sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
dcdadd269ea32ee15fe34311f0f17b165412217269cdb224d4d2f9d006396ae9 | Python | 4,604 | 148 | from datetime import datetime, timedelta
from typing import List, Optional, Union
import dateutil.relativedelta
from dependency_injector.wiring import Provide, inject
from fastapi import APIRouter, Depends, Header
from starlette import status
from carbonserver.api.errors import EmptyResultException
from carbonserver.... |
4df02892d4f8156adace464f9607de3935fa7b71bf79ba7da888ee2d19100bc9 | Python | 4,605 | 183 | #!/usr/bin/env python3
import codecs
import os
import re
import setuptools
NAME = 'celery'
# -*- Extras -*-
EXTENSIONS = (
'arangodb',
'auth',
'azureblockblob',
'brotli',
'cassandra',
'consul',
'cosmosdbsql',
'couchbase',
'couchdb',
'django',
'dynamodb',
'elasticsearc... |
7ef46df370b150d3eb94b38ae07cf9b01c35ad01b104b8a9258d4070669fe5be | Python | 4,605 | 102 | import glob
import h5py
import numpy as np
import os
import pandas as pd
from sklearn.linear_model import RidgeCV
from sklearn.model_selection import GroupKFold
from sklearn.linear_model import LinearRegression
from sklearn import preprocessing
import sys
from scipy.stats import pearsonr
"""
This script will run ridge... |
db43e529b67badfadc281922d2ee4c165dc55345e68b46a1ae20872048591fc5 | Python | 4,605 | 101 | from keras.src import initializers
from keras.src import ops
from keras.src.quantizers.geometry import EinsumProjectionGeometry
from keras.src.quantizers.modes.common import apply_bias_activation
from keras.src.quantizers.quantization_config import TernaryQuantizationConfig
from keras.src.quantizers.quantized_weight im... |
e3dfb219c7b99e455703a7319bac0856a06460318fa9a381d4480f09c2274d47 | Python | 4,605 | 114 | # 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... |
1cb0a48fc35d08cb1d41b3a9b619508c5f05a6d2485f7bee466aa59c15579e78 | Python | 4,606 | 129 | import os
import numpy as np
import pandas as pd
import torch
from tqdm import tqdm
from typing import Tuple
from torch import Tensor
from torch.utils.data import Dataset
from e3fp.fingerprint.generate import fprints_dict_from_mol
from e3fp.fingerprint.db import FingerprintDatabase, concat
from e3fp.fingerprint.fprint... |
bc17d0bb6ab7a7bd806c1dfd56c7f169c67471a80a757063c2e4382aac5497f8 | Python | 4,606 | 155 | # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Functions for generating the executive summary."""
import numpy as np
from nipype import logging
LOGGER = logging.getLogger('nipype.utils')
def plot_gii(mesh, coord, color, slicer, view, max_distance... |
5a92de74d9208f75fa85494bcc12b576ccda6f7852ac784440e13e5326cf60a6 | Python | 4,608 | 138 | # 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... |
b5216a22aa9733ffcb992ec659af77a93e55a39abadb545f4fd1832801fd600e | Python | 4,608 | 165 | from tempfile import TemporaryDirectory
import numpy as np
import polars as pl
import pandas as pd
import seqpro as sp
import xarray as xr
from pytest import fixture
import seqdata as sd
import zarr
def read_fasta(file_path):
"""
Reads a FASTA file and returns a dictionary of sequences.
Parameters:
... |
817b2d7c62a5310eadc50f980da168a576baa490641160bebc34925cf2249e3f | Python | 4,609 | 142 | from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.optimizers import optimizer
@keras_export("keras.optimizers.SGD")
class SGD(optimizer.Optimizer):
"""Gradient descent (with momentum) optimizer.
Update rule for parameter `w` with gradient `g` when `momentum` is 0:
... |
d74acce7997466c1694d8ad1a11081b09feb46f2bf082a057ac64d908376e67a | Python | 4,609 | 130 | import numpy as np
import pytest
from absl.testing import parameterized
from keras.src import backend
from keras.src import layers
from keras.src import models
from keras.src import ops
from keras.src import testing
class FlattenTest(testing.TestCase):
@parameterized.named_parameters(
[
{"tes... |
58f3ae65b55fd0d92598b6f05afc4fdb6d87bf3124391cec0063b142e165f711 | Python | 4,610 | 156 | """Coordinate Attention for efficient mobile networks.
Paper: Coordinate Attention for Efficient Mobile Network Design.
Hou, Zhou, and Feng, CVPR 2021.
Coordinate attention factorizes global pooling into height-wise and width-wise
1D encodings. The two encodings share a bottleneck transform, then produce
direction-a... |
6fcd99d3d93c1dc42a94d44149172c960018b128995df139e57be2a1ed33aa1a | Python | 4,610 | 131 | # 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 torch
import torchvisi... |
ce05491080eab071249fff66be184fbdac00c5a835cf486e980c0a0e89429772 | Python | 4,610 | 165 | """Functions for generating synthetic data."""
from collections.abc import Callable
from typing import Literal, cast
import dask.array as da
import numpy as np
import zarr
from skimage import data
from skimage.filters import threshold_otsu
from skimage.measure import label
from skimage.segmentation import clear_borde... |
212147ddeba9a5991c381381b0cffad6dedf18d1ca83cece82a0dabbfad357f3 | Python | 4,615 | 119 | from unittest.mock import patch
import pytest
from sqlalchemy.exc import OperationalError
from sqlalchemy.orm import Session
from celery.exceptions import BackendStoreError
@pytest.fixture
def db_retry_app(celery_app, tmp_path):
"""Fixture to set up a Celery app with a database backend and retry configs."""
... |
333b188d7c17cd141b2ef4283da6465c0277f9e6d5be13635926cf6647f3aaee | Python | 4,615 | 139 | # 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... |
1215889a99acaea6577ec83b14e8e151d4e931adae12621e4e84ba3821d1a356 | Python | 4,616 | 129 | import warnings
import numpy as np
from neurogym.envs.registration import make
from neurogym.wrappers.noise import Noise
from neurogym.wrappers.pass_action import PassAction
from neurogym.wrappers.pass_reward import PassReward
from neurogym.wrappers.reaction_time import ReactionTime
# TODO: No tests exist for wrappe... |
215911853fc15ba04de634f1668f5050e6841f229501959a7b168371604b31ec | Python | 4,616 | 171 | """Featurizers to use with the preprocessors"""
from collections import defaultdict
import rdkit
from rdkit.Chem import AllChem
# nfp features copied to remove dependence on nfp if these are updated
def get_ring_size(obj, max_size=12):
if not obj.IsInRing():
return 0
else:
for i in range(max_... |
7111b4fcb7b29b930eb1d558f15c84b13033c6d98b0f9a3abfd959f0d05dd9ce | Python | 4,616 | 145 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "ohlc.decreasing"
_path... |
a1f27b0838cd96f6c4a730e71870393ecc2adee7011b4552fac27dca3d8dfe35 | Python | 4,616 | 145 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "ohlc.increasing"
_path... |
45bfdc1d7b9022868aabd7f0ca3ec5356b6e9237f37e73896f3d67914a4557c9 | Python | 4,617 | 121 | """Tests for documentation-plan structural link checks."""
from __future__ import annotations
from scripts.check_plan_link_consistency import find_invalid_s2_6_citations
def _v33_like_plan(citation_range: str) -> list[str]:
"""Build a plan fixture whose §2.6 table matches v33 line placement.
Parameters
... |
68dc4b36997c49cfa3dc85ad4bf7e9e73cba1c282ae5ce62dd22e8b8225828d3 | Python | 4,617 | 126 | #Autor: Carlos Alberto Hernández Nava
#ASVspoof2017 spectrograms MFCC 1D
import cv2, sys, os, gc
import librosa
import numpy as np
import pandas as pd
import seaborn as sns
import openpyxl as pxl
import tensorflow as tf
from tensorflow import keras
import IPython.display as ipd
from numpy.random import randn
from pand... |
a58dffb28c363c6416073c1ee5bb85193d9413462ccd8fe26a2ea4b58fc8f373 | Python | 4,617 | 158 | """Recommender model."""
from __future__ import print_function
import sys
import numpy as np
import theano.tensor as T
from theano import function, shared
__author__ = "Gianluca Corrado"
__copyright__ = "Copyright 2016, Gianluca Corrado"
__license__ = "MIT"
__maintainer__ = "Gianluca Corrado"
__email__ = "gianluca.c... |
c9d00477aca43abc3cf0b8997a7097d8fd7f9aa88c22f47842726451cc2782dc | Python | 4,617 | 127 | """Branch coverage for feature modules and the graph-export prep (#272).
Uses the real bundled PBF data and derives malformed inputs from it (dropping a
column / using a no-data bbox) to exercise the validation / no-data / warning
branches that the happy-path tests don't reach.
"""
import pytest
from geopandas import... |
f86a5de3af0173929512e1ecdde7cf24e3e8605ad84e89abfceb3ab9ac1f820c | Python | 4,617 | 141 | # import torch.nn.functional as F
from dataclasses import dataclass, field
import torch
import torch.nn as nn
# from dgl.nn import GCN2Conv, GraphConv
@dataclass
class Args:
dataname: str
gpu: int = 0
epochs: int = 1000
lr1: float = 1e-3
wd1: float = 0.0
lambd: float = 1e-3
n_layers: int... |
3c6161e92d3f7175d7e179bf2a832000bfa1416d390fe639f40373ba0612297a | Python | 4,618 | 136 | """Behavioral tests for debug cost ranking, byte model, compile counting, and audits."""
from __future__ import annotations
from collections.abc import Iterator
import pytest
import torch
from torch import nn
pd = pytest.importorskip("pandas")
import torchlens as tl # noqa: E402
from torchlens.debug import audit_... |
8956d93572ae23578b8dc4fbb6728f90c32f75a0cd22c075ba767ebcd4743393 | Python | 4,618 | 164 | """
Kullback-Leibler Importance Estimation Procedure (KLIEP).
"""
from numbers import Number
from numpy import arange, asarray, inf, log, mean, ones
from numpy.random import choice, permutation
from .RuLSIF import compute_kernel_Gaussian
from .density_ratio import DensityRatio, KernelInfo
def KLIEP(x, y, sigma="au... |
dcec43ced2e483cb134ebe780d10160ab702d46463522ba11796b73e3b2a8409 | Python | 4,618 | 157 | import argparse
import json
import warnings
import pandas as pd
from galaxy_ml.model_persist import load_model_from_h5
from galaxy_ml.utils import clean_params, get_scoring, read_columns
from scipy.io import mmread
from sklearn.metrics._scorer import _check_multimetric_scoring
def _get_X_y(params, infile1, infile2):... |
777d19b7e1eb90d00279698199f2054978ac0e06e81b1c8b9e85165fc0a36c23 | Python | 4,619 | 114 | # 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... |
8a5c7205cc8e2d4b4b04a6564050e04a96427e85ca60c232acbc4bf9701e940b | Python | 4,619 | 110 | import torch
from torch import nn
class PairwiseDistances(nn.Module):
"""
Layer for computing the pairwise distance matrix. Matrix is quadratic
and symmetric with entries d_ij = r_i - r_j. All possible atom pairs are
considered. This Layer is particularly used in the nn module.
Returns:
... |
18f53e0312cb34c17eb7e7092b4cc8228c6ab9493d551e5e7e7d5a96d2a1d096 | Python | 4,620 | 171 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Perform Hypermutation analysis based on Hypermut v2.0
@author: Ce Gao
"""
import re
import logging
from Bio import SeqIO
from scipy.stats import fisher_exact
# pylint: disable=C0103
# Invalid constant name
logger = logging.getLogger('pipe.hypermut')
def get_pos(p... |
4bd9cc0a7b62be74c86cbe36b3da9809d968409d99f94c5af6ab203250ddb192 | Python | 4,620 | 160 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Bounds(_BaseLayoutHierarchyType):
_parent_path_str = "layout.map"
_path... |
63091cda15367b4c6ca29ff70fa53e2f667b5b32e825246bd01acf227fbc87b1 | Python | 4,620 | 138 | from abc import abstractmethod
import torch
from torch import Tensor, nn
from chemprop.nn.hparams import HasHParams
from chemprop.utils import ClassRegistry
__all__ = [
"Aggregation",
"AggregationRegistry",
"MeanAggregation",
"SumAggregation",
"NormAggregation",
"AttentiveAggregation",
]
cl... |
cc0aa6d264ca1db43d8699ea3cf869eafcf9480f62d12d5baf8b096eb4074632 | Python | 4,620 | 134 | """Regression coverage for fast-pass output population."""
from __future__ import annotations
import torch
from torch import nn
import torchlens as tl
class _SelectiveSaveModel(nn.Module):
"""Small stable graph with an explicit output node."""
def __init__(self) -> None:
"""Initialize deterministi... |
00ba2ab28d403b60d0eea341d4ec14c4c65eb0338d5e075d49bbe4c8863f28ee | Python | 4,621 | 144 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Transition(_BaseLayoutHierarchyType):
_parent_path_str = "layout"
_path... |
779fdb6643967e60e3561f9ef27d1da823d75a11d97ae95487bbecc2e0d980c2 | Python | 4,621 | 145 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "funnel.connector"
_pat... |
11086069b3b3a050b07b2f8fb65349f8b4ffe03556acffbe0d0dec786085dc73 | Python | 4,623 | 147 | import os
from types import SimpleNamespace
import h5py
import numpy as np
import torch
import torch.nn as nn
from modular_splicing.models.motif_models.types import motif_model_types
from modular_splicing.motif_names import get_motif_names
from modular_splicing.utils.construct import construct
import modular_splicin... |
290fc3c7df7e78720975f11e76af611e7fa9652f68f0cb1e49d5c0213c252d44 | Python | 4,623 | 116 | from contextlib import AbstractContextManager
from typing import List
from uuid import uuid4
from click import UUID
from dependency_injector.providers import Callable
from fastapi import HTTPException
from carbonserver.api.domain.emissions import Emissions
from carbonserver.api.infra.database import sql_models
from c... |
423930641a69e6809d17656b7a1defe4ca3b1ba89c8e9152c45f603c890d1437 | Python | 4,624 | 145 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Line(_BaseLayoutHierarchyType):
_parent_path_str = "layout.selection"
_... |
482aa76f01484328c720fd4fcde9831ace45d501c0d13d2cd41384a0b6e4741f | Python | 4,625 | 97 | import torch
import copy
import utility
import data
import model
import loss
from option import args
from trainer import Trainer
from torchinfo import summary
from thop import profile, clever_format
torch.manual_seed(args.seed)
checkpoint = utility.checkpoint(args)
def main():
global model
if args.data_test... |
516ef380840af51a8a924d46d727f75c883128fc2e1fb50cb31a1df0622e8b15 | Python | 4,625 | 125 | # SOURCE: vendored from yael-vinker/SceneSketch @ master
# https://github.com/yael-vinker/SceneSketch
# https://raw.githubusercontent.com/yael-vinker/SceneSketch/master/models/painter_params.py
#
# Vinker et al. 2023 (ICCV) "CLIPascene: Scene Sketching with Different
# Types and Levels of Abstraction" -- the official r... |
520b8fb1b2792bb3f0f9fe7db4d00b33e72ebf00d2d1dc57cf5ff466563ae73a | Python | 4,625 | 99 | # MNIST-SVHN multi-modal model specification
import os
import torch
import torch.distributions as dist
import torch.nn as nn
import torch.nn.functional as F
from numpy import sqrt, prod
from torch.utils.data import DataLoader
from torchnet.dataset import TensorDataset, ResampleDataset
from torchvision.utils import sav... |
aff7a87def1855a0e8f9a81bf6e444a732468bcf2f0e472d1a1bcd0ee824a0d0 | Python | 4,625 | 122 | # 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 pytorch_l... |
f78059d0f8c88968a80afb2fa41bc05ec20783342d03a717e7ff09d481e7058c | Python | 4,625 | 126 | import io
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt5agg import (
FigureCanvasQTAgg as FigureCanvas)
import nanite.fit as nfit
import numpy as np
from PyQt5.QtWidgets import QApplication
from PyQt5 import QtCore
from .. import units
from ..head import custom_widgets
class MPLEDel... |
73691e6e84c00a924c1480aba9dda4f476d3194c4d8cd5999fa197374ad719ee | Python | 4,626 | 127 | from typing import List, Tuple
import torch
from pytorch_lightning import LightningModule
from torch import Tensor
from torch.nn import Identity
from torchvision.models import resnet50
from lightly.loss.vicreg_loss import VICRegLoss
from lightly.models.modules.heads import VICRegProjectionHead
from lightly.models.uti... |
34f4b6ae8a2f91c776a3c39e10d353c2aa55ee2eecccfe7346fbc193f087b5c1 | Python | 4,628 | 170 | import logging
import os
from typing import Callable, Dict
import gc
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
def _list_available_layers(
model: nn.Module,
key_word = None
) -> list:
"""List the available layers in a model
Parameters
----------
model : tor... |
c9800c72b4556e41df1dd7cdf821a5f40e0b457b6128472a26e1d207e04a4acd | Python | 4,630 | 145 | #!/usr/bin/env python3
"""
PIN Migration Utility for Ethoscope Node
Migrates existing plaintext PINs to secure hashed format using bcrypt.
This utility should be run before enabling the new authentication system.
Usage:
python migrate_user_pins.py --help
python migrate_user_pins.py --dry-run
python migrat... |
0bf4961683271abf6eeaeae142d224fda405f14e3ab32f02028842489c38e897 | Python | 4,631 | 156 | """
Plot stimulus weights as a function of lags
"""
import matplotlib
import matplotlib.pylab as pl
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
matplotlib.rcParams["pdf.fonttype"] = 42
sns.set(
style="ticks",
font="Helvetica",
font_scale=1,
rc={
... |
28a34733c6444bd2abea8d4085018a7dc44d416d18544f699b588d5d7024d62e | Python | 4,631 | 95 | import sys
import os
# setting path
sys.path.append('../TM2_segmentation')
import numpy as np
import pandas as pd
import nibabel as nib
from skimage.transform import resize, rescale
from scipy.ndimage import zoom
from settings import target_size_unet, scaling_factor
import matplotlib.pyplot as plt
from scripts.prep... |
5d7f3b9c3b0ed1bf26ee0984f2bf7c7a6ac387cb66fe9361a3ff9539d3b872a3 | Python | 4,631 | 129 | ####################################################################################################
# Translated from matlab:
# Original script by Boris Bernhardt and modified by Casey Paquola
# Translated to python by Jessica Royer
#
# geoDistMapper Compute geodesic distance between parcel centroids and all other... |
77c6038d84dad86d43bad62ef98b957f5e52fc39faa0a9fcf87cc44687abb0b0 | Python | 4,631 | 102 | # Copyright (c) 2023, Tri Dao.
import math
import json
import re
from pathlib import Path
from collections import OrderedDict
import torch
import torch.nn.functional as F
from einops import rearrange
from transformers import GPT2Config, AutoConfig, PretrainedConfig
def remap_state_dict_hf_btlm(state_dict, config)... |
d5654afbd2f9c163479f146b527a59489fed1442ef407519b2beaf914780a335 | Python | 4,631 | 110 | """
Leaky Integrator Rate Neuron Model
==================================
The `leaky integrator <https://en.wikipedia.org/wiki/Leaky_integrator>`_ (LI) is a standard model for neuronal dynamics.
It has been used for spiking as well as rate neuron models. Here, we introduce a rate-coupled LI neuron model.
It has a sing... |
043f911e3482615ff089cdd90193b7e780f356b576b8841930fdb31d193f5ae0 | Python | 4,632 | 136 | import subprocess
import sys
import time
import argparse
import os
import shutil
from datetime import datetime
import sys
from PyQt5.QtWidgets import QApplication, QWidget, QTextEdit, QPushButton, QVBoxLayout, QHBoxLayout, QFileDialog
from PyQt5.QtGui import QPalette, QColor
from PyQt5.QtCore import Qt
# i... |
7dbe2969306bcee56769aba67b2ce1ac0404fd8b683b89f7535d4feb79d06983 | Python | 4,632 | 142 | #!/usr/bin/env python3
"""Refuse a push whose outgoing commits ADD an internal-notes path.
This repo is PUBLIC. The ``no-internal-notes`` pre-commit hook blocks ``git add``
of a private path, but it is deliberately scoped to the commit stage: at pre-push
the same path matcher would also fire on DELETIONS of those path... |
02a5a4451be499752f811ec7a46ee774817f8100a3992ab2efdf2c1699b86d7c | Python | 4,635 | 140 | # import graph_tool as gt
# from graph_tool.centrality import pagerank
from interpretability.utils import (
get_attentions_map_simple,
get_weight_head_combi,
set_hook_to_get_attention_map,
load_sequences,
load_model_and_vocab,
)
from tqdm import tqdm
import numpy as np
from analyse_how_to_agregate_a... |
09acc26b6dc0b1d0114914c841d73ff5fb8c3be3dbb01acef440f433aab24951 | Python | 4,635 | 123 | import pandas as pd
from sklearn.utils import shuffle
def binarize_data(df):
num_cols = list(df.select_dtypes(exclude=['O']).columns)
df.loc[:,num_cols] = (df.loc[:,num_cols] > 0.0).astype(int)
return df
def customized_cv_index(train):
young_1 = train.loc[train.target==0, ].animal.unique()[0]
youn... |
2bdac709e5de175fcf15ee5f912ecced78a6fd65b252bd068883a3f75530c607 | Python | 4,635 | 116 | """
org_drug_times.py
Finds drug application times from
Open Ephys Message_Center-904.0 dir.
Return drug times from metadata dict
for select drug applications.
"""
import pathlib
import os
import math
import pandas as pd
import numpy as np
#########################################################################... |
38836d5e50d814d65592378b0a7817ab09e79760d1bf63d9888645c1354bf370 | Python | 4,636 | 145 | # --- 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 Line(_BaseTraceHierarchyType):
_parent_path_str = "waterfall.connector"
_... |
58d9cdf644201093ebeecff3e51ea002a8f022c6810b14839b53de17c9a17b5d | Python | 4,636 | 128 | import pytest
from rpy2.robjects import packages
from rpy2.robjects import rl
from rpy2.robjects.vectors import StrVector
try:
from rpy2.robjects.lib import dplyr
has_dplyr = True
msg = ''
except packages.PackageNotInstalledError as error:
has_dplyr = False
msg = str(error)
datasets = packages.imp... |
8e80635fa9db2c4122be4409ceae114b8d49e1f42c9670d80aabdd6aa9180205 | Python | 4,636 | 146 |
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test objects and function of the ``tfep.nn`` package.
"""
# ==========================================================================... |
a57ab6042f46c376e705a0010f66bdbd7a1ff3e005b89fe8414dfc2327b54d4f | Python | 4,636 | 126 | from collections import OrderedDict
from bmlab.session import Session, get_valid_source, get_session_file_path, \
BmlabInvalidFileError, is_session_file
from bmlab.controllers import EvaluationController
import h5py
import numpy as np
import errno
from ..util import hashfile, hashobj
def load_h5(path):
"""L... |
1cdd60ab93b4bc68546d03ae445400042dd5c3eadea75d9472f8ad7742a73b3b | Python | 4,637 | 141 | from dolfin import *
from rm_basis_L2 import rigid_motions
set_log_level(10)
def elastic_stress(u, E, nu):
"Define the standard linear elastic constitutive equation."
d = u.geometric_dimension()
I = Identity(d)
mu = E/(2.0*((1.0 + nu)))
lmbda = nu*E/((1.0-2.0*nu)*(1.0+nu))
s = 2*mu*sym(grad(u)) ... |
391b008980e945b3a608ae18eab08c6268bb6ce0982b1a4448fe4ae719a96890 | Python | 4,637 | 116 | #!/usr/bin/env python
"""
Extract sequences from a GFF3 file.
This works for examlpe with the GlimmerHMM GFF3 output format:
#gff-version 3
#sequence-region Glarea 1 38755942
Glarea GlimmerHMM mRNA 1017 1644 . - . ID=Glarea.path1.gene1;Name=Glarea.path1.gene1
Glarea GlimmerHMM CDS 1017 1126 . - 2 ID=Glarea.cds1.1;Par... |
b5df10407c17ebc51fa559d48fe8eb9f7f5f06dfbd400feca319628413a85017 | Python | 4,638 | 116 | import sys
import torch
import numpy as np
from torch.autograd import Variable
class DataBasicLoader(object):
def __init__(self, args):
self.cuda = args.cuda
self.P = args.window # 20
self.h = args.horizon # 1
self.d = 0
self.add_his_day = False
self.rawdat = np.load... |
45542d34a002eb892d75fb3575636ac76e09eb8f9bc549eabdb047c1c6fd2c8b | Python | 4,639 | 253 | def check_index(crm_file):
from pprint import pprint as pp
o_crm = open(crm_file)
chr_dic = {}
first_line = True
chr_count = 0
for line in o_crm:
split_line = line.strip().split('\t')
start= int(split_line[1])
chr = split_line[0]
try:
chr_dic[chr].... |
1106abe88fbf94032b2ebfcc33bf1179dc5c451befe99275463b3e7c39903325 | Python | 4,640 | 119 | """A09 agent stage-0 item 4: the analytics WIRE PATH runs without pandas.
Four of the six ready-made debug analytics returned DataFrames, so any
agent/MCP consumer of ``pip install torchlens[mcp]`` served tools that
ImportError'd unless the pandas extra happened to be present. The fix is a
pandas-free rows core per an... |
9e8442829e3dd2056487a7865e64e97fc7298042779710ac5883d1136e343192 | Python | 4,640 | 139 |
"""
Usage example for models defined in models.py. Change the variable 'network_name'
to evaluate the other networks. By default SonoNet32 is evaluated. The example
images used for this script are from the test set from experiment III-A in
"Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D
Free... |
e22bf88ebbe981b00b280c6a4214a9ecfb3bdc09d544ce380d3e504edb63f988 | Python | 4,642 | 145 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Title(_BaseLayoutHierarchyType):
_parent_path_str = "layout.legend"
_pa... |
2e7ab61cb50fbeef1dfe2f1ed527b701ade923bdf2cabf7123b27410737c3fa2 | Python | 4,643 | 105 | """
core.feature_spec — Canonical feature pool definitions.
The classifier consumes 17 features in a fixed order:
- 4D state-geometry channels (`CHANNELS_4D`):
I_A, org, I_M, rel_alpha
(I_R retired from the production pool — see "I_R retirement" below.)
- 10 established / candidate EEG-AD markers (`FEAT... |
5d646b9e5e66f5b1847a22de1ce2984ba3d9d4d178bfbca7542bb0aae3fb85cc | Python | 4,643 | 127 | # 05/23/2023 Fengyao Yan
# construct a deep learning model and train the model for tissue deconvolution.
import os
import pickle
import pandas as pd
import numpy as np
import random
import tensorflow as tf
from scipy.stats import pearsonr
from sklearn.preprocessing import MinMaxScaler
from sklearn.utils import shuffle... |
856632ce31e554361472707ed1e9cef4ea562dc7207160c6591db24439abbace | Python | 4,643 | 113 | #!/home/ubuntu/miniconda2/bin/python
from __future__ import division
import sys
import glob, os, gc
import uuid
import os.path
import csv
import numpy as np
from time import time
from subprocess import (call, Popen, PIPE)
from itertools import product
import shutil
import re
import pickle
from boto3.session import Ses... |
96f9dd5b67377796f458d5bbb20dadcf5bf34c351b1c2b32a3598bf19ddccce0 | Python | 4,643 | 137 | # coding=utf-8
# Copyright 2022 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
b532cbd9c86502b27af0817663a1881d035ccfbab5230c3dbc4d49a66dc48448 | Python | 4,643 | 142 | """L5 M6 pins: rendering L1's ``Layer.shape_summary`` (across-pass shape row).
The data is L1's (memo 1.2: ONE field, slate-7.3 semantics, rendered
VERBATIM); L5 renders it as one plain-text row directly after the title row
on rolled multi-pass nodes whose passes vary in shape, escaped by the S5
choke point like every... |
51ded72ae4acbf852c2de5a3b0db69479219ee81478a18398b4a8978cdea4612 | Python | 4,644 | 133 | """Utility scripts for pydeface."""
import os
import shutil
import sys
from pkg_resources import resource_filename, Requirement
import tempfile
import numpy as np
from nipype.interfaces import fsl
from nibabel import load, Nifti1Image
def initial_checks(template=None, facemask=None):
"""Initial sanity checks."""... |
b8af805a3f5b657a1cde3b5dd9137992121093477f97b8f13cc9cffa6751b126 | Python | 4,645 | 130 | from keras.src.backend.config import backend
if backend() == "torch":
# When using the torch backend,
# torch needs to be imported first, otherwise it will segfault
# upon import.
import torch
from keras.src.api_export import keras_export
from keras.src.backend.common.dtypes import result_type
from ke... |
33886f8e15e518c81cbf1d2b7272a68e1d11750412274171c944d530e4ffb40a | Python | 4,647 | 102 | import numpy as np
from os.path import exists, join, basename
from ovseg.utils import io
from os import environ, sep, listdir
import pickle
from ovseg.data.utils import split_scans_random_uniform, split_scans_by_patient_id
from ovseg.data.Dataset import Dataset
class DataBase():
def __init__(self, val_fold, prep... |
bce8782da275bbf7bbabb7c7cedbac7d4a1d733cbc885d1a3fb3169c47861d97 | Python | 4,647 | 117 | import os
from argparse import ArgumentParser
from pytorch_lightning import Trainer, seed_everything
from pl_bolts.models.self_supervised.ssl_finetuner import SSLFineTuner
from pl_bolts.models.self_supervised.swav.swav_module_cifar import SwAV
from pl_bolts.models.self_supervised.swav.transforms import SwAVFinetuneTr... |
52dd95c1edf27719f7664649d8bd4bc5130a739f8c998b5d27f6509a3b02c0c6 | Python | 4,648 | 103 | import tensorflow.keras.backend as K
from tensorflow.keras.layers import Conv1D, Conv3D, BatchNormalization, Activation, Lambda, Dense, Input, Cropping1D, add
from tensorflow.keras.models import Model
from Configurations import CNN
from Utilities.common_packages import np
'''
Keras part: https://stats.stackexchange.co... |
61e1378fb07417a3d7352f8a924ec8cab3e761b8e50480d09b74e920da370d2d | Python | 4,648 | 143 | import pandas as pd
import numpy as np
import scipy.stats as st
import yaml
import os
from sklearn.preprocessing import StandardScaler
import scipy as sp
# def load_datasets(dataset_file):
# datasets = defaultdict(dict)
#
# with h5py.File(dataset_file, 'r') as fp:
# for ds in fp:
# for arra... |
a67607f1f4d0d55796b8ecf88d35726ccfc131cda7f2d4eaf4a64a055caf59b4 | Python | 4,648 | 122 | import mne
from mne.channels.layout import _find_topomap_coords
from mne.io.pick import _pick_data_channels, pick_info
from mne.viz.topomap import _GridData
import numpy as np
import collections
import functools
class memoized(object):
'''Decorator. Caches a function's return value each time it is called.
If c... |
b2362525af4975b900ba9a4a55ede3535f9e550c0f86d34b642ecdba6e92a356 | Python | 4,648 | 134 | """Persistence honesty: the intervention-spec door validates, gates, and keeps
edge addresses.
WT1 A-IV item 20 (lane A08): the intervention-spec load door silently
discarded ``FireRecord.edge_address``; ``save_intervention`` had no settled-
outcome gate; and ``spec.json`` deserialized with no structural validation
(a... |
eac3ecdfdd7a330978142c67d762bbf078ace5038ad1f3067e50e58922284d75 | Python | 4,648 | 151 | """
Interactive dashboard to inspect any model configuration available
"""
from __future__ import annotations
from typing import Any
import holoviews as hv
import pandas as pd
import panel as pn
from holoviews.streams import Buffer
from panel.template import DarkTheme
from larvaworld.lib import reg
from larvaworld.... |
66409cb87e222a13eb1f3912ffb03859ead5d659d3a431a2d750b31e035a1b65 | Python | 4,649 | 135 | # 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_lightni... |
edba88dd5bbab725625d97a7ec3909a022e85358449aee90ca819453c86750fd | Python | 4,649 | 98 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
ef5d0e018a7bf801e5b31b4dcaf030ded8044d28aff914d0aa53675bd27a46f5 | Python | 4,649 | 152 | """Bounding Box Utils"""
from __future__ import annotations
# Copyright (c) 2020. Lightly AG and its affiliates.
# All Rights Reserved
class BoundingBox:
"""Class which unifies different bounding box formats.
Attributes:
x0:
x0 coordinate (normalized to [0, 1])
y0:
y... |
3f1ce9cc557a9f42cc26f2ecb5c9effd43fb76c109f24eeec7f65a43471618d6 | Python | 4,650 | 144 | """server.py
model server example
Usage:
server.py test [options]
server.py [options]
Options:
-p --port=<port> The port number to communicate over [default: 5795]
-h --host=<host> The host name to communicate over [default: localhost]
-s --socket=<socket> A socket file to use, instead o... |
d538c955d6c385007836c8ca9a638fde3b23e525402846f193f88f943d932e5f | Python | 4,650 | 109 | # 2022/2023 Josue Page Vizcaino pv.josue@gmail.com
"""
This script processes XLFM data by deconvolving the images and saving the resulting volumes to disk.
It takes in several command line arguments, including the path to the data folder, the path to the PSF file, and the indices of the images to use. It also takes in ... |
92df23d6e60e236892a439ecef352c5f93530bd4a5c28f5078188cc6f0531f48 | Python | 4,651 | 116 | """F16 B3: the ported truncation protocol (treescope memo section 4).
Pinned regressions from the memo's test plan: port equivalence against
upstream on the measured shapes AND a non-default ``doubling_bonus``
(dropping the fifth parameter silently changes which cells are visible);
truncation-budget provenance (OUR 4,... |
28f1c1a0fc66f5c620f0848249679fff3f4bf3244c36e230cd70d8adc0d0ed8d | Python | 4,652 | 147 | """Tests for built-in MLP/FFN recipe behavior."""
from __future__ import annotations
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens import trace as trace_fn
class FFN(nn.Module):
"""Tiny transformers-4.57+ DistilBERT FFN block (lin1/lin2 children).
transformers >= 4.... |
bfaf2780ccdf5c56f356ef65c4e519ed46649f094275a690e6182d97545fc956 | Python | 4,652 | 141 | import unittest
from modular_splicing.evaluation.evaluation_criterion import MultiEvaluationCriterion
from modular_splicing.dataset.generic_dataset import dataset_types
from modular_splicing.evaluation.run_evaluation import evaluate_model_on_data
from modular_splicing.models_for_testing.list import AM, FM
from modular... |
345fea6ba360e7bf5d2da50855c16e94a736c9c28c9c8a5531f655d065a08876 | Python | 4,653 | 129 | #!/usr/bin/env python
"""
Tool for playing (and augmenting) single samples or samples from Sample Databases (SDB files) and DeepSpeech CSV files
Use "python3 play.py -h" for help
"""
import os
import sys
import random
import argparse
from deepspeech_training.util.audio import get_loadable_audio_type_from_extension, A... |
e1b41cfb694fa16d01cc3c6cc7149e07f2ca756905302c416510e4515142775b | Python | 4,653 | 101 | """5. Getting Started with Pre-trained SlowFast Models on Kinetcis400
=====================================================================
`Kinetics400 <https://deepmind.com/research/open-source/kinetics>`_ is an action recognition dataset
of realistic action videos, collected from YouTube. With 306,245 short trimme... |
44b83a04d51cfdc8af4fc0f0277e261634723be5c1210f5a6401141df59bd0a8 | Python | 4,654 | 145 | from typing import Optional, Tuple
import torch
from pytorch_lightning import LightningModule
from torch.nn import functional as F
from torchmetrics import Accuracy
from pl_bolts.models.self_supervised import SSLEvaluator
class SSLFineTuner(LightningModule):
"""Finetunes a self-supervised learning backbone usin... |
274d22a1434140289eaadc74b6e0b083faf6eae7305012351be2586e35e42c7a | Python | 4,655 | 142 | from .MarkovModel import MarkovModel
import sympy as sp
import numba as nb
from numba import njit, cfunc
import numpy as np
import numbalsoda
from numbalsoda import lsoda, lsoda_sig
# Simplest Artefact model containing cell capacitance
class ArtefactModel():
def __init__(self, channel_model, C_m=20e-3, R_s=30):
... |
cef4f99aafcc1aba13821117984ff12ccaf519db11fd5380ecde4efe3be1f09b | Python | 4,655 | 136 | # -*- coding: utf-8 -*-
import os
import glob
from re import search
from Bio.SeqIO import parse
from numpy.lib.function_base import select
import pandas as pd
import argparse
from utils import remove_files, clean_len_exaa
from preprocess import run_preprocess
from generate_interlayer_vec import run_generate
from calcu... |
9eb0fbae58d7660a40221174fd3f5e056d538f57e5e068cd0fd103f825b06ece | Python | 4,656 | 139 | # 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... |
f3f4f7124a34e899565a075ad1143df5ab223c484570f6264ccf75bd51d42c10 | Python | 4,656 | 115 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Written by Bin Xiao (leoxiaobin@gmail.com)
# Modified by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
fro... |
2025b1f413aa2f6f230d0abdb88083cf8c29e042a66edd695ed1f28bba0daca9 | Python | 4,662 | 112 | from model.SLD.encoder import Encoder
from model.SLD.IC_encoder import ICNet
from model.SLD.reducer import Reducer
from model.SLD.ode_func import ODEFunc
from prodict import Prodict
import torch
import torch.nn as nn
from torchdiffeq import odeint_adjoint as odeint
class TDNODE(nn.Module):
def __init__(
s... |
5a12386c50994110671b2af98ef06ebb9ab0d9253ab29407ad5582643917a8ee | Python | 4,662 | 134 | """
This part of the code was originally published by mahmoodlab and adapted for this project.
https://github.com/mahmoodlab/CLAM
Lu, M.Y., Williamson, D.F.K., Chen, T.Y. et al. Data-efficient and weakly supervised computational pathology on whole-slide images.
Nat Biomed Eng 5, 555–570 (2021). https://doi.org/10.1038... |
b73abcbda2c9eb6ab10936317f258c12c9cad3d47dcbdd31bd23acb1eaa79311 | Python | 4,663 | 125 | # %%
'''
Extracts regions based on SPM results. Saves ROI masks and a list of centroids.
Looks at con_0006 ('threat reversal') and con_0007 ('safety reversal') specifically.
Be mindful that this script needs 'supervision', e.g., to hand label each ROI which
may change depending on the exact parameters (namely cluste... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.