sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
8696590b73fd97e6b56d4bb431df277c8002028a06de38431d923f4af4cddfef | Python | 2,775 | 56 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import shap
import pickle
import seaborn as sns
import argparse
def get_feature_importance():
parser = argparse.ArgumentParser(description='Caculate the importance for each feature and pathway.')
parser.add_argument('--input_shap'... |
f14dc90de340187a5f3adaccc60f3b5f065ce3f7729eed7e6ceb7055dfb6c9c4 | Python | 2,775 | 75 | '''
Created on 19 Nov 2022
@author: Francois STÜDER
Only feature count was tested in this script
'''
import pandas as pd
import sys
from os import path
from subprocess import Popen, PIPE
from SysISTD import tools
cmdQuantification = "featureCounts -T __core__ -F GTF -t __feature__ -s 0 -a __GTF__ -o __out__"
tsvF... |
6517af99ada509607377dcc4431784acd2e95cb53c8a6352a6838ed175d9c5b5 | Python | 2,776 | 96 | import os, math, random
import numpy as np
from matplotlib.patches import Ellipse
from sklearn.datasets import make_blobs
import matplotlib.pyplot as plt
def calc_p (x):
return 2 * np.min([
np.mean(np.array(x) >= 0),
np.mean(np.array(x) <= 0)
])
def calc_diff_p(a, b):
random.seed(0)
r... |
888045b4c75431da2a6b549a7bac77d048d22614e4175dfd7bfe9d771b0f42a3 | Python | 2,776 | 75 | from medperf import config
from medperf.entities.cube import Cube
from medperf.entities.model import Model
from medperf.entities.dataset import Dataset
from medperf.entities.execution import Execution
from medperf.entities.benchmark import Benchmark
from medperf.enums import ModelType
from medperf.commands.execution.co... |
d5108b7dbfa72b51e6ce9517ef00712f4649a50686853d1f2f0d32044b47bc0e | Python | 2,776 | 76 | import numpy as np
import hickle as hkl
from grid_cell.ploter import error_bar_plot
import scipy.ndimage as ndi
from grid_cell.tuning import ppdata_to_avg_ratemap
from scipy import stats
import matplotlib.pyplot as plt
import os
from global_setting import *
#################### Hyperparameters ####################
mou... |
550586c1621031667ae9513b14b6494b0282a9bdb0bd7771c2f07c55b62119b5 | Python | 2,778 | 116 | # pylint: disable=protected-access
"""Shared typing definition."""
import ctypes
import os
from typing import (
TYPE_CHECKING,
Any,
AnyStr,
Callable,
Dict,
List,
Optional,
Sequence,
Tuple,
Type,
TypeVar,
Union,
)
# os.PathLike/string/numpy.array/scipy.sparse/pd.DataFrame... |
d02923a50c9671b0c4650048f625fdc4e150eb8b831c769afed2ccbb0c3067f2 | Python | 2,779 | 74 | import pandas as pd
peps = pd.read_csv("peptides.tsv", "\t")
peps.fillna("", inplace=True)
print(len(peps), "Total peptides")
hpeps = peps[peps["Species"].str.contains("Human")]
print(len(hpeps), "Human peptides")
# if the peptide has a smiles, we should be ok
smipeps = hpeps[hpeps["SMILES"] != ""]
print(len(smipeps)... |
ec899276960af879a3822e62cc018b17ff7d7fae03b3bedd790d2902bb82592f | Python | 2,779 | 83 | from collections import OrderedDict
import torch
from torch import nn
class VoxNet(nn.Module):
"""
Original code is from:
https://github.com/MonteYang/VoxNet.pytorch/blob/master/voxnet.py
Notes
-----
Compared with the original model, ReLU is chnaged to PReLU(1, 0.25)
The higgen layer in... |
fc6e56aa8ecd1f956bd0abd707cb6c4c433850796db75dfec537027b5bcc67da | Python | 2,780 | 113 |
#from bluepyopt.ephys.models import CellModel
import bglibpy
from bglibpy.importer import neuron
import collections
import logging
logger = logging.getLogger(__name__)
class HocModel(object):
"""Neurodamus model class"""
def __init__(
self,
morphname=None,
template=Non... |
1e2187bcc56045d5af956f9762b5290cbd7afe88dd0b31b86150b047b857aef6 | Python | 2,781 | 88 | """pytorchexample: A Flower / PyTorch app."""
import torch
from flwr.app import ArrayRecord, Context, Message, MetricRecord, RecordDict
from flwr.clientapp import ClientApp
from task import test as test_fn
from task import train as train_fn
from models import SimpleCNN as Net
from data_loader import ChestXrayDataset
... |
0a12984743aafe0c0c19c7407e955eae10bf324e53207ed395e0966ec749360e | Python | 2,782 | 115 | '''Sink for Parquet format.'''
from pathlib import Path
from typing import Any
import pandas as pd
from pyarrow import Table
from pyarrow.parquet import write_table
from kgx.sink.sink import Sink
DEFAULT_NODE_COLUMNS = {
"id",
"name",
"category",
"description",
"provided_by"
}
DEFAULT_EDGE_COLU... |
1ff419312cd2793a006d409ba5de5c920aac587c9810cae2bb6ba62d3d99090c | Python | 2,782 | 88 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def default_conv(in_channels, out_channels, kernel_size, bias=True):
return nn.Conv2d(
in_channels, out_channels, kernel_size,
padding=(kernel_size//2), bias=bias)
class MeanShift(nn.Conv2d):
def __init__(
... |
54cb91a8129ff875f3b637e2a2d7b9e3f837a512b11fda2fcc6379e4ad035136 | Python | 2,783 | 76 | ## simulator for BRIE2
import numpy as np
from scipy.special import expit
from tensorflow_probability import distributions as tfd
def simulator(adata, Psi=None, effLen=None, mode="posterior",
layer_keys=['isoform1', 'isoform2', 'ambiguous'],
prior_sigma=None):
"""Simulate read counts f... |
8290414ea1f57bdab7fed90daf5ed2cad4093ec5fbd1acfa0e8387ad01ca116e | Python | 2,783 | 88 | #!/usr/bin/python
import sys
import argparse
import requests
from requests.auth import HTTPBasicAuth
class CatmaidApiTokenAuth(HTTPBasicAuth):
"""Attaches HTTP X-Authorization Token headers to the given Request.
Optionally, Basic HTTP Authentication can be used in parallel.
"""
def __init__(self, tok... |
f97e1be39b49b7b7e8ae804132ca4cb3c632a45745507d95250942efb17a0ed1 | Python | 2,784 | 88 | import numpy as np
from sklearn.manifold import TSNE, Isomap, MDS
from experiment import *
from matplotlib import pyplot as plt
from ethomap import pdist_dtw, IsomapPrecomputed, affinity_propagation
from scipy.spatial.distance import squareform
from scipy.interpolate import CubicSpline
from zigzeg import find_runs
f... |
60d24cf6458f5890b235f1546fc86b80a31d8f126dd1a17d9e695e6404d25f35 | Python | 2,789 | 70 | from _operator import itemgetter
from collections import namedtuple
GMMparameter = namedtuple('GMMparameter', 'mergedName numberOfComponents searchStrings')
def kvlReadSharedGMMParameters(fileName):
# Read text file where each line is formatted as:
# mergedName numberOfComponents searchString(s)
share... |
0a28d6b1849b3343a81a473b4019d08d2316898d7dd5074b502a1163ac75f80e | Python | 2,790 | 94 | from __future__ import annotations
import os
import pytest
import medperf.config as config
from medperf.tests.mocks.cube import TestCube
from medperf.commands.mlcube.submit import SubmitCube
from medperf.exceptions import InvalidArgumentError
PATCH_MLCUBE = "medperf.commands.mlcube.submit.{}"
# rename ficture to su... |
2abccfbc3b4cd95bdaee3f09ae45c102e91e8647b3ed80ddaf3cca208a0b4967 | Python | 2,790 | 91 | import pickle
import numpy as np
from tqdm import tqdm
import multiprocessing
def cosine_similarity(u, v):
return np.dot(u, v) / (np.linalg.norm(u) * np.linalg.norm(v))
def find_most_similar_embedding(target_emb, umls_ent_emb):
max_similarity = -1
max_index = None
for idx, umls_emb in enumerate(umls_e... |
d8364de1f90b2391c11c8e623a653103067c6a7184c57a2e5fbc6e805927d0a7 | Python | 2,790 | 109 | """Test that files marked as 'streamable' when 'streaming_allowed' can be named pipes."""
import os
from pathlib import Path
from typing import cast
import pytest
from cwl_utils.types import CWLObjectType
from ruamel.yaml.comments import CommentedMap
from schema_salad.sourceline import cmap
from cwltool.command_line... |
70ecaae5d356af8dba45731a48764e7d27a02f3892ab1fc847ce4e4f76a10aa9 | Python | 2,795 | 92 | from __future__ import annotations
from typing import Annotated
import typer
from zndraw.schemas import ActiveCameraResponse, SessionsListResponse
from .connection import (
PasswordOpt,
RoomOpt,
TokenOpt,
UrlOpt,
UserOpt,
cli_error_handler,
get_zndraw,
resolve_room,
)
from .output im... |
0b59b6858657e0b4760e5bed17ac138cf20c4646be8e2cf5805e41274c2eae1b | Python | 2,796 | 98 | from collections.abc import MutableSequence
import pytest
from cwl_utils.types import CWLDirectoryType, CWLFileType, CWLObjectType
from cwltool.pathmapper import PathMapper
from cwltool.utils import normalizeFilesDirs
def test_subclass() -> None:
class SubPathMapper(PathMapper):
def __init__(
... |
3ee987dfc33dfd7a19fc32f9bd4cd5e044927545c56dc6aa19698d00cb7ea467 | Python | 2,797 | 71 | from datetime import datetime
from dfa_lib_python.performance import Performance
from dfa_lib_python.method_type import MethodType
def test_get_start_time_pass():
start_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
end_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
performance = Performance(sta... |
a49d12a0a2a15a86214c09bd2bd18712e1e670c38ec17ff179595934df99bfb3 | Python | 2,798 | 65 | # coding=utf8
import argparse
import sys
import os
from concurrent.futures import ProcessPoolExecutor
def _generate_cache_arrow(index, ds, path):
print('saving dataset shard {}'.format(index))
ds.save_to_disk(os.path.join(path, 'part_{}'.format(index)))
return 'saving dataset shard {} done'.format(index)
... |
97603165140494c0b902a31435b5176f0ce33a604d19b020bf162a9268496676 | Python | 2,799 | 64 | #intended to be functions that are used in the other src fils (computation.py, plotting.py) but avoids putting them in config.py
#each other module should import helper_functions as hf
import numpy as np
import lmfit
from copy import deepcopy
from src import config as cfg
from src import data_io as io
def get_num_ti... |
a1caf8389358385bdb5845c6f18a54ceb4c1be0b38515b2110598224eec1b319 | Python | 2,800 | 70 | """Tests for the HMDB download.
HMDB fronts its download URL with a Cloudflare bot challenge, so the unattended download cannot
succeed and the operator has to place the zip by hand. These tests cover the two halves of that:
that Babel still recognizes the live response as a challenge, and that a hand-placed zip is
ac... |
ed8bd61f7ec4a041af082e5c80f7028f98153fe73add70eef1189bbda673e677 | Python | 2,802 | 65 | from transformers import LlamaTokenizer
import torch
def pad(ids, pad_id, max_length):
if len(ids) > max_length:
return ids[:max_length]
return ids + [pad_id] * (max_length - len(ids))
prompt_without_output = "<human>:{prompt}\n<bot>:"
def generate_samples(s, tokenizer, max_seq_length):
max_leng... |
fd785db122f5b3b9e2e764fecb9e0fc7ca53203ff1b3ed47c615f4cc553e26bf | Python | 2,802 | 95 | from contextlib import contextmanager
from functools import wraps
from typing import Callable, Tuple
try:
import torch._dynamo as dynamo
except ImportError:
dynamo = None
from e3nn import get_optimization_defaults, set_optimization_defaults
from torch import autograd, nn
from torch.fx import symbolic_trace
Mo... |
2c65dd5a575bd51a559825e546138943c4727dd6046e3515b9930014040d0ba0 | Python | 2,803 | 86 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
import torch.nn as nn
# Different encodings for the atom distance embeddings
class GaussianSmearing(torch.nn.Module):
def ... |
e080b0bbca7d61193af2c74cdaca84e95087b801c304c5826b66068c4cf8a4d6 | Python | 2,804 | 101 | from luna.paths import LunaPaths
from luna import candidate_info, dataset
from luna.ct import Ct
from luna.prepcache import LunaPrepCacheApp
from torch.utils.data import DataLoader
#from Utils.dataloader import *
from Utils.models import *
from Utils.TrainModelLUNA import *
from Utils.config import *
from multiprocessi... |
fe07560035a8808398bf6c29f609e92997a1a204f64631f3634b3aa2966b14ac | Python | 2,804 | 101 | from luna.paths import LunaPaths
from luna import candidate_info, dataset
from luna.ct import Ct
from luna.prepcache import LunaPrepCacheApp
from torch.utils.data import DataLoader
#from Utils.dataloader import *
from Utils.models import *
from Utils.TrainModelLUNA import *
from Utils.config import *
from multiprocessi... |
0522efd8e8a27bb225644246004c69dbcc28089c3abbd89712f0663f4563020d | Python | 2,805 | 63 | from pyxtal import pyxtal
from p_tqdm import p_map
from pymatgen.core import Structure
from pymatgen.core.lattice import Lattice
def structure_to_str(structure):
# 转换pymatgen结构为pyxtal结构
px_structure = pyxtal()
px_structure._from_pymatgen(structure)
# 获取空间群信息
spg_symbol = px_structure.group.number
... |
44731bd71034feba144a86ff503370a9b67c786c50c5f5a709ca6560497b5d6a | Python | 2,805 | 84 | from __future__ import annotations
import os
import re
from typing import Literal
import pytest
import torch
from ase.filters import ExpCellFilter, Filter, FrechetCellFilter
from pymatgen.core import Structure
from chgnet.graph import CrystalGraphConverter
from chgnet.model import CHGNet, StructOptimizer
@pytest.m... |
f15a6f8e36e06f38f0d38a40da9e4e42f9e0934d0dd8c3b4e8e9d3808dd3cd2d | Python | 2,806 | 74 | import numpy as np
import torch
from nanoUtil import fetchSignal
import time
import random
def aggregate_scors(scores, method):
if method == 'mean':
return np.nanmean(scores)
elif method == 'median':
return np.nanmedian(scores)
elif method == 'min':
return np.nanmin(scores)
elif... |
291a5548523e3712fd69074cfe1e83317df6998bf414472eac3c39e8cb6f5e71 | Python | 2,807 | 82 | # coding=utf-8
# Copyright 2022 IDEA-CCNL and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... |
5feb7a386f7efe78700860214b1cf6ba00f1a722c464acb2989fbe7ff161de7c | Python | 2,807 | 75 | import argparse
import pandas as pd
import torch
import torch.utils.tensorboard
from tqdm.auto import tqdm
torch.backends.cuda.matmul.allow_tf32 = True
torch.backends.cudnn.allow_tf32 = True
from rde.utils.misc import get_logger
from rde.utils.train import *
from rde.models.rde_ddg import DDG_RDE_Network
from rde.util... |
e377c4e5b741c4a2f31b50bbaf3643d8978ea96eadac539f59af4b4cf07bd6dd | Python | 2,810 | 78 | """Regression: RoomRenamed reaches the previous owner's user channel (finding #14).
Alice owns room "foo". A Group G has member Bob. A third client is "in the room"
on the surrogate channel. Alice (as superuser) transfers foo from her namespace
to G's namespace. Expectations:
- Alice receives RoomRenamed on user:<a... |
9b7a3506b88842ec09031fb7cd0fc1d3fed82e137ce06dbca10495e6c180dda9 | Python | 2,811 | 92 | # 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.
import os
import time
import numpy as np
import torch
from tqdm import tqdm
from sam2.build_sam import build_sam2_video_... |
8d39deec79eaa40190d8e0764463e3b0ec0897deff4c0338499b23137f91ef28 | Python | 2,813 | 72 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.14 on 2018-09-10 18:45
from __future__ import unicode_literals
from django.conf import settings
import django.core.validators
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
... |
d7cfaa12154ce9d68fc2e594875de1ff742974fe885e98ef5dc39b8e1f9dc2a5 | Python | 2,813 | 79 | # pytest unit tests for all cli scripts
import pytest
import sys
import importlib
from importlib.metadata import entry_points
import subprocess
scripts = [cs.name for cs in entry_points().select(group='console_scripts') if cs.value.startswith("spinalcordtoolbox")]
scripts_where_no_args_is_valid = [
'isct_test_an... |
2af69dac34ac0d29bb9ce617b1f6a35dbf9280fac37843f95dcad61fa8ed3cd1 | Python | 2,814 | 101 | import functools
import ase.io as aio
import ase
import torch
import zntrack
try:
from mace.calculators import MACECalculator
except ImportError:
print(
"""
WARNING: MACE is not installed!
You need to install MACE to use this package.
You can install it via 'pip install git+https://github.com/ACEsuit... |
1fa3062d6db4dd618d7b3c6a9229d168836a4a75bf6443c718ad08f55625b5b6 | Python | 2,815 | 86 | # MLCube Entrypoint
#
# This script shows how you can bridge your app with an MLCube interface.
# MLCubes expect the entrypoint to behave like a CLI, where tasks are
# commands, and input/output parameters and command-line arguments.
# You can provide that interface to MLCube in any way you prefer.
# Here, we show a wa... |
6327e76e260e8e99ce31e00d193f27383abec72ef376adef5d69575072bc062d | Python | 2,817 | 91 | _base_ = [
'../_base_/models/fpn_poolformer_s12.py', '../_base_/default_runtime.py',
'../_base_/schedules/schedule_40k.py'
]
# dataset settings
dataset_type = 'ADE20KDataset'
data_root = 'data/ade/ADEChallengeData2016'
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb... |
f94f0a92944742e383095e8d7f8afa576ede7769aa1626be40d6d1d65637732d | Python | 2,818 | 106 | #!/usr/bin/env python3
#
# Creates a tex table of all reported midpoints.
#
import base
filename = 't3-all-midpoints.tex'
nooocytes = True
qo = 'where cell != "Oocyte"' if nooocytes else ''
# Collect journal references
refs = {}
with base.connect() as con:
c = con.cursor()
q = 'select key, tex from publicati... |
9416005dedb23a129b86ffeb1c04ca108ae4b779a473b1482cf3fd35a81ab203 | Python | 2,821 | 69 | from inspect import signature
from typing import Union
from gymnasium import Space
from gym.vector.utils import spaces
from CybORG.Agents.SimpleAgents.BaseAgent import BaseAgent
#agent that does random action
from CybORG.Simulator.Actions import Sleep
#testing
from CybORG.Simulator.Actions.ConcreteActions.ControlTr... |
1ed73213b721f6fea74ed768dd4c1f83b2291fcdbc907ac006488b492d83b5c3 | Python | 2,822 | 75 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from torch import nn
from torch.nn import functional as F
class Encoding(nn.Module):
"""Encoding Layer: a learnable residual encoder.
Input is of shape (batch_size, channels, height, width).
Output is of shape (batch_size, num_codes, channels)... |
afd3b14343d931b378efa53b1c5d6afd8fee960a8967c8f12792a03fda6b892b | Python | 2,822 | 60 | from PyQt5 import QtCore, QtWidgets
from PyQt5.QtWidgets import QSizePolicy
# https://stackoverflow.com/questions/52615115/how-to-create-collapsible-box-in-pyqt
# https://github.com/By0ute/pyqt-collapsible-widget
class CollapsibleBox(QtWidgets.QWidget):
def __init__(self, title="", parent=None):
super(Co... |
5882e2dc3a58701b0079f9f6d77c691c05f94c45da18d0e70b2d43bc73745de7 | Python | 2,823 | 83 | _base_ = [
'../_base_/models/bisenetv2.py',
'../_base_/datasets/cityscapes_1024x1024.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_160k.py'
]
crop_size = (1024, 1024)
data_preprocessor = dict(size=crop_size)
norm_cfg = dict(type='SyncBN', requires_grad=True)
models = dict(
data_prep... |
ce16b561394428e40c30b787c12bdd5e2cb6ea4a7970b1d45d79c2fa3ea25f64 | Python | 2,823 | 91 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import os
import shutil
import numpy as np
from dmriqcpy.analysis.stats import stats_frf
from dmriqcpy.io.report import Report
from dmriqcpy.io.utils import (add_online_arg, add_overwrite_arg,
assert_inputs_exist, assert_ou... |
db56c7f76d7ccbb48a7362a399c59adf1840ea55eacf3d526fb778fdd2946ad8 | Python | 2,823 | 84 | from PyQt5 import QtCore, QtWidgets
import quantities as pq
import numpy as np
import pyabf
from threads.Worker import Worker
from view.ABFLoaderDialog import ABFLoaderDialog
from model.Source import Source
class ABFLoader():
def __init__(self, data_manager, filepath):
"""
Starts the... |
36f65ef9ad9925f997d3af805af226dd543a42c9a8603ff810254c33ee03233a | Python | 2,825 | 86 | import glob
import os
import numpy as np
from PIL import Image
root_path = 'data/'
img_suffix = '.jpg'
seg_map_suffix = '.jpg'
save_img_suffix = '.png'
save_seg_map_suffix = '.png'
tgt_img_dir = os.path.join(root_path, 'images/train/')
tgt_mask_dir = os.path.join(root_path, 'masks/train/')
os.system('mkdir -p ' + tgt... |
f382ca605e3b066314516d8c6113019b398bbcfeafd84980d9f8e3b8091875fc | Python | 2,825 | 87 | import pytest
from playwright.sync_api import expect
@pytest.mark.ui
def test_save_to_file_button_removed(page, live_server_url):
page.goto(live_server_url)
expect(page.get_by_role("button", name="Save to file...")).to_have_count(0)
@pytest.mark.ui
def test_label_stores_button_visible(page, live_server_url)... |
bea759a56aef19aa572015a7d92b533e97b38a0cd6943114ceaa87ea9aa73640 | Python | 2,826 | 80 | from selenium.webdriver.common.by import By
from ..base_page import BasePage
class DatasetDetailsPage(BasePage):
PREPARE_BTN = (By.ID, "prepare-dataset")
PREPARED_TEXT = (By.CSS_SELECTOR, 'div[data-testid="prepared-section"]')
SET_OPERATIONAL_BTN = (By.ID, "set-operational")
SET_OPERATIONAL_TEXT = (... |
7242cf1948ab628d0de568128084d0108828792a13510fd6c4f386ce52cbfb4a | Python | 2,827 | 87 | import pandas as pd
import argparse
import os
import yaml
import json
from utils import get_image_data_df
class Stats:
def __init__(self, data_path, labels_path, out_file, params):
self.data_path = data_path
self.labels_path = labels_path
self.data_file = os.path.join(data_path, params["o... |
cfd19894dec2a3171df3133e605f6a356c9ff99bedd8e926a11ebc9941b5ee29 | Python | 2,829 | 97 | from Utils.dataloader_GRAZPEDWRI import *
from Utils.config import *
from Utils.models import *
from Utils.TrainModel import *
from multiprocessing import Process
def task(lr, data_partition:float=None, run_idx:int=None, backbone: str='eff0'):
_cuda = 'cuda:0'
_image_size = get_image_size_for_backbone(backbone=backb... |
05045319b85a2fc6ea05d7c32758c64eecdd8c13da687dfee623aabebf6e76d4 | Python | 2,830 | 74 | # run fit_gkr_models.py first
import hickle as hkl
from umap import UMAP
from grid_cell.ploter import gp_torus_surface
from grid_cell.util import pca_accumulated_variance_explained_ratio
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
from grid_cell.gkr import GKR_Fitter
from grid_cell.manifold_fi... |
1115808f3f724ab08f9c2f616d0889571191d3efbe3dbc4251b75bbcfa4fe5d5 | Python | 2,831 | 79 | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.transforms.loading import LoadImageFromFile
from mmcv.transforms.processing import (RandomFlip, RandomResize, Resize,
TestTimeAug)
from mmengine.dataset.sampler import DefaultSampler, InfiniteSampler
from mmseg.datasets.l... |
3968f136dee2ce30fb5a37e8145bb50f64a556b9b8de56f5706d7dd41426bd74 | Python | 2,832 | 96 | from transformers import TrainingArguments
from trl import SFTTrainer, DataCollatorForCompletionOnlyLM
from unsloth import FastLanguageModel
from datasets import load_dataset
import pandas as pd
import argparse
import torch
def preprocess_logits_for_metrics(logits, labels):
with torch.no_grad():
logits = logits.cpu... |
052d5610bd89eabc0070a784be8671f4ab54ff0c328770594c885424daae3be2 | Python | 2,833 | 65 | # pytest unit tests for sct_resample
import pytest
import logging
from spinalcordtoolbox.image import Image
from spinalcordtoolbox.scripts import sct_resample
from spinalcordtoolbox.utils.sys import sct_test_path
logger = logging.getLogger(__name__)
@pytest.mark.sct_testing
@pytest.mark.parametrize("path_in,type_a... |
24fefa07cdc859e1fe4eb42aed39a0ee9a038496d2b7a5a1ce2df06886f86a43 | Python | 2,833 | 78 | #!/usr/bin/env python
#
# Copyright 2009, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
7226dfdbed0cb8d9c64ab8b13c133001b30384806d6ce150404374a776a60f72 | Python | 2,835 | 97 | import os
import sys
import numpy as np
import random
import string
import pandas as pd
################ Paths and other configs - Set these #################################
data_dir = '/u/scr/nlp/dro/multinli/data'
glue_dir = '/u/scr/nlp/dro/multinli/glue_data/MNLI'
type_of_split = 'random'
assert typ... |
6178f74a3bf95ae1c3b4cbcea15192d09f4bf89fc11f8ab47eb813d89bf3b856 | Python | 2,836 | 91 | from .ProvenanceObject import ProvenanceObject
from .set import Set
from .set_type import SetType
class Transformation(ProvenanceObject):
"""
This class defines a dataflow transformation.
Attributes:
- tag (:obj:`str`): Transformation tag.
- sets (:obj:`list`, optional): Transformation se... |
9e1855f555ebd8c671159db0c7596851ae4b969f5037008871aa5dde6f8c7c39 | Python | 2,836 | 75 | import os
import numpy as np
import matplotlib.pyplot as plt
from grid_cell.util import select_arr_by_t, get_data_filename_by_keywords
from global_setting import *
mouse_name = 'R'
day = 'day1'
module = '2'
session = 'open_field_1'
pca_str = '6' # none or number as a string
## raw data
file_name = get_data_filename_... |
3f495fbc25c4b5912a1353a1c215f2db6cb33959d7c1c98e0a7f919a4339dec2 | Python | 2,837 | 96 | from Utils.dataloader_COVID import *
from Utils.config import *
from Utils.models import *
from Utils.TrainModel import *
from multiprocessing import Process
def task(lr, data_partition:float=None, run_idx:int=None, backbone: str='res152'):
_cuda = 'cuda:0'
_image_size = 224
_lr = lr
_info = "RadiologyNet_"+str(l... |
70005485fac8dc36add36255bc48b057e336f75d5e064847efbe216230ff74e4 | Python | 2,837 | 69 | """
Compatibility layer to launch old scripts
Copyright (c) 2019 Polytechnique Montreal <www.neuro.polymtl.ca>
License: see the file LICENSE
"""
import sys
import os
import subprocess
import multiprocessing
from numexpr.utils import detect_number_of_cores
from spinalcordtoolbox import __file__ as package_init_file
... |
1da8a1e6dcef4ba1e5d614c558084408bda4b3047a8233c6469f58361e26d162 | Python | 2,838 | 79 | ## Restormer: Efficient Transformer for High-Resolution Image Restoration
## Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang
## https://arxiv.org/abs/2111.09881
import numpy as np
import os
import argparse
from tqdm import tqdm
import torch
import torch.nn as nn
imp... |
950a9b7d67fc3d74d321d4fc335bd7c492007f4a051f7ad6458805aa54bc8050 | Python | 2,838 | 125 | import io
from picsl_c3d import Convert3D
class C3D:
def __init__(self):
self.cmd = []
self.c = Convert3D()
def __repr__(self):
return ' '.join([str(part) for part in self.cmd])
def assign(self, var):
self.cmd.append('-as')
self.cmd.append(var)
return sel... |
eed7e92494acc19e8e044bd7c728ac541bafaa767983ec8531f642df8213f932 | Python | 2,839 | 89 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
import shutil
import tempfile
import zipfile
from mmengine.utils import mkdir_or_exist
def parse_args():
parser = argparse.ArgumentParser(
description='Convert NYU Depth dataset to mmsegmentation format')
parser.add... |
f29b1033373aa652a71ed000354718d6feaa04df6d28d48c1bc13653f888f4b7 | Python | 2,839 | 87 | import glob
import os
import numpy as np
from PIL import Image
root_path = 'data/'
img_suffix = '.jpg'
seg_map_suffix = '.jpg'
save_img_suffix = '.png'
save_seg_map_suffix = '.png'
tgt_img_dir = os.path.join(root_path, 'images/train/')
tgt_mask_dir = os.path.join(root_path, 'masks/train/')
os.system('mkdir -p ' + tgt... |
24492d9035c7ae918692b0f626f5b808b9f348b8fd47e831eb1c7ff273ac0d15 | Python | 2,841 | 67 | # dataset settings
dataset_type = 'GID_Dataset' # 注册的类名
data_root = 'data/gid/' # 数据集根目录
crop_size = (256, 256) # 图像裁剪大小
train_pipeline = [
dict(type='LoadImageFromFile'), # 从文件中加载图像
dict(type='LoadAnnotations'), # 从文件中加载标注
dict(
type='RandomResize', # 随机缩放
scale=(512, 512), # 缩放尺寸
... |
28734fec5da40c8890c8f5c17fc198b32bba2a4bd80621e45dc3c92b70e97074 | Python | 2,841 | 93 | from django.http import Http404
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework import status
from django.contrib.auth import get_user_model
from drf_spectacular.utils import extend_schema
from .serializers import UserSerializer, UserMetadataSerialize... |
cdbd874d66ef7fb98979994488415bda75e79a2f31e3a5fa171f3fad20558024 | Python | 2,842 | 84 | # load badrun json
# query specific run by opening run specific csv
# extract value
# save in corresponding dataframe
# TODO: compile mean values
# %%
import nilearn
import pandas as pd
import matplotlib.pyplot as plt
import os, glob, sys
import numpy as np
import seaborn as sns
import re
import nibabel as nib
import ... |
090303719a063b8ad207ea1579731dc7f5017b8255e0828f467ec07a9c2752a4 | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse075_noise_final_'
baseSimTag = 'sparse075_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
5847e86b2d66a2e93f763a22ceb4c89fb7799413330141c5b4e43ea229c03b98 | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse100_noise_final_'
baseSimTag = 'sparse100_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
6d69f66b7e28dbe9b02df3221bc3c425db3c290107fd8b6633c6335196fcf4b4 | Python | 2,844 | 85 | import os
import numpy as np
num_to_modality = {
"_0000": "_brain_t1n.nii.gz",
"_0001": "_brain_t2w.nii.gz",
"_0002": "_brain_t2f.nii.gz",
"_0003": "_brain_t1c.nii.gz",
}
def get_subdirs(parent_directory):
subjects = os.listdir(parent_directory)
subjects = [
p
for p in subjec... |
804236276c3cdf231b1b87b0992929938c239e0f47689dea01e7b2322fa554b0 | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse050_noise_final_'
baseSimTag = 'sparse050_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
91f57833a8fc3af68f3399d00f21e7d0be9417adbecc6f794303bff1d3a9ad4e | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse070_noise_final_'
baseSimTag = 'sparse070_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
a4c7c636ad2d1cdbb3fcb892b5a110661cc0e429c2ebedf0458362840ab4ec82 | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse090_noise_final_'
baseSimTag = 'sparse090_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
b55b6d08476c7eb1b5e4cae8253aff4b8036be4ec840b86c73dcfffbf832c0a2 | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse095_noise_final_'
baseSimTag = 'sparse095_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
e654d611d1ed0152bc5d94c688607f476b4bd23ada1183cd7596c7997d92dc3b | Python | 2,844 | 75 |
baseFileName = './shellScripts/sparse080_noise_final_'
baseSimTag = 'sparse080_noise_final_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_sparse... |
360d2e468f57e377ba9425040a154d0a253272a6223c0135ce2a434f953af500 | Python | 2,845 | 82 | import shutil
from pathlib import Path
import pytest
from guppy.testing import compare_output_folders
from guppy.testing.api import locate_run_folder, step1, step2, step3, step4
from guppy_test_data import TESTING_DATA, event_ts_offset_for
STORE_ID_TO_STORE_LABEL = {
"Sample_Control_Channel": "control_region",
... |
644ceb84069d6fe8d756a7c515fba78e036f282b1d86cfcb31804e589811b7ce | Python | 2,847 | 51 | # pytest unit tests for sct_warp_template
import logging
from spinalcordtoolbox.image import Image
from spinalcordtoolbox.scripts import sct_warp_template, sct_register_to_template
from spinalcordtoolbox.utils.sys import sct_test_path
logger = logging.getLogger(__name__)
def test_sct_warp_template_warp_small_PAM50... |
964a8927a44d2c25361de5bfedee0722dd1eeca295c56b7b5e0be24bf956aad7 | Python | 2,849 | 91 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
# Default using 4 gpu when training
config_8gpu_list = [
'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py', # noqa
'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py',
'co... |
4974eeefa4e4ce2d982aa9feb0d7c256051609173e4f05a968a0eb0b0155e19f | Python | 2,850 | 76 |
baseFileName = './shellScripts/sparse080_10class_noise_'
baseSimTag = 'sparse080_10class_noise_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_s... |
534fdf3c9e1568120dc88dccdbe58111cacf319faf78c646fa4a69ae37032ceb | Python | 2,850 | 76 |
baseFileName = './shellScripts/sparse050_10class_noise_'
baseSimTag = 'sparse050_10class_noise_'
def generateCommand(trial_num=0,
num_trials=10,
learning_rate=0.001,
sim_tag='default',
exc_hid_rat=0.5,
epochs=30,
log_file='example.log',
w1_std=-1,
w1_s... |
f9e84b327dc49d8c26c85e514b3fe76f46a7e5fbe6c32cb4c66bcc6a5c85aa03 | Python | 2,853 | 80 | from medperf.entities.dataset import Dataset
import medperf.config as config
from medperf.utils import approval_prompt, dict_pretty_print
from medperf.exceptions import CleanExit, InvalidArgumentError
import yaml
class DatasetSetOperational:
# TODO: this will be refactored when merging entity edit PR
@classme... |
6f372a9592e236df904d82bf33dff76fb4d3a94b2a9e14031daf8724e9ada38d | Python | 2,854 | 86 | # model settings
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[127.5, 127.5, 127.5],
std=[127.5, 127.5, 127.5],
bgr_to_rgb=True,
pad_val=0,
seg_pad_val=0)
# adapted from stable-diffusion/configs/stable-diffusion/v1-inference.yaml
stable_diffusion_cfg = dict(
base_learning_rate... |
9c19a8799950944d8c5a8bd74d9bb124e5ebf6967df0be6ec93489133bc24785 | Python | 2,854 | 75 | from mpi4py import MPI
import hickle as hkl
import numpy as np
from grid_cell.persistent_homology import Is_Torus
from grid_cell.manifold_fitter import GP_Fitter, Avg_Fitter
from grid_cell.ploter import error_bar_plot
import matplotlib.pyplot as plt
import tensorflow as tf
import os
from sklearn import datasets
from gl... |
b28f8c69f7a12d37272cb7bd911487636041df13c26965c5e9bb0753ab92aec2 | Python | 2,854 | 110 | import traceback
import numpy as np
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import classification_report, precision_score, recall_score, roc_auc_score
import torch
from collections import defaultdict
def cal_recall(y_pred, y_true, top):
a_sort_idx = y_pred.argsort()
b_sort_idx = y_tr... |
d7737284ecdd66efc4df4aae1c7aea3c16f93ce69618e6c7e9c4491348d1ed5c | Python | 2,854 | 68 | import argparse
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
import time
from scipy import stats
import edl
import data_loader
import trainers
import models
from models.toy.h_params import h_params
parser = argparse.ArgumentParser()
parser.add_argument("--num-trials", default=20, type=i... |
51963161810779f42e0cb95efdccfb7781e01c5a69098726d8d86f6e9b89499a | Python | 2,855 | 84 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 16 11:45:02 2023
@author: schwab
"""
import torch
from torch.utils.data import DataLoader, Subset
from ..models.encoder import HetEncoder
from ..models.decoder import DisplacementDecoder
from ..data.handlers.particle_image_preprocessor import Part... |
966a98f37b598a39c62f1faa3a776efca7d7d7125617867f0f39a1d47505cbca | Python | 2,855 | 58 | from sklearn.model_selection import train_test_split
from sklearn import metrics
import seaborn as sns
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv1D, MaxPooling... |
28eca72c0800f20972a12537b5e478407571e738bca5a86112a7146dbe4cdb5b | Python | 2,857 | 78 | import numpy as np
import cv2
import torch
from yolov9_model import YOLOv9_GPU, YOLOv9_FPGA
from dataset_preprocessing import get_datasets, get_data_loaders
class ReinforcementLearning:
def __init__(self, use_fpga=False):
"""
Initialize the reinforcement learning module with explicit state and acti... |
3c98e3be479d7f74150536b7761bb569cfac567254eade2138e62056e15c690a | Python | 2,859 | 81 | # Copyright (c) OpenMMLab. All rights reserved.
from mmcv.transforms.loading import LoadImageFromFile
from mmcv.transforms.processing import (RandomFlip, RandomResize, Resize,
TestTimeAug)
from mmengine.dataset.sampler import DefaultSampler, InfiniteSampler
from mmseg.datasets.p... |
52cc02acd27a6046e4d95cd6e999de56af063a42e057dfcd5b7859319ece710b | Python | 2,861 | 72 | # Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# 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://w... |
588aaa9000bdce9e5db67d14b067858bc3d6a392e93e5cbb37cb797a2d0f4251 | Python | 2,861 | 107 | """Responses classes"""
"""
Copyright (c) 2016-2020, EPFL/Blue Brain Project
This file is part of BluePyOpt <https://github.com/BlueBrain/BluePyOpt>
This library is free software; you can redistribute it and/or modify it under
the terms of the GNU Lesser General Public License version 3.0 as published
by the Fre... |
0cd78fdeee319c29cde68778e7f58fee3ba91a898ed3cc40aaa236df939833d8 | Python | 2,863 | 89 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmengine.registry import init_default_scope
from mmseg.registry import MODELS
def test_pidnet_head():
init_default_scope('mmseg')
# Test PIDNet decode head Standard Forward
norm_cfg = dict(type='BN', requires_grad=True)
backbone_cfg =... |
a9d7b398c3ed28c8f5605500453c75d55599a9cc824195f11780db02711b8a86 | Python | 2,864 | 63 | from django.db import migrations, models
import django.db.models.deletion
forward = """
SELECT disable_history_tracking_for_table('catmaid_userprofile'::regclass,
get_history_table_name('catmaid_userprofile'::regclass));
SELECT drop_history_view_for_table('catmaid_userprofile'::regclass);
ALT... |
619d8e118708c79de54f4687e6f6d26af6423da7fdaf6ff98a80bd58faa52e03 | Python | 2,866 | 89 | import numpy as np
# target_dist (target_distribution) f : x(state) -> double(probability)
# proposed_dist (proposed_distribution) f : x(current_state) -> x'(new_state)
# for sampling, object(MetropolisHasting).get_sample f : int(size) -> list(sampled values)
class MetropolisHasting:
def __init__(self, size, m... |
21b9d799ff58e5ce6f42edc0eb89c1e8627cbc9aa22357baadbcecccbf25102c | Python | 2,867 | 90 | import torch.nn as nn
import torch.nn.functional as F
from layers import GraphConvolution
import torch
class GCN(nn.Module):
def __init__(self, nfeat, nhid, out, dropout):
super(GCN, self).__init__()
self.gc1 = GraphConvolution(nfeat, nhid)
self.gc2 = GraphConvolution(nhid, out)
se... |
ca7354e528b68560591d923f410bf636a9563576f19ccaee58e9af560550f4cc | Python | 2,867 | 99 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from functools import partial
import torch
def _standardize(kernel):
"""
Makes sure that N*Var(W) = 1 and E[W] = 0
"""
eps ... |
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