sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
aaa708cd6f3ef1194d3117bdd5680be3233f7d778923b746d6bc75edac443273 | Python | 5,994 | 143 | # This code is part of OpenFE and is licensed under the MIT license.
# For details, see https://github.com/OpenFreeEnergy/openfe
import pytest
from gufe import AlchemicalNetwork, SolventComponent
import openfe
from openfe.setup.alchemical_network_planner import (
RBFEAlchemicalNetworkPlanner,
RHFEAlchemicalNet... |
b1e4d97c6d4103a14c986f508a3aef5a97c13af46e6c9c04095dbe9f92a8f48b | Python | 5,995 | 202 | # --- Python 标准库 ---
import os
import gc
import random
import warnings
# --- 第三方核心科学计算库 ---
import numpy as np
import pandas as pd
import scipy.stats
# --- 生物信息学与数据分析库 ---
import anndata as ad
import scanpy as sc
import seaborn as sns
import matplotlib.pyplot as plt
# --- 机器学习库 (Scikit-learn) ---
from sklearn.model... |
33f06bfb60138db2d5386d82e294890648f3f514c2d119eceebf6f0221fab67d | Python | 5,998 | 168 | import json
import re
from dataclasses import dataclass, field, InitVar
from pathlib import Path
from typing import Optional
import pandas as pd
from tbparse import SummaryReader
from .. import io
from .trial import TrialView
__all__ = ['ExperimentHandler', 'get_closest_samples']
_PATTERNS = [
r'projections/([^... |
9d480eaae104a9d862b646ee78d01277cff869e2716c2f95e688eb7c05211495 | Python | 6,001 | 154 | #####DO NOT REVIEW, CHANGES IN PATHS#####
import os
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
from nilearn.image import math_img
from nilearn.masking import apply_mask
from nilearn.glm import threshold_stats_img
from tristan_pipeline.io.params import *
from tristan_pipeline.utils.loadin... |
13a2ef2ebc79fbbf3bd63f6eb48640fe5364f2ab0e2f0c6c1e45e1a2c3f0d5ab | Python | 6,002 | 156 | """sPhysNet-Taut tautomer-selection backend (external, subprocess, Linux only).
sPhysNet-Taut (https://github.com/xiaolinpan/sPhysNet-Taut) enumerates tautomers
and ranks them by predicted aqueous free energy. It depends on the compiled
PyTorch-Geometric extension stack (torch-scatter/sparse/cluster) and ships no
expl... |
b7c1eab2f8b775d6df9351bbd7b5700e4d27704ef086aa8bc5dd51cb4b22a305 | Python | 6,002 | 162 | import os
import pathlib
from openmmtools import states
from openmmtools.states import GlobalParameterState
def serialize(item, filename: pathlib.Path):
"""
Serialize an OpenMM System, State, or Integrator.
Parameters
----------
item : System, State, or Integrator
The thing to be seriali... |
837efc5b1dfb034c7eb29fc5d806911da100875ce9423817995874a1623e2b8b | Python | 6,006 | 147 | # -*- coding: utf-8 -*-
"""
Plant Spatio-Temporal Integration Network (PSTN)
Main Training Script |
------------------------------------------------
Description:
- This script jointly optimizes cell-to-space mapping matrices (M_t)
across multiple infection stages (0h, 12h, 24h) to reconstruct spatial
transc... |
84430a2f4fc989f1d85b744a23bec81cbdec7b1f68f039c86c48e999dfeed562 | Python | 6,013 | 129 | #python motifSeqAlign.py /home/ash022/Animesh/Motif/uniprot_sprot.motif.found.seq.txtEnolase\ .csv /mnt/f/structue/
#cp -rf /mnt/f/structue/*.png /home/ash022/promec/promec/Animesh/Motif/enolase/Enolase/.
#tar cvf structures.tar /mnt/f/structue/*.png
#wget https://ftp.uniprot.org/pub/databases/uniprot/current_release/k... |
d87d34bd43da44f62aa66df1e741d818e667d7265b1fa98a3774baae4d21fa2e | Python | 6,014 | 170 | import torch
from torch import nn
import torch.nn.functional as F
from typing import Dict
class MultiOutputUnet3D(nn.Module):
"""
3D U-Net architecture supporting multiple output heads (e.g., segmentation, flow).
Adapted from Li, X. et al. Real-time denoising enables high-sensitivity fluorescence time-lap... |
edb0696dfd13dbfb181b4044de8a3a2a01f8ee3d0d1b95f4014a4c260ef8ac6d | Python | 6,017 | 188 | # Copyright (c) Facebook, Inc. and its affiliates.
# -*- coding: utf-8 -*-
import typing
from typing import Any, List
import fvcore
from fvcore.nn import activation_count, flop_count, parameter_count, parameter_count_table
from torch import nn
from detectron2.export import TracingAdapter
__all__ = [
"activation_... |
113480855e855348abd13fda3c435b1d81c4c254ed3646a22a8e5b4873fb5398 | Python | 6,020 | 170 | # Run simulations to calculate vapourisation enthalpy
# Argument is output directory and force field name
# Run with conda activate garnet
# Install garnet following instructions on garnet GitHub,
# and then install openmmforcefields in the env as well
from openmm.app import *
from openmm import *
from openmm.uni... |
4e25610e58038b39c5e93dc73d92a61b3227adad52313ba5ffd4b97a0fdc7aea | Python | 6,022 | 218 | from functools import partial
import composer.utils.dist as comp_dist
from omegaconf import DictConfig
import os
import pandas as pd
import torch
from torch.utils.data import Dataset, DataLoader
from transformers import PreTrainedTokenizer, AutoTokenizer, BatchEncoding
from typing import Dict
def build_tokenizer(cfg:... |
56f21676a0d7ece3ff18be9c9c504c5b840d726191e34e422065fa8a7d7601c2 | Python | 6,027 | 121 | from typing import Tuple
import numpy as np
from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.evaluation.evaluate_predictions import load_summary_json
from nnunetv2.paths import nnUNet_results
from nnunetv2.utilities.dataset_name_id_conversion import maybe_convert_to_dataset_name, conve... |
6110a533844aa19fc7e3c1bc741dc12cf89a1fd3f0b79d36c4653a14c7187ed0 | Python | 6,027 | 139 | import atexit
import nibabel as nii
import numpy as np
import argparse
import os
import glob
import csv
import sys # Added import statement for sys module
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir)))
from common.artifact_manifest import start_output_tracking
from common.scri... |
65af816bc9cbbaceda1c3cfc5e057db2e7aea8266183b4e20a28d89f88cb6d4f | Python | 6,028 | 186 | """Observable collection types that emit signals when modified.
This module extends Mesa's reactive programming capabilities to collection types like
lists. Observable collections emit signals when items are added, removed, or modified,
allowing other components to react to changes in the collection's contents.
The m... |
bbaecccddee234f30346a92f6a1b3ed7378fd4f05b2033bd87b8ea111c264fdf | Python | 6,028 | 216 | import contextlib
import os
import nrrd
import json
import navis
import pytest
import functools
import threading
import warnings
import numpy as np
import pandas as pd
from http.server import SimpleHTTPRequestHandler, ThreadingHTTPServer
from typing import List
from pathlib import Path
@pytest.fixture(scope="sessio... |
083b843615828417b9172ed5035bddbf34169ca30975589e2e85a2ea6c0c745e | Python | 6,035 | 158 | from astartes import train_val_test_split
from astartes.utils.warnings import NormalizationWarning
import numpy as np
import pytest
from rdkit import Chem
from chemprop.data.splitting import _unpack_astartes_result, make_split_indices
@pytest.fixture(params=[["C", "CC", "CCC", "CN", "CCN", "CCCN", "CCCCN", "CO", "CC... |
79ba852dfc114290eb9ec6c4ff376dac7d1d966f003f538f79ce20ddd13eba9a | Python | 6,037 | 131 | import argparse
import multiprocessing
import shutil
from typing import Optional
import SimpleITK as sitk
from batchgenerators.utilities.file_and_folder_operations import *
from nnunetv2.paths import nnUNet_raw
from nnunetv2.utilities.dataset_name_id_conversion import find_candidate_datasets
from nnunetv2.configuration... |
16492733113faa16b1b8ffba4b058af3433f288cc08280a295e58112d6066ae4 | Python | 6,040 | 165 | from __future__ import annotations
import os
from pathlib import Path
from typing import Any, Iterable, Optional, Sequence, Type, TypeVar
from sqlalchemy import create_engine, select
from sqlalchemy.exc import IntegrityError
from sqlalchemy.orm import joinedload, sessionmaker, Session
from hsnn.core.logger import lo... |
513697adee83829aad6dac520260c0c7ca74ba03fff201808f0c73d3b35e00ee | Python | 6,046 | 253 | from pathlib import Path
import click
import click_log
import numpy as np
from ... import io
from ..._cli.utils import catch_exception, logger
from ..._steinbock import SteinbockException
from ..._steinbock import logger as steinbock_logger
def _get_cellpose_module():
try:
from .. import cellpose as cel... |
89149aef17a76ed0d28b0d37fec543ceb9ca9a2fb9daaff2fcf336cdf954eef6 | Python | 6,066 | 151 | import pytest
import torch
from chemprop.nn.ffn import MLP, ConstrainerFFN
class TestMLPBuild:
"""Tests for MLP.build() with per-layer hidden dimensions."""
def test_legacy_single_int(self):
mlp = MLP.build(input_dim=10, output_dim=2, hidden_dim=300, n_layers=2)
x = torch.randn(4, 10)
... |
4e5acfd849fb9ed6fdfdffec7b9c04c5e590331fae691c851a6d1ad38e74df30 | Python | 6,068 | 164 | #!/usr/bin/env python
# Copyright 2016-2020 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obt... |
6eba557c4727210ca93d01089ff0a71f1cce81880151795248e35e2a55943371 | Python | 6,070 | 160 | """
Created on 10/08/2017
@author: Niklas Pallast
Neuroimaging & Neuroengineering
Department of Neurology
University Hospital Cologne
"""
from __future__ import print_function
import argparse
import os
import sys
import numpy as np
import nibabel as nib
from calendar import month_name
from datetime import datetim... |
53385c846444811718b7d41e063f128a2aabec3c68fede61b268f4ed76b2a8b2 | Python | 6,073 | 166 | #!/usr/bin/env python
import os
import pandas as pd
import numpy as np
import scanpy as sc
import scib
from scib.metrics import kBET
result_dir = "PATH_TO_OUTPUT_DIR_FOR_ALL_METRICS/"
os.makedirs(result_dir, exist_ok=True)
unintegrated_path = "PATH_TO_UNINTEGRATED_COMBINED_ADATA_H5AD"
METHODS = {
"Conos": "pca",... |
855de134e0419f9e3bd5c980c7ff32bc8b4a5f7fb050c67b0e967e7173e07a64 | Python | 6,073 | 210 | import numpy as np
import pandas as pd
import pytest
from chemprop.cli.main import main
from chemprop.cli.utils import build_MAB_data_from_files, make_dataset
from chemprop.data import MolAtomBondDatapoint, MolAtomBondDataset
# Maybe we will add a test for the normal parser in the future.
def test_MAB_parsing(data_... |
e9cb23e51440194333b6168bba0fc2800f6dbee65917ca97fcd1a9e53cbc9ab7 | Python | 6,073 | 196 | '''
(c) 2015 Brendan Bulik-Sullivan and Hilary Finucane
Iterativey re-weighted least squares.
'''
from __future__ import division
import numpy as np
import jackknife as jk
class IRWLS(object):
'''
Iteratively re-weighted least squares (FLWS).
Parameters
----------
x : np.matrix with shape (n, ... |
3d68c7fcc37c0763c42bfaf6099b4b2f5dd30710f9870b6b38d7a9e1ac18b790 | Python | 6,077 | 163 | import argparse
def main(args):
import numpy as np
import os, time, gzip, json
import glob
folder_with_pdbs_path = args.input_path
save_path = args.output_path
ca_only = args.ca_only
alpha_1 = list("ARNDCQEGHILKMFPSTWYV-")
states = len(alpha_1)
alpha_3 = ['ALA','ARG','AS... |
97736a00601ae54433fc074950b79ee661901c2fd8dc3d542ce2f5023811370c | Python | 6,077 | 73 | import argparse
def main(args):
import glob
import random
import numpy as np
import json
import itertools
with open(args.input_path, 'r') as json_file:
json_list = list(json_file)
homooligomeric_state = args.homooligomer
if homooligomeric_state == 0:
tied_lis... |
08745e572b0dcba7a42da879577f2892de4d1dc0707c155560c6d2ab7d645cfa | Python | 6,083 | 190 | """
Visualize NEURON model
======================
<!-- difficulty: advanced -->
Visualize a NEURON compartment model in 3D.
We will jump right in, so please make sure to have a look at the [introductory NEURON tutorial](../tutorial_interfaces_00_neuron)
first.
## Setup the model
!!! note "Same setup as the previous... |
e0f57fbe6a375b61e242b78c95aaadb6c8ca58fa2aac8e21538dbf6c71d6f9d6 | Python | 6,084 | 161 | from torch import nn
import torch
from models.gcl import GCL, GCL_rf, E_GCL
class AE_parent(nn.Module):
"""Graph Neural Net with global state and fixed number of nodes per graph.
Args:
hidden_dim: Number of hidden units.
num_nodes: Maximum number of nodes (for self-attentive pooling).
... |
e4040184b2b4e2653146d1d0d7f4ac0acc8809585028fd8079859ab60962b9db | Python | 6,086 | 182 | #!/usr/bin/env python
#
# Copyright (c) 2019 10X Genomics, Inc. All rights reserved.
#
"""Commonly-used constants which have not yet been organized."""
######################################################
# DO NOT add new items to this file.
#
# - If a constant is only used from a single module, put it in that modu... |
3f3ff7cc011c55bd56f0c6f1d5db2e5d3cb4884b00cf949ec972c1b837fb09cb | Python | 6,087 | 134 | ############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2019-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
############################################################################
... |
3f84cf7f87d765444f2f6683ed5e62344910fe9092065a46852ecd285761456b | Python | 6,087 | 184 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
b9619e46391dc2458f1f8cf252060514474d5ba563f2b4297b54201f58cf19a9 | Python | 6,089 | 139 | import glob
import json
import os
import shutil
import nibabel as nib
from nilearn.image import index_img
# ==============================================================================
# Fmap preparation for Caroline_Full_Dataset
# ==============================================================================
# Each... |
e0bdeba16f0b187aab3d1417618e3cd3e3de8c1d9732d843fa46bf815489488c | Python | 6,089 | 193 | ## below code is to run the LISI metric for the knn output methods (samap and bbknn)
import pandas as pd
import numpy as np
import scanpy as sc
import os
import sys
import scipy.sparse
from scipy.io import mmwrite
import itertools
import logging
import multiprocessing as mp
import pathlib
import subprocess
import tempf... |
eaa5d387b42bd8d1efa0e31a7c5f547419ad0aa9d8d878b16454e69dd5d67550 | Python | 6,093 | 182 | """Collection class for managing and querying groups of cells.
The CellCollection class provides a consistent interface for operating on multiple
cells, supporting:
- Filtering and selecting cells based on conditions
- Random cell and agent selection
- Access to contained agents
- Group operations
This is useful for ... |
6ca09b94edb115b38c19c3b311f7119d83ac3d423f012590c6e7c0fcf2281858 | Python | 6,096 | 200 | import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connected_layer import PairwiseConnected
from itertools import combinations
from keras.callbacks import EarlyStopping
# Design matrix generation from factor model
# Input:
# n: number o... |
2e65aecae0c83d7d543ee2eff57ba191b54f9b60209349efd9a4e5acd26f1fbe | Python | 6,097 | 174 | """Network-based cell space using arbitrary connection patterns.
Creates spaces where cells connect based on network relationships rather than
spatial proximity. Built on NetworkX graphs, this enables:
- Arbitrary connectivity patterns between cells
- Graph-based neighborhood definitions
- Logical rather than physical... |
5229422ee165158bc0c84dd8ab978f7c6d6bfe7f0fd6a6c6bb44813bb8c95ed7 | Python | 6,102 | 150 | import logging
from typing import Optional, List
from intervaltree import IntervalTree
logger = logging.getLogger('IsoQuant')
class GenomicIntervalIndex:
"""Interval-tree index for mapping genomic coordinates to biological entities.
Pre-builds interval trees for genes and exons to eliminate repeated databas... |
e8b0386eb0bd84e2ad334c160260231bd16ee932a262214cfb734ff8a0b6b792 | Python | 6,104 | 156 | import os
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
from nilearn import surface, plotting
import nibabel.freesurfer.io as fsio
from matplotlib.colors import ListedColormap
from tristan_pipeline.utils.plotting_utils import *
from tristan_pipeline.utils.analysis_utils import *
from trista... |
2d4880cf711a04464b7bb6798fbd435480484704ea6137a7723683fdcb6afeeb | Python | 6,117 | 189 | import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.lines import Line2D
from tristan_pipeline.utils.plotting_utils import *
from tristan_pipeline.io.params import *
spaces = ["MNI152NLin2009cAsym", "T1w", "native bold"]
for subj in subjects:
for ses in sessions:
plt.figure(figsize=... |
a2c81d1c79b2ed9fcf8bf628c36b522befd61054849385096924c2c870c0f02a | Python | 6,121 | 208 | from pathlib import Path
from typing import Any, Optional, Sequence
import matplotlib.pyplot as plt
import numpy as np
import numpy.typing as npt
import pandas as pd
from matplotlib.axes import Axes
from matplotlib.colors import Colormap
from matplotlib.figure import Figure
from mpl_toolkits.axes_grid1 import make_axe... |
11602740f5e6c5860684c7d5432bce32fa13d3f7c9d93ce57b405bbd4a8b7e5a | Python | 6,126 | 158 | """Agents for the Tram Route Model."""
import math
from mesa import Agent, Model
from mesa.experimental.mesa_signals import HasEmitters, Observable
from mesa.experimental.states import ContinuousState, Threshold
class Tram(Agent, HasEmitters):
"""A tram travelling an ordered route of station positions.
Att... |
eacc87f7bec09003efbe56958ac7db2f7d6eeae5a768f4db0a717a1f6e947c6d | Python | 6,130 | 144 | #!/usr/bin/env python3
"""Performs significance testing on detected HFBs by generating surrogate data.
This script relies on existing detections, e.g. generated by `detection.py`, and
produces results that vary with each run, being inherently non-reproducible.
The statistically significant HFBs are output to the speci... |
387ba0538a20028368a00e5a68bf96b9ea8c4b07f11c75853c3f4c0b57768aab | Python | 6,133 | 192 | #!/usr/bin/env python
#
# Copyright (c) 2016 10X Genomics, Inc. All rights reserved.
from __future__ import annotations
import json
import math
import os
import shutil
from collections import defaultdict
from typing import TYPE_CHECKING
import martian
import pandas as pd
from six import ensure_binary, ensure_str
im... |
08aded787fcafa818f946afaddf3a4661cdde447821c176e6a5076cfef18ff3c | Python | 6,138 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
4e4f2698023f3ae772a383966cdcd1ac06d0f94ed465c23e068afa55b29a50e5 | Python | 6,138 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
8b761cc8b1fd8c3793d7e1005dfc93a6983b3370b51107b26859c3871e468eb3 | Python | 6,138 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
e51369d99fb82fb7adc287dfcab3a590f571b8d992fb3e422b147476d0d7c8b2 | Python | 6,138 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
b9431a7a84a7da0213b3d3b8aed10a84c30be880588a90e42e02876b718cadcf | Python | 6,139 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
cb516ff1ca056bd01178f2ace32a42c9562a94aa7450ca529ab8b9d71ebf5237 | Python | 6,139 | 179 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/newdata1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_co... |
ca7a80a813f3a845f89b60fd40382466f8ef6a491aeb77b218fb38eddad8870f | Python | 6,148 | 154 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from typing import Any
import torch
from torch.nn import functional as F
from detectron2.structures import BitMasks, Boxes, BoxMode
from .base import IntTupleBox, make_int_box
from .to_mask import ImageSizeType
def resample_coarse_segm_tensor_to_bbo... |
960ba8e306e1c64858f905754d3997c65511b408807866517ae97e2fd2b4b0da | Python | 6,149 | 137 | import torch
import torch.nn as nn
import timm
from transformers import ViTModel, AutoModel, SwinModel
class MultiModalTransformer(nn.Module):
def __init__(self, task, img_model_name, img_modalities, with_text, cxr_pretrained=False):
super().__init__()
if 'vit' in img_model_name:
... |
b1957cc05846c953c59742eb9a0d2cbec988a1e66bb76abd107baeea111df816 | Python | 6,153 | 178 | """Fig 5A-C: Example PL and NPL raw traces, pulse rasters, and spike probability.
Usage:
python python/fig5/example_panels.py
"""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as... |
305941ea4538edf8436005ae443eeb3a27aadc47dfbfd027797eecf36cd2b3f7 | Python | 6,173 | 138 | ### variable selection in one step
import tensorflow as tf
import numpy as np
import math
# enter the current training set, the current validation set, the column indexes of current remaining variables, the weights and biases of the last network (for a warm start), and the current number of original variables and sur... |
f2da089dbcc8b098330af681b1afd108b62f92f067c0a2115ec21b849a2a3e55 | Python | 6,174 | 190 | from typing import Optional
import torch
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
from .utils.activation_manager import ActivationManager
from .utils.pgd_attack import PGDAttack, AttackParams
from .attack_examples import run_attack
from .utils.data_utils import prepare_data,... |
0ecb81d2f76984367d463aabcac43326bf8fa1b29f09612cc243118c525bd81a | Python | 6,191 | 191 | #!/usr/bin/env python
#
# Copyright (c) 2019 10X Genomics, Inc. All rights reserved.
#
#
# Determine the locations of the cell barcode, cDNA sequence, UMI, sample index.
#
from __future__ import annotations
import json
import os
from collections import OrderedDict
from cellranger.mro_types.structs import ChemistryDe... |
14557300aa74829c330553e6319934c2b907fe4841ddcff2ced2f00dc3c675d7 | Python | 6,192 | 194 |
'''This file contains functions that can be applied to calculate normalized mutual information '''
import numpy as np
import ennemi
import scipy
import math
from scipy.stats import gaussian_kde
from sklearn.metrics import mutual_info_score
from . import binning
def gaussian_mi(s1, s2, normalize=True):
"""
E... |
fd8ea7839c5e3f91003e77cf8dab28cf558555b916ca2e82e7aebfe5d6f1b0f7 | Python | 6,192 | 173 | import types
import torch
import stoic.seq_emb_models as sem
from stoic.seq_emb_models import Esm2
class DummyHFModel(torch.nn.Module):
def __init__(self, hidden_size: int = 7):
super().__init__()
self.config = types.SimpleNamespace(hidden_size=hidden_size)
self.device = torch.device("cp... |
4d3aaa576b7eaab5e5b319b209e5d3676836715b45ae4021e58eb24c0440f740 | Python | 6,194 | 208 | # -*- coding: utf-8 -*-
"""
Created on Sat Nov 26 14:37:26 2016
@author: Federico Barabas
"""
import os
import numpy as np
import matplotlib.pyplot as plt
import tifffile as tiff
import ringfinder.utils as utils
import ringfinder.tools as tools
def loadData(folder, ax, subimgPxSize, technique, mag=None):
"""
... |
be4bbf67819b014f9c0bf2b1abfa5acb84a7cf97c7e71a379846e62ebe2489be | Python | 6,199 | 170 |
import numpy as np, time, os
import pandas as pd
from tqdm import tqdm
import scipy.sparse as sp
from .utils import process_data
import torch
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.nn as nn,gc
import matplotlib.pyplot as plt
import random
from .model import SPIDER, MMDLoss, Z... |
d7264f83a72a75f5371ffcad8346d9e3f8441b88fbcdf2484142969a09787d17 | Python | 6,199 | 179 | #!/usr/bin/env python
#
# Copyright (c) 2022 10x Genomics, Inc. All rights reserved.
#
from __future__ import annotations
import json
from typing import TYPE_CHECKING
import martian
import cellranger.constants as cr_constants
import cellranger.h5_constants as h5_constants
import cellranger.matrix as cr_matrix
impor... |
f7d4516748b62c29bbf281c19ae1ba1f109219820c00ee4fc88ceee651ccb092 | Python | 6,201 | 156 | import torch
from nnunetv2.training.loss.dice import SoftDiceLoss, MemoryEfficientSoftDiceLoss
from nnunetv2.training.loss.robust_ce_loss import RobustCrossEntropyLoss, TopKLoss
from nnunetv2.utilities.helpers import softmax_helper_dim1
from torch import nn
class DC_and_CE_loss(nn.Module):
def __init__(self, soft... |
0eeb7da8f816792fa305a8a5e9b8dd31307869da3f23e11d0075c4530eaa178a | Python | 6,202 | 161 | from typing import Mapping
from omegaconf import OmegaConf
from pathlib import Path
import pandas as pd
import xarray as xr
from .trial import TrialView, CheckpointView
from . import artifacts
from .. import io
__all__ = ["ArtifactStore"]
_ARTIFACT_EXT_MAPPING = {
'results': '.pkl.gz',
'config': '.yaml',
... |
2f1d7df3951dbb3c01322c96d8b3b12e4bf4e091c8ceda59cb265f5fdc7b46ae | Python | 6,202 | 177 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Panoptic-DeepLab Training Script.
This script is a simplified version of the training script in detectron2/tools.
"""
import os
import torch
import detectron2.data.transforms as T
from detectron2.checkpoint import DetectionCheckpointer
fro... |
9a9e20b0c06d032ee4c88674a7181357a5aff3df4b0c50a2f12cc2d33cd8cf14 | Python | 6,202 | 160 | # -*- coding: utf-8 -*-
"""
Created on Mon May 20 17:10:56 2024
@author: ronsun
"""
import pandas as pd
import numpy as np
import h5py
import os
from pathlib import Path
from allensdk.core.reference_space_cache import ReferenceSpaceCache
from abc_atlas_access.abc_atlas_cache.abc_project_cache import Abc... |
a0ffa838b8fde1c272f99166952fd5780321f644b88971eb06542beb1764092d | Python | 6,203 | 191 | #!/usr/bin/env python3
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# Copyright (c) 2020-2022 Saint Petersburg State University
# # All Rights Reserved
# See file LICENSE for details.
######################################################... |
69efac377e3b1462bef5b087b7b6228864ee9d4c95a206d4f0de3711439c387b | Python | 6,210 | 196 | """This integration test is designed to ensure that the chemprop model can _overfit_ the training
data. A small enough dataset should be memorizable by even a moderately sized model, so this test
should generally pass."""
from lightning import pytorch as pl
import pytest
from torch.utils.data import DataLoader
from c... |
dddc33f35c3c3bf564813bc3014401f626aee9472aa5b7ee416645bc803c1157 | Python | 6,212 | 120 |
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
import os
from collections import namedtuple
import pytest
... |
d765c41f245ca59fb3ed91e86f5ae2c1330f5df4f929db7631d07aacc6ef445d | Python | 6,224 | 205 | from unittest.mock import MagicMock, call
import numpy as np
import pytest
from rdkit import Chem
from sklearn.preprocessing import StandardScaler
from chemprop.data.datapoints import LazyMoleculeDatapoint, MoleculeDatapoint
from chemprop.data.datasets import CuikmolmakerDataset, MoleculeDataset
from chemprop.data.mo... |
db32cb05814482a6b8747f1f1c5c0a038b349bc7fef8910a8ca5bc331b7c608c | Python | 6,236 | 148 | import os
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
import numpy as np
import tifffile
from skimage import io
from nnunetv2.imageio.natural_image_reader_writer import NaturalImage2DIO
from nnunetv2.imageio.reader_writer_registry import determine_reader_writer_from_file_ending
fr... |
922e5b8292aeec055e16586333de35b8252a022a67227d52eafe200484473eb3 | Python | 6,241 | 201 |
""" Abdomen datasets """
__author__ = "Fabi Bongratz"
__email__ = "fabi.bongratz@gmail.com"
import os
from typing import Union, Sequence
from enum import IntEnum
from data.image_and_mesh_dataset import ImageAndMeshDataset
from utils.modes import DataModes
from utils.utils import global_clip_and_zscore_norm
from log... |
bee0d5f5a4541e62ff353eea2ac40e7f92cf0930a254b00acb606aefedb62772 | Python | 6,241 | 137 | from collections import defaultdict
from csv import DictReader, reader as TupleReader
from pathlib import Path
from typing import Dict, List, Any
import warnings
from taming.data.annotated_objects_dataset import AnnotatedObjectsDataset
from taming.data.helper_types import Annotation, Category
from tqdm import tqdm
OP... |
9f14547f13a3122e518d1d26dbef88b9c518cdb06514352275211c71ac4f1ecb | Python | 6,247 | 163 | # This script is part of navis (http://www.github.com/navis-org/navis).
# Copyright (C) 2018 Philipp Schlegel
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of... |
6c6e22be501715381f3c98901c59d0fbc78184e25536aad152fa18cdfb007ffe | Python | 6,254 | 167 |
############################################################################
# Copyright (c) 2022-2026 University of Helsinki
# All Rights Reserved
# See file LICENSE for details.
############################################################################
#!/usr/bin/env python3
import argparse
import numpy as np
... |
c56042b8c98cc491c0515f47c0796c07d3cbb8c471ec40e54864d165c2866380 | Python | 6,254 | 177 | #!/usr/bin/env python3
#
# Copyright (c) 2016 10x Genomics, Inc. All rights reserved.
#
"""Shell interface for docopt, the CLI description language.
Usage:
docopts [options] -h <msg> : [<argv>...]
Options:
-h <msg>, --help=<msg> The help message in docopt format.
If - is gi... |
fa49cf75f5df88bb22a4b1559b51bca82fcea2dc4bdc196502edd2a54901d060 | Python | 6,254 | 127 | # Copyright (c) Facebook, Inc. and its affiliates.
from typing import List
import torch
from detectron2.layers import nonzero_tuple
# TODO: the name is too general
class Matcher:
"""
This class assigns to each predicted "element" (e.g., a box) a ground-truth
element. Each predicted element will have exac... |
1b00e8759b49d88ad5c098aee68454c9c018e7d56596c36199255b0abc053260 | Python | 6,258 | 205 | from typing import Optional
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from itertools import product
from tqdm import tqdm
from .utils import aggregate_chisquare_test, false_discovery_rate, percent_change
class CShift:
"""
A method of performing cluster enrich... |
951c8241cf8514b15908f3be7569f95f03069d75787c12cf1cadcacb118d9f74 | Python | 6,260 | 192 | """ Test vtk wrapping interface """
import pytest
import numpy as np
import vtk
from vtk.util.vtkConstants import VTK_TRIANGLE, VTK_LINE, VTK_VERTEX
from brainspace.vtk_interface import checks, wrap_vtk, is_wrapper, is_vtk
from brainspace.vtk_interface.pipeline import serial_connect
from brainspace.vtk_interface.wr... |
1923f0bd723c99db0e38e3249b4009109f800ac6dbd3e091e8264a609d6b66f3 | Python | 6,263 | 126 | #https://towardsdatascience.com/learn-how-to-quickly-create-uis-in-python-a97ae1394d5 follow with PyInstaller ?
#!pip install PySimpleGUI
import sys
from pathlib import Path
if len(sys.argv)!=2: sys.exit("USAGE: python dePepGUI.py <path to tab-sep-peptide-hits>, \n e.g.,\npython dePepGUI.py L:/promec/Elite/LARS/2021... |
7b08eed32be62a72b750956933bbdaed2a79d826b9a89b18357bb4e264da7df8 | Python | 6,270 | 143 | # Copyright (c) Facebook, Inc. and its affiliates.
import logging
import os
import pickle
from urllib.parse import parse_qs, urlparse
import torch
from fvcore.common.checkpoint import Checkpointer
from torch.nn.parallel import DistributedDataParallel
import detectron2.utils.comm as comm
from detectron2.utils.file_io i... |
b9af9a03d6f403e940557a895428c931d2683a4c8c3410fbc2485b2f4eac0a26 | Python | 6,273 | 146 | from matplotlib import pyplot as plt
import numpy as np
import os
import pickle
from scipy.interpolate import interp1d
import re
from scipy.optimize import minimize
from rCPGswCPG.utils.gen_utils import get_project_root
import matplotlib as mpl
mpl.use('MacOSX') # on macOS built-in backend
# mpl.use('QtAgg') # if you... |
229ed93ea2d6f62024f6984efa9bc9775cedffa5d4dbc7031b53065cfae165a9 | Python | 6,275 | 183 | from typing import List, Optional
import numpy as np
import numpy.typing as npt
import xarray as xr
import sparse
from ._base import assert_recording
from hsnn.core import SpikeRecord
from hsnn.core.types import SpikeEvents, SpikeTrains, FiringRates
__all__ = [
"spike_trains_to_events",
"spike_events_to_trai... |
b9ea4791ef28d54cc2b000e762d7c4e221341e10217feeb240e4b10d20f938fd | Python | 6,280 | 179 | '''
Created on 20.08.2020
Author:
Michael Diedenhofen
Max Planck Institute for Metabolism Research, Cologne
'''
from __future__ import print_function
try:
zrange = xrange
except NameError:
zrange = range
import os
import sys
import numpy as np
import nibabel as nib
import proc_tools as pt
def create_rois... |
3768fd1e011570c70d4f3af3f6e70ef31f0f03e216334bd862ead90627266882 | Python | 6,286 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
7cdd463c5d4264f070e53d2edd11ddfc7ab2aea1e37c02a3dff7b713ea1b66d7 | Python | 6,286 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
a1d9795cdd817eb29c09be941cb9c04c7bc5d252047ad8add8fbf9d46d204443 | Python | 6,286 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
abb01689b5db753cb5cce91e389cc2889996aee8574e5d07a87f3c88b985a19c | Python | 6,286 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
1ae2f1458bee0df26a36115af59bc0e6d86246510b03a71f152de1282939b2fc | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
2aca064ab4df9207091832086b62eb5d9492575507e6860ab7b708c3300166a9 | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
3cebda2706910a2d80a783e37bdd7d6d4ae6448bac65471dfbff1b69dc7e3aba | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
7e3fe46b82f2a6b9476b231410d8a664aac02b6076a00d7b9a76c4923413310a | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
a22cbe555e954a2333bc362568f7d3bda9d9be4aecf3a5e02ea2a6f54e84c7cd | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
cc811487b491ce5db0df11666ac6d0946d818072f9f6596a1a2dbb10838e361d | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
e115b510b03c0f2628c5d670e7e2231ad210dbd7388d3bd945b240ebea7139d1 | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
ed5537466493819e67fc4018f6de77c6c7f0c368c7c98e64cc6c95d3097bc9ee | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
faefa3cec1247894030b25df9077f48d47cb0f3099c8595c6247da9f98dc4499 | Python | 6,287 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna2')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
12a31f819e242360c0b10016203b3389ed949e290e115d6dffa4df0db5ada863 | Python | 6,288 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
8b27bb79c2d467748cf037d69861bbdcdb0af031a941a027301e860208bb918c | Python | 6,288 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
b449296b97c758689a45666481c75ada30f92b109c57b5d6c3867926c62e727a | Python | 6,288 | 183 | import os
# os.chdir('/Users/yikong/Dropbox (CSU Fullerton)/aResearch/DeepPINK/Documents_2020.07.04_1/real_data')
os.chdir('/home/yinfeiko/DeepLINK/rna1')
import random
import DeepLINK as dl
import numpy as np
import keras
from keras.layers import Dense, Dropout
from keras.models import Sequential
from pairwise_connec... |
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