sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
9fed5663b288e939d99aef538f46453f88af316ee2d4f8734167092bf992d26f | Python | 2,996 | 74 | import holoviews as hv
import numpy as np
import pytest
from guppy.visualization.transients import build_peaks_overlay
from guppy_test_data import resolve_plot
@pytest.fixture
def timestamps():
return np.array([0.0, 1.0, 2.0, 3.0, 4.0])
@pytest.fixture
def z_score():
return np.array([0.5, 1.5, 0.2, 2.5, 0.... |
40e8d8c76e1561333bc8dee9e85b0354f1d8a58307ee998036a406ca5c196b11 | Python | 2,997 | 94 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import sklearn.metrics as metrics
def plot_roc_auc():
# Create figure
plt.figure(figsize=(10, 8))
# Define colors for different modes (expand as needed)
colors = plt.cm.rainbow(np.linspace(0, 1, len(mode_list)))
for mode, col... |
db11efd9fee2f5b49668346d569e75d734c1a9c4f2f5e25aa16a35d87d639448 | Python | 2,997 | 60 | import sys
tumor_id=T2 # specify ID
age=77*365 # specify age (in days)
import math
import numpy as np
from pyabc.external.r import R
r = R(tumor_id+"Run_model_heme_WGS_data_2_branched_clones.R")
model = r.model("myModel")
distance = r.distance("myDistance")
sum_stat = r.summary_statistics("mySummaryStatistics")
... |
b934e7f6ebdab7c5faa800c0a261abd31420aba26afb7dce18e15ffddd2b69ca | Python | 2,998 | 89 | """
Generate all nulls for annotations
"""
from pathlib import Path
import numpy as np
from eigenstrapping_analysis.utils import (
get_rootdir, MSEED, get_medial, join, save_npy, load_npy,
get_num_threads
)
from eigenstrapping import SurfaceEigenstrapping
from neuromaps.nulls import alexander_bloch, burt2020... |
300ebe6157c959793a05ebfcca9920f155d004abab8b29122fb2aed7f8900ce1 | Python | 2,999 | 92 | # Authors: Pierre Ablin <pierre.ablin@inria.fr>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD (3-clause)
import warnings
import pytest
import numpy as np
from sklearn.utils._testing import assert_array_almost_equal
from sklearn.utils._testing import assert_warns
from picard import Pica... |
140b63672eb10555ba0b9899ab5c5ebf6ffabec31c521936c18da5393ffbad0c | Python | 3,000 | 82 | #!/usr/bin/env python
import argparse
import torch
from torch.utils.data import DataLoader
from rdkit import Chem
from rdkit import rdBase
from tqdm import tqdm
from MCMG_utils.data_structs import MolData, Vocabulary
from models.model_rnn import RNN
from MCMG_utils.utils import decrease_learning_rate
rdBase.DisableL... |
226a09fd6f4bee44a4d42a08722ed255a920cc68b0c8ec1af71421e5e34a6944 | Python | 3,001 | 115 | """
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 torch
from ..initializers import he_orthogonal_init
class Dense(torch.nn.Module):
"""
Combines dense layer wit... |
3315e6ee6629e831fddc47e0c6af29c4840de1f021f05f7b0df9e5467e5ab28c | Python | 3,003 | 79 | """
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.
"""
# Borrowed from https://github.com/rusty1s/pytorch_geometric/blob/master/torch_geometric/transforms/random_rotate.py
# with changes to keep t... |
9ca8aa517afad244216632ca8c339a276ef43515e5dd73f19fe404025f6aa487 | Python | 3,003 | 93 | """E2E test: Client data persists across disconnect/reconnect cycles.
Uses a real uvicorn server via the server_factory fixture.
"""
import ase
import numpy as np
from zndraw import ZnDraw
def _make_atoms(x: float) -> ase.Atoms:
"""Create a simple H atom at position (x, 0, 0)."""
atoms = ase.Atoms("H", pos... |
c76314940364e401750ce7a829516305293c8f65fea0eb0a7bb1b0ac8ad54c51 | Python | 3,003 | 72 | # -*- coding: utf-8 -*-
@login_required
def initialize_components_for_skeleton(request, project_id=None, stack_id=None):
skeleton_id = int(request.POST['skeleton_id'])
# retrieve all treenodes for the given skeleton
treenodes_qs, labels_qs, labelconnector_qs = get_treenodes_qs( project_id, skeleton_id )
... |
deed638affd6a639f1ffd971f55ed666b0831d82a4239ba59441366505fe51ae | Python | 3,003 | 94 | import json
import argparse
from pathlib import Path
def get_class_labels(data):
class_labels_map = {}
index = 0
for class_label in data["labels"]:
class_labels_map[class_label] = index
index += 1
return class_labels_map
def load_ground_truth(ground_truth_path, subset):
with grou... |
a422a54ea27d0dfd8b9d0d1fd0596a54a2c3250dc96e8d6fb820eb6bd7c4098c | Python | 3,005 | 74 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ======================================================================
# SCRIPT INFORMATION:
# ======================================================================
# SCRIPT: UPDATE THE FIELDMAP JSON FILES
# PROJECT: ZOO
# WRITTEN BY LENNART WITTKUHN, 2020
# CONTACT: WI... |
8fedac02af27225b0c8a23166e190cba6b0db9dc8fb60d089ad6549b85b4a1fe | Python | 3,006 | 92 | import logging
import numpy as np
import torch
import torch.nn as nn
class SkipNetwork(nn.Module):
"""
Implements a Skip network which starts with takes
a tensor of shape N x in_dims as input and outputs N x out_dims as output
Inbetween the input and the output is a fully connected network with added... |
c4a0657db2a92bda2a7ff116cd4017f6b1c59af6408093d8874eb08a0df476ad | Python | 3,007 | 93 | # 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.
"""Some utilities for backbones, in particular for windowing"""
from typing import Tuple
import torch
import torch.nn as... |
0706eea5dd93baa47ea5ff9895c5b33f0338bc67ae9b346194ca564f4e9eeea4 | Python | 3,008 | 106 | import numpy as np
import pytest
import torch
from simgen.manifolds import (
MultivariateGaussianPrior,
PointCloudPrior,
StandardGaussianPrior,
)
def test_standard_gaussian_prior_calculates_correct_restorative_forces():
positions = np.array([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0]])
forces = StandardGau... |
7895389fdf69968338497f72721afe73d6d31773f91c4cac904d59c006bb569d | Python | 3,008 | 89 | # -*- coding: utf-8 -*-
import json
from catmaid.models import Message
from .common import CatmaidApiTestCase
class MessagesApiTests(CatmaidApiTestCase):
def test_read_message_error(self):
self.fake_authentication()
message_id = 5050
response = self.client.post(f'/messages/{message_id}... |
53066c8bd5a1a8aa10a0568836cd794a1d053018b7bc3feae9bb31ab10d0380e | Python | 3,009 | 94 | # generate rate map data
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.colorbar as mcolorbar
from matplotlib import cm
import grid_cell.ploter as plter
import os
from grid_cell.grid_cell_processor import Grid_Cell_Processor
from global_setting import *
#######... |
198e08f2b470fdfb63fc53cc21e87ae9cd13a7b5608fd12d624ed17fe868777a | Python | 3,011 | 68 |
# aggregate the results of eegnet
import os, sys
import pandas as pd
import numpy as np
from natsort import natsorted
# go to base directory and import globals
base_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
#ptmp_dir = "/ptmp/kroma/m4d/"
os.chdir(base_dir)
sys.path.append(base_dir)
from src.... |
cb9bf179cdb98824c77b93491d4c3aded899f5d1c4adc672e5b5d90668256766 | Python | 3,011 | 80 | import os.path as op
from pathlib import Path
import numpy as np
from eigenstrapping.fit import SampledSurrogateMaps
from eigenstrapping_analysis.utils import (
get_rootdir, MSEED, join, save_npy, load_npy
)
from eigenstrapping.stats import compare_maps
ROOTDIR = get_rootdir()
DATADIR = Path(ROOTDIR, 'datasets',... |
d51e0a10069663762a3cfc5d05a20e772c5fc435ec29455e07604d94d9bd746c | Python | 3,011 | 81 | import base64
import uuid
from medperf.account_management import get_medperf_user_data
from medperf.exceptions import CleanExit, MedperfException
from medperf.utils import get_pki_assets_path, approval_prompt
import os
from medperf import config
from medperf.ui.interface import UI
from medperf.entities.certificate impo... |
ef78b332114ea1b1b6082319f43811bb8dd1cf76419d366176c890561ed5df8b | Python | 3,011 | 90 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import qtools as qt
from qtools.attribution_scores import calculate_mutagensis_scores, mutagenesis
# =============================================================================
# set up input an... |
29cea1babdc5450102f57e808c1b98eecf1e7e6e0a5a511517efce06bf34d69d | Python | 3,012 | 75 | import importlib
import torch
import numpy as np
import random
def import_module(module_name: str, class_name: str):
"""
Import a module (class_name) from a module_name (path).
:param module_name:
Name of the module from where a class should be imported.
:param class_name:
Name of the... |
1b28ad9e400b457b70a55960af6cbd8ca1c1b298ef975a8f46edee145dca18bb | Python | 3,013 | 102 | _base_ = [
'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py',
'../_base_/datasets/coco-stuff164k_384x384.py'
]
custom_imports = dict(imports=['cat_seg'])
norm_cfg = dict(type='SyncBN', requires_grad=True)
crop_size = (384, 384)
data_preprocessor = dict(
type='SegDataPreProcessor',
... |
ccab47b3b4b555d5103992974b0993b7420da4faac84358cf4fbde6017b509ab | Python | 3,013 | 90 | # dataset settings
dataset_type = 'REFUGEDataset'
data_root = 'data/REFUGE'
train_img_scale = (2056, 2124)
val_img_scale = (1634, 1634)
test_img_scale = (1634, 1634)
crop_size = (512, 512)
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadAnnotations', reduce_zero_label=False),
dict(
... |
61ba0245df67da60e45e8b4e76aa3949216b40b1d9da80d1d05aac86da743f82 | Python | 3,014 | 82 | #!/usr/bin/env python
import argparse
import torch
from torch.utils.data import DataLoader
from rdkit import Chem
from rdkit import rdBase
from tqdm import tqdm
from MCMG_utils.data_structs import MolData, Vocabulary
from models.model_rnn import RNN
from MCMG_utils.utils import decrease_learning_rate
rdBase.DisableL... |
cee3425313bd42ff9da93053798a1219258f57c6ba0bbcb10a9dcdea2b29e470 | Python | 3,016 | 103 | import pathlib
from dataclasses import dataclass
from typing import List
import ase
import ase.io as aio
import numpy as np
import pandas as pd
import torch
import typer
from torch.utils.data import DataLoader
from tqdm import tqdm
from hydromace.interface import HydroMaceCalculator
from hydromace.tools import get_mo... |
d0f56313791e1680b223171743870b209007366a35ca18eaa637fb844e4ed270 | Python | 3,016 | 94 | # Based on https://github.com/lucidrains/siren-pytorch
import torch
from torch import nn
from math import sqrt
class Sine(nn.Module):
"""Sine activation with scaling.
Args:
w0 (float): Omega_0 parameter from SIREN paper.
"""
def __init__(self, w0=1.):
super().__init__()
self.w... |
84f4d22a2e6af064f738b26771d9653eb17fc2779906900dab408686c367c7a9 | Python | 3,018 | 110 | import pytest
from kgx.graph.nx_graph import NxGraph
from kgx.utils.graph_utils import get_parents, get_ancestors, curie_lookup
def get_graphs():
"""
Returns instances of defined graphs.
"""
g1 = NxGraph()
g1.add_edge("B", "A", **{"predicate": "biolink:sub_class_of"})
g1.add_edge("C", "B", **... |
eb620fd38fc30e39ad0965385df4ca57dea7a7ef1140b96515f9155e744dca75 | Python | 3,018 | 71 | # 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.persistent_homology import betti1_equal_2, betti_torus_check
from grid_cell.util import pca_accumulated_variance_explained_ratio
from sklearn.decomposition import PCA
import matplotlib.p... |
a4b04b5966ab223fc619208447bee20a433b2353a1921928c30674173026fe85 | Python | 3,019 | 40 | # Module for different configurations classes
class ModelConfiguration:
def __init__(self, input_size=35, num_layers=3, bidirectional=False, hidden_size=35, kernel_sizes=[3], no_hidden=False, gru=False, frames_per_second=None):
"""
Initializes the configuration for a neural network model, particula... |
3a87f6b5f0577add8164fbc73921c07a78c8bd7f3e12f5d818cdd31a9de2ed5a | Python | 3,020 | 60 | import sys
tumor_id=T2 # specify ID
age=77*365 # specify age (in days)
import math
import numpy as np
from pyabc.external.r import R
r = R(tumor_id+"Run_model_heme_WGS_data_2_linear_clones.R")
model = r.model("myModel")
distance = r.distance("myDistance")
sum_stat = r.summary_statistics("mySummaryStatistics")
o... |
17911302ad2d84ddc6855223f853ee73ee8dfb63acf516505ae917dffa7d8216 | Python | 3,023 | 96 | """InternalExecutor implementation for zndraw-joblib.
Runs built-in extensions (modifiers, selections, analysis) in a thread
because the ZnDraw client uses synchronous HTTP and Socket.IO.
Status transitions use the same JobManager HTTP API as external workers.
"""
from __future__ import annotations
import asyncio
i... |
816c06d7021a4c84987c4cc04d74897ce9b0b11a4b02c78cfe3e8e281f89b232 | Python | 3,025 | 76 | import torch
import math
import matplotlib.pyplot as plt
import seaborn as sns
import scienceplots
import matplotlib.gridspec as gridspec
import numpy as np
hermes = torch.load('../results/custom_metrics_full_log_likelihoods_unsloth-Hermes-3-Llama-3.1-70B-bnb-4bit.pth')
nemotron = torch.load('../results/custom_metrics... |
cf6176cec3f08b4b637ed29a32b5ff46a6cef3ce7c06477fd36e91a15d4b29d3 | Python | 3,025 | 76 | # Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import os
import logging
import pickle
from typing import List, Tuple
import faiss
import numpy as np
from tqdm import tqd... |
fe6ed946cc2bf81d3aa022ea10d4115f4dd100e89044bd32efe6ecffa4a57268 | Python | 3,028 | 105 | import logging
import sys
from pathlib import Path
from typing import Optional, Union
import colorlog
class CustomFormatter(colorlog.ColoredFormatter):
"""Custom formatter with colors for different log levels"""
def __init__(self):
super().__init__(
"%(log_color)s%(levelname)-8s%(reset)s %(... |
99b5aa9e6a192e8c92b6a5bfc242e35c2c405d386891ef893f4a5d48014b2cb6 | Python | 3,029 | 92 | import ast
import numpy as np
import pandas as pd
from .metrics import Metrics
def load_submission_data(submission_path):
"""
Extract necessary data for model evaluation from the submitted csv file.
Args:
submission_path (str): Complete path to the submission file.
Returns:
tuple: ... |
1ddf9ee99def854be16b267a7d04e45c32940dc097ca3508b103d841d556b75b | Python | 3,031 | 85 | # -*- coding: utf-8 -*-
import django.core.validators
from django.db import migrations, models
import django.db.models.deletion
forward = """
CREATE OR REPLACE FUNCTION refresh_skeleton_summary_table_for_project(target_project_id int) RETURNS void
LANGUAGE plpgsql AS
$$
BEGIN
-- Remove all ent... |
6933aae8d2cf08dfd9ee672ccdd4ca8f305e74c0dae2e69ef86bb119ee2a4981 | Python | 3,031 | 85 | from model import common
import torch.nn as nn
url = {
'r16f64x2': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x2-1bc95232.pt',
'r16f64x3': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x3-abf2a44e.pt',
'r16f64x4': 'https://cv.snu.ac.kr/research/EDSR/models/edsr_baseline_x4-6b446fa... |
76720d1b2a1e9bd9f23f464b19526503de51ebcf90e6351af1019fbd96b52d8b | Python | 3,033 | 78 | from pathlib import Path
from typing import List, Tuple
import SimpleITK as sitk
import numpy as np
def check_subject_validity(
subject_dir: Path, labels_dir: Path
) -> Tuple[List[Path], List[Path], List[Path], List[Path]]:
"""Checks if all files exist. Also checks size, spacing and label set of images and m... |
2a9960c9f587aa1966adc6053e058c41759f650daa0a499b07a87adbad13a835 | Python | 3,034 | 75 | from PIL import Image
import numpy as np
def crop_and_resize(source_img, target_img):
"""
Make source_img exactly the same as target_img by expanding/shrinking and
cropping appropriately.
If source_img's dimensions are strictly greater than or equal to the
corresponding target img dimensi... |
392344a9d87b6cda04a2ec04d29a8bfc426d5534201fabe8041722413bbd2629 | Python | 3,034 | 84 | # 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... |
a004426fb72c40407ce56aa7d874cea8729569c8d325eb4705ecf4273248479e | Python | 3,036 | 73 | # -*- coding: utf-8 -*-
import django.core.validators
from django.db import migrations, models
import django.utils.timezone
class Migration(migrations.Migration):
"""This data migration adds missing skeleton summary table entries. They
should have been created as part of the original summary table migration,... |
a17de990280563b5ebf7ca5e66650cf741e10c38a035b8294b3b1ea822f12cd9 | Python | 3,037 | 100 | import json
import os
from medperf.entities.interface import Entity
from medperf.entities.schemas import CASchema
import medperf.config as config
from medperf.account_management import get_medperf_user_data
from medperf.entities.utils import handle_validation_error
class CA(Entity):
"""
Class representing a c... |
0a9860f7e59792f92eab3ef5b57891ebe89c3cade6b76d1142cd51125f556f6b | Python | 3,038 | 103 | _base_ = [
'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py',
'../_base_/datasets/ade20k_384x384.py'
]
custom_imports = dict(imports=['cat_seg'])
norm_cfg = dict(type='SyncBN', requires_grad=True)
crop_size = (384, 384)
data_preprocessor = dict(
type='SegDataPreProcessor',
size=cro... |
32ba04f126da7ee5968473c0c9938a4467a4f2bd08eaac4fff157f2ff503d8ff | Python | 3,038 | 100 | # -*- coding: utf-8 -*-
# Generated by Django 1.11.11 on 2018-04-03 20:07
import catmaid.fields
import django.contrib.postgres.fields
from django.db import migrations, models
import django.db.models.deletion
forward = """
SELECT disable_history_tracking_for_table('stack'::regclass,
get_history_table_n... |
2630f0082aabbaf6fe647823479889c5ca1e28e79aef99ba9ab0752f332ffd4b | Python | 3,039 | 92 | # Copyright (c) OpenMMLab. All rights reserved.
from mmengine.structures import BaseDataElement, PixelData
class SegDataSample(BaseDataElement):
"""A data structure interface of MMSegmentation. They are used as
interfaces between different components.
The attributes in ``SegDataSample`` are divided into ... |
4755fffc2e5d4f6926fb32789347217943099253b972d08e7e6c3cfa5c13a58b | Python | 3,039 | 84 | from medperf import config
from medperf.account_management.account_management import get_medperf_user_data
from medperf.entities.ca import CA
from medperf.entities.training_exp import TrainingExp
from medperf.entities.cube import Cube
from medperf.utils import get_pki_assets_path
from medperf.certificates import verify... |
28748a26d8829b8261a4124a253731e43a6efa1bcbf7ed9881bf3d7b638f7c13 | Python | 3,040 | 56 | #!/usr/bin/python
"""
This file to create Site Frequency Spectrum (SFS) from Priors or parameters
"""
import argparse
import sys
# from Simulation.msprime import Demography
# noinspection PyUnresolvedReferences
import Class
# noinspection PyUnresolvedReferences
import Demography
from _version import __version__
pars... |
cabd0b8283d02566fed743e67a0fa75bead45e3f78a44660ff5bb67e0d591081 | Python | 3,041 | 85 | # Copyright (c) 2021, EleutherAI
# This file is based on code by the authors denoted below and has been modified from its original version.
#
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in complian... |
805c99c87e7d2349bd84ebd907c5a5236864c83870eef0aaeb4b4ec4759e1c1e | Python | 3,042 | 80 |
# %% auto 0
__all__ = ['TransformerModelMod', 'TransformerPlus']
# %% ../../nbs/108_models.TransformerModel.ipynb 3
from tsai.imports import *
from tsai.models.layers import *
from tsai.models.utils import *
from torch.nn.modules.transformer import TransformerEncoder, TransformerEncoderLayer
class TransformerModelM... |
996020dc12fc9db27ab61965f714de75d029cafdbbab665bb1068307e35822aa | Python | 3,042 | 92 | from neurolib.utils.loadData import Dataset
from neurolib.models.aln import ALNModel
import matplotlib.pyplot as plt
import neurolib.utils.functions as func
import neurolib.utils.stimulus as stim
import numpy as np
import scipy.io as sio
from scipy import signal
# adding varx to the system path
import sys
sys.path.ins... |
89afe4c06c96743d1ef1f5ee9c5d8c3f86a9b89def735238f637cabb568f212f | Python | 3,043 | 92 | # This file is part of h5py, a Python interface to the HDF5 library.
#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
import os
import threading
import time
import pytest... |
27edbb86ef1a51478fb63c43033b9d5b3581091e72f4ee1d1d5946358f634985 | Python | 3,044 | 106 | from ..client import inject_client
@inject_client
def fetch_custom(cypher, dataset="", format='pandas', *, client=None):
'''
Make a custom cypher query.
Alternative form of :py:meth:`.Client.fetch_custom()`, as a free function.
That is, ``fetch_custom(..., client=c)`` is equivalent to ``c.fetch_custo... |
46179aef609fbbcb1d7e729038cb78aeb14d037d1ea715b85e5500c5d809af30 | Python | 3,044 | 85 | import numpy as np
import pandas as pd
from sklearn.cluster import AgglomerativeClustering
from scipy.cluster.hierarchy import dendrogram
from matplotlib import pyplot as plt
from experiment import *
def plot_dendrogram(model, **kwargs):
# Create linkage matrix and then plot the dendrogram
# create the coun... |
4ec5bcd99d69610dd0b0908db7388d3bc86008cc1c99e80d4e4ca18c6a8b00e8 | Python | 3,044 | 103 | _base_ = [
'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py',
'../_base_/datasets/pascal_context_59_384x384.py'
]
custom_imports = dict(imports=['cat_seg'])
norm_cfg = dict(type='SyncBN', requires_grad=True)
crop_size = (384, 384)
data_preprocessor = dict(
type='SegDataPreProcessor',
... |
3c709ca27d1ca261faaa63352446bc985a688a8a6c9c357bc1df712444a8e9c3 | Python | 3,045 | 77 | import sys
sys.path.append(r"C:\Users\dm3169\PycharmProjects\comparative_prey_capture")
from experiment import *
import pandas as pd
import numpy as np
from scipy.spatial.distance import cdist
from scipy.optimize import linear_sum_assignment
class ArtemiaTracker:
def __init__(self, x_init, err_tol):
self... |
c1d6a8e0490bf3a2b72540563426ec9b68c4a47aad864ebfb95d0de2e330a4ec | Python | 3,046 | 88 | import numpy as np
from myphdlib.general.labjack import filterPulsesFromPhotologicDevice
class StimuliProcessingMixin():
"""
"""
def _processMovingBarsProtocol(
self,
invertOrientations=True
):
"""
"""
self.log('Processing data from the moving bars stimulus... |
020fbd26ebbeb277c607e87491acb63e1f559ef195e60ce7e609301170c12b38 | Python | 3,049 | 73 | import pytest
from src.memory import (
_bytes_to_gib,
_parse_cgroup_memory_value,
_parse_kv_kb_bytes,
_parse_proc_cgroup,
log_memory_snapshot,
process_peak_rss_bytes,
)
@pytest.mark.unit
def test_bytes_to_gib_formats_and_handles_none():
assert _bytes_to_gib(None) == "unknown"
assert _... |
be9b177310a884f3da98403ab2d4e6e0de8d9f0116f053977ef375214506829b | Python | 3,051 | 81 | import httpx
import pytest
import socketio
import socketio.exceptions
from zndraw_socketio import wrap
from zndraw.socket_events import UserGet, UserGetResponse
@pytest.mark.asyncio
async def test_socketio_connect_without_token(server: str) -> None:
"""Test that Socket.IO connection is rejected without a token."... |
f008b3a0143c16d1bd97236706809e733ad1adec12d6ca73b8eef445d705ec91 | Python | 3,052 | 113 | """
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 torch
from ..initializers import he_orthogonal_init
class Dense(torch.nn.Module):
"""
Combines... |
10e4d477895ee7e46cb3bbabb5c426b85097240c31e8d5dddf57277796729df5 | Python | 3,053 | 96 | from pathlib import Path
from modules.run_svr_lsm_iteration import run_svr_lsm_iteration
if __name__ == "__main__":
base_folder = Path.cwd() # CURRENT DIRECTORY
base_folder = base_folder / "symptoms"
'''
symptom_folder = base_folder / 'Dysmetropsia'
csv_name = "Dysmetropsia.csv"
... |
fb0bc65b73d0bb84bfe1b13f57c667bcd685a7b7a2c89ebf52a91170dac9bdbe | Python | 3,053 | 83 | import pytest
from dnaio import SequenceRecord
from cutadapt.qualtrim import nextseq_trim_index, expected_errors, poly_a_trim_index
def test_nextseq_trim():
s = SequenceRecord("n", "", "")
assert nextseq_trim_index(s, cutoff=22) == 0
s = SequenceRecord(
"n",
"TCTCGTATGCCGTCTTATGCTTGAAAAAA... |
6aa42a336430612f7ea2db05caeef774e245bc30fd9bcb14a5e0b591dd4c6ff3 | Python | 3,054 | 109 | """XGBoost Experimental Federated Learning related API."""
import ctypes
from threading import Thread
from typing import Any, Dict, Optional
from .core import _LIB, _check_call, _deprecate_positional_args, make_jcargs
from .tracker import RabitTracker
class FederatedTracker(RabitTracker):
"""Tracker for federat... |
5c76536c35759e1f212a9329b9136dcf8a37023e020f489f6acabef8766dbb00 | Python | 3,056 | 80 | from contextlib import contextmanager
import pytest
# These tests require a live connection to ubergraph.apps.renci.org.
# They are only run when pytest is invoked with --network or --all
# (see tests/conftest.py for CLI options).
#
# The shared `ubergraph` fixture (tests/conftest.py) handles three cases:
# - Netwo... |
d618d6e87cf6138241b035c57b59ffc275d621f2d0cbdec64441243141fe10db | Python | 3,056 | 89 | import os
import pandas as pd
from rano_monitor.messages import InvalidSubjectsUpdated
from rano_monitor.messages.report_updated import ReportUpdated
from textual.widgets import Label, ListItem, ListView
from rano_monitor.utils import (
get_hash,
tumor_has_been_finalized,
get_finalized_tumor_path,
get_b... |
cba7c886f43a9a75b202dae97002594b04eb2d41e5b7795cd3601b35923ae5ed | Python | 3,059 | 91 | # -*- coding: utf-8 -*-
from django.db import connection
from django.shortcuts import get_object_or_404
from django.test import TestCase, TransactionTestCase
from django.test.client import Client
from django.contrib.auth import get_user_model
from django.contrib.auth.models import Group
from guardian.shortcuts import ... |
3d4243b34a90c72bc13827bfad59e3615e28d45384b9f0f001ce25173e1b51b9 | Python | 3,060 | 65 | """Shared, import-safe test-data locations and helpers.
This module holds constants and helpers that test modules need at *collection* time
(e.g. inside ``@pytest.mark.parametrize`` decorators and module-level case lists), so it must
stay a plain importable module with no pytest or heavy imports. It lives under a uniq... |
2cfc57bb2ad8cf2febcd0686cec28ae1c0537c5bf1fab524d85307901864e877 | Python | 3,061 | 51 | #!/usr/bin/env python
# coding: utf-8
import os, sys, argparse
import numpy as np
from utils_dp import MASS_LIST, STIFF_LIST, CUR_SCENE_DICT, BLENDER_CAM, mkdir, get_depth_map
parser = argparse.ArgumentParser(description='')
parser.add_argument('--cur_scene_idx', type=int, default=1, help='wind=1|drape=2|ball=3|rotat... |
4714085fc7fc6067545f29ddf4b941ea80e8c59f41df66ac214d4e0fbed4ff88 | Python | 3,063 | 97 | from pyalfe.tasks.dicom_processing import DicomProcessing
from pyalfe.tasks.initialization import Initialization
from pyalfe.tasks.quantification import Quantification
from pyalfe.tasks.registration import (
CrossModalityRegistration,
Resampling,
T1Registration,
)
from pyalfe.tasks.segmentation import (
... |
b68de822028d56978bd09f5d072c730f82d7436b8082a24f1419b2b4f75e48e3 | Python | 3,065 | 91 | from django.http import Http404
from rest_framework.generics import GenericAPIView
from rest_framework.response import Response
from rest_framework import status
from drf_spectacular.utils import extend_schema
from .models import Dataset
from .permissions import IsAdmin, IsDatasetOwner
from .serializers import (
D... |
b8c75efc0be20d19f5166b7ecad29cd53d8f9d5f21609c6935e2047b8568a8ea | Python | 3,069 | 92 | # 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 --------------------------------------------------------------
# If ex... |
cbbdadcfe9276ef7c68e8d1879468b250de50903c2961e70129339c47ebedd1d | Python | 3,069 | 98 | import torch
import torch.nn as nn
def normalized_cross_correlation(x, y, return_map, reduction='mean', eps=1e-8):
""" N-dimensional normalized cross correlation (NCC)
Args:
x (~torch.Tensor): Input tensor.
y (~torch.Tensor): Input tensor.
return_map (bool): If True, also return the co... |
d433efcd9f232558ee37dcbd74124eac055eb90316650ff123b7520d3a8f2630 | Python | 3,071 | 90 | from pydantic import BaseModel
class ContainerInput(BaseModel):
name: str = ""
config: str
parameters: str = ""
additional_local: str = ""
additional_remote: str = ""
HOST = "127.0.0.1"
WEBUI_PORT = 8100
SERVER_PORT = 8000
LOCAL_PROFILE = "Local"
BASE_URL = f"http://{HOST}:{WEBUI_PORT}" + "{}"... |
4ec43c7346d59538179e9e64e44d4daf40738430a74db606fac40b4ec6cafc15 | Python | 3,073 | 58 | #!/usr/bin/env python
import sys, os
use_message = '''
'''
# GRCh38 release 84
def build_indexes():
# Build indexes
if not os.path.exists("indexes"):
os.mkdir("indexes")
os.chdir("indexes")
aligners = ["HISAT2", "HISAT", "Bowtie", "STAR", "GSNAP", "BWA", "minimap2"]
genomes = ["22_20-2... |
58b7fae969779c374e1e496b5b5b7be5ebc1cbc3de7a51b22a7ef58556d081a3 | Python | 3,073 | 96 | # grab all .csv files
# concatenate into one big dataframe
# TODO: add sub, ses, run, task info to pandas
# resources:
# * https://community.plotly.com/t/multiple-traces-plotly-express/23360/4
# %%
from operator import index
import os, glob
from turtle import color
import pandas as pd
import matplotlib.pyplot as plt
... |
bfeda1c788d41d4feee4be5fed8e1258c52b2158a5aa44a6a71e15e8150b13e4 | Python | 3,074 | 90 | #!/usr/bin/env python
"""
MetaWIBELE: download_config_file module
Download template configuration files and vignette files for prioritization used by MetaWIBELE
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 associa... |
b2c4c5622b18344d8b2cae9636d22c738e6153b2e164d68d83d554a8e1862f28 | Python | 3,075 | 97 | ##################################################################
# Plotting the PCA t-SNE and UMAP based on TrimNN representations
# Reproducibility for Figure.3B
##################################################################
import pandas as pd
import numpy as np
from sklearn.decomposition import PCA
from sklea... |
719129b7d983f316cb933df045e243874503f05cc0ffe8a97ecfc15a2d4d61b5 | Python | 3,076 | 123 | """Tests for automatic connectivity calculation."""
import ase
import numpy as np
from zndraw.connectivity import add_connectivity
def test_auto_connectivity_small_molecule():
"""Small molecule gets connectivity computed."""
# Water molecule — O-H bonds should be detected
atoms = ase.Atoms(
"OHH... |
80b5762bbfe1c17592440ff6da56dc714f14f672754686a45173c2cdff69cd36 | Python | 3,076 | 67 | import pandas as pd
import math
from functools import reduce
df_exp = pd.read_csv('../experiments.csv', sep=';')
df_llama_70b = pd.read_csv('../results/all_data_unsloth-Meta-Llama-3.1-70B-bnb-4bit.csv')
df_llama_70b = df_llama_70b[df_llama_70b['unseen'] == 'participants'][['task', 'unsloth/Meta-Llama-3.1-70B-bnb-4bit... |
f47d0ce857e393104ffc2602fc17017a8bf3a3b9be0a05726592530eb6431c4c | Python | 3,076 | 80 | #!/usr/bin/env python3
import os
import glob
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import argparse
def main():
parser = argparse.ArgumentParser(description="Generate violin plots of absolute sums per model directory.")
parser.add_argument("--dataset", choices=["MNIST", "CIFAR10... |
895744531e68024641835220329102d64060119a9d61b685976ed841fae0c18f | Python | 3,078 | 91 | # Copyright DST Group. Licensed under the MIT license.
from CybORG.Shared.Enums import PasswordHashType
from CybORG.Simulator.Entity import Entity
from CybORG.Simulator.LocalGroup import LocalGroup
class User(Entity):
"""User entity
Attributes
----------
username : str
password : str
pas... |
06ad94160ef915fe4b4ae6de8f1222b743771ac685482004075bc57967848378 | Python | 3,079 | 105 | from medperf.exceptions import CleanExit
import pytest
from unittest.mock import ANY
from medperf.entities.model import Model
from medperf.entities.benchmark import Benchmark
from medperf.commands.model.associate import AssociateModel
PATCH_ASSOC = "medperf.commands.model.associate.{}"
@pytest.fixture
def model(moc... |
dfe08f737e95404eca86d4a97c2fbef57049b4b360742b0ef0bd736e57a59ed7 | Python | 3,079 | 95 | """Logic file"""
from pathlib import Path
import torch
import numpy as np
import SimpleITK as sitk
from src.utils.utilities import helper
def pseudo_predict(subject_dir: Path, output_dir: Path):
"""
In this dummy example, the four MR sequences are loaded from `subject_dir` and then class 0 is "predicted" fr... |
27ad957e90d556f4d03c228ea7e45cf1cf755b54f141615b6add1c6e80346c27 | Python | 3,081 | 72 | # pytest unit tests for spinalcordtoolbox.deepseg_.gm
import os
import nibabel as nib
import numpy as np
import spinalcordtoolbox.deepseg_.gm as deepseg_gm
class TestCore(object):
def test_data_resource(self):
"""Test the DataResource manager, and check if files exists."""
resource_models = dee... |
3b6b00df5dbbee09aa0f2360159a8010b6be4e7cdcefe03f28ccad2df83e64ca | Python | 3,081 | 94 | """
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 logging
import torch
class ForceScaler:
"""
Scales up the energy and then scales down the forces
to prevent NaNs and inf... |
a8d0e78c9c9bf88eebef32d822521dbf48f96f02b00776052f9f3dcc110c5e4a | Python | 3,081 | 82 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os.path as osp
from collections import OrderedDict
import mmengine
import torch
from mmengine.runner import CheckpointLoader
def convert_mit(ckpt):
new_ckpt = OrderedDict()
# Process the concat between q linear weights and kv linear weigh... |
5569d18f50faae9e79cb3d174e479fac2498a642ab15e7caf468e66e5655e76c | Python | 3,082 | 105 | import os
# Encode a fragment.
from rdkit import Chem
from mol_utils import join_fragments
from mol_utils import split_molecule
import pandas as pd
def encode_molecule(m):
fs_list = []
count = 0
error_index = []
for index,i in enumerate(m):
try:
fs = [Chem.MolToSmiles(f) for f in s... |
28017449737463ab37892581a0e51694cd4c26cf1c3863a074ca1699f02f1ca7 | Python | 3,083 | 97 | import os
import torch
import pandas as pd
from PIL import Image
import numpy as np
import torchvision
import torchvision.transforms as transforms
from models import model_attributes
from torch.utils.data import Dataset, Subset
from data.dro_dataset import DRODataset
from data.utils import *
from data.torchvision_datas... |
2ec742c25c0efc186985e6fadfcb6b2841c7a4e9ae6d6fd4b3e6ae0ae94d06e8 | Python | 3,084 | 92 | #!/usr/bin/env python
"""
Time ``cache()`` for every weight/property type.
Separates the properties derived from the topology alone from the ones that call
out to RDKit/OpenBabel/ChargeFW2. Only the cheap ones belong in a GPU benchmark;
the rest measure third-party libraries rather than Nearl.
Usage:
python profi... |
2f8b2d5ebd93241970923014e2e96ff86a88b9d8f83ae03df853518ce7eb0d25 | Python | 3,085 | 103 | # model settings
backbone_norm_cfg = dict(type='LN', eps=1e-6, requires_grad=True)
norm_cfg = dict(type='SyncBN', requires_grad=True)
data_preprocessor = dict(
type='SegDataPreProcessor',
mean=[123.675, 116.28, 103.53],
std=[58.395, 57.12, 57.375],
bgr_to_rgb=True,
pad_val=0,
seg_pad_val=255)
mo... |
4a6827caffcf684f6155439c740589ea35562137ca690dd31ae80f9ce9a47ddb | Python | 3,085 | 91 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmengine.utils import is_tuple_of
from mmseg.registry import MODELS
from ..utils import resize
from .decode_head import BaseDecodeHead
@MODELS.register_module()
class LRASPPHead(BaseDecodeHead):
... |
b0ec2090829370553110c0263315886a00dfad0406f9f9d6ebac3c6ea896dbf5 | Python | 3,085 | 76 | ######################################
# wrapper for rule: deduplicate_single_genomics
######################################
import os
import sys
import math
import subprocess
import glob
from snakemake.shell import shell
UMITOOLS = "umi_tools"
SAMTOOLS = "samtools"
BAMCOVERAGE = "bamCoverage"
shell.executable("/bin... |
3f21afb420d331ea9b59f60a92029eb1c68dd9ed6ac0310ed9e44f235a358485 | Python | 3,086 | 86 | import numpy as np
def get_angle(inp, cross, k, direction):
# inp is the input plane, represented by 3 xzy sets
# cross and k is the normal vector of the plane
# Direction defines whether we want the mediolateral or dorsaventral angle
section = inp.copy()
# transform vector into absolute coordinat... |
6115080ad343737655d31a71cc814c4615f7adb23253196960b1ed7687b26c4e | Python | 3,086 | 82 | import numpy as np
def get_angle(inp, cross, k, direction):
# inp is the input plane, represented by 3 xzy sets
# cross and k is the normal vector of the plane
# Direction defines whether we want the mediolateral or dorsaventral angle
section = inp.copy()
# transform vector into absolute coordinates... |
b474e67265f23e542f07f8263ccea308cbd9eb0488cbcb1d47a1777236b3a048 | Python | 3,087 | 93 | import copy
import torch
from torch.utils.data import Dataset
from Bio.PDB.PDBParser import PDBParser
from Bio.PDB.MMCIFParser import MMCIFParser
from Bio.PDB.Polypeptide import index_to_one, one_to_index
from rde.utils.transforms import Compose, SelectAtom
from rde.utils.protein.parsers import parse_biopython_structu... |
e3e41e80da4b1fda763d43d2cfc42b94017fd2fd89e6a4d9cbd605f092ae655e | Python | 3,088 | 103 | import os
import platform
import socket
import psutil
import shutil
import subprocess
from datetime import datetime
import uuid
def is_container():
try:
with open("/proc/1/cgroup", "rt") as f:
content = f.read()
if any(x in content for x in ["docker", "kubepods", "containerd", "podm... |
68aff1bb228ea6feefb15c81ff777815075830d92d32761d7daa57ee7dde991d | Python | 3,089 | 71 | import os
import sys
# Dynamically append project root to sys.path
ROOT_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
if ROOT_DIR not in sys.path:
sys.path.insert(0, ROOT_DIR)
from DeepChemModels.CustomizedDateLoader import *
from DeepChemModels.ModelFeatureGenerator import generate_model_f... |
96c71bbc8339071f493e9eb76cf4ab51d51e150acc22691ebaf1c283dcd62975 | Python | 3,090 | 91 | '''Calculate QC metrics that fastqc doesn't explicitly provide.'''
import sys
import os
import re
import argparse
import zipfile
def unzip_fastqc_dir(zipped_file):
'''Unzip fastqc raw directory and return data file.'''
zip_base = os.path.basename(zipped_file)
unzip_dir = os.path.splitext(zip_base)[0]
w... |
55a7f2ca31fae709eee2713209f695708ebce5d8ff320c4e8a49cfcee4ab3003 | Python | 3,092 | 97 | import json
import os
import os.path as op
from heudiconv.utils import (
get_known_heuristics_with_descriptions,
get_heuristic_description,
load_heuristic,
json_dumps_pretty,
load_json,
create_tree,
save_json,
get_datetime,
JSONDecodeError)
import pytest
from .utils import HEURISTI... |
60a7857a57b04cd81e1d3363ab48f4e48642d0f5bd121273d7da393544ecbdf2 | Python | 3,096 | 104 | """Shape geometry for ZnDraw - 2D polygons rendered in 3D space."""
from pydantic import Field
from .base import (
BaseGeometry,
ColorProp,
InteractionSettings,
PositionProp,
RotationProp,
ScaleProp,
)
class Shape(BaseGeometry):
"""A 2D polygon shape rendered in 3D space.
Vertices d... |
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