sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3030f2683915234a9e60bd9119235cc3c3f7066464a04ea66fb39c4cd2adbd89 | Python | 8,410 | 192 | import argparse
import time
import json
import random
from collections import Counter
from dataset import Mol3DDataset, SimpleTokenizer
import argparse
from utils import set_seed
import numpy as np
import wandb
import os
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from torch.nn import fun... |
4f6027113c234cada9a3abeccac946f2f8a1ea37788bf5e85dd59dc720376997 | Python | 8,412 | 213 | import settings
from pandas.core.frame import DataFrame
import re
from torch.utils import data
import pandas as pd
class Dataset(data.Dataset):
""" A class implementing :class:`torch.utils.data.Dataset`.
Dataset subclasses the abstract class :class:`torch.utils.data.Dataset`. The class overrides
``__len__... |
3c7ee8b1d5d87ea0fb48c4aaceab8d39a8e82060b287e0ecef1bdc79de933db4 | Python | 8,415 | 197 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models_no_res import *
def seed_everything(seed):... |
53f5e07c44866f51cfe470b289eeb2ef6d04256e3033426166b1eb84797de643 | Python | 8,417 | 266 | # coding: utf-8
""" MIT License """
'''
Project: Parenchymal Attention Network
Authors: Axel Masquelin
Description:
'''
# Libraries
# ---------------------------------------------------------------------------- #
from argparse import Namespace
import matplotlib.pyplot as plt
import pandas as pd
import numpy... |
a2ec1bc57fa6eb9a7e07a75d755f951532250b83333906da9ea4b9a765f65908 | Python | 8,420 | 192 |
from copy import copy
import numpy as np
import pandas as pd
from statsmodels.stats.multitest import multipletests
def ttest(params):
"""Perform a T-test on the data
Args:
params (list): list containing control and experimental groups,
normalized dataframe and if the variables are dependent... |
bc6a4db7f1c311a7d8efe4ac96cc287598184c15a1ee2126e93a20eb1fc0f8a3 | Python | 8,422 | 279 | from datetime import datetime, timezone
from unittest.mock import patch
import pytest
import pytest_asyncio
from langchain_core.indexing import InMemoryRecordManager
@pytest.fixture
def manager() -> InMemoryRecordManager:
"""Initialize the test database and yield the TimestampedSet instance."""
# Initialize... |
9493f5832bc10696f419f3194e04c06de69812971d1bcf475c35bddd9f308901 | Python | 8,423 | 258 | from pathlib import PosixPath
import matplotlib.pyplot as plt
import mlflow.pytorch
import numpy as np
import pandas as pd
import torch
from mlflow import start_run
from monai import transforms
from monai.data import PersistentDataset
from torch.utils.data import DataLoader
def log_mlflow(
model,
arg... |
e9c5f28db507a9a9d68e3fa0f4b53f1286d8071b0a900e80afe92a30facc177f | Python | 8,425 | 283 | import logging
import os
import warnings
from importlib import resources as impresources
from typing import Tuple, Union
import pandas as pd
import pytorch_lightning as pl
import torch
from rdkit.Chem import PandasTools
from torch_geometric.loader import DataLoader
from torch_geometric.transforms import Compose, Norma... |
20ab584638f0602ca5cda3bcd3519b7dd0efb61f17faeede882ef12e2e538558 | Python | 8,429 | 219 | import torch
from torch_geometric.loader import DataLoader
import os
import pickle
from sklearn.model_selection import KFold
import numpy as np
import random
from torch_geometric.nn import global_mean_pool, GATConv
import torch.nn.functional as F
import torch.nn as nn
from torch import optim
import datetime
class GATC... |
b31778cbbc03ab683f63ba2bb99a3cb0b015c85922cbe401522a2376a17b0d42 | Python | 8,430 | 203 | """
Defines model classes to compute and store nearest neighbor sets that can be
inherited across different `Embedding` objects.
"""
import numpy as np
from sklearn.neighbors import NearestNeighbors
from .utils import *
class Neighbors:
"""
An object representing a serializable set of nearest neighbors within... |
157408e3e2247422ad85d97f85201bfec849e38d75894de657393727fe3511f4 | Python | 8,432 | 222 | # Description: This script is used to test the influence of sample size on the classification performance of the three harmonization methods.
# The script is comparable to ABCD_ROCAUC_Comparison_controlled.py, but additionally iterates over different sample sizes and subsequently plots the results in a bubble plot.
# T... |
9880c26441a84a2daa96d69caf1829148951e7e5dad7c247b4230dadd54f0967 | Python | 8,442 | 224 | """
Trace: read trace summaries (.tr/.MN) or LD scores (.ldscore.gz) and
compute blockwise traces for FLEX.
Reference: https://github.com/sriramlab/SUMRHE/blob/main/src/trace.py
"""
import numpy as np
import pandas as pd
from os import listdir, path
def _calc_trace_from_ld(ldsum, n, m1, m2):
"""
Calculate t... |
95e14345c8caeeb28955fa8cf95de8e49184886ae2cfc6b066b8ac89af6a47a1 | Python | 8,443 | 204 | # 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... |
40b1ed188d4023858868254f3431103ccad71fc0fdd50721a9a7192dce62b006 | Python | 8,445 | 258 | """
:AUTHORS: Martin M. Müller
:ORGANIZATION: Department of Neurobiology, Bielefeld University
:CONTACT: martin.mueller@uni-bielefeld.de
:SINCE: Tue Nov 23 12:23:57 2021
"""
import numpy as np
from scipy.stats import vonmises
import scipy.integrate as integrate
from scipy.stats import norm
from scipy.stats import gamma... |
730116b4aa56bb1fc296b3e62420c9ac93eac4f9de97096507e091acaf2e6808 | Python | 8,447 | 161 | """Concise permanent logs and disposable stage records preserve the output data."""
import json
from pathlib import Path
import subprocess
import sys
import tempfile
import unittest
from unittest.mock import patch
import SimpleITK as sitk
import trimesh
from inference.native import main as native_main
from preprocess... |
c926e74a2ef8c33e1ad0f661e189302e6ca69435f57a9769533ab33141add03d | Python | 8,448 | 236 | """
Examining the variation explained of gene expression for sex-specific
expression differences by:
1. All DEGs
2. Allosomes only
3. Autosomes only
Also examine correlation for all DEGs accumentively.
"""
import numpy as np
import pandas as pd
from pyhere import here
import errno, os, argparse
from functools i... |
834384cefb5c3fe85ec4f4d37b8e07733c972616597b44eb58463ee650a4d396 | Python | 8,450 | 204 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
9ce3ea2056d7f5958a97c6843c7ce166f2500d7c750388ab4cc1291408aa0bbc | Python | 8,450 | 254 | import os
import cv2
import torch
import random
import numpy as np
from glob import glob
from torch.utils.data import Dataset
import h5py
from scipy.ndimage.interpolation import zoom
from torchvision import transforms
import itertools
from scipy import ndimage
from torch.utils.data.sampler import Sampler
import augment... |
3f66a24a9a05d33751ed7d94fd0c9963d3e08f3db3bbd52722126dc6258333f2 | Python | 8,454 | 206 | # -- coding: utf-8 --
# @Time : 2022/10/15 16:11
# @Author : Biao Zhang
# @Email : littlebiao@outlook.com
# @File : heco_config.py
import time
from yacs.config import CfgNode as CN
# --------------------------------------------------------------
# Config of model
# ------------------------------------------------------... |
b09ca596162f97b0477ef6fa4a2c65dd365bf566bd1b25f0db0d5b2c4006e19c | Python | 8,459 | 197 | import csv
import numpy as np
import os
import pandas as pd
from tqdm import tqdm
from mimic3benchmark.util import dataframe_from_csv
def read_patients_table(mimic3_path):
pats = dataframe_from_csv(os.path.join(mimic3_path, 'PATIENTS.csv'))
pats = pats[['SUBJECT_ID', 'GENDER', 'DOB', 'DOD']]
pats.DOB = p... |
e7b71114d36a00a944456e4397f2671e5b805e79771457d053d0171ee26817d6 | Python | 8,460 | 199 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models import *
def seed_everything(seed):
ra... |
1078c5cf7e12c335aae46cb54367ea66b6c68e007b9e68b9db8bd78d1698916f | Python | 8,462 | 198 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models import *
def seed_everything(seed):
ra... |
e60de31d953983abaa613d7373a54e3f15d95cbaa9c7817fe7aa7dc19166056e | Python | 8,463 | 182 | import numpy as np
import networkx as nx
import torch as pt
import pytorch_lightning as ptl
import torch_geometric as ptg
import torch
from torch.nn import Sequential as Seq, Linear, ReLU
from torch_geometric.nn import MessagePassing
from pytorch_lightning import LightningModule
from torch.optim.adam import Adam
from t... |
143f006226705cdfd0aa42f63c58a2ed85a92b031c8cd5779c7752722e168cf6 | Python | 8,464 | 241 | import numpy as np
try:
import openmm
from openmm import unit
except ImportError: # OpenMM < 7.6
from simtk import unit
from simtk import openmm
import os, os.path
import logging
from nose.tools import assert_raises
from openmmtools import testsystems
from functools import partial
def _equiv_topol... |
0247a26d9520a31ee98358307e39d5b24853994f733efafcedfdf077413218d4 | Python | 8,466 | 248 | """Caduceus config for Hugging Face.
"""
from typing import Optional, Union
from dataclasses import dataclass
from transformers import PretrainedConfig
from mamba_ssm.models.config_mamba import MambaConfig
@dataclass
class ExtendedMambaConfig(MambaConfig):
interact: str = ""
use_bio_mask: bool = False
... |
8918808a6ccc4f003e556431f2a26fa8bc7df3772a30d8ef3e1332d78f7462c9 | Python | 8,467 | 199 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models import *
def seed_everything(seed):
ra... |
5554cc98651a961f892845d8542d880bce330bb0ca935d09eec9ad9b8a128c55 | Python | 8,468 | 197 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models import *
def seed_everything(seed):
ra... |
c1a6daf23aaf3b01de5caadeac90cc6c36111b62c009f08d9debb5534182e983 | Python | 8,478 | 250 | # MIT License
#
# Copyright (c) 2022 Matthieu Kirchmeyer & Yuan Yin
from torchvision.utils import make_grid
from torch.utils.data import DataLoader
from torch.utils.data.sampler import Sampler
from torch.nn import init
import copy
import random
from torch import nn
import torch
import torch.nn.functional as F
from log... |
7cb0c91dd670d185cdf1d665699eac320438831f82f5e7bbe41d32ceb93a5776 | Python | 8,480 | 258 | """Schema definitions for representing agent actions, observations, and return values.
!!! warning
The schema definitions are provided for backwards compatibility.
!!! warning
New agents should be built using the
[`langchain` library](https://pypi.org/project/langchain/), which provides a
simpler an... |
f5d202bf5a4057db3dbe46275d1668bb211ecb4bd2a47949d5bd3a75fd752ac3 | Python | 8,482 | 260 | import logging
import os
import socket
import sys
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.transforms import Affine2D
import numpy as np
import pandas as pd
import seaborn as sns
from configs.configs import get_config_dict
def plot_quantitative_results(
config_dict: dict,
performanc... |
8c8e8c97fa89d1ce17b507694d923926886a1c654c5ceb0b3e8bc8e139fe3540 | Python | 8,487 | 200 | #!/usr/bin/env python3
import os
import torch
import hydra
import logging
from models import get_model
from torch_geometric.loader import DataLoader
from ori_dataset import Mixed_MD17_DFT, get_mask
from torch_ema import ExponentialMovingAverage
from transformers import get_polynomial_decay_schedule_with_warmup
logger =... |
f198e44a4b07247e86252d1e1c60524c9a1321d2eba7246dd146b3788fc89235 | Python | 8,488 | 241 | def extract_local_csf_mask(
csf_mask_path,
binary_roi_path,
dilated_roi_path,
csf_threshold=0.6,
save_path=None,
verbose=True
):
'''
Extracts a local CSF mask by identifying CSF voxels that lie within a dilated ROI
but outside the original binary ROI. Saves the result as a binary... |
3bba2a45edd577157854eb27f913391623441956d37d6cce703c80c2b51f95c7 | Python | 8,489 | 209 | """Tool error middleware for agents."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, cast
from langchain_core.messages import ToolMessage
from langgraph.errors import GraphBubbleUp
from langchain.agents.middleware.types import (
AgentMiddleware,
AgentState,
ContextT,
Res... |
64cb9bd701cb7079f3f5393d3eeecb8e4f4abd784d9e62e7d866cdc7b2574084 | Python | 8,491 | 212 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from __future__ import absolute_import, division, print_function
import os
import pandas as pd
import re
from pymatgen.core import Structure
from .conformer impor... |
6f34abfb4408773aa75aad9854e37a73014ff44cf5547dd2cd92aa72bf68c50a | Python | 8,495 | 212 | import os
import numpy as np
import tensorflow as tf
from tensorflow.keras import Model
from tensorflow.keras.applications import ResNet50
from tensorflow.keras.layers import BatchNormalization, Conv2D, Conv3D, \
Dense, Input
from explainability.model.utils import fuse_batchnorm
... |
048349989f193e9daf0922ead57ca66b6914290359a60742b1e993a3d3164a43 | Python | 8,496 | 221 | import torch
from torch_geometric.loader import DataLoader
import os
import pickle
from sklearn.model_selection import KFold
import numpy as np
import random
from torch_geometric.nn import global_mean_pool, GATConv
import torch.nn.functional as F
import torch.nn as nn
from torch import optim
import datetime
# 定义图神经网络模... |
3431c3b01dd0d2f15c20bacd5df17b4bbd373b3aa1d56cc7f89a92abacca5ada | Python | 8,498 | 248 | #!/usr/bin/env python3
"""CUDA-synced inference timing for an SCDP (ChgLightningModule) checkpoint.
Mirrors scdp/scripts/bench_flow_infer.py but uses direct coeff regression.
"""
from __future__ import annotations
import argparse
import json
from pathlib import Path
import time
import numpy as np
import omegaconf
i... |
d848634cde63d811dc6f6611300d21096e1c1295be258331889aadc4d45b2912 | Python | 8,498 | 233 | # Copyright 2024 DeepMind Technologies Limited
#
# AlphaFold 3 source code is 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... |
8cf18bd8c78bb86ce9ad2bca0ab5316cd783af2b9207b4f503033ab4c1aaa0af | Python | 8,499 | 235 |
import numpy as np
import torch as T
from nflows.distributions.base import Distribution
DATALOADER_args = {"pin_memory": True,
"num_workers": 4,
"prefetch_factor": 12,
"persistent_workers":True
}
class Iterator:
def __init__(self) -> No... |
e9bf631470ce5ff51402e80e004763af9cc40bdf1786591453aa3f0d6b27c29e | Python | 8,499 | 183 | import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
FONT_AXIS_TITLE = 14.5
FONT_LEGEND = 14.5
def plot_regions_per_group(data, regions, group, x_pos, vp, ID):
Nsamples = len(group)
dx = 0.1
x0 = Nsamples*0.1 / 2.
g = []
fig, ax = plt.subplots(figsize=(9,5))
my_cmap ... |
726e970bc02e07cbeb33a8f031fc617f02adf59334186f987ccce99d49317b9a | Python | 8,502 | 222 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Adapted from https://github.com/florentmeyniel/TransitionProbModel
"""
import itertools
from operator import mul
from functools import reduce
from scipy.stats import dirichlet
import numpy as np
def get_clipped_grid_indices(Dir_grid, p1_min=None, p1_max=None):
if... |
b8e0708132a22efe40a49826ab22788c300ec1c168b1ee45a0749e3613a6c765 | Python | 8,506 | 280 | import os
import sys
import re
import types
import itertools
import math
import numpy
from RnaseqReport import *
class MappingStatus(Status):
'''status information for mapping stage.'''
@property
def tracks(self):
d = self.get("SELECT DISTINCT track FROM view_mapping")
return tuple([x[0... |
b99685914683bea66ba657c78ab6c5b14774fbb0f9ef287c2b542198315b8629 | Python | 8,508 | 289 | # Copyright 2021 AlQuraishi Laboratory
# Copyright 2021 DeepMind Technologies Limited
#
# 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
#
# U... |
28687e818c3de38cd637e7a426da85d1142789715dd11e2cca0502c8f81ee98a | Python | 8,514 | 383 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import pickle
import os
import yaml
from sklearn.impute import SimpleImputer
import numpy as np
import math
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
np.random.seed(100)
get_ipython().run_line_magic('matplotlib', 'inline')
# %config Inli... |
758cea62a6961b69efe71a00453f07f10f3bac614a8c5422b3fbbb313b7629ca | Python | 8,521 | 178 | import argparse
import random
import time
import numpy as np
from . import logger
import torch
import os
class RunManager(object):
def __init__(self):
self.parser = argparse.ArgumentParser()
self.parser.add_argument("--workers", type=int, help="number of data loading workers", default=0)
... |
6cd844e7c83d9ffe940b67b2f9ce7bcb096aea0cf2b21269474c99b78816a2a5 | Python | 8,527 | 193 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this sof... |
0e8e3fd7a0fb17f0d853cb4b2b9564c2d506284167798568b4b336edc1172305 | Python | 8,533 | 176 | import argparse
from models import twostage_Unet
from tensorflow.keras import optimizers
import glob
import numpy as np
from utils.utils import prctile_norm
from utils.loss import read_mrc
import tifffile as tiff
import os
import tensorflow as tf
import math
os.environ["TF_ENABLE_AUTO_MIXED_PRECISION"] = '1'
os.enviro... |
cd31325f0b0e5b56981a940f446e05d801c13a20fb119c9f91152f39fff6990c | Python | 8,533 | 177 | import os
from time import time
from copy import deepcopy
import gc
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib.gridspec as gridspec
from natsort import natsorted
from utils.read_mda import readmda
N_CH = 24
F_SAMPLE = 30000
# MAP_PATH="../geom_channel_maps/map_corolla24c... |
1c3111642e67fbe759d7462b47e0b9b098d662296df945cf0df5de3d1f4443b0 | Python | 8,534 | 244 | import os
import sys
import re
import types
import itertools
import matplotlib.pyplot as plt
import numpy
import numpy.ma
import Stats
import Histogram
import cpgReport
from cgatReport.Tracker import *
from cgatReport.odict import OrderedDict as odict
##################################################################... |
b3c3df0c4261028a0e361f7706bcbc945d4e5f163bba0e32bc4d7460a22f03a9 | Python | 8,534 | 179 | #pylint: disable=E1101, E0401, E1102, W0621, W0221
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import random
import time
from random import SystemRandom
import models
import utils
parser = argparse.ArgumentParser()
parser.add_argument('--niters', type=int, default... |
d13903b57c1e619aec21131196783d75fb95470dc03bd0d7c45eb22f7afffdc4 | Python | 8,536 | 259 | """Question answering with sources over documents."""
from __future__ import annotations
import inspect
import re
from abc import ABC, abstractmethod
from typing import Any
from langchain_core._api import deprecated
from langchain_core.callbacks import (
AsyncCallbackManagerForChainRun,
CallbackManagerForCha... |
23bd878bcfe153c82e7dd05011bc4508c41fe1c9af94e96bc21e4ee665363689 | Python | 8,540 | 212 | # -*- coding: utf-8 -*-
"""
Class definition of YOLO_v3 style detection model on image and video
"""
import colorsys
import os
from timeit import default_timer as timer
import numpy as np
from keras import backend as K
from keras.models import load_model
from keras.layers import Input
from PIL import Image, ImageFont... |
2070786c9666a9aaf61ccd77167f8dd7519bc3b31d32b76ed9332f605a2a10ef | Python | 8,542 | 289 | """ This module provides implementations for corrupting the training data.
:Implemented:
- Identity
- Sampling Binary
- BinaryNoise
- Additive Gauss Noise
- Multiplicative Gauss Noise
- Dropout
- Random Permutation
- KeepKWinner
- KWinnerTake... |
c53bb5d5e122b156c5f3849342f431265ba25ec057165da9d13645cd694ecddc | Python | 8,543 | 227 | ###########################################################################################
# Adapted from MACE
###########################################################################################
import opt_einsum_fx
import torch
import torch.fx
from e3nn import o3
from e3nn.util.codegen import CodeGenMixin
fr... |
66eb3b69434897539d0069e394418b9dac9ea9ad4a1b1ae411a4fb487ef6eb76 | Python | 8,545 | 171 | # srun --nodes=1 --ntasks=1 --cpus-per-task=24 --mem=80g --time=04:00:00 --pty bash -i
# Sconda conda activate TensorFlow_CPU_01; cd /mnt/BioAdHoc/Groups/RaoLab/Edahi/Projects/09.TimeCourse5hmC/ForFerhatGit/FCDNN/code/; python
import matplotlib.pyplot as plt
import numpy as np
import os
import pandas as pd
import csv
i... |
c3d2ce4b081d83881f5fe304e4892dddb2bd8b84e9632b0a48bd35c682df38aa | Python | 8,546 | 266 | """A PyTorch Dataset class for annotated spectra."""
from typing import Optional, Tuple
import depthcharge
import numpy as np
import spectrum_utils.spectrum as sus
import torch
from torch.utils.data import Dataset
class SpectrumDataset(Dataset):
"""
Parse and retrieve collections of MS/MS spectra.
Param... |
33c38c788078a0e37ef872129445e9fc5e757f8939b6b8fb3b92f32de51fb718 | Python | 8,548 | 280 | import datetime as dt
import warnings
from collections.abc import Sequence
from typing import Any, Literal
from langchain_core.utils import check_package_version
from typing_extensions import TypedDict
try:
check_package_version("lark", gte_version="1.1.5")
from lark import Lark, Transformer, v_args
_HAS... |
1bd078082251d6176b565153fa462b457063485d92367b33de0da1b15fa47457 | Python | 8,549 | 253 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import sys
if '../../../embeddings' not in sys.path:
sys.path.append('../../../embeddings')
from seq2tensor import s2t
import keras
from keras.models import Sequential, Model
from keras.layers import Den... |
d5ccae607a04c40403ef099987894edf13c2a4a538a17592a45b7e833fa092ec | Python | 8,559 | 248 | '''
Author: Alexandra Fischbach
Github repo: https://github.com/AlexFischbach/local_csf_pipeline/tree/main
Date: 04-18-2025
Contact: fischbach.a@northeastern.edu
'''
def extract_local_csf_mask(
csf_mask_path,
threshold_roi_path,
dilated_roi_path,
csf_threshold=0.8,
save_path=None,
verbose=Tr... |
9e0dab920d0073822a8a09a9dac305c398947b6c8fdf33dc631160d12a417dec | Python | 8,560 | 192 | import numpy as numx
from scipy.signal import convolve2d
import pydeep.base.numpyextension as numxExt
from pydeep.base.activationfunction import Sigmoid
from sklearn.linear_model import LogisticRegression
class Unit_layer_binary_1D(object):
def __init__(self,
input_weight_layer,
... |
237b88c57e33c5f8f98ff05b270dc93a0fb1cbcd07a160f23b84883ef86caa41 | Python | 8,562 | 200 | # *=========================================================================
# *
# * Copyright Erasmus MC Rotterdam and contributors
# *
# * Licensed under the GNU GENERAL PUBLIC LICENSE Version 3;
# * you may not use this file except in compliance with the License.
# *
# * Unless required by applicable law or agre... |
3f8cd76769acef7e7607104772a966091ea450fdf38401f8f684f3bd674f255e | Python | 8,569 | 197 | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset
"""
In this file is presented the management of the N-Cars dataset.
The dataset is presented by a tree of directories:
-train : train part of dataset
+ cars : contains al... |
68594678b5cc78660a1c36bbbf1c16c6e7d899e75c3c33f4b9b25bf36f704972 | Python | 8,586 | 251 | import sys
import cv2
import numpy as np
from affine import Affine
from numba import jit
import json
import datetime
import platform
import os
import base64
class Field:
"""Standardized field names for embeddings and projections. These data can
all be versioned within a ColumnarData object."""
POSITION ... |
38d2cd8912010f87005f8cdd5474aa7248a5eae959f4b492fffc7e4247025961 | Python | 8,588 | 255 | # -*- coding: utf-8 -*-
"""
Created on Wed May 5 20:08:52 2021
@author: Xingyan Liu
"""
import came
from came import pipeline, pp, pl
import logging
import os
import sys
from pathlib import Path
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt # optional
import seaborn as sns # optional... |
83a96b7cea3e75f18d24bddbaace4c845a7bff2323d435647a77226e58c5b939 | Python | 8,588 | 189 | import torch
import torch.nn as nn
import logging
from .gpt_model import Block
logger = logging.getLogger(__name__)
class Bert(nn.Module):
""" the full GPT language model, with a context size of block_size """
def __init__(self, config):
super().__init__()
self.beta_params = (3, 9)
... |
d0b19a4cd889a279a32f7071d36d7ed1234ad09793478b75e0958ff948b91d3b | Python | 8,607 | 188 | import torch
from torch.distributions.distribution import Distribution
from torch.distributions import Categorical
from torch.distributions import constraints
# Taken from https://github.com/pytorch/pytorch/blob/master/torch/distributions/mixture_same_family.py
class MixtureSameFamily(Distribution):
r"""
The... |
b7ae90e1058500d4dbe748336d5c17fd0b6c4d214fec61ded46ff19bb91f9df8 | Python | 8,609 | 180 | # Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to... |
867e18d53c894a91215c7d9a51458dc51b3e9e87a1fa42f8aeb21c29228c7344 | Python | 8,623 | 220 | from __future__ import annotations
import re
import networkx as nx
import pandas as pd
from skbase.utils.dependencies import _safe_import
from pgmpy.base import DAG
from pgmpy.causal_discovery._base import BaseCausalDiscovery
litellm = _safe_import("litellm")
class LLMPairwise(BaseCausalDiscovery):
"""
LL... |
a4ac09ff96324e0dd78feeadce32bbda4cab5608437edfeca59c4b66abf6d3a0 | Python | 8,623 | 221 | import scanpy as sc
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
from pyslingshot import Slingshot
import palantir
##################################################### Utils #####################################################
def get_iroot(adata, idx_... |
61c5dc4ad377c43b2235b0db22c59c3387a5a1dd1ba5c8d9ff74396ac3071ce1 | Python | 8,626 | 264 | # coding: utf-8
""" MIT License """
'''
Project: Parenchymal Attention Network
Authors: Axel Masquelin
---------------------------------------
Functions related to pytorch dataloader and generating dataframe for dataloader.
Includes inference dataloader (InferLoader), Nrrd dataloader (NrrdLoader) an... |
577e250e439570bfba10aab1593c15e74397a58701c83bc1638c9c553185e7a8 | Python | 8,629 | 176 | import os
from copy import deepcopy
from collections import OrderedDict
from itertools import groupby
import warnings
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import matplotlib.font_manager
from matplotlib.cm import get_cmap
import scipy.stats as stats
print("- matplotlib version:", matpl... |
b6d3cbeb6b18dd397723584e6dd260db614686235612df671bd4955bea9d142f | Python | 8,632 | 192 | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 26 12:07:50 2020
@author: nishe
"""
import numpy as np
from cfc_analysis.bandpassSig import bandpassSig
from cfc_analysis.find_Hilbert import find_Hilbert
from cfc_analysis.find_MI_cfc import find_MI_cfc
#%%
class cfc(object):
def __init__(self):
"""... |
e652aba22168cadffd9f65605cb74887c06328ab1473a15c2b5f86eb1b0ddc0a | Python | 8,632 | 211 | # Visualization of DNN features (PCs) using activation maximization
# Copyright (c) 2021 Laurent Caplette
import torch
import torchvision
from torch import nn
from robustness.model_utils import make_and_restore_model
from robustness.datasets import RestrictedImageNet, ImageNet
import numpy as np
from kornia.augmentati... |
637116dce7a34a4d6284fd11e277198bae1024277f396bc849abb9c741bb5187 | Python | 8,633 | 186 | #!/usr/bin/env python
# Author: Francois Aguet
## Edited by Kynon J Benjamin (05/05/2021)
import gzip, os
import subprocess
import rnaseqnorm
import numpy as np
import pandas as pd
import argparse, feather
import scipy.stats as stats
def prepare_bed(df, bed_template_df, chr_subset=None):
bed_df = pd.merge(bed_te... |
6b47874f767984a3fe8a1e72713801eb3f9613b9b6782dd802cb29e121205d16 | Python | 8,633 | 201 | from __future__ import division
from __future__ import print_function
import os
import time
import h5py
import random
import argparse
import numpy as np
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch_geometric.data import Data
from models import *
def seed_everything(seed):
ra... |
22224ac5e4862d0c87399dc35d8bfe4ca0a0d8f8c1aabd5fa1e708053e3f7cb7 | Python | 8,647 | 203 | import argparse
import logging
import os
import random
import shutil
import sys
import time
import numpy as np
import torch
import torch.backends.cudnn as cudnn
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from tensorboardX import SummaryWriter
from torch.nn import B... |
a439d546f00f7fdf2826f9d919d127e3753c37001bb06be262168d4374e3aaca | Python | 8,651 | 260 | from abc import ABC, abstractmethod
from typing import Any, Dict, Tuple
import gymnasium as gym
import numpy as np
import torch
from bindsnet.datasets.preprocess import binary_image, crop, gray_scale, subsample
from bindsnet.encoding import Encoder, NullEncoder
class Environment(ABC):
# language=rst
"""
... |
c83118448cff41793c429ac566498033b2fd15da3e77766954e33b0cfbed435d | Python | 8,654 | 239 | """
##############################################################################
#
# Generate final MAPP report in html with jinja2 templating mechanism.
#
# AUTHOR: Maciej_Bak
# AFFILIATION: University_of_Basel
# AFFILIATION: Swiss_Institute_of_Bioinformatics
# CONTACT: wsciekly.maciek@gmail.com
# CREATE... |
959fca1da0272f7ceadaacb93c6cb76da64986548756efcb2ebbf578774d0cdb | Python | 8,661 | 269 | import os
import sys
import mmap
import time
import numba
import pickle
import argparse
import numpy as np
import multiprocessing
from skimage.morphology import remove_small_objects, remove_small_holes, ball
import adv
me = "cell_detection.py"
def stamp(s):
if Verbose:
sys.stderr.write("%s: %d: %s\n" % (... |
3877b00a1fac9b99abe3c7f4c7888b66fb3db58d4f362be6fe890f6b77b45263 | Python | 8,675 | 245 | # Copyright 2024 DeepMind Technologies Limited
#
# AlphaFold 3 source code is 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... |
fef27de5bff92021ca864b606e1a37bdb7cae1269c10b8dc247db9550e801662 | Python | 8,675 | 246 | # Jared Sagendorf
"""A simple set of methods and classes for dealing with and performing basic operations on
triangular meshes."""
# builtin modules
import os
# third party modules
import numpy as np
try:
import igl
except BaseException as E:
from ..exceptions import ExceptionModule
igl = ExceptionModule... |
e83902e0945d31cac5736d4a4d5308a8a7b1047de40e6d955e242c0f1edac1e5 | Python | 8,684 | 209 | import sys,os,gc
sys.path.insert(1, os.path.join(sys.path[0], '../../../'))
import numpy as np
import pickle
from Simulator.SimulatorPattern import simulatorPattern
from FiguresFunctions.FiguresPattern import *
import matplotlib.pyplot as plt
import argparse
import itertools
from datetime import datetime
parser = argp... |
1bd9d1b0be98e2c248853164ed609fa08a331bdb0e49ebc6b336e7451dd112e1 | Python | 8,688 | 246 | # -*- coding: utf-8 -*-
# author: Felix Repp felix.repp@mpikg.mpg.de
# !/usr/bin/env python
import networkx as nx
import scipy.optimize as op
import numpy as np
import tinanet
import matplotlib.pyplot as plt
import pdb
from scipy.ndimage import morphology as morph
"""@package tinana
%This module provides the tools to ... |
ba66326a70ddef36593c16b074bfa69a51726d4c8459debb3a651853cc6d6bcd | Python | 8,690 | 240 | #!/usr/bin/env python
"""
scanner.py -
Assemble a "feature scanner" using Aho-Corasick string matching.
This takes a list of features (byte sequences) and builds a DFA
that when run on a byte stream can identify how often each of
the features is present in a single pass over the stream.
Marco Lui, January 2... |
e9fe6c4f8f8368e346f3d9b37a3131b29db0cc29b23ac284c8f8571545be9b37 | Python | 8,691 | 268 | # builtin modules
import os.path as osp
import hashlib
from pickle import dump, load
# third party modules
import numpy as np
import torch
from torch_geometric.data import Data, InMemoryDataset
from sklearn.preprocessing import StandardScaler
# pnabind modules
from pnabind.nn.utils import balancedClassIndices
class ... |
c6b857fde78c44563172c873588ad36b5e8d7f89fba0e330c0e9a8a56d547d6b | Python | 8,693 | 215 | import itertools
import numpy as np
from functions.series import cython_upper_bessel, cython_upper_bessel_k, cython_gsl_sf_gamma, cython_gsl_sf_gamma_inc
from joblib import delayed, Parallel
NUM_CPUS = 32
def zeta_cal(v, w, vecs, vecs_inv, d, det, p=1.0, eps=1e-12):
result = sum(
np.e ** (2 * np.pi * 1... |
4281de7be635e13d77c146a02d025d9941ca7f615b0ca4479e42ee95b0bf68b1 | Python | 8,701 | 165 | import numpy as np
import pandas as pd
from sklearn.cluster import KMeans
import random
import seaborn as sns
import torch
import matplotlib.pyplot as plt
import h5py
from sklearn.preprocessing import MinMaxScaler, StandardScaler
import shap
import sys
from modal_type_list import *
import argparse
def get_shap_gene(... |
b5172c0f30942144a3964cb3996efbbf6295d76d71a9f3192c21d623f740ca7f | Python | 8,702 | 268 | import sys
import torch
import torch.nn as nn
import math
from typing import Optional, Tuple
from copy import deepcopy
from h3xsemble.model.primitives import Linear, ipa_point_weights_init_
from h3xsemble.utils.residue_constants import (
restype_rigid_group_default_frame,
restype_atom14_to_rigid_group,
rest... |
9cf365f2ce989c49b71bf1f53c24b2cc0f79f74b09efec7626215b10ca53c8cc | Python | 8,703 | 240 | from __future__ import print_function
import tensorflow as tf
from nn import linearND, linear
from mol_graph_direct_useScores import atom_fdim as adim, bond_fdim as bdim, max_nb, smiles2graph
from models import *
import math, sys, random
from optparse import OptionParser
import threading
from multiprocessing import Que... |
0fd0364a958fc42ec3f7f5cafc3cb4475f4b686135f6a9a4ae8cd0e66300ce3d | Python | 8,708 | 226 | import uncertainpy as un
import numpy as np
import matplotlib.pyplot as plt
from prettyplot import *
import os
import h5py
from scipy.stats import zscore
def compute_first_AP(t,variable,interval):
index_left = np.where(t >= interval[0])[0][0]
index_right = np.where(t >= interval[1])[0][0]
local_time = t[... |
f8fbd1299704f6ecd57fa41652ffa033aa98089b595cb539018a24513ac85e91 | Python | 8,709 | 197 | '''
***************************************************************
Author: LU
Date: Nov 2020
Description:
CNN architecture used for thalamic nuclei segmentation in
MPRAGE images.
***************************************************************
'''
# import files
import sys, os
import tensorflow as tf
from keras... |
6c6455825364a5cf95be225832614f13f08b28f62b2932ac22127eed008b0a1b | Python | 8,711 | 195 | import logging
import os
import socket
import sys
import numpy as np
import pandas as pd
from configs.configs import get_config_dict
from helpers.data import load_data
from helpers.evaluation import get_corr_matrices_tril_spearman_correlation
from helpers.evaluation import get_cov_matrices_rmse, get_corr_matrices_rms... |
94971d82b43b1722a2e081652e66da6659de9fb2172e341d2f8a71cdd7cd4330 | Python | 8,711 | 228 | ####################################################################################
#
# STEPS - STochastic Engine for Pathway Simulation
# Copyright (C) 2007-2026 Okinawa Institute of Science and Technology, Japan.
# Copyright (C) 2003-2006 University of Antwerp, Belgium.
#
# See the file AUTHORS for detai... |
9e69182b8b64bd5e1083e0fec60d49cfce7601d761a23031e57c0d1498c0a941 | Python | 8,711 | 169 | """Conformal prediction intervals for SOH regression.
Implements
split conformal (absolute-residual score, optionally scaled by a dispersion estimate) -> marginal coverage
Mondrian conformal (per-group quantile, e.g. by chemistry or dataset) -> group-conditional coverage
weighted conforma... |
b1282855a4cfcf70960e9a59b281da59e19e70af4efc7d6f22e8763985038876 | Python | 8,715 | 540 |
bohr2ang = 0.529177
# Divisor for (probe - atom) vectors before GTO radial eval (same convention as QM9).
GTO_VEC_LENGTH_SCALE_TO_AU = bohr2ang
# GTO locality mask uses raw stored coords (before / bohr2ang). QM9 stores Å → 5.0 ≈ 5 Å.
ORB_CUTOFF_ANGSTROM = 5.0
# Bohr-stored MD LMDB: same physical sphere as ORB_CUTOFF... |
c470936f14d867dec2ff304646ab8084de8b9a7b8ee70d67c76c90609ecc3124 | Python | 8,715 | 218 | from copy import deepcopy
from pathlib import Path
from typing import List, Union
import numpy as np
from omegaconf import DictConfig, ListConfig
from libs.dataset.barsignal import BarSignal
from libs.dataset.spotsignal import SpotSignal
from libs.function.cluster import ts_cluster_lib
from libs.function.function imp... |
e8720fc61a9fe7efd8a4f5ded811384b4f29acd72cb197e8352d19d99ac18169 | Python | 8,716 | 247 | # Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, so... |
365206c9d266f88cf65a8add3249acad175fd4f76cefa21a0a13310313e6f27e | Python | 8,717 | 277 | import math
import numpy as np
import h5py
import torch
from torch import nn
from torch import Tensor
import torch.optim as optim
import torch.utils.data as Data
import torch.nn.functional as F
from sklearn import metrics
from sklearn import manifold
from sklearn.cluster import KMeans
from sklearn.metrics import davies... |
d378d8201326a5c1f6326f2a797db1ec1c3f88e916dcb2ea3615f30f454f34bf | Python | 8,717 | 154 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 12 12:42:09 2020
@author: shni2598
"""
import numpy as np
#import brian2.numpy_ as np
#import matplotlib.pyplot as plt
import connection as cn
import warnings
from scipy import sparse
#from brian2.only import *
#import time
#import mydata
#import f... |
6aa0ca4d152f45b8bfddd0b3e59f48fb0c5b43f65c8640c7109d036c93c0d9d4 | Python | 8,718 | 187 | import numpy as np
import pandas as pd
import pytest
from sklearn.utils.estimator_checks import parametrize_with_checks
from pgmpy.base import ADMG
from pgmpy.causal_discovery import ANM, PC, BootstrapEstimator, HillClimbSearch
from pgmpy.causal_discovery._base import BaseCausalDiscovery
@parametrize_with_checks(
... |
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