sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
86ea53357e191342c4b2e30e99f6f8609da9a2acceb35249db259fbeccdf7a54 | Python | 2,054 | 75 | import numpy as np
import pytest
import pandas as pd
import pandas._testing as tm
@pytest.mark.parametrize(
"keep, expected",
[
("first", [False, False, True, False, True]),
("last", [True, True, False, False, False]),
(False, [True, True, True, False, True]),
],
)
def test_duplic... |
92dfe1d780e5872c9f8f2e3f8546264019d80b1a1c92766810f0e2d8983cb60b | Python | 2,054 | 93 | from __future__ import annotations
from typing import TYPE_CHECKING
from pandas.plotting._matplotlib.boxplot import (
BoxPlot,
boxplot,
boxplot_frame,
boxplot_frame_groupby,
)
from pandas.plotting._matplotlib.converter import (
deregister,
register,
)
from pandas.plotting._matplotlib.core impo... |
bbb1713cc1e3662d0ced53c6d5f8e0a8b3527ebf0492b3a13aeb354e193b2949 | Python | 2,054 | 42 | ###############################################################################
# This script converts the table to a network and prepares the files to the #
# gephi format #
# #
... |
963cbd9cea2c433dc893367a941b37303d52de9d56c601530d0df8743c1c9b7d | Python | 2,055 | 65 | # 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... |
c03062c17333c9b03eb4d26cff12d87fc3cf766d890fad5be7b7a3db316a6698 | Python | 2,055 | 83 | # 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... |
092166ad58da6c9dae12a691eabef0c06ab22532d5d4a4970e02573d52645291 | Python | 2,056 | 39 | import pandas as pd
import os
import sys
from pathlib import Path
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
from config.globals import ENVIRONMENT
visit_dictionary = {
... |
6f87001ca2c52e7eb20b15a9163aee86ef8f712763cbedc742eb911c75a3d5fa | Python | 2,057 | 47 | """Transparent exposure and transferred-risk calculations, without health records."""
import numpy as np
def who_band(values, cutpoints):
"""Upper-inclusive guideline bands, with -1 reserved for missing values."""
values = np.asarray(values, dtype=float)
result = np.searchsorted(np.asarray(cutpoints), val... |
7772d44d48f613b5291aa2506c4cefe819f413f684eeb37b19470753d18ff361 | Python | 2,057 | 68 | """Alembic environment.
Pulls the database URL from `pycaret_server.config.get_settings()` and the
metadata object from `pycaret_server.db.Base`, so new tables auto-appear in
``alembic revision --autogenerate``.
Override the URL for one-off ops (e.g. running migrations against a staging
DB without touching env vars) ... |
3f0edc30586c44ab39fc590dfd5e110cea4a2376c748f39669e5686ca34b1d57 | Python | 2,059 | 82 | # -*- coding: utf-8 -*-
import json
import time
import sys
import uuid
import qsub
dcc_data_path = "/projectnb/dunlop/JB/deepcellcontrol/"
dcc_repo_path = "/project/dunlop/shared_python_packages/deepcellcontrol/"
sys.path.insert(0,dcc_repo_path)
import deepcellcontrol as dcc
def params_change(params):
pri... |
a0d0c2532f023e73a8148b1e84195920054ec6cc3e42e25b3978ea09756f3770 | Python | 2,059 | 69 | import pytest
import pandas as pd
from pandas.tseries.offsets import (
BaseOffset,
Day,
Hour,
MonthEnd,
)
class TestFreq:
@pytest.mark.parametrize("values", [["0 days", "2 days", "4 days"], []])
@pytest.mark.parametrize("freq", ["2D", Day(2), "48h", Hour(48)])
def test_freq_setter(self, ... |
beff8aa0efc867e071b7f87f60ac6449948e16a003af5ff9817ae0f7f0a02583 | Python | 2,059 | 58 | #####################################################################################################################
# Date created : 10/21/2022
# Date modified: 10/21/2022
# Purpose : This program is to crate features for forward and reverse direction to next and previous Ca-Ca total 6
########... |
3ef3a99dee47fc99c1fa19e9c645976bc9e312c864ae7d30cc41b6779eefed4b | Python | 2,060 | 64 | """
.. module:: tool_manager
:platform: Linux, Windows
:synopsis: Manager for handling state of segmentation tools
.. moduleauthor:: Fredrik Nysjo
"""
from tool_common import *
from tool_brush import BrushTool
from tool_polygon import PolygonTool
from tool_livewire import LivewireTool
from tool_smartbrush impor... |
1e5b83f899e7a9ddaa1bf0eb8c5dc42dc56b9afdc0c853c1c7934a77beab5275 | Python | 2,061 | 104 | background_style = """
QMainWindow {
background: qlineargradient(x1: 0, y1: 0, x2: 1, y2: 1,
stop: 0 #000000,
stop: 0.25 #0f3460,
stop: 0.5 #000000,
stop: 0.75 #0f3460,
stop: 1 #000000);
}
"""
separator_style = """
color: #4b77be;
background-color: #4b77be;
"""
title_style... |
4777cb88482932dda199717031ff5086ece1a223a295afaa870d04d667fd9c91 | Python | 2,061 | 51 | #! /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... |
7dd88377eef260bcca9dcf44365e4e50b089606b2b11cd222eb1531ba45bc2d3 | Python | 2,061 | 48 | import sys
import os
import argparse
import pandas as pd
from cdr.data import compute_splitID, compute_partition
if __name__ == '__main__':
argparser = argparse.ArgumentParser('''
A utility for splitting a dataset into train, test, and dev sets given splitting criteria.
''')
argparser.add_argument(... |
f572bf242a1a10621b2f827c66103134471422ab6d4992f5bf81e1ffa6454660 | Python | 2,061 | 69 | ######################
### Import Library ###
######################
from rdkit import Chem
import networkx as nx
##########################
### Utilities Function ###
##########################
# smiles to mol
def mol_to_smiles(mol):
smiles = Chem.MolToSmiles(mol)
return smiles
# mol to smiles
def smiles_t... |
d974fcca24e421ca7cc91e722317c609a77113aff663bb18f132203a614c4214 | Python | 2,062 | 84 | # %%
from pathlib import Path
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from scipy.stats import pearsonr
results_dir = Path(__file__).parent.parent / "results" / "3_gf"
# %%
preds_fname = "cv-LOO_corrsign-pos_sigthresh-0.01_cvpreds.csv"
preds_df = pd.read_csv(results_dir / preds_fname... |
77009cdb85528710b116ce92bf04f38ba103e1e58e2942da68bcf0b57608412c | Python | 2,065 | 90 | # coding: utf-8
from pytest import raises
import io
from multiprocessing import Process, Queue
import time
from atropos.commands.multicore import *
class TimeoutException(Exception):
pass
log_capture_string = None
def setup():
### Create the logger
logger = logging.getLogger('basic_logger')
logger... |
0839d8aaf5ca6ae8002faf0063e4f0953aafd3ce068da8e8949921daa998be8e | Python | 2,068 | 59 | # NHE3 exchanger modules
#---------------------------------------------------------------------
# NHE3 EXCHANGER AT LUMINAL MEMBRANE OF CELL
# n is for Na, c is for Cl
# p (or prime) is for the luminal compartment (M)
# pp (or double prime) is for the cytosolic compartment (I)
#-----------------------------------------... |
14942584b15cf5ba59b737ccb8441f8dfc40ed071fcd5da558394972edf270ea | Python | 2,068 | 59 |
class RLScheduler:
def __init__(self):
pass
def update(self,current_lr, entropy_coef, epoch, frames, **kwargs):
pass
class IdentityScheduler(RLScheduler):
def __init__(self):
super().__init__()
def update(self, current_lr, entropy_coef, epoch, frames, kl_dist, **kwargs... |
ea0133e9b276f1e264364d0799f46963827f91496c7595df7e271ef68b1e3641 | Python | 2,069 | 51 | import numpy as np, matplotlib.pyplot as plt
from scipy.stats import mannwhitneyu
import pumpprobe as pp
plt.rc('xtick',labelsize=18)
plt.rc('ytick',labelsize=18)
plt.rc('axes',labelsize=18)
wt_f = np.loadtxt("/projects/LEIFER/francesco/funatlas/funatlas_intensity_map_cache.txt")
unc31_f = np.loadtxt("/projects/LEIFE... |
4240df608c99bc02ef6825f5337069cb48f3fb418a6eda7ec3e170a101fbe91d | Python | 2,072 | 65 | import pytest
import pandas.core.dtypes.concat as _concat
import pandas as pd
import pandas._testing as tm
def test_concat_mismatched_categoricals_with_empty():
# concat_compat behavior on series._values should match pd.concat on series
ser1 = pd.Series(["a", "b", "c"], dtype="category")
ser2 = pd.Serie... |
8a2892aca8a147115eac9e3b3f6f0daa188d67dcfc24fd526f6b65abfb5def45 | Python | 2,074 | 69 | """A clock may demand a preprocessing marker in ``adata.uns``.
No shipped clock uses this any more -- the cohort-relative clocks preprocess
themselves inside ``predict_age`` (see ``test_cohort_transform.py``) -- but the
mechanism stays for any future clock whose input contract cannot be satisfied
automatically, and a ... |
1c3b9781cf68690324cec9f95335385246d77d4008235400ecc155553588cb44 | Python | 2,078 | 73 | import pytest
import pandas as pd
import pandas._testing as tm
class TestSeriesDelItem:
def test_delitem(self):
# GH#5542
# should delete the item inplace
s = pd.Series(range(5))
del s[0]
expected = pd.Series(range(1, 5), index=range(1, 5))
tm.assert_series_equal(... |
c8559ca35a3ab019452701c5a04b98ff561f7d9019f5c5fcfee990070816f0bf | Python | 2,079 | 53 | import numpy as np, matplotlib.pyplot as plt, sys
import pumpprobe as pp, wormdatamodel as wormdm
plt.rc('xtick',labelsize=14)
plt.rc('ytick',labelsize=14)
plt.rc('axes',labelsize=14)
ds_list = "/projects/LEIFER/francesco/funatlas_list.txt"
funa = pp.Funatlas.from_datasets(
ds_list,merge_bilateral=Tr... |
64b8c5d23eef989f702cc4f4c51d7beeeaa772964d22c44b2ee612b8a2ddf984 | Python | 2,080 | 78 | import torch
import torch_geometric
import logging
from pathlib import Path
from tqdm import tqdm
import os
from ocpmodels import models
from ocpmodels.common import logger
from ocpmodels.common.utils import setup_logging, load_config
from ocpmodels.datasets import LmdbDataset
from ocpmodels.common.registry import regi... |
a500259674820bf6e8a52b7d2c413281e53e151afad1054c070b2c493b94f49b | Python | 2,080 | 73 | import dclab
import matplotlib.pylab as plt
# dataset
ds = dclab.new_dataset("unknown_dataset.rtdc")
# kernel density estimate
kde = ds.get_kde_scatter(xax="area_um", yax="deform")
# isoelasticity lines
isodef = dclab.isoelastics.get_default()
iso = isodef.get_with_rtdcbase(lut_identifier="LE-2D-FEM-19",
... |
0f41127c9343e8c7944eac183989b0ac9b1f0de608408a56d8235a07307d28d2 | Python | 2,083 | 73 | from datetime import (
datetime,
timedelta,
)
import pandas as pd
import pandas._testing as tm
def test_unique(tz_naive_fixture):
idx = pd.DatetimeIndex(["2017"] * 2, tz=tz_naive_fixture)
expected = idx[:1]
result = idx.unique()
tm.assert_index_equal(result, expected)
# GH#21737
# En... |
29353b9712cad398274ff147a1cab94553381163ce293c32e82ec032a2367913 | Python | 2,086 | 52 | from __future__ import print_function
vapor_version='vapor.py V1.0 12-21-2015'
def print_read_me():
print (vapor_version)
print ('Contact: Xuefang Zhao (xuefzhao@umich.edu)')
print ('')
print ('Usage: vapor.py [Options] [Parameters]')
print ('Options: ')
print (' svelter')
print (' vcf')
print (' bed')
print (... |
9a5f8e131f4109065d4bc013af9a256f518d4d8121f4382172ce8977047aefdc | Python | 2,086 | 60 | from setuptools import setup, Extension, find_packages
import sys
import numpy as np
from Cython.Build import cythonize
__author__ = "etseng@pacb.com"
version = "29.0.0"
ext_modules = [
Extension("cupcake.tofu.branch.intersection_unique",
["cupcake/tofu/branch/intersection_unique.... |
d0e4ae3c5b72d9fe9e41508ced1b449bb4070d164a5e7fb6eb711e7eb005d5b4 | Python | 2,087 | 61 | # -*- coding: utf-8 -*-
class Homopolymers(object):
"""
Class is primarily used to determine the error probabilities based on homopolymers.
"""
@staticmethod
def _default_error_function(homopolymer_length):
"""
Default/Fallback function to calculate error probabilities based on hom... |
1bc3ea9b58a3965a00ac7a9394ce3892f46dfe10cdcbd30c3f0b575eced3c204 | Python | 2,091 | 60 | import torch
from torch import nn
from torch_geometric.utils import scatter
from ..mlp import MLP
# Typing
from torch import Tensor
from typing import List, Optional, Tuple
class EdgeProcessor(nn.Module):
def __init__(self, dims: List[int]) -> None:
super().__init__()
self.edge_mlp = nn.Sequenti... |
2396e191348551adc47349b990b8c5cf2ccf1b6b5bfcfd4876f3637bbb04f898 | Python | 2,093 | 56 | import os
import cv2
import numpy as np
def _colorMap_blur_JET_(image):
# image = cv2.imread("figure/temp.jpg", cv2.IMREAD_GRAYSCALE) # imput origin image data
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
zoomScale = 0.8
# res_image = None
res_image = cv2.resize(image, dsize=None, fx... |
d8317acdea9dab86769914620f2230d371bc8fa255427d0410cfe68f2dc59551 | Python | 2,095 | 66 | # Copyright 2018-2022 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... |
08abe4c75ed52de8391d9cad961e492fdf5807367fbca1a6630ff3f7371804b8 | Python | 2,096 | 82 | import h5py
import matplotlib.pyplot as plt
import numpy as np
import sigpy as sp
from sigpy.mri import sms, retro
import os
DIR = os.path.dirname(os.path.realpath(__file__))
print('> current directory: ', DIR)
HOME_DIR = DIR.rsplit('/', 1)[0].rsplit('/', 1)[0]
DAT_DIR = HOME_DIR + '/data'
print('> data directory: ... |
163614ad430017b84ece985a5c40ffffcca3785d074dc7194baab4e7ffeb1f8e | Python | 2,096 | 81 | import json
import os
import re
from pandas.util._print_versions import (
_get_dependency_info,
_get_sys_info,
)
import pandas as pd
def test_show_versions(tmpdir):
# GH39701
as_json = os.path.join(tmpdir, "test_output.json")
pd.show_versions(as_json=as_json)
with open(as_json, encoding="u... |
43b335f5a8ba31729179f26f49d1acb42e137e5ecf6e0859b4267c1cdaaee683 | Python | 2,096 | 55 | #Run and save results of sweeps over time constants for 20 fields, for eta = 4 and epsilon = -3 (equiv to -12)
#Date written and executed: 2021-12-18
import numpy as np
from placerg.funcs import *
from placerg.funcsrg import *
from placerg.objects import *
from placerg.runfunc import *
from placerg.avafunc import *
N... |
e309d81ef1bffac5d8acf0b4323f06dae2885247c1a0d372409c4640c7ec3893 | Python | 2,096 | 63 |
import pytest
from pcntoolkit.normative_model import NormativeModel
from pcntoolkit.regression_model.blr import BLR
from pcntoolkit.regression_model.hbr import HBR
class TestNormFactory:
"""Test normative model factory functionality."""
@pytest.fixture(autouse=True)
def setup(self, temp_output_dir):
... |
e6c1a30be71ce33084f99deb28978115904fd14bb05d94694c9596781176acfc | Python | 2,096 | 60 | """
Script to prepare training csvs with pseudo-labels
"""
import shutil
import matplotlib.pyplot as plt
import pandas as pd
import os
import cv2
import numpy as np
test_path = r'data\segmentation\test'
test_list = os.listdir(test_path)
test_list = [x.lower() for x in test_list]
train_path = r'data\segmentation\trai... |
ad2d1aaafc73fba8bcf19cc049b969cac653e9e60c24223f5a16fc111ec17b0a | Python | 2,097 | 60 | import argparse
import json
import os
from typing import List
parser = argparse.ArgumentParser()
parser.add_argument("--rnng_data_root", type=str, default="rnng-pytorch/data")
parser.add_argument("--train_file", type=str, default="npcmj-train.json")
parser.add_argument("--val_file", type=str, default="npcmj-val.json"... |
dd4cdf78c7ad5878eb4d8c3e7f40aeff996375ebd4f59b15c3b5b69452efbbae | Python | 2,097 | 77 | import sys
import numpy as np
from sklearn.model_selection import train_test_split
from util.check_tools import get_input_file,check_label_config
import os
import setproctitle
setproctitle.setproctitle("DASDC")
soft_limit = 2000
hard_limit = 1500
ipt = sys.argv[1]
config = sys.argv[2]
outdir = sys.argv[3]
if os.path... |
14219fc90be28ae059e7994cdecaadeadec27b5b60345f2183beed58f6a5cecd | Python | 2,098 | 72 | # 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... |
572c2733e0e83587e4fb80822402110270dafb52dce7a7ea4d55b386ddfe10dc | Python | 2,099 | 55 | import numpy
import os
import subprocess
from distutils.core import setup, Extension
from Cython.Build import cythonize
from pathlib import Path
from typing import List
class LPCNetExtension(Extension):
"""
Extended extension class that runs the autogen.h and configure script before installing the LPCNet wrap... |
bfa76ca91a5da238c0fbcbbc5bfbc86e79089ba2d215fb24139f2e638e6b6f1e | Python | 2,101 | 54 | import pandas as pd
from src.plotting import set_r_params, set_style
import seaborn as sns
def load_worklist(path,column_names, column_name_mapping):
"""Load worklist from excel file
args:
path (str): path to excel file
column_names (list): list of column names to load
column_name_mappi... |
ffec1014cae890bb13908885da0f047153d4263405e9bb030bbccb3b0eded0cb | Python | 2,102 | 72 | '''
Script to generate a test dataset from an existing dataset with resampling and data augmentation if requested.
'''
import argparse
import windseer.data as data
# parse the command line arguments
parser = argparse.ArgumentParser(
description='Script sample a fixed dataset for model performance evaluation'
... |
c035f42b32eb0e36df0cd17b683ef7a11b51d42619ba5d0855b28ef4d0aa12a2 | Python | 2,103 | 60 | import argparse
import os
from Bio import SeqIO
def get_args():
"""
Get arguments from command line with argparse.
"""
parser = argparse.ArgumentParser(
prog='Fasta-Make-Long-Seq-Bins.py',
description="""Write fasta seqs to individual fasta files if longer than length threshhold.""")
... |
5b00488ea8591a742c7e73251096c1c34a5c78170280a05e7b8f26ea11dd2907 | Python | 2,108 | 71 | import numpy as np
import pytest
from pandas._libs.byteswap import (
read_double_with_byteswap,
read_float_with_byteswap,
read_uint16_with_byteswap,
read_uint32_with_byteswap,
read_uint64_with_byteswap,
)
import pandas._testing as tm
@pytest.mark.parametrize("read_offset", [0, 1, 7, 11])
@pytest... |
c359e87c3b2b2d7f75e46d374bc0a9cd5b4fc03a99a366ca92dad17a94cdf9d7 | Python | 2,109 | 60 | """
Test to verify that MSLL is computed correctly regardless of data scale.
This test addresses the issue where MSLL was scale-dependent because the baseline
log-likelihood was computed on unscaled Y values while the model log-likelihood
was computed on scaled Y values.
The fix ensures both are computed on the same ... |
7a66598ded7fd581caef601a0e4f48aef653f2be9984003541c7bad47473ece3 | Python | 2,111 | 74 | # JN 2015-02-09 refactoring
"""
These functions allow for fast and convenient access to clusters
"""
from __future__ import print_function, division, absolute_import
import logging
logger = logging.getLogger(__name__)
import numpy as np
def get_data_from_sessions(sorting_man, sessions,\
sign='pos', items=Non... |
d2900f6f9767d1947e3ed0d555af00a3cb2226ca9d26f247e506387365c8914a | Python | 2,111 | 59 | # 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... |
f582d25531f7f20867bd113a273dbb5e09150a437e856ca8030c15deb02bd15d | Python | 2,112 | 60 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for GCPNet (https://github.com/BioinfoMachineLearning/GCPNet):
# ----------------------------------------------------------------------------------------------... |
2f9a35d7f13357e4ab56c160b9e6f59bb714080b8eff7a0a62dc59c02380650c | Python | 2,113 | 65 | from pandas.core.internals.api import make_block # 2023-09-18 pyarrow uses this
from pandas.core.internals.concat import concatenate_managers
from pandas.core.internals.managers import (
BlockManager,
SingleBlockManager,
)
__all__ = [
"Block", # pyright:ignore[reportUnsupportedDunderAll]
"BlockManage... |
c39e61c62232d350e427ea69a04faef484909aa956cea6870ec7eace66e7ec4b | Python | 2,113 | 79 | # -*- coding: utf-8 -*-
from itertools import product
import numpy as np
import pytest
from emcee import moves
from .test_proposal import _test_normal, _test_uniform
__all__ = [
"test_normal_gaussian",
"test_uniform_gaussian",
"test_normal_gaussian_nd",
]
@pytest.mark.parametrize("mode,factor", produ... |
234096c8bc19202c32f02929b02eee69e4e559a4ed51240173ffb29060bba3e8 | Python | 2,117 | 78 | from setuptools import find_packages, setup
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
long_description += "\n\n"
with open("README.md", "r", encoding="utf-8") as fh:
long_description += fh.read()
extras = {
"all": ["dm-reverb", "flappy-bird-gymnasium"],
"rever... |
cea4d9370d6a27047ef21c3a740fcce01c3f5e6daa885fe2d68482d52092e8cc | Python | 2,117 | 59 | import torch
import pandas as pd
import copy
import itertools
from pytorch_classes_and_functions import AmesDataset, DNN, do_training
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
#store parameters and auc in lists for each hyperparameter combination
parameter_list = []
auc_list = ... |
0198e743ab9a636e623358b9508022a3e79e1260abe35e365fdeef6afd68b74e | Python | 2,119 | 46 | from matplotlib import pyplot as plt
from matplotlib import pyplot as plt
import math
import os
import numpy as np
import scipy as sc
import pylab as pl
import seaborn as sns
from scipy.stats import ranksums
import random
def plot_hcc1395_recall():
fig, ax = plt.subplots(1, 1, figsize=(4, 4))
size = 0.2
... |
4b515e43b0280aadc5aab29a8a984bb82a28364523a8f41b72063d6357c54cac | Python | 2,119 | 50 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
4f561d4dab5546fb0009624094e0a5ec5b6d759b7d0e67259864b5fc8ec22c44 | Python | 2,119 | 74 | """
Three Gaussians spread along the diagonal of a six-dimensional hypercube.
This coding style for the integrand is the simplest but also gives the
slowest runtime. Compare performance with faster.py and fastest.py.
"""
from __future__ import print_function # makes this work for python2 and 3
import vegas
impor... |
910c361c9a8872129972f266884e02e0953df01ab943b28cd2a8cd59356c6048 | Python | 2,119 | 75 | import os
import pandas as pd
from matplotlib import pyplot as plt
import os
import numpy as np
def plot_denovo_number():
val_dict = {
"debreak_SURVIVOR": 8269,
"debreak_Jasmine": 10597,
"cuteSV_SURVIVOR": 5831,
"cuteSV_Jasmine": 12074,
"SVision_SURVIVOR": 6813,
"... |
6938fa4b4de5da1a1ab6059657464f659a919126298d22c627376d0ba5c1d5e2 | Python | 2,120 | 66 | import sys
sys.path.append('.')
import time
from CommonSystem.MessageReceiver.ExchangeMessageManagement import ExchangeMessageManagement
from CommonSystem.Config import Config
from OperationSystem.operationOperator import operationOperator
from OperationSystem.AnalysisProcess.AnalysisController import AnalysisC... |
9b6353065794009ad9595277094f497a9fdefa933f2f8fdad861c74484884988 | Python | 2,120 | 70 | from os.path import join
import sys
import argparse
import json
import h5py
import VINNA.utils.misc as misc
from VINNA.utils.load_config import get_config
from VINNA.train import Trainer
def setup_options():
# Training settings
parser = argparse.ArgumentParser(description='Segmentation')
parser.add_argu... |
174eea24d4a6c24e2a3e352e0c9e13925443d62ea7991c495a6ec1b53639fab2 | Python | 2,121 | 47 | 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
from config.globals import ENVIRONMENT
... |
4823e60518a1f7a9dca601ebf21b7f0e5efaf73c2f583151824c0e624fd26efb | Python | 2,121 | 49 | # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/01_data.ipynb (unless otherwise specified).
__all__ = ['canonicalize_with_dict', 'generate_buchwald_hartwig_rxns']
# Cell
from rdkit import Chem
from rdkit.Chem import rdChemReactions
# Cell
def canonicalize_with_dict(smi, can_smi_dict={}):
if smi not in can_smi_di... |
bbc961439ddc9cc9839e6865ea94f6e908d00557fbb4884d9390090932187cc9 | Python | 2,122 | 45 | # SmoothGrad
from .guided_backprop import get_guided_backprop
from .grad_cam import get_grad_cam
from .guided_grad_cam import get_guided_grad_cam
from .guided_ig import get_guided_integrated_grads, compute_grads
from .integrated_grads import get_integrated_grads
from .vanilla_grad import get_vanilla_grad
from ..utils.p... |
eb1c927376d8e268e1d1c09e4740874bc33214444866f7eb24bdb9c22b7c9c92 | Python | 2,122 | 92 | """Module for zernikegram convention"""
from typing import Iterable,List,Dict
import numpy as np
channel_ordering = ['C','N','O','S','H','SASA','charge']
def channel_freq_to_ind(
channel: str,
freq: int,
channels: Iterable[str]=channel_ordering,
freqs: Iterable[int]=np.arange(21)
) -> int:
"""Ge... |
8c705a7ccf8618a764f51e182e51affa7447e44470441e98751093b5541381e5 | Python | 2,123 | 68 | import setuptools
import codecs
import os.path
def read(rel_path):
here = os.path.abspath(os.path.dirname(__file__))
with codecs.open(os.path.join(here, rel_path), 'r') as fp:
return fp.read()
def get_version(rel_path):
for line in read(rel_path).splitlines():
if line.startswith... |
bb65b87507572cb3caf06a2a21a40e16c6fc08c4c9c5cf64db743ebd0683dfca | Python | 2,123 | 74 | import torch
import torch.nn as nn
from copy import deepcopy
class BlockRegularization(nn.Module):
def __init__(self, args):
super(BlockRegularization, self).__init__()
self.regs = []
for a in args:
self.regs.append(a)
def forward(self, net: nn.Sequential):
reg = 0... |
245f8caff1c9102f6c900d050636d56d2f0da15e55e3b3f5d62744d518e438b4 | Python | 2,125 | 54 | import numpy as np
import pandas as pd
from immupute_dis import immupute_dis
def tfidf(ATAC):
O = 1 * (ATAC > 0)
tf1 = O / (np.ones((O.shape[0], 1)) * np.log(1 + np.sum(O, axis=0))[np.newaxis,:])
idf = np.log(1 + O.shape[1] / (1 + np.sum(O > 0, axis=1)))
O1 = tf1 * (idf[:, np.newaxis] * np.ones((1, O.sh... |
72e040f9244e44703f7cfa4b439840e5b12bf39b325c23c96aaa37a81f4f022f | Python | 2,128 | 71 | import vegas
import numpy as np
from outputsplitter import log_stdout, unlog_stdout
import gvar as gv
dim = 20
x0list = np.array([
5 * [0.23] + (dim - 5) * [0.45],
5 * [0.39] + (dim - 5) * [0.45],
5 * [0.74] + (dim - 5) * [0.45],
])
@vegas.batchintegrand
def f(x):
ans = 0
for x0 in x0list:
... |
db8ed95a08594307cd48a9d5e333b4b8e2aa02d5df22a2f61a058442ab2a5c5e | Python | 2,129 | 65 | #%%
from src import estimator
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import RBF
import numpy as np
def test_estimator_gpr_kernel_none():
gpr_expected = GaussianProcessRegressor()
gpr = estimator.GPR(kernel=None)
assert gpr.kernel == gpr_expected.... |
83850a3351b5bbb6072d74355b25827a4c7a6b95e47f52092da702d0e56c1b9a | Python | 2,130 | 45 | import numpy as np, matplotlib.pyplot as plt
import pumpprobe as pp
plt.rc("xtick",labelsize=18)
plt.rc("ytick",labelsize=18)
plt.rc("axes",labelsize=18)
'''funa = pp.Funatlas(merge_bilateral=True)
RID, ADL, URX, AWB = funa.ai_to_head(funa.ids_to_i(["RID","ADL","URX","AWB"]))
act_conn = np.loadtxt("/projects/LEIFER/f... |
8e117545b0abd9386ad37411f2e0083048a4ef18f228438ed5924763d5da3d1d | Python | 2,130 | 54 | # -*- coding: utf-8 -*-
import json
SYNTHESIS_ERROR_JSON = "config/error_sources/synthesis.json"
STORAGE_ERROR_JSON = "config/error_sources/storage.json"
SEQUENCING_ERROR_JSON = "config/error_sources/sequencing.json"
class ErrorSource(object):
def __init__(self, process=None, config_file=None):
"""
... |
4681716308498f14441b1fac59bc185fcbc1306f7b2287c73a36fd776946c19c | Python | 2,131 | 53 | import os
import json
import concurrent.futures
import time
from collections import defaultdict
# 提取permission ，并统计频次
# 此处的filename传入的是反编译后的apk文件名
# 遍历提取每个文件的permission并存储
# 写多线程
# 多进程 一次处理20个 开16进程：
permission_frequency = {} #统计所有权限出现的频次
apkfilename = [] #带绝对路径的文件名列表
path = r'E:\pythonProject\Experiment\... |
478825b0613dbdea93a512d6d03d547a24bff2ed44cd2aac2518733514180f72 | Python | 2,131 | 76 | import numpy as np
import pandas as pd
from pandas import DataFrame
try:
from pandas.core.construction import extract_array
except ImportError:
extract_array = None
class DataFrameAttributes:
def setup(self):
self.df = DataFrame(np.random.randn(10, 6))
self.cur_index = self.df.index
... |
9d2e1f36236c733cf2c9d6930f72ad1388a20f2b688430aa191bbe8a06f880cd | Python | 2,131 | 92 | import os
import sys
import time
from multiprocessing import Pool
import h5py
import matplotlib.pyplot as pl
import numpy as np
import emcee
sys.path.append(os.path.abspath(os.path.join(__file__, "..", "..", "..")))
# import acor
def lnprobfn(p, icov):
return -0.5 * np.dot(p, np.dot(icov, p))
def random_cov... |
7ab49da583d0746b961ead1b23a2a925aada4e5e8cabbcee86615d69b6521ffb | Python | 2,133 | 77 | import numpy as np
import torch
from sequence_models.convolutional import ByteNetBlock, ByteNet, ConditionedByteNetDecoder, \
HierarchicalCausalConv1d, MaskedCausalConv1d
if torch.cuda.is_available():
device = torch.device('cuda')
else:
device = torch.device('cpu')
b = 5
d = 8
ell = 7
k = 3
dil = 2
block ... |
4f65c95475e242b04baa8f480c3bda711c94615371881abf586842ac5ec3f6cf | Python | 2,134 | 52 | import time
from ApplicationProcess.BasicAppProcess import BasicAppProcess
from psychopy import core, event
class AppdisplayProcess(BasicAppProcess):
def __init__(self) -> None:
super().__init__()
def run(self):
escape_key = 0
while escape_key == 0:
... |
88afad58c0eed0a9582591c300052d11f2d8a269f7ae43b0fcd4383bd3455f8f | Python | 2,134 | 46 | # -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import numpy as np
import json
import time
import openmc
from utils.mcsimulation_square import *
from env_config import *
#=========================set values below==========================
num_sources = 1 # the number of radiation sources to place.
a_num = ... |
3e380dcbe3e7631159fb93f411122a2a326ee6ea4be403763b8a837ed82ebc0c | Python | 2,136 | 61 | import logging
from pathlib import Path
import click
from dotenv import find_dotenv, load_dotenv
import mlflow
from train_model import load_data
from evaluation import summarize_per_seqlens
import glob
def get_last_models(exp_name, run_id=None):
exps = mlflow.search_runs(experiment_names=[exp_name])
if run_id... |
adb1bf40e88aef687a01533da314c470a576664f6a242ac1c9f90e28f4ed88c7 | Python | 2,136 | 49 | import torch
from torch_geometric.data import Data
from graphite.nn import bond_angles, dihedral_angles
class MolData(Data):
def __inc__(self, key, value, *args, **kwargs):
if key in {'edge_index', 'bnd_index', 'aux_bnd_index'}:
return self.x_atm.size(0)
if key in {'ang_index', 'bnd_a... |
f3dd78e97872c55fda283369b2c3e2bd4fccf64716c9dbb7adde0f16ed58c29c | Python | 2,136 | 67 | #-----------------------------------------------------------------------------
# Vina Features
#-----------------------------------------------------------------------------
import os
import fileinput
import sys
def runVina(fn, protpdbqt, ligpdbqt):
"""Run modified AutoDock Vina program with Vina score and 58 fea... |
ca46ec5b57ddb0652ffbc7ae36ab5c69e381aa5b561e64b85e4fdc4a5f1c6540 | Python | 2,137 | 66 | #!/usr/bin/env python
synopsis = "\n\n usage: format_OrthNetEdges_4SIF.py <input.clustered.edges>\n\
\n\
1. Input\n\
- expect the format same as the '*.clustered.edges' file generated by 'create_ortholog_network.py'.\n\
- i.e. <clusterID>, <queryID>, <subjectID>, <CLtype_fwd>, <CLtype_rev>, tab-delimited.\n\
2. O... |
1ad9aad4fcca0376626f7f97713a1ba336e573c5554fdcd892846f36793e1bfd | Python | 2,138 | 75 | import sys
import os
from ._version import get_versions
class Versions_cached:
def __init__(self):
self._git_version = None
self._conda_list = None
self._module_version = None
self._hostname = None
@staticmethod
def _get_module_versions():
out = {}
for ... |
d32b3f82f6bc69efb58b553a534b6d59362350f96524d65b4a6b63b3836a32ec | Python | 2,138 | 87 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun May 14 08:11:31 2023
@author: tomas
"""
import numpy as np
import glob
import random
import pathlib
import math
from matplotlib import pyplot
from skimage.io import imshow
from matplotlib.patches import Ellipse
from sklearn import decomposition, clust... |
a805f17a586e99147192b195f3b5ecdf66785732139b7d4dac5a633934b1014b | Python | 2,140 | 64 | __all__ = [
"AminoAcidInfo",
"AminoAcidCollection",
]
import os
from dataclasses import dataclass
from typing import Dict, Mapping, Optional
from ...util.io.yaml import load_yaml
from ..common.elements import ElementCollection, ElementComposition
@dataclass(frozen=True)
class AminoAcidInfo:
name: str
... |
8018898c47a0c11ca668b1107c416c4b2dcc8bf7532faf310f8f398d61738b7b | Python | 2,141 | 66 | """Text extraction tools."""
import logging
import os.path as op
import pandas as pd
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
from ..utils import get_resource_path
LGR = logging.getLogger(__name__)
def generate_counts(text_df, text_column="abstract", tfidf=True, min_df=50, max_d... |
879c0cdb4afb3ff43c09c62fc7f71dd7faf95384111ce0246640c5e4f5e3cc4f | Python | 2,141 | 82 | #!/usr/bin/env python
from __future__ import print_function
import argparse
import windseer.nn.models as models
import windseer.utils as utils
import numpy as np
import time
import torch
import os
import gc
parser = argparse.ArgumentParser(
description='Script to plot a prediction of the network'
)
parser.ad... |
18c5dc8a566ceace766f336de3202227adb9299438c435208efde63ba3740336 | Python | 2,142 | 46 | # Copyright (c) 2018-2023, NVIDIA Corporation
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of condit... |
b7e0ab185bc49f883c34c7e191c5d83fbe938623af572ff5ca0f459c71e0ee27 | Python | 2,142 | 65 | import torch
from torch.utils.data import Dataset, DataLoader
from torch.distributions.bernoulli import Bernoulli
import numpy as np
torch.manual_seed(0)
# stationary bandit
class StationaryBbs(Dataset):
def __init__(self, n_samples, n_actions, lamada):
super().__init__()
self.n_samples = n_sampl... |
311039b247981d23cf79a9da90b341fe68b65f7ff440ddcdcfd2811da9c558ad | Python | 2,143 | 44 | """PyTest fixtures for signal models."""
import pytest
# Shape combinations for signal models
SHAPE_VARIATIONS_SIGNAL_MODELS = pytest.mark.parametrize(
('parameter_shape', 'contrast_dim_shape', 'signal_shape'),
[
((1, 1, 10, 20, 30), (5,), (5, 1, 1, 10, 20, 30)), # single map with different contrast ... |
a837d0bb31ef3a3245afbfe45ecd20a0dccf3c33c358d2bd917c7f1abe600fd1 | Python | 2,143 | 81 | import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sys
import matplotlib.ticker as ticker
import matplotlib.transforms as transforms
from pathlib import Path
#set font
plt.rcParams['font.family'] = 'Gargi'
#create figure
fig, ax = plt.subplots()
#import data
dataSheet = sys.argv[1]
#p = P... |
acd56a8c3f47e093c6ff6a45679e318d4c8ea37619a30a3603b96ebe190aa38d | Python | 2,144 | 62 | import numpy as np, shutil, os
import pumpprobe as pp, wormdatamodel as wormdm, wormbrain as wormb
ds_tags = None
ds_exclude_tags = "inx1"
ds_list = "/projects/LEIFER/francesco/funatlas_list.txt"
dst_main = "/projects/LEIFER/francesco/funatlas/exported_data_full/"
# Load Funatlas for actual data
funa... |
88be541c19132695cece01854033723bfdc79b5c8b39b6f204df1b22ee6b4df1 | Python | 2,145 | 77 | #%%
from src.config_handler import read_yaml, get_entry
from src.step_factory import StepFactory
class PipelineRepresentation():
"""
A class representing a pipeline with a name, description, and steps.
Attributes:
-----------
name : str
The name of the pipeline.
description ... |
a8bf201293df3e02cb479895b53f01f01c2ecb98f42efd05e656eb44c738fe31 | Python | 2,145 | 62 | """Remap command for the lightning-pose CLI."""
import argparse
from pathlib import Path
from textwrap import dedent
from typing import Any
def register_parser(subparsers: Any) -> argparse.ArgumentParser:
"""Register the remap command parser."""
# Choose documentation link depending on whether we're being im... |
d1644fb21b8e9fdea78332de3e653ca17bd7a8d02947bbd088c0337c2a2384c7 | Python | 2,145 | 64 | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Get ROI time course from ROI.
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 severity of specific sympt... |
5717373e36d60d6f10f3bcda61704bba3083b657968d4d1439d718d7174b36f2 | Python | 2,146 | 88 | import re
from typing import List, Optional
from nltk import Tree
def _remove_wrapper(tree: Tree) -> Tree:
tree = tree[0]
return tree
def _remove_thematic_role(tag: str) -> str:
tag = re.sub(r"([^-]+?);.*", r"\1", tag)
return tag
def _remove_func_tags(tag: str) -> str:
if tag == "multi-senten... |
b965ab93aba7cc60f9f2d76964afb3cf6d08cbf759e3b83237b033b14df59d27 | Python | 2,147 | 43 | _chained_assignment_msg = (
"A value is being set on a copy of a DataFrame or Series "
"through chained assignment.\n"
"Such chained assignment never works to update the original DataFrame or "
"Series, because the intermediate object on which we are setting values "
"always behaves as a copy (due t... |
0b8c175d19b9e145e887bf2eb95f1869f2dea9daf681cd8f2f59dc7967c62860 | Python | 2,148 | 71 | # 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... |
a6c562227af80ba6e01bfe2c6bd1d81cf09406194403400ebae1847cb05e3a0e | Python | 2,150 | 50 | """Run native compatibility tests with explicit parent installation guards.
Run from a source checkout. --installed requires that checkout to have no
in-place extensions, imports the installed package before pytest collection,
and verifies that every subprocess test derives that same installation.
"""
import argparse... |
35a09c7160bd6c3af34367e7a952fde1bbcf8eeefc52c8af5fcde388fdd5aac9 | Python | 2,151 | 64 | from Bio import AlignIO
####bonobo de novo gene regions
idx = AlignIO.MafIO.MafIndex("panpanY.mafindex", "mPanPan1.dip.20221111.chrY_onto_X.maf", "mPanPan1.chrY")
multiple_alignment1 = idx.get_spliced(
[28075448,28076422,28077214,28077861],
[28075528,28076556,28077296,28078641
],
1
)
idx = AlignIO.MafIO.... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.