sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a1095997bea941d1180906b7afa4a04d7057a56583ef14797458ca261079c138 | Python | 13,629 | 295 | """
This file evaluate the testing dataset for the SPLAM model.
Parameters:
MODEL_VERSION : the version of the model.
Input directory : "./INPUTS/"+SEQ_LEN+"bp/input_pos/"
Output directory: "../src_tools_evaluation/splam_result/"+MODEL_VERSION+"/"
"""
import os, sys
sys.path.append(os.path.dirname(os.p... |
c3c57b6c25a0d42517e4ad49687ad1f2d7d06922bdcc6f587c50fedf37f1c33b | Python | 13,630 | 435 | import os
import pandas as pd
import datetime
import numpy as np
from joblib import Parallel, delayed
import torch
from torch import nn
from torch.utils.data import DataLoader
from torch.optim import Adam
from hyperopt import hp
import ray
from ray import tune
from ray.tune.schedulers import AsyncHyperBandScheduler
f... |
99260c9aeb9ec300068a9834cc32c17159999a5743d46eda291cd50128dec877 | Python | 13,632 | 299 | import argparse
import pickle
from typing import Dict, List
import numpy as np
import torch
import tqdm
import lib.data_utils.data_util as du
import lib.data_utils.dynamic_data_util as ddu
import lib.dataset_config_parser.dataset_config_parser as dcp
from generate_cropped_glm_hqs_reconstructions import make_glm_stim_... |
56a44effe653ac21a985438d98301463971ad587415f59bbe6fe4c192d4f2c93 | Python | 13,636 | 347 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import spectral_norm
from torch.optim import Adam
import math
import numpy as np
from utils import *
from lookahead import Lookahead
class SelfAttention(nn.Module):
def __init__(self, hid_dim, n_heads, dropout, device):
... |
86c84b508f8c7247c47c268891b668af57ffb539f3ad94f0836a7a795ff48ff0 | Python | 13,654 | 288 | ''' Unit testing
'''
__author__ = "Jonathan Dan"
__email__ = "jonathan.dan at epfl.ch"
import unittest
import numpy as np
from src.timescoring.annotations import Annotation
from src.timescoring import scoring
class TestAnnotation(unittest.TestCase):
def assertListOfTupleEqual(expected, actual, message):
... |
a4c681b970be08a3ce784cd53ffd6f5f96fce3496b1fc6c0625ee3fe080e8cac | Python | 13,660 | 401 | #!/usr/bin/python
# -*- coding: iso-8859-15 -*-
# System imports
import sys, os, re, math
import subprocess
import argparse
import numpy as np
import seaborn as sns
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.font_manager
from matplotlib.ticker import PercentFormatter
from... |
9967ed0e694c7a36ff5b07252cf9a39b6ce33ca15095eb39233778865fba6f90 | Python | 13,661 | 388 | from subprocess import Popen, PIPE
import numpy as np
import itertools
import re
def view( infile, *args, **kwargs ):
'''
A simple wrapper around samtools view command that will just return the stdout iterator
The command should accept the same arguments as samtools view except that any single argu... |
9f403ec6815df43cc1bae4eafe621c4a29daf684f0f111d4d89a7b36047c78dc | Python | 13,662 | 361 | import copy
import numpy as np
from spinnaker2.mla import conv2d
params_conv = {
"op_a_use_noc": 1,
"op_a_is_signed": 1,
"op_b_is_signed": 0,
"op_a_is_16bit": 0,
"op_b_is_16bit": 0,
"output_shift_width": 8,
"output_mode": 0, # only tested for 32 bit output
... |
97844421b7c932fe29c41aff07a95d4ca10e4f15e50f3c55d840aa332148abdf | Python | 13,664 | 383 | #%%
# -*- coding: utf-8 -*-
"""
Created on Tue Sep 12 13:22:36 2023
@author: meaha
"""
import seaborn as sns
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from scipy import stats
from scikit_posthocs import posthoc_dunn
from scikit_posthocs import posthoc_tukey
from statannotations.Annotator ... |
2971424c66b70346667dea8a72999329bc6e705387cbf6f25d43ad23be263b72 | Python | 13,672 | 394 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 15 20:10:37 2021
This script is for de novo generation of novel antimicrobial peptides.
The RNN language model was adapted from the pytorch tutorial "NLP from
scratch: generating names with a character-level RNN" by Sean Robertson.
(https://pytorc... |
5d7febfc8dadc2fd8f4b4e6d6a0df502ea655cb786dd10fbe21102cc8bf7a404 | Python | 13,682 | 396 | # Copyright 2021 AlQuraishi Laboratory
#
# 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 i... |
82f02ab0559119ef3e0e2ad8b18d39cbee3f0c28cb79575e3e8a5887c9bf40b4 | Python | 13,687 | 396 | # Copyright 2021 AlQuraishi Laboratory
#
# 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 i... |
bd8f8b755b7fac874d47d6d5ccb73b054ccdcb7e05f6a635f3f7fccb59d0bcab | Python | 13,688 | 339 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
06ecbeedf2f963cd1d7b5210c1842876c2e9d72bb84b9e0413871a7ceb5d2574 | Python | 13,689 | 348 | # Ultralytics YOLO 🚀, GPL-3.0 license
"""
Ultralytics Results, Boxes and Masks classes for handling inference results
Usage: See https://docs.ultralytics.com/predict/
"""
from copy import deepcopy
from functools import lru_cache
import numpy as np
import torch
import torchvision.transforms.functional as F
from ult... |
b95238cb81c047b95bf4c573421be762316e3d664ad084f1c7bc51bd64fffc5e | Python | 13,690 | 367 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
6b3bd358e0b5dee35b714b0b79a6e11a244c69bb4475d2e87ef0fb9f5c583972 | Python | 13,691 | 393 | """Code in this file is heavily based on the code from the following repository: https://github.com/CompVis/invariances"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import BatchNorm2d
class DenseEncoderLayer(nn.Module):
def __init__(self, scale, spatial_size, out_size, in_c... |
36bfc711c4171e41aaf37d805225a44dbd6ae4c217d8c86d3c64339f15f6aac4 | Python | 13,692 | 471 | """
For historical reasons, this script generates two separate plots which were
combined in inkscape.
"""
from utils.grid_funcs import (
gridpop_clustering,
gridpop_conj,
gridpop_repsupp,
gen_offsets,
traj,
traj_pwl
)
from utils.utils import (
convert_to_rhombus,
get_hexsym,
get_pat... |
2d30c2d224ea252c612a4cdc891d430bc34600d75b1d74e3696642f2445fc752 | Python | 13,695 | 408 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
8bc94f182e53809a4cff4a5fb592cb20e9be7f1c310922e13bd171bd47bc74bb | Python | 13,695 | 353 | """
The intention of this script is to easily sync a given IonTorrent or IonProton run path into the :doc:`NGSData <../ngsdata>` structure
You need to ensure that the run directory for the run you want to sync is available and that you know the path to it.
The run directores for IonTorrent and IonProton are located u... |
4dbda6192ec5b337c2ebc7e68991d6b345cbddc497806e428503c96b60bf1ba1 | Python | 13,696 | 398 | #!/usr/bin/env python3
#
# Copyright 2021 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... |
5d8c67f42b3858809a54c46954cfaa13d406c710f820d45fab834ceb8653dda3 | Python | 13,700 | 321 | r"""FCS (Flow Cytometry Standard) reader for OmicVerse I/O.
WHY THIS LIVES IN ``ov.io``
---------------------------
Reading an FCS file is I/O, not an assay. The only FCS reader omicverse had was
``ov.single.ev.read_fcs``, buried inside the single-extracellular-vesicle
module, and it was shaped for that assay: it stam... |
b7e52a8682aa81fbeecccac83e6fb0d57bb83667fc009d88216cd1bc19752cdd | Python | 13,701 | 365 |
# coding: utf-8
# In[18]:
import csv
import pandas as pd
import numpy as np
import os as os
import sys as sys
from collections import defaultdict
import time
from IPython.display import display
import copy
import traceback
# In[2]:
from datetime import datetime
now = datetime.now()
current_time = now.strftime... |
fbae16e483f1c7aa19f8d5e007b3fb78bf54fd7cf660a1d1f76a721457133ca9 | Python | 13,703 | 352 | import os
import torch
import time
import argparse
import numpy as np
from torch.utils.data import DataLoader
from torch.optim import lr_scheduler
from data_preprocessing import ABUSsetNew
import logging
from config import CFG
from monai.utils import set_determinism
from sklearn.metrics import roc_auc_score
classes=[... |
97cb401e453307cd4323ebe4a1d2d89f670dc983461bf5596fe9d337625b9084 | Python | 13,704 | 426 | ####################################################################################################
# Copyright (c) 2020 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
1ad6e9a8642286bbd4fd3155dbb80e278adfaa160b9bcd92f436d99abae07bec | Python | 13,706 | 346 | r"""Tissue-zone / cellular-compartment discovery via NMF.
After a spatial deconvolver (Cell2location, Tangram, SpatialDWLS, ...)
writes a per-spot cell-type abundance matrix, a common follow-up is to
ask *which groups of cell types co-locate?* That answer becomes
**tissue zones** (germinal centre, T-cell zone, stromal... |
a9d190c32a5b16496fb53fd8b02229d78e81fb8e8edce2abd533511cc5c0308f | Python | 13,707 | 398 | import argparse, os, sys, glob
import clip
import torch
import torch.nn as nn
import numpy as np
from omegaconf import OmegaConf
from PIL import Image
from tqdm import tqdm, trange
from itertools import islice
from einops import rearrange, repeat
from torchvision.utils import make_grid
import scann
import time
from mul... |
dee0faeee2f75a3aee997e64b60f16b5aed6aac40ff1fe0f88e0ac39a2ffd9b3 | Python | 13,708 | 371 | # -*- coding: utf-8 -*-
r"""Co-located cell combination model - de-novo factorisation of cell type density using sklearn NMF."""
import matplotlib
import matplotlib.pyplot as plt
# +
import numpy as np
import pandas as pd
from ...models.base.base_model import BaseModel
# defining the model itself
class CoLocatedGr... |
837ddbe0f80a612b96398f94cbd5d04a82be28c16d9566e015712190da7c74da | Python | 13,713 | 366 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import contextlib
import itertools
import tempfile
import zipfile
from collections.abc import Generator, Iterable, Iterator, Sequence
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from ... |
c9f429951edaecd744c86a75732719ecc1230b5a9716a73c91afe486a060769f | Python | 13,714 | 317 | r"""Regulatory-element strength & expression prediction.
Predict how strongly a construct is transcribed and translated, from sequence:
* :func:`rbs_strength` — translation-initiation rate from a 5'UTR, via a
thermodynamic model (Salis-style): the Shine–Dalgarno : anti-SD (16S rRNA)
hybridisation energy minus the... |
3367d435ace14999793c493c2c13957b69da900d4623288d604fabccbeba2026 | Python | 13,717 | 304 | """R CellChat pipeline steps around ``computeCommunProb`` (OmicVerse port).
Each function ports the R function named in its docstring from
jinworks/CellChat 2.2.0 (presto 1.1.0 for the Wilcoxon test, igraph/sna for
centrality) and is checked numerically against R in
``tests/single/test_cellchat.py``. Communication ten... |
77e082e9ceb26ded46a829042b5cff284addf5efe09c07b10f5fed1b331098a9 | Python | 13,717 | 239 | from nilearn.connectome import ConnectivityMeasure
from sklearn.covariance import LedoitWolf, EmpiricalCovariance
import numpy as np
import pandas as pd
from neuroCombat import neuroCombat
import matplotlib.pyplot as plt
import seaborn as sns
def connectivity_matrix(timeseries,
roilabelid=[],
... |
2e6977689106a334db693c929754794a11c6065db0d77beb9fda1707f90557f2 | Python | 13,719 | 324 | from mozaik.storage.queries import *
import pylab
import math
from scipy.interpolate import griddata
import matplotlib.cm as cm
from mozaik.meta_workflow.analysis import load_fixed_parameter_set_parameter_search
from collections import OrderedDict
import pickle
from builtins import zip
def single_value_visuali... |
0128f9625b8567c00c6c2800a0032211f97ca16d698fa45e64e8eff58f6659ce | Python | 13,734 | 357 | import unittest
import numpy as np
import pytest
import torch
from pfrl import action_value
from pfrl.testing import torch_assert_allclose
assertions = unittest.TestCase("__init__")
class TestDiscreteActionValue:
@pytest.fixture(autouse=True)
def setUp(self):
self.batch_size = 30
self.actio... |
08a89652e4ebf6ee77e7c421820f5dcd7d6b212d97a2c61a70b2e1d90dfbbe79 | Python | 13,735 | 334 | import argparse
from utils.utils import load_data, define_logger, tokenize_gen, evaluate_gpt2, gpt2_evaluate, compute_ppl
import random
import numpy as np
import torch
from model.generatively_model import gpt2_generate, bart_generate
from transformers import AdamW, GPT2LMHeadModel, GPT2Tokenizer
import sys
import torch... |
3b99c6c953f5743bb968dc9c52caa4e1d14b9c13bb1207f05e7996b21762cc27 | Python | 13,736 | 364 | import numpy as np
#import matplotlib.pyplot as plt
import os
import struct
import gzip
import pickle
from sklearn.cluster import KMeans
from sklearn.mixture import GaussianMixture
import scipy.io
def format_float(num):
return np.format_float_positional(num, trim='-')
def download():
'''
From http://ufldl... |
203e1fb3e1a6f4d9ef4591ccc24b7fe91dbf395c888a34cf64cb2e90533ff7b9 | Python | 13,739 | 350 | import numpy as np
import nibabel as nib
import json
import argparse
import os
from os import makedirs
from os.path import isdir, splitext
import matplotlib.pyplot as plt
from skimage.measure import label, regionprops
from scipy.ndimage import binary_dilation
import lib
__scriptname__ = 'idif'
__version__ = '0.3.2'
... |
f749067a79bcc2a0196364b653a7f1f090be7ad2c64fbc332bb0efbbc6ac74e9 | Python | 13,739 | 347 | import math
from typing import Callable, Dict, List, Set, Tuple
import numpy as np
from rdkit import Chem
from GR_pKa.args import InterpretArgs
from GR_pKa.data import get_data_from_smiles, get_header, get_smiles, MoleculeDataLoader, MoleculeDataset
from GR_pKa.train import predict
from GR_pKa.utils import load_args,... |
c6c0df15b7cf544efe7d3770cfa23cee61b090e88b30654914b1ffbf49e463b4 | Python | 13,742 | 354 | import os
from progress.bar import Bar
import numpy as np
import pandas as pd
from pyfaidx import Fasta
import itertools
'''Run all parts in sequence'''
def run_all(db_name, overwrite_all=False):
types = ['noN', 'N']
versions = [1, 2, 3, 4, 5]
print('AGGREGATING SPLAM DATA...')
splam_aggregator(db_na... |
2546a4cfd2dd4f9caf6dba1bb2ce41c6a805c03279d09c4bb794e032a8a0fa87 | Python | 13,743 | 350 | # coding=utf-8
# Copyright 2023 HuggingFace 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 ag... |
6879b9f1458633176cec14d2231b6ebe0c33e88e7bc605555a50de8990cfe010 | Python | 13,744 | 382 | ####################################################################################################
# Copyright (c) 2020, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This library is free softw... |
2cacf516beee6ca480f8ab3b5e8f8a4301d7b23a96ffc430ad8f3f78d6a86ec6 | Python | 13,747 | 338 | """Self-contained enrichment plots — the running-ES GSEA curve, dot-plot and
bar-plot used by :mod:`omicverse.bulk` enrichment.
These were previously imported from the vendored ``gseapy`` package
(``omicverse.external.gseapy.plot``). gseapy has been removed in favour of
omicverse's own NumPy GSEA/ORA backends (:mod:`o... |
4548642627ede1e166182a38d8845d879ca5412aa75510bb933e65a64fac4dc6 | Python | 13,752 | 313 | import logging as log
import pandas as pd
import numpy as np
import numbers
from matplotlib import pyplot as plt
from sklearn.model_selection import KFold, ParameterGrid, ParameterSampler
from sklearn.metrics import mean_squared_error
from sklearn.feature_selection import RFECV
from sklearn.utils.multiclass import type... |
a094dc2a3ed4dd071afef93b9339142e094a838ce4a5bf025851dbd8ea58fb3c | Python | 13,755 | 266 | from numpy import *
intro = "This subroutine evaluates the "
pgstr = ["potential ", "potential and its gradient "]
intro2 = "\n\n .. math::\n\n"
eq_start = "u(x) = "
eq_start2 = "\sum_{j=1}^{N} "
str1 = "c_{j} \\frac{e^{ik\|x- x_{j}\|}}{\|x-x_{j}\|}"
str2 = "v_{j} \cdot \\nabla \\left( \\frac{e^{ik\|x-x_{j}\|}}{\|x-... |
34b90449d71d3957112d6771b53ac3dd39eedcc372aa8d7a085b623c1d5016cc | Python | 13,756 | 372 | from typing import Dict, List, Sequence, Union, Tuple, Optional
import torch
import torch.distributed.distributed_c10d as dist
import torch.nn as nn
from monai.networks.blocks import SubpixelUpsample
from monai.networks.layers import Act
from torch.nn import functional as F
from src.networks.vqvae.vqvae import VQVAEB... |
84e4ebf041ab98b64adfcdd91ac019044ebd10ab6712f6adf6a05b93bccfb284 | Python | 13,757 | 382 | from typing import Optional, Dict
import scanpy as sc
import networkx as nx
import numpy as np
import pandas as pd
import anndata as ad
import networkx as nx
def filter_low_confidence_edges(adata: sc.AnnData,
edge_threshold: float,
flowsig_network_key: ... |
f44da722c0a70c923b07b5db2ce8e1d894214168092afc78228279729d02b426 | Python | 13,757 | 474 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
964a01ef1ac06623361ea71bb2e0d767909ed30200ff31c9ac8919c481933ad0 | Python | 13,764 | 388 | import os
import time
import random
import numpy as np
import torch.utils.data as data
import torch
import threading
import queue
from dataclasses import dataclass, field
from typing import Any
import torchvision.transforms as transforms
@dataclass(order=True)
class PrioritizedItem:
priority: int
... |
4121976deb78d367a01fcb320d9da49c7cc8bcfaeadfabff667ba6c9d462730d | Python | 13,768 | 400 | ###RF1-SRA
###shared reward, event related
from psychopy import visual, core, event, gui, data, sound, logging
import csv
import datetime
import random
import numpy
import os
#maindir = os.getcwd()
#parameters
useFullScreen = True
useDualScreen=2
DEBUG = False
frame_rate=1
instruct_dur=3
initial_fixation_dur = 4
#... |
1707747065a6cf4e7cfb00997272081208661ec2de6394bb080c59edc786a98d | Python | 13,772 | 375 | """A Python class containing an implimentation of MPPCA denoising.
Inputs are a 4D image with dimentions (X x Y x Z x N)
Usage:
import mpdenoise as mp
imgdn, sigma, nparameters = mp.denoise(img, kernel=[7,7,7], M=60, shrinkage='frobenius')
LICENCE
Authors: Benjamin Ades-Aron (... |
f7d31c09f4d93d791e76f67a4c577b8acdd0c9bde9762790920c4c73ed9590f1 | Python | 13,773 | 370 | #!/usr/bin/env python
import argparse
import os
import sys
import subprocess
import dxpy
ENCODE_DNA_ME_PROJECT_NAME = 'long-rna-seq-pipeline'
''' This DNA Nexus project holds all the created applets and folders'''
ENCODE_REFERENCES_PROJECT = 'ENCODE Reference Files'
''' This DNA Nexus project holds Reference files ... |
f4894b71e3288ce0df84b78481f9a081281e742ba202ee56ade5b62377ad3809 | Python | 13,777 | 354 | # Copyright (c) 2020-2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are permitted
# provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright notice, this list of
# ... |
ead0c2e44585ca475c5e56da1f6a6e827b33eefcc08fe3b66d6636e1a58c4756 | Python | 13,782 | 319 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
# Adrien Fleury <adrien.fleury@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.co... |
ca25b3a3e75461ea03fc1a9b8492733a6dccf46bfc2a4b91d48ed03586461982 | Python | 13,785 | 331 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
FastCSP - Fast Crystal Structure Prediction Workflow
This module provides the main orchestration script for the FastCSP (Fast Crystal Structur... |
606ab8a5f155ebf15996d7f981d2a85e89dbf9c6c45622d8bf513b6f4f16ea67 | Python | 13,789 | 345 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for Bio-Diffusion (https://github.com/BioinfoMachineLearning/bio-diffusion):
# --------------------------------------------------------------------------------... |
e64bd231cc97d212f8b3a0daec0696eb7d0e61e667cc964d4b4872d13aa961b8 | Python | 13,795 | 373 |
from typing import List, Tuple
import numpy as np
from torch import Tensor
import torch, copy, math
import torch.nn as nn
from torch.nn.functional import log_softmax
from ..utils.model_utils import Feature_extract, Embeddings, PositionalEncoding
"""
Generate mask for padding position and causal mask
"""
def subseque... |
113bd128df0804878c176e7ab1081decf1cb9ef0cbb1d4c308c6afa07ce8355b | Python | 13,798 | 350 | # Copyright 2026 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
d5c9e640d311b251ea4a7dc069f059984c35939cee9b83a8da02f26d8d75550f | Python | 13,802 | 461 | """Utility functions for tensors and arrays."""
from typing import Any, Dict, Iterable, List, Literal, Mapping, Union
import numpy as np
import torch
from numpy.typing import NDArray
from torch import nn
class RefTensor:
"""A tensor with reference indices along the last dimension.
Attributes:
value... |
4b68b7342f22fd80fdec4e6f2fa0b2f1db84771309d6bad4130fa0262177f280 | Python | 13,810 | 221 | import collections
import os
import pickle
import random
import struct
import sys
import zipfile
import numpy as np
def remove_low_intensity_peaks(array, removal_threshold, removal_percentage):
candidate_indices = np.where(np.logical_and(array > 0.0001, array <= removal_threshold))[0]
indices_to_remove = np.r... |
84e206fbe29521808b1ea7f979b235271dd685a33f8e9251ada3bf02d51c80fe | Python | 13,811 | 513 | import numpy as np
import matplotlib.pyplot as plt
import glob
from pyboat import WAnalyzer
def gaussian(x, mu, sigma):
return np.exp(-0.5*((x-mu)/sigma)**2)
# 1. Retrieve info from file names
def get_file_names():
data_dir = './RAFL_data/'
return np.array(glob.glob(data_dir+'*.txt'))
... |
79120b38865e090f75d539cab8b214dcd92db6446e6218e128c929f35c7e1128 | Python | 13,816 | 353 |
import scanpy as sc
import numpy as np
import networkx as nx
from community import community_louvain
from sklearn.ensemble import IsolationForest, RandomForestClassifier
from sklearn.decomposition import PCA
from collections import Counter
from scipy.spatial.distance import pdist, squareform
from tqdm import ... |
38b1faf8ad48afb8eac9b1f325e11ed50544e6e350b0ac2d1071d838022b22b9 | Python | 13,819 | 427 | # -*- coding: utf-8 -*-
#
"""
svfile.py
Wrap the pysam API to permit clustering of standardized SV VCF records.
"""
import numpy as np
from collections import defaultdict
from .utils import recip, make_bnd_alt, update_best_genotypes, get_called_samples
from .genomeslink import GSNode
class SVFile(object):
def _... |
912fa86228c77d0da9556a0866b010a5066202a9cd544b0598d3ed64f9b1b6f1 | Python | 13,824 | 337 | from utils import *
import csv
import pandas as pd
import torch
import torchvision
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import Dataset, DataLoader
from torchvision import datasets, transforms
from torchvision.transforms import ToTensor
def get... |
919c65625cbca45d4a3f4995dfa29c4cdb74b032b6a2b35db08ae4ae14bdcfd5 | Python | 13,832 | 250 | import torch
from torch import optim
import lightning as L
import sys
from .mask import mask_graph_batch
from .position import add_noise_to_batch_pos, scale_batch_pos, unscale_batch_pos, wrap_batch_pos
sys.path.append('/crystal-transformer')
class TrainerGANLit(L.LightningModule):
def __init__(self, generato... |
7f7021f439253a3679c59417cb57b491810ff312ae660fa19c1e8e9e5f6f3f19 | Python | 13,836 | 344 | import torch
import random
from sklearn.metrics import accuracy_score, roc_auc_score, confusion_matrix, auc, precision_recall_curve, precision_score
import matplotlib.pyplot as plt
from torch.utils.data import DataLoader, Dataset
import calibration as cal
import logging
import yaml
import os
import pandas as pd
import ... |
c35a707e9c22a23fdbf50318bf58b003db2b34937108e9fc415856139bd9af4e | Python | 13,837 | 362 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
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 annotations
import time
from contextlib import suppress
from dataclasses import dataclass
from datetime import time... |
349f1352223c0980ea81bef1200347bd25a7ba3890f41c04b154a3e027ed3a7d | Python | 13,840 | 429 | import json
try:
import itertools.izip as zip
except ImportError:
pass
import numpy as np
import pandas as pd
import scipy.sparse as sparse
from scipy.ndimage import generate_binary_structure
from lib5c.util.system import check_outdir
class DirectedDisjointSet(object):
"""
Based on https://stackover... |
d66a27d0a77c038094c8f7e8ad1aad58cffa031635004e9c3cc076cea7ef5222 | Python | 13,841 | 457 | # Copyright 2024 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
b27c770d1e54299a27cb67bd89d0b39802c6a38897cb7b6f92049678592275f6 | Python | 13,842 | 313 | # Copyright 2023 Katherine Crowson and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... |
b8ca3d1cded2b4803e821002972f92867995256d6fa40bcaf21ec78b131adaaa | Python | 13,842 | 369 | # import numpy as np
import warnings
from deeplift.layers import BatchNormalization
from keras.layers import SpatialDropout1D
warnings.filterwarnings('ignore')
import tensorflow as tf
from tensorflow.keras import initializers
from tensorflow.keras.layers import Layer, InputSpec
from tensorflow.keras import ba... |
72546b28880b10948d3f32c21721f34ad2d3659ec6ffc2ad9c5da515a16cbb01 | Python | 13,848 | 384 | import pdb
import os
from itertools import product
from tqdm.auto import tqdm
import numpy as np
from connectivity import Connectivity
from pathos.pools import ProcessPool
class DataStore(object):
def __init__(self, dirname):
self.directory = dirname
self.data_arr = []
self.data = dict()
... |
8ac3fd4da777f48476b567017d19043ccf4b326bb0c7c5409f960ec7978e8ec7 | Python | 13,849 | 350 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Merging of spatially overlapping components that are temporally correlated
Created on Tue Sep 8 16:23:57 2015
@author: agiovann
"""
#\package caiman/source_extraction/cnmf
#\version 1.0
#\copyright GNU General Public License v2.0
from builtins import range
import n... |
2ce4f2545803a05b26838414e0fabda56ca8a59f19795caec1675fc0dac28ca4 | Python | 13,855 | 320 | r"""``ov.pl.bonsai`` — draw the Bonsai tree computed by :func:`omicverse.tl.bonsai`.
Bonsai returns a tree, not coordinates, so the layout is computed at draw time by
:func:`omicverse.external.bonsai.equal_angle_layout`. Branch lengths survive the
layout, which is the point: distance along the drawing is distance in t... |
4f414deb594b6e4e2914d4d118f29166f00dab281085a18408c106356aa61e4d | Python | 13,859 | 322 | from typing import List, Dict, Tuple
import torch
from common import TrainingRecord, TrainingScenarios, SEED
from utils import load_json_file, append_date, dump_as_pickle, load_pickle
import torch
from torch.optim import Adam
from torch.nn import CrossEntropyLoss
from torch.utils.data import DataLoader, TensorDataset... |
82b5354ac9b33e32e08a92bd56f6451bcf9756934b1e4835bd77a7ad3880d0d2 | Python | 13,860 | 301 | import re, unidecode, datetime, pickle, os, logging
import pandas as pd
from pymed.article import PubMedArticle
try:
from nltk import pos_tag
from nltk.tokenize import regexp_tokenize
from nltk.stem import WordNetLemmatizer
from nltk.corpus import wordnet as wn
except:
logging.fatal("call nltk.down... |
b6202f4fd2c0019580f26beaa511e5c8b86462b8a0d61241ab1f74585bd73b4e | Python | 13,866 | 319 | import numpy as np
import torch
from torch import autocast
from torch.cuda.amp import GradScaler
from typing import List, Tuple, Callable, Iterator, Optional, Union
import lib.data_utils.dynamic_data_util as ddu
from convex_optim_base.prox_optim import ProxFISTASolverParams
from convex_optim_base.unconstrained_optim ... |
f44cf96c3d40ab9387f8c961a122825a175814e5e2bbcf1aa95cf222c5a7a91e | Python | 13,868 | 367 | #
# CEBRA: Consistent EmBeddings of high-dimensional Recordings using Auxiliary variables
# © Mackenzie W. Mathis & Steffen Schneider (v0.4.0+)
# Source code:
# https://github.com/AdaptiveMotorControlLab/CEBRA
#
# Please see LICENSE.md for the full license document:
# https://github.com/AdaptiveMotorControlLab/CEBRA/bl... |
82d0a3910ad7d47cc505bc45bf469bbc271b471317b34471780b77f3235aae6d | Python | 13,871 | 449 | #
# Copyright (c) 2021, NVIDIA CORPORATION.
#
# Licensed under the Aeache 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... |
7172c8833a2667e3017e472a1d067476f6b2c7045ca0bed0e0ebf63ce4f280e5 | Python | 13,875 | 309 | #!/usr/bin/env python
import sys
import os
import warnings
import enum
import argparse
import tempfile
import pysam
from typing import List, Text, Optional, Iterator
from sv_utils import common, genomics_io
# noinspection PyArgumentList
class FlippedIntervalStrategy(enum.Enum):
end_to_pos = enum.auto()
fli... |
d2e9e0eb29b6064dab9e715510048dcc4f8c9c61b0b005d1e0fce701e32e0b32 | Python | 13,876 | 331 |
#lisa modules
import lisa.core.gene_selection as gene_selection
from lisa.core.utils import LoadingBar, Log, LISA_Results
from lisa._version import __version__
from lisa._version import __file__ as version_file
from lisa.core.data_interface import DataInterface, PACKAGE_PATH, DatasetNotFoundError
#standard library
im... |
58a8ed5814232b41f30c2fda6ac10206f3e696d7801a9d1883febda0049e3b1c | Python | 13,878 | 322 | from functools import partial
from typing import Any, cast, Dict, List, Optional, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
class VGG(nn.Module):
def __init__(
self, features: nn.Module, num_classes: int = 1000, init_weights: bool = True, dropout: float = 0.5
)... |
a98da5144181f0aec304f21955c68f764229a0fb51d740b8ed123f8a57bbd578 | Python | 13,882 | 436 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 22 16:11:44 2019
@author: gary
"""
from tools.radialShape import *
from scipy.interpolate import splprep, splev
import pickle
import os
from skimage.filters import threshold_otsu, threshold_yen
import time
####################
#File managment
de... |
835c57ab11299b5762923f25d8e8f08bb4ca49ebda1e885317589c4aaa10c7a5 | Python | 13,885 | 293 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
518119bc16ff417cfcc64817862b66f00a024628418799427688c9a052390f3b | Python | 13,899 | 300 | import os
import csv
import gzip
import torch
import anndata
import numpy as np
import pandas as pd
import scanpy as sc
import tensorly as tl
import sklearn.neighbors
from scipy.io import mmread
from scipy.sparse import coo_matrix
tl.set_backend('pytorch')
def preprocessing(raw_data_path, PPI_data_path, load_label... |
65060e5e02dc71b26e871cc3d8f7a6fa3520576c3d261f542ee0f68a4cb09937 | Python | 13,903 | 309 | # Copyright 2023 Katherine Crowson and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... |
98e50a4ff5cd920fe1ccf62f5960b0cb0b61422c1590878c6b52380b79f3bb59 | Python | 13,908 | 370 | import math
import operator
import random
import scipy
from scipy import sparse
import numpy as np
def select_stable(full, modality = "RNA", stable_number = None, criterion = "signal"):
'''
full is the data in np array format, either dense or sparse
'''
if sparse.issparse(full) is True:
f... |
33adaa5d268e660064c1c6cfda5d995a28d222099743d4ac4be0171ba2ae6f8a | Python | 13,923 | 344 |
import pandas as pd
import numpy as np
import sklearn.neighbors
import networkx as nx
from .mnn_utils import create_dictionary_mnn
from .._pymclustr import fit_pymclustr
def match_cluster_labels(true_labels,est_labels):
true_labels_arr = np.array(list(true_labels))
est_labels_arr = np.array(list(est... |
47a58da00647158d4fbc748c2220d50fb06e8ca45705b759d89d6f9610a2661f | Python | 13,930 | 346 | """Prompt template engine — composable prompt construction for OVAgent.
Breaks monolithic prompt strings into reusable template blocks and
deterministic overlay composition. The engine guarantees that the same
set of overlays always renders in the same order.
Prompt composition contract
---------------------------
*... |
e1b0a3ab28f4bbcb24ba0cc5a2f71b7e2596d0dc6c2543c66fa1b82e5cc529e5 | Python | 13,930 | 441 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""aihwkit example 22: 2-layers LSTM
War and Peace dataset on a 2-layers LSTM inspired network based on the paper:
https://www.frontiersin.org/articles/10.3389/... |
337629be4c70f8e79dd284e789d3029e1f0461f27f36ffa9ba18b0511506f459 | Python | 13,940 | 425 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""aihwkit example 6: analog CNN with hardware aware training.
Mnist dataset on a LeNet5 inspired network.
"""
# pylint: disable=invalid-name, possibly-used-bef... |
25d58df2cacd175c9cc9ac4d4bc63be05b4547938966ae4be4a851bbc510450d | Python | 13,942 | 478 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
45349a4f8dc732df7e61e954d969db219a4c2aad5f19a87b53626c62ef3d45b5 | Python | 13,942 | 397 | from typing import Optional, Dict
import scanpy as sc
import networkx as nx
import numpy as np
import pandas as pd
import graphical_models as gpm
import networkx as nx
def filter_low_confidence_edges(adata: sc.AnnData,
edge_threshold: float,
flowsig_netw... |
a889476651a83e535cc53f2f64f8db02d645944a0bacaef6162a8555874684f6 | Python | 13,944 | 430 | import os
import re
import sys
from tempfile import TemporaryDirectory
from unittest import mock
import pytest
from ci.ray_ci.linux_tester_container import LinuxTesterContainer
from ci.ray_ci.tester import (
_add_default_except_tags,
_get_all_test_query,
_get_container,
_get_flaky_test_targets,
_g... |
c561cc32938b3d17cdffc886b1355187545b55a58ecf9ec17174b18e774cc1da | Python | 13,955 | 341 | import pandas as pd
import scanpy
from collections import defaultdict
import numpy as np
from scipy.optimize import nnls
import scanpy as sc
from scipy.stats import pearsonr
import matplotlib.pyplot as plt
from ..utils import pyomic_palette
import matplotlib
from typing import Union,Tuple
import anndata
from .._registr... |
b767128d7a180339566c74ad1ad02a3ab7c35dcc9e82120e6f5860f177724a19 | Python | 13,957 | 293 | import serial
import numpy as np
from collections import deque
from time import gmtime, strftime
from scipy.signal import butter, lfilter
LOG_DIR = "logs/"
class QRSDetectorOnline(object):
"""
Python Online ECG QRS Detector based on the Pan-Tomkins algorithm.
Michał Sznajder (Jagiellonian University... |
839b90ade6a1c4558910bd7bd30198fa94ddb87c9e6fe9ae50108627323e5991 | Python | 13,966 | 495 | """
Logger copied from OpenAI baselines to avoid extra RL-based dependencies:
https://github.com/openai/baselines/blob/ea25b9e8b234e6ee1bca43083f8f3cf974143998/baselines/logger.py
"""
import os
import sys
import os.path as osp
import json
import time
import datetime
import tempfile
import warnings
from collections im... |
1125f1ebb5b107fa88161b6c3e8793557b17534a6372d10420bea49083f87a8b | Python | 13,967 | 381 | """
Integration tests for the pyamdsmi wrapper functions.
Run on a machine with AMD GPU(s):
python3 -m unittest discover \
-s python/ray/_private/thirdparty/pyamdsmi/tests \
-p "test_pyamdsmi.py" -v
"""
import importlib.util
import pathlib
import unittest
_mod_path = pathlib.Path(__file__).parent... |
b653a4ce3cb915bd5dc452a02851f1300dc0d9a31d2c5c9ab8dbda8a35f3134b | Python | 13,971 | 387 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
c2e33b75b613364b791020445d038d41ad21e3d20af9e7280e49166060364880 | Python | 13,975 | 376 | """
Build the chunk lists that drive the Experanto ``RandomizedExperanto`` experiment.
A *chunk list* is a JSON file named ``{trial}_{chunk}.json`` holding, in presentation order,
the stimuli that one simulation job presents::
[{"modality": "image", "file": "00042.yml", "trial": 0}, ...]
Those three fields are t... |
327b2a40baa5b9ffb1c539173f5c6975fa3dd77e4b49d03700c4a43a80fc0553 | Python | 13,984 | 395 | import os
from glob import glob
from logging import Logger
from math import e, log, ceil
from pathlib import Path
from typing import Tuple
import ignite
import ignite.distributed as idist
import pandas as pd
import monai
import torch
from ignite.utils import setup_logger
from monai.utils import set_determinism
from s... |
cc72b36065a1f97ebeeda309c43cdf46a1d58ccb0267dc91aede19351eaec86e | Python | 13,985 | 276 | import grpc
import projectmetis.python.utils.proto_messages_factory as proto_factory
from projectmetis.python.logging.metis_logger import MetisLogger
from projectmetis.python.utils.grpc_services import GRPCServerClient
from projectmetis.proto import controller_pb2_grpc
class GRPCControllerClient(GRPCServerClient):
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.