sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
194927b2b005670ec37b602fd0dbd680461b90afe992782ccdcdfa1d9623d89f | Python | 3,308 | 118 | import torch
from torch import nn
import math
import torch.nn.functional as F
def critic_loss(model, value_preds_batch, values, curr_e_clip: float, return_batch, clip_value: float):
"""
Computes the critic loss using the default critic loss function.
When the model is compiled via torch.compile, this func... |
31beb83e528a168f79ac164e18ef1f45c8a669294e021bd1052b1e47d37595ca | Python | 3,308 | 94 | import pathlib
import importlib.resources
from PyQt6 import uic, QtCore, QtWidgets
import pyqtgraph.exporters as pge
from ..pipeline_plot import PipelinePlot
from ..widgets import show_wait_cursor
from ...util import get_valid_filename
EXPORTERS = {
"png": ["rendered image (*.png)", pge.ImageExporter],
"sv... |
aaf6b0591fc034b9f52ddec4c504ef707e6b709e60dbcd915686c22020c99642 | Python | 3,308 | 125 | # coding: utf-8
from contextlib import contextmanager
from importlib import import_module
import os
from subprocess import check_output, CalledProcessError
import sys
import tempfile
import traceback
import urllib.request
from atropos.commands import get_command
from atropos.io import xopen
@contextmanager
def redire... |
e3a2343bfc57ba4b395960355ebd24aa9309bcc20f0848dd9d1ef3a60949f8f7 | Python | 3,310 | 61 | import numpy as np
import sys as sys
import os
from MM2SF.acsf.sfc_functions import *
def compute_ACSF(trjname=None,itype=None,irad=None,iang=None,new_format=True):
"""
Compute ACSF (Atom-Centered Symmetry Functions) based on input geometry files.
Parameters:
- trjname (str): Name of the trajectory fi... |
ce0dc3e926fdd2a3432df320fccdcf16cbd91a35a92e43e9d66e7aa10b1a07f9 | Python | 3,311 | 106 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or... |
0f0550d029245475ed68d6f07967c417d320e6f6426cecf32761328ff027421c | Python | 3,312 | 92 | """
Given a delimited flat text file, with a specified "key" column, generate an index specifying where to find
rows with a given value
This is useful for, eg, looking up all information associated with a given phenotype ID
# TODO: I should probably be embarrassed by this. Daniel can shame me later.
"""
import o... |
2f0aea2eace2b0ae0636bc80bdca335ad6bf4f7325bc10337ee8cf70a756f3cd | Python | 3,312 | 47 | import numpy as np
np.random.seed(26)
import os, torch
basedir = os.path.abspath(os.path.dirname(__file__))
os.chdir(basedir)
file_path = os.path.abspath(os.path.join(basedir, 'literature_data'))
data_path = os.path.abspath(os.path.join(basedir, 'new_data'))
# 1. drug_disease
drug_disease_co = torch.Tensor(np.loadtx... |
a31325954eb6cb3642407ab6e9a9ed6f7cbf5770924e0e0a3a03def05e81a318 | Python | 3,312 | 92 | import numpy as np
import pytest
import pandas._config.config as cf
import pandas as pd
class TestTableSchemaRepr:
def test_publishes(self, ip):
ipython = ip.instance(config=ip.config)
df = pd.DataFrame({"A": [1, 2]})
objects = [df["A"], df] # dataframe / series
expected_keys = ... |
db976912bfaffa644ee7cc6299871492f58d45a87df7d98a763954b0c104ea20 | Python | 3,312 | 92 | # -*- coding: utf-8 *-*
import numpy
#import fftw3
def applyKernel(right, dims, num_nodes, Kv, el_vol, scale=True):
"""
Apply the V kernel to momentum, with numpy fft, used for multi-threaded
processing.
"""
krho = numpy.zeros((num_nodes, len(dims)))
for j in range(len(dims)):
rr = right... |
0843455542f7f27f97d1a0f69b439875e8c748033f4e3b14fb6d48402b93ac85 | Python | 3,313 | 89 | """Script to recenter and crop T1w
Instructions
The inputs include T1w and an initial brain mask (e.g., U-Net mask), in *.nii.gz format.
The output will be a recentered and cropped T1w in the working directory.
For example, if all data is in the same folder as following:
/projects/working_dir/sub-032114
- sub-032... |
15fa2689d52dffb68c945be1fbe38dfc52b421fa7140ed096364073331046d62 | Python | 3,314 | 62 | import psycopg2
import pdb
from sqlalchemy import create_engine
import sqlalchemy.orm as orm
import os
import sys
import pandas as pd
import numpy as np
import json
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", ... |
0a5b9a08528390da74f5f614eb37ef1cca5656395db6186f0f7b65301590a159 | Python | 3,316 | 121 | # JN 2016-01-12
"""
manage spikes for data viewer
"""
import os
from .tools import debug
class SpikeManager(object):
"""
Represent spikes for data viewer
"""
def __init__(self, sign, label):
self.fnames = {}
self.openfiles = {}
self.times = {}
self.spikes = {}
s... |
43146bc404539e107697d7cd71d4b93b25ac8e33531b906f4d257445b426bdd7 | Python | 3,316 | 101 | import pdb
def years_education_convertion(field845, field6138):
if field845:
try:
field845 = int(field845)
if field845 > 0:
return field845 - 5
elif field845 == -1 or field845 == -3:
return None
elif field845 == -2:
... |
950920859809edd5e5bd690144aaf1b82973842fb56c4409e13e806ca078de7c | Python | 3,316 | 78 | import numpy as np
from mpi4py import MPI
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
import time as clocktime
################################################################
################################################################
N = 1000
frequencies = np.arange(1, 101)
ttot = 1000.
twindow, tbin = 1.0, 0.0... |
3c2ba0cf6b092e10cf54166b4a407a0b755cdbd6550d8ca1d3491c95f9a334c2 | Python | 3,318 | 75 | import pandas as pd
from rdkit.Chem import PandasTools
import torch
from pytorch_classes_and_functions import AmesDataset, DNN
from captum.attr import IntegratedGradients
from local_evaluation_functions import map_attr_to_atoms, attribution_auc
from helper_functions import string_to_int_list, dict_to_string, stri... |
14c5f17c5178594f911c4a2bdd96cd0d2481f1ff1ca4d95ade018f29519a18bc | Python | 3,319 | 77 | from Environment import *
from Parameter import *
from scipy.stats import variation
def coefficient_of_variation(csv_path, save_path, index):
fs_array = np.zeros((205, len(Stats['fst_data_name'])))
ctrl_array = np.zeros_like(fs_array)
for i in range(len(index)):
fs_file = open(os.path.join(csv_path... |
0afa0da5fdc34cd970aa7b312418d88945f2a96adb3f5f7e3e137df08545c8d3 | Python | 3,321 | 126 | """
Common plotting routines for validation figures
Designed to accompany the paper "Network-level encoding of local
neurotransmitters in cortical astrocytes" (DOI: TODO)
"""
## ------------------------------------------------------------------------ ##
## Imports
## -------------------------------------------------... |
6d9bb2d36d9fb8a80089decf00a35046bbb3e492740ed942a98e24c8ee9f81ae | Python | 3,321 | 111 | import json
import pandas
import aggregate_figures as af
import tube2
import cine
import numpy as np
import tensorflow as tf
from tensorflow import keras
from matplotlib import pyplot
import seaborn
from skimage.filters import threshold_li, threshold_isodata
def get_batch(video, idx, batch_size=8):
zone = []
i... |
3f2a5b01e707751c879bf8b8e215bcc14b35882dcf6d6624d480d8e0f8baf5c7 | Python | 3,322 | 89 | """Customized argparse classes with improved help formatting for the litpose CLI."""
import argparse
import shutil
import sys
from typing import Any
class ArgumentParser(argparse.ArgumentParser):
def __init__(self, **kwargs: Any) -> None:
"""Initialize ArgumentParser with custom formatting and epilog."""... |
c972b42f29dab81985b85f5123e3e0bc869815157a9ec6d96d745313c32bca78 | Python | 3,325 | 86 | import os
import sys
from copy import deepcopy
from trainers.bow_trainer import BoWTrainer
from evaluators.evaluator import Evaluator
from models.bow.args import get_args
from datasets.scar_bow import SCARBoW
import warnings
import datetime
from tables.generate_token_counts import count_bow_tokens
if __name__ == '__ma... |
3de53eac13bcf79b3b83d0f03f7a5a09a7bbc4a0a43c597f6dac331aac327d6e | Python | 3,327 | 91 | """Efficient sliding window implementation for tensors."""
from collections.abc import Sequence
import torch
from mrpro.utils.reshape import normalize_indices
def sliding_window(
x: torch.Tensor,
window_shape: int | Sequence[int],
dim: int | Sequence[int] | None = None,
stride: int | Sequence[int] ... |
a1bf7e7b438c0a0b3355623b48b35d92e43705f3c2d21827c8daa2add058121e | Python | 3,327 | 104 | from xml.etree import ElementTree
from os import path
import re
import json
from tensorflow.keras import utils
from collections import OrderedDict
import tensorflow as tf
from tensorflow.data import Dataset
_base = path.dirname(__file__)
FILENAME = _base + "/CVATdata/annotations.xml"
FILENAME2 = _base + "/CVATdata/ima... |
d7cd7f59cfe985e7cf719f86d7d64599dd8c112282392fd96b848795ecd7b51f | Python | 3,328 | 89 | import sys
import argparse
import numpy as np
import pandas as pd
import configparser
def compute_filter(y, field, cond):
"""
Compute filter given a field and condition
:param y: ``pandas`` ``DataFrame``; response data.
:param field: ``str``; name of column on whose values to filter.
:param cond:... |
2bc06011ee542a8585e00e93f40eed77dd3d6b3442349ab3de0eff1cd5928195 | Python | 3,329 | 118 | import pytest
from pandas.core.dtypes.dtypes import PeriodDtype
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import (
PeriodArray,
)
pa = pytest.importorskip("pyarrow")
def test_arrow_extension_type():
from pandas.core.arrays.arrow.extension_types import ArrowPeriodType
p1 ... |
4c0055db392c0bb6595e3dd68e337a38fa6d38030a72c3010fb7e6057bd4faa2 | Python | 3,330 | 138 | from typing import List
import pandas as pd
def read_qbed(filename: str) -> pd.DataFrame:
"""\
Read .qbed file.
:param filename:
Path to the qbed file.
:Returns:
pd.DataFrame for the qbed file.
:example:
>>> import pycallingcards as cc
>>> qbed = cc.rd.read_qbed("https... |
49f37a8344a16f9e8935e9eaefc0a751d0a3b1f0b9ee89f40491e161c499ea0e | Python | 3,333 | 90 | import numpy as np
from scipy.interpolate import RegularGridInterpolator
import torch
def interpolate_flight_path(wind_prediction, grid_dimensions, flight_path):
'''
Interpolate the wind and turbulence (if available) prediction of the regular grid along the flight path.
Parameters
----------
wind... |
8bc2d2a831ad0354259b0c35ab4a86ca6aeed667c3987b680805f97311c0f525 | Python | 3,335 | 107 | # !/usr/bin/env python
"""
Script to convert mmCIF files to PDB format.
usage: python cif2pdb.py ciffile [pdbfile]
Requires python BioPython (`pip install biopython`). It should work with recent version of python 2 or 3.
@author Spencer Bliven <spencer.bliven@gmail.com>
"""
import os
import sys
import argparse
import l... |
e34d84e8de716ef58c2e79bb41f638245ba524b458fbebedf698177dd8e70fef | Python | 3,336 | 109 |
from tensorflow import keras
import math
import numpy as np
from skimage import transform, util
class ImageSeq(keras.utils.Sequence):
def __init__(self, ins: np.ndarray, outs: np.ndarray, batch=32):
assert ins.shape == outs.shape
self.inputs = np.copy(ins)
self.outputs = np.copy(outs)
... |
72bc809dc3dd9093f78f7280161ddfb7a3ea53f2bd187b4af5e2d7be2598b25d | Python | 3,337 | 94 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or agre... |
b4a311c0e9fac126bce9a6d6aff2060d4c8d0de544254aa343fed57f0e8c6466 | Python | 3,337 | 72 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import json
import time
import openmc
from utils.mcsimulation_tetris import *
from env_config import *
#=========================set values below==========================
num_sources = 1 # the number of radiation sources to place.
shape_na... |
829e51a10c60d4117fb604096331fe2b4e6cbf809395544a5095f3426b3f7c53 | Python | 3,340 | 118 | import numpy as np
import ants as an
from pathlib import Path
from deepbrain import Extractor
from scipy.stats import pearsonr
import pdb
'''
Functions for fast preprocessing of anatomical images
'''
def extract_brain(image):
'''
Brain Extraction
Parameters
----------
image: ANTs image object
... |
33b1180803cacab7a2eb1f942a65a251bd2e729b708ea81e13ddce7cc2a61561 | Python | 3,341 | 98 | import sys
import types
import pytest
import pandas.util._test_decorators as td
import pandas as pd
pytestmark = pytest.mark.single_cpu
@pytest.fixture
def dummy_backend():
db = types.ModuleType("pandas_dummy_backend")
setattr(db, "plot", lambda *args, **kwargs: "used_dummy")
return db
@pytest.fixtu... |
4140a37f7df407b73652b6ca7b11e3064283087bea3cbcac5631965b3dc67ea1 | Python | 3,344 | 93 | # Copyright 2026 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or agre... |
a08fb171061c960289207e2252e5ba4f0519a28ecedd101cb4f9280a73518a39 | Python | 3,344 | 95 | #! /usr/bin/env python
##############################################################################
## DendroPy Phylogenetic Computing Library.
##
## Copyright 2010-2015 Jeet Sukumaran and Mark T. Holder.
## All rights reserved.
##
## See "LICENSE.rst" for terms and conditions of usage.
##
## If you use this wo... |
bf525f44a759086bc6e26aa7657cb599a68f7cee5e4f387a6de306f5b421adab | Python | 3,345 | 96 |
from pyrosetta_hdf5_holograms import get_hologram
from preprocessor_hdf5_neighborhoods import PDBPreprocessor
from argparse import ArgumentParser
import numpy as np
import h5py
import sys
sys.path.append('/gscratch/spe/mpun/protein_holography/utils')
from posterity import get_metadata,record_metadata
import logging
fr... |
50b7e32dcf69c31b8f641e3a68c9455934d4b999af8183b5a426a18aefdfd872 | Python | 3,346 | 91 | import numpy as np
gregory_omega = np.array([
np.array([5.00000000000000000000e-01]), #k=0
np.array([4.16666666666666666670e-01, #k=1
1.08333333333333333330e+00]),
np.array([3.75000000000000000000e-01, #k=2
1.16666666666666666670e+00,
9.58333333333333333330e-0... |
3667d89341184322525fff32e51cc2ca6dca62e9853e53c2cb8ed68974cdd7e7 | Python | 3,349 | 102 | """
Tests for offsets.CustomBusinessDay / CDay
"""
from datetime import (
datetime,
timedelta,
)
import numpy as np
import pytest
from pandas._libs.tslibs.offsets import CDay
import pandas as pd
import pandas._testing as tm
from pandas.tests.tseries.offsets.common import assert_offset_equal
from pandas.tse... |
4201a68d23f5c6f51e54d97ee92b8c72724023e7a4bfc95dc379ab20a623e720 | Python | 3,351 | 120 | import torch
from isaacgym.torch_utils import *
@torch.jit.script
def my_quat_rotate(q, v):
shape = q.shape
q_w = q[:, -1]
q_vec = q[:, :3]
a = v * (2.0 * q_w ** 2 - 1.0).unsqueeze(-1)
b = torch.cross(q_vec, v, dim=-1) * q_w.unsqueeze(-1) * 2.0
c = q_vec * \
torch.bmm(q_vec.view(shape[0... |
50cbdee905359e8aaa8fd797e1394c064930f14e143d1a60c24c9e7fb0777ae6 | Python | 3,351 | 121 | # -----------------------------------------------------------------------------
# @brief:
# The logger here will be called all across the project. It is inspired
# by Yuxin Wu (ppwwyyxx@gmail.com)
#
# @author:
# Tingwu Wang, 2017, Feb, 20th
# -----------------------------------------------------------... |
8af225f41a49a73c992d47aebaa59a0b162a1dedeee395a0e65a47c620997b45 | Python | 3,353 | 92 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# Filename: model_performance.py
# Author: Alessandro Gerada
# Date: 2023-03-16
# Copyright: Alessandro Gerada 2023
# Email: alessandro.gerada@liverpool.ac.uk
"""Test the performance of a saved model on a set of colony images. Use model_performance.py -h for help."""
... |
cc9e42c93d129d416dc8a5db981b79d2a3fccc37599450fd95b65a6c9d74e19a | Python | 3,354 | 104 | import pytest
import torch
from mrpro.operators import ProximableFunctional, ProximableFunctionalSeparableSum
from mrpro.utils import RandomGenerator
class Dummy(ProximableFunctional):
"""Only for testing purposes."""
def __init__(self, prox_scale: float = 1.0):
super().__init__()
self.dummy ... |
21bbe52874ca98cf575563052607c0151a9703a409c1f2216c9d9b1bcc5a7d5a | Python | 3,355 | 105 | # -*- coding: utf-8 -*-
"""
Train the linear regression model & get the results for table S1
Created on Fri Apr 22 16:16:27 2022
@author: jeanbaptiste
"""
import copy
import time
import json
import uuid
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import tensorflow.keras
# sys.path.in... |
0dfabd59ef5f087a44bb4d428b536c5eb6a13c69c73907a34a6e65b498628570 | Python | 3,356 | 89 | import numpy as np
import random
import os
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
import time
import sklearn.linear_model
from sklearn.model_selection import train_test_split
from sklearn.linear_model import Perceptron, LogisticRegression
import... |
206a6f9619e31783e75da05333ea52c2c1c580074c95c8c4c1a35cb17ea277ea | Python | 3,357 | 79 | """Command line interface for the qc command.
"""
from atropos.commands.cli import (
BaseCommandParser, parse_stat_args, configure_threads, positive, int_or_str,
writeable_file)
class CommandParser(BaseCommandParser):
name = 'qc'
usage = """
atropos qc -se input.fastq
atropos qc -pe1 in1.fastq -pe2 in2... |
2bc0681647e6cf3c33b1d028f7b9945bb2ca2400f65c9372c6053544fa875184 | Python | 3,357 | 92 | import distributed
# import fasteners
# import redis
import yaml
import os
import warnings
if 'ISF_DISTRIBUTED_LOCK_CONFIG' in os.environ:
config_path = os.environ['ISF_DISTRIBUTED_LOCK_CONFIG']
with open(os.environ['ISF_DISTRIBUTED_LOCK_CONFIG'], 'r') as f:
config = yaml.load(f)
else:
warnings.war... |
99ba08be04251886e7955bae6b7edeb0ce57e4296cef832c1f9a6fa36399576f | Python | 3,357 | 127 | from initialization.initialization import *
from initialization.config import *
import numpy as np
import pandas as pd
import os
import matplotlib.pyplot as plt
import plotly.graph_objects as go
plt.rcParams.update({
"figure.facecolor": (1.0, 1.0, 1.0, 1.0),
"axes.facecolor": (1.0, 1.0, 1.0, 1.0),
"... |
ad787011bbabcb59686fe93181f27a16b0b6446b71698e1b0069128ac4e08486 | Python | 3,358 | 115 | import tensorflow as tf
from tensorflow.keras import Model
from tensorflow.keras.layers import Activation, Add, Dense
class Critic(Model):
"""
Critic
===============
Attributes:
units (list): list of the numbers of units in each layer
n_quantiles (int): number of predicted quantiles
... |
68ce6f578c0630d0a1c360838177617109e63acc26b280f826fce7f600d6b79d | Python | 3,359 | 82 | # Copyright 2018-2024 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or... |
9c26f2b4c4daa3ef928f646960743d4cb5a442525f8b97342304a9e44244565e | Python | 3,359 | 96 | #---------------------------------------------------------------------72
#---------------------------------------------------------------------72
# COMPUTE WATER FLUXES
#---------------------------------------------------------------------72
#---------------------------------------------------------------------72
# ... |
eddd72ee65b23b541fe9ef09beeab39309a35a764842f7a13a32696cac8f7269 | Python | 3,359 | 112 | import imageio
import numpy as np
import imgaug as ia
import imgaug.augmenters as iaa
import glob
import cv2
import matplotlib.pyplot as plt
import numpy as np
import re
from tqdm import tqdm
import vuba
import pandas as pd
import os
import multiprocessing as mp
import imageio
import random
import time
# Parameters --... |
efb711da493123f6127585388be3139ab0dce1086700e936f2b36c86142e2c1a | Python | 3,359 | 109 | """
.. _decoding_1d:
====================================================
Decoding the Principal Gradient
====================================================
Gradec provides .
"""
# Download HCP S1200 principal gradient
from gradec.fetcher import _fetch_gradients
gradients = _fetch_gradients(cortical=True)
####... |
11d4f74b0a7b3057bccef1c22e7761d082640b3e4b6fc716afffad3f3f1c5f85 | Python | 3,361 | 103 | """
Includes test for last_valid_index.
"""
import numpy as np
import pytest
import pandas as pd
class TestFirstValidIndex:
def test_first_valid_index_single_nan(self, frame_or_series):
# GH#9752 Series/DataFrame should both return None, not raise
obj = frame_or_series([np.nan])
assert ... |
8f3f3ac32796cf01cf25473e7617a3a392e48b4dbbf1eeff01c64e775471532d | Python | 3,361 | 112 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
def test_fillna(idx):
# GH 11343
msg = "fillna is not defined for MultiIndex"
with pytest.raises(NotImplementedError, match=msg):
idx.fillna(idx[0])
def test_dropna():
# GH 6194
idx = pd.MultiIndex.from_ar... |
4693d73a75095a0b7c17a0a76de8fc5437960ccc20e385309fc2dfc27ca53542 | Python | 3,363 | 77 | # Imports
from scipy.stats import ttest_ind
from sklearn.metrics import confusion_matrix
from sklearn.preprocessing import StandardScaler
from src.vizualization import heatmap
import numpy as np
np.random.seed(1)
import os
import matplotlib.pyplot as plt
import matplotlib.backends.backend_pdf
from sklearn.dec... |
f187b848d1f3aef384344f22996f4b5c360b0997a1894160eee6962f073a8e11 | Python | 3,363 | 88 | ###############################################################################
# This script reads pubmed ids and retrieves the title, abstract, and publica #
# tion date for each of them. The script also removes duplicates and saves the#
# results in an excel file. #
... |
b493187a56f02ece819967c015951844e7843b44218ef20e8049181fe4f62d05 | Python | 3,365 | 79 | import argparse
import multiprocessing as mp
import os
import sys
import yaml
paths = [os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), 'src')]
sys.path.extend(paths)
from src.draw import draw_angle_stimulus, draw_stimulus_proximit... |
e312ebf1143a468fedb8ca0e9c476776399a1d19bb3843ba770b3ceb3417be48 | Python | 3,365 | 95 | import sys
import os
import numpy as np
import torch
import torch.utils.data as du
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
import util
from util import *
from drugcell_NN import *
import argparse
def predict_dcell(predict_data, gene_dim, drug_dim, model_file, hidden_f... |
7e366844d41229d99e562a297e252db1871461d6feaf12c1b477238fb1d51ea7 | Python | 3,366 | 104 | import sys
import os
import configparser
from cdr.formula import Formula
X_path = sys.argv[1]
y_path = sys.argv[2]
outdir = sys.argv[3]
main_effects = sys.argv[4:]
config = configparser.ConfigParser()
config.optionxform = str
config.readfp(sys.stdin)
if 'data' in config and 'X_train' in config['data']:
X_train ... |
8c84b392850b0040f49a39e66a664d7be3656b6fff71fbd1cc596aeae693667e | Python | 3,366 | 95 | from sys import path as sys_path
sys_path.append('..')
sys_path.append('../base')
import argparse
import logging
from base import loggingUtils
from base import surfaces
from base.kernelFunctions import *
from base import surfaceMatching
from base import affineRegistration
def runLongitudinalSurface(template, targetL... |
c4c513e5bf059bfb28581bf53fddbe99e2d7d04f733c9b77c69e980784161d1b | Python | 3,367 | 111 | import io
import sys
import numpy as np
import pytest
from pandas.errors import Pandas4Warning
import pandas as pd
import pandas._testing as tm
from pandas.io.excel import ExcelFile
from pandas.io.excel._base import inspect_excel_format
xlrd = pytest.importorskip("xlrd")
pytestmark = pytest.mark.filterwarnings(
... |
338c249d6742a861950c714e34b9cd6b67ffed04b379dfc5d9b28815477595ab | Python | 3,368 | 80 | import numpy as np
import pandas as pd
import sys, os
from random import shuffle
import torch
import torch.nn as nn
from models.gat import GATNet
from models.gat_gcn import GAT_GCN
from models.gcn import GCNNet
from models.ginconv import GINConvNet
from utils import *
import pickle
from flashtorch.utils import apply_t... |
b5f360b1d1eacf332560c1e206185dac0187c47ff4c552ec1c2a356ee95f581c | Python | 3,371 | 111 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or... |
d658405ba4efed22abf87b07486182ddc0f0685d8bf5debd282573cb822b3c98 | Python | 3,372 | 101 | import numpy as np
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import IntervalArray
class TestGetNumericData:
def test_get_numeric_data_preserve_dtype(self):
# get the numeric data
obj = pd.DataFrame(
{"A": [1, "2", 3.0]}, columns=pd.Index(["A"], dtype="ob... |
924b71c70ac7592732305abb80c46001de1924666842880c1c98b4de506314d9 | Python | 3,374 | 81 | import shutil
from pathlib import Path
from ..logger._live import SimpleStep, display_enabled, live_step, quiet_hf_bars
from ..utils._files import atomic_output_path
from ..utils._hf import download_hf_file
_EXAMPLE_DATA_FILENAMES = {
"GSE130735": "GSE130735_subset.pkl",
"GSE193140": "GSE193140.pkl",
"GSE... |
9e22824e140f0ed0945fd5436768f4dba6eca80db92817562233dbb2ea4ea16d | Python | 3,375 | 113 | # Module: internal.display class
# Author: Antoni Baum (Yard1) <antoni.baum@protonmail.com>
# License: MIT
from typing import Any, Dict, List, Optional
from pycaret.internal.display.display_backend import SilentBackend, detect_backend
from pycaret.internal.display.display_component import MonitorDisplay
from pycaret.... |
589630849e7bbb2071c578e7f7713e44b545fa991dc6b6e809a24216e36b8f66 | Python | 3,376 | 100 | """Tools for managing meta-analytic results."""
import copy
import logging
import os
from nibabel.funcs import squeeze_image
from .utils import get_masker
LGR = logging.getLogger(__name__)
class MetaResult(object):
"""Base class for meta-analytic results.
Parameters
----------
estimator : :class:`... |
d299adb5da75f246974d1b571d1bf933d855c83d235120f705c4a730d297e743 | Python | 3,379 | 89 | import numpy as np
from multiprocessing import Pool, cpu_count
from discrepancy_measures import *
def permuted_ND(N, all_results, distance):
"""
Calculate the permuted ND values by shuffling the observable_results N times.
Parameters:
N (int): Number of permutations to be performed.
all_re... |
263f34ae618b75a7ffa6cd420c4aec4d0d00909a110b2695bbabc37cfdd0301e | Python | 3,380 | 87 | import pytest
import pandas as pd
@pytest.fixture(
params=[
(pd.Timedelta("0 days"), pd.Timedelta("1 day")),
(pd.Timestamp("2018-01-01"), pd.Timedelta("1 day")),
(0, 1),
],
ids=lambda x: type(x[0]).__name__,
)
def start_shift(request):
"""
Fixture for generating intervals ... |
380f15eca369970dbce0345d167edcb03bbe8bb0569d04568be1883b3d291a28 | Python | 3,381 | 86 | import argparse
import os
import shutil
from Bio import SeqIO
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='Make-Incomplete-Contigs.py',
description="""Identify long complete contigs from checkm2 scores.""")
parser.add... |
3de0e1393884e8cad59a110c00d76429f3f8c60439e38ceb439610b27f3682de | Python | 3,381 | 93 | #!/usr/bin/env python3
# to install: `pip3 install -e .`
# to install latest from pypi: `pip3 install --upgrade --upgrade-strategy eager --no-cache-dir pheweb`
# to upload to pypi: `./setup.py publish`
# to update deps: `kpa pip-find-updates`, edit, `pip3 install -U --upgrade-strategy=eager .`, test
# to test: `./setup... |
0666e2b4f5750c6b0e2c09d5959f73e037f10e4232f5e43d23bd185ef384e994 | Python | 3,382 | 87 | """
.. module:: model_manager
:platform: Linux, Windows
:synopsis: Manager for handling calling of DL segmentation models
.. moduleauthor:: Fredrik Nysjo
"""
import json
import sys
import os
import subprocess
class ModelManager:
def __init__(self):
self.modelinfo = []
self.result_filename ... |
517149f23447c3a58c2f387bead02a443034320c2ac1e5fd2f83a71835048a62 | Python | 3,383 | 100 | """Tools for managing meta-analytic results."""
import copy
import logging
import os
from nibabel.funcs import squeeze_image
from nimare.utils import get_masker
LGR = logging.getLogger(__name__)
class MetaResult(object):
"""Base class for meta-analytic results.
Parameters
----------
estimator : :c... |
5d5c0a0d496e15507bed51afb635cc0f499ec8d0f244fdba421a0175f7307677 | Python | 3,383 | 92 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Make noise convariance matrix from empty room data.
Vinding, M. C., Eriksson, A., Low, C. M. T., Waldthaler, J., Ferreira, D., Ingvar, M., Svenningsson, P., & Lundqvist, D. (2021). Different features of the cortical sensorimotor rhythms are uniquely linked to the seve... |
7e772e1d29bb5b993269ed4aafdf0f89460c2ff4415ca45dc454702123c4382c | Python | 3,385 | 128 | # ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: percent
# format_version: '1.3'
# jupytext_version: 1.14.5
# kernelspec:
# display_name: ol-connectome
# language: python
# name: python3
# ---
# %%
from pathlib import Path
import sys
impor... |
52b9e37a36483e5a47ef6cd3bce23c53541c263116e2a1ab50a256a6ec615aea | Python | 3,386 | 115 | """
common.py
Created February 17, 2021
Holds helper functions and types used throughout.
"""
from collections import Counter
from typing import Any, Callable, Dict, Iterable, Iterator, Optional, Sequence, Tuple, TypeVar, Union
from dataclasses import dataclass
import numpy as np
from numpy import mean, median
# Ty... |
6093096ef582184741180e24283522c0423b9e9b57ce017633948e52077b301d | Python | 3,388 | 82 | # Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or... |
124d31c31a69e384827398f1b68007de5c50ea06dee91004d455680c4e7521a6 | Python | 3,389 | 103 | r"""
General math utils.
"""
__all__ = ['lerp', 'normalize_tensor', 'append_value', 'append_zero', 'append_one', 'vector_cross_matrix',
'vector_cross_matrix_np', 'block_diagonal_matrix_np']
import numpy as np
import torch
from functools import partial
def lerp(a, b, t):
r"""
... |
6bdfd939a9f583dbc75813d351c46ac144acfad2ab09ccc31683b51c501917e8 | Python | 3,389 | 123 | # -*- coding: utf-8 -*-
"""
This module simply implements the `NeoPixel` class with a serial connection to
the arduino that controls the NeoPixel LED ring.
"""
import time
import warnings
import serial
class NeoPixel:
'''
Class to control the Neopixel LED ring.
Make sure the neopixels_python.ino sketch is... |
7d7fb0b59e774c678321addd194ba7e6ee22ad4c09e29ee383dbf5a05db4028d | Python | 3,389 | 119 | import os
import os.path
import hashlib
import errno
from tqdm import tqdm
def gen_bar_updater(pbar):
def bar_update(count, block_size, total_size):
if pbar.total is None and total_size:
pbar.total = total_size
progress_bytes = count * block_size
pbar.update(progress_bytes - pb... |
78c27bdab55b1eb695c5cd2ff5c5a730fde99a835b5c85a1b23cc85f26271f4e | Python | 3,393 | 84 | """Subject-wise train/test and stratified fold creation, with leakage checks.
**Documented divergence from the legacy notebook** (see
`docs/legacy-notebooks-inventory.md`, `Dataset_MRI.ipynb` step 10 and open
question 5): the notebooks used a fixed positional slice split
(`sample[:75]`, etc.) baked into row-count assu... |
3f95b05318bc8dbb86a3eb93e8c951765d7601334fb56b3bb0e7b1288bb2ef82 | Python | 3,395 | 106 | """
Tests for subclasses of NDArrayBackedExtensionArray
"""
import pickle
import numpy as np
import pytest
from pandas._libs.arrays import NDArrayBacked
import pandas as pd
import pandas._testing as tm
from pandas.core.arrays import (
Categorical,
DatetimeArray,
NumpyExtensionArray,
TimedeltaArray,
... |
92325f7fd2335c96875d3c6cb340b606c4e3034de384b1535e03f1f6f9ce6239 | Python | 3,395 | 103 | """This script creates figure 1."""
import os
import glmtools as glm
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import gaussian_kde
import lemon_plotting
from glm_config import cfg
outdir = cfg['lemon_figures']
#%% ------------------------------------------------
# Data scatter example
co... |
b4b49c9fa2a7568f32077c4f940dbc642a2f3c0e9e457360569d3ad355aefbd1 | Python | 3,395 | 114 | import os
import pandas as pd
import yaml
import numpy as np
import shutil
dataset_root = "/path/to/your/dataset"
image_root = os.path.join(dataset_root, "images")
export_root = os.path.join(dataset_root, "export")
num_clients = 4
iid = True
alpha = 0.5
seed = 0
n_classes = 4
class_names = [
"point_like_corneal_u... |
2dd9a752d2aa3c3d4046003da5d1f6f77562399d33441fd2f9a33ee6a6c00d20 | Python | 3,396 | 90 | #!/usr/bin/env python3
# type: ignore
'''
$ wget https://github.com/PheWAS/PheWAS/blob/master/data/phemap.rda
$ wget https://github.com/PheWAS/PheWAS/blob/master/data/pheinfo.rda
$ r
> load('phemap.rda')
> load('pheinfo.rda')
> write.csv(phemap, 'phemap.csv', row.names=F)
> write.csv(pheinfo, 'pheinfo.csv', row.names=... |
2ce045a9ebbd2860764402a58403d43c9f1d660ac9c373dc281bc41bd68f9165 | Python | 3,398 | 65 | import pandas as pd
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
from app import create_app, db
from app.models import Subject, SourceDataset, Visit, Condition
from load_db.ADNI imp... |
e34c828489ad4160b81bda4ba627ad5b10950388672ffb3b90ddd0e3753c8dea | Python | 3,398 | 100 | __author__ = 'etseng@pacb.com'
"""
To be used to evaluate phase switching by assuming the genome is already fully "phased".
For example, in Falcon-Unzip, which is pseudo-phased, there could be switching errors.
Since IsoPhase only uses the primary contig (or one of the haplotypes), a switching error shows up
by seein... |
4bc600ccc2a105f5c90d5b682fec223e44cea4d68571ead474673edca914ee5c | Python | 3,399 | 123 | from typing import Iterable, List, Literal, Mapping, Optional, Sequence, Tuple, Union
import matplotlib as mpl
import numpy as np
import scanpy as sc
from mudata import MuData
_method = Optional[
Literal["avginsertions", "logAvginsertions", "suminsertions", "logSuminsertions"]
]
def _adata_insertions(
mdata... |
b12175385b08d18b495e90d4e037694b86927cc98b39a5a2d8e83bd55dbc802b | Python | 3,400 | 89 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 16 20:03:05 2023
Script to download a subset of images from COS (only one image per subject).
@author: Eduardo Castro
"""
import ibm_boto3
from botocore.client import Config
from os.path import join as opj
import sqlalchemy as db
import pandas as... |
f5d05b171b0f3446f3cd99ce0e0b3d3b0e18184cc50435352a6cf4175c48c1e5 | Python | 3,402 | 104 | #!/usr/bin/python3
# post-comment.py: post standard input as a Github comment
"""
Post a Github comment.
"""
import argparse
import os
import sys
import github
def parse_args(args):
"""
Takes in the command-line arguments list (args), and returns a nice argparse
result with fields for all the options.
... |
509b888984a856f1aacf757a8de07bd4a459f402b794c8c05faef2d1b8971ed8 | Python | 3,403 | 105 | # Copyright 2025 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or agre... |
cf655a1047164fe28001266fcf5bdee350c6f024b74015c9055f3b9dd505b3a4 | Python | 3,403 | 85 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Oct 30 10:30:42 2023
@author: nrq2
"""
print("load libraries")
import os
import scenicplus
import scanpy
import pycisTopic
## 1. Initialize cisTopic object
from pycisTopic.cistopic_class import *
from pycisTopic.utils import *
from pycisTopic.lda_models... |
9dc2d878142b50cc594d8e7e5d8facc6751e2296a056f3dfc9b96e47b209a125 | Python | 3,405 | 109 | #-----------------------------------------------------------------------------
# Optimized Structure
#-----------------------------------------------------------------------------
import os
import fileinput
import sys
import DXGB.get_pdbinfo as get_pdbinfo
#### Do minimization, structure file should have hydrogen ato... |
3c8a187c8a3944170e698d20f86d5937d4ac580f6673920f9dc6d9f3eb7dc136 | Python | 3,406 | 71 | import scipy as sp
import scipy.io
import numpy as np
import pandas as pd
from tqdm import tnrange, tqdm_notebook
import matplotlib.pylab as mpl
from scipy import stats
def find_sig_bins(aucs):
auc_col_names = aucs.columns.str.contains('auc')
low_conf_col_names = aucs.columns.str.contains('low')
up_con... |
bafbfddd681ba4880625fe58cf2197e7a1b58b3b1e6ba7268728f65dc37c22cb | Python | 3,408 | 105 | import pytest
from pcntoolkit.math_functions.warp import *
def test_parseWarpString():
warp = parseWarpString("WarpLog")
assert isinstance(warp, WarpLog)
warp = parseWarpString("WarpCompose(WarpLog, WarpAffine)")
assert isinstance(warp, WarpCompose)
assert len(warp.warps) == 2
assert isinstan... |
22b09a5be3b8de674e94fea2945c21932f499db2facc1694c40228b0e50fb2f6 | Python | 3,409 | 146 | """
Engine classes for :func:`~pandas.eval`
"""
from __future__ import annotations
import abc
from typing import TYPE_CHECKING
from pandas.errors import NumExprClobberingError
from pandas.core.computation.align import (
align_terms,
reconstruct_object,
)
from pandas.core.computation.expressions import norma... |
00faf90635f9322cf2b09f185530c4e77bb0694fac5c60ebb11e6f32c0841fd5 | Python | 3,410 | 79 | import os
import sys
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.axes_grid1 import make_axes_locatable
from matplotlib import rc
from pylab import rcParams
from matplotlib.ticker import FormatStrFormatter
# the axes attributes need to be set before the call to subplot... |
2739f4233c3305feae24411fd0d7479dc3e37a2b0d57e1a1864c43aa6b4f3b41 | Python | 3,410 | 92 | import os
if 'PYTHONPATH' not in os.environ:
print("Error: Run `source env.sh` to be able to run `/scripts/*.py`")
exit(1)
import cv2
import numpy as np
# Super janky but makes backwards compatibility easier
from ecgdigitize.vision import getLinesInDirection
from ecgdigitize.visualization import *
from ecgdig... |
3af01b091ac662367d01881a13570dc827096f26aab10a1291b2196864d8e9ae | Python | 3,411 | 101 | from AYN_Package.DataSet.ForObjectDetection.VOC_nwpu import *
from AYN_Package.Task.ObjectDetection.D2.YOLO.V4 import *
from yolo_nwpu_attack.other.yolo_v4_config import *
from yolo_nwpu_attack.other.yolo_v4_helper import *
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True
import torch
import nump... |
daef3c59fc25ae73296b150d6260f73d31f488c7036ae9bccbdfa85ca549d0b8 | Python | 3,411 | 69 | from typing import Literal, Union
import pandas as pd
from med_associates_utils.session import FieldList, SessionCollection
def calculate_cumulative_events(df: pd.DataFrame, event: Union[str, list[str]], groupby: Union[str, list[str]], time_key: str = 'time') -> pd.DataFrame:
df = df.copy() # make a copy
d... |
94ba244a192f8e4c229c2f7c86b73ee28afffb478c22315de1e0aef1bf5b294b | Python | 3,412 | 94 | # Copyright 2018-2023 Xanadu Quantum Technologies Inc.
# 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 required by applicable law or... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.