sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
50ab0a26722eb63d6fd174d22c6dee507b32224f56e5413ef5d3f5524394f3ad | Python | 810 | 32 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
num_motifs = 10
msp.architecture["num_motifs"] = 80 + 2
msp.architecture["channels"] = 200
msp.architecture["motif_model_spec"]["motif_width"] = 13
msp.architecture["motif_model_spec"]["motif_feature_extractor_spec"] = d... |
88d0ffbdb744a41fc97277f9b21417fdf30ce16dad1b009b044bac33e3114cd6 | Python | 811 | 23 | import math
from typing import Optional
def make_divisible(v: float, divisor: int, min_value: Optional[int] = None) -> int:
"""
This function is taken from the original tf repo.
It ensures that all layers have a channel number that is divisible by 8
It can be seen here:
https://github.com/tensorfl... |
aa83207291b674562bbf833d7608d45d7c8b446a506c4f217b43c40be5d094b2 | Python | 811 | 25 | """
This module create TransformerClassifPerAminoAcid
"""
# pylint: disable=W0223
import torch.nn as nn
class TransformerClassifPerAminoAcid(nn.Module):
"""
This class define a Transformer model that classify each amino acid of a protein
"""
def __init__(self, transformer_embedder, num_classes, dropo... |
ae054313680a7f660199d44837eeef21a5a0286f6192a475b75588fee492f8a0 | Python | 812 | 27 | # import the pyabf module from this development folder
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_SRC = os.path.abspath(PATH_HERE+"/../../src/")
PATH_DATA = os.path.abspath(PATH_HERE+"/../../data/abfs/")
sys.path.insert(0, PATH_SRC) # for importing
sys.path.append("../../src/") #... |
ebd109aa4826c071d676b18734558c1137936ee18059a60f7429f563ae45b9fe | Python | 814 | 29 | from pathlib import Path
import nibabel
import pydicom
import numpy
def dcm_to_nii(dcm_folder: Path, nii_file: Path):
"""
Converts DICOM files in a folder to a NIfTI file.
Parameters:
dcm_folder (Path): The path to the folder containing the DICOM files.
nii_file (Path): The path to the N... |
39021ebea8e6572a1a005841e9126f3a5dab063808389b177b45499da371837f | Python | 815 | 30 | import sqlite3
from .db import DB
class CaseInformation(DB):
def __init__(self):
super().__init__()
self.table_name = 'TG_case_info'
self.table_desc = 'Telangana daily new cases, recoveries, deaths information'
self.cols = self.getcolumns()
def getcolumns(self):
col... |
865579dbde1763880b760231cfb1b14b8cb75fef1ad863aa2698dc2ceda805cb | Python | 815 | 20 | """Module defining inputters.
Inputters implement the logic of transforming raw data to vectorized inputs,
e.g., from a line of text to a sequence of embeddings.
"""
from bioseq2seq.inputters.inputter import get_fields, build_vocab, filter_example
from bioseq2seq.inputters.iterator import max_tok_len, OrderedIterator
... |
a996e062415d617031c3d355afe47fa02c031cd3edee3d892d7c4a78846356dd | Python | 815 | 25 | """
Try to figure out how to read file creation date/time from ABF1 files.
19122043.abf according to ABFInfo:
Created: Jan 22, 2019, at 22:22:10.750 [10:56:42]
File GUID: {EA774D20-4346-4219-ACCF-DB3B6DD89ABD}
"""
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.... |
aa7b380852ee86ea80b683c793d87a3c9d1b087eedaf1048af74bd6a42830cd5 | Python | 815 | 36 | """Added organization to project
Revision ID: 3f64cdda4d67
Revises: 951141858cff
Create Date: 2024-06-16 22:27:43.746807
"""
import sqlalchemy as sa
from alembic import op
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision = "3f64cdda4d67"
down_revision = "298059b19bde"
bra... |
c85e590268b21f50cb7200c3f8596eea2101972569c101d6c9193249c1af3339 | Python | 815 | 26 | import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="DeepRegFinder",
version="0.0.1",
author="Example Author",
author_email="author@example.com",
description="Deep learning based transcriptional regulatory elements finder",
long_descript... |
ee54237ea28ff52ae07efd6d04741ad4a5fdf557d1d2a521b9065481f785aedf | Python | 815 | 25 | import os
import tns
from tns import extract_input
def run():
# Extract distributions from cells in input directory
dir_path = os.path.dirname(os.path.realpath(__file__))
filename = os.path.join(dir_path, '../test_data/bio/')
distr = extract_input.distributions(filename, feature='path_distances')
#... |
a24b094a733c99d49793ed911cbec679217770e511df9697e4c8c15374a57dfc | Python | 816 | 27 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import tensorflow as tf
import pandas as pd
import argparse
import os
import sys
import pwd
import pdb
import csv
import re
import math
df = pd.read_c... |
1e80a0def9e51a370f0f2e2d5d0d3d943ab95b8fbfc1fecf4246a5f917d6e636 | Python | 817 | 27 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._decreasing import Decreasing
from ._hoverlabel import Hoverlabel
from ._increasing import Increasing
from ._legendgrouptitle import Legendgrouptitle
from ._line import Line
from . import decreasing
from . import hoverlabel... |
507ef38fe46523d09194f65cda8ee0163f349ec9c56f645567ebe2782b21d523 | Python | 817 | 30 | from typing import Any
from ._ak_interop import DTYPE_co, RDTYPE_co
from ._core import Ragged, Ragged as _CoreRagged, is_rag_dtype
from ._ops import concatenate, hash, reverse_complement, to_packed, to_padded
from ._utils import OFFSET_TYPE, lengths_to_offsets
def zip(fields: "dict[str, _CoreRagged[Any]]") -> "_Core... |
a5f4c2f4ebd0b54ef6c17f1a3c3ee9cb05ca045d36b62f26935289977b5f365d | Python | 817 | 19 | #!/usr/bin/env python
import argparse
from angorapy.agent.ppo_agent import PPOAgent
from angorapy.analysis import investigators
parser = argparse.ArgumentParser(description="Inspect the dynamics an episode of an agent.")
parser.add_argument("id", type=int, nargs="?", help="id of the agent, defaults to newest", defaul... |
4d03adf3bebc7278f079b6ff73e79141e6de89539c8e9608911023fce06ade08 | Python | 818 | 30 | import sqlite3
from .db import DB
class CaseInformation(DB):
def __init__(self):
super().__init__()
self.table_name = 'MH_case_info'
self.table_desc = 'Maharashtra daily new cases information'
self.cols = self.getcolumns()
def getcolumns(self):
cols = {
... |
6c15d3785f984bebd489d58e97f7a9252b9ca8dac4ebe6c378e2551853918a29 | Python | 818 | 22 | # Copyright (c) 2023 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... |
807f8825d97afaadf140f4d13ea321022ab9c4882f95e8a80adf20c9671d3006 | Python | 818 | 27 | import sqlite3
from .db import DB
class PsychosocialSupport(DB):
def __init__(self):
super().__init__()
self.table_name = 'KL_psychosocial_support'
self.table_desc = 'Psychosocial support provided through the program Ottakalla Oppamundu'
self.cols = self.getcolumns()
def get... |
71338faff6f8b2677bd913792a309ba4b91257a24a3508a646721fae21016400 | Python | 819 | 42 | from neuron import h, gui
def check_basic_pointer(make_instance):
s = h.Section()
s.nseg = 2
s.insert("basic_pointer")
s025 = make_instance(s, 0.25)
s075 = make_instance(s, 0.75)
s025._ref_p1 = s025._ref_x1
s025._ref_p2 = s025._ref_x2
s075._ref_p1 = s(0.25)._ref_v
s075._ref_p2 ... |
a244f438ba43c73ec9c0baa981f5920c8ef1a70e88f513b5a2e89295450d2a4e | Python | 819 | 31 | """
Smoke tests for simulation modules.
Minimal entry point test, NO heavy computation.
Tests that module can be imported and has expected structure.
"""
import importlib
import pytest
@pytest.mark.fast
def test_agent_simulations_entry_point():
"""
Test agent simulation entry point exists.
... |
bef3c9186fddad387da7ac51f0c6784047661c1d4b8ca325ebc1ec5f0158f770 | Python | 819 | 25 | '''
The code here is modified from https://github.com/charlesq34/pointnet under MIT License
'''
if __name__ == '__main__' and __package__ is None:
from os import sys
sys.path.append('../')
import torch.nn as nn
from scene_graph_prediction.pointnet2_dir.pointnet2.models.pointnet2_msg_cls import PointNet2Classi... |
444beb50189b50782a23d4bec30d02f5b854fa7f0fc9a43c4a5af5fcd47169a1 | Python | 820 | 32 | __all__ = []
__metaclass__ = type
try:
# Python >=3.2
from tempfile import TemporaryDirectory
except ImportError:
import shutil
import tempfile
class TemporaryDirectory:
"""
Very simple temporary directory context manager.
Will try to delete afterward, but will also ignor... |
9bc758e960866f8e05ccb5c6abee854cd66628fa0823c9d3233e67515d2a6e87 | Python | 820 | 33 | from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
import lokatt.gpu_beamsearch_opt as basecaller
modules = [
'basecaller',]
__version__ = '0.0.1'
def main():
parser = ArgumentParser(
'lokatt',
formatter_class=ArgumentDefaultsHelpFormatter
)
parser.add_argument(
... |
b6863ac761be1c946458d1c3c97592d00293d0a3685a38ef69feb9644a3c8665 | Python | 820 | 28 | from PIL import Image
from lightly.transforms.fda_transform import (
FDATransform,
FDAView1Transform,
FDAView2Transform,
)
from .. import helpers
def test_view_on_pil_image() -> None:
single_view_transform = FDAView1Transform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = sing... |
5d87c82bbc9261ae9c4ee32a08057a291ce516195e6dbdf89038ed4019f3ca2b | Python | 821 | 42 | #!/usr/bin/env python
import unittest
import os
import numpy as np
from wyrm.types import Data
from wyrm.io import load, save
FILENAME = 'test_load_save.npy'
class TestLoadMushuData(unittest.TestCase):
def setUp(self):
data = np.arange(10).reshape(5, 2)
axes = [np.arange(5), np.array(['ch1'... |
70ce87f08aba8cb006eb6a29eb1b3f1e7b0e13475fe5c9298cf0c94336f815f5 | Python | 822 | 34 | import numpy as np
def time_gate(freq, arr, start, end, n = None,time_info = False):
n_org = arr.shape[-1]
if n is None: n = n_org
arr_t = np.fft.ifft(arr,n=n)
dt = 1/(freq[1]-freq[0])/n/2
t = np.arange(0,dt*n,dt)
idx_start = int(start/dt)
idx_end = int(end/dt)
if idx_end>idx_... |
73c1613029b3a2050cc1e34d2873c92271fb09c6d358a46ae484e31a715355ca | Python | 822 | 24 | import argparse
from irnlm.data.extract_semantic_features import integral2semantic
from irnlm.utils import write
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Extract semantic features (content words) from the integral text."
)
parser.add_argument("--text", type=str)
... |
9ee68636d695537415a84737e173c23c337f4a0504ec8aed7c4a44a36be6eb5e | Python | 822 | 40 | #!/usr/bin/env python
# coding: utf-8
# In[ ]:
import argparse
# In[1]:
import pandas as pd
# In[ ]:
parser = argparse.ArgumentParser()
parser.add_argument('-n', type=int, help='Maximum number of rows to select.')
parser.add_argument('--min-FC', type=float, help='Minimum fold-chage versus control.')
parser.a... |
b0010fec368948a20e1e8459cf76294434c173b1c9f28c51fe83c1f07be68713 | Python | 822 | 21 | from PIL import Image
import numpy as np
def rotate(img,angle):
rotatedArray = np.empty((Image.fromarray(img[:,:,0]).rotate(angle,Image.NEAREST,True).size)+(img.shape[-1],))
for i in range(img.shape[-1]):
rotatedArray[:,:,i] = Image.fromarray(img[:,:,i]).rotate(angle,Image.NEAREST,True)
return rota... |
f25a548e5dde142052011009ad4d9f7608331aa6bab9257bb72b85a1e0d9deb7 | Python | 822 | 45 | """myapp.py
Usage::
(window1)$ python myapp.py worker -l INFO
(window2)$ python
>>> from myapp import add
>>> add.delay(16, 16).get()
32
You can also specify the app to use with the `celery` command,
using the `-A` / `--app` option::
$ celery -A myapp worker -l INFO
With the `-A myproj` argume... |
3b7bb18faf05493f4797c360cda3270d555f683b647c081ab18556678d4ff872 | Python | 823 | 27 | import unittest
import pytest
from PIL import Image
from lightly.utils.dependency import torchvision_transforms_v2_available
if not torchvision_transforms_v2_available():
pytest.skip("torchvision.transforms.v2 not available", allow_module_level=True)
import torch
import torchvision.transforms.v2 as T
from torchv... |
a694f388db537a893790a8c12644f969219abaae30195d2855206fad5a59bd5d | Python | 823 | 29 | 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"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
b6d042f0bfc9d580cb09685320f852171bbc8d6b8e5a5fefba91c515a03f34ff | Python | 823 | 30 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""tests for closeness.py"""
import unittest
from sknetwork.data.test_graphs import *
from sknetwork.ranking.closeness import Closeness
class TestDiffusion(unittest.TestCase):
def test_params(self):
with self.assertRaises(ValueError):
adjacency... |
219fca66c25b0b6f442b91d959bbb218626d0a479ab3332775a42e408d370cd8 | Python | 824 | 29 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._domain import Domain
from ._hoverlabel import Hoverlabel
from ._legendgrouptitle import Legendgrouptitle
from ._link import Link
from ._node import Node
from ._textfont import Textfont
from . import hoverlabel
from . i... |
e1912311ae984537c551dcc9da6f994f9499df0c3499239f1d35bc9fef46fa8f | Python | 824 | 34 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture = dict(
type="PreprocessedSpliceAI",
preprocessor_spec=dict(type="Identity"),
spliceai_spec=dict(type="SpliceAIModule", output_size=3),
)
msp.data_dir = "../data/canonical_and_gtex_dataset/"
... |
e7b5c81514661fa077059098d4a4184429c7c40379c5109d1798b745ff748cfb | Python | 824 | 32 | import streamlit as st
import pandas as pd
import duckdb
def download_files(database):
"""_summary_: Streamlit page to provide download links for the
NOCICEPTRA database and the NOCICEPTRA database schema
Args:
database (DuckDBConnection): _description_
Returns:
None
"""
st.hea... |
2baf221768b88b643a27a3286c31f4a5f24d08b432dff6fe6f00c5275e416167 | Python | 825 | 24 | import SimpleITK as sitk
import sys
# Make transform
elastixImageFilter = sitk.ElastixImageFilter()
elastixImageFilter.SetFixedImage(sitk.ReadImage(str(sys.argv[1])))
elastixImageFilter.SetMovingImage(sitk.ReadImage(str(sys.argv[2])))
elastixImageFilter.SetParameterMap(sitk.ReadParameterFile(str(sys.argv[3])))
elasti... |
df7bea91646a72fae41e654eeeb90d562eb1c8ca967a4eb244cd72617df8122e | Python | 825 | 24 |
"""
Demonstrate how to place text in arbitrary locations on a matplotlib figure.
"""
import numpy as np
import matplotlib.pyplot as plt
if __name__ == "__main__":
fig = plt.figure(figsize=(6, 4))
plt.title("some title")
plt.ylabel("vertical axis")
plt.xlabel("horizontal axis")
plt.grid(alpha=.5, ... |
fc12ae3b39459acf96e64435de801c0ba7f25d37293d6018e7f1616e89549652 | Python | 825 | 37 | import os
import pytest
from mirp.utilities.config_utilities import get_settings_xml, get_data_xml
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
@pytest.mark.ci
def test_copy_settings_xml(tmp_path):
target_file = os.path.join(tmp_path, "settings.xml")
# Start with a clean slate.
if os.path.ex... |
59e18b6a74c7bd498bc5850b2f0ae254c132fbe48cc7de5744ff09ff40543bd9 | Python | 826 | 20 | import os,pickle,torch
from args import *
from model import *
from trainer import Trainer
from dataset import *
from utils import *
import warnings
warnings.filterwarnings("ignore")
args.node_in_dim = 8
args.edge_in_dim = 5
option = args.__dict__
for fold in range(3):
test_dataset = TestDataset(args.m... |
e183fa1c5179bc0f6769772ab05d5e483f9d2a55c060e12fec93496b818fdae0 | Python | 826 | 32 | from __future__ import annotations
from typing import TypeVar
import numpy as np
from numpy.typing import NDArray
DTYPE = TypeVar("DTYPE", bound=np.integer)
LENGTH_TYPE = np.uint32
OFFSET_TYPE = np.int64
def lengths_to_offsets(
lengths: NDArray[np.integer],
dtype: type[DTYPE] | DTYPE = OFFSET_TYPE, # pyre... |
091d62b7266ea59285c9d3830b11fbbe18d564183a839f61be25c87a137cba3c | Python | 827 | 21 | from drug_interactions.datasets.dataset_builder import DatasetTypes
from drug_interactions.features.Char2VecFeature import Char2VecFeature
from drug_interactions.features.EmbeddingFeature import EmbeddingFeature
from drug_interactions.features.CNNFeature import CNNFeature
from drug_interactions.features.OneHotFeature i... |
074c5cdc6cfd9e28eb8d85d4c3c8b4476f35d3bd48b9cc6d2b6764fb76122069 | Python | 828 | 28 | from PIL import Image
from lightly.transforms.byol_transform import (
BYOLTransform,
BYOLView1Transform,
BYOLView2Transform,
)
from .. import helpers
def test_view_on_pil_image() -> None:
single_view_transform = BYOLView1Transform(input_size=32)
sample = Image.new("RGB", (100, 100))
output =... |
198c72befeb8c58cb2d505410bb81b42c304adc96c5ef9c27b521325d742b584 | Python | 828 | 23 | """Tests for TensorFlow private compatibility probes."""
from __future__ import annotations
import pytest
from torchlens.backends.registry import BackendUnsupportedError
from torchlens.backends.tf import _tf_compat as tfc
@pytest.mark.smoke
def test_op_callbacks_absence_marks_capability(monkeypatch: pytest.MonkeyP... |
6c812b306f656c5c0850d4b64fff58cc32ebd7977fcd89df93f3541c2b9c0e62 | Python | 828 | 33 | # Generated by Django 3.0.4 on 2020-03-25 09:09
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('biomedisa_app', '0068_auto_20200324_1641'),
]
operations = [
migrations.RemoveField(
model_name='mushroomspot',
name='pictur... |
aa21e8202b60e08c1577607f08208513048313aa2332097911f378510c754939 | Python | 828 | 32 | import re
import pytest
import gym
from gym.wrappers import HumanRendering
def test_human_rendering():
for mode in ["rgb_array", "rgb_array_list"]:
env = HumanRendering(
gym.make("CartPole-v1", render_mode=mode, disable_env_checker=True)
)
assert env.render_mode == "human"
... |
61b946c28699620403069c11e36fe25fbedba392cb14bd8286a4a3103793a885 | Python | 829 | 26 | """
This module define a LMCrossEntropy
"""
# pylint: disable=W0223
import torch
from utils.utils import select_output_lm
class LMCrossEntropy(torch.nn.modules.loss._Loss): # pylint: disable=protected-access
"""
This class define a specific loss for language model, that do the cross
entropy loss only... |
7632b0eb46c978286bf72c869676f5903ce19bc774457c0b1b8c29b337dd6f83 | Python | 829 | 33 | import pickle
from datetime import datetime, timezone
from celery.exceptions import Reject, Retry
class test_Retry:
def test_when_datetime(self):
x = Retry('foo', KeyError(), when=datetime.now(timezone.utc))
assert x.humanize()
def test_pickleable(self):
x = Retry('foo', KeyError(),... |
79b689993c2c7652cc8d0f6934bd6da144d5df84e9e51aaf637a9844dd2f85c0 | Python | 830 | 20 | # Copyright (c) 2022 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... |
c808826021d391ad044110d1eac8e197b1b918b90c84272e7eea68fa5a958b2f | Python | 830 | 33 | """
Demonstrate how to overlay voltage and dV/dt plots
"""
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0, PATH_SRC)
import pyabf
import matplotlib.pyplot ... |
dcaa5a2131931b21982a80f23893a10900fb2b0e908acd1bdf3c7635dac7286d | Python | 830 | 27 | """
Practice printing epoch info
"""
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0, PATH_SRC)
import pyabf
import glob
import numpy as np
if __name__=="__m... |
11da17e3e5d3b34f463b134c4890e2ff8a496a82afb369689485ba1871e4f687 | Python | 831 | 40 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 20
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="PSAMMotifModel",
motif_spec=dict(type="rbns"),
... |
4c013a0fdb023a2362b592526b9b6c4c6b1474111b420eac2ae048e7d5301ffd | Python | 831 | 42 | import pickle
# [f1_begin, f1_end, f2_begin, f2_end]
AB_list = [
[1, 0, 0, 1], # Run from A to B
[1, 0, 1, 1], # Run from A+B to B
[1, 1, 0, 1], # Run from A to A+B
]
BA_list = [
[0, 1, 1, 0], # Run from B to A
[0, 1, 1, 1], # Run from B to A+B
[1, 1, 1, 0], # Run... |
79d19a4048d365247bc2b4cbb359fa789e8e58df13f6cdbbbd3d263ffd5520ff | Python | 831 | 23 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture["num_motifs"] = 66
msp.architecture["sparse_spec"] = dict(type="SpatiallySparseAcrossChannels")
msp.architecture["motif_model_spec"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
ad7e630b4088c24b0a72962d0f77c0695cddb4e19c38ad2ac782b5202a6ea621 | Python | 831 | 26 | import argparse
import json
def read_tsv(filename, max_num_lines):
train_json_filename = filename.replace(".tsv", ".jsonl")
with open(filename, 'r') as f_in, open(train_json_filename, 'w+') as f_out:
f_in.readline()
for idx, line in enumerate(f_in.readlines()):
if idx < max_num_li... |
eba6565bd1331cf425c21fb24efdb5066ccb6c89fea8685dfc2199563c697e47 | Python | 831 | 32 | """Screenshots for quick guide extensions"""
import pathlib
import sys
from PyQt5 import QtCore
from PyQt5.QtWidgets import QApplication
from pyjibe.head.main import PyJibe
from pyjibe.head import preferences
data_path = pathlib.Path(__file__).resolve().parent / ".." / "data"
app = QApplication(sys.argv)
QtCore.QLo... |
d8cebbdab91798c550d0e0efb101534f24e5434609a3e4e631a91a0697853284 | Python | 832 | 28 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2018 Braintech Sp. z o.o. [Ltd.] <http://www.braintech.pl>
# All rights reserved.
"""
Module defines single :class: 'DataAsciiWriteProxy'.
Author:
Mateusz Kruszyński <mateusz.kruszynski@gmail.com>
"""
from .data_generic_write_proxy import DataGenericWriteProxy, SampleP... |
5f903b081649c01815cd8ed04380c97e65e263b8e087aea7ee6cc1113731828f | Python | 833 | 28 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import numpy as np
import tensorflow as tf
import pandas as pd
import argparse
import os
import sys
import pwd
import pdb
import csv
import re
import math
df = pd.read_c... |
5fadd29e2b05cb62c9f0a1f16f3a383004f4a5e31ddef9ddd70df4fa2fd4a093 | Python | 833 | 31 | """API router for handling telemetry data in the CarbonServer API."""
from uuid import UUID
from dependency_injector.wiring import Provide, inject
from fastapi import APIRouter, Depends
from starlette import status
from carbonserver.api.schemas_telemetry import TelemetryCreate
from carbonserver.api.services.telemetr... |
7ebc87328d031d005283970f4e5dab132799054fd8e07b14474861e709a9205e | Python | 833 | 18 | """
This module is the core of the `ethoscope`.
It defines the building bricks at the basis of the package.
Overview:
* :class:`~ethoscope.core.monitor.Monitor` is the most important class. It glues together all the other elements of the package in order to perform (video tracking, interacting , data writing and draw... |
99abeaec5549e9dba5be4dd958c372ea456a026c20434c310d74ce417e2ed586 | Python | 833 | 26 | import glob
from PIL import Image
import lightly
# let's get all jpg filenames from a folder
glob_to_data = "/datasets/clothing-dataset/images/*.jpg"
fnames = glob.glob(glob_to_data)
# load the first two images using pillow
input_images = [Image.open(fname) for fname in fnames[:2]]
# create our transform
transform... |
16931a2884842b3f15d8480a3e42a847a5b86e7b7f45aefa86505dfb55398000 | Python | 834 | 32 | # %%
import argparse
import gzip
# %%
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--positive')
parser.add_argument('--negative')
parser.add_argument('-o', '--output')
args = parser.parse_args()
with open(args.output, 'w') as f_out:
print('sequence\tlabel', file=... |
3dc05b7f5ad9ddb26dd200b71594fbf4cfe6729c3c763b22657a74d4528dac30 | Python | 834 | 30 | from __future__ import annotations
from larvaworld.gui_v2.apps.models_environments.env_builder_widget import (
EnvBuilderWidget,
build_environment_builder_widget,
)
def build_environment_builder_text(entry) -> tuple[str, str, list[tuple[str, str]]]:
return (
"Environment Builder",
"PySide... |
9a91779d4105f35cee67393b8a6886b380ab2afecdbb9574a95007f13d4281ba | Python | 834 | 30 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._delta import Delta
from ._domain import Domain
from ._gauge import Gauge
from ._legendgrouptitle import Legendgrouptitle
from ._number import Number
from ._title import Title
from . import delta
from . import gauge
... |
dcd3a651164fb79782affa9781421bf6a8ac82fa4402b2df7ffc705524ff5144 | Python | 834 | 29 | # %%
import argparse
# %%
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('bed', metavar='<file.bed>')
args = parser.parse_args()
with open(args.bed) as f:
_ = f.readline()
for line in f:
row = line.strip().split('\t')
chrom, st... |
2b9d707080456fb0a5d6afb60bfd9eab085621e324238b0696bd12f0ab2d8317 | Python | 835 | 30 | 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"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
3f2fbf5cd45d0e8b371c121041cf114e5c71fb27f66b099a23fbf01f95a6e0fd | Python | 835 | 30 | 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"] = dict(
type="AdjustedMotifModel",
model_to_adjust_spec=dict(
... |
ced6c79a8df8dd515d902dd5efbd6b0849fdb66d2fd2b2b6ecbc98f5b7b5f223 | Python | 835 | 44 | '''Utilities for Pandas dataframe
This file is a part of BdPy
'''
__all__ = ['convert_dataframe', 'append_dataframe']
import pandas as pd
def convert_dataframe(lst):
'''Convert `lst` to Pandas dataframe
Parameters
----------
lst : list of dicts
Returns
-------
Pandas dataframe
'... |
ec1ca3961bf021b6cef534bbd4ee8af25f07d06b942bc3dd60e22d3d553683ab | Python | 836 | 28 | """Tests for specparam.utils.convert."""
import numpy as np
from specparam.utils.convert import *
###################################################################################################
###################################################################################################
def test_dict_arra... |
19d6727659553ad2769450abfd49b13e9ba0faa5993b3c28788836b8f89a1066 | Python | 837 | 27 | import torch
from lightly.transforms import IRFFT2DTransform, PhaseShiftTransform, RFFT2DTransform
# Testing function image -> RFFT -> PhaseShift.
# Compare shapes of source and result.
def test() -> None:
image = torch.randn(3, 64, 64)
rfftTransform = RFFT2DTransform()
rfft = rfftTransform(i... |
32f4d7fb9432ba5c3f31a586db4665204017b15b45aed0e1f82b8cdfb9400a17 | Python | 837 | 24 | from nitorch import io
from nitorch.spatial import euclidean_distance_transform as edt
import torch
root = '.'
root += '/lsfm/layers'
for i in (8, 9, 10, 11, 12, 17, 19):
fname = f'{root}/extracted_9.9um/layers.{i:02d}.nii.gz'
f = io.map(fname)
d = f.data(device='cuda')
planemask = d.reshape([-1, d.sh... |
86cb98d9d96991c999973d9dc880e35947ba8cce5cf1f9cdfcceb8ce45bbe4c8 | Python | 837 | 31 | """
Comparing version numbers
"""
# import the pyabf module from this development folder
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_SRC = os.path.abspath(PATH_HERE+"/../src/")
PATH_DATA = os.path.abspath(PATH_HERE+"/../data/abfs/")
sys.path.insert(0, PATH_SRC) # for importing
sys... |
ecc3d7bf15ca86e77797b10699a664f9df001bb86a3a227ad1f7c64b82799ae3 | Python | 837 | 31 | from typing import Literal
import numpy as np
from hobj.learning_models import BinaryLearningModel
from hobj.types import ImageId
from typing import cast
class RandomGuesser(BinaryLearningModel):
"""
A dummy model which simply returns random outputs, independent of the given image.
"""
def __init__... |
248c96e48a650ce8f412548587213e2a8e46c07352bb09755bb518cf45a7fff2 | Python | 838 | 31 | from setuptools import setup, find_packages
setup(
name = 'chroma-pytorch',
packages = find_packages(exclude=[]),
version = '0.0.1',
license='MIT',
description = 'Chroma - Pytorch',
author = 'Phil Wang',
author_email = 'lucidrains@gmail.com',
long_description_content_type = 'text/markdown',
url = 'ht... |
4aa52957f11f9a937fd30fcd0ddac7ff5cb8b0a11386b7d578f10ef299a09c16 | Python | 838 | 22 | from pyabf.abf2.section import Section
class EpochSection(Section):
"""
This section contains the digital output signals for each epoch. This
section has been overlooked by some previous open-source ABF-reading
projects. Note that the digital output is a single byte, but represents
8 bits correspo... |
7bdedbc62f597ea642e092df9599d37bac6f80880ae2410bbc7da2096d7487e1 | Python | 838 | 39 | from os.path import basename
import sys
import collections
def cal_RT(mutation_file):
d = collections.defaultdict(lambda :0)
#x = []
with open(mutation_file) as RT:
for line in RT:
line = line.strip('\n').split('\t')
if len(line) == 1:
continue
else:
chrID = line[0]
position = line[2]
re... |
b7dee92833314fd442fbf62c818f9cf2d431ade932004ea2dbf82ebf10181e14 | Python | 838 | 28 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Tests for cliques"""
import unittest
from scipy.special import comb
from sknetwork.data.test_graphs import *
from sknetwork.topology.cliques import count_cliques
class TestClique(unittest.TestCase):
def test_empty(self):
adjacency = test_graph_empty()
... |
c804573d45cdd6128123959e174850e333ccd26fcc43c7f1039f4b54667a8868 | Python | 838 | 32 | import importlib
import sys
import pytest
@pytest.mark.parametrize(
"import_statement",
[
"import lightly.api",
"from lightly import api",
"from lightly.api import ApiWorkflowClient",
],
)
def test_lightly_api_imports_raise_deprecation_error(import_statement: str) -> None:
sys... |
f9c422f73fcd3132a39ea91845331adcc89895918321fedf7e174477bcafa5c9 | Python | 838 | 34 | """Spatiotemporal modeling of spatial transcriptomics
"""
from . import (
align,
benchmark,
bp,
density,
em,
external,
icell,
label,
moran,
simulation,
simulation_evaluation,
utils,
vi,
)
from .align import refine_alignment
from .benchmark import compare
from .density... |
22092d7a0f277bbbb937db0d5e5c2e7012b7831dc2e0da81b86b687083593caf | Python | 839 | 31 | from sys import argv
from msp import MSP
from msp_fly import fly_am
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fly_am(msp)
msp.architecture["propagate_sparsity_spec"] = dict(
type="OnlyAllowInfluenceOnSplicesites"
)
msp.architecture["final_processor_spec"].update(
dict(
bottleneck_spec=... |
438600f1e50556e9ec77d6b00f78161607895ea8b060d9910c3eb879ede50ba9 | Python | 839 | 31 | from sys import argv
from msp import MSP
from msp_fly import fly_am
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fly_am(msp)
msp.architecture["propagate_sparsity_spec"] = dict(
type="OnlyAllowInfluenceOnSplicesites"
)
msp.architecture["final_processor_spec"].update(
dict(
bottleneck_spec=... |
46874eef4b8dbf0e045b82a6e2a2c80151766a2b5fe16c373d377ced8341208d | Python | 839 | 31 | from sys import argv
from msp import MSP
from msp_fly import fly_am
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
fly_am(msp)
msp.architecture["propagate_sparsity_spec"] = dict(
type="OnlyAllowInfluenceOnSplicesites"
)
msp.architecture["final_processor_spec"].update(
dict(
bottleneck_spec=... |
4c50fa912ac743a211070a381debc6b24a3d1dd6b7a89413890b5f2dcca40dee | Python | 839 | 35 | # %%
# import all_raw_aligned
import pandas as pd
from globals import path
all_raw_aligned = pd.read_csv(f"{path}/all_raw_aligned.csv")
# %%
# plot scatter plot with dummy data and star like shape
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.lines as mlines
from plotting import prettifySpinesTi... |
63e9897ca10b166ce7fcf4d6c05a11b0a488e75f4f7092bd90e0addcecc0b91c | Python | 839 | 24 | import argparse
from os import path
parser = argparse.ArgumentParser()
parser.add_argument("--bg", action = "store",
help = "string to write for bg in ldcts")
parser.add_argument("--bg_dir", action = "store",
help = "directory where bg ldscore files are located")
parser.add_argument("--celltypes", action = "store", ... |
891c2b2f52ce6ad55863082e425b9a4a7364c1da7a9426686201f84a13f060ae | Python | 839 | 15 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from eelbrain.pipeline import PrimaryEpoch, SecondaryEpoch, SuperEpoch, EpochCollection, ContinuousEpoch
def test_epoch_repr():
primary_epoch = PrimaryEpoch('session')
assert repr(primary_epoch) == "PrimaryEpoch('session', samplingrate=200, baseline=(No... |
13bd5587a8db3a18f631371c7800d3f290a5e8f6971cd1d5cd747e2130553721 | Python | 840 | 45 | import eugene as eu
# Configure EUGENe for a test spin
eu.settings.dataset_dir = "eugene_data"
eu.settings.output_dir = "eugene_ouput"
eu.settings.logging_dir = "eugene_logs"
eu.settings.config_dir = "eugene_configs"
# Extract the data
sdata = eu.datasets.random1000()
# Preprocess sequences for training
eu.pp.prepar... |
63b3d79a7a6fab8a2538e54488fda48445cfc9292340d5da23981fd7ecaadcf0 | Python | 840 | 32 | """Screenshots for quick guide extensions"""
import pathlib
import sys
from PyQt6 import QtCore
from PyQt6.QtWidgets import QApplication
from pyjibe.head.main import PyJibe
from pyjibe.head import preferences
data_path = pathlib.Path(__file__).resolve().parent / ".." / "data"
app = QApplication(sys.argv)
QtCore.QLo... |
8958741b6eb1177ce3f232b6b871f14a1f6899b63e895d3789baa36a135ced22 | Python | 840 | 29 | # fix problems with pythons terrible import system
import os
import sys
file_dir = os.path.dirname(os.path.realpath(__file__))
#sys.path.append(os.path.join(file_dir, '../bin/'))
sys.path.append(os.path.join(file_dir, '..'))
# import extract_genes module
import prob2020.console.extract_gene_seq as eg
import prob2020.p... |
3f8c0afa146e0f6797059ed9bef82f0a413ef79c55f3b8fc3e6dd3b0bdfbc243 | Python | 841 | 34 | #!/usr/bin/env python
import fileinput
from pprint import pprint
def author(line):
try:
A, E = line.strip().rsplit(None, 1)
E.replace('>', '').replace('<', '')
except ValueError:
A, E = line.strip(), None
return A.lower() if A else A, E.lower() if E else E
def proper_name(name):... |
5c051de44c417b4494d03e54827634a91e2197901b56957cf1d4091b2b8f9948 | Python | 841 | 28 | import sys
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from ._autorangeoptions import Autorangeoptions
from ._minor import Minor
from ._rangebreak import Rangebreak
from ._tickfont import Tickfont
from ._tickformatstop import Tickformatstop
from ._title import Title
from ._unifiedhov... |
f3e42f22b6d7a75dbc95600c8009154e1b2821a3fa4d5652e85285d1a3b42267 | Python | 842 | 26 |
import time
from ethoscope.hardware.interfaces.interfaces import BaseInterface
from ethoscope.stimulators.sleep_depriver_stimulators import SleepDepStimulator
from ethoscope.tests.integration_api_tests.old.utils import test_stimulator
class MockSDInterface(BaseInterface):
def send(self,channel, dt=350,margin=1... |
387c0a158c6bdb7872dc95f4ec73fa8965799d0033e04e7924455a9320fdfe0b | Python | 843 | 25 | #!/usr/bin/env python
import os, re, sys, subprocess
trinity_package_dir = os.path.abspath(sys.argv[0] + "/../../../")
print("Trinity package dir: {}".format(trinity_package_dir))
trinity_package_name = os.path.basename(trinity_package_dir)
print("Trinity package name: {}".format(trinity_package_name))
destination_... |
37da6a039ffb93797a916b0acd1da19016e032c8dbd1f0cf5ec489e08d53c945 | Python | 844 | 24 | # 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... |
448ff6bdfac039a10eb1e6ec4c4ac9a2688b475ac3a9367a1fb35b001a6b240e | Python | 844 | 29 | """
Refactor the AP detection module to provide a clean interface.
You can always refactor the core later.
"""
import os
import sys
PATH_HERE = os.path.abspath(os.path.dirname(__file__))
PATH_DATA = os.path.abspath(PATH_HERE+"../../../data/abfs/")
PATH_SRC = os.path.abspath(PATH_HERE+"../../../src/")
sys.path.insert(0... |
480a893b3767cb6b235e53dc7afc8ecb9e3551f1b658c5cb6090be6a73dd9c7b | Python | 844 | 25 | """Tests for specparam.modes.definitions."""
from specparam.modes.mode import Mode, VALID_COMPONENTS
from specparam.modes.definitions import *
###################################################################################################
##########################################################################... |
ddec2caec7369db9c0257a42d242c846bd70d01cb092b1134a76747a6d06cd62 | Python | 844 | 44 | from neuron import h, gui
def make_accessors(mech_name, read_only):
get = getattr(h, f"get_gbl_{mech_name}")
if read_only:
return get, None
set = getattr(h, f"set_gbl_{mech_name}")
return get, set
def check_write_read_cycle(mech_name, read_only=False):
get, set = make_accessors(mech_na... |
fb0eebb1dee704826bf492114d359f12173da34747323cbfde3d33144224666f | Python | 844 | 45 | # -*- coding: utf-8 -*-
"""
Created on Wed Jan 14 13:04:36 2015
@author: rh04
arg1 = path
e.g. Z:\DWI\Subject1\Rep1\
arg2 = name of DWI volume
e.g. DWI_brain
"""
import nibabel as nib
from gibbs_removal import volume_gibbs_removal
from sys import argv
script, arg1, arg2 = argv
# load data
print 'loading ...'
pri... |
1bf7d2e3c25cec845c577081a629e9c57453071be923d17b65d072e263e93e4b | Python | 845 | 36 | from sys import argv
from msp import MSP
msp = MSP()
msp.file = __file__
msp.seed = int(argv[1])
msp.architecture = dict(
type="PreprocessedSpliceAI",
preprocessor_spec=dict(type="Identity"),
spliceai_spec=dict(type="SpliceAIModule", output_size=3),
)
msp.data_dir = "../data/canonical_and_gtex_dataset/"
... |
549b96c4b645297417ce505cceec68f78c1759250b9d7c1b3bfe6e97f870b1ed | Python | 845 | 28 | """Utilities used by the message signing serializer."""
import sys
from contextlib import contextmanager
import cryptography.exceptions
from cryptography.hazmat.primitives import hashes
from celery.exceptions import SecurityError, reraise
__all__ = ('get_digest_algorithm', 'reraise_errors',)
def get_digest_algorit... |
a672b6af121ffb4710ec0f02348fdab5b5b8f427807c79e38f231f91c7062262 | Python | 845 | 27 | #!/usr/bin/env python
"""
Extract importent information from the standard output file and put it in some standard format, like BED and tabular.
"""
import sys
bed = open(sys.argv[2], "w+")
tabular = open(sys.argv[3], "w+")
for line in open(sys.argv[1]):
# Sequence 'CRISPRs' (10798 bp)
if line.startswith... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.