sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
159384fabafb203f02b228bf79627f2be1604d305513e1679be50717f1c95699 | Python | 1,147 | 42 | #import tensorflow as tf
import numpy as np
import math
import random
from sklearn import preprocessing
seed=1 # set a seed
np.random.seed(seed)
whole_X=np.random.uniform(0,1,(10000,28*28))
n=whole_X.shape[0]
p0=whole_X.shape[1] # the number of original variables
random.seed(seed)
art=np.array(random.sample(range(p0... |
e74e7470694b4055796409bf2a2a0ae0beaa92c99389a683af9ac39eb37f9e50 | Python | 1,147 | 40 | from pathlib import Path
pathFiles = Path('L:/promec/Animesh/Kathleen')
fileName='allPeptides.txt'
trainList=list(pathFiles.rglob(fileName))
import pandas as pd
df=pd.read_table(trainList[0], low_memory=False)
df.columns.get_loc("DP Proteins")
dfDP=df.loc[:, df.columns.str.startswith('DP')]
dfDP=dfDP[dfDP['DP Proteins... |
9d4f0fb5bcae765514eded3ffbfac505c39849cd0b69378c873a927bc7f87d3e | Python | 1,148 | 35 | import click
from .._version import version as steinbock_version
from ..classification._cli import classify_cmd_group
from ..export._cli import export_cmd_group
from ..measurement._cli import measure_cmd_group
from ..preprocessing._cli import preprocess_cmd_group
from ..segmentation._cli import segment_cmd_group
from ... |
5f388f1b19636c0c63c5d5e5093f76e270a1d5e4a346cd84570dff0cd769d9e3 | Python | 1,150 | 32 | # Copyright (c) Facebook, Inc. and its affiliates.
import torch
from detectron2.modeling import PROPOSAL_GENERATOR_REGISTRY
from detectron2.modeling.proposal_generator.rpn import RPN
from detectron2.structures import ImageList
@PROPOSAL_GENERATOR_REGISTRY.register()
class TridentRPN(RPN):
"""
Trident RPN sub... |
5c2101e3fde164a895e54ab6122d4f2ecf8a56edf7554d974d00317bbbe0a9f0 | Python | 1,153 | 34 | #python pagesDown.py <link> start end
import sys
link = sys.argv[1]
start = sys.argv[2]
end = sys.argv[3]
import os
import time
import codecs
from selenium import webdriver
from selenium.webdriver.common.by import By
options = webdriver.ChromeOptions()
options.headless = True
driver = webdriver.Chrome("/home/animeshs/b... |
d0f74c94846f03d19658c01c429260ca18c0d7bd2fcc59dab61c82d8d588acaa | Python | 1,153 | 32 | import torch
from torch import nn, Tensor
import numpy as np
class RobustCrossEntropyLoss(nn.CrossEntropyLoss):
"""
this is just a compatibility layer because my target tensor is float and has an extra dimension
input must be logits, not probabilities!
"""
def forward(self, input: Tensor, target:... |
3b1124a413c41db3bcc37b9414c1f84719693cb1b4cb2739716b0d433e3f4e5e | Python | 1,157 | 28 | # -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates.
def add_deeplab_config(cfg):
"""
Add config for DeepLab.
"""
# We retry random cropping until no single category in semantic segmentation GT occupies more
# than `SINGLE_CATEGORY_MAX_AREA` part of the crop.
cfg.INPUT.CR... |
4da8a4fbb4db5bd5a428a596793c0bd685d360ec8b24bd4be7495fda59352e9f | Python | 1,157 | 24 | import numpy as np
def get_patch_size(final_patch_size, rot_x, rot_y, rot_z, scale_range):
if isinstance(rot_x, (tuple, list)):
rot_x = max(np.abs(rot_x))
if isinstance(rot_y, (tuple, list)):
rot_y = max(np.abs(rot_y))
if isinstance(rot_z, (tuple, list)):
rot_z = max(np.abs(rot_z))... |
b72060451ea83b8d664fe3f4e02d7378fcf3fa9610cb4fdfb13d33115e9049aa | Python | 1,158 | 50 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
"""
Restraint Geometry classes
TODO
----
* Add relevant duecredit entries.
"""
import abc
from pydantic import BaseModel, ConfigDict, field_validator
class BaseRestraintGeometry(BaseMode... |
0c3e181c1865977a13fc4a169e71338ac8b12bf4a0b9274efe4d3bf3ac5afc55 | Python | 1,160 | 32 | from typing import List
import torch
from torch import Tensor, nn
from detectron2.modeling.meta_arch.retinanet import RetinaNetHead
def apply_sequential(inputs, modules):
for mod in modules:
if isinstance(mod, (nn.BatchNorm2d, nn.SyncBatchNorm)):
# for BN layer, normalize all inputs together
... |
11194c99e05bbc88a66615452cc10f189ea2f3d210b61b5221fe46ca021b646d | Python | 1,160 | 30 | import torch
from torch import Tensor
from chemprop.data import BatchMolGraph
class _BondMessagePassingMixin:
def initialize(self, bmg: BatchMolGraph) -> Tensor:
return self.W_i(torch.cat([bmg.V[bmg.edge_index[0]], bmg.E], dim=1))
def message(self, H: Tensor, bmg: BatchMolGraph) -> Tensor:
i... |
de3689ff8a7459f45631267ac1b8452c18a7a06f27b867a64edb0eafb7819dea | Python | 1,161 | 43 | from __future__ import annotations
import errno
import json
from pathlib import Path
from typing import TYPE_CHECKING, Any
from snakebids.io.yaml import get_yaml_io
if TYPE_CHECKING:
from _typeshed import StrPath
def write_config(
config_file: StrPath, data: dict[str, Any], force_overwrite: bool = False
) ... |
ecc013f246ffb4d7e8181f7eeec4016c2cb3613c04b53d99d3f30666b9040531 | Python | 1,161 | 31 | import pytest
from typing import Sequence
import numpy as np
import xarray as xr
from hsnn import ops
from ._utils import get_data
@pytest.mark.parametrize("test_input, expected", get_data('as_spike_events'))
def test_as_spike_events(test_input: dict, expected: Sequence):
spike_events = ops.as_spike_events(test... |
3ef39da7e7b8d7c423aeb6dbc7ba6310a76fc62f3ecec0d146dbbb0b3d4f5f8d | Python | 1,162 | 38 | from typing import Protocol, Type, TypedDict
class HParamsDict(TypedDict):
"""A dictionary containing a module's class and it's hyperparameters
Using this type should essentially allow for initializing a module via::
module = hparams.pop('cls')(**hparams)
"""
cls: Type
class HasHParams(Pr... |
dfbb61196c155e3a1099d30d0b37a764b7065116be673e1b930a95641423e261 | Python | 1,162 | 39 | from importlib import resources
import click
import pytest
import openfe
from openfe import SmallMoleculeComponent
from openfecli.parameters.mol import get_molecule
def test_get_molecule_smiles():
mol = get_molecule("CC")
assert isinstance(mol, SmallMoleculeComponent)
assert mol.name == ""
assert mo... |
f417edc84f571ddfe4652821fe2afa52fdedf3caa398aa97a081ea304c7aabe1 | Python | 1,166 | 33 | # Python03.py
# IJ BAR: https://github.com/tferr/Scripts#scripts
####################################################
# 3. Import Jython modules and Java classes
####################################################
# Importing a Jython module:
import math
print "[Line 09]", "Python PI=", math.pi # https://docs.python.... |
2840c396ea2f2b999a573eeeae6b92ea93c0fd65618d25ea565ceea912114765 | Python | 1,168 | 37 |
import scanpy as sc
import pandas as pd
import numpy as np
import os
import sys
sys.path.append(".../benchmark_script/evaluation/ARI_LISI/evaluation_LISI_knn.py")
from evaluation_LISI_knn import evaluate_LISI_knn
input_path = "PATH_TO_INPUT_DIR/samap_LISI_input.h5ad"
output_path = "PATH_TO_OUTPUT_DIR/samap_LISI.csv"... |
57298102d27dc19a88945399048dba6e07c73d35c0f4cad42c698995c4d2f1ac | Python | 1,174 | 39 | import numpy as np
from scipy.ndimage import binary_fill_holes
from acvl_utils.cropping_and_padding.bounding_boxes import get_bbox_from_mask, bounding_box_to_slice
def create_nonzero_mask(data):
"""
:param data:
:return: the mask is True where the data is nonzero
"""
assert data.ndim in (3, 4), "... |
d685dfd334d0f0499694ac8f9d17f906491f89f5a37420408c4125eb0cc56000 | Python | 1,174 | 50 | from django.contrib import admin
from django.contrib.auth import get_user_model
from django.contrib.auth.hashers import make_password
from import_export import resources
from import_export.admin import ImportExportModelAdmin
from .models import ResultsABX, User
# Register your models here.
class UserResource(resour... |
2816e057fcd12524e5b122354a28b715ad1c82e2f639772b2d02b401e3b9820b | Python | 1,175 | 38 | import sys
import unittest
from pathlib import Path
import numpy as np
SCRIPTS = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS))
from baseline_models import grid_search_grouped_cv
class FoldTargetScalingTests(unittest.TestCase):
def test_grid_search_can_fit_target_scaling_with... |
a6b9fec7ad4a9044199177e96ce836f2cc71613a98a1965a5a078d4528b8dbd6 | Python | 1,176 | 33 | # Copyright (c) Facebook, Inc. and its affiliates.
from __future__ import absolute_import, division, print_function, unicode_literals
import unittest
import torch
from detectron2.layers import batched_nms
from detectron2.utils.testing import random_boxes
class TestNMS(unittest.TestCase):
def _create_tensors(self... |
36d475ccca6d1c6d4133db6018ea380d2389c817dbb491a7adf83950041be4e7 | Python | 1,177 | 60 | from argparse import ArgumentTypeError
def pos_int(s):
v = int(s)
if v <= 0:
raise ArgumentTypeError('must be > 0')
return v
def n0_int(s):
v = int(s)
if v < 0:
raise ArgumentTypeError('must be >= 0')
return v
def lim_int(llim=float('-inf'), ulim=float('inf')):
def f(s)... |
a495b88cde124dcd2da637906e134a982d20946712a2252ee44645151f015da9 | Python | 1,177 | 34 | # Copyright (c) Facebook, Inc. and its affiliates.
import importlib.abc
import importlib.util
from pathlib import Path
__all__ = []
_PROJECTS = {
"point_rend": "PointRend",
"deeplab": "DeepLab",
"panoptic_deeplab": "Panoptic-DeepLab",
}
_PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent / "proj... |
ea733dd367625b8afb930f263ff1a72c26801937288abc134bf33814982ee012 | Python | 1,178 | 33 | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.poolers import ROIPooler
from detectron2.modeling.roi_heads import KRCNNConvDeconvUpsampleHead
from .mask_rcnn_fpn import model
[model.roi_heads.pop(x) for x in ["mask_in_features", "mask_pooler", "mask_head"]... |
982b2f216fffd488994a3858d9cc8d3dadfcd710617d7700f9719d30870f044a | Python | 1,179 | 43 | import os
import h5py
import numpy as np
import matplotlib.pylab as plt
from python_scripts.laminarfMRI import interpolate_axis0, find_ind
base_path = '/Users/Tommy/all/eeg-fMRI/results'
filename = 'result_raw_eeg_power.mat'
freq_sel = 'gamma'
with h5py.File(os.path.join(base_path, filename), 'r') as f:
data = ... |
44c2dc08ec2de5cf9cfab587fb80078d0b5a4ab45d89836d1340fea1a0f05bf4 | Python | 1,181 | 34 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import unittest
import torch
import detectron2.export.torchscript # apply patch # noqa
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.layers import ShapeSpec
from detectron2.modeling.backbone import build_r... |
75ef1283b572e61a6918b5d6b799276c560a11652513411e9e431c3c304d15d3 | Python | 1,181 | 38 | import argparse
import os
import lpips
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-d0','--dir0', type=str, default='./imgs/ex_dir0')
parser.add_argument('-d1','--dir1', type=str, default='./imgs/ex_dir1')
parser.add_argument('-o','--out', type=str, def... |
0b3223c2cb19eda03a4821f4a92655aa0d9c59652e417074373cd0e05bd1951f | Python | 1,182 | 48 | """Prediction and inference pipelines for molecular property prediction."""
from nfml.predict.uncertainty import (
classification_confidence,
ensemble_uncertainty,
flag_ood_molecules,
tanimoto_nearest_neighbour,
)
from nfml.predict.inference import (
graph2mol,
sample_vae_latent_space,
pred... |
b8305c6ede0d5d2e4e144414d13e8e6e0408b7b7254e91ebae13e768a3b1c798 | Python | 1,183 | 34 | import sys
import unittest
from pathlib import Path
import numpy as np
SCRIPTS = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS))
from metrics import evaluate_held_out_pv_predictions
class HeldOutMetricTests(unittest.TestCase):
def test_held_out_summaries_use_main_weight_and_do... |
d232d446ae218fbc728d39e510231be4a82442551ff27a472b2f97f799984dcc | Python | 1,185 | 42 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 29 19:27:26 2016
@author: Federico Barabas
"""
import os
from tkinter import Tk, filedialog
def getFilename(title, types, initialdir=None):
root = Tk()
root.withdraw()
# filename = filedialog.askopenfilename(title=title, filetypes=types,
# ... |
b762d23c61dec4b152e024c8222b893f36069e7e62d083f4aa97f38b5a6665ee | Python | 1,188 | 37 |
import pytest
import os
import shutil
import vtk
from brainspace.vtk_interface import wrap_vtk
from brainspace.mesh import mesh_io as mio
def _generate_sphere():
s = vtk.vtkSphereSource()
s.Update()
return wrap_vtk(s.GetOutput())
@pytest.mark.parametrize('ext', ['pial', 'white', 'orig', 'sphere', 'inflat... |
46f78eb59acaf639eadd2893e9cd4a0b2c1efb86c2fe0c95491ea2832c0748c5 | Python | 1,189 | 56 | from nilearn import plotting
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import matplotlib
matplotlib.use("Agg")
dim = (
-0.5
) # seems to be more reliable, dim=-1 was blacking out some images that had low dynamic range..
fig, (ax1, ax2, ax3) = plt.subplots(3, 1)
# original plot (... |
e7a62e7e6cab402cf5d1698948761406997272f33005581e68ee7223eb576305 | Python | 1,191 | 31 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
674f19a95650d387ca704761c88668b9e6cb68d5de1edac1de7971a53b26caf5 | Python | 1,192 | 44 | # Generated by Django 4.2 on 2024-11-13 08:17
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("abx_app", "0005_remove_user_is_first_adjustment_and_more"),
]
operations = [
migrations.RenameField(
model_name="user",
... |
97b29c961bc7d783aef8464a34b66762feb7ac9b73b4a09d56435391e9e593c1 | Python | 1,193 | 44 | ### By Anoushka Joglekar
### Modified 2019_02_27
import sys
import pandas as pd
import time
from itertools import chain
start_time = time.time()
input_file = sys.argv[1]
all_info = [x.strip('\n').split('\t') for x in open(input_file).readlines()]
iso_names = [x[0] for x in all_info]
cellsPerIso = [x[1::2] for x in a... |
9bf5c8f1c206c0dc048dc173ad9258bf577ab6858a32724d440c216d977941f5 | Python | 1,198 | 39 | from __future__ import annotations
from collections.abc import Iterable
class ConfigError(Exception):
"""Exception raised for errors with the Snakebids config."""
def __init__(self, msg: str) -> None:
self.msg = msg
super().__init__(msg)
class RunError(Exception):
"""Exception raised f... |
1402b62dec05c57cbdc345a1cba1cc262f18d71de64c27fdb5bfbad4c9d91007 | Python | 1,205 | 50 | """
Created on 10/08/2017
@author: Niklas Pallast
Neuroimaging & Neuroengineering
Department of Neurology
University Hospital Cologne
"""
import numpy as np
import os,sys
def getPar(filename):
## Open the text file.
fileID = open(filename,'r')
# Read columns of data according to the format.
fileID... |
b639ed00d137235ae6b7e9a1b9d0e4df0f515e23f384ed9cdfe8dd7b477f673e | Python | 1,205 | 34 | import numpy as np
class LambdaWarmUpCosineScheduler:
"""
note: use with a base_lr of 1.0
"""
def __init__(self, warm_up_steps, lr_min, lr_max, lr_start, max_decay_steps, verbosity_interval=0):
self.lr_warm_up_steps = warm_up_steps
self.lr_start = lr_start
self.lr_min = lr_min
... |
7fdb67c566ac61ad651f1d29511ee5a35537bada2bfcc2352e9ef7de2938973c | Python | 1,206 | 37 | # Copyright 2011-2022 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the Licen... |
9457b37050d4e0752460368a1a356e2418391e5167d7d92470a0dc4381b24fb6 | Python | 1,206 | 34 | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_fpn import model
from ..common.train import train
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone impor... |
1d7d83a608982dec484c0c30bb5cc6c77d193eea32d55485af606cdb7a9b0869 | Python | 1,209 | 33 | from pathlib import Path
# `navis.interfaces` talks to remote services, so its doctests cannot run in CI.
# Matched as a path rather than as the substring "interfaces", which would also
# swallow the tests *for* those modules (e.g. `tests/test_interfaces_base.py`).
INTERFACES = Path(__file__).resolve().parent / "navis... |
f394e3d21b3b78a41fdd1e1d7612343c36f910b6652da2fe944cf94daff3fc02 | Python | 1,209 | 42 | from __future__ import annotations
from typing import Optional
class CodeBlock:
def __init__(self, value: Optional[str | CodeBlock] = None) -> None:
self.value = self._as_str(value)
def __add__(self, other: Optional[str | CodeBlock]):
return CodeBlock(self._as_str(self.value) + '\n' + self._... |
e7f4f79e440be803a16eda133c8e3a3e31206505586f9f98b222065fea78c6ea | Python | 1,210 | 43 | from gufe import Transformation
from ..chemicalsystem_generator.component_checks import (
ligandC_in_chem_sys,
proteinC_in_chem_sys,
solventC_in_chem_sys,
)
def both_states_proteinC_edge(edge: Transformation) -> bool:
return proteinC_in_chem_sys(edge.stateA) and proteinC_in_chem_sys(edge.stateB)
de... |
d15ef26b835dc1a647f0820b1e7a332152fc14701d3345d40fc8adae9889b19e | Python | 1,211 | 36 | def convert_mhz_to_ut(nu_mhz, g_factor= 2.0023):
"""
Converts frequency in MHz to magnetic field in µT using the given formula.
Parameters:
nu_mhz (float): Frequency in MHz.
g_factor (float): Electron g-factor (default is 2.002319).
Returns:
float: Magnetic field in µT... |
fc09c8ca9054ac66ce461284b0143f8f1064faecca9d9fac220b7790fbb153e0 | Python | 1,216 | 35 | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
import sys
import torch
from fvcore.nn.precise_bn import update_bn_stats
from detectron2.checkpoint import DetectionCheckpointer
from detectron2.config import LazyConfig, instantiate
from detectron2.evaluation import inference_on_dataset
from det... |
a3f1ecde81ae8b2e4378c8f3b2905120a43a1e9942e37f3ff371c470f41aa483 | Python | 1,218 | 42 | #import tensorflow as tf
import numpy as np
import math
import random
from sklearn import preprocessing
seed=1 # set a seed
lb,ub=0.8,1 # set a lower bound and an upper bound for variation values
np.random.seed(seed)
whole_X=np.random.uniform(0,1,(10000,28*28))
n=whole_X.shape[0]
p0=whole_X.shape[1] # the number of ... |
132f4141d9377cb8fca22d310b53ade8cf6b022289d43499e80610bcd3641607 | Python | 1,220 | 36 |
import torch
import torch.nn as nn
# EEG_BiLSTM
class Model(nn.Module):
def __init__(self, input_size=128, hidden_size=128, num_layers=2, num_classes=40, dropout=0.3):
super(Model, self).__init__()
# BiLSTM
self.lstm = nn.LSTM(input_size=input_size,
hid... |
b6f94e52f857de893df1f83dab2bb363b63f932b85e48e850d98b5a42be8b522 | Python | 1,222 | 37 | import numpy as np
import pandas as pd
def tables(results_or_tables):
if "tables" in results_or_tables:
return results_or_tables["tables"]
return results_or_tables
def metric_value(row: pd.Series, metric: str) -> float:
corrected = f"selection_{metric}_optimism_corrected"
if row["setting"] i... |
b4fb7ba575ad678cb2ce922bff5364a91233fcbb48988a5001f20e7f408f1310 | Python | 1,225 | 43 | """
Tools for integration with miscellaneous non-required packages.
shamelessly borrowed from openff.toolkit
"""
# don't format vendored code
# fmt: off
import functools
from typing import Callable
def requires_package(package_name: str) -> Callable:
"""
Helper function to denote that a funciton requires som... |
d1c666a7d7d9eb7d637b6698567cd66925c26129cf1178e06a8bcf2bcffc8a28 | Python | 1,226 | 35 | from ..common.optim import SGD as optimizer
from ..common.coco_schedule import lr_multiplier_1x as lr_multiplier
from ..common.data.coco import dataloader
from ..common.models.mask_rcnn_fpn import model
from ..common.train import train
from detectron2.config import LazyCall as L
from detectron2.modeling.backbone impor... |
8f943e932cc664d60614502dc94f716406e13dd4dfba252beebc29204c2bb5d4 | Python | 1,227 | 49 | import torch
import esm
import tqdm
import biotite.structure.io as bsio
import subprocess as sb
import sys
args = sys.argv
model = esm.pretrained.esmfold_v1()
model = model.eval().cuda()
assert len(args)==3, 'Please type: python3 run_ESMFold_prediction.py <input_fasta_path> <output_dir_path>'
input_fasta_path ... |
a6b5d1251d057b5e9e0604f4bae3262a7e0a63e383f516a4708659947f229907 | Python | 1,228 | 50 | import torch
import matplotlib.pyplot as plt
from ..utils.lib import readSignal
from ..models.VisualTransforms import LogPowerSpectrum, LogWaveletCWT
data_path = "eeg_visual_classification/data/block/eeg_55_95_std.pth"
data = torch.load(data_path)
signal = readSignal(data, recordNo=10, channelNo=10)
signal = torch.... |
f33d86d729454b1675b0ce326913d17c6a34f3a61f0529200c13457ed1c1ee28 | Python | 1,228 | 51 | #!/usr/bin/env python3
#
# Copyright (c) 2016 10x Genomics, Inc. All rights reserved.
#
from __future__ import annotations
import argparse
import sys
from six import ensure_str
from tenkit.fasta import check_fastq_types_multipath
def make_parser():
parser = argparse.ArgumentParser(
description="Check ... |
ec7d000fb9604027cd789a75b1b3f93448b8a010253bc8ce80ff81665bfff304 | Python | 1,230 | 41 | from NeuroPy import NeuroPy
#from pyeeg import *
#import pyglet
npo=NeuroPy('/dev/ttyS25')
eegcoll = []
def npacb(attention_value):
print attention_value
return None
npo.setCallBack("attention",npacb)
npo.start()
i=1
while i<100:
eegcoll.append(npo.rawValue)
if(npo.meditation>50):
print npo... |
96f1ed78353c7f5d1da1bbb1bd037e41b9d98d0f4584f866aaf02f803e21d104 | Python | 1,237 | 39 | # Copyright (c) Facebook, Inc. and its affiliates.
from iopath.common.file_io import HTTPURLHandler, OneDrivePathHandler, PathHandler
from iopath.common.file_io import PathManager as PathManagerBase
__all__ = ["PathManager", "PathHandler"]
PathManager = PathManagerBase()
"""
This is a detectron2 project-specific Pat... |
90d61de14db5a8c0f86e4d5abd3c45606b45ab3945afaffeba293d28ccf43415 | Python | 1,240 | 46 | from dataclasses import dataclass
import numpy as np
PF_MAPPING = {1: 0.5, ## 4/8
2: 0.625, ## 5/8
4: 0.75, ## 6/8
8: 0.875 ## 7/8
}
ASYM_ECHO = {0: 1.0,
1: 0.0}
LPS_TO_RAS = np.diag([-1., -1., 1., 1.])
... |
3abe9631bde16bf593c7141bea1ccafedbc15462cf060a3cbc77373b9611956e | Python | 1,242 | 32 | class InvalidOrderException(Exception):
def __init__(self, function, execute_first):
super(InvalidOrderException, self).__init__(f'Invalid order for function {function} call {execute_first} before calling this function')
class InvalidCsvFileException(Exception):
def __init__(self, path):
super... |
59b37559113e3d6b4d0a745b12a3e487e3eee6a3d430edd729ae0bc0a98a4fe7 | Python | 1,243 | 45 | # Copyright (c) Facebook, Inc. and its affiliates.
import unittest
import torch
from detectron2.modeling.meta_arch import GeneralizedRCNN
from detectron2.utils.registry import _convert_target_to_string, locate
class A:
class B:
pass
class TestLocate(unittest.TestCase):
def _test_obj(self, obj):
... |
9b7c81f7d7635e57ada8c9c89e1a57297b46b971a6817642d2e264783f091419 | Python | 1,244 | 34 | import tensorflow as tf
import numpy as np
import math
import random
from sklearn import preprocessing
from tensorflow.examples.tutorials.mnist import input_data
# load the MNIST dataset
mnist=input_data.read_data_sets("../MNIST_data/",one_hot=True)
train_X_,train_Y_,test_X_,test_Y_,val_X_,val_Y_=mnist.train.images,m... |
30fff5245f81b4769211c910afe0fc9506595a97557ec484804a9b344f109864 | Python | 1,245 | 42 | import re
from pathlib import Path
from setuptools import find_packages, setup
try:
import torch # noqa: F401
except ImportError as e:
raise Exception(
"""
You must install PyTorch prior to installing DensePose:
pip install torch
For more information:
https://pytorch.org/get-started/locally/
... |
abeb86c7581accee452f94d01d13c987261cac13e97f40ea28a68cafe0cc100d | Python | 1,245 | 32 | import pytest
from src.preprocessing.smiles_cleaner import AmbiguousFragmentError, SmilesCleaner
from src.utils.models import MolecularRecord
def _record(smiles: str, access_code: str = "CMPD") -> MolecularRecord:
return MolecularRecord(access_code=access_code, smiles=smiles, source_row=2)
def test_removes_cou... |
26ea098013a2f89b66b855a03e9aabccb52e4b0525f668241d18f2f1e5c3078a | Python | 1,247 | 31 | #
# Copyright (c) 2020 10X Genomics, Inc. All rights reserved.
#
"""Methods for identifying and working with 10X product releases."""
from __future__ import annotations
def get_cmd_names(product_name: str) -> tuple[str, str]:
"""For a given product name (must be either cellranger or spaceranger) returns the hum... |
a9a0956861597e897a3670fcdb8040556a0def20b9936247638fa9a03dbe1e91 | Python | 1,247 | 38 | from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
import pandas as pd
from pathlib import Path
def aln_from_csv(input_csv: str | Path, genus: str, out_parent: str | Path) -> None:
"""
Method for generation of alignment files from input csv
Args:
input_csv: The inpu... |
903dca5cfc4aadf9331c6f4e9c86aac9e0d172d6dc03e16c6471dff2d4bd372b | Python | 1,250 | 30 | import os
import nibabel as nib
from nilearn import image
from tristan_pipeline.io.params import *
space = "MNI152NLin2009cAsym"
os.makedirs(grp_dir, exist_ok=True)
for moco_label in list(mocos.keys()):
subject_maps = []
#########LOOP OVER SUBJECTS AND SESSIONS#########
for subj in subjects:
for s... |
3876be8555a7094d13ce572627a77613feed9622391aceb660a909ba251ad6a2 | Python | 1,251 | 53 | from __future__ import annotations
import matplotlib.pyplot as plt
import mne
from ..utils import get_soi_picks
def plot_sensors(
inst: mne.io.BaseRaw | mne.Epochs | mne.Evoked,
sois: list[str] = ['O', 'P', 'C', 'F', 'T'],
) -> None:
"""Plot the sensors of the SOI.
Parameters
----------
ins... |
8e75af33b56e5d3a835a51cbb3cc631d4333526cc3cc806b138205c7fdeaea29 | Python | 1,253 | 38 | from plus_slurm import Job
#%%
import pandas as pd
#import pymc as pm
import bambi as bmb
import arviz as az
#import aesara.tensor as at
from scipy.stats import zscore
import os
from os.path import join
#%%
class BayesPred(Job):
#%% the run method starts here
def run(self, key2corr, channel, outdir, **sample... |
168d6416d9cbc39b086543b1a9c9fe55228862479af8e816d74453d4e9747732 | Python | 1,259 | 36 | from detectron2.config import LazyCall as L
from detectron2.layers import ShapeSpec
from detectron2.modeling.box_regression import Box2BoxTransform
from detectron2.modeling.matcher import Matcher
from detectron2.modeling.roi_heads import FastRCNNOutputLayers, FastRCNNConvFCHead, CascadeROIHeads
from .mask_rcnn_fpn imp... |
16e3337316ce2f0e55da7b033f41632958f0863eb818588bb715a3ae5b80e071 | Python | 1,261 | 47 | """
NoClaMe
-------
This script implements a series of metrics for node-classification.
These metrics are for binary node-classification, intended to work
for node-classification on molecular graphs, which usually involves
a large number of relatively small graphs (<50 vertices).
Implemented node-classification me... |
7c13de4821a2e4efe3fb20d414a72162e8f09e9572dd5aa88d6212327af57240 | Python | 1,262 | 38 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 7 13:33:47 2022
@author: schmidtfa
"""
#%% imports
from cluster_jobs.preprocess_meg import Preprocessing
from obob_condor import JobCluster, PermuteArgument
import pandas as pd
#%% get jobcluster
job_cluster = JobCluster(required_ram='2G',
... |
bf6c8915f4737f8a9f2a46ca3c1e112cc101f45ea9b8d8e1e1166d90fddcdc44 | Python | 1,262 | 48 | #!/usr/bin/env python
#
# Copyright (c) 2024 10X Genomics, Inc. All rights reserved.
#
"""This stage extracts a projection from a cloupe file."""
__MRO__ = """
stage ETXRACT_LOUPE_PROJECTION(
in cloupe sample_cloupe,
in string projection_name,
out csv projection,
src py "stages/cas_cell_typin... |
ad7d8a4ee489881cb58485a2f8aae3ea24a451de26413c43743c4a3c419315f2 | Python | 1,265 | 35 | """Audio loading utilities."""
import subprocess
from pathlib import Path
import numpy as np
def load_audio_16k(path, sample_rate=16000):
"""Decode an audio file to a float32 mono array at ``sample_rate`` via ffmpeg.
ffmpeg does the resampling/downmixing out-of-process, so the native-rate
buffer never ... |
b2318475468c1aed304fecec5efa54dde6f75ef88b3390d5c4e7893693eddb7d | Python | 1,265 | 43 | import shutil
import subprocess
from importlib import resources
from os import PathLike
from pathlib import Path
from typing import Union
from ..._env import run_captured
from . import data as cellprofiler_data
def create_and_save_segmentation_pipeline(
segmentation_pipeline_file: Union[str, PathLike]
) -> None:... |
b5f035391b590c5fddba1c78bce8951971ab1eaf62a146e78777ed6c1ca73fca | Python | 1,266 | 42 | import os
import sys
import anndata as ad
import torch
# 获取当前脚本的绝对路径
current_dir = os.path.dirname(os.path.abspath(__file__))
# 获取父目录（模型定义脚本）的路径
parent_dir = os.path.dirname(current_dir)
if parent_dir not in sys.path:
sys.path.append(parent_dir)
from config import MethyAnnoConfig
from main import *
my_config = M... |
b95a16d0b529ec9054e394a5d6d5213c268d63df243fea35513d20b949a7cab5 | Python | 1,266 | 34 | #!/usr/bin/env python3
import argparse
import gffutils
parser = argparse.ArgumentParser()
parser.add_argument("annotation_file", help="GTF file containing gene annotations. For example, from https://www.gencodegenes.org/")
parser.add_argument("--filter", default="Ensembl_canonical", help="Only keep GTF features with t... |
54b5814351472796635c5ece98008555aa76e3c22b09a9850af130ab2027e924 | Python | 1,267 | 35 | from pathlib import Path
import numpy as np
import pytest
from steinbock import io
from steinbock.segmentation import deepcell
from steinbock.segmentation.deepcell import Application
keras_models_dir = "/opt/keras/models"
@pytest.mark.skipif(not deepcell.deepcell_available, reason="DeepCell is not available")
clas... |
82e9e1539dec3092695e6613814b3da092b9ca121398ccd566c7719a3f65ae37 | Python | 1,268 | 27 | # %% setup
#for i in /cluster/work/users/ash022/veronica/*He*.d ; do echo $i ; timsconvert --chunk_size 5000000000 --verbose --input $i ; done
#sage sage.json -f human_crap.fasta --batch-size 40 /cluster/work/users/ash022/*.mzML
#cp lfq.parquet $HOME/PD/TIMSTOF/LARS/2024/240605_Veronica/HeLa/
# %% data
proteinHits=pd.... |
e2130334f1861b9582b69fbb70f3d7fc679da8ccce04dacee8926b1cce08d0a7 | Python | 1,269 | 43 | from os import PathLike
import torch
from chemprop.models.model import MPNN
from chemprop.models.mol_atom_bond import MolAtomBondMPNN
from chemprop.models.multi import MulticomponentMPNN
def save_model(
path: PathLike,
model: MPNN | MolAtomBondMPNN | MulticomponentMPNN,
output_columns: list[str]
| t... |
e990dfee1ea20f1adbfba808613383d2bb6fa69eefc0e0288502ac465aaa0b92 | Python | 1,270 | 43 | import subprocess
from importlib import resources
from os import PathLike
from pathlib import Path
from typing import Union
from ..._env import run_captured
from . import data as cellprofiler_data
def create_and_save_measurement_pipeline(
measurement_pipeline_file: Union[str, PathLike], num_channels: int
) -> No... |
fe04ee8c6d081b4cc654c2c681409d02cac1e618d333e825bd7b222cae59137e | Python | 1,273 | 48 | #!/usr/bin/env python3
import sys
import matplotlib.pyplot as plt
import matplotlib
import numpy as np
matplotlib.rcParams['pdf.fonttype'] = 42
# --- Example data matching the plot ---
# Adjust these or load from a file
groups = ["Standard\nsimulation", "Concatenated\nreads"]
categories = ["Precision", "Recall"]
val... |
d8455ba427957b2c011033119c36d6403111264095da050178f60401ee54872e | Python | 1,274 | 35 | import os
import pandas as pd
import numpy as np
from src.utilities.statistical_tests import apply_enrichment
from loguru import logger
logger.info('Import OK')
input_path = 'results/preprocessed/RC_significant_summary.csv'
background_path = 'results/preprocessed/identified_background.csv'
output_folder = 'results/R... |
7c032c6175c0e5d604f7eb76324a9849341deef646cd3e5ae446cd39d5dcbeee | Python | 1,276 | 33 | from __future__ import annotations
from dataclasses import dataclass
import numpy as np
@dataclass(frozen=True)
class WeightedTargetScaler:
mean: np.ndarray
scale: np.ndarray
@classmethod
def fit(cls, targets: np.ndarray, weights: np.ndarray) -> "WeightedTargetScaler":
targets = np.asarray(... |
1c00e5389a1194ac96145d51e67980a17eb171dcb625f68b756bcfd96008f9ed | Python | 1,277 | 41 | #!/usr/bin/env python
# Copyright 2011-2014 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
df038581650b2787e486695aeb08c887ca977d7a61102500b3928efa9128d947 | Python | 1,280 | 37 | import cv2
from os import listdir
from os.path import isfile, join
import numpy as np
def threshold_images(in_path, out_path):
"""
Performs the threshold function on all the images in the folder `in_path` and outputs them in `out_path`
Params:
in_path: folder of source images
out_path: fold... |
cc1cd2fdf5f1aaba7ff7dc897824e17bcd3dfb69ff2da3730ef993105894ac60 | Python | 1,282 | 41 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
342d6a562eb82d238618e9c8a8dd382494d207178c74d5c780b16252710b1e02 | Python | 1,283 | 38 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
from __future__ import annotations
import json
import pathlib
from openfe import AlchemicalNetwork, LigandNetwork
from openfecli.utils import write
def plan_alchemical_network_output(
... |
114abb9847aefadd4780fee395d6b4712de5a390674d7f1f9e1d7f26ac25bc9b | Python | 1,284 | 39 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
743a55b246f1993b4a43c5a33ff4fdf284a360e9d31692d3b8d2cace65cf6ef1 | Python | 1,284 | 44 | from __future__ import annotations
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import Optional, Sequence
import numpy as np
import numpy.typing as npt
__all__ = ["PNG"]
@dataclass
class PNG:
layers: npt.NDArray[np.int_]
nrns: npt.NDArray[np.int_]
lags: npt.N... |
b4335757bd219462fc1f540b55d8002342b1d4bb4f228fc39e536184ed6b953c | Python | 1,284 | 31 | #!/usr/bin/env python
# Copyright 2016-2019 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
c20436daa3e54b00386f0fc30207fabaed3220cf91fd6e07dac8f86e15c05788 | Python | 1,285 | 40 | from functools import partial
from fvcore.common.param_scheduler import MultiStepParamScheduler
from detectron2 import model_zoo
from detectron2.config import LazyCall as L
from detectron2.solver import WarmupParamScheduler
from detectron2.modeling.backbone.vit import get_vit_lr_decay_rate
from ..common.coco_loader_l... |
ff4d6dd2a450848177112f4205c82591161d50952e8382cbae294581011320fc | Python | 1,285 | 38 | from plus_slurm import Job
#%%
import pandas as pd
#import pymc as pm
import bambi as bmb
import arviz as az
#import aesara.tensor as at
from scipy.stats import zscore
import os
from os.path import join
#%%
class BayesPred(Job):
#%% the run method starts here
def run(self, key2corr, channel, outdir, **sample... |
3c2f1a16433c0022312af92b535decf6f7dbc6420b17685bdbf38c1652e72d52 | Python | 1,286 | 37 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from collections import OrderedDict
from detectron2.checkpoint import DetectionCheckpointer
def _rename_HRNet_weights(weights):
# We detect and rename HRNet weights for DensePose. 1956 and 1716 are values that are
# common to all HRNet pretra... |
abfcff867a7230dde40d0471d99e9f4683ea45ca02522851377e2367ba81f6ef | Python | 1,287 | 43 | # commands extensions to PyMOL for batchmin
from pymol import cmd
from chempy.bmin import realtime
import threading
def amin(*arg,**kwarg):
realtime.assign(arg[0])
apply(bmin,arg,kwarg)
def bmin(object,iter=500,grad=0.1,interval=100,
solvation=None):
realtime.setup(object)
t ... |
522570660d5f9e08ed70f4176b3f2f69312f912296abdd034738f1c28933d86b | Python | 1,292 | 33 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2019-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
... |
12e89249a87482b866e5b5e9b00add386f3ab474c37f2cf66ea4c1f63fe047b8 | Python | 1,293 | 38 | #!/usr/bin/env python
# Copyright 2016-2019 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
2f1e0ec377f4767a3457deda3170b093d35d43b77b58f2dfe5cbbd2cc4e06181 | Python | 1,293 | 48 | """ Created on Thu Oct 12 13:18:03 2023
@author: dcupolillo """
import json
def save_to_json(
node_bundle: object,
json_filename: str,
) -> None:
"""
Save NodeBundle data to a JSON file.
This function serializes key properties of a NodeBundle, such as the total
number of nodes, total neu... |
919e52f162396898d98a768ad4cc6b6c303331b8f2b0a24dfecadf2a48a02110 | Python | 1,299 | 44 | #
# Copyright (c) 2025 10X Genomics, Inc. All rights reserved.
#
"""Structify aggregated cell typing outputs."""
from cellranger.cr_io import recursive_hard_link_dict
__MRO__ = """
struct AggregatedCellTypes(
csv all_cell_types,
json.gz all_cell_annotation_results,
)
stage STRUCTIFY_AGGREGATED_CELLTYPES... |
6e1154eb3d528c4e28fe7527f029213cd9407143083f4edf1cc739ca29b426f0 | Python | 1,300 | 46 | import inspect
from typing import Any, Iterable, Type, TypeVar
T = TypeVar("T")
class ClassRegistry(dict[str, Type[T]]):
def register(self, alias: Any | Iterable[Any] | None = None):
def decorator(cls):
if alias is None:
keys = [cls.__name__.lower()]
elif isinstanc... |
e107045b20a15ef193ba6cd0ee189bd786415e77239399c12ce0cd8cebe8fb59 | Python | 1,303 | 47 | """ Created on Thu Jul 27 15:25:49 2023
@author: dcupolillo """
import ROIpy as rp
import matplotlib.pyplot as plt
from pathlib import Path
date = "240912"
cell_n = "cell0002"
data_folder = Path(r"C:/Users/dcupolillo/Projects/spyne/data")
neuron_path = Path(rf"{date}\{cell_n}")
stack_filename = Path(
data_fo... |
bbb1a625070525039d11742228c469b088728f4879db20d1652ca2d85fd59b71 | Python | 1,304 | 59 | # -*- coding: utf-8 -*-
"""For testing neuromaps.points functionality."""
import numpy as np
import pytest
from neuromaps import points
def test_point_in_triangle():
"""Test point in triangle."""
triangle = np.array([[0, 0, 0], [0, 0, 1], [0, 1, 1]])
point = np.array([0, 0.5, 0.5])
inside, pdist = p... |
dfbc2abedc0d30e2823e2666142b5dccb50ff170b80df23fd9cfd2de1b5f5f1d | Python | 1,304 | 39 | #!/usr/bin/env python
#
# Copyright (c) 2026 10x Genomics, Inc. All rights reserved.
#
"""Compute segmentation plots for Visium HD data."""
__MRO__ = """
stage STRUCTIFY_WEBSUMMARY_INPUTS(
in WebSummaryCellTypeInputs websummary_inputs,
in map<json> cell_type_spatial_plot,
out WebSummaryCe... |
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