sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1c4cd0dd12f00a08cfd451b8f1d65ab0216a98ecb831716b14ccf3bd668ddb07 | Python | 838 | 25 | """
Test for issue 388:
https://github.com/Data-Centric-AI-Community/data-profiling/issues/388
"""
import pytest
from data_profiling.controller import console
def test_issue388(get_data_file, test_output_dir):
console_data = get_data_file(
"titanic.csv",
"https://raw.githubusercontent.com/datasci... |
7704b757d56027821162bd92c079005af73332c3bd2bf98f3a6379db7f90b8c0 | Python | 838 | 38 | # -*- coding: utf-8 -*-
import sys
from pathlib import Path
# vtkplotlib isn't zip safe and I have no intention of trying to make it so.
# Hence, using __file__ instead of (super slow) pkg_resources is fine.
from vtkplotlib import __file__ as _init_path
DATA_FOLDER = Path(_init_path).with_name("data")
MODELS_FOLDE... |
8d452080a71209840fcd940b7af20aebc111e164a7bd9fd90de6228bbe95c9aa | Python | 840 | 30 | #!/bin/python
import sys
from collections import defaultdict
def count_vids(list_path):
counts = defaultdict(lambda: 0)
with open(list_path, 'r') as f_list:
for path in f_list:
with open(path.strip(), 'r') as f:
for vid in f:
counts[vid.strip()] += 1
... |
daf18fe87d87d5fa88b929be29d6d1aeb46ffab3fc92b80c8824bda8299a1e0b | Python | 840 | 24 | from typing import Any, Callable
from data_profiling.report.presentation.core.item_renderer import ItemRenderer
from data_profiling.report.presentation.core.renderable import Renderable
from data_profiling.report.presentation.core.toggle_button import ToggleButton
class Collapse(ItemRenderer):
def __init__(self,... |
f84adf961e975aa850eb13df45ee1308b3d1d9275c85be414da4bfe516c31b01 | Python | 840 | 35 | import os
from typing import Optional
import click
from ci.ray_ci.automation.update_version_lib import (
get_current_version,
update_file_version,
)
@click.command()
@click.option("--new_version", required=True, type=str)
@click.option("--root_dir", required=False, type=str)
def main(new_version: str, root_... |
9414ea966a88957b7a3783a7c3d5d8cc371b4d118e5c14d73f319eb9b584e585 | Python | 842 | 31 | from os import path
def paragraphs(document):
start = 0
for token in document:
if token.is_space and token.text.count("\n") > 1:
yield document[start:token.i]
start = token.i
yield document[start:]
def unique_terms(entities):
seen = set()
ents = []
for item in... |
81ea74290365dbebbaf872628f76151b843cdbf7faa73dcae31ae257ea9ff053 | Python | 843 | 28 | import numpy as np
def sample_n_k(n, k):
"""Sample k distinct elements uniformly from range(n)"""
if not 0 <= k <= n:
raise ValueError("Sample larger than population or is negative")
if k == 0:
return np.empty((0,), dtype=np.int64)
elif 3 * k >= n:
return np.random.choice(n, k... |
c73d822a0ca23bb2a368ba8d105723b9868bbe032378060abdbb1133e8327418 | Python | 843 | 19 | from model_dummy_1 import expected_output as expected_output_1
from model_dummy_1 import input_dummy as input_dummy_1
from model_dummy_1 import snn as snn_1
from model_dummy_2 import expected_output as expected_output_2
from model_dummy_2 import input_dummy as input_dummy_2
from model_dummy_2 import snn as snn_2
from m... |
86978346437f3c8c118bdbda19ee9f478728a79c8d31668f1b4315dfc719925b | Python | 844 | 31 |
import os
import argparse
import numpy as np
import torch
parser = argparse.ArgumentParser(description='')
parser.add_argument('--aptnn', type=str, default='aptnn.torch', help='File name of the trained committee nnp (default: aptnn.torch)')
args = parser.parse_args()
# Note: This is just to gather information, no n... |
5a6a360e8e254f3e909f56964faf708c71b5eab1c8d019ae42064da3518b7dba | Python | 848 | 31 | #!/usr/bin/env python
# coding: utf-8
import torch
import torch.nn as nn
from Actor1 import init_weights
class Actor(nn.Module):
def __init__(self, OBS_DIM, ACTION_DIM, TARGET_DIM, RNN_SIZE, FC_SIZE, RNN):
super().__init__()
self.OBS_DIM = OBS_DIM
self.ACTION_DIM = ACTION_DIM
... |
3ef3188493eb8f8ff72e28c1278c51caa8afadb187b532f9cd8dd3ecf623967b | Python | 849 | 29 | import sys
import pytest
from ci.ray_ci.linux_container import LinuxContainer
def test_get_docker_image() -> None:
assert (
LinuxContainer("test")._get_docker_image()
== "029272617770.dkr.ecr.us-west-2.amazonaws.com/rayproject/citemp:test"
)
def test_get_run_command() -> None:
command ... |
b20af91a9acc918ab88a22dcb742fe6a37be0c722e5d78b84ddba3d8f03e9c5b | Python | 850 | 29 | import numpy as np
import pandas as pd
import sklearn
from sklearn.model_selection import train_test_split
import time
import tensorflow as tf
import sys
from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_v... |
6533818ac8c8394a3e0edeaff1ac3a5745d508bd9635c5c13d45d69ef1954f5a | Python | 851 | 16 | import case1,sys
from case1 import *
case1.rng=np.random.default_rng(5); rng=case1.rng
TS=[float(x) for x in sys.argv[1].split(',')]; nmul=int(sys.argv[2])
idx=[NAMES.index(k) for k in FREE["M2"]]
T=[];E=[];SE=[]
import time;t0=time.time()
while time.time()-t0<200:
p=TRUE+rng.normal(0,0.6,10); p[9]=np.log(0.7); p[8... |
c0710ea97d9c99e8bd35a57603cf9f97bb3fbbdda84eb876e3a72e3fe32fbd08 | Python | 851 | 30 | """Pure-Python port of mcRigor (Hou & Li, Nat Commun 2025).
Reference
---------
Hou X, Li JJ. *Rigorously detecting dubious metacells in single-cell genomics.*
Nature Communications 16, 5236 (2025).
https://doi.org/10.1038/s41467-025-63626-5
Original (R + Rcpp) implementation: https://github.com/JSB-UCLA/mcRigor
Thi... |
c09598785c39f22716c07063fe6706aea1659372d7e5273aa200076a155cd691 | Python | 851 | 32 | import pathlib
import sys
import glob
import pandas as pd
cleaned_path = sys.argv[1]
out_path = sys.argv[2]
outliers = sys.argv[3]
file_list = glob.glob(cleaned_path)
outlier_list = outliers.split(',')
# specify the missing preproc scans
failed_list=['sub-jgrAesAWc21L_ses-1_task-rest_acq-EPI_run-1_bold', 'sub-212_ses... |
d56c7ad0e4dd8d890473c94fcee92e26c2b76c1dbb451584f08d4cd66deb3d19 | Python | 853 | 19 | # Copyright 2023 The HuggingFace Team. All rights reserved.
#
# 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 applicabl... |
468223dd4210a59f9c8b8a2c56e313377281d4b93c51fbb72d0df2971cff1533 | Python | 855 | 31 | from __future__ import annotations
"""
Lightweight PDF extractor using PyMuPDF (fitz) if available.
Falls back to a clear error if dependency is missing.
"""
from pathlib import Path
from typing import List, Tuple
def extract(path: Path) -> List[Tuple[str, str]]:
"""Extract text from a PDF file into markdown c... |
cb1ac649b547774d4f34d03f168136333de7ec2de96fb87db45e70c5a5e0ce10 | Python | 856 | 31 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -------------------------------------------------------------------------
# Created By : Kangjoo Lee (kangjoo.lee@yale.edu)
# Last Updated: 08/06/2024
# -------------------------------------------------------------------------
# Imports
import h5py
import os
import glo... |
ed4864547f4070aeaf666929d867631de5b8457eb32d754d933e6f125c4ccc1a | Python | 856 | 12 | from .setrunparameters import setRunParameters
from .mmutils import (findPointDensity, gencmap, createProjectDirectory, readMat, embeddingFolder,
embeddingSuffix, loadProjections, saveProjections, loadTrainingSet,
loadEmbeddings, loadWatershed)
from .motionmapper import (run_... |
869c5b5d11d539fcd11b8f88140fe29b735cdb0735ff9937719b5c234792cdd9 | Python | 857 | 16 | from .logger import get_caller_name, log_img_scale, print_colored_log
from .memory import AvoidCUDAOOM, AvoidOOM
from .process_debug import process_debug_mode
from .setup_env import (register_all_modules, setup_cache_size_limit_of_dynamo,
setup_multi_processes)
from .typing_utils import (ConfigT... |
ccf7faecdd585609a3b2ce102c904ae841584d5b0c3a18c7ecf71b1e64b9e690 | Python | 857 | 26 | import torch
import torch.nn
from convex_optim_base.optim_base import SingleDirectSolveProblem, BatchParallelDirectSolveProblem
def single_direct_solve(problem: SingleDirectSolveProblem,
verbose: bool = False,
**kwargs) -> float:
with torch.no_grad():
solv... |
01016d87e2cea5657a852156613428e55878c8994f9a6b34bc19cdea6f48843a | Python | 858 | 33 | """Noisy Networks
See http://arxiv.org/abs/1706.10295
"""
import torch.nn as nn
from pfrl.nn.noisy_linear import FactorizedNoisyLinear
def to_factorized_noisy(module, *args, **kwargs):
"""Add noisiness to components of given module
Currently this fn. only supports torch.nn.Linear (with and without bias)
... |
25e3f13c0c5dfd4a3255d9cec2cfec4408eb540272bad91e11059cc3c52e08fb | Python | 858 | 27 | import numpy as np
import torch
from ..utils import common_functions as c_f
from ..losses.large_margin_softmax_loss import LargeMarginSoftmaxLoss
class ArcFaceLoss(LargeMarginSoftmaxLoss):
"""
Implementation of https://arxiv.org/pdf/1801.07698.pdf
"""
def __init__(self, *args, margin=28.6, scale=64,... |
6273e335486b0dfba0497957773c1c1b9f35bb2516797c2d8f9281e57b1fc308 | Python | 858 | 27 | default_scope = 'mmdet'
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=50),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', interval=1),
sampler_seed=dict(type='DistSamplerSeedHook'),
visualization=dict(typ... |
b1091511037bccbc10cfd24435bea59d94e11e7efc1831af898a104eaaef5cf0 | Python | 858 | 20 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
606955c91e105c9561adf3eddd8fadab8d7f55f5d85e0bc1db0b7ba9713d2835 | Python | 859 | 35 | # flake8: noqa
accuracy = 42
# __keras_hyperopt_start__
from ray import tune
from ray.tune.search.hyperopt import HyperOptSearch
import keras
def objective(config): # <1>
model = keras.models.Sequential()
model.add(keras.layers.Dense(784, activation=config["activation"]))
model.add(keras.layers.Dense(1... |
dba53373fd6df44a72e7138e8238c05cb626c68a49425a2074d8a04bcbbdc47a | Python | 859 | 26 | from siapy.entities import SpectralImage
from siapy.utils.images import blockfy_image, calculate_image_background_percentage, spy_merge_images_by_specter
# Merge VNIR and SWIR images
vnir_image = SpectralImage.spy_open(header_path="vnir_data.hdr")
swir_image = SpectralImage.spy_open(header_path="swir_data.hdr")
merge... |
2342359da92b1749e058187ed921c783b3a408ec68b6aba4c07390e39196c82b | Python | 860 | 36 | from typing import Tuple
import torch
import torch.nn as nn
class FlipDims(nn.Module):
def __init__(
self, flip_x: bool = False, flip_y: bool = False, swap_xy: bool = False
):
super().__init__()
self.flip_x = flip_x
self.flip_y = flip_y
self.swap_xy = swap_xy
def ... |
6f7052aabcc4b1cb8b25e879d783e5cda2c3a82ca5c1b246a9f93202c31c70c6 | Python | 860 | 34 | """Contains skorch-specific exceptions and warnings."""
from sklearn.exceptions import NotFittedError
class SkorchException(Exception):
"""Base skorch exception."""
class NotInitializedError(SkorchException, NotFittedError):
"""Module is not initialized, please call the ``.initialize``
method or train ... |
93ff230f037e71a282ad7af467034611b12b3a88a53b898d05efe4eb7a5fc189 | Python | 860 | 48 | # flake8: noqa
# fmt: off
from ray import serve
@serve.deployment
def f(*args):
return "Hi there!"
serve.run(f.bind())
# __prototype_code_start__
import requests
response = requests.get("http://localhost:8000/")
result = response.text
# __prototype_code_end__
assert result == "Hi there!"
# __production_co... |
574b9a7aad793a29e26ee9d02ff7e5c609cb1ccc7f2a3a0930d42dfdce8d2b26 | Python | 862 | 35 | from samri.pipelines.glm import l1, l1_physio, seed
PREPROCESS_BASE = '/usr/share/samri_bidsdata/preprocessing'
def test_l1(tmp_path):
l1(PREPROCESS_BASE,
mask='mouse',
match={'session': ['ofMaF'], 'acq':['EPIlowcov']},
out_base=tmp_path,
workflow_name='l1',
)
# Takes too long or hangs
#def test_physio():... |
3fae88b436c0dd800230c06d7de6862f87d643329ae924c071d1e076c80aacaa | Python | 863 | 29 | """Test workflow parser utility functions."""
import argparse
import pytest
from tedana.workflows.parser_utils import check_tedpca_value
def test_check_tedpca_value():
"""Test the check_tedpca_value function."""
with pytest.raises(argparse.ArgumentTypeError):
check_tedpca_value("hello", is_parser=Tr... |
32bf9aebe9026d765c9886f6f8b9c4bdd9c6303c274f6c201df87779eb49efb5 | Python | 864 | 27 | default_scope = 'lqit'
default_hooks = dict(
timer=dict(type='IterTimerHook'),
logger=dict(type='LoggerHook', interval=50),
param_scheduler=dict(type='ParamSchedulerHook'),
checkpoint=dict(type='CheckpointHook', interval=1, max_keep_ckpts=1),
sampler_seed=dict(type='DistSamplerSeedHook'))
# visuali... |
409573d1e17b5a888c6be6e960e6ae390ce146db05c23a6ea49f1756858d6cc4 | Python | 864 | 39 | '''numpy-stl Sphinx configuration.'''
import datetime
from stl import __about__ as metadata
# -- Project information
project = 'numpy-stl'
author = metadata.__author__
version = release = metadata.__version__
copyright = f'2014-{datetime.date.today().year}, {author}'
# -- Extensions
extensions = [
'sphinx.ext.a... |
5346e5796c96485d4bc1b07384dcd033201fc30be62a6c806307c34e32aec5ef | Python | 864 | 35 | from abc import ABCMeta, abstractmethod
class StateQFunction(object, metaclass=ABCMeta):
"""Abstract Q-function with state input."""
@abstractmethod
def __call__(self, x):
"""Evaluates Q-function
Args:
x (ndarray): state input
Returns:
An instance of Acti... |
6317c74f391e7a48a41e9d1870f7f3c6417e8fa54987977c4aea544d7709925a | Python | 864 | 40 | import os
import sys
import gzip
import bz2
import argparse
import logging
import urllib.request
from collections import OrderedDict
def Decode(x):
"""
Decoding input, if needed
"""
try:
x = x.decode('utf-8')
except AttributeError:
pass
return x
def Open(infile, mode='rb'):
... |
152079890c3db9927a7a10f05e6c2213d08ee92f9b36649eba8c55d6bd2820bd | Python | 866 | 29 | try:
from pathlib import Path
from siapy.entities import SpectralImageSet
print("Libraries detected successfully.")
except ImportError as e:
print(f"Error: {e}. Please ensure that the SiaPy library is installed and the environment is activated.")
exit(1)
# Set the path to the directory containing... |
4c70bfd0f4bb485a16719cb9d5ce57fa3169de5af034fa7ec998622a48fed976 | Python | 868 | 32 | import logging
from collections import defaultdict
from Bio.PDB import Selection
from pokeformer.utils.pdb_utils import calc_id_model, get_biopdb_struct
import freesasa
logger = logging.getLogger(__name__)
coeff = 0.9033294541493975
intcep = 5.528451433776809
def calc_sasa(pdb_path, name="protein"):
struct =... |
e5f7abcf93a70492ac3715e822dadd3049344234abc7d60f387405cfe8855d18 | Python | 868 | 19 | #Test multinomial
import pytest
import geopandas as gpd
import pandas as pd
from shapely import geometry
from src import multinomial
def test_run(tmpdir):
#Create predictions
boxes = [geometry.box(0, 0, 5, 5),geometry.box(0, 0, 5, 5),geometry.box(0, 0, 5, 5), geometry.box(0, 0, 5, 5)]
p = gpd.GeoDataFrame... |
bc0678a9e1adb62ffd83114884e00b8305f5c5e4da59d595e39d01a19cfb1fc9 | Python | 869 | 19 | # This file is part of the INTREPPPID programme.
# Copyright (c) 2023 Joseph Szymborski.
#
# This programme is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, version 3.
#
# This programme is distributed i... |
5575fea373714ef734090f7285b28d1fbe7c27a5a98bf8ef5848bbfd0dd1e9ca | Python | 870 | 26 | """
Bypass the required registration step for higher level analyses in FSL FEAT
"""
import subprocess
import glob
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
subs = ['sub-08']
for sub in subs:
featFolders = sorted(glob.glob(f'{ROOT}/derivatives/{sub}/ses-0*/func/*bold*_trunc.feat'))... |
5a26d95fe195c4bfa25856a9ea644c5c59e8f4f96680c85977645157d41d0083 | Python | 870 | 26 | # 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... |
8a33349d055d8822435f4e328566765a67713d6e99227f05b2a9b51181b534dc | Python | 871 | 31 | # -*- coding: utf-8 -*-
# @Time :2024/6/6 20:43
# @Author :MENGLong Li
# @File :ShowHistory.py
# @Software:PyCharm
import matplotlib.pyplot as plt
def plot_results(history, EPOCHS):
# 显示 MAE
plt.figure(figsize=(10, 6))
epoch_range = range(1, EPOCHS + 1)
plt.plot(epoch_range, history.history['m... |
e3754db20a286d244b8cdcbc736ef71b871a0df0491acb1d17222efaffe94f99 | Python | 871 | 31 | #test metrics
from src import metrics
import pandas as pd
def test_site_confusion():
y_true = [0,0,1,1,1]
y_pred = [0,0,1,1,0]
site_lists = {0:[0], 1:[0]}
assert metrics.site_confusion(y_true, y_pred, site_lists) == 1
y_true = [0,0,1,1,1]
y_pred = [0,0,1,1,0]
site_lists = {0:[1], 1:[0]... |
b4f04200cfb0628822056c0f72d44cba9bdc5a3c115f16d9d13bc635673558e2 | Python | 872 | 37 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
from setuptools import setup, find_packages
from Cython.Build import cythonize
import pysam
setup(
name='svtk',
version='0.1',
description='Structural variation toolkit',
author='Matthew Stone',
author_email='mstone5@mgh.harvard.edu',
p... |
da93d7608f4c9bf742074b88df5fbfab9defa43b6c59c727d65ef0145b0414a4 | Python | 873 | 25 | from setuptools import setup
import torch.cuda
from torch.utils.cpp_extension import CppExtension, CUDAExtension, BuildExtension
from torch.utils.cpp_extension import CUDA_HOME
ext_modules = []
if torch.cuda.is_available() and CUDA_HOME is not None:
extension = CUDAExtension(
'structured_kernels', [
... |
1d96bb8401050473adf92062fdad7785f5806c0dfb21741382d1c7cc9b6bb28f | Python | 874 | 40 | import cc3d
import numpy as np
import scipy.ndimage
from cloudvolume.lib import save_images
from cloudvolume import CloudVolume, view
import time
from PIL import Image
def twod():
img = Image.open('test2d.png')
return np.array(img)[:,:,0].T
def threed():
labels = np.zeros( (480, 480, 3), dtype=np.uint8)
tmp... |
819998b6863073a0a73a8f7183a320feb7a1719f2905a1e2d2e31090b77a4027 | Python | 874 | 25 | #!/usr/bin/env python
__author__ = ""
__email__ = ""
import numpy as np
import torch
import torch.nn as nn
from typing import Union, Tuple, Optional
from torch_geometric.typing import (OptPairTensor, Adj, Size, NoneType,
OptTensor)
from torch import Tensor
import ... |
1eb89a5293a915602501c7b934f9755b43807f408dc7e8c246739d6f1b9fb124 | Python | 875 | 33 | """
Specialized API clients for DataCollect.
This module provides API clients for specialized databases including:
- BLAST: Sequence similarity searches
- JASPAR: Transcription factor binding profiles
- MPD: Mouse Phenome Database
- IUCN: Species conservation status
- PRIDE: Proteomics data repository
- cBioPortal: ... |
601caa3c2657752cd4ad9b4f798a74010e10b44ce843eec261ec0b0d1dfd1a23 | Python | 875 | 19 | import os
import torch
base_config = [
{"input_channels": 2, "cnn_channels": 128, "conv_kernel_size": 3, "pool_kernel_size": 2, "conv_stride": 1, "pool_stride": 2, "fc_padding": 1, "fv_padding": 1, "avr_pool": True},
{"input_channels": 128, "cnn_channels": 256, "conv_kernel_size": 3, "pool_kernel_size": 2, "... |
82593a188d18c0f731da739ef01ad378173fbf7c6f90fe720bf31c68d36bea0f | Python | 875 | 19 | import os
import torch
base_config = [
{"input_channels": 2, "cnn_channels": 128, "conv_kernel_size": 3, "pool_kernel_size": 2, "conv_stride": 1, "pool_stride": 2, "fc_padding": 0, "fv_padding": 1, "avr_pool": True},
{"input_channels": 128, "cnn_channels": 256, "conv_kernel_size": 3, "pool_kernel_size": 2, "... |
671c7a8ecf807bd31a402bea11961a8777e32e1aece9b2dc4ba2a081bd01e0ae | Python | 876 | 37 | import cv2
import os
import numpy as np
import argparse
import message_filters
import io
import PIL.Image
import time
from subprocess import call
if __name__ == '__main__':
'''
parser = argparse.ArgumentParser()
parser.add_argument('imgDir', type=str, default='',
help='path to data'... |
96112d7650001a115bc469e0cd29a8e5edeef5d13a7c897c70b754de9d7400bf | Python | 876 | 33 | import datetime
import logging
from ray.autoscaler._private.cli_logger import cli_logger
logger = logging.getLogger(__name__)
class LogTimer:
def __init__(self, message, show_status=False):
self._message = message
self._show_status = show_status
def __enter__(self):
self._start_time... |
f0161d1c6e78fdc92d1c7fda6422b8ae09b0686e5afb07a4997b8f216a4266bf | Python | 876 | 25 |
import gym
env = gym.make("gym_sted:PreferenceMOSTED-easy-hslb-v0")
env = gym.make("gym_sted:PreferenceMOSTED-easy-hshb-v0")
env = gym.make("gym_sted:PreferenceMOSTED-easy-lslb-v0")
env = gym.make("gym_sted:PreferenceMOSTED-easy-lshb-v0")
env = gym.make("gym_sted:PreferenceMOSTED-hard-v0")
env = gym.make("gym_sted:... |
6d619316d519cde67ba5e65c80ed55406ffc606ca189341429413f5fd8e70b91 | Python | 877 | 31 | from typing import Dict, List
import samna
from samna.speck2f.configuration import SpeckConfiguration
from sinabs.backend.dynapcnn.dynapcnn_layer import DynapcnnLayer
from .dynapcnn import DynapcnnConfigBuilder
# Inherit DynapCNNConfigBuilder to share implementation with other DynapCNN/Speck devices
class Speck2FC... |
74325b1bd0d485e50eb095171e9c6420862516453fa9d17170a928821ca6b74f | Python | 877 | 34 | import torch
import torch.nn as nn
from packaging import version
import sinabs.layers as sl
def test_repeat():
data = torch.rand((5, 100, 2, 10, 10))
conv = nn.Conv2d(2, 4, 10)
repeated_conv = sl.Repeat(conv)
output = repeated_conv(data)
alt_output = conv(data.flatten(0, 1)).unflatten(0, (5, 100)... |
a8aebfa3c9d84e8e3a16d927bbd6766d9a926af61250fbb2813b8a0394f3197f | Python | 877 | 24 | import sys
from itertools import groupby
def fasta_iter(fasta_name):
with open(fasta_name) as fh:
faiter = (x[1] for x in groupby(fh, lambda line: line[0] == ">"))
for header in faiter:
headerStr = header.__next__()[1:].strip().split()[0]#Entire line, add .split[0] for just first column... |
d827b67bbe785a1c3d9b06bcab5431d08e29472484dd6af79f6f0bbd8ae3ab46 | Python | 878 | 29 | import sys
import argparse
import vamb
parser = argparse.ArgumentParser(
description="""Command-line bin creator.
Will read the entire content of the FASTA file into memory - beware.""",
formatter_class=argparse.RawDescriptionHelpFormatter,
add_help=False,
)
parser.add_argument("fastapath", help="Path to ... |
2b45bb60e2248ff802d6b100503e5a0a4f9f24f7c56e6cd51ef55ca63a20af84 | Python | 879 | 38 | # __without_backpressure_start__
import ray
ray.init()
@ray.remote
class Actor:
async def heavy_compute(self):
# taking a long time...
# await asyncio.sleep(5)
return
actor = Actor.remote()
NUM_TASKS = 1000
result_refs = []
# When NUM_TASKS is large enough, this will eventually OOM.
fo... |
5a8f591a76738896ea06c36e21c30c398fe7abd8aedc47b2cb0c4c1c3a5deff0 | Python | 879 | 20 | ################################################################################
# -- Default set of parameters
################################################################################
from defaultParams import *
fr_chg_factor = np.array([1.0])
E_extra_stim_factor = np.array([1.0])
EEconn_chg_factor = np.aran... |
aeae91bd2f85184e5a3ad4d79af90a4e62099701b1673e2f04543e9d5dc72c2a | Python | 879 | 31 | from typing import Dict
import samna
from samna.speck2e.configuration import SpeckConfiguration
from sinabs.backend.dynapcnn.dynapcnn_layer import DynapcnnLayer
from .dynapcnn import DynapcnnConfigBuilder
# Inherit DynapCNNConfigBuilder to share implementation with other DynapCNN/Speck devices
class Speck2EConfigB... |
d4da55ff46836d67b84002c4cf880a6fb82683d37e0607efccef507031b8588a | Python | 879 | 33 | """
Test for issue 1602:
https://github.com/ydataai/ydata-profiling/issues/1602
"""
from pyspark.sql import types as T
from data_profiling import ProfileReport
def test_spark_handles_decimal_type(test_output_dir, spark_session):
from decimal import Decimal
spark = spark_session
schema = T.StructType(
... |
99369ac72abee7a54781e1d2075a53efa9d09f4967d39115a436be48f6c0e358 | Python | 880 | 35 |
class GeneralMicroscope:
"""
Implements a General Microscope. This class should be inherited
by other microscopes
"""
def __init__(self, config):
self.config = config
def get_conf_params():
return {
"p_ex" : self.config["conf-params"]["p_ex"],
"pdt" : ... |
2c0c15d340a6a912cabf42b4af5588821ebff06befbee9fad0c7bb082f865624 | Python | 884 | 21 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
4022af17b26788918ae44d510f8e1713653385277c495320f7f48c6b70f04102 | Python | 884 | 33 | from typing import Any, List, Tuple
import pandas as pd
from data_profiling.config import Settings
from data_profiling.visualisation.plot import scatter_pairwise
def get_scatter_tasks(
config: Settings, continuous_variables: list
) -> List[Tuple[Any, Any]]:
if not config.interactions.continuous:
ret... |
06816b8150cb87686979b396e1e16fa73da3cf7d7e976701e40a2fdd32eaafe2 | Python | 885 | 30 | from Bio import SeqIO
import sys, os
from itertools import imap
def is_sanger():
'''
Inspect the top read in the file and see if the quality encoding
max > 40
'''
filepath = sys.argv[1]
reads = SeqIO.parse( filepath, 'fastq' )
r1 = next( reads )._per_letter_annotations['phred_quality']
r... |
356ff41c1b7dd4bb94f421229e31b1b9ffc3e052abf88f6462853bbc56749ce9 | Python | 885 | 30 | """
==============================
Utility Function
==============================
Utility function for plots in the documentation.
"""
import matplotlib.pyplot as plt
import torch
import sinabs
def plot_evolution(neuron_model: sinabs.layers, input: torch.Tensor):
neuron_model.reset_states()
output = neuron... |
7041d1b2f14281f50788cfe5bcc19fb8af8694f899d072558292cff4052c06c5 | Python | 885 | 26 | import logging
from datetime import datetime
from agent.pipeline.review_level_mgmt import update_sentence_review_level_spo_to_check
from agent.pipeline.review_level_mgmt import update_sentence_review_level_spo_skip_validations
from agent.pipeline.review_level_mgmt import update_sentence_review_level_spo_completed
fro... |
d73e838d85375f2367a35ae1872a255b10fee11b54e96a5d6a3d1e0403d713e8 | Python | 885 | 34 | """
Test for issue 864:
https://github.com/Data-Centric-AI-Community/data-profiling/issues/864
Validate Extreme Values sub-tabs state the correct number of extreme values shown.
"""
import random
import pandas as pd
from data_profiling import ProfileReport
def test_issue864():
def random_list(n):
retur... |
66790068a727d77e64072081072e87918a6babcafaba7f91c6d5162b2b95e9a3 | Python | 886 | 26 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
81e4923e935d87d0b160a1340d83308f7295425ca7cf14e4f50ade9bad146cdc | Python | 886 | 25 | import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
parser = argparse.ArgumentParser()
parser.add_argument('-i', '--input', required=True, help='Input bedgraph.')
parser.add_argument('-c', '--chrom-sizes', required=True, help='Chromosome size file.')
parser.add_argument('-o', '--output', requ... |
b77af39dfa307ee1ee579ccd3e6523fc66da4d72f8e6339cd34450eebe9ad9f8 | Python | 887 | 30 | from PIL import Image
import numpy as np
from ctypes import *
import ctypes
import copy
import os
import cv2
import time
import pdb
import PySpin
import matplotlib.pyplot as plt
import torch
import torch.nn.functional as F
def showOn2ndDisplay(monitorNo, windowNo, x, xShift, y, yShift, array):
Lcosl... |
0c22244eb182aaa7666fa1e414f8037831dbb6b932a5893c31583d1076ed1477 | Python | 888 | 35 |
CODE_DIR = '/home/kelarion/github/'
SAVE_DIR = '/mnt/c/Users/mmall/Documents/uni/columbia/assignment_errors/'
import socket
import os
import sys
import pickle as pkl
import numpy as np
import scipy as sp
import scipy.linalg as la
import scipy.io as sio
from sklearn import svm, manifold, linear_model
from sklearn.mod... |
af5ac2a7e430c94097cfd236d0fcb734aa7c5c0893147fd84f0a758f8c132897 | Python | 888 | 32 | """Reference implementations for testing consistency and backward compatibility.
This package contains reference implementations of previously deprecated or
parametrized model components, used for testing consistency and backward compatibility
in the test suite.
"""
from .deprecated_transforms import (
cebra_tran... |
e18a42afb9c05c7d0eeacf651fb26be20a4e69807c49e06057cfdb8a5fbcbb85 | Python | 888 | 27 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
2b7eb2ee78172e8a3480ac73137170888dc3a98c3b689d5e19ae38b60eb679d8 | Python | 890 | 25 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Helper class for adding rpu_config to neural network model"""
# pylint: disable=no-name-in-module,import-error
from aihwkit.cloud.converter.definitions.i_inp... |
7a21d628248e642851f7e26ae479052135d643ce01e74cc02b8549b867bb1115 | Python | 890 | 40 | # __memray_profiling_start__
import memray
import ray
@ray.remote
class Actor:
def __init__(self):
# Every memory allocation after `__enter__` method will be tracked.
memray.Tracker(
"/tmp/ray/session_latest/logs/"
f"{ray.get_runtime_context().get_actor_id()}_mem_profile.bi... |
f0df3b0f3eb9d73623f2dd66283c1c8246acff1d908060829d069da16c6e1457 | Python | 890 | 35 | import cv2
import numpy as np
from glob import glob
from sklearn.model_selection import StratifiedKFold
import numpy as np
from sklearn.model_selection import StratifiedKFold
def threshold_at_one(x):
return x>75
def jpg_to_ndarray(path):
image=cv2.imread(path, cv2.IMREAD_GRAYSCALE)
return image
def label... |
163a8e41cee76321f41db37a5be985d5d593afbfbc3a01768dc2256a40f6be65 | Python | 892 | 37 | # __anti_pattern_start__
import ray
import numpy as np
ray.init()
def process_results(results):
# custom process logic
pass
@ray.remote
def return_big_object():
return np.zeros(1024 * 10)
NUM_TASKS = 1000
object_refs = [return_big_object.remote() for _ in range(NUM_TASKS)]
# This will fail with heap... |
30423687bf9d226fae351d53a17728904f30f78df2f51dec6d3052a8c6a19c2b | Python | 892 | 18 | """Vendored backbone-based Bonsai (upstream v1.0.0), CC BY-NC 4.0.
For datasets too large for a direct reconstruction: build a tree on a subset,
graft the remaining cells onto it, refine, repeat. Upstream's own four steps.
Modifications, all mechanical and marked ``omicverse:`` at the site:
* imports rewritten to re... |
47017a473f29df13992a8c551496ee27fe3ff325dc3fdecf43b23723992d1df9 | Python | 892 | 38 | import setuptools
import ava
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="AVA: Autoencoded Vocal Analysis",
version=ava.__version__,
author="Jack Goffinet",
author_email="jack.goffinet@duke.edu",
description="Generative modeling of animal vocalizations",
long_descrip... |
9ff12b4b587fa69a21b9e22ed51275b4aae966b4948f09dcaf180f2147c62577 | Python | 892 | 31 | from setuptools import setup, find_packages
setup(
name="chromoformer",
packages=find_packages(exclude=[]),
include_package_data=True,
version="1.1.3",
license="MIT",
description="Chromoformer - Pytorch",
author="Dohoon Lee",
author_email="dohlee.bioinfo@gmail.com",
long_description... |
aab3fb92028342efc02be16445e77015b298f015bc15ec76cc1b74589a49da20 | Python | 893 | 41 | import unittest
from rising import AbstractMixin
class Abstract:
def __init__(self, **kwargs):
super().__init__()
self.abstract = True
class AbstractForward:
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.abstract = True
class PreMix(AbstractMixin, Abstract)... |
0ad07e3d49af35535ae53076ee0f79ae04cfd458095174c6c686ce626fd0b857 | Python | 894 | 32 | """ A collection of miscellaneous tools used by the feature extractor
"""
from typing import Dict, Any
def unnest(inputs: Dict[str, Any], _prefix="") -> Dict[str, Any]:
""" Convert nested dictionaries (with string keys) to a dot-notation flat
dictionary.
Parameters
---------
inputs: The diction... |
22a0714029f4ffe2efbd5974c7d6af8edb1c7ca29bfe963e86a76aac1373c602 | Python | 895 | 39 | # flake8: noqa
# __websocket_serve_app_start__
from fastapi import FastAPI, WebSocket, WebSocketDisconnect
from ray import serve
app = FastAPI()
@serve.deployment
@serve.ingress(app)
class EchoServer:
@app.websocket("/")
async def echo(self, ws: WebSocket):
await ws.accept()
try:
... |
48bf1bdf09312e8f5b356562461df9106d0a8cbbc7b1b41c71657b2ffbbc0fe3 | Python | 895 | 27 | import logging
from datetime import datetime
from agent.data.entities.config import ROOT_LOGGER_ID
from agent.data.sql.sql_mgmt import get_connection
from agent.data.entities.item import select_last_items
from agent.crawlers.twitter_crawler import get_tweets
logging.basicConfig(format='%(levelname)s : %(message)s', l... |
9a53fb1be3e8de56ff9acaf7ae021e4c22e5853a3a9d726122eda7d3b5b9fe16 | Python | 895 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
2e179aa5a299aae493edf7d02073d377539b98ee5e180f7aa7286a8c671dd677 | Python | 896 | 26 | import re
from ipywidgets import widgets
from data_profiling.config import ImageType
from data_profiling.report.presentation.core.image import Image
class WidgetImage(Image):
def render(self) -> widgets.Widget:
image = self.content["image"]
if self.content["image_format"] == ImageType.svg:
... |
368f11e2350a8c1ee2b03aa06090787a4a465a27b1dab60128e725567ef46398 | Python | 896 | 25 | import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
parser = argparse.ArgumentParser()
parser.add_argument('-i', '--input', required=True, help='Input bedgraph.')
parser.add_argument('-c', '--chrom-sizes', required=True, help='Chromosome size file.')
parser.add_argument('-o', '--output', requ... |
3a749454774ca6632c13f074ce1e2918fffeca9c29987627997a089f0f902e4f | Python | 896 | 32 | # Generated by Django 4.1.6 on 2023-02-07 00:52
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("infer", "0012_alternategenename_alternateproteinname_go_protein"),
]
operations = [
migrations.CreateModel(
name="ProteinEmbeddin... |
af12f6209a37f3f94cf42f9e17dabeba39884f38e0d962fd2e1fc7617386934b | Python | 897 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
182af0160a4b5c3aac30346244bbf6078f0ec0cfd91ffe96182d54a1a7587053 | Python | 898 | 29 | import setuptools
# read the contents of requirements.txt
with open('./requirements.txt') as f:
requirements = f.read().splitlines()
setuptools.setup(
name = 'adrd',
version = '0.0.1',
author = 'Chonghua Xue',
author_email = 'cxue2@bu.edu',
url = 'https://github.com/vkola-lab/adrd_tool/',
... |
20da34a5966e971a79f4a343ee2918cfe0ce5e970d7dc944e6f4ac055a5c1c9f | Python | 898 | 28 |
import bpy
####################################################################################################
# @SomaReconstructionDocumentation
####################################################################################################
class SomaReconstructionDocumentation(bpy.types.Operator):
"... |
3a6101f64f437748768e2da31e8cefa8074e8b01a159d1bdb7cb62acffbc6d96 | Python | 898 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
8807e9c0528d164e404b5e39c013afcae34cccee559e004322be1f4d32e564cc | Python | 898 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
3c45e2085e42a52ffae80db9ee7bce7bf3fc0a761fbf67912f8af0aae531efea | Python | 899 | 30 | import unittest
import torch
from rising.transforms.functional import tensor_op
class TestSpatialFunctional(unittest.TestCase):
def setUp(self) -> None:
self.batch_2d = torch.arange(1, 10).reshape(3, 3)[None, None]
def test_tensor_op_tensor(self):
outp = tensor_op(self.batch_2d, "permute", ... |
8aeed3dcefd969352dca505579283997c21bd7a287f3fbabd2c0fc61842622a6 | Python | 899 | 28 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
932561f905745d8125da6c762466d8f3e9a20b02a7eea3cb5676a26f3bd69ef2 | Python | 899 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
9b751e287b99943b490659420624664c794b85788dc6c0eb740d461c10b9431c | Python | 899 | 27 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
a1ba648e746b3f8b24f777da3eef2322430755d0d633c4203dc804a81e2173f7 | Python | 899 | 26 | # -*- coding: utf-8 -*-
### -------------- IMPORTS ------------- ###
import numpy as np
from helper import features
### ------------------------------------ ###
# define metrics
metrics = ['total', 'detected', 'percent_detected',
'false_positives', 'false_positive_rate']
## define parameter l... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.