sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e54021ca1abd94d2decd5246e9b7d514fe507111eea926f5d0aaf7c88d7a6550 | Python | 47,812 | 826 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from HierarchiaPy import Hierarchia
import matplotlib
matplotlib.style.use("seaborn-v0_8-whitegrid")
import igraph as ig
import networkx as nx
import os
import sys
import seaborn as sns
from weighted_rc_coeff import weighted_rich_club
from scipy imp... |
8bb8bc7d3657fb3952d19adfff9bd9992b8f09071e30f7013bafbb6f2ba9c091 | Python | 47,818 | 1,218 | from __future__ import annotations
import math
import os
import shutil
from collections.abc import Callable, Mapping
from dataclasses import dataclass
from typing import Any, Self, overload
import networkx as nx
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from jaxtyping impor... |
46b9f49c099cb43e1b6755db16cfa32683ea391cd63b488048abeec64fc44158 | Python | 48,058 | 1,241 | from __future__ import annotations
import logging
import warnings
from functools import partial
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import rich
import torch
import torch.distributions as dist
from anndata import AnnData
from tqdm import tqdm
from scvi import settings
from scvi.dat... |
cf1295ae38b6dbd298d82cfa6916345e23f2f5d3082764272d8bd29964ab9439 | Python | 48,089 | 1,235 | """
This is a module that contains functions generally useful for the
gmx_MMPBSA script. A full list of functions/subroutines is shown below.
It must be included to insure proper functioning of gmx_MMPBSA
List of functions and a brief description of their purpose
-remove: Removes temporary work files in this directory... |
4c661233c17d57730a7e46f3af4f7b6bdc58ced0844970b40856e82b77a65190 | Python | 48,152 | 1,061 | import logging
from dataclasses import dataclass
from typing import Dict, List, Optional
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import pytorch_lightning as pl
from .backbones import ResNet18Enc, ResNet18Dec
logger = logging.getLogger(__name__)
@dataclass
class... |
3386ef6b239ee4a363863b4516b6ee752b2b0c3e4ceea4a6b99822f1414b906b | Python | 48,394 | 999 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors, Facebook AI Research authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the L... |
0e36b1e3c652250b2193dee75a9f542f531220eac59ae8895b4bff3171e0633a | Python | 48,415 | 1,177 | import functools
import json
import time
import traceback
from pathlib import Path
from typing import Callable, Tuple, Union
import polars as pl
import yaml
from PyQt6 import QtCore, QtGui, QtWidgets
from rnalysis import __version__
from rnalysis.exceptions import InvalidValueError
from rnalysis.gui import gui_style,... |
1ede934a70c79d28688859f8448f7c0518a6ebfde9c1ad0b35fe9daf81e3324c | Python | 48,422 | 1,122 | # Copyright (C) 2025 ETH Zurich, Moritz Thürlemann, and other AMP contributors
import json
from openmmforcefields.generators import SMIRNOFFTemplateGenerator
from openmm.app import PDBFile, Modeller, PME, Simulation
import sys
import os
from abc import abstractmethod
import time
import numpy as np
import openmm as mm... |
53de0cbf1b645443103a324e37dd820b5418fed24461a277a4e330d1f6194843 | Python | 48,466 | 1,041 | # coding=utf-8
# Copyright 2019-present, Facebook, Inc and the HuggingFace Inc. team.
#
# 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
#
# Un... |
627133634b4a4719310a98d560d86af87dc8cd69b419ec025ad8550a1b98be5f | Python | 48,467 | 1,042 | # coding=utf-8
# Copyright 2019-present, Facebook, Inc and the HuggingFace Inc. team.
#
# 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
#
# Un... |
7a98528e12e01d36031beb3b2af3ac3ad4b6ec7831f8996f3a6a6b39f73e622f | Python | 48,508 | 1,245 | """DIAGVI model for multi-modal integration with guidance graphs."""
from __future__ import annotations
import logging
import os
import warnings
from typing import TYPE_CHECKING, Literal
import numpy as np
import scipy.sparse
import torch
from mudata import MuData
from scvi import REGISTRY_KEYS, settings
from scvi.... |
002ef0b24be7aeec97888842d0003a4b8876015007c2184440fb39a7487108aa | Python | 48,586 | 1,178 | import abc
import enum
import inspect
import itertools
import math
import types
import typing
import warnings
from datetime import date, datetime
from functools import lru_cache
from pathlib import Path
from typing import Callable, Dict, Optional, Tuple, Union
import joblib
import lazy_loader as lazy
import matplotlib... |
9ad9b9c90de54e70bd7d0f59fe72566aef8db1f2ac4ae8aaf4724bea6902a87f | Python | 48,643 | 1,340 | """
This module builds secondary structure prediction.
Author: wangning(wangning.roci@gmail.com)
Date : 2023/2/25 15:08
"""
import math
import time
import pickle
import os.path as osp
from collections import defaultdict
import numpy as np
from tqdm import tqdm
import paddle
import paddle.nn as nn
from paddle.nn im... |
c8bd15a932bc52e9d10f2e9a4b9f73b1b36ecec0b042dd249211b7d8cb91fbac | Python | 48,792 | 1,429 | """`precompute-embeddings` embeds what it was asked to, and stores it all.
Everything here is about the bookkeeping around the embedding, which is stubbed
out: that every document reaches the LMDB, that every flag reaches the
embedder, that a run which stopped early cannot look finished, that the store
records what wr... |
09dd8bffb8888f27e0242f6cce3b76a9335b729f8753497aea0e69f3f78b59bd | Python | 48,931 | 1,066 | # important first import
import torch
import torch.nn.functional as F
import os
import re
import sys
import glob
import configparser
import numpy as np
import datetime
import logging
import random
import threading
import time
import shutil
import sounddevice as sd
from scipy.signal import lfilter, butter, lfilter_zi, ... |
bf6ae6824b7d78e5f0f53fc8b86f4c14ac88640ada901473b9581d246bd0f060 | Python | 48,986 | 1,061 | """Old plotting tools. Deprecated.
.. warning::
This module is deprecated and will be removed in 6.0.0.
"""
import math
import numpy as np
import h5py
import pysam
import pyBigWig
import pybedtools
# You must install bpreveal with conda develop in order to import bpreveal tools.
from bpreveal.internal.con... |
23e32127f217e07e6d93d132677c1a3b84f0c285247f3f049f30da582f983ab8 | Python | 49,162 | 1,113 | """
Holdout Training Script for HIPPIE - WAVEFORM + ISI ONLY (Bimodal)
This script trains HIPPIE using only two modalities:
- Waveform (wave): Spike waveforms
- ISI Distribution (isi): Interspike interval histograms
The ACG (autocorrelogram) modality is excluded from this version.
This is the inductive/holdout ev... |
ec02f59c250762d1aad059b42b647bafadf8b960d1a9e53220abaa340140db90 | Python | 49,180 | 1,216 | """Controller for telemetry plotting, overlays, and aligned temp/act extraction."""
from __future__ import annotations
import logging
import math
import re
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from PySide6.QtWidgets import QInputDialog, QMess... |
cf7d7806a897a54ca7994f14b7051b35b2dc3d33b10dc4a8a56f5fbad9dc4f08 | Python | 49,184 | 1,240 | import copy
import warnings
warnings.filterwarnings('ignore')
import torch
from torch import Tensor
import torch.nn as nn
import torch_geometric.nn as gnn
import torch.nn.functional as F
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.typing import Adj, OptTensor, Size
from torch_geometric.util... |
893e127f94077bd5d09e940ee20d9f28a877cfbc81de9c0bd1090f16dd3244bb | Python | 49,268 | 1,077 | """Useful tools for creating sequences with a desired property."""
from __future__ import annotations
import ast
import random
from typing import TypeAlias, Literal
from collections.abc import Callable
import numpy as np
import matplotlib.axes
import matplotlib.colors
import numpy.typing as npt
from bpreveal import uti... |
a169c910a800682eca26ef602eec360019a7b7cb7f28bbaf6de116e05f36e069 | Python | 49,334 | 923 | import os
import sys
import argparse
from typing import Dict, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader, random_split
import time
import math
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as DDP
from typing imp... |
bf2d76ebe9a77d6bcde080ae4be6b554354dbb43dfc4577dc64563e0ba653c0c | Python | 49,372 | 901 | ###主要功能：在已经获得的组内叠加平均数据的基础上进行时间窗叠加平均和组间叠加平均
###首先在第29行设置需要保存结果的日期文件夹
###时间窗叠加平均：1）先选择视觉刺激或电流刺激
### 2）在visualresults或者/electricalresults中选择已经被组内叠加平平均的数据组
### 3）按顺序依次处理完所有数据组
###组间叠加平均：1）选择视觉刺激还是电流刺激（处理对象是已经进行过时间窗叠加的数据组）
### 2）选择起始数据和终止数据（就是确认哪些组是要进行叠加平均的）
###20210915 将组间叠加的数据添... |
11289dc5abd214b794f46d9869dd540deb012550c2627bb7475e405f4a7f4406 | Python | 49,407 | 910 | ###主要功能：在已经获得的组内叠加平均数据的基础上进行时间窗叠加平均和组间叠加平均
###首先在第29行设置需要保存结果的日期文件夹
###时间窗叠加平均：1）先选择视觉刺激或电流刺激
### 2）在visualresults或者/electricalresults中选择已经被组内叠加平平均的数据组
### 3）按顺序依次处理完所有数据组
###组间叠加平均：1）选择视觉刺激还是电流刺激（处理对象是已经进行过时间窗叠加的数据组）
### 2）选择起始数据和终止数据（就是确认哪些组是要进行叠加平均的）
###20210915 将组间叠加的数据添... |
8998d346da85d4a7a06b7baae720b314d1961259120ae9b450e645e5f5ef99aa | Python | 49,492 | 1,041 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
9ec73220e7bcc227467dd7d5d8917026c87ef54d1717b5296f9b019dfe3149a7 | Python | 49,658 | 992 | # ##############################################################################
# GPLv3 LICENSE INFO #
# #
# Copyright (C) 2020 Mario S. Valdés-Tresanco and Mario E. Valdés-Tresanco ... |
1467762da2db64d2707189aa81bf99ed22832ee73f39f6ba0e4f722353a3db3c | Python | 49,742 | 1,372 | #!/usr/bin/env python
"""
src/global_prototypes_splitfit.py
---------------------------------
Train global prototypes on TRAIN segment embeddings, then assign VALID/TEST segments
to nearest train prototype. Sweeps K over a list and produces publication-ready
stats + plots.
Expected directory structure:
segments/<mod... |
91aabb8ba7a6aa57a3cea85777c51f29d78db5d6b61ccac6badf1bd0e2a43a44 | Python | 49,817 | 1,329 | """Main module."""
from collections.abc import Callable, Iterable
from typing import Literal
import numpy as np
import pyro
import torch
import torch.nn.functional as F
from pyro.distributions import (
Categorical,
Delta,
Dirichlet,
Exponential,
Gamma,
Independent,
LogNormal,
Multinomi... |
48aa191c7cfd90cdd07d9ed027bf4197f647e6347188899448cd7a1e982416b2 | Python | 49,990 | 1,299 | """The linking block `evaluate` logs, and what keeps two authorities apart.
An evaluation reports one linking score per outside authority — NCBI's taxids
for the organisms, ENZYME's numbers for the enzymes, the collections' deposit
numbers for the strains — and `score_linking` refuses to put two authorities in
one rep... |
6660f95cb1d6a3348fdec491767e386d83ad9643db5a1e347d95f1ea94834a04 | Python | 50,308 | 1,504 | import os
from unittest.mock import Mock, patch
import pytest
import statsmodels.stats.multitest as multitest
from rnalysis.enrichment import *
from rnalysis.enrichment import _fetch_sets
from rnalysis.exceptions import InvalidTypeError
from tests import __attr_ref__, __biotype_ref__, is_ensembl_available, is_uniprot... |
8e7dd7eef2efc8479a15836dec00e7abad14aae2c198b1a7f47d11f1b21d0974 | Python | 50,337 | 1,220 | import h5py
import numpy as np
import os
import pandas as pd
import pickle
import scipy.io
import skfda
# NOTE: calculateMeanCoefficients was previously imported from BOTH auxFuncChPt
# and sharedUtils (the second import silently overwriting the first, since
# both modules define an identical, byte-for-byte-matching ... |
e101e5b1ffad0e42893db1af62bfec109fd817968a67100645f71fcedb06e909 | Python | 50,602 | 1,007 | import argparse
import logging
import os
import pysam
import medaka.common
import medaka.export
import medaka.features
import medaka.labels
import medaka.models
import medaka.options
import medaka.prediction
import medaka.rle
import medaka.smolecule
import medaka.stitch
import medaka.tandem.tandem
import medaka.train... |
8478cec48b78b025787eab286c5db57590024e2ba70025a7be03364e378d3c2c | Python | 50,620 | 1,084 | import torch
import torch.nn as nn
import torch.nn.functional as F
from dropblock import DropBlock2D, LinearScheduler
from modelR.layers.convolutions import Convolutional, Deformable_Convolutional
from modelR.layers.shuffle_blocks import Shuffle_new, Shuffle_Cond_RFA, Shuffle_new_s
import config.cfg_lodet as cfg
... |
9d43a0dd3a832d6d92166741051cbc64bf0bce3bbd3f68eb43fb7d0478acb8c8 | Python | 50,624 | 1,282 | from __future__ import annotations
import logging
import warnings
from collections.abc import Iterable as IterableClass
from functools import partial
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import torch
from mudata import MuData
from scipy.sparse import csr_matrix, vstack
from torch.di... |
fd5de0c7a1feb49c98f241c71f2dc7d4db6db97e5434834718e5ef688ceede5e | Python | 50,860 | 1,935 | from __future__ import annotations
import json
import logging
import os
import re
import sys
import tempfile
import uuid
from hashlib import sha256
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Any
from typing import Literal
import pytest
from packaging.utils import canonicalize_name
... |
f75d0712e3b13bebd8daa0a15e4eb32c9e3034a933f4fcccf65b1e999a7ae066 | Python | 51,024 | 1,387 | #!/usr/bin/env python
#
# Copyright 2007 Google Inc.
#
# 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 o... |
fb5e2c23a8f6602e782a300c1a45f7415ec0f53933c4b6e33aec37670eb4df71 | Python | 51,111 | 1,077 | import os
import numpy as np
import matplotlib.pyplot as plt
""" requires the data structure to be
raw data = /derivatives/sub01/ses01/eeg/preprocessed/pat1_preprocessed.edf
spindle data frame = /derivatives/Group/spindles/SP_events.csv
SO data frame = derivatives/Group/slow_waves/SO_events.csv
"""
def epoc... |
984c87bda0dc348ac907b6ce8a2316f90eb3923d891cadf3f75543a5f0504650 | Python | 51,214 | 800 | #!/usr/bin/env python
import argparse
import collections
import json
import numpy as np
import os
import pandas as pd
import random
import scipy.io as sio
import sys
import intervaltree
import scipy
from datetime import datetime
from pathlib import Path
from scipy.sparse import csr_matrix, coo_matrix
import common.u... |
7f77286d510ac4d7e7f34cdd16f9450949496e76e03763c647a243c55d7b4741 | Python | 51,334 | 1,190 | # -*- coding: utf-8 -*-
"""
Standalone benchmark utilities for reviewer-oriented CNN reconstruction checks.
This script intentionally avoids importing the Streamlit app. The numerical
formulas mirror the physics helpers in app.py, while the command-line defaults
point at the existing processed output folder.
"""
from... |
d3fc436d5f5649026874e3e0a1d01876843c5c08f36e9ece260635ef760bf10a | Python | 51,432 | 1,437 | """
phreeqc_simulator.py
====================================
致密砂岩多组分气体溶解度模拟器 — Lattice Boltzmann 前处理工具
基于 PHREEQC + phreeqpy 实现鄂尔多斯盆地深层水环境下的气体溶解度计算
作者: Claude AI
功能:
1. 单点计算器 (T/P 单次查询)
2. 2D 溶解度-温度多压交会图
3. 3D T-P-Solubility 互动相图 (Plotly)
"""
import os
import sys
import gc
import time
import warnings
import su... |
d7bb24331de809353726c9e6a6fe594bec3ad1b2aadce7107f0059794fee9790 | Python | 51,493 | 1,499 | # 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 math
from dataclasses import dataclass, field
from typing import List, Tuple
import numpy as np
import torch
import torch.nn as nn
imp... |
9a19529f874b82ab098db21898bfddfd2d5fde936b286dcbd373383de4b39f4a | Python | 51,549 | 1,324 | """Schemes to encode and decode truth labels and network outputs."""
import abc
import collections
from copy import copy
import functools
import importlib
import itertools
from operator import attrgetter
import intervaltree
import numpy as np
import pysam
import libmedaka
import medaka.common
import medaka.rle
import... |
4a3c4fbb4d60ae023dcf7c0d97ef7af943c8c4d14b379178481955f240fb4bf1 | Python | 51,688 | 1,231 | import itertools
import unittest
import numpy as np
import numpy.testing as np_test
from skbase.utils.dependencies import _check_soft_dependencies
from pgmpy import config
from pgmpy.example_models import load_model
from pgmpy.factors import factor_product
from pgmpy.factors.discrete import DiscreteFactor, TabularCPD... |
fe39e7e47256d270f5d00319c8ffba3fb037e9440e7aa55eea2a541da9db418e | Python | 51,726 | 1,268 | """
Phage competition sequencing analysis.
Stages:
1. QC + Alignment: fastp filtering -> minimap2 alignment (primary only)
2. SNV-based Read Assignment: score reads at variable positions, windowed chimera detection
3. Fold Change Calculations: cumulative log2 proportion FC, signed AUC, T0->Tfinal comparison
4.... |
7fc08d392b886b81928d180a12faff62cdb51f737cf45955224b6b99c7f50b1e | Python | 51,869 | 1,240 | #!/usr/bin/env python3
"""
NEMO Benchmark Evaluation Script for HIPPIE Pipeline
This script runs NEMO (Neural Multi-modal Embedding) evaluation on C4 database
H5 files using the same CV protocol as HIPPIE and PhysMAP for fair comparison.
IMPORTANT: NEMO requires data in H5 format with:
- Waveforms: (N, 90) interpolat... |
f82a9a934f539c97d4ea30145e3a5b8c6cc8b6f1fee8d6c1b3150aee26cab57c | Python | 52,041 | 1,344 | import logging
import os
import sys
import numpy as np
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
current_dir = os.path.dirname(os.path.abspath(__file__))
# 将当前目录添加到 Python 路径中
sys.path.append(current_dir)
from ernie_rna_utils import multi_head_attention_forward
from torch.autogr... |
546906bbbddf377f301b7799596890e8064304a4cd18d428a810b0e68a76baa1 | Python | 52,153 | 1,053 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
=============================================================================
Physarum polycephalum: History x Test-substance reanalysis at test phase 1
=============================================================================
DATA
Boisseau, R. P., Vogel, D. & D... |
65dceeeab7d63b0dd8b4b2575033a8546155b69aabdc0d37d7d35c526fde2d1e | Python | 52,192 | 976 | import os
from pathlib import Path
import joblib
import numpy as np
import pandas as pd
from joblib import Parallel, delayed
from sklearn.linear_model import LogisticRegression, LogisticRegressionCV
from sklearn.model_selection import ShuffleSplit
from sklearn.model_selection import StratifiedKFold
from sklearn.pipeli... |
6b3e130ed99b2813f882147e5fd2b03f9133bfa08635ed3929911960c9ec541a | Python | 52,297 | 1,403 | """Reading and writing of Variant Call Format files."""
import collections
import contextlib
from copy import deepcopy
import itertools
import os
from threading import Lock
import intervaltree
import numpy as np
import parasail
import pysam
import libmedaka
from medaka import __version__ as medaka_version
import med... |
c9c88819c7485e5619974f532a89e29a06d6f32092e408b6d6ed9b4d62f3b8ac | Python | 52,627 | 1,252 | import os
import io
import pkgutil
import scanpy as sc
import anndata as ad
from anndata import AnnData
from muon import MuData
import numpy as np
import pandas as pd
import scipy
from scipy.sparse import csr_matrix
from scipy.sparse import issparse, csr
from sklearn.preprocessing import MaxAbsScaler
... |
58623f5d89d0c849ad8d67f08fe3ca3e682570cd97ec3a65e29558382ab77925 | Python | 52,691 | 1,333 | import typing
from collections import defaultdict
from dataclasses import dataclass
from itertools import chain, combinations
import networkx as nx
import numpy as np
import pandas as pd
from pgmpy import config
from pgmpy.base import DAG
from pgmpy.factors.discrete import TabularCPD
from pgmpy.utils import compat_fn... |
f71b73729ff9d0c46c6797930646e2f8a226eef27a59cd7792ed86b193bc6ea9 | Python | 52,866 | 1,119 | from __future__ import print_function
import json, time, os, sys, glob
import shutil
import numpy as np
import torch
from torch import optim
from torch.utils.data import DataLoader
from torch.utils.data.dataset import random_split, Subset
import copy
import torch.nn as nn
import torch.nn.functional as F
import random
... |
2773a059fd59039a23e08c5e0a6f3385c2e69d5637133f3e95d2693a7b6e1493 | Python | 52,960 | 1,494 | import argparse
import dataclasses
import functools
import logging
import os
import re
import subprocess
import sys
import threading
import time
from collections import OrderedDict, namedtuple
from collections.abc import Callable
from dataclasses import dataclass
from functools import wraps
from pathlib import Path
fro... |
e27afd49c0838731a65be316f0138696727bb6dec3b5b504ffbf3889c59e3f7f | Python | 53,655 | 938 |
# -*- coding: utf-8 -*-
"""
Created on Tue May 20 16:30:53 2025
@author: HT_bo
"""
import numpy as np
import scipy.io
import scipy.signal
from scipy.stats import zscore
import pandas as pd
import matplotlib.pyplot as plt
# from open_ephys.analysis import Session # Bypassing for manual load
import os
... |
5f9011a17a79cae01ac7191fd9f1035d443e60298699d996682b3bf7ed6c3ca4 | Python | 53,732 | 947 | # -*- coding: utf-8 -*-
"""
Created on Thu Mar 23 13:32:45 2023
@author: fbigand
"""
# -*- coding: utf-8 -*-
"""
Created on Wed Sep 14 17:15:46 2022
@author: fbigand
"""
#%%
##############################################################
############ IMPORT LIBRARIES AND SET PARAMETERS ############... |
b2d8a1dff1c93c435a413a1e4707f9cc781f2858932424093164ba1033c0e0c0 | Python | 54,047 | 1,721 | # -*- coding: utf-8 -*-
# Copyright 2015 Google Inc. 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 require... |
4674f22773d352c790411d507e61aa2aad858a575bc8001127aab7fc7c9d7188 | Python | 54,473 | 1,226 | import itertools
import os
import warnings
from glob import glob
from typing import List, Union
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import ruptures as rpt
import scikit_posthocs as skph
import scipy
import seaborn as sns
import statsmodels.api as sm
from matp... |
db7e1340fcc91f4a6a8b7f48f5c7ba1e39368d2aef0b2b85f99093ce0a6ffa82 | Python | 54,563 | 1,425 | #!/usr/bin/env python3
import os
import unittest
import networkx as nx
import numpy as np
import pandas as pd
from skbase.utils.dependencies import _check_soft_dependencies
import pgmpy.tests.help_functions as hf
from pgmpy.base import DAG
from pgmpy.ci_tests import Pearsonr
from pgmpy.example_models import load_mod... |
13631a9ddad1fb7c90451df1007f17f8808531b9240f2df73252a527c146df4b | Python | 54,693 | 1,217 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
3ddb60726f2743a05fa6e7e7303f370ead80aec7e168a1a9bf6057951ae84b65 | Python | 54,710 | 1,350 | # analysis_kernels.py
import torch
import torch.nn.functional as F
import numpy as np
import math
from pathlib import Path
from typing import Dict, Tuple, Callable
from scipy import stats
import matplotlib.pyplot as plt
import seaborn as sns
from einops import rearrange
#!/usr/bin/env python
# %%
from einops.layers.t... |
ca92c329be679a77bb097f5b45ac47092d52bfdbe356a61c5768bb78d8e7a66b | Python | 55,318 | 1,610 | import pandas as pd
import pdb
# sys.path.append("../../corecode/")
from build import *
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy.stats import gaussian_kde
import matplotlib.colors as colors
import matplotlib.pyplot as plt
plt.switch_backend('agg')
from pathlib import Path
from... |
aade15b75c1cdc1c1f1addfb9a9e013ccb09e7e6975c42aff5cd9f8d921ee961 | Python | 55,387 | 1,335 | """
This module contains all implementation of windows in UI. There are adjustment
window, hardware window, control window, animal window, e-mail window, sensors window and
analysis window.
"""
"""
Copyright (c) 2019, 2022 [copyright holders here]
This file is part of NoSeMaze.
NoSeMaze is free software: you can red... |
1dba47bb9033dc97561a74fbeaffba9a622fa2056375f46780e2b2420ff647bd | Python | 55,505 | 1,011 | """LBM extraction-coefficient diagnostics for Scientific Reports revision.
The script is intentionally standalone. It does not modify the Streamlit LBM
applications. If exported final 2D fields are unavailable, it constructs
lattice-normalized post-processing proxy fields from phi_total.npy plus the
multi-slice summar... |
a35c3fa65e90f5247fafb3653d72f95784c853549191f41b32ce49d2583c9b3d | Python | 55,549 | 1,284 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
7e4365f195c681923ce2ef420db365469e545566d4a89a04e5e4e3842d9c4ba6 | Python | 55,750 | 918 | import inspect
import multiprocessing
import os
import traceback
from copy import deepcopy
from time import sleep
from typing import Tuple, Union, List, Optional
import numpy as np
import torch
from acvl_utils.cropping_and_padding.padding import pad_nd_image
from batchgenerators.dataloading.multi_threaded_augmenter im... |
ab0e3572b821331ded32dbe581f91e5d95e9852c4f2dd0a59fcbb8c0fa3c247b | Python | 55,874 | 1,584 | # src/segment_characterize.py
# -----------------------------------------------------------------------------
# Purpose
# Characterize discovered units (segments/clusters) from residue assignments.
# Reports:
# - size + contiguity + fragmentation metrics
# - label usage inequality (gini/entropy)
# - OPT... |
4aaa9b736871e18597ebeb157c19d5cfa098a6f5821b07b8e9ffa14495b38ca8 | Python | 56,355 | 1,162 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
af0c38e169f5c819f60e04a50d92413de0eb091f3b39e7e6b4b6a7debc9c9486 | Python | 56,356 | 1,163 | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... |
826fa39b4aa6b583637599ed7bacee481e8fc78a2991d006c72b93936286f71e | Python | 56,408 | 1,409 | # Copyright (c) 2022, Tri Dao.
# Inspired by / adapted from https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
import math
import re
from collections import OrderedDict
from copy import deepcopy
... |
4a633c1d759239fce4de9ebe069a1835bb26124e6eaeefd2653b1d33ae9e6659 | Python | 56,432 | 1,214 | import torch
import torch.nn as nn
import torch.nn.functional as F
from dropblock import DropBlock2D, LinearScheduler
from modelR.layers.convolutions import Convolutional, Deformable_Convolutional
from modelR.layers.shuffle_blocks import Shuffle_new, Shuffle_Cond_RFA, Shuffle_new_s
import config.cfg_lodet as cfg
... |
122cae1876a73ebddc4022ddff87e893967a94426ecef3489c61b90f0e6c0d52 | Python | 56,500 | 1,277 | #
# Copyright 2017-2023 Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with
# Sandia Corporation, the U.S. Government retains certain rights in this software.
#
# See LICENSE for full license details
#
import time
import numpy as np
import pickle
from .activate import Activate, RECTLINEAR,... |
a0acebbebac7c7a01691e3c3fbbfc7f68077d10a0b85caacf1ec7a1d208e5589 | Python | 56,626 | 1,775 | import simplejson as json
from ..globals import BMapType
from .global_options import TooltipOpts
from .series_options import (
BasicOpts,
ItemStyleOpts,
JSFunc,
LabelOpts,
LineStyleOpts,
Numeric,
Optional,
Sequence,
TextStyleOpts,
Union,
AreaStyleOpts,
)
# Chart Options
cl... |
d87b51680f86fa04e85c395582f252020bc8e6eba71491d7f05d845c6c5d8b81 | Python | 57,020 | 981 | import click
import os
import subprocess
import re
import functools
from trogon import tui
from .source.utils.decorators import debug_handler, timing_handler
timeit = False
LOG_FILE = "runs.log"
STATUS_FILE = "runs.status"
@tui()
@click.group()
def cli():
pass
@cli.command()
def version():
"""Prints version."""
c... |
78017ffe14d03b76ec740651c44420347b7180396d10efb347776d21d4049c2c | Python | 57,156 | 871 | #!/usr/bin/env python
import argparse
import collections
import json
import numpy as np
import os
import pandas as pd
import scipy.optimize
import scipy.io as sio
import time
import sys
import random
from datetime import datetime
from pathlib import Path
from scipy.sparse import csr_matrix, coo_matrix
from common.l... |
5d087541548b0e05e1f670b6df4bf2afc76b36732e4f777718adb8a90de614af | Python | 57,358 | 1,401 | """Evolutionary Bayesian Optimization and MCMC explorers.
Ported from D_Peptide_BO/bo_evolutionary.py and mcmc_evolutionary.py,
with fasthit dependencies removed. Uses local Encoder/Model/Landscape interfaces.
"""
import json
import math
import time
from datetime import datetime
from typing import Optional
import num... |
b839f11e5d4747701637e986ca1cf67f6075a0bf48ee605853c7c6ae2c6ab657 | Python | 57,448 | 1,996 | from __future__ import annotations
import sys
from pathlib import Path
from typing import TYPE_CHECKING
import pytest
import tomlkit
from packaging.utils import canonicalize_name
from poetry.core.constraints.version import Version
from poetry.core.packages.package import Package
from poetry.console.commands.instal... |
21dae85b09a5ac06f4642ee29fe75227de661a9a44dca4344ca83971105a52a6 | Python | 57,813 | 1,426 | import math
import os
from typing import Optional, Any, Literal
import logging
from dataclasses import dataclass
import torch
from torch import nn
import torch.nn.functional as F
from einops import rearrange
from .import_utils import is_flash_attn_2_available
if is_flash_attn_2_available():
from flash_attn import ... |
be441719d43c249e2588a9b2ba67a14f8721aec0845a4ac566a32690e15bb50d | Python | 58,130 | 1,401 | """
Transductive Training Script for HIPPIE - WAVEFORM ONLY
This script trains HIPPIE using only one modality:
- Waveform (wave): Spike waveforms
The ISI Distribution and ACG (autocorrelogram) modalities are excluded from this version.
Usage:
python train_multimodal_transductive_waveonly.py \\
--config... |
3dd9e3290aed70f08f7a00ae15ed2e82a4ec2e187466a51b218872063748b12f | Python | 58,450 | 1,498 | """Creation of neural network input features."""
import abc
from collections import defaultdict
import concurrent.futures
from contextlib import contextmanager
import importlib
import itertools
import os
import queue
import time
from timeit import default_timer as now
import numpy as np
from numpy.lib import recfuncti... |
3f0248e1b4bb909fa833928f251607ababe268694b84753c53edbc654dd4d282 | Python | 58,599 | 1,355 |
#!/usr/bin/env python3
"""
═══════════════════════════════════════════════════════════════════════════════
MS2 EIF2S1 DEFINITIVE PIPELINE — Google Colab (12GB RAM) — FIXED v2
═══════════════════════════════════════════════════════════════════════════════
MANUSCRIPT: "EIF2S1 Co-expression Network Reveals a Closed-Loop... |
991807744484b4dea6be426bf01dba131b27fa6944189b035926f0d10d9a767d | Python | 59,003 | 1,288 | """A bunch of helper functions for making plots."""
import math
from typing import Literal
import pysam
import pyBigWig
import pybedtools
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.figure
from matplotlib.transforms import Bbox, Affine2D
from matplotlib.font_manager import FontProperties
from ... |
157f1f1050b634afcaff0ccf38421bf9e1c16e578c3fb4b7313f3ac5caac7b5a | Python | 59,107 | 1,196 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... |
c4575352fe6ff348eb626e9dc9332751d42f00e3d9f3ed6a66509ee32ff1faca | Python | 59,108 | 1,197 | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... |
9ee9736a8262106ea9727b8c5d49205b57ff673af07261c8b562a7eabcebb4ac | Python | 59,212 | 1,704 | #!/usr/bin/env python2
# Daniel Kim, CS Foo
# 2016-03-28
# Script to run ataqc, all parts
import matplotlib
matplotlib.use('Agg')
import os
import sys
import pysam
import pybedtools
import metaseq
import subprocess
import multiprocessing
import timeit
import datetime
import gzip
import numpy as np
import pandas as p... |
a9a8703b4fb32b19a168bc6b3ac34731ab4db096540ddb9c31449d63d33f001d | Python | 59,242 | 1,378 | #!/usr/bin/env python3
"""
═══════════════════════════════════════════════════════════════════════════════
MS2 EIF2S1 DEFINITIVE PIPELINE — Google Colab (12GB RAM)
═══════════════════════════════════════════════════════════════════════════════
MANUSCRIPT: "EIF2S1 Co-expression Network Reveals a Closed-Loop
Translation... |
5d8c369cf64ba50d071372dd5f491acbbf2856a1b63595bd4cecfc6fd605027f | Python | 59,697 | 1,691 | """
Random bar width stimulus analysis pipeline.
Analyzes fish behavioral responses to random-width bar stimuli by constructing
spatiotemporal image representations of the stimulus in the fish's reference frame,
then filtering for periods of active following behavior.
Produces per-trial and per-experiment summary plo... |
591b07968a288c65fb3ffd1219eeb35c7472ae246994e22c4f5c0f27695191b3 | Python | 59,711 | 1,381 | from npyx.c4.dataset_init import (
N_CHANNELS,
WAVEFORM_SAMPLES,
extract_and_check,
get_paths_from_dir,
prepare_classification_dataset,
)
from torch.utils.data import Dataset
import npyx
import torch
import numpy as np
import os
import pandas as pd
import math
from math import pi
from celltype_ibl.p... |
a1b21e7ebefc584b4186156201d5149ad036902e947e6ef4c5815ce5145d0afd | Python | 59,902 | 1,996 | # @license
# Copyright 2017 Google Inc.
# 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... |
a21e2653f5d55a4543b33c426823f0e846173ef6785389dca5aaaec7ac5012ad | Python | 59,978 | 1,735 | #!/usr/bin/env python2
# Daniel Kim, CS Foo
# 2016-03-28
# Script to run ataqc, all parts
import matplotlib
matplotlib.use('Agg')
import os
import sys
import pysam
import pybedtools
import metaseq
import subprocess
import multiprocessing
import timeit
import datetime
import gzip
import numpy as np
import pandas as p... |
91391492ae861f686961f838d0c62e9d80de16671ae0233b6dd8186652b35c94 | Python | 60,004 | 1,314 | import sys
import os
import time
code_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'hippie'))
sys.path.append(code_dir)
# Now import directly from the modules (no 'code.' prefix)
from dataloading import MultiModalEphysDataset, none_safe_collate
from multimodal_model import MultiModalCVAE, Multi... |
93eb26c3ad745fa595769618a388ff43ed03a39f28d1ab392615727e680ba806 | Python | 60,102 | 1,564 | """
utils.py — Drosophila Body Orientation Predictor Utilities
Consolidated utility module for the full prediction pipeline:
- Data loading and merging (HDF5 → CSV)
- Feature augmentation (groundspeed, airspeed, thrust, etc.)
- Heading correction (naive unwrap and convex-optimization variants)
- Trajectory fil... |
5bd41a023831d1d3d0d9773358674a4b5cb16a29a9fda31aaacfd6b342b7606a | Python | 60,123 | 1,521 | from __future__ import annotations
import os
from typing import TYPE_CHECKING
import numpy as np
import torch
from lightning.pytorch import LightningDataModule
from scipy.sparse import issparse
from sklearn.preprocessing import LabelEncoder
from torch.utils.data import DataLoader
import scvi
from scvi.model._utils i... |
e2abd39014e40519a512d91fa41c8025347e3e69959d03b14a8ef6836010b0e4 | Python | 60,194 | 908 | """Build the revised MDPI manuscript for foods-4481855 from the submitted .docx.
Works on the original submission in place-preserving fashion: every edit is applied through
python-docx against the real MDPI styles, so the template formatting survives. All new or changed
text is coloured dark red so editors and reviewe... |
153135a01b684403c340efa445938ee03355e76919059e4729c48d04a49c1e6a | Python | 60,209 | 1,471 | #!/usr/bin/env python3
"""
Evaluate distortion correction methods on the synthetic test set.
This script compares:
1. FSL FUGUE simulation (single-direction unwarp using known VDM)
2. FSL TOPUP simulation (bidirectional field estimation and correction)
3. Our diffusion model (CNN + Diffusion refinement)
Metrics compu... |
52511e66ae824a81a4688bb4b297aa95e1be5cea67099bd1ad3032aab455cf56 | Python | 61,065 | 1,465 | """
Transductive Training Script for HIPPIE - WAVEFORM + ISI ONLY
This script trains HIPPIE using only two modalities:
- Waveform (wave): Spike waveforms
- ISI Distribution (isi): Interspike interval histograms
The ACG (autocorrelogram) modality is excluded from this version.
Usage:
python train_multimodal_t... |
bd4b316e0d794d8fd5ac37cfb8420510a67e7bc78719877ac6fc366ea16aada1 | Python | 61,071 | 1,175 | """
This module provides a means for users to take advantage of gmx_MMPBSA's parsing
ability. It exposes the free energy data (optionally to numpy arrays) so that
users can write a simple script to carry out custom data analyses, leveraging
the full power of Python's extensions, if they want (e.g., numpy, scipy, etc.)
... |
3f7c0d8312ab9c5caf71cf9764f7396f1464b18625ba5622307234b3481d9e2b | Python | 61,077 | 1,678 | """Pure unit tests for `d3text.models.base`.
The shared `Model` base class and the module-level helpers — pooling,
telemetry, metrics, embeddings-store plumbing. Everything runs on CPU with tiny
synthetic tensors through the `stub` fixture, which supplies only the
attributes each method reads.
"""
import logging
impo... |
4dbf53582bc58a1d50170d8b1e709752ef42d40a21d018cfdb27237a16c79558 | Python | 61,161 | 1,391 | """
This module contains calculation classes that call the necessary programs
for running MM/PBSA calculations.
Methods:
run_calculations(FILES, INPUT, rank) : Determines which calculations need to
be run, then sets up the calculations and runs them
Classes:
Calculation: Base calculation class
Energy... |
f1142e44e2c88233d10a1bf66bbe97a20e9e17f337f9bfea81f4f0b6e76cd1dc | Python | 61,227 | 1,396 | import os
import json
import warnings
from concurrent.futures import BrokenExecutor
from pathlib import Path
from pickle import PicklingError
from joblib import Parallel, delayed
import numpy as np
import matplotlib.pyplot as plt
try:
from mtscomp import Reader
MTSCOMP_AVAILABLE = True
except ImportError:
... |
7b08ca5b95670e255883fe69a36103beb6b131107cfd64ae2f232a57a9830ce2 | Python | 61,238 | 1,608 | # Authors: Christian O'Reilly <christian.oreilly@sc.edu>
# Scott Huberty <seh33@uw.edu>
# James Desjardins <jim.a.desjardins@gmail.com>
# Tyler Collins <collins.tyler.k@gmail.com>
#
# License: MIT
"""Classes and Functions for running the Lossless Pipeline."""
from copy import deepcopy
from ... |
02720756f05b0245fd9c9962419e868b4d7a5c11d9728a9908d921c250186dc1 | Python | 61,857 | 1,536 | import shutil
import time
import datetime
import inspect
import yaml
import numpy as np
import pandas as pd
from scipy import optimize
from sklearn.cluster import MiniBatchKMeans
from sklearn.decomposition import PCA, FastICA
from sklearn.metrics import mutual_info_score, normalized_mutual_info_score, adjusted_rand_sco... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.