sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3316c26e4334fd8f005eeeff935f05fa7dd4e3300aba6a4f56a19ac2ba5d908b | Python | 3,116 | 77 | """
=====================================================================
Sample from the Riemannian Gaussian distribution in the SPD manifold
=====================================================================
Spectral embedding of samples from the Riemannian Gaussian distribution
with different centerings and disp... |
45ba596c2a838578c1ba680da8e645c88de2686c12822dbbabccfb281c8b1642 | Python | 3,116 | 67 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from ultralytics import SAM, YOLO
def auto_annotate(
data: str | Path,
det_model: str = "yolo26x.pt",
sam_model: str = "sam_b.pt",
device: str = "",
conf: float = 0.25... |
60c6789c0d2b91d24f4e75b3db0959ded4dea46d36c6a54097d00a9896acb2a7 | Python | 3,116 | 99 | # This example requires the following dependencies to be installed:
# pip install lightly
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import copy
import torch
imp... |
eb52883022e698baa15a9be4fce8f20abacfcc35b9a6a8068c53205eaaf46f40 | Python | 3,116 | 68 | """Consumer-case exit tests for Spec C: nested R=2 Ragged + string-under-axis.
Three real-world use-case shapes drawn from the shape survey
(genoray / GenVarLoader / genvarformer):
1. test_consumer_alleles_string_under_axis
(ploidy=2 flattened, ~variants) opaque allele strings -> chars (R=2).
2. test_consumer_fla... |
ca5145ed073fa9204805aa575e2e4ab94733c178f05554318cf4bf40cf07f942 | Python | 3,117 | 83 | from __future__ import division
import unittest
import numpy as np
from wyrm.types import Data
from wyrm.processing import calculate_signed_r_square
from wyrm.processing import swapaxes
class TestSelectClasses(unittest.TestCase):
def setUp(self):
# create noisy data [40 epochs, 100 samples, 64 channel... |
ec31d0f65282a043f3b0c37ecf85d613bb681180ec99b28fd384b86b28d6850f | Python | 3,117 | 74 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# Some parts of the code were referenced from or inspired by below
# - Tristan Bepler's code (https://github.com/tbepler/protein-sequence-embedding-iclr2019)
# PLUS
""" SecStr FASTA file loading functions """
import numpy as np
import torch
impo... |
47f4ed69f9b195783d0879c5869698b92f73a95ccd4cfb28a93e73f2bd67831c | Python | 3,118 | 103 | import numpy as np
from numpy.random import default_rng
import pathlib
from mpi4py import MPI
from causal_optoconnectics.tools import conditional_probability, joint_probability, roll_pad
from causal_optoconnectics.generator import (
construct_connectivity_filters,
construct_connectivity_matrix,
simulate,
... |
deb4811f80e7e03a3849af448e080e4f6fd238c98be1d12b88bd06df82514a6c | Python | 3,118 | 96 | # Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
from typing import Callable, Tuple, Union
import numpy as np
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.torchvision_v2_compatibility import functional as F
from lightly.transforms.torchvision_v2_compatibility... |
98662ac4af54a2982e854de57423f012c5565d0955b46c4841180588fb09eda2 | Python | 3,119 | 90 | from datetime import datetime
from unittest import mock
import dateutil.relativedelta
from api.mocks import FakeAuthContext
from carbonserver.api.infra.repositories.repository_runs import SqlAlchemyRepository
from carbonserver.api.usecases.run.experiment_sum_by_run import (
ExperimentSumsByRunUsecase,
)
EXPERIME... |
1daf18117e4757b09c5e5c9c680427a64002b03dfd58b022464292b03a6c44e2 | Python | 3,120 | 92 | # --- 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 Root(_BaseTraceHierarchyType):
_parent_path_str = "treemap"
_path_str = "... |
415f7815fcd9b20e10b02b2360c0d17cd10593e2265b3211d4686ff5567c66f7 | Python | 3,120 | 101 | """
Tests to make sure the dataload module isn't busted
"""
import os
import pytest
import numpy as np
import eugene as eu
from pathlib import Path
HERE = Path(__file__).parent
@pytest.fixture
def sdata():
"""
sdata
"""
sdata = eu.datasets.random1000()
eu.pp.ohe_seqs_sdata(sdata)
eu.pp.rever... |
a24345099deff5d637e647ffc79f135bc61e2209fd8eb4bcbd9e975e2b58676a | Python | 3,120 | 80 | try:
from pyscf import gto
from pyscf.dft.numint import eval_ao
except ImportError:
raise ImportError("You need to install pyscf to use this module")
import numpy as np
import numpy.typing as npt
from ase.data import chemical_symbols
class OrthoCoeffMatrixToMolecularOrbitals:
def __init__(
s... |
e26598645aabefaedebe8a56468088e56181472b923b23b698f40f7a5c2a46f4 | Python | 3,120 | 92 | # Copyright 2022 Deepfold Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writin... |
40cae8f01fc96f977ee2cff3ce6f1fab4b4b497e5eab479c4217e18dc1f0a97b | Python | 3,121 | 82 | """FLOORLEAK regression pins: test fixtures must not outlive the tests they serve.
Two session-pollution leaks flipped later tests red in the W051 backstops:
* ``tests/real_model/r0/conftest.py`` cached every realism-sweep model and its
finished ``Trace`` in a SESSION-scoped dict, so the traces' saved activations
... |
3906a22daa91d9a7686b7ba61097f333768e14527aed2353b72f3992f9c3a4c6 | Python | 3,122 | 104 | import logging
import yaml
import copy
import argparse
import numpy as np
from bson.objectid import ObjectId
from pymatgen.core import Molecule
from atomate.qchem.fireworks.core import SinglePointFW, ForceFW
from atomate.common.powerups import add_tags
from fireworks import LaunchPad, Workflow
from instance_mongo... |
5b9807f2ff08df4d8202025681c662fff575576567607ee77f602671723f7076 | Python | 3,122 | 141 | # 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 complian... |
24cf8e44499a12ab6bab41a7e123273ebb0b8809b21a85d6f5a5367606617727 | Python | 3,123 | 80 | import pandas as pd
import numpy as np
import torch
def atom_features(atom):
return np.array(one_of_k_encoding_unk(atom.GetSymbol(),['C', 'N', 'O', 'S', 'F', 'Si', 'P', 'Cl', 'Br', 'Mg', 'Na','Ca', 'Fe', 'As', 'Al', 'I', 'B', 'V', 'K', 'Tl', 'Yb','Sb', 'Sn', 'Ag', 'Pd', 'Co', 'Se', 'Ti', 'Zn', 'H','Li', 'Ge', 'Cu'... |
7c0ffb932f40ebdc40a4664c5b21271158553b427d9965d2825b7df9caf4947d | Python | 3,123 | 111 | """Helper methods for handling units in PyJibe"""
def si2hr(name, value, si_unit=None):
"""Convert an SI unit to a human readable unit
Parameters
----------
name: str
The parameter name string, see `human_units`.
value: numbers.Number or array
The value of the parameters that will... |
9a142abb27c4e5a92de9a01d91c92545dfed5638633c9eb8deadb8e21c4837a1 | Python | 3,123 | 91 | """Regression coverage for capture-wrapper unwrapping's common fast path."""
from __future__ import annotations
from collections.abc import Callable
from typing import Any
from unittest.mock import MagicMock
import torch
from pytest import MonkeyPatch
from torchlens import _state
from torchlens.utils import _callab... |
b2fdf38bb7806c4094c482249582c967b86a5a338e2b32005c285f495f01e2a2 | Python | 3,123 | 86 | import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from typing import Optional
from external_src.group_free_3D.models.multi_head_attention import MultiheadAttention
class TransformerDecoderLayer(nn.Module):
def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1, activati... |
6276da9f9701c83fc9cc33dba8f87b1695a320da9c8bbee99e5db78284776c9d | Python | 3,124 | 105 | # -*- coding: utf-8 -*-
# @Author : Yue Liu
# @Email : yueliu19990731@163.com
# @Time : 2022/9/21 0:38
import torch
import numpy as np
def numpy_to_torch(a, is_sparse=False):
"""
numpy array to torch tensor
:param a: the numpy array
:param is_sparse: is sparse tensor or not
:return a: torch... |
aad0993c9840299e2ce6a40dfd1d2d040b47016dddabc4be27b7db5d7cd7c5f5 | Python | 3,124 | 98 | import pickle
import cv2
import time
from ethoscope.hardware.interfaces.interfaces import HardwareConnection
from ethoscope.hardware.interfaces.sleep_depriver_interface import SleepDepriverInterface
obj = HardwareConnection(SleepDepriverInterface)
with open("/tmp/pickled.pkl", "w") as f:
pickle.dump(obj, f)
obj.s... |
43b3af2f1002e4107f53ea3381f05e1e7f8671cb013d6c9445bfacd5064f47aa | Python | 3,125 | 74 | """
Reference structure validation module.
author: gaojie01
"""
import json
from helixfold.data.templates_input import get_refer_structure_features
from helixfold.data.templates import Error as TemplateError
from infer_scripts.validation import ValidationException
def ref_structure_check(all_entities: list, kalign_bi... |
76eb8d829c47e590699d04fd78b0ab63a25c5c37a60892ecf7195aa31ab76127 | Python | 3,125 | 84 | import os.path
import numpy as np
CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
GENERIC_KWARGS = dict([
("write_images", False),
("export_images", True),
("image_export_format", "native"),
("image", os.path.join(CURRENT_DIR, "data", "ct_images_seg", "CRLM-CT-1004", "image")),
("mask", o... |
926a7a49445efd4ef407970e84f8ebdf0266d1f96d8b794fef42b0bc04e94cf8 | Python | 3,125 | 82 | from typing import Any, Optional, Union
from pl_bolts.datamodules.emnist_datamodule import EMNISTDataModule
from pl_bolts.datasets import BinaryEMNIST
from pl_bolts.utils import _TORCHVISION_AVAILABLE
class BinaryEMNISTDataModule(EMNISTDataModule):
"""
.. figure:: https://user-images.githubusercontent.com/46... |
a5a0527fa5b0e5468aa5adaddb2eea21d33e1a6a92aa2f812861c7a75316fb4b | Python | 3,125 | 92 | # --- 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 Root(_BaseTraceHierarchyType):
_parent_path_str = "sunburst"
_path_str = ... |
af750112361918c0186594545602e3d47cfec55ad8dcca33d0ae947194920587 | Python | 3,125 | 69 | """this script is used to prepare Otb2015 dataset for tracking,
which is Single Object Tracking benchmark"""
import argparse
import tarfile
import os
import time
import json
import numpy as np
from gluoncv.utils import download, makedirs
otb50 = ['Basketball','Biker','Bird1','BlurBody','BlurCar2','BlurFace','BlurOwl'... |
1003b01bb2d266bfe691bc8854ab3b379aef09066429aeccdbb437bb6ad6e991 | Python | 3,126 | 106 | from cmath import nan
import pickle
from matplotlib import pyplot as plt
from numpy.lib import math
from scipy.sparse.construct import rand
from ssm.plots import gradient_cmap, white_to_color_cmap
import seaborn as sns
import numpy as np
import os
import os
from scipy.io import savemat,loadmat
import os
from os import ... |
939317761b43d9df5a6d16085414f977b005f37cc49e892b398f346ce803dc13 | Python | 3,127 | 110 | def getDigitizerName(digitizerNumber):
digitizers = {
0: "Unknown",
1: "Demo",
2: "MiniDigi",
3: "DD132X",
4: "OPUS",
5: "PATCH",
6: "Digidata 1440",
7: "MINIDIGI2",
8: "Digidata 1550"
}
if (digitizerNumber in digitizers.keys()):
... |
86090fcce973070edae67676cb7b55fd1e56dc18d1398872636eb23152f9404c | Python | 3,128 | 86 | import numpy as np
import sympy as sp
import markov_builder
import pints
from . MarkovModel import MarkovModel
class ClosedOpenModel(MarkovModel):
def get_default_parameters(self):
return self.default_parameters
def __init__(self, voltage=None, times=None, Erev: float = None,
parame... |
5741b2c2dd9e3063d0b891bdb272ef0713b7262e11f348f1b1f543b7085ee4d0 | Python | 3,129 | 82 | """r-b4 R27-6a: chained selector composition stays flat and stack-safe.
``&``/``|`` built one binary composite per application, so
``functools.reduce(operator.or_, [tl.func(n) for n in five_hundred])`` made a
500-deep binary tree and blew the interpreter stack at trace entry. Chained
same-operator composition now accu... |
22d36eddf56daa6742fea9fbbd32f76ce25ab512f322d4bbac3e8b4c561da986 | Python | 3,130 | 80 | import pytest
import numpy as np
from causal_optoconnectics.core import Connectivity
from causal_optoconnectics.tools import compute_trials
def test_connectivity():
stimulus = np.arange(10, 510, 10).repeat(2).reshape((50, 2)).astype(float)
stimulus[:,0] = 3 # event id
A = stimulus + 1
A[:,0] = 0 # eve... |
8568472b0b0516bea6d60a66eb2cf1a8f01367ff5bacd1050f63791e1320c05e | Python | 3,130 | 64 | # Copyright 2019 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://w... |
02c1a4796887189b90e950d3a64a67c9372f497e3ba80364be27b1df3b91eeaf | Python | 3,131 | 82 | """F16 B6: the diagnostic frontier query (treescope memo F-E).
One injected NaN flags the whole downstream cone; the frontier is the
clean-to-dirty transition -- exactly one first-dirty site with its last
clean parent and first dirty child, in deterministic order.
"""
from __future__ import annotations
import torch
... |
b36929e4c52e9097d05a079e00c3a330a7cde2f5b484fdec18f5ce5412bb9b7a | Python | 3,131 | 61 | """Wrapper that autoreset environments when `terminated=True` or `truncated=True`."""
import gym
class AutoResetWrapper(gym.Wrapper):
"""A class for providing an automatic reset functionality for gym environments when calling :meth:`self.step`.
When calling step causes :meth:`Env.step` to return `terminated=... |
c5a657842a87883fbcaa4079fabc439549706d194d2eecf5c30df4b9c63baa6e | Python | 3,132 | 107 | from pathlib import Path
from typing import Dict
import torch
from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.callbacks import DeviceStatsMonitor
from pytorch_lightning.loggers import TensorBoardLogger
from torch.utils.data import DataLoader
from lightly.data import LightlyDataset
from l... |
c7cf6d7316508a491bd846ded79bd58e3e967759ddc5968a7e41a0405a01925a | Python | 3,132 | 91 | # 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... |
8bf35cff06ef85942be42fce0fde8e9332ed7964e449615352ccca9b67e19e22 | Python | 3,133 | 107 | from pathlib import Path
from typing import Dict
import torch
from pytorch_lightning import LightningModule, Trainer
from pytorch_lightning.callbacks import DeviceStatsMonitor
from pytorch_lightning.loggers import TensorBoardLogger
from torch.utils.data import DataLoader
from lightly.data import LightlyDataset
from l... |
dad858e6c580348e4a846aa7e18dbcd87198605ccfd3f9410c718b2d6f5c584c | Python | 3,133 | 91 | __author__ = 'quentin'
from ethoscope.core.monitor import Monitor
from ethoscope.trackers.adaptive_bg_tracker import AdaptiveBGModel, ObjectModel
from ethoscope.utils.io import SQLiteResultWriter
from ethoscope.hardware.input.cameras import MovieVirtualCamera
from ethoscope.drawers.drawers import DefaultDrawer
import ... |
e2f8ae6d8fc37ce2bfee35b3eebe656bb988af753bd6b1336aad54c926371cb6 | Python | 3,133 | 74 | """Minimal reproducer: cp.async.bulk (raw address) triggers racecheck hazard.
Warp 0 loads via cp.async.bulk, warp 1 reads from smem after mbarrier wait.
Pipeline is correctly synchronized but racecheck reports 1 error.
python AI/racecheck_repro_1d_bulk.py # correctness
CUTE_DSL... |
68795787f2d25cdb9b1e3d6cc496fa19c42f4b5a05d7638573a31ceb9ae4d192 | Python | 3,137 | 104 | # This example requires the following dependencies to be installed:
# pip install lightly
import pytorch_lightning as pl
import torch
import torchvision
from torch import nn
from lightly.models import utils
from lightly.models.modules import MaskedVisionTransformerTorchvision
from lightly.transforms.mae_transform imp... |
71a120264362ea5c056d124382b79b68fb024ab16d03f063929b09da9688ccda | Python | 3,137 | 80 | #!/usr/bin/python3
# Copyright (c) ByteDance, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import functools
import os
import socket
import subprocess
import sys
from typing impo... |
8975b71388b44f006ecdf76ae0dcd2383385ac2ab6c58a36cdf4e6ae65a42707 | Python | 3,137 | 91 | import numpy as np
from neurogym.core import TrialEnv
from neurogym.utils import spaces
class GoNogo(TrialEnv):
"""Go/No-go task.
A stimulus is shown during the stimulus period. The stimulus period is
followed by a delay period, and then a decision period. If the stimulus is
a Go stimulus, then the ... |
ada3395e2584077240e751f3b42eedfa8500cd37cb9e2a51e0434146f99a4b3c | Python | 3,137 | 103 | """Utility to dump events to screen.
This is a simple program that dumps events to the console
as they happen. Think of it like a `tcpdump` for Celery events.
"""
import sys
from datetime import datetime, timezone
from celery.app import app_or_default
from celery.utils.functional import LRUCache
from celery.utils.ti... |
c60ad3f10ad9ff0a1f8e154a20bc39d8f435795d09282e232160ba92e3b12116 | Python | 3,137 | 80 | """grind-r5 corroborated LOWs: belt sweep watermark + rescue warning routing.
* The belt's sweep watermark was a ``len(sys.modules)`` EQUALITY test, so a
same-length module-table mutation (del one key + insert another) skipped
the sweep and left a protocol-invisible stale
``from_numpy``/``frombuffer``/``as_subcl... |
08188058cc79810c0a8227f3b75b6d20adf4c52ceb54cf54ae309dbedb43d810 | Python | 3,138 | 88 | import numpy as np
import pandas as pd
from anndata import AnnData
from scipy.sparse import csr_matrix
from stlearn.spatial.sme._weighting_matrix import (
_PLATFORM,
_WEIGHTING_MATRIX,
impute_neighbour,
weight_matrix,
)
def sme_impute0(
adata: AnnData,
use_data: str = "raw",
weights: _WEI... |
5465cabb70c66d1950d9e3c6b18830a31e1dc341a0330047a917ddd161b1caa2 | Python | 3,138 | 95 | from __future__ import print_function
# to filter some unnecessory warning messages
import warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
import os
import numpy as np
import pandas as pd
import glob
import keras
from... |
b3ddc14206dcb7ee215352beaf5e2a471190861a3c1d1f2eeec97124b4226c8b | Python | 3,138 | 95 | from __future__ import print_function
# to filter some unnecessory warning messages
import warnings
warnings.filterwarnings("ignore", message="numpy.dtype size changed")
warnings.filterwarnings("ignore", message="numpy.ufunc size changed")
import os
import numpy as np
import pandas as pd
import glob
import keras
from... |
f6c39c2aa0a48ad3c2fdf92b851f57f1e6701701f1fb94ed66cf178a88c5f7de | Python | 3,138 | 74 | # 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... |
9186624e79335378627ec6bb920030cc69e9d95b1c8090ff7a3890729b165747 | Python | 3,139 | 102 | # This example requires the following dependencies to be installed:
# pip install "lightly[timm]"
# Note: The model and training settings do not follow the reference settings
# from the paper. The settings are chosen such that the example can easily be
# run on a small dataset with a single GPU.
import pytorch_lightn... |
64bac4b6fb10830a395e3678a80994cb1d763a0c79fdf3cfc86386cb333b699d | Python | 3,141 | 87 | import torch
from torch import nn
import torch.nn.functional as F
def make_model(args, parent=False):
return IDN(args)
class FBlock(nn.Module):
def __init__(self, num_features):
super(FBlock, self).__init__()
self.module = nn.Sequential(
nn.Conv2d(3, num_features, kernel_size=3, pa... |
7a7b9fde5806ea791a5e13ebe6bd462c7fcdc207dd364dacd75d9e7989a80096 | Python | 3,141 | 114 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
import numpy as np
from eelbrain import datasets, plot, testnd, cwt_morlet
from eelbrain.plot._figure import Figure
from eelbrain.plot._utsnd import _ax_bfly_epoch
from eelbrain.testing import requires_mne_sample_data
from eelbrain.testing import hide_plots
@h... |
e3f8ddfae2fc8700d5aa78ebcefa81d319dd0698086df3f36dd151d1f3d928a8 | Python | 3,141 | 77 | import numpy as np
def calculate_chain_pair_pae_matrix(pae_matrix, token_chain_ids,
mask_chain, mask_value=np.nan, metric_type='mean'):
"""
Compute a square matrix where each entry (i, j) is the minimum PAE between chains i and j.
Args:
pae_matrix (list or... |
1f37ebd8c828f6644237db83b7977c071f9fa67aac85c4ce8f5ea93fbe1b8a11 | Python | 3,142 | 124 | '''
Feature selector class
This file is a part of BdPy
'''
class FeatureSelector(object):
'''
Feature selector class
Parameters
----------
expression : str
Selection command
Attributes
----------
expression : str
Selection command
token : tuple
Tokens
... |
34d169d3cdd2b56f817646a268b6fba9c7e59cd484e3d44ad9e7f1e8995d9eae | Python | 3,142 | 90 | from permacache import permacache, stable_hash
import tqdm.auto as tqdm
import numpy as np
import matplotlib.pyplot as plt
from modular_splicing.data_for_experiments.standardized_sample import (
standardized_sample,
)
from modular_splicing.models.modules.lssi_in_model import LSSI_MODEL_THRESH
from modular_splicin... |
5c9bee936bc95495940de53b58202937524eb7b1a02d507f8576c10077c0b0ae | Python | 3,142 | 76 | import torch
from collections import OrderedDict
from torch import nn
from torch.nn import Linear,Dropout,BatchNorm1d,Sequential,LayerNorm
from torch.nn import Softplus,GELU,Tanh,SiLU
from torch.nn.init import xavier_normal_,zeros_,constant_
import numpy as np
class ResBlock(nn.Module):
def __init__(self, nl, drop... |
328f6a5ffa0487616f696807f83faebef1781c16a73893ac14ca9724f6b9aa3a | Python | 3,143 | 84 | # Backends based on https://github.com/chung-neuroai-lab/adversarial-manifolds
# Removed Backends that are not used in Feather et al. 2022
import numpy as np
import torch
from torch import nn
from collections import OrderedDict
from .modules import FakeReLU, SequentialWithArgs, FakeReLUM
# AlexNet Back-End architectu... |
67349e5aab04c74be4dac80a045d4806028e5878178be35c3837a693ebb9af97 | Python | 3,143 | 109 | from permacache import permacache, stable_hash
import tqdm.auto as tqdm
import numpy as np
from modular_splicing.lssi.utils import second_half_of_spliceai_cached
from modular_splicing.utils.run_batched import run_batched
from modular_splicing.models.modules.lssi_in_model import LSSI_MODEL_THRESH
from modular_splicing... |
effb50dc04cad27939754116a5aac9bf830d79d9e9e06286d76d177df0f59152 | Python | 3,143 | 102 | """Settings for plots."""
from collections import OrderedDict
import numpy as np
from matplotlib.colors import to_hex
from specparam.modutils.dependencies import safe_import
plt = safe_import('.pyplot', 'matplotlib')
##################################################################################################... |
2dc9f306647aae7886eef8aa87391eab1e8c4a245961ecf66b49ca0ee6156012 | Python | 3,145 | 82 | """An OpenAI-compatible chat completions endpoint served from the test process.
Point Galaxy's AI base URLs at it and Galaxy uses the real OpenAI client against a
scripted reply, so tests can assert on the request that actually reached the provider.
"""
import json
from typing import Any
from galaxy.util.unittest_ut... |
7c35d365d294872e4eaed885d9a67fd611b39f2db19d4fe90f3b556dbe2d004a | Python | 3,145 | 94 | import numpy as np
from mudcod.community_detection import MuDCoD, StaticSpectralCoD
from mudcod.network_simulations import MuSDynamicDCBM
from sklearn.metrics.cluster import adjusted_rand_score
T = 4
S = 4
# Multi-subject Dynamic DCBM
model_dcbm = MuSDynamicDCBM(
n=100, # Total number of vertices
model_order... |
0404242698762bb8d41139f0b8cf4d6d83af2c296e3b661e8bbf69448af9cce7 | Python | 3,146 | 92 | from typing import Optional, Tuple
import numpy as np
from numpy.fft import fftshift, ifftshift, fftn, ifftn
class Noiser:
def __init__(self, sigma: float = 0.01):
"""
Initializes the Noiser object with the given sigma value.
Args:
sigma (float, optional): The sigma value for... |
23ed9503a24765c11c2b0ceb4a5152d1b1e931dee2b0b1da192f0fd0e5b230b4 | Python | 3,146 | 47 | """Prepare COCO datasets
==============================
`COCO <http://cocodataset.org/#home>`_ is a large-scale object detection, segmentation, and captioning datasetself.
This tutorial will walk through the steps of preparing this dataset for object tracking in GluonCV.
.. image:: http://cocodataset.org/images/coco-... |
5fae15bc63cbd806d444ac1846c5893975c60183a217fbf6aa2c5e4e40142ee5 | Python | 3,146 | 86 | # This file originally from pip:
# https://github.com/pypa/pip/blob/8f4f15a5a95d7d5b511ceaee9ed261176c181970/src/pip/_internal/utils/glibc.py
from __future__ import absolute_import
import ctypes
import re
import warnings
def glibc_version_string():
"Returns glibc version string, or None if not using glibc."
... |
ac338a1af6dab201ea3c745a1ffde0989905a6b375c7aa65076d52477d790e94 | Python | 3,146 | 108 | import errno
import socket
from unittest.mock import Mock, patch
import pytest
import t.skip
from celery.contrib.rdb import Rdb, debugger, set_trace
from celery.utils.text import WhateverIO
class SockErr(socket.error):
errno = None
class test_Rdb:
@patch('celery.contrib.rdb.Rdb')
def test_debugger(se... |
ed965a8dcfbfb130fdf71cfda810a51a7d92a11c2b33d4401492416120fd49ab | Python | 3,146 | 105 | """File I/O for specific file types."""
import io
import json
from json import JSONDecodeError
from specparam.io.utils import create_file_path
from specparam.utils.convert import dict_lst_to_array
###################################################################################################
####################... |
0142a5ba618665710e55cc2f66e3c29e2cd74ef3e620f52e54087c13fa4192a2 | Python | 3,149 | 89 | from io import StringIO
from pathlib import Path
import numpy as np
import pandas as pd
import pysam
import pytest
from anndata import AnnData
from scipy.sparse import csr_array
import muon.atac as ac
@pytest.mark.parametrize("empty_distance", [True, False])
def test_add_peak_annotation(empty_distance: bool) -> Non... |
a8cfc9454dd098f2d65bad6bd2fd3ae6d8e6bcf574eaa5da95cafda0e6af91ae | Python | 3,149 | 95 | import warnings
import os
import tempfile
import unittest
import arviz as az
import logging
from pmsurv.models.weibull_nn import WeibullModelNN
import tests.syntheticdata
from pathlib import Path
warnings.simplefilter("ignore")
logger = logging.getLogger(__name__)
class TestWeibullNN(unittest.TestCase):
def te... |
299ccc292e482df0bf274163e4c16510e2fb67d9ce9e545fa384e719d5c43d66 | Python | 3,150 | 65 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
""""tests for cycles.py"""
import unittest
import numpy as np
from scipy import sparse
from sknetwork.data import star_wars, house, cyclic_digraph, cyclic_graph, linear_digraph, linear_graph
from sknetwork.topology import is_connected, is_acyclic, get_cycles, break_cycle... |
15a013fc032cfaabbe8e5e7fd1f37fee965d5216a0d2493ce166865b4f296709 | Python | 3,151 | 78 | import warnings
import pytest
from absl.testing import parameterized
from keras.src import backend
from keras.src import testing
from keras.src.backend import config
from keras.src.testing.test_utils import x64_mode_scope
X64_SUPPORTED = backend.backend() in config._X64_BACKENDS
class X64ModeTest(testing.TestCase)... |
a68bff6480b4ae1a9c53fc6c9f881c74170c2562280ccd885f9d0d80984afacf | Python | 3,151 | 90 | import numpy as np
import pandas as pd
from anndata import AnnData
from natsort import natsorted
from sklearn.cluster import KMeans
def kmeans(
adata: AnnData,
n_clusters: int = 20,
use_data: str = "X_pca",
init: str = "k-means++",
n_init: int = 10,
max_iter: int = 300,
tol: float = 0.0001... |
32edbbd29936299f7a0446efca8247ca5a589a92ff8130b89e7e80e320ddde23 | Python | 3,152 | 95 | """Position feed-forward network from "Attention is All You Need"."""
import torch
import torch.nn as nn
class ComplexLinear(nn.Module):
def __init__(self,n_blocks,d_per_block):
super(ComplexLinear, self).__init__()
self.weight = nn.Parameter(torch.randn(n_blocks,d_per_block,d_per_bl... |
12d6ac058be9f287e9aee29ed356da5477372f07dbaf7815ec8084725c7e2049 | Python | 3,153 | 78 |
'''
Note: reference frames in numpy and opencv2
[x,y] in numpy array:
x = row; y = col
***********************************
* [0,0] → increasing y → [0,ncol] *
* ↓ *
* increasing x *
* ↓ *
* [nrow,0] [nrow,ncol] *
****************... |
5ebc4f6825923e38efcb202583e1b34326379ab6247c45c12b8ed6a68f2502af | Python | 3,154 | 114 | from __future__ import print_function, division, absolute_import
import math
import torch
import torch.nn as nn
import torchvision.transforms as transforms
from PIL import Image
from munch import munchify
class ToSpaceBGR(object):
def __init__(self, is_bgr):
self.is_bgr = is_bgr
def __call__(self, te... |
63b45ab7753ce24f033f641db6eb97b8956d758a9b3b32bcac885852d664ee4c | Python | 3,154 | 84 | """One-time recording sweep over the postprocess axes matrix.
Runs every axis of ``tests/support/postprocess_axes.py`` with the combined
read+write audit in RECORD mode and dumps the per-step observation unions as
JSON. The output is EVIDENCE for seeding the declared ``reads`` sets and the
four-category findings revie... |
6e2bb9a20137b29718835a690b663e5c01eeb61b981e292deb5fd919f7f3e203 | Python | 3,154 | 90 | import os
from typing import (
Annotated,
)
from fsspec.implementations.local import LocalFileSystem
from pydantic import Field
from galaxy.files.models import (
FilesSourceRuntimeContext,
StrictModel,
)
from galaxy.util.config_templates import TemplateExpansion
from ._fsspec import (
CacheOptionsDict... |
408a92e38714508747b1726ba4aaea901db222b10d0f2d862361607048a6a3b1 | Python | 3,155 | 87 | """Module for build dynamic fields."""
from collections import Counter, defaultdict
import torch
from bioseq2seq.utils.logging import logger
from bioseq2seq.utils.misc import check_path
from bioseq2seq.inputters.inputter import get_fields, _load_vocab, \
_build_fields_vocab
def _get_dynamic_fields(opts):
# NO... |
9bc7cf46a1c75869f7116f6023b4c4b57ccd5c257ffd5d49f66965e38c0e9898 | Python | 3,157 | 111 | import numpy as np
import dgl
import torch
import torch.nn.functional as F
import h5py
import sys
sys.path.append('../pkgs/graph-sc/')
import train
import models
device = train.get_device()
import warnings
warnings.filterwarnings("ignore", category=FutureWarning)
import scanpy as sc
from scbig.utils import setup_seed
i... |
b8cf3b7fc78fcdfc7b520139115a8ec0945e594c1b18cc367f06b621e7db240c | Python | 3,157 | 100 | import subprocess
import sys
import textwrap
from pathlib import Path
import example_models
import pytest
import torch
import torchlens as tl
from torchlens import trace as trace_fn
from torchlens.experimental import dagua
def test_dagua_renderer_requires_experimental_opt_in() -> None:
"""Core renderer rejects ... |
d4a6a64a8e6886157c4bedbfd89ad453a56f897a71869251c9f21b48cb541a7e | Python | 3,157 | 96 | import torch
import torch.nn as nn
from modular_splicing.models.entire_model.modular_predictor import (
ModularSplicePredictor,
)
from modular_splicing.models.motif_models.types import motif_model_types
from modular_splicing.models.modules.lssi_in_model import (
LSSI_MODEL_THRESH,
load_individual_lssi_mode... |
67af9dde601a34740d13b92ab212dbdb3b8584416b006dcc3c967591ec683a5b | Python | 3,158 | 104 | #!/usr/bin/env python3
"""
Test script comparing CPU-only (package) vs CPU+DRAM power measurement.
This shows how rapl_include_dram=True gets closer to powerstat's readings.
"""
import subprocess
import time
from codecarbon.core.cpu import IntelRAPL
from codecarbon.core.units import Time
print("=" * 80)
print("Testi... |
8a65f9eb1fcd399d23090f56ba01919f39b0a2e6bed946821cb04a1cb2407b53 | Python | 3,158 | 79 | from ovseg.preprocessing.SegmentationPreprocessingV2 import SegmentationPreprocessingV2
from ovseg import OV_PREPROCESSED
import os
# name of your raw dataset
data_name = 'MY_DATASET_NAME'
# name after preprocessing
preprocessed_name = 'MY_PREPROCESSED_NAME'
# whether to apply resizing, pooling and windowing during p... |
20796c7495de1ea3d4f3f4819b87885ee6b9661c91200507e1c02d54d351ecd8 | Python | 3,160 | 62 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on March 2019
@author: Thomas Bonald <bonald@enst.fr>
"""
import unittest
from sknetwork.data.test_graphs import *
from sknetwork.data import cyclic_graph
from sknetwork.hierarchy import Paris, LouvainIteration, dasgupta_cost, dasgupta_score, tree_sampling_di... |
86c4c25fe65c9a48c4b412f5e515058a1810ac4e18dd50bcca6b418c72d485b2 | Python | 3,160 | 103 | """Analyse the edge weights for gene to gene interactions"""
from posixpath import split
from pprint import pprint as pp
def get_edge_per_TR(mapfile):
from numpy import mean, median, std, percentile
outfile = open(mapfile.replace('.', '-edge_weight_stats80th.'), 'w')
open_map = open(mapfile)
# again,... |
de1c1157b62722c22d4e4c3f81db5e0d41175087e92111361482b29cda9f1a15 | Python | 3,160 | 81 | """Models that incorporate tacticity in one way or another"""
# TODO document better
import nfp
import keras
import tensorflow as tf
from keras import layers
# TODO switch order of model_summary
def pm_model(preprocessor, model_summary, prediction_columns, params):
# Define the keras model
# Input layers
... |
225af6a122ce7831b96ae56104a2fc28fed25a141bda8cff9ce3193a101b0832 | Python | 3,161 | 82 | """Provides a generic testing environment for use in tests with custom reset, step and render functions."""
import types
from typing import Any, Dict, Optional, Tuple, Union
import gym
from gym import spaces
from gym.core import ActType, ObsType
from gym.envs.registration import EnvSpec
def basic_reset_fn(
self,... |
8bad573b05a218aca686596c00ed7e75a10532a82ec58cd5fdbad37411297ff8 | Python | 3,161 | 94 | # Copyright 2024 The Google Research Authors
#
# 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 agree... |
d4249cd80154acb03e47d29e99795b480d8fe64350dd9f1e000e311314c8f0ce | Python | 3,162 | 78 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from ultralytics.utils import LOGGER
def onnx_calibration_reader(dataset, transform_fn, input_name: str = "images"):
"""Create an ONNX Runtime calibration data reader from an Ultralytics calibration dataloader.
Args:
dataset (Iterab... |
4c21d605b3aab316586c39111d962969c68f1ff4deeac0549dfca29ccb64c2b0 | Python | 3,164 | 62 | import numpy as np
import torch
from scipy.spatial.distance import cdist
from scipy.spatial.transform import Rotation
def apply_data_augmentation_to_object_pcs(object_points, config=None):
if config is None:
config = {'brightness': 0.1, 'colors': 0.05, 'x_rot': 20, 'y_rot': 45, 'z_rot': 20, 'shift': 0.15,... |
10cabeada91e57120a8a16bde73578c0cdea24fc99341c1752a51d186bd56237 | Python | 3,165 | 100 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Provide utility functions to read output files generated by PLUMED.
"""
# ====================================... |
508b0094bb4fc64c68e6fd714e1fb9cda5e0f2f36668a91dedb13ca69375c83b | Python | 3,165 | 73 | #!/usr/bin/env python3
import os
from argparse import ArgumentParser
def main():
"""
This is a utility script created to work with the ThermoNet ddG prediction protocol.
It takes a given list of variants and the path to the Rosetta binary. It runs the
Rosetta binary to create a structural model for e... |
6afd5cf0a2ab910789ff2b3b42d9dcda1498945f3e6cd0aad3305db1e3d8b860 | Python | 3,165 | 109 | # This example requires the following dependencies to be installed:
# pip install lightly
import torch
import torchvision
from torch import nn
from lightly.models import utils
from lightly.models.modules.masked_vision_transformer_torchvision import (
MaskedVisionTransformerTorchvision,
)
from lightly.transforms.m... |
ff6aa130ada42f6c78afa6e77a559c98436484369e2f74b029275563b0752c80 | Python | 3,165 | 83 | # ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.16.0
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# # Setup
# ... |
bc4c8ef6d14a86147a169ba9d6fdcbef2da37e668099348944279d572e0bde13 | Python | 3,166 | 96 | # 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... |
f04926cafc8bcceec7a8b7a2baeeb4ded62daa9f265c55351176b399c8bc91e3 | Python | 3,166 | 89 | import os
import warnings
from math import sqrt
import h5py
import numpy as np
import pandas as pd
import scanpy as sc
from scipy.stats import pearsonr,spearmanr
from sklearn.metrics import mean_squared_error
from scbig import run_scbig, preprocess, setup_seed
warnings.filterwarnings('ignore')
for sparity in ['0.8'... |
2a92526ed147119883612aa26c4f7fae717d10dabfc03bb354c3ae1160549a16 | Python | 3,168 | 109 | """Collect together library of available built in metrics."""
from specparam.metrics.metrics import Metric
from specparam.metrics.error import (compute_mean_abs_error, compute_mean_squared_error,
compute_root_mean_squared_error, compute_median_abs_error)
from specparam.metrics.gof ... |
418512c2eb42b21c080164e14ea8798177cfb5333654a13fa1f662d283b963e4 | Python | 3,168 | 91 | """Admin CLI for the GTN search database.
Run as ``python -m galaxy.gtn --refresh`` from within a Galaxy
virtualenv to force-redownload the published database. The CLI resolves
``gtn_database_path`` from Galaxy configuration unless ``--path`` is supplied.
"""
import argparse
import logging
import os
import sys
from p... |
55844414609f0770a2dd64ebc3b5b51248a10741fa8459eaed810f180a2e2f77 | Python | 3,168 | 99 | """SiamRPN network
Code adapted from https://github.com/STVIR/pysot"""
# coding:utf-8
# pylint: disable=arguments-differ,unused-argument
from mxnet.gluon.block import HybridBlock
from mxnet.context import cpu
import mxnet as mx
from gluoncv.model_zoo.siamrpn.siam_alexnet import alexnetlegacy
from gluoncv.model_zoo.siam... |
936e9492c33a60ee0dffca9b69ac3bbfb9f300d020e5d2e9d2053c5ae89863fc | Python | 3,170 | 102 | import importlib.util
import json
from pathlib import Path
import pytest
SCRIPT = (
Path(__file__).resolve().parents[1]
/ "codecarbon/data/private_infra/update_usa_emissions.py"
)
DATA = (
Path(__file__).resolve().parents[1]
/ "codecarbon/data/private_infra/2023/usa_emissions.json"
)
# The script is ... |
cde69d4bf2a1e78de456f52ccf72197439dd84faa16761f9f2e5d74ab4101c52 | Python | 3,170 | 91 | """Prepare ADE20K dataset.
========================
`ADE20K <http://sceneparsing.csail.mit.edu/>`_ is a scene-centric containing
20 thousands images annotated with 150 object categories.
This tutorial help you to download ADE20K and set it up for later experiments.
.. image:: http://groups.csail.mit.edu/vision/datase... |
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