sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
b88dc09efe966d303c6689381469ff7e3a11e63bce3cebaa63855d9ca7c4694e | Python | 1,868 | 59 | import torch.nn as nn
from torch import Tensor
from torch.nn import init
from custom_layers.custom_dropout import Dropout
from custom_layers.custom_module import BatchEvalModule
class Dense(BatchEvalModule):
# A dense layer following the idea of Tensorflow
def __init__(self, in_features, out_features, activa... |
62b88504a3a1db4f9fb5b5cf2cd988b9a1bfb2f9478422fb894eeab4d598c122 | Python | 1,869 | 73 | # Figure 2
import numpy as np
from scipy.constants import epsilon_0 as e0
import impedancefitter as ifit
from impedancefitter.single_shell_wall import eps_cell_single_shell_wall
from impedancefitter.suspensionmodels import bhcubic_eps_model, eps_sus_MW
em = 5.0
dw = 250e-9
Rc = 2.75e-6 - dw
dm = 7e-9
km = 0.0
kcp = ... |
cb0a1ad008f67585d04394476f9dc070dbf897cf64022fba4afaa6fd2ebf8579 | Python | 1,869 | 50 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import os
from urllib.request import urlretrieve
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_prepro... |
571e73b8fdcc5e9608ae7e5f408aac8e15979e4d222ba2c6ecc0a2d877c882bd | Python | 1,870 | 51 | import torch
def sinkhorn(feature1, feature2, pcloud1, pcloud2, epsilon, gamma, max_iter, sim_k=50, dist_k=10):
feature1 = feature1 / torch.sqrt(torch.sum(feature1 ** 2, -1, keepdim=True) + 1e-8)
feature2 = feature2 / torch.sqrt(torch.sum(feature2 ** 2, -1, keepdim=True) + 1e-8)
S = torch.bmm(featur... |
b0721065839963a9be7a90cd2a6840770e7786f9ae6552b075a886e7b2c1ab22 | Python | 1,870 | 71 | import sys
import genutils3
import os
from optparse import OptionParser
USAGE = """
extract-50mers.py --fai <.fai file> --fa <fasta file> --outdir <out dir for kmer files>
prints out 50mers with step of 5.
"""
###############################################################################
parser = OptionParser(U... |
fa7effe96063f17af0d91f9acfe4f8e19581369ce051d8e0246e4416a323888d | Python | 1,870 | 45 | import numpy as np
from brainscore_core import Metric, Score
class Dimensionality(Metric):
def __init__(self, factor):
self.factor = factor #factor to return
def __call__(self, assembly1, assembly2) -> Score:
#each assembly should have 3 dimensions: (factor, sample_num, neuron_i)
dims... |
ac316a19690b9800ce1c628f5ad3f3cadd4b8e52272410d9bc1b866564d27218 | Python | 1,871 | 50 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import os
from urllib.request import urlretrieve
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_prepro... |
f9529243b9099509407b47d13592368265b834c51b3283b45033485dc0bd1107 | Python | 1,871 | 89 | """
Utility functions for working with `Bitset`s and treating lists of (start,end)
as `Bitset`s.
"""
from bx.bitset import (
BinnedBitSet,
MAX,
)
def bitset_intersect(ex1, ex2):
bits1 = list2bits(ex1)
bits2 = list2bits(ex2)
bits1.iand(bits2)
return bits2list(bits1)
def bitset_subtract(ex1, ... |
08fcdfe9a7135a93e3a867e6fbc6c55fab66cdac1be4d30706a11010d87686ee | Python | 1,872 | 53 | import os
import json
#TODO change results dir
def setup_paths_and_config(config_path, result_dir_name = 'results', root_dir=None, transfer=False):
if root_dir is None:
root_dir = os.path.dirname(os.getcwd())
data_dir = os.path.join(root_dir, 'data')
result_dir = os.path.join(root_dir, result_di... |
99add8b28486ec1650775864b0f593cd016e10f51221770286fbfe6a6c4f169f | Python | 1,872 | 50 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import os
from urllib.request import urlretrieve
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_prepro... |
df0c41a95600a1c0d8b18802056628bf122d834e2bb5fcf76e998038badac4dd | Python | 1,872 | 79 | """
nelpy core objects
``nelpy`` is a neuroelectrophysiology object model and data analysis package.
"""
# __all__ = ['IntervalArray',
# 'EpochArray',
# 'RegularlySampledAnalogSignalArray',
# 'SpikeTrainArray',
# 'BinnedSpikeTrainArray',
# 'EventArray']
# ... |
b9339cb20cc828c86fb184bdfb7c16053a3e00d7a46f2f58bd4e651759caf292 | Python | 1,874 | 53 | from typing import List
class OperationalUnit:
def __init__(
self,
input_precision: List[int],
output_precision: int,
unit_cost: float,
unit_area: float,
):
"""
General class for a unit that performs a certain operation. For example: a multiplier unit.
... |
e3cecc1b0017241126fabd24a627e15173df26dad427bc20832472747a32ca29 | Python | 1,874 | 22 | from testsetclass import TestsetClass
class CARBHB12(TestsetClass):
def __init__(self):
self.weak = 1.0
self.molecules = ['2O_A', '4N_A', '4CL', '4CL_A', '1N_A', '1CL_A', '3O_A', '3CL_A', '2CL_A', '4O_B', '2N_B', '3CL', '1O_B', '1O', '2N', '2O', '3N_B', '1N', '3O', '2O_B', '4N_B', '4CL_B', '3N', '... |
8fa93bd8c096701efc800f7191ed6338a0c9371c820b0c19af1ae48be9c87fbb | Python | 1,875 | 58 | # 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... |
98b573d35df0b781b5079a6aa99b9312ffe22cfc38912672e582412961676b63 | Python | 1,875 | 69 | import SimpleITK as sitk
import os
import sys
dir_script = os.path.dirname(os.path.abspath(__file__))
loc_atlas_gm = os.path.join(dir_script, "grey.nii.gz")
loc_atlas_wm = os.path.join(dir_script, "white.nii.gz")
loc_atlas_csf = os.path.join(dir_script, "csf.nii.gz")
loc_exclude = os.path.join(dir_script, ... |
bebfd6c6140bf4c36fec2367df0bf23f527e7ba5cb2f76a43445f9ef45d85a41 | Python | 1,875 | 46 | #!/usr/bin/python
"""
Gamepad310 HAL module.
Hazen 04/18
"""
import storm_control.sc_hardware.baseClasses.joystickModule as joystickModule
import storm_control.sc_hardware.logitech.gamepad310 as gamepad310
class Gamepad310Module(joystickModule.JoystickModule):
def __init__(self, **kwds):
su... |
2d90563b8a5f1ddf73432342b5f646642da4f78ed30cb9c5375f383e2f9672d7 | Python | 1,876 | 59 | import utils
import argparse
from os.path import join
import keras
from keras.models import load_model
import numpy as np
import gc
'''
get average of ensemble predictions for X_train to generate new y_train
new y_train will be used to train an ensemble distilled model
'''
def parse_args():
parser = argparse.Argu... |
55a8ec50193aa4e1c37a593c4d2c474ea43cb73e55252bbb86d256b75a266cde | Python | 1,876 | 50 | import torch
import torch.nn as nn
import numpy as np
class InputSpikes(nn.Module):
def __init__(self, opt, prec_type=torch.float32):
super(InputSpikes, self).__init__()
self.prec_type = prec_type
self.opt = opt
if opt.n_rnn_in == 200:
p_stim = 0.5
elif opt.n_rn... |
5e90fa63cd36d5a9ed24cfa8715ef6194428997e418341df28aa0f6b31b9d47d | Python | 1,876 | 51 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
import torch.nn.functional as F
def resize(input,
size=None,
scale_factor=None,
mode='nearest',
align_corners=None,
warning=False):
if warning:
if size is not None ... |
9edc6b0beab2c3e6852802f1e7bcaceb49e12d9736da80fd24bafc46c33eba59 | Python | 1,876 | 45 | from brainscore_vision import stimulus_set_registry
from brainscore_core.supported_data_standards.brainio.s3 import load_stimulus_set_from_s3
BIBTEX = """@article{hendrycks2019benchmarking,
title={Benchmarking neural network robustness to common corruptions and perturbations},
author={Hendrycks, Dan and Dietterich... |
aaeb0b59f06b7a92b314891e1b1212d12e4a9ea46065d7b6095ea6705e677f87 | Python | 1,876 | 57 | import numpy as np
from impyute.ops import matrix
from impyute.ops import wrapper
from impyute.ops import error
@wrapper.wrappers
@wrapper.checks
def locf(data, axis=0):
""" Last Observation Carried Forward
For each set of missing indices, use the value of one row before(same
column). In the case that the... |
26d930f04d826f2a53695096d4f5eeacd82ea8e005df580bb8a34cdfbc29f257 | Python | 1,877 | 71 | """Configurations to train a MultiRNN model on MSI task.
See ../models/multi_rnn.py for model details.
"""
from models import multi_rnn
import msi_task
import torch
import trainer
def model_config():
config = {
"constructor": multi_rnn.MultiRNN,
"kwargs": {
"input_feature_len": 3,
... |
2ee5d827d93e32e790f2a303ef371c308c6f65e7d33ab1def10de89dc34a1259 | Python | 1,877 | 60 | import pandas as pd
import re
human_data = pd.read_csv('human_data_normal/human_data.csv')
images_shown = pd.read_csv('human_data_normal/images_shown.csv')
human_data["image_shown"] = "FILL"
columns = {"Participants 1-7": [1,2,3,4,5,6,7],"Participants 8-13": [8,9,10,11,12,13],
"Participants 14-19": [14,15,... |
3267c7c38c193f260d84615942eb684b2f7b104be33f9ee571ea0383463eab47 | Python | 1,878 | 63 | '''
1. Load brain phantom
2. Add Rician noise
3. Denoise using denoise algorithm
4. Check that sum of squared residuals decreased after denoising
'''
import os
import numpy as np
from phantoms.brain.sim_brain_phantom import simulate_brain_phantom
import nibabel as nib
import matplotlib.pyplot as plt
from src.original.... |
3cf679dc394416471596710dfa464a82b8bf414dfaaad900ce3f7338a7554909 | Python | 1,878 | 51 | from chemgraph.schemas.multi_agent_response import PlannerResponse
def test_planner_response_accepts_full_payload():
payload = {
"thought_process": "Decomposing into per-molecule calculations.",
"next_step": "executor_subgraph",
"tasks": [
{"task_index": 1, "prompt": "Calculate... |
e6b905767023f0fa68fac31d770ca1e3ceab7424376db94b3a26f48a7061029e | Python | 1,878 | 50 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import os
from urllib.request import urlretrieve
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_prepro... |
fd09c43400cf902c8ff2c77538c4ab5a171bc3ada5fb328baa58d3ece4224714 | Python | 1,878 | 44 | from tests.common import *
def test_dryrun(demo_dir):
r = run("snakemake -n -c1", dir_path=demo_dir)
message = "This was a dry-run (flag -n). The order of jobs does not reflect the order of execution."
assert message in r.stdout
def test_pipeline_no_run(demo_dir):
LOGGER.info("run entire pipeline wit... |
012abbbc654b49d0a06ad5eafd7762b73897f53d6ba820b48710395fc22bec47 | Python | 1,879 | 42 | import numpy as np
import pytest
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet
from brainscore_vision import load_stimulus_set, load_dataset
from brainscore_vision.model_interface import BehavioralAssembly
@pytest.mark.memory_intense
@pytest.mark.private_access
class TestHebart2023... |
8031a592e3d8ff2e008e8c3d02652bba795315e4e3b8fc047552aa274ae79244 | Python | 1,879 | 60 | import unittest
import warnings
from unittest.mock import patch
from neuralib.imglib.io import tif_to_gif, gif_show
from rscvp.retinotopic.cache_retinotopic import RetinotopicCacheBuilder
from rscvp.retinotopic.main_retinotopic_map import RetinotopicMapOptions
from .util import check_attr
class TestRetinotopicModule... |
80e520a90fd8fb6e6d58925dc7808a0930179d35860131908e4035aaaa15f869 | Python | 1,879 | 50 | # %% ### import modules
from pathlib import Path
import seaborn as sns
import pandas as pd
from matplotlib import pyplot as plt
import bap1b.figures as figures
# %% read results table
results_dir = Path(__file__).resolve().parents[1] / "results"
df = pd.read_excel(results_dir / "cs_a_results.xlsx")
# %% round all ... |
82b8d42930389fcd2a39e639354ce50312bceeae162595cd2e7056d805a4f024 | Python | 1,879 | 47 | #create_toy_computational_sequence.py
#this example shows how to create two toy computational sequences and put them together in a dataset
import mmsdk
from mmsdk import mmdatasdk
import numpy
def random_init(compseq,feat_dim):
for vid_key in vid_keys:
num_entries=numpy.random.randint(low=5,high=100,size=1)
com... |
0332f6233fa48ebda38b7b930e1b910166e17dc3af6898f2da5ddced9ecc9764 | Python | 1,880 | 50 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
import os
from urllib.request import urlretrieve
import torchvision.models
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_prepro... |
08ef5b276d5fa90bbc146689075b529d29302c81dc5e21f5e9d8be76f8c91449 | Python | 1,880 | 56 | #!/usr/bin/env python3
import argparse
import numpy as np
from ase import Atoms
from ase.io import read, write
from ase.optimize import *
from KerNNCalculator.KerNNCalculator import *
'''
Script to calculate the potential energy of a structure.
Usage: python predic_mol.py -i structure.xyz
'''
#parse command line argu... |
16d186094fa71449f826556e7dc7b91b4d60b1f5e534e500cb1401e6c7a03c7a | Python | 1,880 | 84 | """
File I/O utilities for DHG-LGB framework.
Provides standardized loading and saving functions for various file formats.
"""
import os
import pickle
import numpy as np
import yaml
from typing import Any, Dict
def load_config(config_path: str) -> Dict[str, Any]:
"""
Load YAML configuration file.
Param... |
f7f37b8ed8b2e3d8973e0af893ff264acef7d589261cd4fcca7d895d205c0971 | Python | 1,880 | 63 | from nipype import IdentityInterface, Function
import definitions
from PUMI.engine import NestedWorkflow as Workflow
from PUMI.engine import NestedNode as Node
from nipype.interfaces import BIDSDataGrabber
from nipype.utils.filemanip import list_to_filename
import os
from PUMI.pipelines.func.deconfound import despikin... |
fdfcefa398d4f5cb52bb798a6265bf7f9ffa48c753aa14c1e4b756c92f293ee6 | Python | 1,880 | 60 | #!/usr/bin/env python
import json
import sys
import os
import pandas as pd
# Read config file
def read_config_file(config_path):
with open(config_path, "r") as f:
config = json.load(f)
return config
# Concate the different dat files
## all these files should be formated the same way. Column header are s... |
6b203a1268fcbed8eaa8d46e55978b9c374c40744962d7b8447a17612b5c3f37 | Python | 1,881 | 54 | """Regression test for grouped node-cartography composition plots.
Run with::
uv run python -X utf8 python/test_node_cartography_proportions.py
"""
from __future__ import annotations
import tempfile
from pathlib import Path
import numpy as np
import pandas as pd
from meanap.pipeline.plotting_step4 import (
... |
962757598504d0936466dbb1d8249d959b79d41e12c9d64495b8a2c61e0ec8ef | Python | 1,881 | 44 | import numpy as np
from brainscore_vision import load_ceiling, load_metric, load_dataset
from brainscore_vision.benchmark_helpers.neural_common import NeuralBenchmark, average_repetition
from brainscore_vision.data.sanghavi2020 import BIBTEX_SANGHAVI
from brainscore_vision.utils import LazyLoad
VISUAL_DEGREES = 8
NUM... |
14bf895fea444e76142849835a95c739534298f0fcd4723033f0310db7ac47a4 | Python | 1,882 | 63 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
# external inputs
import numpy as np
import nibabel as nb
def clean_ana(file_in, min_value, new_range, overwrite=True):
"""Clean ana.
This function removes ceiling values from a computed T1 map of an mp2rage
acquisition. Low intensity ... |
59fe8d242dedfad3a066d6fa054e46d73b1ada58db618ac8c279f002924459ae | Python | 1,882 | 55 | from ..qt import *
from ..pipeline.data_widget import NodesModel, ChannelComboBox
class TouchDialog(QWidget):
def __init__(self, config, stub):
super().__init__()
self.setWindowTitle('Touch Input Config')
nodes_model = NodesModel(config['nodes'])
if 'touch_config' not in config:
config['touch_... |
68846e1f2ab1a34fdacd70b16d69f09c2439118f75deafa02364d6b19b1cd21c | Python | 1,882 | 53 | import argparse
from pathlib import Path
import pandas as pd
import SimpleITK as sitk
# parse the arguments
parser = argparse.ArgumentParser(
prog='Inference Script for the FeTA Challenge Submission',
description='Runs inference on an input image and\
s... |
b4c478715a86c4a73ec492370700d9fc21d167266b8c0328fb2cfc9a8cb280df | Python | 1,882 | 61 |
import torch.utils.data as data_utils
import torch
from PIL import Image
import numpy as np
import random
import glob
import os
from Utils import utils
Map = {
'tumor': 1,
'normal': 0
}
utils.seed_torch(seed=0)
class Dataset_test(data_utils.Dataset):
def __init__(self, path, transforms=None, padding=0, b... |
0dc4d4d132af8c0f031009caeecba965de73cb31bec016bae54807446fe45773 | Python | 1,883 | 64 | import torch
import numpy as np
import scipy.sparse as sp
from sklearn.neighbors import kneighbors_graph
from sklearn.neighbors import KDTree
from scipy.sparse.csgraph import dijkstra
from typing import Union
def construct_knn_graph(
points,
k: int = 10,
) -> sp.csr_matrix:
n, d = points.shape
if k >=... |
22b2ad9a1ef5fe92ba16c6b1cbc04e56118129469b54dfd6950f39c3ccfaafc2 | Python | 1,883 | 43 | from argclz import AbstractParser, argument, as_argument
from neuralib.atlas.ccf.matrix import load_transform_matrix, SLICE_DIMENSION_10um, slice_transform_helper
from neuralib.plot import plot_figure
from neuralib.util.verbose import publish_annotation
from rscvp.util.cli import HistOptions, CCFOptions
__all__ = ['Sl... |
97c9d94a729f5d29b714f7adef324f4243e5979d42f406455e59ece66cc7ccb0 | Python | 1,883 | 63 | #!/usr/bin/env python
import argparse
import sys
parser = argparse.ArgumentParser(description="")
parser.add_argument("bam", nargs="?", help="input bam file", type=argparse.FileType('r'))
parser.add_argument("ref", nargs="?", help="input bam file", type=argparse.FileType('r'))
parser.add_argument("outfile",nargs="?"... |
f7830bb7de5e0c2b32e9f39f71e636749ebe11367dd0d80431eca0f93b8a1a39 | Python | 1,883 | 75 | # -*- coding: utf-8 -*-
"""
Provides tools for timing
"""
#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City
#:license: GNU, see LICENSE.txt for details.
import time
class Timer(object):
"""Class to stop time and print results in formatted way
Attributes:
... |
d852cdf993ca90b10e8a7b0bc6f56c46f7dc607a9e92136a6a57368f363185de | Python | 1,884 | 74 | import unittest
import numpy as np
import torch
import torch.testing as ptt
from deepdwi import util
from deepdwi.dims import *
if __name__ == "__main__":
unittest.main()
devices = [torch.device('cpu')]
if torch.cuda.is_available():
devices.append(torch.device('cuda'))
class TestUtil(unittest.TestCase):... |
814e8ae0a6041aee30beae0b22440ec1b39ef6ad2a5e23ba4ad5982c39fc7f1d | Python | 1,885 | 84 | import argparse
import sys
from collections.abc import Callable, Generator
from contextlib import contextmanager
from eir import __version__
from eir.predict import main as main_predict
from eir.train import main as main_train
@contextmanager
def patch_sys_args(patched_args: list[str]) -> Generator[None]:
old_ar... |
91045a174d59dfa79f4d408e0cd20eac3a71d152e5b68694bc32a3f95ba370bf | Python | 1,886 | 55 | import torch
from torch import Tensor
@torch.jit.script
def baked_embed_to_prob(
embedding: Tensor, baked_skeletons: Tensor, sigma: Tensor, eps: float = 1e-16
) -> Tensor:
r"""
N Dimensional embedding to probability with a baked skeleton array
Calculates a probability :math:`\phi` based on a euclidea... |
0f50cb325eefd32903cbd408f4632700b28b449f6d9f32fb5ef7a0e4de54acef | Python | 1,887 | 67 | from qtpy.QtWidgets import (
QVBoxLayout, QHBoxLayout,
QLabel,
QLineEdit,
QWidget, QGroupBox,
)
import napari
from typing import TYPE_CHECKING
if TYPE_CHECKING:
import napari
class OutputDataLayout:
def __init__(self, viewer: "napari.viewer.Viewer"):
self.viewer = viewer
... |
5b248210c7e6fe9144facee57572cf3714a81e0b00823903de8b45daf1e8e5b1 | Python | 1,887 | 68 | """ Surface edits """
import SVMTK as svm
from pathlib import Path
if __name__ == "__main__":
print("Start ",__file__)
outdir = Path("results")
outdir.mkdir(exist_ok=True)
sphere1 = svm.Surface()
sphere2 = svm.Surface()
sphere5 = svm.Surface()
# Create two spheres
# First sphere ce... |
9b080aba9cec24bed8fc62f390f55a6dcb70f7826b04b56a7058825ee729e8db | Python | 1,887 | 52 | # Copyright (C) 2019-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import shutil
from datumaro.components.dataset import Dataset
from cvat.apps.dataset_manager.bindings import (
GetCVATDataExtractor,
detect_dataset,
import_dm_annotations,
)
from cvat.apps.dat... |
aee597504132fb381fbf6a6a13d6eb70acf745b2627008f0fe9215b90e9f8792 | Python | 1,887 | 55 | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
# Adapted from https://github.com/facebookresearch/segment-anything
from setuptools import find_packages, setup
from setup... |
0ceb0732ab011c0cf179298a5d6eba2210dfdd747a39a80fe8cafdd0b480b2ac | Python | 1,888 | 60 | from collections import OrderedDict
from typing import Dict, NamedTuple
import numpy as np
from numpy.typing import NDArray
from patsy.design_info import DesignMatrix # type: ignore
class StateMapping(NamedTuple):
mapping: Dict[str, int]
reverse: Dict[int, str]
encoding: NDArray[np.float32]
idx: NDA... |
792560a53355239742a161dc37315e21013ab5a16567b0efb41b9f7076675107 | Python | 1,888 | 50 | import pyvisa as visa
import pyvisascope
import multitimer
import time
import yaml
import logging
visa.log_to_screen('INFO')
logger = logging.getLogger('pyvisa')
log2file = logging.FileHandler('experiment.log')
logger.addHandler(log2file)
def main():
# enter here the ID of your device. On windows, VISA you c... |
bba39c43c4a799fd88b966648ae3a27d4f6eccc9d086dbf737b750b9d5542474 | Python | 1,888 | 62 | import random
from analognasbench.data import AnalogNASBench, DriftMeasurement
def random_search_analog_nasbench(
num_samples=100,
objective_metric='analog_drift_86400',
seed=42
):
"""
Perform a random search over the AnalogNASBench to find
the architecture with the best (maximum) 'analog_drift... |
bfc9a7ca7aef2c6ccfcd78062007bbb9af5147b0667faf80d688288311e25251 | Python | 1,888 | 53 | """
Task-difference control analysis.
This script tests whether a task-difference IBS change variable explains the
same cooperation-gain outcomes. It is intended as a control analysis to show
that the main brain-behavior association is specific to cooperation-related IBS.
"""
from pathlib import Path
import pandas as... |
81d478b729310c7da92c5c1f58585e68d4172021c033c874dc5a18540f584e31 | Python | 1,889 | 52 | import os
import pytest
import numpy as np
import SimpleITK as sitk
import torch
from pathlib import Path
@pytest.fixture
def test_data_dir():
"""Return the directory with test data."""
return Path(__file__) / "test_data"
def dice_loss(pred: torch.Tensor, target: torch.Tensor, smooth: float = 1e-5, reduce: bo... |
91c7ac4eeea396098279e3e93b10d03a7561c41fc6b99f62bbd76cef62843917 | Python | 1,889 | 68 | import os
import os.path as osp
import ssl
import sys
import urllib
from typing import Optional
import fsspec
from torch_geometric.io import fs
def download_url(
url: str,
folder: str,
log: bool = True,
filename: Optional[str] = None,
):
r"""Downloads the content of an URL to a specific folder.
... |
b1fd7356cf063a4f9b929ddae70ae8b2749e57e46edf6904f415e36ab3d5a7e2 | Python | 1,889 | 70 | import os
import glob
from ._prediction_widget import PredictionWidget
from ._training_widget import TrainingWidget
from ._log_widget import LogWidget
from ._data_transform_widget import DataTransformWidget
from qtpy.QtWidgets import (
QVBoxLayout, QHBoxLayout,
QTextEdit, QLabel,
QPushButton, QComboBox,
... |
27228afd2138e2cd42774d8b65f2da639821c0aa892d1e372e6652c755fc4ffe | Python | 1,890 | 57 | # Load a triangle graph, and calculate the distance to the edge of the graph for every triangle.
# Use the pycurv triangle graph tools to identify the edge, the calculate minimum geodesic distance
# from each triangle to the edge.
from pycurv import TriangleGraph, io
from graph_tool import load_graph
from scipy.spat... |
8598c944253a33fbb1b71eb1b5a3fe77c29cf931bb332d731367036eb4492e0c | Python | 1,890 | 77 | #!/usr/bin/env python2.7
import sys
import numpy
import math
from lowess import lowess
import struct
GC_normalize = sys.argv[1]
normalize = open(GC_normalize,'r')
x = []
y = []
stdev = []
i = 0
ave = 0
count = 0
maxCov = 0
for line in normalize:
arr = line.split()
x.append(float(arr[0]))
y.append(float(arr[1]))
... |
3e630995bd99d43c17250266409f2b636815c4156d6b068192fdfc8fc2cd0fc4 | Python | 1,891 | 51 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import json
import os
import tempfile
from scilpy import SCILPY_HOME
from scilpy.io.fetcher import fetch_data, get_testing_files_dict
# If they already exist, this only takes 5 seconds (check md5sum)
fetch_data(get_testing_files_dict(), keys='surface_vtk_fib.zip')
tmp_d... |
e498900bbddac08602208d6b433f1639ffa3b592b874d0c50e25bb842139f6cf | Python | 1,891 | 71 | import os
import sys
import json
"""
Dumps ARA JSON as a flattened file that we can feed into our tree reader
"""
def is_valid_json_file_path(fname):
if not os.path.exists(fname):
print("Can not find file " + fname)
return False
if not fname.lower().endswith('json'):
print("Data shou... |
2585797635f8f45d50c16d15aaca7e9a11a736d9120da41abe7c81bf0e24e8dc | Python | 1,892 | 39 | #!/usr/bin/env python3
import pandas as pd
import argparse
import os
parser = argparse.ArgumentParser(description='Aggregate RNA-SeQC metrics from multiple samples')
parser.add_argument('input_files_tsv', help='TSV file with paths to metrics files')
parser.add_argument('prefix', help='Prefix for output file name')
par... |
5bb341bca7ca5520ed75ba56d36ee6afb06be68906360a85e73a17e231e93bd8 | Python | 1,892 | 70 | from collections import defaultdict
import torch
import torch_geometric.typing
from ._compile import compile, is_compiling
from ._onnx import is_in_onnx_export
from .index import Index
from .edge_index import EdgeIndex
from .seed import seed_everything
from .home import get_home_dir, set_home_dir
from .device import ... |
6dcf8ea0fde61413f52f8a03e5bd6f3fd1524f490b91744c77614c9d68137c1b | Python | 1,892 | 61 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import json
from pathlib import Path
from ultralytics.utils import LOGGER
def onnx2mnn(
onnx_file: str,
output_file: Path | str,
quantize: int | str | None = None,
metadata: dict | None = None,
... |
6eefc1299be2ec0968f55589079ee4542a4ca69ca192e45e9b1f0f98dbb4eff4 | Python | 1,892 | 65 | import glob
import os.path
import numpy as np
import skimage.io as io
import torch
import zarr
from torch import Tensor
def convert(base_dir):
if os.path.isdir(base_dir) and not base_dir.endswith(".zarr"):
files = glob.glob(os.path.join(base_dir, "*.trch"))
else:
files = [base_dir]
print(... |
0b7d0707ae5eb3bf0fdfaab3f3defd7d49d0d08241a8e5f4adb3a03c15272ab4 | Python | 1,893 | 59 | # 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
import os
from datetime import datetime
# -- Project information ---------------------------------------------------... |
1ce8846b8c6fc499e1e97f53d076e18185bc2c2f075b9074510b651ae57a2cff | Python | 1,893 | 81 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import io
import warnings
import tqdm
from cvat_sdk.core.helpers import DeferredTqdmProgressReporter, TqdmProgressReporter
from cvat_sdk.core.progress import NullProgressReporter, ProgressReporter
def _exercise_reporter(r: ProgressReporter) -> Non... |
94039e9cbadae2c64a8e34822089d4bc73de286af036911ed9c02658796b5d78 | Python | 1,893 | 46 | import numpy as np
import math
import soundfile as sf
import librosa
def raised_cosine(x, mu, s):
return 1 / 2 / s * (1 + np.cos((x - mu) / s * math.pi)) * s
def apply_raised_cosine_window(audio, sr, ramps_padding_window_duration):
window_len = int(sr * 0.001 * ramps_padding_window_duration)
left_raised_... |
a380e4d106326e554dd6dade5b2d575f1ce1a0ce78d91378732c343f13b1bed4 | Python | 1,893 | 55 | #!/usr/bin/env python
"""
Emulated Z stage functionality
Hazen 04/17
"""
from PyQt5 import QtCore
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
import storm_control.sc_hardware.baseClasses.lockModule as lockModule
class N... |
349e63245801a336f57f98bb1bb5ec216cd77b98a6cb0faffb66bdb1659ffbc4 | Python | 1,894 | 65 | """
Curve fitting examples
for the Look Locker sequence with a given SNR
"""
import matplotlib.pyplot as plt
import numpy as np
import click
from look_locker import curve_fit_wrapper
def f(t, x1, x2, x3):
return np.abs(x1 * (1.0 - (1.0 + x2**2) * np.exp(-(x3**2) * t)))
@click.command()
@click.option("--values... |
61e9d7abf97f067c9323bbe2070fd53234dc33f469a1b3ae58bfc8ef7882676e | Python | 1,894 | 70 | #!/usr/bin/env python3
# tifffile/lsm2bin.py
# Copyright (c) Christoph Gohlke
# SPDX-License-Identifier: BSD-3-Clause
"""Convert [MP]TZCYX LSM file to series of BIN files."""
from __future__ import annotations
import argparse
import sys
try:
from .tifffile import lsm2bin
except ImportError:
try:
fr... |
5e40a8439d4afd4e4e8c8ce568bce4201c5f891d55cfaf527d4449bccdd6ba1a | Python | 1,895 | 42 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'filter-wheel.ui'
#
# Created by: PyQt5 UI code generator 5.7
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_Dialog(object):
def setupUi(self, Dialog):
Dialog.setObje... |
1db785d8824b6ab2acfe9bfab1418eaf6263575f1df68942f9a5109f154e93ae | Python | 1,896 | 71 |
#!/usr/bin/env python3
import sys
from optparse import OptionParser
USAGE = """
python combine-trf.py --segments < segments file> --trfdir <dir where trf out .dat files are> --out <out file name>
combine the split trf files into a single file
"""
################################################################... |
6e92b0fde295a0f588aa2da42d188784f700be88cf50c9005849aea8742c3656 | Python | 1,897 | 57 | #!/usr/bin/env python
# coding: utf-8
# In[3]:
import scvelo as scv
import numpy as np
import torch
import matplotlib.pyplot as plt
import pyrovelocity as pv
from pyrovelocity.tasks.data import download_dataset
from pyrovelocity.tasks.preprocess import preprocess_dataset
from pyrovelocity.tasks.train import train_d... |
6c8544b2e1bc59b39ca92d24a78d77bca573c471b80358d2a32240b4212b08c3 | Python | 1,898 | 48 | import sys
from pathlib import Path
p_dir = str(Path(__file__).absolute().parents[2])
if p_dir not in sys.path: sys.path.insert(0, p_dir)
import os
from os.path import join
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
class cbr_tiny_hydra(nn.Module... |
d43d207fb9ee8e3b9093ff2029d2d67df87e6b3dbc9af3bb956a037a38a4c179 | Python | 1,898 | 57 | ################## PURPOSE #################
# This script is to remove duplicated coordinates reulted from Bedtools merging
# and removes NULLs if they are not stand-alone values in a cell
################# ASSUMPTION ###############
############################################
# Imports in the pep8 order https://... |
614b5e9c95849f3cc1c68251f3b52cd32ad377ba3ffa3ef2049e66df5dcb0f9f | Python | 1,899 | 30 | """Snapshot telomere pathway hierarchy for annotation, never replace frozen memberships."""
import datetime,hashlib,json,re,subprocess
from pathlib import Path
ROOT=Path(__file__).resolve().parents[2]
OUT=ROOT/'data/raw/context/reactome_dna';OUT.mkdir(parents=True,exist_ok=True)
manifest=ROOT/'metadata/reactome_dna_ann... |
d496a1a2dbf5d6bb668da0b608c48ec86b2da4e8abd5c0887568c081f581ed0a | Python | 1,899 | 73 | """
Classes for implementing `Pipeline`s composed of `Filter`s (intended to be
subclassed).
"""
import abc
class Filter(abc.ABC):
def run(self, reader, writer):
for block in reader:
block = self(block)
if block:
writer(block)
def step(self, reader, writer):
... |
81d9b9b97b9b6f5d4fcb88ea260201c39ec6d4d7852f5ad34a825193f2c06b52 | Python | 1,900 | 57 | ################## PURPOSE #################
# This script is to remove duplicated coordinates reulted from Bedtools merging
# and removes NULLs if they are not stand-alone values in a cell
################# ASSUMPTION ###############
############################################
# Imports in the pep8 order https://... |
93fbb4404e64dbfa7a587b7025830c81ccc2a0b8efa821f6477dadf8a456fd21 | Python | 1,900 | 37 | import os
from .utilities import run_cmd
command_based_on_os = {'Ubuntu': ['wget --output-document sratoolkit.tar.gz https://ftp-trace.ncbi.nlm.nih.gov/sra/sdk/current/sratoolkit.current-ubuntu64.tar.gz'],
'CentOS': ['wget --output-document sratoolkit.tar.gz https://ftp-trace.ncbi.nlm.nih.gov/s... |
b811a181c0b166699678f5526e7ef305c819e7839501cfee05aa6b0a93f597a9 | Python | 1,900 | 46 | import subprocess
import os
import pandas as pd
import argparse
import glob
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--log_dir", required=True, help="Directory containing *.log.txt files for all subjects.")
parser.add_argument("-o", required=True, help="Output file.")
args =... |
d8d8bfd0ce4e2cf76e69b618ce23cf800cfb5e2bd181ceddb7f6517e803b4fd3 | Python | 1,900 | 60 | from .generic import GenericH5
from glob import glob
from os.path import join, isdir
from os import makedirs
from torchvision import datasets
__all__ = ['download_synth', 'SynthTrain', 'SynthVal', 'SynthTest']
def download_synth(directory, url='https://celldetection.org/data/synth.zip'):
"""Download Synth.
... |
7e7a6716f2df184228ea9f9844c146b4573a67630dd5388e7fe5eda5fbf4efc3 | Python | 1,902 | 54 | """Example code for plotting connectivity maps based on a correlation matrix.
In this example we use the inferred state/mode covariance matrices to
calculate the state/mode correlation matrix.
In this script we use an HMM fit, but this can be easily substituted for
a DyNeMo fit.
"""
import os
import numpy as np
fro... |
b2ed7533057461d881f531127c48ed6b107822da099d5f6cda9f743255e587bc | Python | 1,902 | 51 | from nab.detectors.base import AnomalyDetector
from nab.detectors.skyline.algorithms import (median_absolute_deviation,
first_hour_average,
stddev_from_average,
stddev_from_moving_a... |
997b7f9995c7704b66d2598b91c59e0703cae59a66331e95e856bbb3749f342f | Python | 1,903 | 69 | #!/usr/bin/env python
import re
DL = 0
def getblocks(rank, time):
with open('{:06d}/comm.log'.format(rank)) as origin_file:
list = []
for line in origin_file:
found = re.findall(r'^\s*{} BLKL.*'.format(time), line)
if not found:
continue;
list.append(found[0])
return list[DL].s... |
d293e66f7e03cbecdfffb9464127284799e585e71f5b3033c6235fcd53ebd338 | Python | 1,903 | 46 | # Copyright (C) 2020-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import os.path as osp
import zipfile
from glob import glob
from datumaro.components.dataset import Dataset
from datumaro.plugins.transforms import Rename
from cvat.apps.dataset_manager.bindings import Get... |
27af46bdb370259ea468b42311e93528c6c25e4c473a36bab166afb07181dfc4 | Python | 1,904 | 68 | # -*- coding: utf-8 -*-
# python standard library inputs
import os
import datetime
from shutil import copyfile
# external inputs
import numpy as np
from sh import gunzip
# local inputs
from ..io.get_filename import get_filename
def resample_volume(file_in, file_out, dxyz=[0.4, 0.4, 0.4], rmode="Cu"):
"""Resamp... |
927682eb75a0af0638cad1d9edc87a885e1d959d698288ac4fe3927dd41dddc6 | Python | 1,904 | 59 | """AIMNET2 foundation models parameters for ChemGraph
"""
from pathlib import Path
from typing import Optional, Union
from pydantic import BaseModel, Field
class AIMNET2Calc(BaseModel):
"""AIMNET2 calculator configuration.
This class defines the configuration parameters for AIMNET2 machine learning models
... |
b9e7604a72c0563ec139e0d2f4a383caecff595a1f3b8a9cbc8dc31b1a55c1e3 | Python | 1,904 | 64 | import django.utils.timezone
from django.db import migrations, models
import cvat.apps.engine.models
def add_created_date_to_existing_jobs(apps, schema_editor):
Job = apps.get_model("engine", "Job")
jobs = Job.objects.prefetch_related("segment__task").all()
for job in jobs:
task = job.segment.ta... |
4df62d6560302c8b1662dd60f0e8bfb373fe7e6fb499c53730983efc0b4bb774 | Python | 1,905 | 51 | # ==============================================================================
# Binaries and/or source for the following packages or projects are presented under one or more of the following open
# source licenses:
# setup.py The OpenLane Dataset Authors Apache License, Version 2.0
#
# See:
# https://g... |
52dbb85bf7617daa28f3a2c4045714d39e91e02393bd640c881d4fbc982e2788 | Python | 1,905 | 57 | #!/usr/bin/env python
# coding: utf-8
# In[3]:
import scvelo as scv
import numpy as np
import torch
import matplotlib.pyplot as plt
import pyrovelocity as pv
from pyrovelocity.tasks.data import download_dataset
from pyrovelocity.tasks.preprocess import preprocess_dataset
from pyrovelocity.tasks.train import train_d... |
ab006a46e4f0d53c3af575f2a428c655da96c7cbc67b1e72d735e3ab71b9dd8b | Python | 1,906 | 69 | # pylint: disable=line-too-long
import argparse
from datetime import datetime
from deepreg.predict import predict
name = "unpaired_ct_abdomen"
ckpt_index_dict = {"comb": 5000, "unsup": 5000, "weakly": 5000}
parser = argparse.ArgumentParser()
parser.add_argument(
"--method",
help="Training method, comb or uns... |
be1c3db42029b1db470936a5270172d97786a92ce7fe92ca9d0f12b4df02e319 | Python | 1,906 | 54 | import os
import pandas as pd
import yaml
from pathlib import Path
from drop.config.SampleAnnotation import SampleAnnotation
def fixSampleAnnotation(input_file, output_file):
"""
:param input_file: sample annotation file with relative paths
:param output_file: location for sample annotation file with abso... |
78aa4cf5a3ee66778b8fbef09820ee1a84bff3ace08081fa303f55b261bc3274 | Python | 1,907 | 30 | import os
from nipype.interfaces.base import (CommandLineInputSpec, CommandLine, traits, TraitedSpec, BaseInterface, BaseInterfaceInputSpec, File)
from traits.api import Directory, Str, List, Bool, Enum, Int, Float, TraitError, Either
class SegCSVDPVSInputSpec(CommandLineInputSpec):
t1w = Str(mandatory=True, argst... |
a8086b54d0e1ea2f711e8556c39e83e9e1ee5a337bd19a606636c4f8bdf4f103 | Python | 1,907 | 22 | from brainscore_vision import model_registry
from .helpers.helpers import CORnetCommitment, _build_time_mappings
from .model import get_model, TIME_MAPPINGS, get_layers
### ReAlnet01_cornet with different fields of view than 8 visual degrees (default) ###
# exploring 4, 12, 16 visual degrees
# code is adapted from the... |
ac241f43d3f76a0224cb7573727f83c62e55c413b39b18ee3842e171fb5f382e | Python | 1,907 | 74 | """ChemGraph package metadata."""
from importlib.metadata import PackageNotFoundError, version
from pathlib import Path
from typing import Any
_DISTRIBUTION_NAMES = ("chemgraphagent", "chemgraph")
def _load_toml(path: Path) -> dict[str, Any]:
"""Load TOML data from a file path.
Parameters
----------
... |
645dbe44ada3a3a9987105149bd45cba88b52f052148e0450c8be4629507c63c | Python | 1,908 | 60 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
"""Authenticate without putting a token in your code: use a saved profile.
Create a profile once on the command line, then any script can use it:
cvat-cli --server-host 'https://app.cvat.ai' profile create --name app --set-default
Steps:
1. If... |
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