sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
cf5c6882f518797c87f588ee92387719feaba69a0f7b5c46a2083e7a234efb00 | Python | 10,080 | 302 | import argparse
import json
import re
import sys
import time
import zlib
from time import sleep
from urllib.parse import (
parse_qs,
urlencode,
urlparse,
)
from xml.etree import ElementTree
import requests
from requests.adapters import (
HTTPAdapter,
Retry,
)
BATCH_SIZE = 50000 # Limit at UniPro... |
54d90b9e3674164b568367d83e1c55d7ca1bff0ca55838c1a2f891e72a6d2237 | Python | 10,081 | 241 | import torch
import torch.nn as nn
from tqdm import tqdm
import argparse
import os
import PIL
import cv2 as cv
from PIL import Image
import numpy as np
import functools
from torchvision.models import squeezenet1_1
class StainNet(nn.Module):
def __init__(self, input_nc=3, output_nc=3, n_layer=3, n_channel=32, kerne... |
f82fd0b432ed742215c3584d8668e48d1a72b2745df5bb8f15d7b1672925746b | Python | 10,081 | 234 | # SPDX-License-Identifier: LGPL-2.1-or-later
#!/usr/bin/env python
#-*- coding: utf-8 -*-
import numpy as np
import os
from collections import OrderedDict
from .utils import general as utils
from .write_to_file import save_data_cvs, save_visit_duration
from .plotting_functions import make_visit_duration_histogram
def... |
3a3136b0e1c7819ace670bef71ce47a34fce31dc3e1b87a27140a19abdd9e28e | Python | 10,082 | 273 | # Run test with:
# torchrun --no_python --nproc_per_node=8 pytest -q -s tests/modules/test_block_parallel.py
import math
from functools import partial
import pytest
import torch
import torch.nn as nn
import torch.nn.functional as F
from apex.transformer import parallel_state, tensor_parallel
from einops import rearra... |
402bd38484fcade795d8fb56b8fb5c9b45c717ff120fbebfaae267c194440a12 | Python | 10,086 | 276 | # -*- coding: utf-8 -*-
# Copyright (c) 2016-2018 Braintech Sp. z o.o. [Ltd.] <http://www.braintech.pl>
# All rights reserved.
"""Raw analysis."""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
def test_signal(T=100, fs=1):
"""Return a test signal."""
dt = 1 / fs
x = np.arang... |
0d9c5790a603adfd5a9b7550edade27e8e0e7dcdb5e7965fca539ec160af4640 | Python | 10,088 | 277 | #!/usr/bin/env python
"""Refresh the vendored extract indexes in ``pyrosm/data``.
Run this to update the extract lists used by ``pyrosm.get_data_by_bbox`` and the area extract
lookup::
python scripts/update_extract_indexes.py # both
python scripts/update_extract_indexes.py geofabrik # or: bbbike, ... |
a15b9d7eba8c0e72805209c0484412eb841116131819c062d6891893fa677eb8 | Python | 10,088 | 301 | """This module handles indels and frameshift mutations.
Indels and frameshifts are detected from the allele columns of the mutation
input.
"""
import prob2020.python.utils as utils
import numpy as np
import pandas as pd
def simulate_indel_counts(indel_df, bed_dict,
num_permutations=1,
... |
5e7a1beb2b00889f3896ea565050813130f884c07f66cf351d3cb020131cfc93 | Python | 10,089 | 202 | # -*- coding: utf-8 -*-
"""
Created on Fri Jul 15 15:26:39 2022
@author: 8
"""
import os
import torch
import copy
import utils
import json
import warnings
import numpy as np
import pandas as pd
import tgan_utils
import time, operator
import matplotlib.pyplot as plt
import torch.optim as optim
# from MSCNN.MSCNN_uk impo... |
f93133bd174f481118998146f67a554d2b949fe03ae05083db399c07b98f2e27 | Python | 10,090 | 271 | from collections import OrderedDict
import copy
import pkg_resources
import numpy as np
from PyQt6 import uic, QtCore, QtWidgets
class Visualize(QtWidgets.QWidget):
image_changed = QtCore.pyqtSignal(np.ndarray)
def __init__(self, *args, **kwargs):
"""Everything concerning image visualization"""
... |
ccdfd8d44fd0616e592bd9b6eb851d767abe50187c553e0e20acdc296ad8773b | Python | 10,091 | 407 | r"""Functions that can be used for model fitting.
Conventions:
- Each function in this file should be named as `{LABEL}_function`
- Each function takes as input:
- `xs` : the input frequency vector
- `*params` : a variable number of input parameters
- For aperiodic functions, this is the number of inpu... |
ea3d2de145e76ae40ee51eed78f96e179714da806f754eca175350efc22c8f87 | Python | 10,092 | 228 | # coding: utf-8
import glob
import pandas as pd
import os
import nolds
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats
from helper_functions import get_total_number_of_epochs
from create_histograms import _get_histogram_values_in_sec
from nolds.measures import logarithmic_n, poly_fit, plot_reg
... |
cb82b86830f07f76c15b5f5bdc702454075ed13956b0132ac0b0c280d9d78b3f | Python | 10,103 | 279 | """
Unit tests for database metadata caching (io/cache.py).
Tests SQLiteDatabaseMetadataCache operations including:
- Cache file creation and management
- Metadata querying and caching
- Experiment info storage and retrieval
- Cache listing and summarization
"""
import json
import os
import shutil
import sqlite3
impo... |
f8caf30623821a3254d73731b7c7184354b77780a78a52148b4db4b90c1e2aef | Python | 10,104 | 276 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in compl... |
707456789e426fc54c09816cbdca68e9b98dec9917d5ff09d4d2ecfd096117cb | Python | 10,105 | 333 | """T-CALLABLE-IDENTITY: the D8 classifier battery (lane F18, item 15).
The merged acceptance shape: legitimate transforms classify COMPLETE with
zero false refusals, collision pairs SEPARATE (defaults, kw-only defaults,
bound methods differing only in instance state, closure tensors with
identical repr), must-refuse c... |
e1f9a17a8fc5cbf6faef57155b5fca742eaf6215ff05805458c9fa31c271b2a2 | Python | 10,106 | 274 | '''Test for bdpy.vstack'''
import unittest
import numpy as np
from bdpy import BData
from bdpy.bdata.utils import vstack, metadata_equal
class TestVstack(unittest.TestCase):
def test_vstack(self):
x0_data = np.random.rand(10, 20)
x0_label = np.random.rand(10, 1)
x1_data = np.random.r... |
457b14eb475e0ad9fa1ee04db066d97107fc4d61b76997057d8f3d0e28ff553e | Python | 10,108 | 312 |
import time
import logging
import numpy as np
import pylsl
import ipdb
from libmushu.amplifier import Amplifier
logger = logging.getLogger(__name__)
logger.info('Logger started.')
class LSLAmp(Amplifier):
"""Pseudo Amplifier for lab streaming layer (lsl).
This amplifier connects to an arbitrary EEG dev... |
0f4f85e59eb0bd6ae0fe24ddb56039ef2befd947902269f14a4ce91cfd4259eb | Python | 10,110 | 238 | import subprocess
import pkg_resources
def install_required_packages():
# List of required packages
required_packages = ['spams', 'staintools']
installed_packages = [pkg.key for pkg in pkg_resources.working_set]
missing_packages = [pkg for pkg in required_packages if pkg not in installed_packages]
... |
75c0b4f2aa7bbfd00e6d8b5d0bb10d17c588f0331ab29e8206c3d1659cc3f0f7 | Python | 10,120 | 388 | """
This module contain all tools
"""
import numpy as np
from scipy.linalg import norm
from scipy.optimize import minimize_scalar
from .core import Connectivity
def histogram(val, bins, density=False):
"""Fast histogram
Parameters
----------
val : array
Values to be counted in bins.
bin... |
d0b8f440c45e0708c75d618d4ed9e2b76c1fcaed003d4083740c4d3e58ac0f6a | Python | 10,120 | 272 | import fnmatch
import logging
import os
import os.path as osp
import time
import numpy as np
from qtpy import QtCore
import llspy
from llspy.gui import workers
from llspy.gui.helpers import (
newWorkerThread,
shortname,
wait_for_file_close,
wait_for_folder_finished,
)
_watchdog = False
ActiveWatcher ... |
f376849f3510202470e9dc8b2852eab2816289348ecf9e82ebfd41e88dcddf4d | Python | 10,121 | 259 | """Golden receptive-field tests for the built-in T5 rule pack."""
from __future__ import annotations
from collections.abc import Iterator
import pytest
import torch
import torch.nn.functional as functional
from support.rf_isolation import preserved_rf_registry
from torch import nn
import torchlens as tl
from torchl... |
579267c0a6c42f3fc349f5ce78259b9a2cf0193622cefe8278e457c207b05efb | Python | 10,122 | 316 | """TensorFlow static-label intervention preview tests."""
from __future__ import annotations
from typing import Any
import numpy as np
import pytest
from conftest import tensorflow_backend_modules
import torchlens as tl
from torchlens.backends import BackendUnsupportedError
from torchlens.backends.tf.backend import... |
83eaa774c2dc1fdce1d78af4372a6c0a57b98b0299833312c17040a54708f74c | Python | 10,123 | 264 | """
Framework Phi computation — single source of truth.
The Consciousness Potential is computed as a product of channels:
Phi = I_A · (1 - H_norm) · I_R · I_P (canonical, 2026-06-13)
C100 = 100 * Phi / (Phi + PHI_REF)
Channels:
I_A — directed-coupling-weighted activity (∑_i n_i · D_i)
org ... |
adf4f439cdef638414c31289e5ea8dfb47434dec95978e1d5e9219c4530ce2ac | Python | 10,123 | 232 | from aud_dnn.resources import d_layer_reindex, d_randnetw
import numpy as np
import pickle
import pandas as pd
def load_rsa_scores_across_layers_across_models(source_models,
target='NH2015',
value_of_interest='all_data_rsa_for_best_layer',
roi=None,
randnetw='False',
... |
540a396a137f8357d61b26869dfe02d7e66bbd268f29da5e3bea5aa36e6453a1 | Python | 10,127 | 326 | """Tests for TorchLens stack introspection helpers."""
import os
from types import FrameType
import pytest
import torch
from torch import nn
import torchlens
import torchlens as tl
from torchlens.data_classes import FuncCallLocation
from torchlens.utils import introspection
class RecursiveStackModel(nn.Module):
... |
08e7b39b3b22938da9ff5ba76f640917518894803eac08e6615c917be21edf33 | Python | 10,128 | 283 | import time
from datetime import datetime, timedelta
from datetime import timezone as datetime_timezone
import pytest
import requests
from pytest_celery import CeleryTestSetup
from requests.auth import HTTPBasicAuth
from celery import Celery, chain
from t.smoke.tasks import add, noop
from t.smoke.tests.quorum_queues.... |
bb1852ce9728abdd9b7f8bfb2ab03b6bb46880982d5be1c80f1524a3dc6af612 | Python | 10,128 | 253 | # flake8: noqa
import numpy as np
import pytest
import tensorflow as tf
from absl.testing import parameterized
from tensorflow.python.eager import context
from keras.src import backend
from keras.src import testing
from keras.src.optimizers.sgd import SGD
@pytest.mark.skipif(
backend.backend() != "tensorflow",
... |
57bf3aed21059ef604f1e6db4eec8f6069f3416f245dd9b09cda188c2f716074 | Python | 10,132 | 280 | """L6 stage 4a: cross-run selection alignment (``ResolvedSelection.align_to``).
Pins the cross-run door: alignment keys on the L1 structural site keys each
ACT entry records (the bridging relation), SAME-POLICY captures only per the
L1 cross-stamp rule (healthy, agreeing grouping stamps on both sides), masks
travel un... |
41688b6b86efe568f856a06a83115b7b5172bc2bce2c98744be812c88875b00f | Python | 10,134 | 240 | import os
import subprocess
import logging
import tempfile
import json
import time
from pathlib import Path
from getpass import getuser
import pytest
def _get_gpu_ids():
visible = os.environ.get("CUDA_VISIBLE_DEVICES")
if visible:
return [g.strip() for g in visible.split(",")]
try:
resul... |
629d481658aaec7076a55913eda38c270ec45d430b34b2f9d38b2eec2b0ad3da | Python | 10,134 | 298 | from __future__ import annotations
import importlib.metadata
import typing as t
from contextlib import contextmanager
from contextlib import ExitStack
from copy import copy
from types import TracebackType
from urllib.parse import urlsplit
import werkzeug.test
from click.testing import CliRunner
from click.testing imp... |
d39574de085e78ad90ad03433b5b8bf331d0553a730456521707dc5bc9b9ebed | Python | 10,135 | 243 | import glob
import pickle
import numpy as np
import figure_properties as fp
import matplotlib.pyplot as plt
from matplotlib import gridspec, colors, cm
def fetch_parameter(path, seed, case):
try:
ff = open(path + '/' + str(seed) + '_' + case + '.npz')
ff.close()
print(path + '/' + str(see... |
24910382dc7d42ba4fb443b0b333b2dc989997dcab3d58d3d21d48b3562d6b4b | Python | 10,137 | 251 | from abc import ABC, abstractmethod
from typing import List, Optional, Tuple
from torch import Tensor
from torch.nn import Module, Parameter
from lightly.models import utils
class MaskedVisionTransformer(ABC, Module):
"""Abstract base class for Masked Vision Transformer models.
Defines the interface for a ... |
318597a7d1496ae65f64a914804a6700746866e15168c6656632febfb776c6e3 | Python | 10,137 | 289 | '''
load the RBNS data
'''
import csv
import re
import h5py
import urllib3
import urllib
import gzip
from io import StringIO
import requests
import numpy as np
import time
from utils_rbns import create_datapoints
rbns_data = 'metadata_rbns.csv'
encode_dir = 'encode/'
data_dir = 'data/'
protein_idx_map_txt = 'protein... |
dcb4ac58dc2a1ff76e6a28726ce40e97c1e204d4fa64c5fd9b94ace414eafae1 | Python | 10,138 | 246 | """Error-refusal contract doc <-> code LOCKSTEP (grind B1-11 / matrix R64+R11).
``docs/reference/error_refusal_contract.md`` is the public vocabulary of stable
refusal codes, and its closing sentence makes adding or renaming a code a
documented public change. Until this module existed nothing enforced that:
the doc's ... |
f35754d4e6ce4352026cf8b15738b7e288e64df7c066e8fd7fcda072f7eaea3c | Python | 10,138 | 243 | '''
Functions to compute performance metrics.
Note that these functions are much slower than your usual
performance metrics. Due to overlap and window scoring.
'''
import pandas as pd
import numpy as np
import os
import pickle
from typing import List, Tuple
from tqdm.auto import tqdm
PEPTIDE_START_STATE, PEPTIDE_EN... |
1052767ffbf08fc113801e0d3358d2c0d03a3d59648c0b3bfd40a4271f62cefc | Python | 10,139 | 308 | import re
from multiprocessing import TimeoutError
import numpy as np
import pytest
from gym.error import AlreadyPendingCallError, ClosedEnvironmentError, NoAsyncCallError
from gym.spaces import Box, Discrete, MultiDiscrete, Tuple
from gym.vector.async_vector_env import AsyncVectorEnv
from tests.vector.utils import (... |
258537f9fb6327b7e6562663455c024a05e53ef0d0d5cb631dffa75f68ae23d0 | Python | 10,141 | 287 | from keras.src import ops
from keras.src.api_export import keras_export
from keras.src.backend.common import standardize_dtype
from keras.src.initializers.initializer import Initializer
from keras.src.saving import serialization_lib
from keras.src.utils.module_utils import scipy
@keras_export(["keras.initializers.Con... |
a417bb0e8a99a6a722fcf25a5a97a1ecd86a8436c501b7d608f8521f1510f129 | Python | 10,142 | 292 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Utilities to read and write nifiti and cifti data."""
import os
import shutil
import nibabel as nb
import numpy as np
from isal import igzip
from nilearn import masking
from nipype import logging
from ... |
91c90e761d952f1026be1e983628bc02c095eb1ffbfc40e54d61868bdfcf87ee | Python | 10,144 | 210 | from __future__ import division
from __future__ import print_function
import sys
import argparse
import logging
logging.basicConfig(level=logging.INFO)
import time
import numpy as np
import mxnet as mx
from tqdm import tqdm
from mxnet import nd
from mxnet import gluon
import gluoncv as gcv
gcv.utils.check_version('0.6... |
ad4c4f62751563f04d28d788c03cd81f512d4f84dda98088331c7d736cee1da3 | Python | 10,146 | 295 | import torch
import torch.nn as nn
from modular_splicing.models.modules.constant import Constant
from modular_splicing.models.modules.positional_encoding import PositionalEncoding
from modular_splicing.utils.construct import construct
class TanhConvolvedAttnLayer(nn.Module):
def __init__(
self,
e... |
e66f8dac2fa2f1a3d6f4e96efa0c56e06d7a5b7040f33de9f93156325f9fb85c | Python | 10,147 | 266 | """Tests for structured replay-failure diagnostics (sprint bucket B1).
These cover the ADD-ONLY diagnostics side-channel that lets a forward-validation
mismatch carry the ACTUAL reason (divergent op, shapes/dtypes, max abs/rel diff,
which check fired) instead of the bare ``repr(False) == "False"`` that previously
reac... |
ce062e2e85e9bf2695abcd801f5acdc77535e8b5f22849d1a4b5d9ed8861c4ff | Python | 10,151 | 281 | # SOURCE: vendored from Nablax/ACLnet-Pytorch @ master
# (https://github.com/Nablax/ACLnet-Pytorch/blob/master/models_pt.py,
# https://github.com/Nablax/ACLnet-Pytorch/blob/master/ConvLSTM.py)
#
# The queue's listed repo (wenguanwang/DHF1K) is the *dataset* repo for Wang et al.'s
# original ACLNet paper and contains n... |
254e4de2da21e91bfd4a81106dc2e183f90225d9e3ca2cfd29be1eb347ead229 | Python | 10,153 | 296 | """Staged intervention hooks never accumulate across repeated runs.
Regression pin: after ``tl.trace(model, x, intervene=spec)`` every legacy
rerun ``trace.run(model, x)`` merged the hook plan it had normalized FROM the
trace's own spec back INTO that same spec object, so the staged hooks doubled
per rerun (1, 2, 4, 8... |
338e03de7ce74e166cc82e9e47fc14de7339076c3ed7e97a3b36800ba1358ae8 | Python | 10,153 | 254 | import torch
import pandas as pd
from transformers import BertModel, BertConfig
import pdb
from omop_learn.utils.date_utils import to_unixtime
eps = 1e-8
class OnehotModel(torch.nn.Module):
def __init__(self, featdim, outdim):
super().__init__()
self.featdim = featdim
self.outdim = outd... |
4f4934898fb86aa03b0dcbf24c19c8286a1bc8f28081e4bb7d63c251c276adfd | Python | 10,153 | 231 | # pylint: disable=line-too-long,too-many-lines,missing-docstring,arguments-differ,unused-argument
import mxnet as mx
from mxnet import init
from mxnet.gluon import nn
from mxnet.gluon.nn import HybridBlock
from ..vgg import vgg16
__all__ = ['vgg16_ucf101', 'vgg16_hmdb51', 'vgg16_kinetics400', 'vgg16_sthsthv2']
class ... |
a9703123a20af03ecf83b8876c0537868320de80aefdfde992156197cb0b8b0f | Python | 10,153 | 318 | """.. _lightly-simclr-tutorial-3:
Tutorial 3: Train SimCLR on Clothing
==============================================
In this tutorial, we will train a SimCLR model using lightly. The model,
augmentations and training procedure is from
`A Simple Framework for Contrastive Learning of Visual Representations <https://ar... |
61293aa17e9c30d1d6dd3bdf127c5dcce98c25b6607c193641264db982dd5f5c | Python | 10,156 | 251 | import pytest
import torch
from torch.nn import Linear
from lightly.models import utils
from lightly.utils import dependency
if not dependency.timm_vit_available():
# We do not use pytest.importorskip on module level because it makes mypy unhappy.
pytest.skip("TIMM vision transformer is not available", allow_... |
184e54948794d6cb16d554d8fa3a73c65b4001b7c7c52ce9ac119a59f17490d7 | Python | 10,157 | 287 | """
Functions for annotating spots as cell types.
"""
import os
import numpy as np
import scanpy as sc
import stlearn.tl.cci.r_helpers as rhs
def run_label_transfer(
st_data, sc_data, sc_label_col, r_path, st_label_col=None, n_highly_variable=2000
):
"""Runs Seurat label transfer."""
st_label_col = sc_... |
2aab5d37aa3d4af11ed94c037061ccd3c1505538f5021769a33baaa0b8a1c486 | Python | 10,157 | 286 | """The completeness backstop counts a stale torch call inside a wrapped submodule.
A torch function bound before TorchLens wraps torch (a module-global
``from torch import f`` alias, as in legacy ``torch.nn.utils.weight_norm``) reaches
the dispatcher with no torch-function wrapper. At the top level the witness records... |
294e98e112ffb165b09282d02dcf00f652b9ba3ef7ff62a4932e005fac65e459 | Python | 10,160 | 387 | """Compact faithful scientific neural architecture classics.
Paper: Deep Ritz Method, Deep Galerkin Method, Behler-Parrinello HDNNP, HIP-NN.
"""
from __future__ import annotations
import torch
import torch.nn as nn
import torch.nn.functional as F
class ResidualMLP(nn.Module):
"""Residual multilayer perceptron ... |
61a89dd951fdcca8663408cdbf326abecab541de46631ef5985de3db3d424875 | Python | 10,160 | 256 | import wandb
import numpy as np
import os
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import argparse
from sklearn import metrics
import torch.nn.functional as F
from datasets.openmic import get_test_set, get_training_set
from models.mn.model import get_model as get_mobilenet
from models... |
2085cb73fac517b3fb057a2838b94b3ec61526087282802275abee01d7e6a72f | Python | 10,164 | 293 | """Functions related to visualization of RDMs.
Authors
-------
Marijn van Vliet <marijn.vanvliet@aalto.fi>
Takao Shimizu <tshimizu.midd@gmail.com>
"""
import types
from functools import partial
import matplotlib.pyplot as plt
import numpy as np
import mne
from mne.fixes import _compare_version
from mne.viz import Br... |
9045faf417d4167b0b566c7cbccc1b2b51df782f33cd0185e8119f1a7746469e | Python | 10,167 | 291 | """Hypergraph Neural Network (HGNN) and Cellular Sheaf Neural Network.
HGNN:
Feng et al., "Hypergraph Neural Networks." arXiv:1809.09401 (AAAI 2019).
Source: https://github.com/iMoonLab/HGNN
Cellular Sheaf Neural Network (SheafNN):
Bodnar et al., "Neural Sheaf Diffusion: A Topological Perspective on
Heterophi... |
9c6a376d00aaa6ba85ce0b92bd469806c6083a229390ae7865a6e254fa54d66d | Python | 10,168 | 245 | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... |
c39f2c61112a5baaad65e249cec186874623b94a95327a7f03d346c038b9d635 | Python | 10,170 | 287 | import os
import argparse
import random
import yaml
import logging
from functools import partial
import numpy as np
import dgl
import torch
import torch.nn as nn
from torch import optim as optim
from tensorboardX import SummaryWriter
logging.basicConfig(format="%(asctime)s - %(levelname)s - %(message)s", level=log... |
472e4c2248f8cb9b789a58af93379e8aa8764b7e2c312f5cc83323eac14b16ee | Python | 10,171 | 227 | import os
import torch
from collections import OrderedDict
from abc import ABC, abstractmethod
from . import networks
class BaseModel(ABC):
"""This class is an abstract base class (ABC) for models.
To create a subclass, you need to implement the following five functions:
-- <__init__>: ... |
50a7c758afff7982bc8c4d8b5a198240543dae1fc5de4c22136d44fdf853829f | Python | 10,172 | 218 | # 均匀采样效果较差
import json
import numpy as np
import os, sys
from collections import Counter
from sklearn import preprocessing
from sklearn.metrics import f1_score
from sklearn.metrics import confusion_matrix
import torch
import torch.nn as nn
import torch.nn.utils.rnn as rnn_utils
import torch.nn.functional as F
from torc... |
57cba50341139787402245aced1ef550f2d3ce0e6f9373cef37cf6130eb3447a | Python | 10,172 | 183 |
import os
import pandas as pd
import numpy as np
import pdb
from sklearn import linear_model
import scipy
import regression_funcs as rf
usage = "regression_model_sliding_window_beta_slope.py [options] <cluster>"
long_help = """
Computes regression model for slope of beta lateralization dependent on bias and stimulus ... |
764aaeea4a3323567ba6076fd0c85ad211bebf7294ac6101a76c39dccb34f35a | Python | 10,172 | 265 | """Module-granularity netron export (lane F14, netron memo D-11/D-12, ruling N2).
Per-call FunctionProtos with recursive nesting, depth-1 interim default,
single-op inlining with FunctionProto DELETION, non-empty root, per-function
valueInfo, signature-style formal input names, per-call keying on reused
modules (compo... |
bfe7eaca567595e4e2c7ef76b5e2df3bd791f661bf7deb394bf4014edd47e27c | Python | 10,174 | 224 | #!/usr/bin/env python3
"""
File: simulate_expression2.py
Created: 2023/07/13
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"... |
cc88cfe42f13d5471410491a88cf923d1148686acaa0a7b9f2363f265b446c61 | Python | 10,177 | 334 | #from ..cython import cutils
import numpy as np
import os
import prob2020.python.mymath as mymath
import sys
# import pickle module
try:
import cPickle as pickle
except:
if sys.version_info < (3,):
print('Falling back to regular pickle module')
import pickle as pickle
def retrieve_scores(gname, sd... |
492869b7b8bd0b958521a73e59d492105b7ffabd2d986be8507905b9cb744825 | Python | 10,179 | 272 | import os
import pandas as pd
import numpy as np
import pdb
import scipy
from sklearn import linear_model
import regression_funcs as rf
usage = "regression_model_motor_beta_dB_new.py [options] <cluster>"
long_help = """
Computes regression model for beta lateralization dependent on bias and stimulus strength
"""
fr... |
d6b457a969f108a132ba22c6af40673b6c91ecc2de855241699029602c6956bc | Python | 10,181 | 271 | """Correlation-ID join correctness on synthetic fixtures (torchnative W2.2).
The join's correctness properties are proven on synthetic normalized-event
fixtures with hand-set thread ids -- the ONLY sanctioned cross-thread
negative control: torch's profiler records nothing on a plain Python
thread, so a live Python-thr... |
7df2d8d7dbcdf55444c904cc76ff65ce716788679fbe03e836436702b1cb397a | Python | 10,183 | 294 | """Quality control metrics."""
import nibabel as nb
import numpy as np
from nipype import logging
LOGGER = logging.getLogger('nipype.utils')
def compute_registration_qc(
bold_mask_anatspace,
anat_mask_anatspace,
bold_mask_stdspace,
template_mask,
):
"""Compute quality of registration metrics.
... |
058f92c48b29c9fe41056721f56b364d99e9e4368a21527a51e6ac9b92cf1908 | Python | 10,185 | 235 | import time
import sys
import os
import functools
import importlib
import multiprocessing as mp
import deepdish as dd
from brian2.only import *
import brian2genn
# for the IDE:
import numpy_ as np
import spatial, model, inputs, readout
from util import brian_cleanup
from digest import get_voltage_histograms
def run... |
8fea3866ec5e4aef981233390d21fe58844a329cb76adf98752f356db95e6906 | Python | 10,187 | 275 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test that the AMBER DFTB implementation of AMBER and CHARMM using 3ob-3-1 parameters are equivalent.
"""
# ===... |
dcdbdf6de143d86b6a15267245fb874b1b135713e27039ebcdcad1aa45307122 | Python | 10,188 | 279 | # -*- coding: utf-8 -*-
"""
Created on Mon May 11 12:21:33 2020
@author: Sergio Marconi and Dylan Stewart
"""
from parameters import evaluation_parameters
from RandCrowns import RandNeon
import time
from tqdm import tqdm
"""
Created on Tue May 5 10:28:41 2020
input variables:
GroundTruthBox - numpy arra... |
4389a330db10d2f5c785f49bb3eeccc98c743d58a47e085ad7076f1397cdf2b6 | Python | 10,191 | 240 | import ipdb
import torch
import numpy as np
from pandas import read_csv
import os
from tqdm import tqdm
import torch.utils.data as dat
class Dataloader:
def __init__(self, database_wdir, nums, time_step, tw):
self.database_wdir = database_wdir
self.nums = nums
self.time_step = time_step
... |
45f2e444d86c2b477181d77ce3124c21c17ce5afda6113949884e7a5259311a2 | Python | 10,191 | 306 | import threading
from types import SimpleNamespace
import pytest
from celery import states, uuid
from celery.app.task import Context
from celery.result import AsyncResult, GroupResult
from t.integration.conftest import get_active_redis_channels
from t.integration.tasks import identity
@pytest.mark.celery(
resul... |
e619b9d0db06c714aad07bfbde24ec6c5d294d4bc05350049b2aaf00fc647249 | Python | 10,191 | 301 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Hoverlabel(_BaseTraceHierarchyType):
_parent_path_str = "ohlc"
_path_str ... |
0bd9b28874cfb4bfd0f6697f40614160f462d7d4e365585c9eaf3f82d3678890 | Python | 10,192 | 242 | # Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the f... |
3011baf76160fefb11140069e51a83adfbbd654aadaa084ebfb5464c5be55d47 | Python | 10,193 | 251 | from library.shared_vars import sim_results_dir, plots_dir
from os.path import join
import numpy as np
import matplotlib.pyplot as plt
import os
import pandas as pd
from library.utils import load_pickle
import matplotlib as mpl
for analysis_tag in ['', '_NoRecurrence']:
print('Analysis Tag = ', analysis_tag)
... |
8febc14098f7b97f57074d1d974d9e82d7136239499f1959d1c3cdfbbe3b156b | Python | 10,193 | 269 | import numpy as np
import pytest
import torch
from conftest import (
dataset_options_factory,
get_mapping_idx_to_euler_angles,
model_options_factory,
network_factory,
)
from e3nn import o3
from e3nn.util.test import assert_equivariant
from torch_geometric.data import Data
from torch_geometric.loader imp... |
22539b991ad414247a8edac79744cf370d3961c6db50b16c7d943fb1268ab665 | Python | 10,194 | 252 | from __future__ import annotations
from typing import Any, cast
import awkward as ak
import numpy as np
from awkward.contents import (
EmptyArray,
IndexedArray,
IndexedOptionArray,
ListArray,
ListOffsetArray,
NumpyArray,
RecordArray,
RegularArray,
)
from awkward.index import Index
fro... |
11d01790971dd4f635b8ef0dae4bb2d191a7d095339a2b14fb61caf4a111d15e | Python | 10,195 | 335 | import argparse
import json
import sys
from copy import deepcopy
from pathlib import Path
def parse_ids(raw):
ids = set()
for token in raw.split(","):
token = token.strip()
if not token:
continue
if "-" in token:
a, b = token.split("-", 1)
ids.update... |
b26b57de715ec019c83249d07b7a6042defd604129f9977ce0508365d009d167 | Python | 10,196 | 312 | # Copyright (c) 2022 PaddlePaddle Authors. 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 required by app... |
f5443ecbd1effce4486f77064c0245722d7e5659f7404a62314f5e25597451a7 | Python | 10,196 | 274 | """A02 refusal + tripwire rows: anchors refuse rather than guess.
Planted-wrong and refusal rows for the residual/lm-head dataflow anchors
(mikit gate 1 item 7 discipline: every wrong implementation must FAIL typed,
never return a plausible tensor):
- resid_pre refuses on ambiguity (two matching streams) and on no-ma... |
841db902c5dbf24b1e986bd2bc97d210ad36b58fff99c559e36d40d48a1c072d | Python | 10,202 | 324 | """
some ordinal regression algorithms
This implements the margin-based ordinal regression methods described
in http://arxiv.org/abs/1408.2327
"""
import numpy as np
from scipy import optimize
from sklearn import base, metrics
from sklearn.utils.validation import check_X_y
def sigmoid(t):
# sigmoid function, 1 /... |
3a4ddf8963045d345bc1a1e8d9df372e01aaac93e4a34e2ad60adb03e326d023 | Python | 10,203 | 254 | import awkward as ak
import numpy as np
import pytest
from seqpro.rag import Ragged
from seqpro.rag import zip as rag_zip
from seqpro.rag._ops import to_packed
def _to_list(rag):
"""Awkward nested-list view of a _core.Ragged for value comparisons.
_core.Ragged is not an ak.Array, so ``ak.to_list(rag)`` cann... |
c6703483260ccbda91e4ab43f5315bda322ceda9ed9b970874d1cc7c1bea2981 | Python | 10,203 | 223 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import ast
import contextlib
import json
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Any
import torch
from ultralytics.utils import YAML
def _read_proto_map(file: Path, path: ... |
111d07229e12840da40cc14368e99edecf2dfd24b30e1b7be5c8b7859c99a95d | Python | 10,206 | 318 | #!/usr/bin/env python3
import numpy as np
import pandas as pd
import sqlite3
import os
import logging
class DbAccess():
"""
This is the class to create sqlite3 db for KEGG pathway and records
"""
def __init__(self, db):
self.db = db
self.conn = None
self.c = None
def init_... |
d1673fce6315f5e582c301f7c3e294288667601527ad4f5154c0ea04870ca19a | Python | 10,207 | 265 | """
The GROVER trainer.
"""
import os
import time
from tqdm import tqdm
from logging import Logger
from typing import List, Tuple
from collections.abc import Callable
import torch
from torch.nn import Module
from torch.utils.data import DataLoader
from BatmanNet.model.models import MyGMAE_Task
from BatmanNet.util.mult... |
d0fe1d7a77ec251476d4747921418f53fd0a8bcc4ddad156e222089792abad28 | Python | 10,208 | 253 | #!/usr/bin/env python3
"""
File: correlate_components_with_genes.py
Created: 2021/05/25
Last Changed: 2022/05/17
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory ... |
3a0100ce4863f63b95b2443a41f8f0703e59914a3072c0a6845354d9be1e1cc5 | Python | 10,210 | 218 | # 均匀采样效果较差
import json
import numpy as np
import os, sys
from collections import Counter
from sklearn import preprocessing
from sklearn.metrics import f1_score
from sklearn.metrics import confusion_matrix
import torch
import torch.nn as nn
import torch.nn.utils.rnn as rnn_utils
import torch.nn.functional as F
from torc... |
9274593d15ad3f7ee1e37bac3733414da6cc26825d91a1dfa369828b6352146e | Python | 10,211 | 312 | # Copyright (c) 2022 PaddlePaddle Authors. 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 required by app... |
a690280c9d0eb494563010922390f61303573749ffb795faefa69015a4b6f344 | Python | 10,211 | 279 | from __future__ import print_function
import random
from copy import deepcopy
import numpy as np
from .ZIFA import checkNoNans, Estep, Mstep, initializeParams
"""
Block zero-inflated factor analysis (ZIFA). Performs dimensionality reduction on zero-inflated data.
Faster than ZIFA: uses block subsampling to increas... |
68e72b30d118b89f2b58ceecadc571032987b0fb109eaecca6b828e10d2431c3 | Python | 10,212 | 262 | """F12 pins: N16 view-aware source families and the N10 budget resolver.
Covers the memo's composition-test rows 5 (the resolver lands the band,
discloses the dial by name, deterministic) and 11 (the view x source
pairing four-cell matrix), plus the zero-coverage refusal in the F12 row
gate.
"""
from __future__ impor... |
f4cc5a132f001e223a8f5eef1779b0090205871458706dd5ae8a9c453dab26fa | Python | 10,218 | 222 | import os
import torch
import pandas as pd
import numpy as np
import scanpy as sc
from sklearn import metrics
import multiprocessing as mp
from sklearn.metrics.cluster import adjusted_rand_score, normalized_mutual_info_score
from sklearn.metrics.cluster import (
v_measure_score, homogeneity_score, completeness_scor... |
58661175b2465aea6457723b96e5b76c7304fb8be76ee70718a6b22cb38280a9 | Python | 10,219 | 215 | import os
import sys
import time
import argparse
import logging
import math
import gc
import json
import numpy as np
import mxnet as mx
from mxnet import nd
from mxnet.gluon.data.vision import transforms
from gluoncv.data.transforms import video
from gluoncv.model_zoo import get_model
from gluoncv.data import VideoCls... |
be5b84cfd74af4f6f7570a26fcf05110facd3c28d8c3d3d2761b9531aeb94623 | Python | 10,219 | 267 | # Prototype of Kohonen's Self-Organizing Maps
import numpy as np
import itertools as itt
from . import metrics
from .metrics import euclidean
import sys
from .utils import _sorted_memberships
from .utils import sort_clusters_by_size
def neigh_gauss(x1,x2, r):
return np.exp(-euclidean(x1,x2)**2/r**2)
def vorono... |
6d73e3cf8d86924b4d41758e4489f18db28a7a37ebacdae506cf08b15469d60d | Python | 10,221 | 349 | ''' Plotly graphs used for results visualization. '''
import os
import copy
import dash
import pandas as pd
import plotly.graph_objects as go
###################################################
## GLOBAL SETTINGS
MY_COLORS = {
'fontColor':'rgb(60, 60, 60)',
'boxesColor': "#F9F9F9",
'backgroundColor':... |
3cb7744eb05f0e920d8d1926073ad80357100b692eb893120fe24ad6c0f36038 | Python | 10,222 | 274 | import pickle
import numpy as np
from absl.testing import parameterized
from keras.src import backend
from keras.src import dtype_policies
from keras.src import losses as losses_module
from keras.src import ops
from keras.src import testing
from keras.src.backend.common import set_keras_mask
from keras.src.backend.co... |
e3e06d335649d02fe609f5cbe8b7b0eca10f10d67af36b5426b664bb6ea9bc1a | Python | 10,223 | 271 | """Checks kit item 1: scan kernel, audit_params, ParamAudit, JSON export.
Pins the checks memo 4.4 contract: mapping-only door, tied-alias dedup,
skip-with-reason, unknown-name refusals, severity mapping, the versioned
export, knob parity with dtype_range_audit, and the fp16 peak-allocated-
bytes regression (NO whole-... |
cdca775a608c8c9ada8dfafd4a04b52f71f8172caea7df5fe53c89414f79ed8f | Python | 10,231 | 246 | """Functions to segment regions of a slice by UMI density.
"""
from collections import Counter
from typing import Dict, Optional, Tuple, Union
import cv2
import numpy as np
from anndata import AnnData
from kneed import KneeLocator
from scipy.sparse import csr_matrix, issparse, lil_matrix, spmatrix
from sklearn import ... |
a87e64f54adf948a17b9ab5372827630461d46ddf9e8fe95f2fcb53125741d68 | Python | 10,233 | 354 | """Test eFEL io module"""
import os
from pathlib import Path
import numpy as np
import pytest
from efel.io import load_ascii_input
testdata_dir = Path(__file__).parent / 'testdata'
neo_test_files_dir = Path(__file__).parent / 'neo_test_files'
meanfrequency1_filename = testdata_dir / 'basic' / 'mean_frequency_1.txt... |
71eb35738c9149aa5cd550ee4d6de85a2a55dc22c8637a960ddbdd6895caa0c8 | Python | 10,235 | 260 | # SOURCE: vendored from Huage001/AdaAttN @ main (models/networks.py)
from __future__ import annotations
import torch
import torch.nn as nn
import functools
from torch.nn import init
from torch.optim import lr_scheduler
def get_scheduler(optimizer, opt):
"""Return a learning rate scheduler
Parameters:
... |
2a506cc966e79f23fcfb927310d6a0ed7dc99a5fbfa8a611769080f96fe20e79 | Python | 10,236 | 279 | """Native delayed delivery functionality for Celery workers.
This module provides the DelayedDelivery bootstep which handles setup and configuration
of native delayed delivery functionality when using quorum queues.
"""
import sys
from typing import Iterator, List, Optional, Set, Union, ValuesView
if sys.version_info... |
f8075c19e49e2ed0405a910fc1e2eb0bfea038114ed5254535b02efd139a4167 | Python | 10,237 | 87 | import torch
from src import datasets, models
def get_dataset(root, name, split, ntau, idx, normalise=True, scale=1):
if name == "single_pvc1":
dataset = datasets.SinglePVC1Dataset(root, split, ntau, normalise, scale)
elif name == "multi_pvc1":
dataset = datasets.MultiPVC1Dataset(roo... |
70c7c68d9610e7c9a2376b61a183792b92b89b31f38f60031fcbcabb830f5c42 | Python | 10,240 | 279 | """
Integration tests for the backup system.
This module contains tests for the backup and data synchronization
functionality in the node package.
"""
import os
import shutil
import tempfile
from pathlib import Path
from unittest.mock import MagicMock, Mock, patch
import pytest
# Note: Actual imports would need to ... |
a24e1d3d32491f6825d37b09f7cd7954b9dba91889d834310d8292a2b2fbe59c | Python | 10,240 | 275 | from typing import List, Optional, Union
import numpy as np
import torch
from anndata import AnnData
from spateo.alignment.methods.backend import NumpyBackend, TorchBackend, get_backend
# from .methods.morpho import con_K
from .methods import (
_chunk,
_data,
_dot,
_mul,
_pi,
_power,
_pro... |
b21e648e2c6a82f12c7f189d7f10006548c841119a4af0e81b5f1d1b86de2006 | Python | 10,240 | 301 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Hoverlabel(_BaseTraceHierarchyType):
_parent_path_str = "candlestick"
_pa... |
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