> Optional[AnnData]:
"""\
Clustering plot for sptial transcriptomics data. Also it ... |
75c7a509b9904a71d0beda0b27a058836f79ce9aab0ad13e311606812a51507c | Python | 2,139 | 32 | etas = {
'generic14_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT': 0.0896875702392, 'muT__muW': 0.00786798398002, 'muT__phi': 0.0, 'muW__hat': 1.0, 'muW__muT': 0.00803419913052, 'muW__muW': 0.214994532712, 'muW__phi': 0.0 },
},
'generic20_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT__down': 0... |
ccc35e2e5f018104bf6d4ab3340e55577d97c5c2a94df58745aadbdaa2da02f0 | Python | 2,139 | 54 | from ptic import pmi_tfidf_classifier as ptah
import numpy as np
import pandas as pd
from sklearn import metrics
import torch
from ptic import neuro_ptic
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
np.random.seed(42)
path = "doc/datasets/"
data_raw = pd.read_csv(path + 'DILI_data.csv')
indi... |
191b5001f2eea758bce69416a049fcb5752015c246f892301cfe9a53ea64112f | Python | 2,141 | 59 | from bioconfpred.data.split import DataSplit
from typing import Dict, Any
from .atomistic.comenet import AtomicComENet
from .atomistic_nn_model import AtomisticNNModel
from bioconfpred.params import (LOG_DIRPATH,
COMENET_CONFIG,
COMENET_MODEL_NAME)
class ComENetModel(AtomisticN... |
53240a65c389ba2ae439e3e3aba514d30f385177a95404df2a0b4f86deb81e22 | Python | 2,141 | 56 | import os
import glob
import shutil
#print [name for name in os.listdir(".") if os.path.isdir(name)]
raw_dir = ""
mask_dir = ""
# Change rootdir as you want:
counter = 0
#List all files in raw_dir
for raw_file in os.listdir(raw_dir):
raw_filename = os.path.join(raw_dir, raw_file)
mask_filename ... |
ad87bb4b199bacc00e915ba1c5a4cd2eeecb5e03b0c451194800448568507b1c | Python | 2,141 | 61 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import remove_classes
from wyrm.processing import swapaxes
class TestRemoveClasses(unittest.TestCase):
def setUp(self):
ones = np.ones((10, 5))
channels = ['ca1', 'ca2', 'cb1', '... |
b4ffbb7bcf89a5fbd50b25e304477c31f5d3baec981ebd6fe1388ae3a38345a0 | Python | 2,141 | 32 | etas = {
'generic14_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT': -0.0160994540422, 'muT__muW': 0.000696975533569, 'muT__phi': 0.0, 'muW__hat': 1.0, 'muW__muT': 0.139179311976, 'muW__muW': 0.0039681776849, 'muW__phi': 0.0 },
},
'generic20_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT__down': ... |
544f2ebbd7becaf52e430e61836be893da3073a99c76d6262e9cc5a609ade1f1 | Python | 2,142 | 65 | import json
import re
import numpy as np
from matplotlib import pyplot as plt
import matplotlib
from angorapy.common.const import QUALITATIVE_COLOR_PALETTE as COLORS
font = {'family' : 'Times',
'weight' : 'normal',
'size' : 12}
matplotlib.rc('font', **font)
with open("storage/predictability_repe... |
7057fe09cb0934d424ad677644925f131a03405d77963dd8b4185a1c8f45d7ab | Python | 2,142 | 61 | import json
from typing import Optional, Union
import requests
from codecarbon.core.telemetry_schemas import TelemetryCreate
from codecarbon.external.logger import logger
class TelemetryClient:
"""
Client dedicated to sending CodeCarbon telemetry payloads.
"""
def __init__(
self,
en... |
7c48e7aa3d468d3b475732255bf14ddec73d06a69e5fa09346ba730c935d474a | Python | 2,142 | 50 | #!/usr/bin/env python
"""Update the featurenames json file that contains the expected names"""
"""
Copyright (c) 2015, Blue Brain Project/EPFL
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
* Red... |
8ce94dc7be79521d21002d8d8587ae37d30a9bf3429e0c1917bcc3688a71913b | Python | 2,142 | 45 | """Pre init checks"""
import sys
def _require_mxnet_version(mx_version, max_mx_version='2.0.0'):
try:
import mxnet as mx
from distutils.version import LooseVersion
if LooseVersion(mx.__version__) < LooseVersion(mx_version) or \
LooseVersion(mx.__version__) >= LooseVersion(max_mx... |
ac64c2fdbefcb2b421125d012bcf720094c4883dffdd40d9ed6b6dc11bcf218e | Python | 2,143 | 62 | import logging
import colorlog
import re
import os
from cvnn.utils import create_folder
from tensorflow.keras.utils import get_custom_objects
from cvnn.activations import act_dispatcher
from cvnn.initializers import init_dispatcher
get_custom_objects().update(act_dispatcher) # Makes my activation functions usable ... |
920fd85dc8f288e1b74334f710a10b9524a44a90b6be4efa221b80c80df29a40 | Python | 2,144 | 67 | from __future__ import annotations
from larvaworld.portal.landing_registry import ITEMS
from larvaworld.portal.registry_logic import validate_registry
from larvaworld.portal.serve import APP_ID_TO_FACTORY_PATH, SERVED_APP_IDS
def test_validate_registry_strict_passes() -> None:
validate_registry(strict=True)
de... |
811afa47d03353a96ff2ad9d3750a3f8601afe0497adb5de044030c907ac41a5 | Python | 2,145 | 63 | import numpy as np
import math
import statistics
import pdb
# ------------------------------------------------------
# 3d distance
def distance3d(a, b):
d = math.sqrt(math.pow(a[0] - b[0], 2) +
math.pow(a[1] - b[1], 2) +
math.pow(a[2] - b[2], 2) * 1.0)
# print("Distance is... |
b9571d8cbda4f3b96f83676ca187e29a3086ddfb1cfbadee14eff9f563fec003 | Python | 2,145 | 62 | """Distributions used in some continuous RL algorithms."""
import torch
class TanhMultivariateNormal(torch.distributions.MultivariateNormal):
"""The distribution of X is an affine of tanh applied on a normal distribution.
X = action_scale * tanh(Z) + action_bias
Z ~ Normal(mean, variance)
"""
de... |
2a20dedee260c1483deb9ebefefb950b934bdd6179038b1a54a2eafd87a17250 | Python | 2,146 | 64 |
import cv2
import time
import logging
import os
import numpy as np
from ethoscope.utils.debug import EthoscopeException
import multiprocessing
from scipy.misc import toimage, imread, imsave
from io import BytesIO
import io
from ethoscope.hardware.input.cameras import PiFrameGrabber, OurPiCameraAsync
class PiFrameGrab... |
a47c557744c77faa8b8dce69546531a8f04c0eb4e0b0014e31ad71223aca66c7 | Python | 2,146 | 64 | from __future__ import annotations
import os
os.environ.setdefault("QT_QPA_PLATFORM", "offscreen")
from PySide6.QtWidgets import QApplication
from larvaworld.gui_v2.apps.models_environments.env_builder_widget import (
EnvBuilderWidget,
build_environment_builder_widget,
)
def _app() -> QApplication:
re... |
cb92b0baf6092bfaa0472339f30fa8b5e3713cf399a4c8769cf6c04553845209 | Python | 2,146 | 81 | import logging
import yaml
import copy
import argparse
from bson.objectid import ObjectId
import numpy as np
from pymatgen.core import Molecule
from atomate.qchem.fireworks.core import (
FrequencyFW,
FrequencyFlatteningTransitionStateFW,
)
from atomate.common.powerups import add_tags
from fireworks import ... |
d0c85e677601a978ef16171104bbb4b44d2cba322dd5b1f128c0456bc2534f95 | Python | 2,146 | 32 | etas = {
'generic14_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT': 0.203084255229, 'muT__muW': -0.000905716822652, 'muT__phi': 0.0, 'muW__hat': 1.0, 'muW__muT': -0.000110063688614, 'muW__muW': 0.201823621185, 'muW__phi': 0.0 },
},
'generic20_learning': {
'alpha_sys': { 'muT__hat': 1.0, 'muT__muT__down'... |
0ff48543448e66488a3fc5e3daedffbae40e63a14411acd5f74af5283ae0b7fa | Python | 2,147 | 71 | import sys
import pathlib
import matplotlib.pyplot as plt
import numpy as np
from typing import Tuple
try:
PATH_HERE = pathlib.Path(__file__).parent
PATH_ABFS = PATH_HERE.joinpath("../../data/abfs/").resolve()
PATH_SRC = PATH_HERE.joinpath("../../src/").resolve()
print(PATH_SRC)
sys.path.insert(0, ... |
c0d60d9e477c9fff979046488e40d6eb01ecc1fd116be249650b4bcc2a9e7bd6 | Python | 2,147 | 70 | """
need FreeCAD daily after Nov 2020
convert off mesh format to some other format and also calc properties like bbox, volume
"""
import sys
import os
try:
sys.path.append("/usr/lib/freecad-daily-python3/lib")
# /usr/lib/freecad-daily/Mod
import FreeCAD as App
import Mesh
except:
pass # it is fine... |
2f67fa9977c38c01e6c93c0f0ee9dda3b803ac390ccd87616197902e13f33fd3 | Python | 2,148 | 69 | import numpy as np
from .conf_ranker import ConfRanker
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Chem.rdchem import Mol
from typing import List, Any
class EnergyRanker(ConfRanker):
"""Can rank conformers based on MMFF94s energy
:param name: Name of the ranker
:type name: str
:... |
4faa2984a3997a03c2ed2701baec23bbe25b84642d1c58587b513d680bb2cc0b | Python | 2,148 | 52 | # Copyright 2019 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://w... |
bcd99dedc0327db50e256beb0a108b07bd66555ae09e66038b29429e3fbc9a8e | Python | 2,148 | 66 | """Image preprocessing.
"""
from typing import Optional, Union
import cv2
import matplotlib.pyplot as plt
from anndata import AnnData
from ..io.image_utils import add_image_layer
def remove_background(
adata: AnnData,
threshold: Union[float, str] = "auto",
slice: Optional[str] = None,
used_img_layer... |
7c13b3d7321235a5a610cc5dbfcaa3abcefc9c0859d648f5df41c395630c00fb | Python | 2,149 | 49 | from angorapy import make_task
from angorapy.common.policies import BetaPolicyDistribution, MultiCategoricalPolicyDistribution, \
CategoricalPolicyDistribution
from angorapy.utilities.model_utils import is_recurrent_model
from angorapy.utilities.core import flatten
from angorapy.models import get_model_builder
d... |
8709c567a1a9508b587ad2f3878e9645f7fa7aa17701ea7fe9d42d8f3dbd4be6 | Python | 2,149 | 65 | """
# > Script for measuring quantitative performances in terms of
# - Structural Similarity Metric (SSIM)
# - Peak Signal to Noise Ratio (PSNR)
# > Maintainer: https://github.com/xahidbuffon
"""
## python libs
import numpy as np
from PIL import Image
from glob import glob
from os.path import join
from ntpath imp... |
b648679bd278fbc4d708d836f595b8b7e503035d4682fcaa71af4c3eb4581c22 | Python | 2,149 | 59 | """AUD-CODE 3.10 regression: the README gate's volatile normalizer.
The README first screen prints ``log.summary()``, whose Memory line carries
the host-RSS forward peak (a runtime measurement documented as never
portable). Two cold runs printed ``78.9 MB`` and ``80 MB`` and the gate went
red non-deterministically. Th... |
d82b35a554c52e90d259fe0ff248ce1c8d52ea6977f6147722cee88e82892ddf | Python | 2,149 | 53 | import numpy as np
import math
import pdb
# -----------------------------------------------------
def checkConsecutive(index_list):
return (sorted(index_list) == list(range(min(index_list), max(index_list) + 1))) and (sorted(index_list) == index_list)
# ------------------------------------------------------
# I... |
4903b28311e2947021ce8f2878e89d93b0a8b2c3d69d16eef153a096fd2143d8 | Python | 2,150 | 53 | from model import *
from utils import *
import numpy as np
import torch
import os,sys
from sklearn.metrics import roc_auc_score, precision_score, recall_score,precision_recall_curve, auc,accuracy_score,f1_score
TEST_BATCH_SIZE =256
model_name = 'ratio_0.9bach32LR_1e-4random_0_onehot.pt'
dataset = ['toy_cls','BindingD... |
db7cdb86cde552dda1832513e538d3c80cb0de33b42d90877d5a4e4c50820b56 | Python | 2,150 | 24 | # Reorganize the data in folders as expected by the code
# developed by Diamant et al.
import os
import shutil
ids = ['HN1004','HN1006','HN1022','HN1026','HN1029','HN1046','HN1047','HN1054','HN1057','HN1060','HN1062','HN1067','HN1074','HN1077','HN1079','HN1080','HN1081','HN1083','HN1088','HN1092','HN1095','HN1096','H... |
343e12b624c5a92b5d5a494177f6492578c997883a07932906ff80dfe73cd035 | Python | 2,151 | 64 | import pytest
import torch
from lightly.loss import FroSSLLoss
class TestFroSSLLoss:
def test_forward(self) -> None:
loss_fn = FroSSLLoss()
for bsz in range(2, 4):
z0 = torch.randn((bsz, 32))
z1 = torch.randn((bsz, 32))
loss = loss_fn([z0, z1])
asse... |
9956c82775041c244a63ac942a2533974149534502f300d1a9b4e23797ede086 | Python | 2,152 | 65 | import os, argparse, shutil
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from gluoncv.utils import makedirs
def parse_opts():
parser = argparse.ArgumentParser(description='Preparing MINC 2500 Dataset',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser... |
35afcc2209a38247180f5b7ff98fa97ccebd62e66ffa58f4b70a63e4f63e4aad | Python | 2,153 | 57 | """Executable gate over ``docs/reference/checks_kit.md`` (memo item 11).
Every Python fence on the checks-kit page executes top to bottom, statement
by statement, in ONE shared namespace with ZERO ambient injections: the page
must define everything it references, so a recipe that drifts from the real
surface fails thi... |
84d81fe6fbea88f2340e3357753253992a99259970b3a9bb0669817f644053b5 | Python | 2,153 | 74 | """Neural Logic Machine, 2019, Dong et al., "Neural Logic Machines".
Paper: Dong 2019, "Neural Logic Machines."
Binary predicate tensors are transformed by existential and universal reductions,
pairwise predicate composition, and an MLP-style logic layer.
"""
from __future__ import annotations
import torch
from torc... |
d38a6ac8a51f528357d12183dc3c078a37ac3c1de4643fc9ecd925494491b423 | Python | 2,153 | 60 | import os
from .parcellation_level import ParcellationLevel
class BinarySplitLevel(ParcellationLevel):
def __init__(self, root, config, hierarchy, structures, region_volume, overwrite=False):
super().__init__(root, config, hierarchy, region_volume, overwrite)
self._structures = structures
@p... |
61691a03cf08d82429c17a427d082566da95c4e2885b4cbad48747b473eb0bf6 | Python | 2,155 | 54 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless requir... |
a206571e4143c1c3bd566c540eff107f356ada3d918ccc50f1ec8de736279a22 | Python | 2,155 | 46 | '''
Regularized LNP model for neural system identification
Author: Santiago Cadena
Last update: April 2019
'''
import numpy as np
import os
from scipy import stats
import tensorflow as tf
import hashlib
import inspect
import random
from tensorflow.contrib import layers
from tensorflow import losses
from cnn_sys_ident... |
c05eec79c9948cc33507755b1eee7c22ba293b12eb228beb7c006e2c46a997e4 | Python | 2,155 | 57 | from pkgutil import ImpImporter
import pgl
import paddle
import math
import numpy as np
class DualDataLoader(object):
def __init__(self, data_2d, data_3d, batch_size, shuffle=False):
''' Load data
'''
self.data_2d = data_2d
self.data_3d = data_3d
self.batch_size = batch_size... |
070d0228a9be722f69a041cc70030ec12054f2d9fe44b8756d36e57263536265 | Python | 2,156 | 64 | # Demonstrates interoperability of the nfp preprocessing methods with the spektral GNN
# library (https://graphneural.network/). Specifically follows the `BatchLoader` example
# for QM9 prediction shown here, https://github.com/danielegrattarola/spektral/blob/
# master/examples/graph_prediction/qm9_ecc_batch.py
import... |
2401674f845b3ed1761348365f8fd955c4e620d3a5e436e80c3ff32a4ac7f83e | Python | 2,156 | 49 | import unittest
from carbontracker.components.cpu.sim_cpu import SimulatedCPUHandler
class TestSimulatedCPU(unittest.TestCase):
def test_simulated_cpu_initialization(self):
handler = SimulatedCPUHandler("Intel Xeon", 150.0)
self.assertEqual(handler.cpu_brand, "Intel Xeon")
self.assertEqual(... |
6c6eff9bc7e1ac34261f273c6dbbb0cfcd8f3adbc592d20f5e911b4fbcc8c85d | Python | 2,156 | 57 | # skip test: data unavailable
"""Compute DSS on Alex's Toolbox demo data"""
from eelbrain import *
# If the raw file is already filtered, the events can be loaded directly with
# the filename
ds = load.fiff.events('DATA/R2290_HAYO_P3H_1-8-raw.fif')
# select the desired events
ds = ds.sub("trigger == 167")
# add MEG t... |
d46341be8438b49e852ba45911d5e45ba88c87af9f91ff9ebda22be9585a11ae | Python | 2,156 | 80 | """
Entry point for the UI software
SimplyFire - Customizable analysis of electrophysiology data
Copyright (C) 2022 Megumi Mori
This program comes with ABSOLUTELY NO WARRANTY
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the F... |
0f5fb4052668f44c2a2d5cdaa3205d1dba6028f3af604780ecd2c30d7935c7c9 | Python | 2,157 | 62 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import spectrum
from wyrm.processing import swapaxes
class TestSpectrum(unittest.TestCase):
def setUp(self):
# create some data
fs = 100
dt = 5
self.freqs = [2, 7... |
47ae3f513c966abc6ed55a005de09f6cb7ba2afe366b97d77e3c921fae15008b | Python | 2,157 | 65 | import os
import json
import ssl
from urllib import request
from urllib.error import HTTPError
from time import sleep
class PFamConnector():
def __init__(self) -> None:
self.base_url = 'https://www.ebi.ac.uk:443/interpro/api/entry/pfam/structure/PDB/'
def from_pdb(self,
... |
58b0207f6441cbaa1aa8928f6d90409971cd8116d73a602a39bd949744aad13a | Python | 2,157 | 74 | import cv2
import numpy as np
class Camera:
def __init__(self):
'''
Initialize the camera
'''
self.snapshot_size = (1024, 1024)
self.scene_size = (2048, 4096)
self.degrees_per_pixel = 0.087890625
self.eye_pos = np.array([0.0, 0.0])
self.target_locatio... |
80c9f7cdf148bc5408893be9b16339464a68e6c647cf268dee9cd29b02a1add0 | Python | 2,157 | 69 | """
"""
import os
class Dataset(object):
"""Base class for dataset fetching and formatting."""
def __init__(self, task_name, dataset_dir=None, url=None):
self.task = task_name
self.dataset_dir = dataset_dir
self.url = url
self.train = None
self.test = None
se... |
d17a360e382ef7047cf6cba1402c94ed3681bf0e363aed13fbde32bfdfd0ad2d | Python | 2,157 | 70 | # -----------------------------------------------------------------------------
# Copyright (c) 2013, The Deblur Development Team.
#
# Distributed under the terms of the BSD 3-clause License.
#
# The full license is in the file LICENSE, distributed with this software.
# -------------------------------------------------... |
04c2de3fe03294c1f07976cb36348dc8d5248a6621379aac2e0327bc65ba9069 | Python | 2,158 | 76 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import torch
import torchvisi... |
55fabc558dd1d8c634a8bd21ea0d3de112e9867953b77646c8a765f42f51106f | Python | 2,158 | 81 | """
Tests for the ethoscope-light CLI.
"""
import io
import json
from unittest.mock import patch
import pytest
from ethoscope.hardware.interfaces import light_cli
from ethoscope.hardware.interfaces.light_daemon import LightDaemonUnavailable
class _FakeClient:
def __init__(self, *_, **__):
self.calls = ... |
9574d440a6bf310a40490cc1e17ffeffd65029ec454a4533e3d26a0dcf9b3330 | Python | 2,158 | 65 | # Mossy layer at 0 deg
from os.path import join
import numpy as np
import os
import pandas as pd
from library.comput_utils import cal_hd_np
from library.params import ParamsHolder
from library.shared_vars import sim_results_dir
from library.utils import save_pickle
from library.simulation import simulate_SNN
analysis... |
c6c2db6920ef95050881919ff873ab4088db51901f16787e7c8944a954f89911 | Python | 2,158 | 88 | import sys
import collections
from scipy import stats
import math
import os
#factor = 1
def cal_RT_value(mutations, factor):
dict_file = collections.defaultdict(lambda :0)
with open(mutations) as f:
for line in f:
line = line.strip('\n').split('\t')
if len(line) == 1:
continue
else:
chrID = line... |
cf856c8d0b41d2b0756eccf4cfede54049889f32fa0246505943ddbf720165af | Python | 2,158 | 64 | # Custom RESNET based on RCAN and SRGAN Code
import keras
import model_builder
# === ResNet ===
def _get_spatial_ndim(x):
return keras.backend.ndim(x) - 2
def _get_num_channels(x):
return keras.backend.int_shape(x)[-1]
def _conv(x, num_filters, kernel_size, padding='same', **kwargs):
n = _get_spatial_ndi... |
d887b1b8b76040617f7d860235f480c46bfafee6a8fd7f40d8b8cfbccf2abf7e | Python | 2,158 | 56 | """Wrapper to enforce the proper ordering of environment operations."""
import gym
from gym.error import ResetNeeded
class OrderEnforcing(gym.Wrapper):
"""A wrapper that will produce an error if :meth:`step` is called before an initial :meth:`reset`.
Example:
>>> from gym.envs.classic_control import ... |
df13add661c278b710257b61bbcf0c3bb6f114a7b2e182709cf41452d09485d9 | Python | 2,158 | 80 | import numpy as np
import scipy
import scipy.spatial
# calculate dihedral angles defined by 4 sets of points
def get_dihedrals(a, b, c, d):
b0 = -1.0*(b - a)
b1 = c - b
b2 = d - c
b1 /= np.linalg.norm(b1, axis=-1)[:,None]
v = b0 - np.sum(b0*b1, axis=-1)[:,None]*b1
w = b2 - np.sum(b2*b1, axis... |
2ed6051d2d5c862abcee6b8d188cca71653b1664d0062e5437ebebe2f7688a11 | Python | 2,160 | 60 | import time
import pandas as pd
from keras import models, layers, optimizers, backend as K
from keras.callbacks import EarlyStopping
import numpy as np
import tensorflow as tf
import optuna
# Load datasets
def load_data(path, skip_cols=5, drop_pattern='EEE', target_cols=(3,5)):
data = pd.read_csv(path, d... |
c75f4bee6522413af2cd24e3161f26adbe85781ee3cc3948bd761e978ca00631 | Python | 2,160 | 75 | import numpy as np
import sympy as sp
from scipy.integrate import odeint
from . MarkovModel import MarkovModel
from . import common
from numba import njit
class LinearModel():
"""
A simple linear model which mocks some of the functions in MarkovModel.
Used for testing and debugging.
"""
n_par... |
746db12535848d1731c8a4ece40ec31723613b9d3eed42a904869615f9b21ff3 | Python | 2,162 | 82 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in July 2019
@author: Nathan de Lara <nathan.delara@polytechnique.org>
@author: Thomas Bonald <bonald@enst.fr>
"""
from typing import Optional
import numpy as np
from scipy import sparse
from sknetwork.utils.neighbors import get_degrees
def get_membership(l... |
be27be2f6f9d0105daa181f5257b16e5426afe26963bfceb243bc3eebab7f4eb | Python | 2,162 | 54 | """Every olfactor states how it reaches locomotion, rather than inheriting it.
`brute_force` selects between the two couplings of the olfactory sensor: False
feeds the turner, so the animal steers up the gradient; True suppresses that
output and only interrupts locomotion when concentration falls.
`ModuleDB.module_co... |
4747362afcfaf1e7a2986c41b6c36ac237ef3df8c9971d4fa242407fa6ba215b | Python | 2,163 | 53 | import sys
from OscopeBootstrap import qvalue
from OscopeBootstrap.create_edge_network_represention import create_edge_network_representation
from OscopeBootstrap.SyntheticDataset import GetSimISyntheticData, true_adj_matrix
from OscopeBootstrap.oscope_tf import bootstrap_hypothesis_test, get_accuracy, get_metrics_for_... |
602a0a3268acf01b600925bcb318ef81ce1be04a61514e48c267f5b79620efea | Python | 2,163 | 71 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import pytorch_lightning as p... |
e823a6750a3071c9363d012d58ab656ee33a30b5e56592c036d882e800a8c2fc | Python | 2,163 | 65 | # -*- coding:utf-8 -*-
import os
import random
import math
import copy
from tqdm import trange
import numpy as np
import predict_model
import torch
import torch.nn as nn
import torch.optim as optim
import re
class PolicyGradient(object):
""" policy gradient"""
def __init__(self, gen_loader, beta=0, score_up=... |
2cc4f198737685ae6230edb965d04e18b03adcc687e9835d36a91a1e3ffc1ba3 | Python | 2,164 | 70 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (leoxiaobin@gmail.com)
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __future... |
98dc972716b3a3b0dfbbc4b442d30c6c5fefefb95d6325d5254e488e3b2d82d6 | Python | 2,164 | 77 | from typing import Optional, Union
from anndata import AnnData
import pandas as pd
from pathlib import Path
import os
def positions(
adata: AnnData,
position_filepath: Union[Path, str] = None,
scale_filepath: Union[Path, str] = None,
quality: str = "low",
copy: bool = False,
) -> Optional[AnnData]... |
b3ebc93ec295e7cc46d8fb12f1b588b18455253a3d356b517c4f1971f020005a | Python | 2,164 | 77 | """
Helpful dataloaders.
"""
import glob
import os
import numpy as np
from skimage.io import imread
def load_data(
channel_1_dirpath=None,
channel_2_dirpath=None,
seg_channel=0,
# load_seg_outlines=False,
img_glob="*.tif",
seg_glob="*.npy",
img_reader_plugin="tifffile",
merge_cha... |
297c5925b66a479c4d329e8a981669df9556840b73ed133eeebe731ee025b6b0 | Python | 2,165 | 58 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in March 2020
@author: Nathan de Lara <nathan.delara@polytechnique.org>
"""
from typing import Optional
import numpy as np
from sknetwork.classification.base_rank import RankClassifier
from sknetwork.ranking.pagerank import PageRank
class PageRankClassifier... |
ddaeb2890b9c3ea6a04f0b016daad1a42779dea3b3237433d61b98899b49ea37 | Python | 2,165 | 81 | import pandas as pd
from . import utils
def concat_TDs(frames, re_index=True):
"""
Concatenate trial_data structures.
Supports if structs don't have the same fields, missing values are filled with nan.
Parameters
----------
frames: sequence of trial_data structs
ex: frames=[td1, td2, ... |
4404c7047da152b40f3d5344ed76a4e71cdae7584fc05a1986672a6ae6744f15 | Python | 2,166 | 67 | """
This module define the class ContactDataset_per_amino_acid to predict contact
"""
import torch
import numpy as np
from scipy.spatial.distance import pdist, squareform
from datasets_pre_processing.generic_dataset import GenericDataset
class ContactDataset_per_amino_acid(GenericDataset):
"""
FINE TUNNING ON... |
65b31da5627e1fe335a02a562487d277e8b83644d345cf721ecead517e1ecbad | Python | 2,167 | 65 | from imodelsx import submit_utils
from os.path import dirname, join
import os.path
repo_dir = dirname(dirname(dirname(os.path.abspath(__file__))))
CUSTOM_CHECKPOINTS = {
"financial_phrasebank": ["ahmedrachid/FinancialBERT-Sentiment-Analysis"],
"sst2": ["textattack/bert-base-uncased-SST-2"],
"emotion": ["... |
f49cb3fdf9d5ae5d61d1ead7cc7bc8504ff35c2f61b8ee5834d2d78a8b6633f4 | Python | 2,167 | 65 | # -*- coding:utf-8 -*-
import os
import random
import math
import copy
from tqdm import trange
import numpy as np
import predict_model
import torch
import torch.nn as nn
import torch.optim as optim
import re
class PolicyGradient(object):
""" policy gradient"""
def __init__(self, gen_loader, beta=0, score_up ... |
6083b24b93cc91a23e28b4e357e7a74f99cea81c7e40f9a6eef3271e46110c27 | Python | 2,168 | 73 | import re
import numpy as np
from imfun.external.physics import Q
from imfun.core import units
from imfun.core.units import QS
def parse_property(line):
l = line.strip().replace('"','')
name, value = l.split('\t')
values = value.split(',')
return name, list(map(str.strip, values))
def from_brackets(s... |
84f3db18a0f1362be3001cdfe96394f9ebfef69e6824fb90b9009489bfbb7c51 | Python | 2,168 | 69 | from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.layers.merging.base_merge import Merge
@keras_export("keras.layers.Add")
class Add(Merge):
"""Performs elementwise addition operation.
It takes as input a list of tensors, all of the same shape,
and returns a singl... |
4f35d0895635946fc22bd67bf86fecd85257feaefd01f58ddcf29516d3bfd7c8 | Python | 2,169 | 74 | """Phase 5(c): exception safety -- pop on exception."""
from __future__ import annotations
import pytest
import torch
import torchlens as tl
from torchlens import _state
class RaisingChild(torch.nn.Module):
"""Child that raises after entering a nested module."""
def __init__(self) -> None:
"""Init... |
25c7f3ec97579c5d2f83034e4377c11d703f8fa06f5fd1d9323743758e34ee12 | Python | 2,170 | 73 | """Tests for the curated Explore scenario catalog."""
from __future__ import annotations
import pytest
from larvaworld.portal.explore.scenarios import (
CATEGORY_ORDER,
CATEGORY_TITLES,
SCENARIOS,
scenario_by_id,
scenarios_by_category,
validate_scenarios,
)
def test_catalog_is_valid_standal... |
30df94eb38402c7de667bd2c421bd0f418102da8c828017ed9553708a1abf7f1 | Python | 2,170 | 61 | """The module describes the ``meminfo`` job metrics plugin."""
import re
from typing import Any
from galaxy import util
from . import InstrumentPlugin
from .. import formatting
from ..safety import Safety
MEMINFO_LINE = re.compile(r"(\w+)\s*\:\s*(\d+) kB")
# Important (non-verbose) meminfo property titles.
MEMINFO_... |
bd5661821f538e77a847c7a748c9e9f1007007864333b34cc3aed88579e75cbc | Python | 2,170 | 49 | import torch
import torch.nn as nn
class MMD_loss(nn.Module):
def __init__(self, kernel_type='linear', kernel_mul=2.0, kernel_num=5):
super(MMD_loss, self).__init__()
self.kernel_num = kernel_num
self.kernel_mul = kernel_mul
self.fix_sigma = None
self.kernel_type = kernel_ty... |
100cf2ab39922cff76b42b491c7bb9299bbfd29e178206a7d25b31073a2381ca | Python | 2,171 | 77 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Line(_BaseTraceHierarchyType):
_parent_path_str = "quiver.selected.marker"
... |
3f18e8aa8997b0a32420773c455c5defd3c7b36a61b607826ed2442286f32d1b | Python | 2,171 | 69 | """Smoke tests for train-mode capture APIs."""
from __future__ import annotations
import pytest
import torch
import torchlens as tl
from torchlens.options import CaptureOptions
from .conftest import TwoLayerMlp
def test_trace_train_mode_basic(two_layer_mlp: TwoLayerMlp) -> None:
"""trace backward_ready keeps ... |
59d0364ea3025103f98e82b0909f01f7c6eac504431d77c564c4d4d0b1f77ba9 | Python | 2,171 | 55 | import os
import glob
import argparse
from tqdm import tqdm
import multiprocessing
from pathlib import Path
from subprocess import check_call, CalledProcessError
# Arguments
parser = argparse.ArgumentParser(description='Build up complete dataset.')
parser.add_argument('--wsj_root', default=None, type=str,
... |
18ad5d083d7d3223ea7de072541178d885850011310bacae8d445b3fac2fa322 | Python | 2,172 | 70 | """test linking against pysam.
"""
import os
import pytest
import subprocess
import pysam
from TestUtils import LINKDIR
if not os.environ.get("PYSAM_LINKING_TESTS"):
pytest.skip("enable linking tests by setting PYSAM_LINKING_TESTS environment variable", allow_module_level=True)
def check_import(statement):
... |
3762f3db4fff1d2aab5eed4ea353a047cf627c9d29615df949232397efb02c89 | Python | 2,172 | 77 | import logging
import yaml
import copy
import argparse
from bson.objectid import ObjectId
from pymatgen.core import Molecule
from atomate.qchem.fireworks.core import FrequencyFW
from atomate.common.powerups import add_tags
from fireworks import LaunchPad, Workflow
from instance_mongodb import instance_mongodb_sei
... |
bf5307837419e45c95f57e858756d460789bf0243dab947851efdd1533a4bc2d | Python | 2,174 | 81 | """Run DTox with different seeds"""
import logging
import os
from sys import argv
import pandas as pd
import dtox
import dtox_interpret
import targettox
logging.basicConfig(format="%(levelname)s [%(asctime)s] %(message)s",
level=logging.INFO)
# constants
AO_COL = 'assay_outcome'
START_DIR = os.g... |
40724a37b8538b7331a3cb2e884af2906b155fcb2a01e239c2e787aa8c02393e | Python | 2,176 | 60 | """Microbench: O(64) linear scan vs O(1) LUT in ``AminoAlphabet.translate``.
Not collected by pytest (filename is not ``test_*``). Run explicitly to measure
the speedup on your hardware::
python tests/bench_translate_lut.py
Speedups are data- and hardware-dependent; this script reports measured numbers
rather th... |
ac9d27b68833547a731851fd865a6f22986acdf4984e97da1b4b3937344b9551 | Python | 2,176 | 69 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... |
c45a12c3824a9fa3440e55f97917bf4a0709dc8ba200691d2ddecdaabb0ca59e | Python | 2,176 | 56 | import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow import keras
from utils import DataGenerator
tf.config.experimental.enable_tensor_float_32_execution(False)
inputKeys = ["rho"]
outputKeys = ["c1"]
# Read simulation data from the prepared files
simData = np.load("data/HS.np... |
1f43e23163bcc0a135d3cd7ddf4acbf95f7cbb93c1b64cde0f47cd92dca5c2eb | Python | 2,177 | 65 | """Tests for xcp_d.utils.plotting module."""
import os
import numpy as np
import pandas as pd
from xcp_d.utils import plotting
def test_plot_fmri_es(ds001419_data, tmp_path_factory):
"""Run smoke test on xcp_d.utils.plotting.plot_fmri_es."""
tmpdir = tmp_path_factory.mktemp('test_plot_fmri_es')
prepro... |
2600e0ba433c694fbe0734b910be21c304e60f358b739beabd99542cbfee1a18 | Python | 2,177 | 49 | import unittest
from carbontracker.components.gpu.sim_gpu import SimulatedGPUHandler
class TestSimulatedGPU(unittest.TestCase):
def test_simulated_gpu_initialization(self):
handler = SimulatedGPUHandler("NVIDIA A100", 400.0)
self.assertEqual(handler.gpu_brand, "NVIDIA A100")
self.assertEqua... |
19883b2f5a4a25780ad004bbabe45240469d0fca91ebb69076411a09583a99de | Python | 2,178 | 73 | """
File: logger.py
Created: 2020/10/16
Last Changed: 2021/09/22
Author(s): M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"""
# Standard imports.
impo... |
3bc60eaa47ef7c38c3eca837f6cbc1b02a6cdc8ac256de8a64a033c5de89a496 | Python | 2,179 | 47 | from ovseg.data.DataBase import DataBase
from ovseg.data.SegmentationDataloader import SegmentationDataloader
from ovseg.data.SegmentationDoubleBiasDataloader import SegmentationDoubleBiasDataloader
from os import listdir
from os.path import join
class SegmentationData(DataBase):
def __init__(self, augmentation=... |
507b675ab8142cfd34b3a4b3bd36bd9acab074a3ab9676da3fe6c3cf106fc08a | Python | 2,179 | 57 | #!/usr/bin/env python
'''Grab all the "Sucess" examples from the database, look if any of the directories exist.
If they do, reval them and update the database'''
import sys, re, MySQLdb, os, argparse, subprocess
from MySQLdb.cursors import DictCursor
parser = argparse.ArgumentParser(description='Fix evaluation of ... |
913287d7fe0bb782d3732b9b793fe1fcdc36c5b90ccfb97e78fd80f53b834454 | Python | 2,179 | 65 | """7. Test with ICNet Pre-trained Models for Multi-Human Parsing
======================================
This is a quick demo of using GluonCV ICNet model for multi-human parsing on real-world images.
Please follow the `installation guide <../../index.html#installation>`__
to install MXNet and GluonCV if not yet.
"""
i... |
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