sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
e4c5e53868e0f69111bd0b627d70eda64e7366b14f3813243bebba5bc29fbbf0 | Python | 7,598 | 231 | """Entrypoint for the `ome_zarr` command-line tool."""
import argparse
import logging
import sys
from .csv import csv_to_zarr
from .data import astronaut, coins, create_zarr
from .format import CurrentFormat, Format, format_from_version
from .utils import download as zarr_download
from .utils import finder as bff_fin... |
764898217fb1cdd93a6c6f7725080e712223de26f75305e6420647fd19988824 | Python | 7,601 | 179 | import tensorflow as tf
import numpy as np
import os
import tensorflow_datasets as tfds
from tensorflow.keras import datasets, models
from cvnn.initializers import ComplexGlorotUniform
from cvnn.layers import ComplexDense, ComplexFlatten, ComplexInput
import cvnn.layers as complex_layers
from cvnn import layers
from pd... |
620c915d470e53f364a2213d91e1f68e5c4b57729da87e5ae50c41730d7ba274 | Python | 7,602 | 170 | """
MXNet implementation of SMOT: Single-Shot Multi Object Tracking
https://arxiv.org/abs/2010.16031
"""
import os
import argparse
import logging
import numpy as np
import cv2
from gluoncv.model_zoo.smot import smot_tracker as Tracker
from gluoncv.model_zoo.smot.tracktors import GluonSSDMultiClassTracktor
parser = a... |
201f2434e6436a8d014e5ebd8b74ecd7db92706226c61725a63fa2c5ec812029 | Python | 7,607 | 244 | import sys
sys.path.append("/home/rzhu/Documents/edamame/")
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import nptdms
import os
from edamame import *
# from edamame.analysis.InfoTheory import *
from scipy.io import loadmat
from dask.distributed import Client
import mkl
from IPython.core.de... |
c53d8f9759bdaa6e54ad8369d0078c6ceeb549842c7674b7dea5c4e7d75a0398 | Python | 7,607 | 190 | """Plots for trial related measures and analyses."""
import numpy as np
from spiketools.utils.base import flatten
from spiketools.utils.options import get_avg_func, get_var_func
from spiketools.plts.settings import DEFAULT_COLORS
from spiketools.plts.annotate import add_vlines, add_vshades, add_significance
from spik... |
e753deb60549af5227ca6978bb44c9903026d68d1f30d824e76fe57a0fc2a243 | Python | 7,607 | 202 | from dataclasses import dataclass
from typing import Tuple
import torch
from PIL import Image
from torch import nn
from lightly.transforms.torchvision_v2_compatibility import functional as F
from lightly.transforms.torchvision_v2_compatibility import torchvision_transforms as T
@dataclass
class Location:
# The ... |
fedffd591479a5de1e9265b98678c861a5f07f8561a60a0169ea4205d30d5cfe | Python | 7,607 | 204 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created in July 2019
@author: Nathan de Lara <nathan.delara@polytechnique.org>
@author: Thomas Bonald <thomas.bonald@telecom-paris.fr>
"""
from typing import Union, Optional, Tuple
import numpy as np
from scipy import sparse
from sknetwork.linalg.normalizer import no... |
0249db51e7492b3f03bec95f19036332f5648aae5c29aaddb9ecde8364c2b6e6 | Python | 7,608 | 216 | import importlib
import pickle
import unittest
import numpy as np
from densratio import densratio
class RCompatibilityTestSuite(unittest.TestCase):
"""Baseline checks ported from the R package tests."""
def setUp(self):
rng = np.random.RandomState(314)
self.x = rng.normal(loc=1, scale=1.0 /... |
882899430119f99c03b8d00a317c95d56a9b778035539d1990301fedd77150e3 | Python | 7,608 | 208 | from collections import OrderedDict
import cv2
import numpy as np
from skimage import img_as_ubyte
from skimage import color
import re
import subprocess
import openslide
class FileHandler(object):
def __init__(self):
"""The handler is responsible for storing the processed data, parsing
the metada... |
b8590c45fb2457fe8e6814b766e2b8d3c5d66f2a628528a5577e4a9a696b0ef5 | Python | 7,608 | 193 | """Real-model Model Explorer regressions (memo section 5; heavy tier).
The id bug survived THREE rounds of toy validation -- capture-side
recurrence folding rescued every toy -- so the id-uniqueness regression, the
158/158 edge-resolution case, model-mode receipt discipline, and the worker
floors are pinned on real to... |
e0c31566e6d975873c63d49036f8ff58243cdf66046215ea578d420b4b260847 | Python | 7,609 | 229 | """
This module holds the core function of pynapple as well as
the dispatch between numba and jax.
If pynajax is installed and `nap.nap_config.backend` is set
to `jax`, the module will call the functions within pynajax.
Otherwise the module will call the functions within `_jitted_functions.py`.
"""
from typing impor... |
66b424b6410b1346d990875f99ca7e9cb15b16a4026af825b1a35ea55306065c | Python | 7,611 | 229 | import datetime
import glob
import os
import subprocess
import sys
from pathlib import Path
from ruamel.yaml import YAML
from pipeline_utils import create_config, extract_sync, find
from registration.registration_spikeinterface import registration as registration_function
from sorting.sorting_kilosort import sorting as... |
7ed383fcd933fe9571d8311ffcb7177c7e37939b565543c15177e3c0bd8917ea | Python | 7,611 | 165 | import argparse
import torch
import torch.backends.cudnn as cudnn
from torchvision import models
from data_aug.contrastive_learning_dataset import ContrastiveLearningDataset
from models.resnet_simclr import ResNetSimCLR
from simclr import SimCLR
import torchvision
import sys
import numpy as np
import os
import yaml
imp... |
0dfce237211e0e2b25c8fae31eba231dd5b3e241ffae8ef682dcabd285fc2fdf | Python | 7,612 | 205 | """Bounded single-worker write pipeline behind the async streaming bundle writer.
``BundleStreamWriter`` submits prepared blob-write jobs here so the slow parts
of a streamed disk save (safetensors serialization, the page-cache write, and
the sha256 integrity hash) overlap forward capture instead of pausing it. The
en... |
47bb24f6676d87647eec152cb733e4f4de0123d712d8935bd6826017ebb11974 | Python | 7,612 | 234 | import torch
#from flash_attn_interface import flash_attn_func, flash_attn_varlen_func, flash_attn_with_kvcache
import flash_attn_interface as fa3
import flash_attn as fa2
import torch.utils.benchmark as benchmark
import time
import argparse
import math
parser = argparse.ArgumentParser(description='Process some integ... |
61566de65157e9e60aca72761fb17bb850cddb4d0bbf80f78e7aeb9559bb8699 | Python | 7,612 | 177 | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import welch
import matplotlib
matplotlib.rcParams['path.simplify'] = True
matplotlib.rcParams['path.simplify_threshold'] = 1.0
matplotlib.rcParams['agg.path.chunksize'] = 10000
# import matplotlib.style as mplstyle
# mplstyle.... |
34251017fb6d3ce7555b0fc4f012e615424c0323617c3d3f79421d77540e84b9 | Python | 7,614 | 204 | #!/usr/bin/env python
"""
Temperature alert monitor for Ethoscope sensor system.
Monitors sensor temperatures against configurable thresholds and sends
alerts through the notification system when thresholds are crossed.
Implements "alert once" behavior - alerts are sent when a threshold is
first crossed, then suppres... |
357641016c5efa6af04893d08af86ece39f997b044db4fc37ac5c04ff9af2cc2 | Python | 7,614 | 205 | import numpy as np
import pytest
import tensorflow as tf
from absl.testing import parameterized
from keras.src import backend
from keras.src import layers
from keras.src import testing
from keras.src.backend.common import standardize_dtype
from keras.src.testing.test_utils import named_product
class HashedCrossingTe... |
351249f46253983d848001e4fcac695fa60dbb22c12a7b6243525593adbe79d0 | Python | 7,617 | 210 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.optim import Adam
import scipy.sparse as sp
import numpy as np
def sparse_to_tuple(sparse_mx):
if not sp.isspmatrix_coo(sparse_mx):
sparse_mx = sparse_mx.tocoo()
coords = np.vstack((sparse_mx.row, sparse_mx.col)).... |
ec786543b642751ee355aad6258e85662e85d9e5e50adb6bd115299e81638900 | Python | 7,617 | 249 | """
Helper functions for some special plot kinds
"""
import numpy as np
import matplotlib as mpl
from matplotlib import pyplot as pl
from ..core import ifnot
_gridshapes = {4:(2,2),
5:(2,3),
6:(2,3),
7:(2,4),
8:(2,4),
9:(3,3),
... |
aae03ac7ed142e9df5fcd345f5d1a567e0c648e8e9ac2a95a79f7fd067a78e37 | Python | 7,621 | 202 | """
Manager and Serializer for Roles.
"""
import logging
from sqlalchemy import select
from sqlalchemy.exc import (
MultipleResultsFound,
NoResultFound,
)
from galaxy import model
from galaxy.exceptions import (
Conflict,
InconsistentDatabase,
InternalServerError,
ObjectNotFound,
RequestP... |
1058e79ddd841d77e75891b5d4aed5921c9f6859998496d8e8b99c228c283343 | Python | 7,624 | 224 | """Helpers for vizualization."""
import numpy as np
from ..embedding import SpectralEmbedding, LocallyLinearEmbedding
def plot_embedding(X,
y=None,
*,
metric="riemann",
title="Embedding of covariances",
embd_type='Spectral'... |
7ca7400b2561ee629395e4a8b8544df2b578352bad71e4dac472a761fd97c452 | Python | 7,624 | 189 | #!/usr/bin/env python
# coding: utf-8
import numpy as np
import pycuda.gpuarray as gpuarray
from pycuda.compiler import SourceModule
def _build_kernel():
code = """
__global__ void Funktion(int *match, float *verts1, float *verts2, int *arr1, int *arr2, int xsh1, int ysh1, int zsh1, int xsh2, int ysh2, int zs... |
2c8c5640929da5fd95f2f0b5d93f9c11b79f419ebca28d7c92bebe205d7f072c | Python | 7,625 | 190 | import copy
import inspect
import itertools
import string
import warnings
from keras.src import tree
from keras.src.backend.common.stateless_scope import StatelessScope
from keras.src.export.saved_model_export_archive import (
BaseSavedModelExportArchive,
)
from keras.src.utils.module_utils import tensorflow as tf... |
b2483097655ef9f9f5a8c82ed4c3c8524bd273173735afd776675070e2c4ccaa | Python | 7,626 | 191 | """Orphan backward-hook fixture: the defensive contracts, provoked on purpose.
TorchLens hooks every discovered grad_fn (posthook + prehooks). A hook is
ORPHANED when it is armed but never fires in a pass, or fires after its pass
closed. Both conditions are deterministically constructible with public torch
APIs — no v... |
185aad32540be3999f3221a7d8463bbb646383b8035bbd0dbdcea0c43fe4dd22 | Python | 7,629 | 187 | import glob
import pylab as pb
import os
from collections import defaultdict
import numpy as np
import argparse
import pandas as pd
import seaborn
from scipy.stats import mannwhitneyu, ks_2samp, ttest_ind
from tqdm import tqdm
from mp_dip.utils.utils import get_all_atoms, read_raw, preanalyse_raw, get_mp_book_paths
... |
f30a68b155f5d45672824ec0888e9245dd0085cdad8bbb49b262bdfc74d0231b | Python | 7,630 | 228 | import os
import subprocess
import tempfile
import numpy as np
from modular_splicing.dataset.additional_data import AdditionalData
from modular_splicing.utils.construct import construct
from modular_splicing.utils.sequence_utils import draw_bases
from permacache import permacache, stable_hash, drop_if_equal
error =... |
78f3990042db6a9864e5236c052e3980ddb79a2d42b2ea2c0c0929a33f2a7329 | Python | 7,631 | 206 | '''
Data manager script with helper classes for neural system identification
Author: Santiago Cadena
Last update: April 2019
'''
import pickle
import inspect
import os
from numpy import *
import numpy as np
PATH = os.path.dirname(os.path.dirname(inspect.stack()[0][1]))
DATA_PATH = os.path.join(PATH, 'Cadena_PlosCB1... |
fc42b1ec32bde06823d5a5383ec10713807f0a5afaa88d397f682798a6da7c26 | Python | 7,631 | 322 | """
Mapping of the R library "grid" for graphics.
The R library provides a low-level coordinate
system and graphic primitives to built visualizations.
"""
import warnings
import rpy2.rinterface as rinterface
import rpy2.robjects as robjects
import rpy2.robjects.conversion as conversion
from rpy2.robjects.packages i... |
1cc78418e095b671b7a85c8061d2fac29aea62dae2e9984da2d2fb30a7f865d9 | Python | 7,632 | 235 | """
Ported to pytorch thanks to [tstandley](https://github.com/tstandley/Xception-PyTorch)
@author: tstandley
Adapted by cadene
Creates an Xception Model as defined in:
Francois Chollet
Xception: Deep Learning with Depthwise Separable Convolutions
https://arxiv.org/pdf/1610.02357.pdf
This weights ported from the Ke... |
5e28e85a4ccf60ae1fc86957cb5149aa64c986fc282681997e3999e122b8eb74 | Python | 7,634 | 179 | """
Aperiodic Parameters
====================
Exploring properties and topics related to aperiodic parameters.
"""
###################################################################################################
from scipy.stats import spearmanr
from specparam import SpectralModel, SpectralGroupModel
from specpa... |
c0940401ac4d25ff1129a6886a980eb71b20153215f4af25bd86b61758b89961 | Python | 7,634 | 149 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# PLUS
import os
import sys
import argparse
import torch
import plus.config as config
from plus.data.alphabets import Protein
import plus.data.solubility as solubility
import plus.data.dataset as dataset
import plus.model.plus_rnn as plus_rnn
im... |
e7af0f2fdbf90c342d2fa60399a0fbbcf34a4514ab924de7d8517030f628fbbd | Python | 7,634 | 172 | """Closed ledger of sanctioned in-place op-lane writers (r7 R03-1).
The producer contract says the op lane is append-only with post-commit
knowledge riding the typed amendment lane -- but the fastlog ancestry-closure
backfill legitimately REPLACES op-lane cells in place on the ``copy_for_replay``
projection a cook own... |
874b94f83c6c98253797b9f8517e0d513f9d26ab200965822b2474a44448f6cd | Python | 7,635 | 178 | import os
import sys
from pathlib import Path
from platform import python_version
import gc
import inspect
from copy import deepcopy
#from imp import reload
import dill
# Custom modules
tr = "" # abs path to workdir
sys.path.append(tr)
import src
from src.models.tree_utils import *
from src.models.ml... |
863186f25705b2ab795d6e1a0b625ce717f7e232e5b95d1545a10ccc75e2bbc1 | Python | 7,637 | 257 | import matplotlib
import numpy as np
import pytest
from packaging.version import Version
from ..exporter import Exporter
from ..renderers import FakeRenderer, FullFakeRenderer
import matplotlib.pyplot as plt
def fake_renderer_output(fig, Renderer):
renderer = Renderer()
exporter = Exporter(renderer)
expo... |
d8e6ed05f309e8f5f6d199eec702e48fdf9c84bcbbdefa7cda0035265286e17c | Python | 7,637 | 211 | #works for
# pandas==0.25.1
# numpy==1.17.2
# scikit-learn==0.21.3
# Theano==1.0.4
# tqdm==4.36.1
# pickle==4.0
####
#Code tested on my machine;
######################
from cox_nnet_v2 import *
import numpy
import sklearn
import sklearn.model_selection
import pandas as pd
import time
from sklearn.preprocessing impor... |
dd3598af9ea0aef1069adfa0ced6bb6b28cb94481250800081bb4ae769cec324 | Python | 7,637 | 240 | """Tests for ``tl.debug`` diagnostic helpers."""
from __future__ import annotations
import builtins
import inspect
from typing import Any
import pytest
import torch
from torch import nn
import torchlens as tl
class NanModel(nn.Module):
"""Tiny model that creates a known non-finite op."""
def forward(self... |
469eee0cd235c8cb09bf812821988561dac2b0b8db1b3a61d374d0f8c7949fa4 | Python | 7,638 | 211 | #works for
# pandas==0.25.1
# numpy==1.17.2
# scikit-learn==0.21.3
# Theano==1.0.4
# tqdm==4.36.1
# pickle==4.0
####
#Code tested on my machine;
######################
from cox_nnet_v2 import *
import numpy
import sklearn
import sklearn.model_selection
import pandas as pd
import time
from sklearn.preprocessing impor... |
9c6dceddbd3fca28e864e009ab6c1fef364eff612b2fb0a3bdb5665555a72d51 | Python | 7,638 | 166 | """
Gregory Way 2017
PanCancer Classifier
tcga_util.py
Usage: For import only
"""
def get_args():
"""
Get arguments for the main pancancer classifier script
"""
import argparse
parser = argparse.ArgumentParser()
parser.add_argument('-g', '--genes',
help='Comma sep... |
41d359166cd7e0bab089c5b444ac5a04971a14e906fa04070ff45dd6f90fc6a6 | Python | 7,639 | 151 | # https://www.kaggle.com/code/vidushibhatia/2-ultrasound-nerve-seg-unet-from-scratch
# https://colab.research.google.com/gist/kumarikanak/254381203742483cbe0ddce4f64945e6/u-net-implementation.ipynb#scrollTo=f5i7Thf4FDFG
# for bulding and running deep learning model
import tensorflow as tf
from tensorflow.keras.layers... |
591b60a716e08b03c70cdfcca29feebd9324d2121443b75615bd117fb0ae159f | Python | 7,640 | 233 | import os
from tensorflow.keras.utils import to_categorical
from sklearn.preprocessing import LabelEncoder
from sklearn.utils import shuffle
from sklearn.metrics import classification_report
from spektral.layers import GCNConv
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, Dropou... |
c9402ff31f80dab81dcfb03fcd35fdbda4649e380f860de29f0dc917df9e64d8 | Python | 7,643 | 206 | """
Tests for CPU, RAM, and GPU utilization tracking functionality.
"""
import time
import unittest
from pathlib import Path
from unittest import mock
import pandas as pd
from codecarbon.emissions_tracker import OfflineEmissionsTracker
from tests.testutils import get_custom_mock_open
empty_conf = "[codecarbon]"
c... |
74cebb74001e087938dba3ed477999c986805c401b8817d126fce552c61a1680 | Python | 7,644 | 149 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# PLUS
import os
import sys
import argparse
import torch
import plus.config as config
from plus.data.alphabets import Protein
import plus.data.localization as localization
import plus.data.dataset as dataset
import plus.model.plus_rnn as plus_rn... |
cefdd0dfdde6bb6f73e7b853aa789de432e2af52a8c920c1c2af17228235b72c | Python | 7,644 | 215 | from __future__ import annotations
import dataclasses
import decimal
import json
import typing as t
import uuid
import weakref
from datetime import date
from werkzeug.http import http_date
if t.TYPE_CHECKING: # pragma: no cover
from werkzeug.sansio.response import Response
from ..sansio.app import App
cl... |
a8eac0cc65622bf89cc9e6c7633a68e8fc984f1adb417e764b8acf2c53e69a20 | Python | 7,645 | 147 | import os
import re
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import sys
sys.path.insert(1,'/home/mila/l/lindongy/deeprl-timecells')
from scipy.stats import kruskal
from analysis.utils_analysis import sort_resp, plot_sorted_averaged_resp, single_cell_visualization, \
time_d... |
93e05b3eb43754f8198f747ea06b9c5f3594b7951eef13fce90bca06a2035899 | Python | 7,646 | 189 | """Gate 2 -- the TransformerLens oracle (mikit D13/D14; legs G2a/G2b/G2c).
LIVE in-process oracle on the transformers-5.x band, pinned transformer-lens
3.8.0 (test-only extra; packaging request filed). Revision-pinned real gpt2
from the local HF cache; the module skips without the pin installed and runs
OFFLINE (no te... |
53efb5115441a46c0ccbcdd0e4a9b0b8997cdabc44b5d24b3716713a5adea502 | Python | 7,647 | 124 | # -*- coding: utf-8 -*-
"""
Created on Wed May 13 10:54:41 2020
@author: Caterina Brighi
"""
import numpy as np
import pandas as pd
import SimpleITK as sitk
import os
from ImageResultsVisualizationFunctions import *
data_supradir = 'Path to data directory'
subjs_path = [ f.path for f in os.scandir(da... |
16575bb60844874b7225a0e803617a28a1085dac6a22d19c87be0d00b70af96a | Python | 7,648 | 180 | import contextlib
import os
import random
import numpy as np
from sklearn.model_selection import KFold, StratifiedKFold
import torch
from torch.utils.data.dataloader import DataLoader
# from torchsummary import summary
from hn_cnn.cnn import MODELS
from hn_cnn.constants import *
from hn_cnn.data_augmentation import g... |
7c124fdea099f3f1bed904132303b7c8d038ac24ba932803bf6760ef2f9cbaa3 | Python | 7,648 | 217 | # SOURCE: vendored from facebookresearch/drqv2 @ main
# https://github.com/facebookresearch/drqv2/blob/main/drqv2.py
# https://github.com/facebookresearch/drqv2/blob/main/utils.py (weight_init helper only)
#
# DrQ-v2: image-based continuous-control RL (data-augmented actor-critic with a
# shared conv encoder). The real... |
163401c41f0a5baa3fdccf763f5c6384ddd4b6b8246a9a76bd612aa174cdfcfd | Python | 7,649 | 190 | #!/usr/bin/env python3
"""Which subjects does the pipeline drop, and why. v2"""
import argparse, glob, os, re, warnings
from collections import Counter, defaultdict
import numpy as np
warnings.filterwarnings("ignore")
HEALTHY_ROOT = "raw/healthy/eegmmidb/eegmmidb_v1"
STROKE_ROOT = "raw/stroke"
STROKE_DIR = "raw/stroke... |
da3b1bf15239bd67d70f3ad114f873e0a51554280eba99ca3e94eecf140eb7ae | Python | 7,649 | 150 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# PLUS
import os
import sys
import argparse
import torch
import plus.config as config
from plus.data.alphabets import Protein
import plus.data.stability as ss
import plus.data.dataset as dataset
import plus.model.plus_rnn as plus_rnn
import plus... |
f2dfbe0c5f73ed95eef7a9125a9dd2352c533087e6d342a5dbe41a814f865aa0 | Python | 7,649 | 176 | import pandas as pd
import numpy as np
import sklearn.neighbors
def Cal_Spatial_Net(adata, rad_cutoff=None, k_cutoff=None, model='Radius', verbose=True):
"""\
Construct the spatial neighbor networks.
Parameters
----------
adata
AnnData object of scanpy package.
rad_cutoff... |
58489d213e851d3bc77b752cc6621cbb0088bc32d304d958ea409ea199a6db51 | Python | 7,653 | 222 | """Sprint A3 semantic output table and surface tests."""
from __future__ import annotations
from pathlib import Path
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.visualization._render_nodes import _render_raw_output
class _Config:
"""Small classifier config carrying ex... |
3a464b3eda3c0a0bf4af83bf029241655aa29dab4fd4d4e8aab7cd26665b5869 | Python | 7,655 | 204 | import numpy as np
import pandas as pd
from rdkit import Chem
from rdkit.Chem import AllChem
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import roc_auc_score
import argparse
rf = RandomForestClassifier()
def init_args():
parser = argparse.ArgumentParser()
parser.add_argument('--tr... |
443c2ec48c46b7ab24d5e706f380f2d0308ad6399a379b85a4ed20ab11c8b136 | Python | 7,658 | 236 | """Repeatable facet-coverage audit producing recipe PROPOSAL inputs.
Runs a roster of models through TorchLens, computes
``torchlens.semantic.facet_coverage`` for each, and writes ONE review document
aggregating classified/unclassified modules and typed facet absences. The
output is evidence for the maintenance sweep ... |
f1c1e5ac5e781f9d370c2b40918a0bb48b572504078df28ba711f17b8f785f91 | Python | 7,659 | 222 | import os
import time
import cPickle
import datetime
import logging
import flask
import werkzeug
import optparse
import tornado.wsgi
import tornado.httpserver
import numpy as np
import pandas as pd
from PIL import Image as PILImage
import cStringIO as StringIO
import urllib
import caffe
import exifutil
REPO_DIRNAME = ... |
8441a39b2d28afcd8d73b574c147a29871678274befaf8eb4e95acb157550984 | Python | 7,660 | 185 | """Implementation of a space that represents textual strings."""
from typing import Any, Dict, FrozenSet, Optional, Set, Tuple, Union
import numpy as np
from gym.spaces.space import Space
alphanumeric: FrozenSet[str] = frozenset(
"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
)
class Text(Spa... |
740c9b517bebe35a2f7d37ab28ce0448ca71cb93e7628d78ded9ca847c9d6dbe | Python | 7,661 | 173 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
bd1866aea35fb0c5b7b4fc6928feeefdd496ca9742ae69b2e9b7291afeb6109e | Python | 7,661 | 221 | #!/usr/bin/env python3
"""
Diagnostic H — Tier 1.1: 7D + FOOOF peaks.
Tests whether adding FOOOF features (aperiodic exponent+offset, alpha peak
CF+PW+BW, theta peak PW) on top of the 7D (5D + IAF + DFA) baseline with
HC-anchored normalization improves AD-vs-HC / FTD-vs-HC / AD-vs-FTD
classification.
Feature variants... |
c8afac99d9d8d0c8fd96f7c569de7a97bbcfc1c8934c5a94b50285482455b536 | Python | 7,661 | 158 | import sys
import optuna
import torch
import torch.nn as nn
import torch.optim as optim
import numpy as np
from sklearn.metrics import roc_auc_score, precision_score, recall_score, average_precision_score, confusion_matrix
from sklearn.utils.class_weight import compute_class_weight
from torch_geometric.loader import Da... |
5f5c08f3521ddfcd9643961dcfa0814c2b44698248433415688f8d3fcc6d1569 | Python | 7,662 | 198 | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
import pandas as pd
import argparse
import os
import sys
import pwd
import pdb
import grp
INPUT_PATH = "SimBoost/data/davis_cv_nmlzd.csv"
LOG_DIR = "logs/"
PATIENCE =... |
a01a5fd12e67cbf1d4ff969561c9508ef19863d311db98f217b42f17a382edbe | Python | 7,662 | 240 | #!/usr/bin/env python
# from galaxy import eggs
import sys
import rpy2.rinterface as ri
import rpy2.rlike.container as rlc
# from rpy import *
import rpy2.robjects as robjects
r = robjects.r
def stop_err(msg):
sys.stderr.write(msg)
sys.exit()
infile = sys.argv[1]
y_col = int(sys.argv[2]) - 1
x_cols = sys... |
ed39dd9ce21055a1653c011806ffdf9a7630a50c60d5f6d798d313d503d9e181 | Python | 7,662 | 221 | import warnings
import numpy as np
from ..utils.distance import distance
from ..utils.utils import check_weights
def _project(X, U):
"""
Project U on the tangent space of orthogonal matrices with base point X.
"""
return X @ ((X.T @ U) - (X.T @ U).T) / 2
def _retract(X, v):
"""
Retraction t... |
093ebbb7697bf262242b53e0d87bdbb30ab09935e122e5a291a0f900318dc52f | Python | 7,664 | 195 | # -*- coding: utf-8 -*-
import os
import time
import torch
import torchvision
import torchvision.transforms as transforms
import platform
from electric_network import *
import shutil
from pytorch_metric_learning.losses import *
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import logging
impo... |
a34a8d1052dcec1a411120ee2df7db935206a6b42324d524dafbed1fafb67e15 | Python | 7,664 | 182 | from .pycobi import ODESystem
from typing import Union, Any
import numpy as np
def continue_period_doubling_bf(solution: dict, continuation: Union[str, int, Any], pyauto_instance: Any,
max_iter: int = 1000, iteration: int = 0, precision: int = 3, pds: list = [],
... |
3148b49952213b6e43e5ce7582ad76b41d9023eab422a288508261e1cbe1d364 | Python | 7,665 | 248 | import os
import re
import shutil
import subprocess
import sys
import warnings
import setuptools
import setuptools.command.build_ext
import wheel.bdist_wheel
_this_dir = os.path.dirname(os.path.abspath(__file__))
_build_dir = os.path.join(_this_dir, 'build', 'python')
_cmake_file = os.path.join(_this_dir, 'CMakeList... |
7dbf2d9f3a1ed88c81c9cce6f42fafd6c58288d87a0214aa0b4665a7a3fc7e4a | Python | 7,665 | 204 | import os
import subprocess
import cv2
import sqlite3
import numpy as np
from datetime import datetime, timedelta
import argparse
from tqdm import tqdm
def load_tracking_data(conn):
"""
Load ROI map and all tracking positions from the database.
Args:
conn: SQLite connection object.
Returns:... |
803e49b35b2ad4aeada11be180e9775cd48ae95bca1ac790929ffe73147ea7ae | Python | 7,665 | 256 | from matplotlib import pyplot as plt
from more_itertools import chunked
import tqdm.auto as tqdm
from permacache import permacache, stable_hash
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
import torch
from modular_splicing.dataset.generic_dataset import dataset_types
from modular_splici... |
f54924122ea64cf4767be836ab275fbcd73afb3f37a446c6a4aaf5a8daefa093 | Python | 7,668 | 145 | """
Hopf Bifurcation and Limit Cycle Continuation
=============================================
Here, we will demonstrate how to perform branch switching at an `Andronov-Hopf bifurcation <http://www.scholarpedia.org/article/Andronov-Hopf_bifurcation>`_
and continue a branch of periodic solutions.
As an example model,... |
1e63d6ace4a869c10a13a38f536b63112960aaf383e3de234bb472c4952f9b77 | Python | 7,670 | 235 | import inspect
from keras.src.api_export import keras_export
from keras.src.backend.common import global_state
GLOBAL_CUSTOM_OBJECTS = {}
GLOBAL_CUSTOM_NAMES = {}
@keras_export(
[
"keras.saving.CustomObjectScope",
"keras.saving.custom_object_scope",
"keras.utils.CustomObjectScope",
... |
c45789da418ceacbe768d8f231fde35886fdf993c4ec28160fdd3605c56684a8 | Python | 7,670 | 173 | # pylint: disable=wildcard-import
from timm.optim.optim_factory import *
_TIMM_FC_NAMES = ('fc', 'head', 'last_linear', 'classifier')
def optimizer_kwargs(cfg):
kwargs = dict(
opt=cfg.optimizer.opt,
lr=cfg.train.lr,
weight_decay=cfg.optimizer.weight_decay,
momentum=cfg.optimizer.mo... |
3e5604d3374bc9300cf4bbe32abd5ac7efd8362a1eaf94bfb11ed5c9eca211d4 | Python | 7,673 | 205 | #!/usr/bin/env python
# python version of fasta-stats with some extra features
# written by anmol.kiran@gmail.com
# git: @codemeleon
# date: 10/11/2021
import argparse
import re
from os import path
import numpy as np
from Bio import SeqIO
def calculate_NG50(estimated_genome, total_length, sequence_lengths):
t... |
41a85ca90983b29fa1195816ac15cdfbaab5455e7a73fab36809117a8a6a61b1 | Python | 7,673 | 209 | import torch.nn as nn
import torch
class AirModel(nn.Module):
'''
Model based on LSTM.
'''
def __init__(self, num_hidden=50, num_fin=36, num_layers=2):
super().__init__()
self.lstm = nn.LSTM(input_size=num_fin, hidden_size=num_hidden, num_layers=num_layers, batch_first=True)
s... |
68b6241d05451e495601498abb6924acd930983e89ecc76d581f2dfb48ce5ca6 | Python | 7,673 | 196 | import torch
from transformers import BertModel, DistilBertModel
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
import datasets
import numpy as np
import os.path
from spacy.lang.en ... |
217130c1e9ee57487eb6c272bf83f3f0642dee94e5662ef0a0b0fcfa84c2b9e9 | Python | 7,675 | 178 | import io
import os, sys, glob
import shutil
import zipfile
import requests
import src.EP_Generator_utils as EP_Generator_utils
from eppy.modeleditor import IDF
from src.Signal_Generator import generate_signal_for_EP
from src.OB_GEN.OB_Generator import ob_gen
def download_epw_create_directory(epw_url, configs):
e... |
4ba28bd935577d51130c8ed64dd3248ec593cb7ba87bd35e74d7ac6a5900dba8 | Python | 7,675 | 212 | from typing import Dict, List, Tuple, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.gaussian_blur import GaussianBlur
from lightly.transforms.multi_view_transform import MultiViewTransform
from lightly.transforms.solarize import RandomSolarization
from lightly.transforms.torchvisi... |
7176a8f4d0d19982015a4917e7e26331ecea9534c23935ca670e4deb8b2c460d | Python | 7,675 | 224 | """
Unit tests for the device scanner module.
This module contains tests for device discovery and management
functionality in the node package.
"""
import threading
import time
from unittest.mock import MagicMock, Mock, patch
import pytest
# Import the updated scanner modules
from ethoscope_node.scanner.base_scanne... |
bc32d37dc8e3d2482a704b1b3c17ef782e02471ca15a23a391efaa37466bf021 | Python | 7,676 | 213 | from __future__ import absolute_import
import logging
import os
import re
from pip._internal.models.link import Link
from pip._internal.utils.logging import indent_log
from pip._internal.utils.misc import (
display_path, make_vcs_requirement_url, rmtree, split_auth_from_netloc,
)
from pip._internal.vcs import Ver... |
4ac253c5963872c3afd9c0eeb4287e7234ea8b6efc04e9bf945e6a2807997912 | Python | 7,677 | 257 | # Copyright (c) 2021 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... |
5b64ef9c8ef5064d183bc1e2b88de73f34345cf3cc6a71398f32fdb76266f979 | Python | 7,679 | 162 | # FAITHFUL REIMPLEMENTATION of the Active Appearance Model (AAM) face decoder
# used in Chang & Tsao, "The Code for Facial Identity in the Primate Brain"
# (Cell, 2017; PMC8088389), built on the classic AAM formulation of Cootes,
# Edwards & Taylor, "Active Appearance Models" (ECCV 1998) and Cootes, Edwards &
# Taylor,... |
df96e1a1a972498f63d00994fe5da61d23b1f15c6632a88a4328ee5f9658e94d | Python | 7,682 | 216 | """Regression tests: ``force_shape_change`` flows from helper kwargs to execution.
Round 26 W3 audit MED-1: ``normalize_hook_plan`` stamped the per-entry
``force_shape_change`` metadata from its own default-False parameter instead of
the helper's kwargs. No production caller passes the parameter, so the
documented esc... |
122ae9608e440499880647379b79ac32ad1749e3b77e76ad964f1ea667b359d3 | Python | 7,684 | 150 | # Written by Seonwoo Min, Seoul National University (mswzeus@gmail.com)
# PLUS
import os
import sys
import argparse
import torch
import plus.config as config
from plus.data.alphabets import Protein
import plus.data.fluorescence as fluorescence
import plus.data.dataset as dataset
import plus.model.plus_rnn as plus_rn... |
3d86a3d7d7379298a6d0f2aa5f43f1cf60966d88b7ae8ebe23964e85b848c356 | Python | 7,684 | 222 | """Helpers for shape-matrix tests.
A "shape-matrix" test verifies that a function applies independently across
arbitrary leading and trailing dimensions surrounding its key axes (length,
ohe, etc). The pattern: build a baseline input plus a "patterned" input that
broadcasts the baseline along new leading and/or traili... |
b5f18c2fb098bf3002f04d18022e916ee73f96ba4233656d211cb92c178d89d4 | Python | 7,684 | 198 | __author__ = "quentin"
import time
from ethoscope.core.variables import BaseIntVariable
from ethoscope.hardware.interfaces.interfaces import DefaultInterface
from ethoscope.utils.description import DescribedObject
from ethoscope.utils.scheduler import Scheduler
class HasInteractedVariable(BaseIntVariable):
"""
... |
7d110748a4a2aad90c33489f4a50da0ac6aa19d64aab5414929be8a3fbb44dcf | Python | 7,686 | 250 | import json
import os
import tomllib
import pytest
import flask
# config keys used for the TestConfig
TEST_KEY = "foo"
SECRET_KEY = "config"
def common_object_test(app):
assert app.secret_key == "config"
assert app.config["TEST_KEY"] == "foo"
assert "TestConfig" not in app.config
def test_config_from... |
c641c1cf78e9b0c7d7f871ceb2cf574495684537d3cd5725995e3d5e08302d27 | Python | 7,687 | 187 | """F29: payload_stats and compare -- bounded numbers, coverage honesty.
Stats: deterministic float64 metrics against a torch reference, tagged
non-finites through the strict serializer, per-row typed statuses (never a
batch failure), byte refusal BEFORE materialization, one retained axis.
Compare: subject-minus-refere... |
d084d49b5b74d775e4b493d08ff4dfa51999e3e537c1d997cfd1810f9fb3ddd5 | Python | 7,687 | 236 | """Kernels for SPD matrices."""
import numpy as np
from .base import invsqrtm, logm
from .mean import mean_riemann
def kernel_euclid(X, Y=None, *, reg=1e-10, **kwargs):
r"""Euclidean kernel between two sets of matrices.
Calculates the Euclidean kernel matrix :math:`\mathbf{K}` of inner products
of two ... |
d06326248d8d63c38c7947d2141294301f6f3dcab8969890a73909aed3085f7b | Python | 7,689 | 215 | """Step-qualified selectors (lane F42, attested coupling).
The trace-verb verdict's evidence-bar item "selectors can name step versus
pass": ``at_step(...)`` matches ops recorded inside declared episode steps at
capture time (the armed join session's live step position) and post hoc (the
persisted ``Op.episode_step`` ... |
4c86aadedec0eaf6df714c9a5449b9d2ff95e2131bc8bd1933c80adfb9507bdf | Python | 7,690 | 238 | # Copyright (c) 2023 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... |
0b487fced791343b8f1b20c1945f944c0d2ced25de50dc5cfe0edd904bb97379 | Python | 7,692 | 181 | import torch as ch
import dill
import os
from .tools import helpers, constants
from .attacker import AttackerModel
class FeatureExtractor(ch.nn.Module):
'''
Tool for extracting layers from models.
Args:
submod (torch.nn.Module): model to extract activations from
layers (list of functions):... |
c0661ebcd476dac1ce69212441a2fbb895b539bed7a0f30bb74ecf158e612242 | Python | 7,692 | 227 | '''
use detectron2 library to detecated the person centered video
'''
# %%
import torch
import numpy as np
import detectron2
from detectron2.config import get_cfg
from detectron2 import model_zoo
from detectron2.engine import DefaultPredictor
from torchvision.transforms.functional import crop, pad, resize
# %%
cl... |
2e4a68311af4aa8f728536f8b50920caa02185d1d673ac68834007764dc571b8 | Python | 7,694 | 212 | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import numpy as np
import slowfast.utils.logging as logging
import torch
logger = logging.get_logger(__name__)
def round_width(width, multiplier, min_width=1, divisor=1, verbose=False):
if not multiplier:
return width
width *= m... |
8b5dfe7fc0e9e59f4ff167cb3d38c76e283680906d890bf76807a7c4d31d1139 | Python | 7,694 | 203 | """
====================================================================
Offline SSVEP-based BCI Multiclass Prediction
====================================================================
Building extended covariance matrices for SSVEP-based BCI. The
obtained matrices are shown. A Minimum Distance to Mean classifier
i... |
eefa0e830c479ca08af073a8b8caf47dd1d9aed7a146002e18fbf53e10c0c075 | Python | 7,694 | 255 | import ast
import importlib
import inspect
import pkgutil
import sys
import textwrap
import pytest
from numba import jit
import pynapple as nap
def valid_func(x):
# do not call
x.__class__
@jit
def valid_func_decorated(x):
x.__class__
def invalid_func(x):
x.__class__()
@jit
def invalid_func_de... |
d826c2a5b2dc38bf94e2196dcd60ef0928584a36f2585c18f59595cc1ee8af68 | Python | 7,698 | 210 | """Smoke tests for intervention Phase 2 selector resolution."""
from __future__ import annotations
import warnings
from dataclasses import FrozenInstanceError
import pytest
import torch
import torchlens as tl
from torchlens.intervention.errors import (
MultiMatchWarning,
SiteAmbiguityError,
SiteResoluti... |
e71c962ad2536a6c33e75f18e432c0f0816c1d6b982ee18746b7aaeda6a3387f | Python | 7,700 | 218 | from model import common
import cv2
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
### Lattice网络
def make_model(args, parent=False):
return LatticeNet(args)
## Combination Coefficient
class CC(nn.Module):
def __init__(self, channel, reduction=16):
super(CC, self... |
abb4dc057617cc0e88d12e536b3a6fc3c96873dc5b01938f391d44650fec1938 | Python | 7,702 | 156 | """R45: `_state` raw-access exemption is declared AND pinned no-growth.
``torchlens._state`` is the sanctioned dependency-free toggle substrate: direct
reads of its published globals from other torchlens modules (including the bare
hot-path wrapper loads) are the documented design, exempt-by-declaration from
private-m... |
35553032ddb43fee3a960a42f9552ef027bb3fdccddde428be54e0d51d943195 | Python | 7,703 | 181 | import datetime
from contextlib import AbstractContextManager
from typing import List, Optional
from dependency_injector.providers import Callable
from fastapi import HTTPException
from carbonserver.api.domain.project_tokens import ProjectTokens
from carbonserver.api.infra.api_key_utils import generate_lookup_value, ... |
3456c3afd9ee5e37894c2e7b312ba94ce21d5fda61e5af65521c5fa2cc62031e | Python | 7,704 | 234 | import glob
import logging
import multiprocessing
import os
import warnings
import numpy as np
import tifffile as tf
from scipy.optimize import least_squares
from . import llsdir, util
try:
from numba import jit
except ImportError:
def jit(**_):
def deco(f):
return f
return deco... |
e478808b843e6f7bb63649ae95a7f5bc75466e3082cf4c527cc35a057d6a4e0b | Python | 7,704 | 263 | import numpy as np
from tqdm.auto import tqdm
from itertools import product
import tensorflow as tf
import pandas as pd
import RNAutils
import matplotlib.pyplot as plt
import scipy.stats
from matplotlib import cm
def subsample_points(x, y, max_points=30000):
assert(len(x)==len(y))
if (len(x)>max_points):
... |
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