sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
480efe59feb082eaaa665ce8a89c0fe0aab51d862a7ec59ec6494b9f717eff13 | Python | 6,312 | 148 | """Unit tests for the PubMed download verification in src/createcompendia/publications.py.
verify_pubmed_downloads() is the backstop that makes it safe to carry PubMed files forward from a
previous run (see docs/RunningBabel.md, "Preloading PubMed downloads"): it MD5s every downloaded
`.gz` against the `.md5` file Pub... |
98bd572facc4016e3ab9b1de3fb20082eb9ea5d0af1e825aafdcb8b4d3e25afe | Python | 6,313 | 118 | # Generate events files for task-narratives
# This script reads raw behavior data files from d_beh for task-narratives, extracts time stamps and design information, and stores them in new *events.tsv files accompanying BOLD files.
# For more information, please see README.md and the associated paper (Jung et al., 202... |
2ef3e3b9d2119a6d3b735ff6343b8c46eb8c79c5fbc030877bcf2c3067bcb901 | Python | 6,315 | 167 | # #############################
#
# Copyright (C) 2018
# Jennifer Dreiling (dreiling@gfz-potsdam.de)
#
#
# #############################
import os
# set os.environment variables to ensure that numerical computations
# do not do multiprocessing !! Essential !! Do not change !
os.environ["MKL_NUM_THREADS"] = "1"
os.en... |
8591b8b6f5631cbf91a5c7956f784fd93d3da94d63da0ddb917043a5bb2fa598 | Python | 6,316 | 128 | # Copyright 2020 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... |
8e0a42e1ad2ba9007658da8fc0bd09dd53b53bc21d00b448ca705778c09c43d0 | Python | 6,316 | 103 | import numpy as np
from batchgenerators.utilities.file_and_folder_operations import *
from nnunet_mednext.dataset_conversion.utils import generate_dataset_json
from nnunet_mednext.paths import nnUNet_raw_data, preprocessing_output_dir
from nnunet_mednext.utilities.file_conversions import convert_2d_image_to_nifti
if _... |
91f768fc735ebb77ce83102e811c59bf6aaccf9ec621e675d83950b96e913ab7 | Python | 6,316 | 199 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 30 14:27:23 2023
@author: ingvieb
"""
from glob import glob
import shutil
import datetime
import SimpleITK as sitk
import numpy as np
import nibabel as nib
import json
import os
def createParameterMap(file, regType):
with open(file, "r") as f:
param_dict ... |
a7bf480bee123e98310b50edd8768c94cafa5dbeda4c3d8d39666ffeb277af6a | Python | 6,319 | 206 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import math
import numpy as np
import torch
from scipy.special import binom
from torch_geometric.nn.models.schnet import Gaussia... |
fa8c94906240152bb0827b8a0053c5f4fa59f9d768f02d48bf61431b234f44a3 | Python | 6,319 | 205 | # pylint: disable=too-many-locals
"""Tests for learning to rank."""
from types import ModuleType
from typing import Any
import numpy as np
import pytest
import xgboost as xgb
from xgboost import testing as tm
from .utils import Device
def run_ranking_qid_df(impl: ModuleType, tree_method: str, device: Device) -> No... |
7f2d0960e4b90adbc2e2423cded3cc28b81e7cc05ac4e590dd7635165aa3f7e9 | Python | 6,321 | 183 | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
import o... |
388a1511ce6fc6ecec02114c014630a87a450d29d92d8cd256afbf15093182b2 | Python | 6,322 | 222 | """Test l5pc example"""
import json
import os
import sys
from contextlib import contextmanager
import bluepyopt
from bluepyopt import ephys
if sys.version_info[0] < 3:
from StringIO import StringIO
else:
from io import StringIO
import pytest
L5PC_PATH = os.path.abspath(
os.path.join(os.path.dirname(__... |
142597235dc525da0ccd40ad025252914fa25a0f758b97002388f03dca2b079b | Python | 6,328 | 201 | #!/usr/bin/env python
"""
MetaWIBELE: extract_uniprot_pfam module
Extract the Pfam and UniProt mapping info
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in... |
653cf711104060960789f9bad99945331a34bcc1647bdd9cf41868d152e7fdc9 | Python | 6,334 | 164 | import torch
from Bio.PDB import Selection
from Bio.PDB.Residue import Residue
from Bio.PDB.PDBParser import PDBParser
from Bio.PDB.MMCIFParser import MMCIFParser
from easydict import EasyDict
from .constants import (AA, max_num_heavyatoms,
restype_to_heavyatom_names,
B... |
eeb17ca8f0be26c74611bf1eb0f0504e72f9b6e878801eb2c12f777081843d0d | Python | 6,334 | 205 | """Database models and session management."""
import logging
import uuid
from collections.abc import AsyncIterator
from datetime import datetime
from typing import TYPE_CHECKING, Annotated
import sqlalchemy as sa
from fastapi import Depends, Request
from fastapi_users.db import SQLAlchemyBaseUserTableUUID, SQLAlchemy... |
a4911461f9c11287efa7d73f8b367b97e1fe3fa70b7286e7864883f608bd67c1 | Python | 6,335 | 180 | # Modified from https://github.com/open-mmlab/mmcv/blob/master/mmcv/video/optflow.py # noqa: E501
import cv2
import numpy as np
import os
def flowread(flow_path, quantize=False, concat_axis=0, *args, **kwargs):
"""Read an optical flow map.
Args:
flow_path (ndarray or str): Flow path.
quantiz... |
cefa64fa35ca6d7cf1d10211bd68778abd8f764d17ee5b1bfae0b7d26bc8bc95 | Python | 6,335 | 148 | # AUTOGENERATED! DO NOT EDIT! File to edit: nbs/07b_collections.callbacks.ema.ipynb (unless otherwise specified).
__all__ = ['EMACallback']
# Cell
import logging
from typing import Any, Dict
from copy import deepcopy
import pytorch_lightning as pl
import torch
import torch.nn as nn
from pytorch_lightning.callbacks i... |
17dec5105c4f975dcff1378bf6c17a6f098c74f899936225cbf00a8a8fffa4b4 | Python | 6,339 | 190 | import pytest
from CybORG import CybORG
from CybORG.Simulator.Scenarios import EnterpriseScenarioGenerator
from CybORG.Agents.SimpleAgents.ConstantAgent import SleepAgent
"""
Testing the implementation of the mission_phases functionality.
Initially, step starts at -1 but allowed_subnets are filled as if mission_phas... |
03f011f710d4f11b2f2751a753d3ddc40c8c716544b7924846a244d38f688bd0 | Python | 6,340 | 115 | # Copyright 2020 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... |
15f304c20b8dfe3f62e87bd606a3f0c86659022ee94d889bcec7d7e3b670387e | Python | 6,343 | 187 | import bdpy
import numpy as np
import pandas as pd
import hdf5storage
import os
from itertools import combinations, product
def load_parameters(param_file):
"""
Load converter parameters from a CSV file.
"""
return pd.read_csv(param_file)
def load_brain_data(brain_dir, subjects_list):
"""
Loa... |
72401534893629798214ed8a4cd226388501e7e173f1880a473d2859aea404c4 | Python | 6,346 | 215 | """
Getting started with learning to rank
=====================================
.. versionadded:: 2.0.0
This is a demonstration of using XGBoost for learning to rank tasks using the
MSLR_10k_letor dataset. For more infomation about the dataset, please visit its
`description page <https://www.microsoft.com/en-us/res... |
e6842a22dbe78b3b61d2b3625fc6633e946ba899ee18dc329a57fbc043555dfc | Python | 6,353 | 212 | """
Experimental support for external memory
========================================
This is similar to the one in `quantile_data_iterator.py`, but for external memory
instead of Quantile DMatrix. The feature is not ready for production use yet.
.. versionadded:: 1.5.0
See :doc:`the tutorial </tutorials/exter... |
5db2b772fc9933ca4283df8f32e5b350769ec35c66afb71b95e010629f5b29e6 | Python | 6,355 | 179 | from typing import List, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import build_conv_layer
from torch import Tensor
from mmseg.registry import MODELS
class PatchTransformerEncoder(nn.Module):
"""the Patch Transformer Encoder.
Args:
in_channels (int): the... |
447b5347fd08b2d165a6922e96ca35b30876ab41bcdc0c717eaf9fe45ecebaad | Python | 6,356 | 203 | from types import SimpleNamespace
import numpy as np
import pandas as pd
from masscube.params import Params
from masscube.raw_data_utils import (
MSData,
McrawStore,
Scan,
load_mcraw,
mcraw_matches_source,
read_mcraw_manifest,
save_mcraw,
)
def _make_mcraw_data():
data = MSData()
... |
e4d2619460d0eae243c7c57c7cb17d0e91dec330695d9c1ab7a39453685ba08a | Python | 6,358 | 205 | #!/usr/bin/env python
"""
MetaWIBELE: mspminer_msp_uniref_annotation module
Assign UniRef annotation to MSPs
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
i... |
42ea6039e7740231244c36a1c004349a3dbb87fe144f4d9228324c7ef2ab702b | Python | 6,364 | 186 | # Modified from https://github.com/open-mmlab/mmcv/blob/master/mmcv/fileio/file_client.py # noqa: E501
from abc import ABCMeta, abstractmethod
class BaseStorageBackend(metaclass=ABCMeta):
"""Abstract class of storage backends.
All backends need to implement two apis: ``get()`` and ``get_text()``.
``get(... |
385ecd8359dfaef6be3b5bac2e3632ff06f154feabbaef06aae9fa004d7abb5f | Python | 6,365 | 164 | import argparse
import os
import json
import torch
from fengshen_inner.models.llama.configuration_llama import LlamaConfig as FengshenConfig
from fengshen_inner.models.llama.modeling_llama import LlamaForCausalLM as FengshenLlama
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
from fengshen_inner... |
d408c134fc599b05c4df2e6147585b9e158dc6a3645cc9bf2bf33a37b6b35e2a | Python | 6,369 | 141 | import torch
import os
import random
import math
import argparse
from fengshen.data.fs_datasets.fs_datamodule import FSDataModule
from fengshen.example.deepVAE.vae_pl_module import DeepVAEModule
from pytorch_lightning import (
Trainer,
loggers,
)
from pytorch_lightning.callbacks import ModelCheckpoint, Learni... |
1bfdd70db2695f233f43f7c862ac2db3a9ae34e76deeaaeb8bd93b0f15497e28 | Python | 6,371 | 143 | import argparse
import pickle
import numpy as np
import tensorflow as tf
from tensorflow import keras
import tsgm
N_EPOCHS_DEFAULT = 10
BATCH_SIZE_DEFAULT = 256
LATENT_DIM_DEFAULT = 16
DEFAULT_GAN_ARCHITECTURE = "cgan_base_c4_l1"
DEFAULT_VAE_ARCHITECTURE = "vae_conv5"
def _gen_dataset(X, y, batch_size=BATCH_SIZE_D... |
61ac96b11fec1df2dac0e68ac3db61f6071c9283cd5ef9c45eeabb5c04db5212 | Python | 6,372 | 153 | """
Benchmark the 3 modes:
1. Static feature: AtomType
2. Marching Observers
3. Probability Density Flow
"""
import os, argparse, time, json
import h5py as h5
import numpy as np
import pytraj as pt
from collections import OrderedDict
import nearl
import nearl.features, nearl.featurizer, nearl.io
# from nearl.io ... |
45bc3e0cb4050bf793d0f8c50116ad2e871b982633b9a664031ecb2d7fe597cd | Python | 6,374 | 204 | #!/usr/bin/env python
"""
MetaWIBELE: sum_to_protein_family_abundance module
Sum over protein families based on reads mapped to gene catalog of nucleotide representatives
Copyright (c) 2019 Harvard School of Public Health
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software a... |
5ca453d7bf9d1d3a436b292aa4b8a5b13d1d38899c7c3e370ce2ba29b5c2e7f6 | Python | 6,376 | 184 | import base64
import logging
import os
from time import time
import yaml
from medperf.asset_management.gcp_utils import CCWorkloadID
from medperf.entities.cube import Cube
from medperf.entities.model import Model
from medperf.entities.dataset import Dataset
from medperf.entities.execution import Execution
from medper... |
3a7eebba22dc3139971b986f804da1f169948991a4d5374466b3322897152bb7 | Python | 6,379 | 179 | from __future__ import annotations
import os
from medperf.entities.interface import Entity
from medperf.entities.schemas import CertificateSchema
from medperf.account_management import get_medperf_user_data
from medperf import config
from medperf.exceptions import MedperfException
from medperf.utils import generate_tmp... |
a25764f7f1b32b0b6d123956e64c0e5a10a9f244f26197c72e7197b30952f609 | Python | 6,379 | 170 | import numpy as np
import scipy.sparse
import scipy.sparse.linalg
try:
import pyamg
except ModuleNotFoundError:
pyamg = None
try:
import cupy
import cupyx.scipy.sparse
import cupyx.scipy.sparse.linalg
except ModuleNotFoundError:
cupy = None
cupyx = None
try:
import sparseqr
except Mod... |
d0ab0dd2741b1dfaf6ec60548022784feb4cef943e2788cee80394b9697fa142 | Python | 6,381 | 188 | # -*- coding: utf-8 -*-
from django import template
from django.db.models import Count
from ..models import Project
from .common import is_string_type, natural_sort
register = template.Library()
@register.filter
def get_stack(stacks, pos):
""" Returns an image stack out of stacks. Which one is
determined by ... |
36d0a00fbfd7b948592a6cd2d5fe9cbfdd227deb1f30fd4cca1aeae89b339548 | Python | 6,384 | 162 | """Whole-session time-binned metrics.
Some experiments score a continuous behavioral variable at a coarse cadence --
akinesia severity rated once every two minutes, say -- and ask how the photometry
signal tracks it. That question needs the session reduced to one value per fixed
time bin rather than to event-triggered... |
d390ce152ac04d8ee66c6c6c2975be00cdc29cfff5eeb5aa165b5b196d982195 | Python | 6,385 | 180 | import importlib
import inspect
import re
import sys
from itertools import compress
from keras import backend as K
import pytest
if K.backend() != 'tensorflow':
pytestmark = pytest.mark.skip
modules = ['keras.layers', 'keras.models', 'keras',
'keras.backend', 'keras.engine',
'keras.wrappers... |
50d2afa85796dec89cc90486fd373fd64b242a84f073cfcbc009655e6494f03b | Python | 6,386 | 183 | # -*- encoding: utf-8 -*-
'''
Copyright 2022 The International Digital Economy Academy (IDEA). CCNL team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.o... |
118a465321803b4dcbb8d702c39bbfd29f35f70a7c6af37a9c52afbc1e2869b8 | Python | 6,387 | 193 | from typing import Dict, List, Optional, Tuple
import torch
from torch import nn, Tensor
from torch_scatter import scatter_mean
from oa_reactdiff.model import EGNN
from oa_reactdiff.model.core import GatedMLP
from oa_reactdiff.utils import (
get_subgraph_mask,
get_n_frag_switch,
get_mask_for_frag,
get... |
81abd48cb6cfae52116b7e2687b654a1c33439b66ab8110c02bd7a47721ae535 | Python | 6,393 | 249 | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from data.sequencing import data_import
from data.sequencing import data_analysis
# Plot settings
plt.rcParams.update({'font.size': 20, 'svg.fonttype' : 'none',
'figure.figsize... |
ae76c0a50d198b0d19565bd8bfc5d6663050de67fbf808152b0a9212818bd410 | Python | 6,395 | 184 | import plotly.graph_objects as go
import plotly.express as px
import plotly.io as pio
import pandas as pd
import numpy as np
import seaborn as sns
from matplotlib.colors import to_hex
from params import palette, nanfiller
def figure_adjustments_rep(fig):
for data in fig.data:
data['mode'] = 'text'
... |
db65e6ed09dce82cd09ad927bc149a5c18982592698ac9939f8b7144b5aa50ed | Python | 6,396 | 159 | """
simulator.py
- main entry point to start the motion simulation
- run this script (from iml-dl/.) with:
python -u ./projects/motion-simulation/simulator.py
--config_path path_to_config_file.yaml
Note: A config file needs to be generated first. An example of a config file
can be found under motion-simul... |
17493ef390f3be4b6b0eb320cb88169faee06f03a3764e912de7507adfbd6b1c | Python | 6,399 | 168 | import os
import sys
import itertools
import numpy as np
import pandas as pd
import torch
from torch.autograd import Variable
import bdpy
# Adding the parent directory to sys.path for module imports
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..')))
from NCC_content_loss.models impor... |
95e3d1ed1c139cd2659525b8e67cf7be860d5faed5e4551b304b5e516853419c | Python | 6,401 | 185 | #!/usr/bin/env python
#
# Utility function to denoise images
#
# Copyright (c) 2015 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
import sys
from time import time
from typing import Sequence
import numpy as np
from spinalcordtoolbox.image import Image
from spinalcordtoolbox.utils.fs i... |
f264b848ea618cb42f045ec34cd06dc66ff6c81313d3ea2dc9a5c984053ce60f | Python | 6,403 | 139 | import logging
import re
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional
import yaml
logger = logging.getLogger(__name__)
_instance: Optional["SynonymFilter"] = None
def get_synonym_filter() -> "SynonymFilter":
global _instance, logger
if _instance is None:
... |
856d64d71e44407401297b551884fb4cd1aba8082de0ff5fc60fac3dd42f094d | Python | 6,405 | 174 | # Copyright (c) Meta Platforms, Inc. and 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 logging
import os
import torch
from hydra import compose
from hydra.utils import instantiate
from omegaconf import... |
f0995adb86fc444621ead57fbb591eea9df7891b0d90bc75e9647627d02b12ca | Python | 6,405 | 159 | """Integration-suite-local shared constants and helpers.
Split out of ``conftest.py`` so the handful of integration test modules that need these symbols
at import time (``test_integration_step2.py``, ``test_integration_dandi.py``) can import them
directly via a package-relative import, instead of relying on the ambigu... |
c24d23af327f196e633e20ac2a5410454b38596981ed33c81658808cf2dbeaff | Python | 6,408 | 194 | from medperf.exceptions import ExecutionError, CommunicationError
from medperf import config
import os
import requests
import semver
from .docker_utils import volumes_to_cli_args as docker_volumes_to_cli_args
import shlex
from medperf.utils import run_command
import logging
def get_docker_image_hash_from_dockerhub(d... |
40b9261dfe0e8fdb67acc0587b40d9927c0e9f529693cf943fd869ed754e1bb9 | Python | 6,413 | 221 | """Ortholog retrieval and donor tracking for v7+ databases.
Provides methods for:
- Finding orthologs from speciation events
- Tracking closest donors for functional annotation
- Filtering orthologs by taxonomic scope
"""
from typing import Dict, List, Optional, Set, Tuple
from .db import EggnogDB
from .tax_scope im... |
195ce1a5efe9e784f44cf6a591b38963cb3c67eb793d805b10531bde43e8d072 | Python | 6,419 | 160 | # tests/test_ordering.py
"""Tests that all paginated list endpoints return items newest-first (DESC)."""
import time
import pytest
from conftest import make_room_address
from zndraw_joblib.schemas import (
JobSummary,
PaginatedResponse,
TaskResponse,
WorkerSummary,
)
# ── Jobs ──────────────────────... |
52dbaed86a67fa39eaa5ccabd1ec9faaa29e13c106664cf34553e3f48c601d28 | Python | 6,419 | 212 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import math
from typing import Dict, Union
import numpy as np
import torch
from scipy.special import binom
from torch_geometric.nn.models.sc... |
f729dafb76bdeb05381496233a97679f74802e6acc19b26c55645246885ca041 | Python | 6,420 | 157 | # -*- coding: utf-8 -*-
"""
Created on Thu May 9 20:36:51 2024
@author: mbmad
"""
import numpy as np
import pandas as pd
import pyabf
from patchanalysis.measures.measuretools import InvalidRecordingError, NoResultError
from typing import Union
class WorkerAttemptedDestructiveOverwrite(Exception):
"""
Raise ... |
cfbdef93235b2b512b8776bba936bf8e334af7499d1517bdc5a071cdc9436006 | Python | 6,425 | 189 | #-*- coding: utf-8 -*-
# Some basic tools for data processing
from numpy import nonzero, sign
from scipy import stats
from scipy.interpolate import interp1d
from pylab import *
from scipy import signal
from scipy.fft import fft, ifft, fftshift
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.color... |
254533aa260ce4bf160fbd1cebf3788cdafa1b3951462d719d6eed3ff1e5bc34 | Python | 6,427 | 138 | # Copyright 2020 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... |
c6ce64d9c9eda83ce489f10d5e5de7c4b482a68d5756028a0affe978cfb81c35 | Python | 6,427 | 142 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
def plot_dbscan_clusters(cluster_arr, dbscan_labels, hierarchical_label, save_path=None):
outlier_indices = np.where(dbscan_labels == -1)[0]
non_outlier_indices = np.where(dbscan_labels... |
5bb8cb706d1f54ea13d46422b89cc42cc3c962c6763fd568e1388c4cde574e71 | Python | 6,432 | 177 | #! python3
# -*- encoding: utf-8 -*-
# ===================================
# File : test_model_with_fine_tune.py
# Time : 2024/06/05 12:19:59
# Author : Zehong Zhang
# Contact : zhang@fmp-berlin.de
# ===================================
import os
import torch
import torch.nn as nn
import torch.optim as o... |
dae9d5a90d4b0d217b97aac6f512dc18d214d2b15d3ec9b24f8953139b814ecf | Python | 6,441 | 153 | """Unit tests for src/datahandlers/doid.py.
Two fixtures, both copied verbatim from `babel_downloads/DOID/doid.json`:
- `doid_icd_xref_sample.json` holds [`DOID:2476`](http://purl.obolibrary.org/obo/DOID_2476)
"hereditary spastic paraplegia", the grouping term whose `ICD10:G11.4` xref -- shared with all 60
of its... |
c7a2cf717da539aca55b35149be8377fdd54d71fbd28e78994e3bc9caf72dbc8 | Python | 6,443 | 205 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import torch
from torch_scatter import scatter
from ocpmodels.modules.scaling import ScaleFactor
from ..initializers import he_orthogonal_i... |
12f5a1e3d4126340e41e2b20304de6bf5ff7456cfae6103a9f006afaf96ccd0c | Python | 6,444 | 201 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 30 14:27:23 2023
@author: ingvieb
"""
from glob import glob
import shutil
import datetime
import SimpleITK as sitk
import numpy as np
import nibabel as nib
import json
import os
def createParameterMap(file, regType):
with open(file, "r") as f:
param_dict ... |
81fdd6ec12cc1c6e328fe3c2b77f8431d2aed52b02215fcc68fa84debf690060 | Python | 6,447 | 134 | import argparse
import pandas as pd
from sklearn.metrics import confusion_matrix
from tqdm import tqdm
# pytorch
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data import DataLoader
from torchsummary import summary
# data set formatting
from nanopore_dataset import create_sample_map
... |
3fe5d450b628330ebdca7868e33031d806d99d79341bca6a3dd5035eed3f0a9f | Python | 6,450 | 200 | """
Demo for defining a custom regression objective and metric
==========================================================
Demo for defining customized metric and objective. Notice that for simplicity reason
weight is not used in following example. In this script, we implement the Squared Log
Error (SLE) objective and... |
ea68b4946da3f1c7e4c8954eff97de480ffb2260d322b7ed269a7c292d80b150 | Python | 6,451 | 181 | import torch
import torch.nn.functional as F
import numpy as np
import matplotlib.pyplot as plt
import os
import logging
from torchvision import datasets, transforms
from torch.utils.data import DataLoader
from torchvision import models
# Ensures reproducibility by setting the random seed across all libraries
def seed... |
a412415b2cad158dcf9f433cd29143cfa8b6b67692f6bc799a850b8319fd72b6 | Python | 6,465 | 152 | ############
# https://github.com/lessw2020/Ranger-Deep-Learning-Optimizer
# This code was taken from the repo above and was not created by me (Fabian)! Full credit goes to the original authors
############
import math
import torch
from torch.optim.optimizer import Optimizer
class Ranger(Optimizer):
def __init_... |
22fdf8c21c86059c81377581b402d1b30a1e336a3c4e7dcb9b88be96bae86800 | Python | 6,467 | 202 | # -*- coding: utf-8 -*-
"""
Created on Mon Oct 30 14:27:23 2023
@author: ingvieb
"""
from glob import glob
import shutil
import os
import datetime
import SimpleITK as sitk
import numpy as np
import nibabel as nib
import json
def createParameterMap(file, regType):
with open(file, "r") as f:
param_dict ... |
bdfb46dcb755c0f7c6ffd8fdaf001b26c2c02211db7f515460a5d8747ff9560d | Python | 6,473 | 211 | """
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
import math
from typing import Dict, Union
import numpy as np
import torch
from scipy.special import binom
from torch_geometric.nn.models.sc... |
01c18ebb306c52f2fb423f2931375ff9ab6494c20fe621cff44d597311f8baa1 | Python | 6,477 | 157 | import torch
import torch.nn as nn
class RealValCNNLineDet(nn.Module):
""" Convolutional network to classify kspace lines
Input to the network is multi-echo kspace data, where real and imaginary
parts are on two separate channels. Output is a mask classifying each line as
artefact-free or corrupted.
... |
8bfe16a6c8d9295b060be8375d42ed5787fc0b077d26abbe52feb4741bc607d9 | Python | 6,486 | 198 | #!/usr/bin/env python
# coding: utf-8
import os.path as op
import random
import time
import matplotlib.pyplot as plt
import numpy
import sklearn
import torch
import torch.nn.functional as nn_func
from sklearn import preprocessing
from sklearn.metrics import adjusted_rand_score
from torch.nn import Linear
from torch_g... |
c1be2a9ef4aad1d5a5bd1c4e6daef62a395af6af765f0dd8dc8cc8539967e4d5 | Python | 6,487 | 180 | """Benchmark numpy-return commands vs the *_dlpack GPU-output commands.
Three destinations per feature family:
1. numpy: the command's own wall time, result on the host
2. numpy+to_gpu: plus torch.from_numpy(...).cuda(), i.e. what a model actually needs
3. dlpack: written straight into CUDA memory, alloca... |
b7a26309632d83ca88e030bb6326786ff799f875b9a7e4cebb7fd6a261c5e54c | Python | 6,489 | 193 | """Integration test for template room isolation.
Verifies that when a room is set as the default template:
1. New rooms copy frames from the template
2. Modifications to new rooms don't affect the template
3. The template remains unchanged after operations on derived rooms
"""
import pathlib
from collections.abc impo... |
a08fa10217b6ee8cf3deec31e55c6c660e80081c27d0dc88d8d63c708fbd32e1 | Python | 6,497 | 194 | from luna.paths import LunaPaths
from luna import candidate_info, dataset
from luna.ct import Ct
from luna.prepcache import LunaPrepCacheApp
from torch.utils.data import DataLoader
from Utils.models import *
from Utils.TrainModelLUNA import *
from Utils.config import *
from tqdm import tqdm
import matplotlib.pyplot as ... |
3938ee423f3d03bfc66aa2068f6350b3d270ffadf3e02035e3b8896c8574eed9 | Python | 6,498 | 192 | #!/usr/bin/env python
#
# Merge images. See details in function "merge_images".
#
# Copyright (c) 2014 Polytechnique Montreal <www.neuro.polymtl.ca>
# License: see the file LICENSE
# TODO: parameter "almost_zero" might case problem if merging data with very low values (e.g. MD from diffusion)
import sys
import os
fro... |
759411e1afe5492d22360e637cc4ecab7379f2ced9e5018c52b80d61d57d21c5 | Python | 6,507 | 158 | import copy
import numpy as np
import torch
from oa_reactdiff.dataset.base_dataset import BaseDataset, ATOM_MAPPING, SAM_CHARGED_ATOM_MAPPING
FRAG_MAPPING = {
"reactant": "product",
"transition_state": "transition_state",
"product": "reactant",
}
def reflect_z(x):
x = np.array(x)
x[:, -1] = - x... |
6c431af9832c92d5af48bf2f0bebafdb6a55b17ca249fc4c3d94f056aca4ff33 | Python | 6,510 | 138 | import numpy as np
import matplotlib.pyplot as plt
import os
from grid_cell.manifold_fitter import label_mesh
from sklearn.model_selection import train_test_split
from sklearn.decomposition import PCA
from grid_cell.sphere_manifold import Circle_Manifold, get_circle_mesh
from grid_cell.ori_tuning_manifold import Ori_Tu... |
b53983a3a4a5325249963436fac14a391e2de5c40220c3a47d095bf97a29bd0b | Python | 6,515 | 99 | # Copyright (c) OpenMMLab. All rights reserved.
from mmseg.registry import DATASETS
from .basesegdataset import BaseSegDataset
@DATASETS.register_module()
class COCOStuffDataset(BaseSegDataset):
"""COCO-Stuff dataset.
In segmentation map annotation for COCO-Stuff, Train-IDs of the 10k version
are from 1 ... |
cfdd42adacaff16b8556499c7f1966161c9cb2ce42815364c382021e44e9fb08 | Python | 6,524 | 200 | # -*- coding: utf-8 -*-
"""
Created on Sat May 23 10:38:20 2020
@author: george.dickinson@gmail.com
This program is a Python script developed to analyze the motion of intracellular Piezo1 proteins labeled with a fluorescent tag.
It allows the user to load raw data from a series of image files and track the movement o... |
28fa3657644b360e20a5e46e3808df4fdc8fd93d30c4d028c9689c3bd0309405 | Python | 6,529 | 195 | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from src.circuit import _positive_angle
from src.bold import calc_sum_activity
def plot_bold(bold,outdir):
"""
Plots bold signal and saves it to file.
Arguments:
bold (dataframe): bold signal for each condition (columns = conditions, rows = ... |
f365ac1205abd71403e32b9c524e440382b7f5874969a19aa9ef8812554be5d2 | Python | 6,530 | 174 | import copy
import numpy as np
class PID:
def __eq__(self, other):
if issubclass(type(other), PID):
return True
if type(other) is int:
return True
return False
def compare_fundamental_observations(obs1: dict, obs2: dict, translation: dict):
assert type(obs1) ... |
4ef182bd36093b06d05c2b708bb48a9661feeb16b088113cf9bc2b61594fd8c2 | Python | 6,531 | 207 | """Isosurface REST endpoint — marching cubes extraction for volumetric data."""
from __future__ import annotations
from typing import Annotated
from uuid import (
UUID, # noqa: TC003 # runtime: FastAPI builds TypeAdapter for owner_id path param
)
import msgpack
import msgpack_numpy
import numpy as np
from fast... |
bd38eb1725f81e9291c072fb74f070f659f64cb68a276ad7746b7e841fd48a64 | Python | 6,533 | 147 | # Copyright 2020 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... |
7c5ce79f4d10338a6e4b3493c6ef8020bc94568941ed32d24c50411526ba470e | Python | 6,535 | 287 | """Pydantic models for Socket.IO events.
Event names are derived from class names in snake_case:
- RoomJoin -> "room_join"
- SessionJoined -> "session_joined"
"""
from __future__ import annotations
from datetime import datetime
from typing import TYPE_CHECKING, Any, Literal, Self
from uuid import UUID
from pydantic... |
199e711f690a043e231e7406a99789e487f2382f732cd9733de26382aac97d91 | Python | 6,536 | 189 | import os
from medperf import config
import yaml
from medperf.utils import get_file_hash
from medperf.exceptions import CommunicationRetrievalError
from medperf.tests.mocks.benchmark import TestBenchmark
from medperf.tests.mocks.dataset import TestDataset
from medperf.tests.mocks.execution import TestExecution
from me... |
8f8331978c8c1ff91a1df00996ec08abcc164834c5c6112d2dea24387e84ea5e | Python | 6,536 | 187 | from django.http import Http404
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework import status
from rest_framework.request import Request
from django.contrib.auth import get_user_model
from .models import Certificate
from .serializers import (
Certi... |
b43e79f2bb72b765eb66a5b858daa004eb5f42e591856a256cc870aa85ce3560 | Python | 6,537 | 207 | #!/usr/bin/env python
#
# Copyright 2006, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
d973ffa7ed2c468f8e9db6e4860f9fb5d9d9ea1348aa7dbfab92e123e497a35e | Python | 6,539 | 203 | import functools
import pandas as pd
from torch.utils.data import DataLoader
import numpy as np
import pandas as pd
from sklearn.metrics import roc_auc_score
from sklearn.linear_model import LinearRegression
from tqdm.auto import tqdm
from rde.utils.misc import inf_iterator, BlackHole
from rde.utils.data import Paddi... |
44034a2982112bbb04f4ee11e8a72f915cdfb3f2dbe08649cc0baaf6cb29158e | Python | 6,541 | 147 | import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
def plot_dbscan_clusters(cluster_arr, dbscan_labels, hierarchical_label, save_path=None):
outlier_indices = np.where(dbscan_labels == -1)[0]
non_outlier_indices = np.where(dbscan_labels... |
574126655d8bcd8af235ed37c119fcae7b5afc12a81659a0f21bf7b528adcae9 | Python | 6,541 | 186 | import argparse
import glob
import logging
import os
from typing import Dict, Optional
import ocpmodels
"""
This script provides users with an automated way to download, preprocess (where
applicable), and organize data to readily be used by the existing config files.
"""
DOWNLOAD_LINKS_s2ef: Dict[str, Dict[str, str]... |
bce37f51949816ed39fff340e92b7139e0cae3cdca8998a27365db8d5048259a | Python | 6,541 | 132 | from ipaddress import IPv4Address
import random
from typing import List, Tuple
import pytest
from CybORG.Agents.Wrappers.BlueEnterpriseWrapper import BlueEnterpriseWrapper
from CybORG.Shared.AgentInterface import AgentInterface
from CybORG.Shared.Session import Session
from CybORG.Simulator.Actions.ConcreteActions.Cont... |
37c25ea4b246cf1cb479fb6e4112d64fdc41c5438eaabd77f035f2ed296d1d60 | Python | 6,542 | 174 | from __future__ import absolute_import
from __future__ import print_function
import pytest
import numpy as np
from keras import backend as K
from keras.utils.test_utils import get_test_data
from keras.models import Sequential, Model
from keras.layers import Dense, Activation, GRU, TimeDistributed, Input
from keras.uti... |
949c34d147bab0f96d48d42e8b38f44c55d819b5f566f08bc1d916981d3cb888 | Python | 6,542 | 206 | """Tests for default camera GET/PUT endpoints, delete cleanup, and Python client."""
import json
import pytest
from helpers import auth_header, create_test_room, create_test_user_in_db
from httpx import AsyncClient
from sqlalchemy.ext.asyncio import AsyncSession
from zndraw.client import ZnDraw
from zndraw.geometrie... |
182e43370f1c115e209c861c61d9f19ba6411f79cbc9958ac7a8dffd3c22fcd1 | Python | 6,544 | 173 | import os
import subprocess
import time
import dask
import numpy as np
from dask.distributed import Client, LocalCluster, performance_report
import nearl
from nearl import _tempfolder, features
# Only needs the fingerprint of the
def parallelize_traj(traj_list, focused_res):
traj_list = [i for i in traj_list]
... |
3e9127bd071114c01ebf740abaab69b8d777c084482ffc9affa58c351916f011 | Python | 6,544 | 140 | import os, sys
sys.path.append(os.path.join(os.path.dirname(os.path.realpath(__file__)), os.pardir))
# For replicating the experiments
SEED = 42
import argparse
import time
import random
import numpy as np
import scipy.sparse as sp
import torch
np.random.seed(SEED)
torch.manual_seed(SEED)
from torch import optim
import... |
3d8bda99d290c6f0a9b3388e50f290751f16ba1649d33a9449d7c8276a6094c1 | Python | 6,546 | 216 | import torch.nn as nn
import torch.nn.functional as f
from torch import Tensor
import torch
import numpy as np
class CE_AV(nn.Module):
"""
0 Anger
1 Anticipation
2 Disgust
3 Fear
4 Joy
5 Sadness
6 Surprise
7 Trust
Positive: Anticipation, Joy, Surprise, Trust
Negative: Anger,... |
23f01acc8ad028217e771ef7c3e5c8b0082ba2ffbe8a1461b8059d89f96bc673 | Python | 6,550 | 202 | import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledSiLU(nn.Module):
def __init__(self, inplace: bool = False) -> None:
super(ScaledSiLU, self).__init__()
self.inplace = inplace
self.scale_factor = 1.6791767923989418
def forward(self, inputs):
return... |
58d45c0f7c4643565eaaf57679a780b61d0591fcab380ea901a95d5f75df8566 | Python | 6,553 | 142 | # run fit_gkr_models.py first
import hickle as hkl
from umap import UMAP
from grid_cell.ploter import gp_torus_surface
from grid_cell.util import pca_accumulated_variance_explained_ratio
from sklearn.decomposition import PCA
import matplotlib.pyplot as plt
from grid_cell.gkr import GKR_Fitter
from grid_cell.manifold_fi... |
081b821deb10c50e49241fb9a3d06a0824144138a63411f5ef1fb84e1c30724e | Python | 6,557 | 142 | # -*- coding: utf-8 -*-
"""
@author: Eslam Mohamed
@email: es.ahmed@nu.edu.eg
Functions to read, load and process EEG Data
"""
import os
import pandas as pd
import numpy as np
from scipy import signal
from typing import List, Tuple
def process_eeg(TIME_STEPS:int = 1200, included_states: List[str] =["Up", "Down", "L... |
f9622a1ae3cc029eab5076d3ef2ba6e7e8cf5ae791dc677293226817867788f4 | Python | 6,561 | 161 | import numpy as np
from collections import Counter
# Custom functions
from src.utils import *
class SIRIRAJ():
def __init__(self, args) -> None:
self.data_dir = os.path.relpath(args.data_dir)
self.results_dir = os.path.relpath(args.results_dir)
self.models_dir = os.path.relpath(args.models... |
91a336d365c620e4ac6e3ca92055a55e46d50143addf37c71d95b5c4f03b00b4 | Python | 6,563 | 182 | import os
from pathlib import Path
import shutil
from medperf.entities.dataset import Dataset
import medperf.config as config
from medperf.entities.cube import Cube
from medperf.entities.benchmark import Benchmark
from medperf.utils import (
approval_prompt,
dict_pretty_print,
get_folders_hash,
sanitize... |
2f30645f9135a82690ec6f677b0f93740eeaadaccaf7f7169f32266666b6db75 | Python | 6,565 | 212 | import os
from kgx.source import OwlSource
from kgx.transformer import Transformer
from tests import RESOURCE_DIR
from pprint import pprint
def test_read_owl1():
"""
Read an OWL ontology using OwlSource.
"""
t = Transformer()
s = OwlSource(t)
g = s.parse(
os.path.join(RESOURCE_DIR, "g... |
a1e0cc51d69c53c436dc75ceae365531f771a03f8c9de966a891ceea120413c1 | Python | 6,568 | 163 | # SPDX-License-Identifier: BSD-3-Clause
import os
import torch
import onnxruntime
import numpy as np
from retinanet.model import Model
from PIL import Image
from torchvision import transforms
from onnx import numpy_helper
import urllib
data_dir = 'test_data_set_0'
url, filename = ("https://github.com/onnx/models/ra... |
7b11a272ed64aa331b6d1cdea66b043ec3214f0cd8e614ba88150d0f538bd476 | Python | 6,572 | 214 | #*******************************************************#
# Classes used as configuration files
#*******************************************************#
class DatasetConfig:
'''
Class for defining dataset parameters: shape, split ratio, augumentation etc.
'''
'''
Imgs_png_home_path = Root direct... |
12279a19fc9f8327a5e7503509f48c8f9c5c45accc3773b0fe4134e41baa4275 | Python | 6,573 | 164 | # Copyright 2020 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... |
405d2bd4ef169cb07034ad6eea5884ba395d1aa78b849461cec74df8a539aca3 | Python | 6,578 | 190 | import pickle
import numpy as np
import torch
from torch.utils.data import Dataset
import torch.nn.functional as F
from oa_reactdiff.dataset.datasets_config import ATOM_MAPPING, SAM_CHARGED_ATOM_MAPPING
class BaseDataset(Dataset):
def __init__(
self,
npz_path,
center=True,
zero_c... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.