sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
4c0954ce965857130a5ea1f0b0611d4b22c441954d024c3f523ef835e0ecd14e | Python | 1,601 | 43 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" MLP model classes and functions """
import torch
import torch.nn as nn
import... |
7090428e262f202171b4dc9beb0495edf2e8e80a700e6b2f7eff842e2cc109cf | Python | 1,601 | 53 | # -*- coding: utf-8 -*-
# @Author: gviejo
# @Date: 2022-09-09 11:59:30
# @Last Modified by: gviejo
# @Last Modified time: 2022-09-15 13:51:30
"""Tests of Suite2P loader for `pynappple` package."""
import os
import warnings
import numpy as np
import pandas as pd
import pytest
import pynapple as nap
path = "nwbf... |
8fd1c32af4e0e837f7838be1028eb59bb4056285317c4bc5ed7311bbb98a701f | Python | 1,601 | 68 | from functools import lru_cache
import numpy as np
from working.synthetic_data.splicing_mechanism.motif.psam_motif import PSAMMotif
from working.synthetic_data.splicing_mechanism.basic_splicing_mechanism import (
BasicSplicingMechanism,
BasicEffect,
)
@lru_cache(maxsize=None)
def mechanism():
rng = np.ra... |
a3afadb8cd124f257862471042368129dafdb64868953135f7244a2a7c02cc25 | Python | 1,601 | 54 | # -*- coding: utf-8 -*-
# @Author: gviejo
# @Date: 2022-04-04 22:40:51
# @Last Modified by: gviejo
# @Last Modified time: 2022-08-19 09:09:23
"""Tests of CNMFE loaders for `pynapple` package."""
import warnings
import numpy as np
import pandas as pd
import pytest
import pynapple as nap
@pytest.mark.filterwarn... |
69da5d0bb0f9617e7fbbdda3b009686f724cf92a76d17330936bb5b2a7912847 | Python | 1,602 | 57 | from numpy.testing import assert_array_equal
import pytest
from pyriemann.channelselection import ElectrodeSelection, FlatChannelRemover
pytestmark = pytest.mark.numpy_only
@pytest.mark.parametrize("kind", ["spd", "hpd"])
@pytest.mark.parametrize("use_label", [True, False])
@pytest.mark.parametrize("use_weight", [... |
790357a32195fa30ab7257fe7a3749e1e96195b341c374f94acfd507c366278f | Python | 1,602 | 39 | # Copyright (c) 2020 PaddlePaddle Authors. 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 app... |
9a7d4250abb8c5baf520575d1418e6c064400c1e809dc3e01eebb8f0638a22ce | Python | 1,602 | 37 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" Localization FASTA file loading functions """
import numpy as np
import torc... |
05f4bbd74dd3e83e12ee485b950ba1a3b3496108666df7097a8396d87027dde2 | Python | 1,603 | 52 | from collections.abc import Iterable
from typing import (
TYPE_CHECKING,
)
from galaxy.model import (
DatasetCollectionElement,
HistoryDatasetAssociation,
)
from . import BaseDatasetCollectionType
if TYPE_CHECKING:
from . import DatasetInstanceMapping
FORWARD_IDENTIFIER = "forward"
REVERSE_IDENTIFIER... |
1eda98407f767aea257e62bc95426a13e6c8b47f057836a092d2d51162f45e4c | Python | 1,603 | 37 |
'''
Main PyMicroCT script.
Assuming main.py is launched from appropriate folder containing subfolder ./data/
Good idea to have an alias for executing main.py, e.g. in ~/.bash_aliases:
alias pmct='python3 /path_to/PyMicroCT/main.py'
Example:
start_folder/ -> where main.py is executed.
├── analysis -> folde... |
6ebee01b5ce5a7dd1b5474a853baec5ad59ada692f14f1d44700993ba3b04fa8 | Python | 1,603 | 43 | from io import open
from os import path
from setuptools import find_packages, setup
import versioneer
here = path.abspath(path.dirname(__file__))
# Get the long description from the README file
with open(path.join(here, "README.md"), encoding="utf-8") as f:
long_description = f.read()
# Arguments marked as "Re... |
53544f02566ed9f1e7e94c43240f4b591d0c1fed1f0ed6f582385f7e6c2d551b | Python | 1,604 | 38 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
8d76837843b3e42dbecbd047ba098e90ce820e71489eaf022e3281da0ea27c46 | Python | 1,604 | 46 | def reformat_argument_for_model(m, xy, evaluation_criterion):
"""
Produce the reformatted argument for the model, given the original argument.
This handles data in batch form, so it has shape (N, L, ...).
Also places the arguments in the correct device.
If the argument is a dictionary, the input ... |
bab26038fc56ff3127c5b748c78a59791e4c9a4dd0637bb1ef7a5205c00b734a | Python | 1,604 | 70 | import numpy as np
import paddle
from math import sqrt
from sklearn.linear_model import LinearRegression
def cos_formula(a, b, c):
''' formula to calculate the angle between two edges
a and b are the edge lengths, c is the angle length.
'''
res = (a**2 + b**2 - c**2) / (2 * a * b)
# sanity chec... |
69096be391e7de39e979815647a394aff003ae578fe9eac84e6fa0ee5c528b63 | Python | 1,606 | 48 | import os
import numpy as np
import json
from data import utils
#TODO:
#build file config ( tam thoi dung` san cua model cung cap)
class ModelConfig():
def __init__(self, hidden_units, num_layers, num_outputs, feature_size, input_dim, num_input, scope, output_points_fw, output_points_bw, num_classes):
self... |
0cade69a5d071104c557a555b9df862e5bfcfa19b684c8bc41d7dde56ff2d2aa | Python | 1,608 | 43 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" CNN model classes and functions """
import torch
import torch.nn as nn
clas... |
4d674a5256a0736b5b31be2bd5e78e7ab09b10ceaeed16cd0eecbce2f05861f9 | Python | 1,608 | 45 | import sys
import os
from binascii import b2a_hex
def save_image (lt_image, page_number, images_folder):
"""Try to save the image data from this LTImage object, and return the file name, if successful"""
result = None
if lt_image.stream:
file_stream = lt_image.stream.get_rawdata()
file_ext... |
5999dd4fd8eb0679244bcba3c15c4a9b485369f33ccb8f694951deb7c8173679 | Python | 1,608 | 50 | """Custom callbacks for tensorflow training"""
import collections
import numpy as np
import pandas as pd
from tensorflow.keras.callbacks import Callback
class PandasLogger(Callback):
"""Callback that logs a pandas df to a specified model"""
def __init__(self, tf_model):
self.keys = None
sel... |
ea4e71a97fe023048c02803ae0af6a4bd486f0d53b57e3d8c0828a851dacc3f8 | Python | 1,608 | 44 | import pytest
import torch
from lightly.loss.patch_kernel_alignment_loss import PatchKernelAlignmentLoss
class TestPatchKernelAlignmentLoss:
def test_forward_returns_finite_scalar(self) -> None:
torch.manual_seed(0)
criterion = PatchKernelAlignmentLoss()
loss = criterion(
stud... |
37e20bc6b8c7804bacf6bf07fe728c3130d9b8d5773e2ab434f7ba8690766e66 | Python | 1,609 | 45 | import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
class Generator(nn.Module):
def __init__(self, latent_dim, img_shape, hidden_dim=256):
super().__init__()
feats = int(np.prod(img_shape))
self.img_shape = img_shape
self.fc1 = nn.Linear(latent... |
50d44010694f16e8fa3142a9f8aaaa99c28fc4799db291d9713385ca12247a7a | Python | 1,609 | 39 | """Lightly Model Zoo"""
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
from typing import List
ZOO = {
"resnet-9/simclr/d16/w0.0625": "https://storage.googleapis.com/models_boris/whattolabel-resnet9-simclr-d16-w0.0625-i-ce0d6bd9.pth",
"resnet-9/simclr/d16/w0.125": "https://storage... |
6c7ebd3d7320d5eb8f26a4e6690317448a3a26599a5c8a29dbb4179160837e2a | Python | 1,609 | 53 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division, print_function
import argparse
import numpy as np
import wave
from deepspeech import Model
def main():
parser = argparse.ArgumentParser(description='Running DeepSpeech inference.')
parser.add_argument('--model', ... |
8ec70b607ec801df8a418ed8d1f4cbb30eb5b8ccef24a7756527669970ff9e7f | Python | 1,609 | 44 | """Shape-matrix tests for pad_seqs (dense, bytes and OHE)."""
from __future__ import annotations
import numpy as np
import pytest
import seqpro as sp
from _shape_fixtures import (
SHAPE_PATTERNS,
add_leading_trailing_dense,
assert_broadcast_equal_dense,
)
@pytest.mark.parametrize("pattern", SHAPE_PATTE... |
1fd0dd2137eb9aef0a12a1005b7e64c2baa74eb62a37dc2bf79cc5adac47406a | Python | 1,610 | 39 | #!/usr/bin/env python
"""Custom layer components to be used in model implementations."""
import tensorflow as tf
class StdevLayer(tf.keras.layers.Layer):
"""Layer carrying parameters to be directly optimized, serving as standard deviations in continuous gaussian
policies."""
def __init__(self, n_actions,... |
8fd9088bf131c1cc47d755aefff09bce3203152d56d7b43b1085761e287e2b3c | Python | 1,610 | 52 | import torch.nn as nn
from modular_splicing.models.modules.influence_value.influence_value_calculator import (
post_sparse_types,
)
from modular_splicing.models.modules.sparsity_propagation import (
sparsity_propagation_types,
)
from modular_splicing.utils.construct import construct
class ReducedDimensionali... |
b3b8d1e3d3a6f0bfefcc698ae337769e366400a28c43d51ef84cbdaf075f2af6 | Python | 1,610 | 57 | from copy import deepcopy
from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.batch_size = 15
msp.architecture["splicepoint_model_spec"] = dict(
type="BothLSSIModels",
acceptor="model/splicepoint-model-acceptor-1",
donor="model/splicepoint-model-donor-1",
... |
f95269f27ea244c176e7aa1bfd207704010a0f319f28190fb8eb307bec23244b | Python | 1,610 | 50 | __author__ = 'diana'
import sqlite3
import mysql.connector
src = mysql.connector.connect(user='root', passwd='mysql',
host='localhost',
db='testdb')
table_name = 'img'
with sqlite3.connect('output_sqlite.db', check_same_thread=False) as dst:
src_cur = sr... |
186b2e8ceb1a969fea2dce28d88393b57849a1085a95397f69d41c89c637c5cc | Python | 1,611 | 58 | """
Check whether the primer sequences are in the sequenes.
"""
import logging
import re
# pylint: disable=C0103
# Invalid constant name
logger = logging.getLogger('pipe.primer')
def primer(configs, seqs):
"""Primer check.
Check whether any of the primer sequences appear in the contig. The primer
seque... |
db419ef402d6632dfb1bcb16f44c68f949f489032ed5ef56eac6a19e9072da88 | Python | 1,611 | 40 | from __future__ import annotations
from larvaworld.portal.landing_registry import QUICK_START_MODES
from larvaworld.gui_v2.registry_bridge import build_navigation_model
def test_build_navigation_model_contains_expected_structure() -> None:
model = build_navigation_model()
assert len(model.quick_start_modes)... |
e6fb79f911b98e5bc860589b0af6aabc8e0eb546db2b124d8f2de5f745d7b6b9 | Python | 1,611 | 53 | from setuptools import setup
import setuptools
# with open("README.md", "r") as fh:
# long_description = fh.read()
setup(
name='nanodeep',
version='0.0.3',
packages=setuptools.find_packages(),
url='https://github.com/shadow-lang',
license='MIT License',
author='Yusen Lin',
author_email=... |
be0a8239c6d72341a7aa2268ff02c829e40a87b619182a4f100668648c5e545d | Python | 1,612 | 45 | import re
import geopandas as gpd
from ...tessellation import tilers
import shapely
import pytest
poly = [[[116.1440758191, 39.8846396072],
[116.3449987678, 39.8846396072],
[116.3449987678, 40.0430521004],
[116.1440758191, 40.0430521004],
[116.1440758191, 39.8846396072]]]
geom = [sh... |
1d054d156f6466db355855418499aa59bd166ca82033cc49ecbc68a378e147ff | Python | 1,613 | 45 | import torch
from nitorch import io
from nitorch.spatial import diff1d
from nitorch.spatial import affine_sub
root = '.'
device = 'cuda'
for i in range(9, 24):
print(i)
f = io.map('{root}/lsfm/init_oct/neun_638/down_9.9um/neun.{i:02d}.nii.gz')
dat0 = f.fdata(device=device)
# we are only looking for ... |
4d7078c129ec464ff7c5400b6aa0ef858acb05230d879f55a2d4c458bcef2a15 | Python | 1,613 | 51 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import torch.nn.functional as F
import math
def flag_bounded(model_forward, perturb_shape, y, optimizer, device, criterion, m=3, step_size=1e-3, mag=1e-3, mask=None):
model, forward = model_forward
model.train()
optimiz... |
a1b09079351991bd28b3a12e4a2a6e5eb5cf55a7dc1842a63a4380c8a68c5827 | Python | 1,613 | 57 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = dict(
type="ResidualStack",
depth=3,
)
msp.arch... |
104acc9c7bdc45cd0bf7ba707715ca17c9e6c7acaf7dc56c1d8716db070349c0 | Python | 1,614 | 66 | '''Definition of basic rotation functionality'''
import math
import numpy as np
def spherical_from_vector(vect):
"""Returns the spherical coordinates
of a vector: phi, theta
"""
x, y, z = vect
phi = np.arctan2(y, x)
# pylint: disable=assignment-from-no-return
theta = np.arccos(z / np.li... |
e1b9bb1997480947721eac0fe3ec471ba06692b4b67a8db42c5d350a6264d00e | Python | 1,614 | 48 | import logging
from typing import (
Any,
)
from galaxy.managers import base as manager_base
from galaxy.managers.context import ProvidesUserContext
from galaxy.managers.datasets import DatasetAssociationManager
from galaxy.model import (
LibraryDatasetDatasetAssociation,
User,
)
from galaxy.structured_app ... |
f4a877ff4666e03663d5c88c8433e8950f67ccccea0d8bb635f315527c35a291 | Python | 1,614 | 49 | import os.path
import numpy as np
import pytest
from mirp import extract_images
from mirp.data_import.import_image import import_image
from mirp._data_import.read_data import read_image
# Find path to the test directory. This is because we need to read datafiles stored in subdirectories.
CURRENT_DIR = os.path.dirname... |
f1886681ec400ed070d71f1cb80dc1c0f111c3f7b0f6d65575b0cc297759a028 | Python | 1,615 | 49 | """Transforms for ImageNet series."""
from __future__ import absolute_import
import mxnet as mx
from mxnet.gluon.data.vision import transforms
__all__ = ['transform_eval']
def transform_eval(imgs, resize_short=256, crop_size=224,
mean=(0.485, 0.456, 0.406), std=(0.229, 0.224, 0.225)):
"""A uti... |
5aca7dd8ffd90dcd75153f435b647ab907d75ef9880e0b53dbab1c1b5dc52a15 | Python | 1,616 | 54 | from _plotly_utils.basevalidators import EnumeratedValidator, NumberValidator
class EasingValidator(EnumeratedValidator):
def __init__(self, plotly_name="easing", parent_name="batch_animate", **_):
super(EasingValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_n... |
76bf2b1c40e29e6b2e53e5a8bdab4cb9d3877dd6d2ed049e6e94e19a8f225afd | Python | 1,616 | 49 | """Utilities for loading tools and workflows from paths for admin user requests."""
from typing import (
Any,
)
import yaml
from galaxy import exceptions
from galaxy.managers.context import ProvidesUserContext
from galaxy.util import in_directory
def artifact_class(trans: ProvidesUserContext | None, as_dict: d... |
55fbbc5bb21f492821d42fdd83668078d55abd58ee86ec57fc252e23a92dafdb | Python | 1,617 | 48 | import numpy as np
def kalman_stack_filter(frames, seed='mean', gain=0.5, var=0.05, fn=lambda f:f):
"""Kalman stack filter similar to that of Imagej
Input:
------
- frames: array_like, e.g. nframes x nrows x ncolumns array or list of 2D
images
- seed: {'mean' | 'first' | 2D arr... |
70afcd7097dc4f95536c7ba29e9215a4e83d8b095505b2cbf6c2b53c09d48ec8 | Python | 1,617 | 55 | import os
import random
import time
import h5py
import numpy as np
import scanpy as sc
import tensorflow as tf
import sys
sys.path.append('../pkgs/ZIFA/')
from ZIFA import block_ZIFA
from memory_profiler import profile
def seed(SEED):
os.environ['PYTHONHASHSEED'] = str(SEED)
random.seed(SEED)
np.random.s... |
9a8228f69629eafb2e73a7ecfcc9d7e78ea7df6ecd8a579f93487725cc8cde8e | Python | 1,617 | 39 | from typing import (
cast,
)
from galaxy.exceptions import RequestParameterMissingException
from galaxy.model import DatasetCollectionElement
from galaxy.tool_util_models.sample_sheet import SampleSheetRow
from . import BaseDatasetCollectionType
from .sample_sheet_util import validate_row
class SampleSheetDatase... |
b4b71ec561beed6ce51d4502c78f4a1ccbbd388e704b9c5e69c4830a724d42b4 | Python | 1,617 | 48 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import swapaxes
class TestSwapaxes(unittest.TestCase):
def setUp(self):
raw = np.arange(2000).reshape(-1, 5)
channels = ['ca1', 'ca2', 'cb1', 'cb2', 'cc1']
time = np.linsp... |
d2de26dbba1f42e8894d0d9883398aa21e5414441b56df7c14caf215d4e7c974 | Python | 1,617 | 36 | """Test functions for specparam.params.definitions."""
from specparam.modes.mode import VALID_COMPONENTS
from specparam.params.converter import BaseParamConverter
from specparam.params.definitions import *
###################################################################################################
###########... |
de71a4f893b9f4698d40e8ec411008eabe3fbcd093974481146c4c2c5ae04b00 | Python | 1,617 | 52 | # Copyright 2025 Google.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, soft... |
0338c9f0aa3e26cb211bcf729b3a2e6d09d73a408d0b0c6f2b847b9b2cc3a67f | Python | 1,618 | 47 | #!/usr/bin/env python
"""
convert fastqsolexa file to separated sequence and quality files.
assume each sequence and quality score are contained in one line
the order should be:
1st line: @title_of_seq
2nd line: nucleotides
3rd line: +title_of_qualityscore (might be skipped)
4th line: quality scores
(in three forms: a... |
4fe3bda7dbe17b755ad1fcee1c747258563926f823b646ca0362863e1579d5cf | Python | 1,618 | 43 | import tempfile
import unittest
from unittest.mock import patch
from cellxgene_gateway.items.file.fileitem_source import FileItemSource
def stub_join(path):
path.join = lambda x, y: x + "/" + y
class TestFileItemSource(unittest.TestCase):
@patch("os.path")
@patch("os.listdir")
def test_list_items_G... |
7ddca9cac19f4ca353d0d7e223ff32730ae4788855c5c31f6232ada837ff136a | Python | 1,618 | 53 | import numpy as np
import torch
import torch_geometric
from torch_geometric.data import Data
from data_loading.loading_utils import train_scaler, scale_dataset, select_target_id
TARGET_ID_TO_PROPERTY = {
0: 'GFN2:TOTAL_ENERGY',
1: 'GFN2:ATOMIC_ENERGY',
2: 'GFN2:FORMATION_ENERGY',
3: 'GFN2:TOTAL_ENTHA... |
d40bf2ee540d4c3bce3f52f085341c84ffbd3b4f0c58272409a40eedd9f9be37 | Python | 1,618 | 53 | import os
import sys
if sys.version_info >= (3, 9):
from importlib.resources import files
else:
from importlib_resources import files
from find_libpython import find_libpython
# try to add libpython*.so path to environment if not already set
try:
os.environ["NMODL_PYLIB"] = os.environ.get(
"NMODL... |
089c2d25f643ff96ba51ba12deaeb29db4e69eb24f87dde53b9e79f9c3b62ef9 | Python | 1,619 | 62 | """Steer with a per-position direction.
What this demonstrates
----------------------
Add a direction tensor with the same non-batch shape as the matched out.
This mirrors per-position steering for sequence models while using a tiny
feed-forward toy.
How to run
----------
``python examples/intervention/14_per_positio... |
0eb1aae52e7fb35d78324958b070ed035f4ff591a3225dbda06d11350aa70ee8 | Python | 1,619 | 65 | """Attach an SAE-style helper with ``splice_module``.
What this demonstrates
----------------------
Use an ``nn.Module`` as a black-box out splice. The module here mimics
an SAE decode-after-encode operation while preserving shape.
How to run
----------
``python examples/intervention/11_sae_attachment.py``
Runnable ... |
4a154ba54b2ea803ec55d24b61a54afea12a87ffaf46b7fab471c2a9fa027f16 | Python | 1,619 | 55 | import http.server
import multiprocessing
import os
import socketserver
import sys
from pathlib import Path
import pytest
def _httpd(wconn, directory):
class QuietHTTPServer(http.server.HTTPServer):
def server_bind(self): # Work around actions/runner-images#14568
socketserver.TCPServer.serve... |
4c6f3859aa0bffcbb2c67ae5c8ed932526d136bdf1dcb864cde31cfe56df3998 | Python | 1,619 | 46 | import opencc
def _check(actual, expected):
if actual != expected:
raise AssertionError('expected {!r}, got {!r}'.format(expected, actual))
def main():
print('opencc module:', opencc.__file__)
print('opencc version:', opencc.__version__)
assert opencc.__version__, '__version__ must be non-em... |
623dc51e4c8bd71a1e901c683e7e2d553e538746971239b26ad9a5c12184d771 | Python | 1,620 | 70 | # path vari
import pathlib
#AMINOACIDS = ['ALA', 'ARG', 'ANS', 'ASP', 'CYS', 'GLU', 'GLN', 'GLY', 'HIS', 'ILE',
# 'LEU', 'LYS', 'MET', 'PHE', 'PRO', 'SER', 'THR', 'TRY', 'TYR', 'VAL']
AMINOACIDS = {
'ALA': 0,
'ARG': 1,
#'ANS': 2,
'ASN': 2,
'ASP': 3,
'CYS': 4,
'GLU': 5,
'G... |
86db91a1189cff34ffd0cc86ae9ebdcff8074c723de656eea1a8175f4f6cc97e | Python | 1,620 | 46 | import os
from typing import (
Any,
cast,
TYPE_CHECKING,
)
if TYPE_CHECKING:
from galaxy.config import GalaxyAppConfiguration
class PopulateConfig:
"""Minimal config the tool source store populator reads, with a sqlite store under ``root``."""
enable_beta_tool_formats = False
tool_search... |
a9a2c7dea1c368f1f5693424af0f6d7b5540dc8c5efc4b48c9dc0ac15037f9ab | Python | 1,620 | 68 | import wandb
api = wandb.Api()
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
from plot_params import get_plot_params
get_plot_params()
from ase import units
if __name__ == "__main__":
"""Plot the variation of the validation loss with the fraction of the training data used."""
... |
eddd3ef2ab565f75c63a691863eba09ef6ff897a1ff90e05854f6e0e41430e34 | Python | 1,620 | 48 | # Generated by Django 3.0.4 on 2020-03-25 09:59
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0069_auto_20200325_1009'),
]
operations = [
migrations.CreateModel(
name='MushroomPic',
fields=[
... |
f32e89b0fa369b7f74bc7acf7380f8e80b30afc7667d0414ce0cd1cd6472e6dc | Python | 1,620 | 52 | import os
import random
import h5py
import numpy as np
import scanpy as sc
import tensorflow as tf
import sys
sys.path.append('../pkgs/ZIFA/')
from ZIFA import block_ZIFA
from scbig.utils import louvain, calculate_metric
def seed(SEED):
os.environ['PYTHONHASHSEED'] = str(SEED)
random.seed(SEED)
np.rando... |
9a07f2cb437597e5fc65a11b8c00f91de5af837fb30c2306eec4a1350d8210d3 | Python | 1,621 | 61 | from .bulletin import Bulletin
from bs4 import BeautifulSoup
import re
class MadhyaPradesh(Bulletin):
def __init__(self, basedir):
statename = 'MP'
super().__init__(basedir, statename)
def get_bulletin_links(self):
burl = "http://sarthak.nhmmp.gov.in/covid/health-bulletin"
... |
b1ad3681b25e3ecf0ccf45b7c0af4a006621e8f19bf7147acdf775c6f5234d02 | Python | 1,621 | 54 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["splicepoint_model_spec"] = dict(
type="BothLSSIModels",
acceptor="model/splicepoint-model-acceptor-1",
donor="model/splicepoint-model-donor-1",
)
msp.architecture["motif_model_spec"]["motif_... |
b5bbb8a804feb687338f4887fa2c5c6f2a2549cc1eaf5d1a6bf7443010c2cdd7 | Python | 1,622 | 54 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["splicepoint_model_spec"] = dict(
type="BothLSSIModels",
acceptor="model/splicepoint-model-acceptor-1",
donor="model/splicepoint-model-donor-1",
)
msp.architecture["motif_model_spec"]["motif_... |
f9619c76268bfcf1e67aefe6b4c088f70ff8066d814d17dc3e95bc1152844068 | Python | 1,622 | 52 | import cv2
import numpy as np
import matplotlib.pyplot as plt
# 读取图像并转换为灰度图像
img = cv2.imread('img.png')
shape = img.shape[0]
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 对灰度图像进行CLAHE增强
clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
gray_clahe = clahe.apply(gray)
# # 使用高斯滤波器平滑图像
# blu... |
12e2528a88c9a0107de95db56108a70ebb66c9d0b574072180d66c7898ba249a | Python | 1,623 | 60 | import numpy as np
from neuron import h, gui
from neuron.units import ms
# In the INITIAL block an event is sent to itself using `net_send`. Once for
# POINT_PROCESS (toggle.mod) and once for ARTIFICIAL_CELL (art_toggle.mod).
#
# When the event is received the variable `y` is "toggled" to 1. This happens
# at differe... |
23ca7a4c08edf8f0dc898e3377f0c9ec016a612bb21629dae2bdf729ddb63157 | Python | 1,623 | 36 | # -*- coding: utf-8 -*-
import sys
sys.path.append('./src/')
import argparse
import json
import os
import torch
from data import GeneratorData
from src.generator_lstm import Generator
'''Loading config'''
parser = argparse.ArgumentParser(description="you should add those parameter for pretrain")
parser.add_argument("-... |
53fa6e7ed4d6e2141d817c589e3ca92475e4c857f327abcda81a9265bed5fdd4 | Python | 1,623 | 53 | from src.datasets.base import BaseDataset
from src.datasets.mineault.pvc1 import PVC1
class PVC1Dataset(BaseDataset):
def __init__(self, root, split, ntau, idx, repeats=True, normalise=True, scale=1):
super().__init__(normalise, scale, True)
split = "traintune" if split == "train" else "report"
... |
c8b12baf56a7f8749a9ab6c62248d81fa200ba9466060348c4f1f0066a7b2506 | Python | 1,623 | 83 | #!/usr/bin/python
### arguments
# 1. filedir
# 2. file name
# 3. headers (":" separated)
# 4. sort col
# 5. sort col dir
# 6. start
# 7. length
###
import os
import sys
import re
import pandas as pd
import numpy as np
if len(sys.argv) < 8:
sys.exit("ERROR: not enought arguments\nUSAGE: ./dt.py <filedir> <file> <dra... |
5a3da4936fd9daea64cc255dbf5efdf5d1902872e530410fb18371acfe60a6c1 | Python | 1,624 | 60 | #!/home/ubuntu/miniconda2/bin/python
from __future__ import division
import sys
import glob, os, gc
import uuid
import os.path
import csv
import numpy as np
from time import time
from subprocess import (call, Popen, PIPE)
from itertools import product
import shutil
import re
import pickle
from boto3.session import Ses... |
7c8cee10cf73224abbfbc37256c75776c36683209f2f175ab069491c8dd57370 | Python | 1,624 | 56 | """
Visualization of MCell4 3D reaction-diffusion simulations. Original simulations run in CellBlender.
Last updated 6.8.2026
Author: Saana Seppälä
## Description
This script reads the .dat output files from the MCell4 simulation with CellBlender, visualizes them and
reorganizes all variables (time, calcium, calmodul... |
a1aea05083c9749b653a3eb4f994fba84b5e66522d76899bea4d5a5c8057a684 | Python | 1,624 | 59 | import numpy as np
from neuron import h, gui
from neuron.units import ms
def run_simulation():
s = h.Section()
s.insert("side_effects")
mech = s(0.5).side_effects
t_hoc = h.Vector().record(h._ref_t)
x_hoc = h.Vector().record(mech._ref_x)
X_hoc = h.Vector().record(mech._ref_X)
Y_hoc = h.V... |
c112327f8cda05ad112fa9f6802fff716f1f61fc71321d843fe90cb1db45ac41 | Python | 1,624 | 55 | import sys
from bulletin_download.states.DL import Delhi
from bulletin_download.states.GA import Goa
from bulletin_download.states.HR import Haryana
from bulletin_download.states.KA import Karnataka
from bulletin_download.states.KL import Kerala
from bulletin_download.states.MH import Maharashtra
from bulletin_downloa... |
ca9a2cd30320b846fe0ce1cc51d558e4332d5ba65b647ded4d023da05ac0f110 | Python | 1,624 | 46 | """Tests for opt-in fastlog recording enrichments."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.fastlog.exceptions import RecordingConfigError
def _mlp() -> nn.Module:
"""Return a small two-layer MLP."""
return nn.Sequential(nn... |
172459798a856f06e44e1d38f48be9cab820027c4d62821a1ac88b461ad856bb | Python | 1,625 | 43 | #!/usr/bin/env python
import sys
def __main__():
input_name = sys.argv[1]
output_name = sys.argv[2]
skipped_lines = 0
first_skipped_line = 0
i = 0
with open(input_name) as fh, open(output_name, "w") as out:
for i, line in enumerate(fh):
line = line.rstrip("\r\n")
... |
7f8e03298983f48f4141f179f330cda4e769884589c4e1bf33a7d73bf1100054 | Python | 1,625 | 50 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Simple volume-preserving MAF on Z-matrix coordinates.
"""
# ==================================================... |
977a4a81de9c5d4734c07cf83fc1ac6fe381a7ee0695197d4262c138e95df158 | Python | 1,625 | 53 | """Tests for documentation code examples using mktestdocs.
This file validates that code blocks in the documentation are correct and
can be executed successfully.
"""
from pathlib import Path
import pytest
from mktestdocs import check_md_file
@pytest.mark.parametrize(
"fpath",
[
"docs/tutorials/pyt... |
aaadf285a505ce7299f6ef55c38e66625f3b0c375098ead447dbf906220f4622 | Python | 1,625 | 62 | # -*- coding: utf-8 -*-
from docutils.parsers.rst import roles
from .directives import (
findoutmoreref,
windowswitref,
)
from sphinx.roles import (
XRefRole,
)
class HandbookRefRole(XRefRole):
"""Custom :ref: roles base class"""
refnodecls = None
refnodeclsname = None
def run(self):
... |
ab729ef27c6d835ecb18a589cdb622e4c3ddb543d1b57afbd488a3cc06b903e2 | Python | 1,625 | 50 | """Test cases for from_coco_panseg.py."""
import json
import os
import shutil
import unittest
import numpy as np
from PIL import Image
from scalabel.common.typing import NDArrayU8
from scalabel.label.coco_typing import PanopticAnnType
from bdd100k.label.from_coco_panseg import panseg2bitmask
class TestFromCocoPanSe... |
0be077d57cb79402c8751406b627cd5cf9f0392e091065fbe0ff9a1d5a93bad8 | Python | 1,626 | 54 | from rpy2.robjects.packages import importr as _importr
from rpy2.robjects.packages import data
import rpy2.robjects.help as rhelp
from rpy2.rinterface import baseenv
from os import linesep
from collections import OrderedDict
import re
class Packages(object):
__instance = None
def __new__(cls):
if cls._... |
a52ead956758248082a9ec7ca10bf97cfdba22d1c2814d34da0826273302f0e0 | Python | 1,626 | 37 | from typing import Any, Optional
import torch.nn as nn
from pl_bolts.models.detection.components import create_torchvision_backbone
from pl_bolts.utils import _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _TORCHVISION_AVAILABLE:
from torchvision.models.detection.backbone_utils im... |
b34189b307a35c765c36b24a1dbcc025213197092d67c53671412867397b8863 | Python | 1,627 | 37 | from typing import Any, Optional
import torch.nn as nn
from pl_bolts.models.detection.components import create_torchvision_backbone
from pl_bolts.utils import _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _TORCHVISION_AVAILABLE:
from torchvision.models.detection.backbone_utils im... |
ca9e9190db9d782bb2bb4b9dff04226f8f10866e296d215963c76eee26e05775 | Python | 1,627 | 50 | """Helper functions about image layer processing.
"""
from typing import Optional
import numpy as np
from anndata import AnnData
def add_image_layer(
adata: AnnData,
img: np.ndarray,
scale_factor: float,
slice: Optional[str] = None,
img_layer: Optional[str] = None,
) -> AnnData:
"""
A hel... |
cd14299c30631e56ad1459556e71e677d3674b08a54cca9996f98f6096c6db46 | Python | 1,627 | 43 | import torch.nn as nn
from modular_splicing.models.modules.positional_encoding import PositionalEncoding
from modular_splicing.models.modules.conv_attn.convolved_attn import ConvolvedAttention
class SingleAttentionLongRangeProcessor(nn.Module):
"""
Uses attention to compute the influence value of each moti... |
3949010d2ef17ada03cfb00e4261c82f711882229ccc6178dc7263365d1cd316 | Python | 1,628 | 40 | """Prepare OTB 2015 dataset
=========================================
`OTB 2015 dataset <http://cvlab.hanyang.ac.kr/tracker_benchmark/datasets.html/>`is Visual Tracker Benchmark.
The full benchmark contains 100 sequences from recent literatures.
This tutorial helps you to download OTB 2015 and set it up for later exp... |
4f401d1b9747e6261cf72b11b425335a6874f4b3d03dd120846ea67a74861f5f | Python | 1,628 | 38 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import seaborn as sns
from tensorflow import keras
from keras import optimizers, layers, metrics
from keras.callbacks import ModelCheckpoint
from sklearn.metrics import confusion_matrix, classification_report, f1_scor... |
9a53e895ad1f8123c6c58d8c90abc686fa00eb7f9baa62460f710efff3785bfb | Python | 1,628 | 58 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 1 + 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_fea... |
61d3bfffe865890e53c0381b7b218621019f8536fc9e4ef30a9072b3040e6dcc | Python | 1,630 | 80 | def build_mir_dic(mirbase):
mir_dic = {}
with open(mirbase) as o_mir:
for line in o_mir:
if line.startswith('>'):
split_line = line.strip().split(' ')
mir_dic[split_line[0].replace('>', '')] = split_line[1]
# print(mir_dic)
return mir_dic
def... |
d93dc8c92bfd9da85308f636548c8bddf47dc7d15de5d42faffc05e72c5a2c16 | Python | 1,630 | 59 | __author__ = 'quentin'
import cv2
import numpy as np
import itertools
def merge_blobs(contours, prop = .5):
"""
Merge together contour according to their position and size.
If the distance between two blobs is smaller than the longest axis of, at least, one of them,
then they get merged.
This algor... |
6e1b94cbe9a8003e204a438c202fe0a7995f74ef42dc2fdeced4352e5ad41bb0 | Python | 1,631 | 50 | import errno
import logging
import os
import signal
from time import sleep
log = logging.getLogger(__name__)
def check_pg(pgid):
"""Check whether processes in process group pgid are still alive."""
try:
pid, exit_status = os.waitpid(-pgid, os.WNOHANG)
except OSError as e:
if e.errno == er... |
73763080b617fe6e73e8b0ef915d56c8eece30e7d32bd01fd74ca12568dff5b1 | Python | 1,631 | 57 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 82
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature... |
972ac4f3ebbb23537c56b10d6daba63dc87b4b2ea0075d6f9dfe087dc8caee7e | Python | 1,631 | 58 | from mirp._images.generic_image import GenericImage
class MRADCImage(GenericImage):
def __init__(self, **kwargs):
super().__init__(**kwargs)
self.calibrated_units = True
@staticmethod
def get_default_lowest_intensity():
return 0.0
def update_image_data(self):
if sel... |
a250a51b322437a44ccc8f5e2cc9617317905eb180d8afb6ef939e2e9ae98a66 | Python | 1,631 | 56 | #!/usr/bin/env python
"""
Remaps a gff file back to genomic intervals using the glimmer3 prediction table.
Author: Bjoern Gruening
"""
import sys
def main():
glimmer_file = sys.argv[1]
gff_file = sys.argv[2]
new_gff_file = open(sys.argv[3], "w")
glimmer_dict = dict()
for line in open(g... |
aefbc92675ca6b6dbd5475e9d05549d7c12761c6f7e9c39f1c5940c1736e9f6b | Python | 1,631 | 57 | import cv2
try:
CV_VERSION = int(cv2.__version__.split(".")[0])
except:
CV_VERSION = 2
try:
from cv2 import CV_LOAD_IMAGE_GRAYSCALE as IMG_READ_FLAG_GREY
from cv import CV_RETR_EXTERNAL as RETR_EXTERNAL
from cv import CV_CHAIN_APPROX_SIMPLE as CHAIN_APPROX_SIMPLE
except ImportError:
from cv2 i... |
2b565fc222736e9a95ddeb5094637400c2601cf3dac0843e89503d6395ce3f7a | Python | 1,632 | 71 | import matplotlib.pyplot as plt
import numpy as np
def get_reference(do_plot=False):
with open('ex.txt', 'r') as f:
s = f.read()
x = [int(a) for a in s[34:-4].split(',')]
if do_plot:
plt.close()
plt.plot(x)
plt.show()
return x
def make_sine(f, fs, NT, phi):
"""... |
74afb24b99a18b5a7b81378c5cdf93be0d4b3c6f432fe354712289f3004c4290 | Python | 1,632 | 50 | import importlib
def relative_import(parent_name, rel_modules=(), rel_classes=()):
"""
Helper function to import submodules lazily in Python 3.7+
Parameters
----------
rel_modules: list of str
list of submodules to import, of the form .submodule
rel_classes: list of str
list o... |
3e5755dcd7e01072662ecea72ea781ce87d07175765a17fbe73c026a230f8f14 | Python | 1,633 | 31 | import os
R = os.path.dirname(os.path.abspath(__file__))
p = os.path.join(R, "run_pipeline.py")
s = open(p).read(); n = 0
for old, new in [
("from classifier_rf_04 import train_evaluate as rf_evaluate, feature_ablation",
"from classifier_rf_04 import (train_evaluate as rf_evaluate, feature_ablation,\n ... |
c744de377bfcca15b1656f67a1b565b5a22ca12c7e5297efa2a47ea2af4b90c0 | Python | 1,633 | 65 | import pytest
from pyrosm import get_data
@pytest.fixture
def test_pbf():
pbf_path = get_data("test_pbf")
return pbf_path
@pytest.fixture
def helsinki_pbf():
pbf_path = get_data("helsinki_pbf")
return pbf_path
def test_parsing_basic_elements_from_pbf(test_pbf):
from pyrosm import OSM
impor... |
b6d95a9b543897b8fcbe761052a14ec964efac7cdc7ca7c97a1451aaca8cb839 | Python | 1,634 | 59 | """Tests for buffer source and sink accessor aliases."""
from __future__ import annotations
import torch
from torch import nn
import torchlens as tl
class BufferWriteModel(nn.Module):
"""Model that reads and writes a registered buffer."""
def __init__(self) -> None:
"""Initialize the registered bu... |
abb5728fd45766450038f774a77f087140448e17356f054138a7704357677292 | Python | 1,635 | 56 | # -*- coding: utf-8 -*-
"""
Created on Tue Dec 21 14:53:21 2021
@author: adrie
"""
import pynapple as nap
import pandas as pd
from sklearn.preprocessing import StandardScaler
import numpy as np
def bayesian_decoder_1d(spike_counts, bin_size, tuning_curves):
spike_counts_array = spike_counts.values
prob... |
ef093dfd9a6e5cb16b9e99fbf49ca7512815b0a7d89d0269a828c086cad5eea2 | Python | 1,635 | 48 | from typing import Optional, Union
from anndata import AnnData
from pathlib import Path
import os
import pandas as pd
import numpy as np
from natsort import natsorted
def labels(
adata: AnnData,
label_filepath: str = None,
index_col: int = 0,
use_label: str = None,
sep: str = "\t",
copy: bool ... |
75ca72084c87d5f5777f551cc79d790cae0aa98141d69e423fe4d45e95a1d3e1 | Python | 1,636 | 43 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
"""Unified gridsearch and shuffled controls. Leverages asynchronous scheduling of Columbia
Yeti cluster to optimally interleave subtasks of each trial type.
Run from the command line with a condition name argument. Optionally, pass the name of
the settings fil... |
83cb4ed33c0e114c35832d1f7b38a3797e6bdceeeced6cfd0f031deefe0577ae | Python | 1,636 | 42 | from __future__ import annotations
import pytest
from pytest_celery import CeleryTestSetup
from celery import group
from t.smoke.tasks import long_running_task
RESULT_TIMEOUT = 30
class test_autoscale_keepalive:
@pytest.fixture
def default_worker_command(self, default_worker_container_cls):
return ... |
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