sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
e6cc58705de96d5c9b6505f6fe1d88ebbd4e7881da62ac6921972cef774504db | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ebc1eaa359a016917db16da44de5c76e33ca8b7ba354ad0379fb4f026b2447e7 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ed0b0370c6bfbcb7101cf771ff9b0e2b7c01997defff4018b1dcc6ac0119c85a | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ee05fd4da123ef8e234f52b0ffc8190f325e3c92c6645f8325ad458af52bd7a9 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ef8830366d4e5b0cf1abb843e81b349ae174041ce84c7d6dcad06aa523950787 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f19e154a5f5dc10c96d4944d073e62dcee0e49357212a7421d22637767bd6e99 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f2b168d92bd1d27e193d6d982d8640d570aaf92e38e00467efa1af77561cd947 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f3e40739c55b809049c3e9c0c6568a73765012497988b51eb885dfcb7bb131b1 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f4331b328a589b983a5739bc2cfb7d36cc5312baf04e1312179fa50e537f2bde | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f88707e42c75eda2558ed877525dc8b70d94beb09da26697f57bd36ad4e873f1 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
f8e42c96b719d3c1657276fbf9a17ab4d3a3fc789dd694b02457c9b5a626a49f | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
fe3daee99ce921e8f68cce628ec169e0a1cb929860c0a4fe563337f48d1eb79f | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ff6c02a7c6570b95d862554624973296b7ac2b40ab4b13e0d578e42d90de5f34 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ff7a82b5c893c60f4a4bb5fe12e1390574afd871532ee4747e11ad601ba05043 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
ffb4d113e2de0d196795b5c1da674fa9d82f39dd703a201b0c701755e930f658 | Python | 41,094 | 1,097 | # mapping = {
# "default": {
# "core_allocation": 1,
# "spatial_mapping": {"D1": ("K", 16), "D2": ("OY", 14), },
# # "temporal_ordering": (('OX', 56), ('OY', 56), ('FX', 1), ('FY', 1), ('K', 4), ('C', 4), ('T', 1), ('B', 1)),
# "memory_operand_links": {"O": "O", "W": "I2", "I": "I1"}... |
d7ac42b4f3802797b25c7aa397d7b3d03438ecf4c3c97d8d065cb55ff69635c5 | Python | 41,195 | 1,228 | """octagonal maze linearization"""
import copy
import numpy as np
# from scipy import interpolate
# from collections import namedtuple
from ..core import _analogsignalarray, _epocharray
from ..auxiliary import _position
from .. import utils
from ..plotting.core import colorline
# TODO: linsmooth(), wrap(), unwrap(),... |
67cc6c7b257909ab78d868a2a58b4d500422ae264c5a51a8a0d581514171ce5c | Python | 41,212 | 1,157 | #!/usr/bin/python
#
## @file
#
# A ctypes based interface to Andor cameras.
# (Andor Software Version 2.82).
#
# Cameras are 1 indexed?
#
# This can control more than one camera.
#
# Hazen 09/15
#
import ctypes
import numpy
import time
import storm_control.sc_library.halExceptions as halExceptions
... |
b689a48d5f13ef614b8d596eaa92b053785b4fd72fbbb07d2fa8420fb50057c3 | Python | 41,308 | 1,302 | """
General utility code for test-time interraction with a SeqNN model.
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import pdb
import sys
import numpy as np
import tensorflow as tf
from basenji.dna_io import hot1_augment
from basenji import accurac... |
a90538818d28060c693bfb02cbb4bf2b53ccd2cba2e8981c7815e2712aa8690e | Python | 41,511 | 1,116 | #!/usr/bin/env python3
"""
PFAS Content Prediction using Gaussian Process Regression for HGBO
This module provides a comprehensive pipeline for predicting PFAS content in soil samples
using Gaussian Process Regression with enhanced kernels, SHAP interpretability analysis,
and Partial Dependence Plot (PDP) visualizatio... |
4b3500cf9e5b613e564f063d3654fc1b58efb8f324c0dd7b3b27a3a2675b2297 | Python | 41,548 | 802 | # -*- coding: utf-8 -*-
"""
Code to reproduce analyses and plots shown on Figure 1 and Supplementary Figure 1
Please make sure to run sequentially as some cells might depend on variables defined earlier.
Created on Fri Jan 17 12:32:43 2025
@author: Lukas Oesch
"""
from chiCa import * #Run inside chiCa path to direc... |
ae867d47e078e351e6a852a9e83ccdad875577bdd0cdd4cb9be8c5870f60b4bb | Python | 41,557 | 1,170 | #!/usr/bin/python
#
## @file
#
# A ctypes based interface to Andor cameras.
# (Andor Software Version 2.82).
#
# Cameras are 1 indexed?
#
# This can control more than one camera.
#
# Hazen 09/15
#
import ctypes
import numpy
import time
import storm_control.sc_library.halExceptions as halExceptions
... |
4cfda08e26d4d532e7b79763db55b034edee30fbd2ffc0172ece856a19921269 | Python | 41,565 | 850 | # This file is part of connectome-manipulator.
#
# SPDX-License-Identifier: Apache-2.0
# Copyright (c) 2024 Blue Brain Project/EPFL
"""Module for building connection/synapse properties models"""
import os.path
import matplotlib.pyplot as plt
import numpy as np
import progressbar
from scipy.optimize import curve_fit
... |
faee43bd9d7628e942f56e3303f1cbcb49b102afe0f803842bdb55141a0fd96b | Python | 41,575 | 890 | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
import numpy as np
from models.rec_weight_matrix import *
import random
def seed(seed=1810):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
... |
c12ee744ae3bb5469164c46a4b9bbb8d7287110a49267b4614c9bdced5413e78 | Python | 41,621 | 1,029 | import numpy as np
from scipy import linalg
import scipy.sparse
import scipy.sparse.linalg
import lapy
import brainspace.mesh as mesh
import mne
from useful_fns import apply_solver, log_exp_var, find_each_nearest_vertex
from dynsim_fns import map_data_to_full_src, centre_loader, generate_com_labels
def get_downsample... |
92e011acd9f15ae98134a6ad23ef4d673d876d7c8af57c76ffe2545c119ec8b1 | Python | 41,670 | 1,358 | #!/usr/bin/env python3
"""Serial ECC registration refinement for MuscleX calibration refinement."""
from __future__ import annotations
import math
import time
import cv2
import matplotlib.pyplot as plt
import numpy as np
try:
from musclex.utils.fold_symmetry import _compute_fold_symmetry
except Exception:
fr... |
b0de084cc693a0bc4ecdf35dda6ab1f416243d423e27110d78fbcf3de026cdf5 | Python | 41,692 | 923 | from attorch.layers import (SpatialXFeatureLinear, elu1,
SpatialTransformerPooled2d, SpatialTransformerPyramid2d)
from attorch.module import ModuleDict
import numpy as np
import torch
from torch import nn as nn
from torch.nn import Parameter
from torch.nn import functional as F
from static... |
e368e1856fdc952eec2ea520be2bb30affa99079bca4b6f32dda9b852f84971a | Python | 41,692 | 677 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'D:\PycharmProjects\ISAT_with_segment_anything\ISAT\ui\MainWindow.ui'
#
# Created by: PyQt5 UI code generator 5.15.11
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you... |
51692b9d789046feee2a50529f89f60ca16445bb71e930c4177f2717a6581f6d | Python | 41,693 | 998 | # -*- coding: utf-8 -*-
import os
import gc
import numpy as np
import pandas as pd
from time import time
import matplotlib.pyplot as plt
from collections import defaultdict
from scipy.ndimage import gaussian_filter
from scipy import stats
import tensorflow as tf
import torch
import torch.nn as nn
imp... |
3bb86c2cddc1db995e2026096d513aec3ce5203a52c603ddc09f3fdb9a75b001 | Python | 41,715 | 834 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 6 15:42:00 2019
Analyze animal now in a seperate file
# Analyse animal is the main analysis function. It takes one obligated argument which is the name of the csv file. It has two optional
# arguments.
# Single = minicube with only one photoreceiv... |
c630912e7b078ed02afb64cc09a5345fbec2dff61f07c0060349b10443041155 | Python | 41,770 | 871 | import codecs
from contextlib import closing
import requests
import csv
import itertools
import statistics
import random
import collections
import copy
import math
import pprint as pp
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import numpy as np
import argparse
... |
e8bb094164d61d1f4e25029b24496da25aa1aea2c089d58a1d39d1f14a71afa5 | Python | 41,847 | 899 | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
import numpy as np
from models.rec_weight_matrix import *
import random
def seed(seed=1810):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
... |
3ba1714f5b3dd9028200a922203333a430061572a7eed8da68b9c905e768086a | Python | 41,903 | 813 | # Kai Sandbrink
# 2023-02-01
# This script performs the analyses for the LEVC task (Task 2)
# %% LIBRARY IMPORTS
import torch
import pandas as pd
import numpy as np
import matplotlib as mpl
from utils import Config, plot_learning_curve, plot_learning_curves_comparison, get_timestamp
from utils_project import load_co... |
cc6589ee841927b01d183834a5e4fd2b560804247f609cf1678d978fec48d76c | Python | 41,926 | 1,239 | """
Module for the Canvas QWidget the task will render into
"""
import json
import time
import enum
import types
import base64
import typing
import logging
import pathlib
import asyncio
import hashlib
import itertools
import functools
import contextlib
import collections
import bisect
import os.path
import stl.mesh
... |
d011c261ac66a85e614511efc3279419ba34f7e9a814d8ec9a57b1f538b79d89 | Python | 41,943 | 1,186 | import os
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.memory_level import MemoryLevel
from zigzag.classes.hardware.architecture.operational_unit import Multiplier
from zigzag.classes.hardware.architecture.operational_array import Multiplier... |
2b2bd15f60d7dcca6f9b9329780abc734797d8ac76079ebd0f3dd6243b89c6eb | Python | 41,956 | 1,186 | import os
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.memory_level import MemoryLevel
from zigzag.classes.hardware.architecture.operational_unit import Multiplier
from zigzag.classes.hardware.architecture.operational_array import Multiplier... |
b3ceea293ece9964006c104c78f1ca37d92877f3aae991dd97b5b66cec1efd76 | Python | 42,024 | 1,097 | # -*- coding: utf-8 -*-
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.patheffects as PathEffects
from mpl_toolkits.axes_grid1 import make_axes_locatable
import numpy as np
import pandas as pd
import seaborn as sns
from scipy.ndimage import zoom
from scipy import stats
def get_2d(arra... |
2adce749b7f7cce2bec10c9d2cab63944a68d08fde61f179652ae4d0259eadfe | Python | 42,029 | 1,188 | import os
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.memory_level import MemoryLevel
from zigzag.classes.hardware.architecture.operational_unit import Multiplier
from zigzag.classes.hardware.architecture.operational_array import Multiplier... |
5171ea0f934cd036cabef9d59798775f8066c86b43e2c76db68ae395e8872a36 | Python | 42,053 | 923 | #!/usr/bin/env python3
"""
DEGU Distillation Training Script for lentiMPRA DREAM-RNN Models
This script implements the DEGU (Distilling Ensembles for Genomic Uncertainty-aware models)
methodology as described in the DEGU paper for lentiMPRA data. It trains distilled student models using:
1. Ensemble mean predictions... |
98cd7225a344df6ef2bddde13563ab674f82014ceb207159655f99cc3274c7c9 | Python | 42,102 | 798 | ###---The very basic intro---###
# This analysis plugin takes advantage of labdatatools to download raw data to
# be analyzed from the churchland gdrive and to upload the results of the
# analysis. Here's a use example in the terminal:
#
# labdata submit caiman -a LO032 -s 20220215_114758 -d miniscope -- run_cnmfe --n_... |
a0fcccfbfc7648ac7e95478550fbaf7d878c030b379ed914b177ab342ee03fec | Python | 42,231 | 1,045 | """
An implementation of HMAX:
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision
import numpy as np
import scipy as sp
import time
import pdb
import random
from ._builder import build_model_with_cfg
from ._manipulate import checkpoint_seq
from ._registry import register_model, g... |
2ebf42d5a08e84720b370a8153610d63db1310e61034db0d27e930b093d3b0ab | Python | 42,235 | 866 | import collections
import os.path
import shutil
import subprocess
import sys
import unittest
import tests.base_test
import tests.output_parser as output_parser
import tests.test_config
import tests.util
class Test(tests.base_test.BaseTest):
def setUp(self):
super().setUp()
self._test_base_dir = ... |
168dde9b078476a856a06e1ccf9f978d7e1852e2c72ebf68995e89d25068a990 | Python | 42,276 | 1,171 | """
TMS Explorer was developed to assist with the data preprocessing of transcranial
magnetic stimulation (TMS) as part of the study "Transcranial direct current
stimulation (tDCS) and mindfulness meditation in fibromyalgia" in the "Non-
invasive brain stimulation lab" (NBS) at the university medicine Göttingen ... |
df5f599f38ef69b4a91980f8a8cd5fc60ba86070c4b176a6082eba82fec08e63 | Python | 42,319 | 979 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
##
# @file lite2.py
# @brief
# @author Zhijie Xie
# @date 2015-11-27
from __future__ import print_function
import sys
import os
import os.path
import argparse
import subprocess
import shutil
import time
from datetime import datetime
from rmatspipeline import run_pipe
VE... |
9d546b2bdd782a14584911c8f7bcf1498cfecdecdd1b4703e0594c200ae762db | Python | 42,359 | 981 | # core.py by CoccaGuo at 2022/05/16 16:45
##############################################
# core.py renew by Zhiwen Zhu at 2023/07/21 Email address: zhiwenzhu@shu.edu.cn
##############################################
import logging
import time
from abc import ABCMeta, abstractmethod
from enum import Enum
import matplo... |
62b2fe34c14e2701c9a45d7cf68e24e9d22e828ec9f5200d69456031cdfa7261 | Python | 42,406 | 1,074 | import itertools
import logging
import math
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
import torch.multiprocessing as mp
from torch import Tensor
from torch_geometric.distributed import (
DistContext,
LocalFeatureStore,
LocalGraphStore,
)
from tor... |
3ebe373867dccbd8c57c1b1f82ccd94b6a108f9082543a067810c72eb35c815d | Python | 42,444 | 986 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# --------------------------------------------------------
# TinyViT Model Architecture
# Copyright (c) 2022 Microsoft
# Adapted from LeViT and Swin Transformer
# LeViT: (https://github.com/facebookresearch/levit)
# Swin: (https://github.com/micro... |
23b1363d1ea42c21d0ff6b7e7e875eed68dbb236c920eec73c524acc8feb39e3 | Python | 42,505 | 1,137 | # -*- coding: utf-8 -*-
# @Author : LG
import math
import typing
from PyQt5 import QtCore, QtGui, QtWidgets
from ISAT.annotation import Object
from ISAT.configs import STATUSMode, ShapeType
# ============================================================
# Outline pen
# ============================================... |
de30f4b8febcbf9c2770024895226eb6399604f3d4556a6d2603ef5926dd871b | Python | 42,523 | 976 | """MEA network plotting: Python port of StandardisedNetworkPlot.m."""
from __future__ import annotations
from pathlib import Path
from typing import TYPE_CHECKING
from dataclasses import dataclass
import numpy as np
import pandas as pd
import scipy.io as sio
if TYPE_CHECKING:
import matplotlib.axes
# ── Data... |
a3626e1dcf91ea1fbee624050fe06d9599232258095b7ccac3d92a73a6b97bc7 | Python | 42,574 | 1,175 | import os
from functools import partial
import numpy as np
import pandas as pd
import tables
import matplotlib
import warnings
from PyQt5.QtCore import Qt, QPointF
from PyQt5.QtGui import QPixmap, QPainter, QFont, QPen, QPolygonF, QColor, QKeySequence, QBrush
from PyQt5.QtWidgets import QApplication, QMessageBox
from... |
3ac12ab1d6b728f8edc92dd768fbf7ada3208d43358a08745182446f37273f6c | Python | 42,583 | 1,144 | # Generated by Django 4.2.25 on 2025-10-20 15:38
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
import cvat.apps.engine.models
class Migration(migrations.Migration):
replaces = [
("engine", "0001_release_v0_1_0"),
(
"engine... |
c6a93311959d2b0aec9b1442d97094bd19ca46a82bc30bec0edc1b03656a7323 | Python | 42,595 | 1,103 | from __future__ import annotations
import copy
import re
from abc import ABC, abstractmethod
from typing import Union, TYPE_CHECKING
import numpy as np
from scipy.signal import stft
import seisbench
from seisbench import config
if TYPE_CHECKING:
import seisbench.data as sbd
class SupervisedLabeller(ABC):
... |
e9ef40f2f947ca6768a659a446b38d6b9db71763d2bf267afe7c8a48a50b08c7 | Python | 42,661 | 849 | import pdb
import models
import torch, torch.nn as nn
import cv2
from torch.autograd import Variable
import sys, os, time, math, numpy as np
sys.path.append("/LiNet")
import torchvision.utils as vutils
# import YuSmith.lib.irnet as irnet
import YuSmith.lib.torch_util as tu
import torch.optim as optim
# from LiNet imp... |
8d1125cd8fa98df0e38fedf3589ca241a2909670833e571adfdae1744dca83e3 | Python | 42,833 | 776 | import copy
import os
import cv2
import re
import tempfile
from typing import Dict, Tuple, List, Union
import functools
import logging
from collections import OrderedDict
from multiprocessing.pool import ThreadPool
import numpy as np
from PIL import Image
from tqdm.auto import tqdm
import xarray as xr
from brainscor... |
2c48480bee2ac3e3f1d9540cb7db08f012bff94750d12f04558933fe1e01c8ee | Python | 43,053 | 1,307 | """Preprocessing functions."""
from __future__ import annotations
import json
from pathlib import Path
from typing import Any
import mne
import numpy as np
import matplotlib.pyplot as plt
from mne.preprocessing import ICA
from mne_icalabel import label_components
from scipy import stats
from scipy.ndimage.filters im... |
520a802c6206e5271e76b43faf17c5e93782f46be9a0ec669c59ba078731f052 | Python | 43,059 | 1,192 | import json
import pandas as pd
from scipy.stats import pearsonr, wilcoxon
import matplotlib.pyplot as plt
import seaborn as sns
from matplotlib.patches import FancyArrowPatch
from sklearn.decomposition import PCA
from infopath.utils.functions import *
from infopath.model_loader import load_model_and_optimizer
def ra... |
229010bbb139775b19e3bf3fac045c218a676e7ca2dad16513877a02196ebeb6 | Python | 43,120 | 1,105 | #!/usr/bin/env python
"""
These classes implement various focus lock modes. They determine
all the behaviors of the focus lock.
Hazen 05/15
"""
import math
import numpy
import scipy.optimize
import tifffile
import time
from PyQt5 import QtCore
import storm_control.sc_library.halExceptions as halExcept... |
3093d84003b6e834e6517c7f2fbdd3090c2437977cb8566e445ce378a9fb826c | Python | 43,155 | 1,105 | #!/usr/bin/env python
"""
These classes implement various focus lock modes. They determine
all the behaviors of the focus lock.
Hazen 05/15
"""
import math
import numpy
import scipy.optimize
import tifffile
import time
from PyQt5 import QtCore
import storm_control.sc_library.halExceptions as halExcept... |
f7b385302b0f0c42390424a2ed186845c53608d469ef3724dad133ae5b45663e | Python | 43,192 | 1,179 | import math
from typing import Optional, Tuple
import torch
from torch import Tensor
from torch.autograd import grad
from torch.nn import Embedding, LayerNorm, Linear, Parameter
from torch_geometric.nn import MessagePassing, radius_graph
from torch_geometric.utils import scatter
class CosineCutoff(torch.nn.Module):... |
2815b97ff44b6bac5e0a9088684c29dfc6032ba020190625c720463e4e5dd108 | Python | 43,204 | 1,028 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jul 27 10:53:04 2020
@author: Cristian
"""
# Core simulator and tools
from brian2 import *
from brian2tools import *
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
import math
import random
import os
# ====... |
e1adff133f42e977fce55e5a9518f050271077aba19ea9fbb8af7fa6404fb99b | Python | 43,265 | 853 | import logging
import os
import json
import vtk
import qt,ctk
import slicer
from slicer.ScriptedLoadableModule import *
from slicer.util import VTKObservationMixin
import numpy as np
from CurveToBundleLib.Widgets.multiHandleSlider import MultiHandleSliderWidget
from CurveToBundleLib.Widgets.multiModelSelector import... |
be3cd0b48099c095042d09ff86c659140d97107fcb07fc826efcf2666e1bf22b | Python | 43,266 | 1,089 | import yaml
import sys
import os
import h5py
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib as mpl
pathpath,myrun,ncluststr,cmethod = sys.argv[1:]
"""
pathpath = 'PATHS/filepaths_carlen.yml'
myrun = 'runC00dMP3_brain'
cmethod = 'ward'
ncluststr = '8'
"""
with open(pathpath,... |
5e1f77c705e1b6eeff021b1fcad3d59cee3621a420edff72b4c93b45e234cc43 | Python | 43,301 | 1,481 | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 11 11:05:25 2022
@author: DELINTE Nicolas
"""
import os
import warnings
import numpy as np
import nibabel as nib
from dipy.io.streamline import load_tractogram
def voxel_distance(position1: tuple, position2: tuple):
'''
Returns the distance between two voxels... |
a222112fd1cc36afc63f0641e9cf0cdfe9dbeeac8880f97de1c3fbb2df29831a | Python | 43,338 | 1,049 | # -*- coding: utf-8 -*-
import os
import gc
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.ndimage import rotate, zoom, gaussian_filter
from collections import defaultdict
from Bio import SeqIO
from torch import masked_select
import json
import warnings
from . import data_utils
from... |
c3078ce1e8911a5bd75dd28c71e85b4526af3f7948fa8062f86ea2fd34d2d0dd | Python | 43,365 | 1,229 | """Tests for the chemgraph.execution abstraction layer.
Tests cover:
- TaskSpec validation
- LocalBackend: python and shell tasks
- GlobusComputeBackend: python and shell tasks (mocked SDK)
- Backend factory (get_backend)
- Shared utilities: resolve_structure_files, gather_futures, write_results_jsonl
"""
import json... |
3e9be182a905d93f7903d65b53f309c0525b0293e8a8558e6e3499a1b15c7219 | Python | 43,410 | 1,260 | """
Compare reflectance distributions (PCA projections) of different simulation sets
with real data, aggregated at different levels (image, subject, organ).
Controlled by a YAML configuration file.
"""
import os
import pickle
import fastkde
import matplotlib.animation as animation
import matplotlib.colors as mcolors
... |
41021e19cb678071f0faaa4781f2ce948cec5f68d77469735bb5111ef1d525b5 | Python | 43,430 | 815 | import anndata
try:
from anndata.base import Raw
except ImportError:
from anndata import Raw
import batchglm.api as glm
import logging
import numpy as np
import pandas as pd
import patsy
import scipy.sparse
from typing import Union, List, Dict, Callable, Tuple
from .external import _fit
from .external import p... |
718e3f95c180ed4adbcc520bba9d6b7e1ff031d2026391036919deaa34c2f8ec | Python | 43,437 | 1,156 | import os, json, sys, shutil
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
from time import time
# DIPY Local PCA Denoising
from dipy.denoise.localpca import mppca
from dipy.core.gradients import gradient_table
from dipy.io.image import load_nifti
import dipy.reconst.dki as dki
sys.path.in... |
82d00d3e9dcf4a7401c27025f95fc508bfd1dc8ce6fb6eccf207344f219519da | Python | 43,446 | 1,261 | import pickle
from collections.abc import Sequence
from pathlib import Path
from typing import TYPE_CHECKING, Literal
import numpy as np
import pytest
from eir import train
from eir.setup.config import Configs
from tests.conftest import get_system_info
from tests.test_modelling.test_modelling_utils import check_perfo... |
029d0ea1f61bf8d13ebf1e9025a06304dba24dc137224744e04c5e8773613958 | Python | 43,496 | 928 | from .trainer import *
from flair.training_utils import store_teacher_predictions
from flair.list_data import ListCorpus
import math
import random
import pdb
import copy
from flair.datasets import CoupleDataset
from ..custom_data_loader import ColumnDataLoader
from torch.optim.adam import Adam
import torch.nn.functiona... |
9295090e53d6f901bbc44b956a1af778c50eb9ddca056c1352a7a0df69d6e618 | Python | 43,506 | 1,061 | #!/usr/bin/env python3
"""
Corrected Semantic Detail Analysis for Translation Module
Analyzes teacher-student pairs individually and provides global summary
"""
import os
import sys
from pathlib import Path
import torch
import torch.nn as nn
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from... |
88efe8d156f5e864cddcacecabf59a4be753b296d10be78a250f23c2a889532d | Python | 43,588 | 922 | import warnings
warnings.filterwarnings("ignore", message="It is not recommended to directly access")
import os
import argparse
import numpy as np
import matplotlib.pyplot as plt
from rdkit import Chem
from rdkit.Chem import AllChem
import matplotlib.patheffects as path_effects
from matplotlib.colors import LinearSegme... |
af2c23b61fd5bfd039381b74d3b07e765bd80ead2f2cf12acf045b35589d7c9c | Python | 43,596 | 1,082 | import tensorflow as tf
tf.compat.v1.disable_eager_execution()
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
import logging
import os
import numpy as np
import pandas as pd
pd.options.mode.chained_assignment = None
import json
import random
from collections import defaultdict
# import s3fs
import h... |
ccf7ce0479d188d72371715763fb857411beebd36b767c9ada5d5ab5a89e3f77 | Python | 43,639 | 879 | #!python
import shutil
import os
import importlib
from pathlib import Path
import argparse,yaml
from argparse import RawTextHelpFormatter
import traceback,time,copy,yaml,sys,uuid
import sys
import subprocess
import re
sys.path.append(Path(__file__).resolve().parent.parent.__str__()) ## this line is for development
imp... |
9f82a48e7e73e78aec3227359860854f1838ef9aca716b90e3575660b34114ac | Python | 43,723 | 663 | #!/bin/python3
# Tests for the arborNetworkConsolidationMultiComp module
# Copyright 2022-2024 Jannik Luboeinski
# License: Apache-2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# Contact: mail[at]jlubo.net
import numpy as np
import json
import os
import inspect
import pytest
import arborNetworkConsolidationMultiC... |
cf6a5fa8c8a14e6bf756c91d6b02bf8f33c31d92bcb8ff32a403d0b89507da4a | Python | 43,763 | 1,178 | # Copyright (C) 2020-2022 Intel Corporation
# Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import io
import os
import os.path
import pickle # nosec
import tempfile
import time
import zipfile
import zlib
from collections.abc import Callable, Collection, Generat... |
e2b19d0be07709ccb160f26b17efe66f3fbd590e278f3ed3b095600c7999b85b | Python | 43,791 | 1,167 | # file: layers.py
# brief: A number of objects to wrap caffe layers for conversion
# author: Andrea Vedaldi
from collections import OrderedDict
from math import floor, ceil
from operator import mul
import numpy as np
from numpy import array
import scipy
import scipy.io
import scipy.misc
import copy
import collections
... |
97f807cb5f20f56b624829b59838a7478bc6ad938b7ada20af0e70244727db71 | Python | 43,807 | 1,196 | import copy
import warnings
from collections.abc import Mapping, Sequence
from dataclasses import dataclass
from itertools import chain
from typing import (
Any,
Callable,
Dict,
Iterable,
List,
NamedTuple,
Optional,
Tuple,
Union,
overload,
)
import numpy as np
import torch
from ... |
e9505257a478da2b1ff81b04fe3880d07e804a0a94917f7dcf6c8bb8a584cffc | Python | 43,808 | 1,064 | ##############################################################################################
### Code to create plots of the neurons and synaptic weights in the network via Matplotlib ###
##############################################################################################
### Copyright 2017-2022 Jannik Lub... |
e6d9689cff1a993f921f0ac16b6ed3c811e3ee372b23c74da51a5026cbf26dc9 | Python | 43,888 | 610 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file '/media/lg/disk2/PycharmProjects/ISAT_with_segment_anything/ISAT/ui/Converter_dialog.ui'
#
# Created by: PyQt5 UI code generator 5.15.10
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit t... |
4b58679477ac809fc21cea05aa5f867ec9e5520c197aea1deef085dd3f25c3ac | Python | 43,934 | 1,170 | # file: layers.py
# brief: A number of objects to wrap caffe layers for conversion
# author: Andrea Vedaldi
from collections import OrderedDict
from math import floor, ceil
from operator import mul
import numpy as np
from numpy import array
import scipy
import scipy.io
import scipy.misc
import copy
import collections
... |
7a302df7b9b751b99c73431636237ab9ac415aa82834ba5ff0acea9556ef347f | Python | 43,970 | 815 | from .base_classes import LearningRule, BiasLearningRule
import torch
import math
class BP_like_1E(LearningRule):
def __init__(self, projection, max_pop_fraction=1., stochastic=False, learning_rate=None, relu_gate=False):
"""
Output units are nudged to target. Hidden dendrites locally compute an e... |
ebc7e380c95a4c2b57be372cfad4c347d10bff61ecb100ed9087d78a5162ae45 | Python | 43,977 | 1,036 | #!/usr/bin/env python3
"""
1. Copy config_template.yaml to config.yaml
2. Edit config.yaml with your data paths and settings
3. Prepare a CSV file with molecular identifiers, SMILES, and labels
4. Run: python batch_processing_script.py
"""
import sys
import os
import logging
import gzip
import tarfile... |
3ca4fd946284713549d1d066b2737400ac25cb8b901b9db2ee14b32b62b89437 | Python | 43,979 | 1,043 | """Pure-Python implementation of the ALCF IRI Facility API integration.
No LangChain. No ``@tool`` decorators. Any Python caller (agent tool,
notebook, test, MCP server) can import :func:`dispatch` and drive the
IRI API directly. See :mod:`chemgraph.tools.alcf_iri_tools` for the
LangChain wrappers layered on top.
Ful... |
d987adcf9ae895d58b258858e003756bc18acc758c7373a984558dedf67d22ae | Python | 43,982 | 925 | # /------------------------------------------------------------------------------+
# | 24-OCT-2022 |
# | Copyright (c) Bone Imaging Laboratory |
# | All rights reserved ... |
20cb7e1eb0acc8754f3014d11abcc9d444412a00ec7eca2d6b98cfd3ff7e8d58 | Python | 43,984 | 1,052 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
import copy
import math
from functools import partial
import numpy as np
import torch
import torch.nn.functional as F
from torch import Tensor, nn
from ultralytics.nn.modules import MLP, LayerNorm2d, MLPBlock
fro... |
31a42bb7e993d4e1a0c0023c18051cbd8724f7440f00c01c56e0e14f90fcda03 | Python | 44,010 | 990 | import collections.abc as collections
import numbers
import os
import stat
import tempfile
from abc import ABCMeta, abstractmethod
from collections import OrderedDict
from collections.abc import Callable, Mapping
from pathlib import Path
from typing import Any, NamedTuple, cast
import torch
import torch.nn as nn
from... |
07801a893a747c806976e4b77b8d2a4fe1c12ce76be919a520a8f6021e7e734c | Python | 44,033 | 1,117 | # -*- coding: utf-8 -*-
"""Module for performing binary classification from multi-voxel pattern using a support
vector machine."""
import csv
from collections import namedtuple
from pathlib import Path
from typing import NamedTuple, Optional
import joblib
import matplotlib.pyplot as plt
import numpy as np
import pand... |
662ae0c3693c700e9f63501472938536d53bd7fd5d905fefc91b1e2bb8c66f8f | Python | 44,055 | 1,394 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2018, 2019 Leonard Thiele, leonard.thiele[AT]uni-rostock.de
# Copyright (C) 2018, 2019, 2020 Julius Zimmermann,
# julius.zimmermann[AT]un... |
e64d0a410071c8f9b6aa9e34cad5d62b99259ddcdbaa4fac59b17094c45d30ed | Python | 44,060 | 1,218 | # -*- coding: utf-8 -*-
"""
D-P rule using just RNAi phen
"""
import obonet
import numpy as np
import os
import networkx as nx
import matplotlib.pyplot as plt
import pandas as pd
import matplotlib as mpl
from scipy.cluster.hierarchy import dendrogram
import great_library_phenotypes as glp
from matplot... |
76be88e02e314d428b45f9681dc8e52cd68c5586939ef1d73a18a05d1c0096b5 | Python | 44,126 | 1,070 | ##############################################################################################
### Code to create plots of the neurons and synaptic weights in the network via Matplotlib ###
##############################################################################################
### Copyright 2017-2022 Jannik Lub... |
762e2ff1fb050739723ebb1ec9c761f1d4ea3a73432e62e4b70f7b0840c71390 | Python | 44,200 | 1,185 | """Runs the PyDesigner pipeline"""
import argparse # ArgumentParser, add_argument
import glob # recursive file search
import json
import logging
import os # mkdir
import os.path as op # path
import shutil # which, rmtree
import subprocess # subprocess
import sys as sys
import textwrap # dedent
import numpy as ... |
071db555e8438cb8c98e2fd8fcab08e44aea05295235dc1b6638c8471c83fddd | Python | 44,335 | 1,370 | import os
import pickle
from typing import Any
import numpy as np
import pandas as pd
import torch
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from nltk.stem import WordNetLemmatizer
from nltk.tokenize import sent_tokenize
from sklearn.model_selection import train_test_split
from torch.utils.data impor... |
3ede583d7ae3461f012f1d7a22d7b002c7caf9bd134593d53213f0fc2ce9caf9 | Python | 44,346 | 1,034 | import os.path as osp
import warnings
from abc import abstractmethod
from inspect import Parameter
from typing import (
Any,
Callable,
Dict,
Final,
List,
Optional,
OrderedDict,
Set,
Tuple,
Union,
)
import torch
from torch import Tensor
from torch.utils.hooks import RemovableHand... |
520e745d0aef2f72f3112ffc5ea6eb8ee3975401fec61b3f583d46eb6aa2b7b2 | Python | 44,399 | 1,264 | # -*- coding: utf-8 -*-
"""snn-leukemia-gradcam.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/15qmb8Dj14uDKFREW6Ojafv2dfHVSoAtE
# SNN Leukemia Classification - Clean Training Pipeline
## Focus: Training + Model Saving + Grad-CAM
**Key Features:**
- C... |
b2976670211754bd0f43229cc5c291fd6fc78a0e364f7a2e77e21cbee830df53 | Python | 44,487 | 1,117 | import sys
import os
from os.path import join
from PySide6.QtWidgets import (
QDialogButtonBox,
QDoubleSpinBox,
QSlider,
QGridLayout,
QCheckBox,
QDialog,
QPushButton,
QLabel,
QSpinBox,
QStatusBar,
QVBoxLayout,
QFileDialog,
QWidget,
)
from PySide6.QtGui import QPixmap,... |
7aac4ffbf1e8d1c60e89cc9726c94d360e621f8c07859f638549ba2cac409dcb | Python | 44,496 | 1,177 | # -*- coding: utf-8 -*-
# =============================================================================
# This code is released for the publication:
#
# "A Transparent AI Assurance and Benchmarking Framework for EEG Seizure
# Detection on TUSZ Seeded with a Reproducible Gradient-Boosting Ensemble"
#
# License:
# ... |
a23d59fc14a2a1b015be7521b3cfdd3979bea3148bd6261f3229bd2429be6b0d | Python | 44,518 | 1,197 | import streamlit as st
# Page configuration -- MUST be first Streamlit call
st.set_page_config(
page_title="ChemGraph",
page_icon="🧪",
layout="wide",
initial_sidebar_state="expanded",
)
import json
import ast
import toml
import os
from io import StringIO
from uuid import uuid4
import re
from typing i... |
807eee34b8bbd97f5f2d8e76655c9ee22670733742ec6d997d4918a23f838bc6 | Python | 44,579 | 1,220 | # Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
8f28ade0a587ac9fbc0eceaf1eb669491346aba322d0760629fa90d767482cc6 | Python | 44,597 | 1,187 | from .trainer import *
from flair.training_utils import store_teacher_predictions
from flair.list_data import ListCorpus
import math
import random
import pdb
import copy
from flair.datasets import CoupleDataset
from ..custom_data_loader import ColumnDataLoader
from torch.optim.adam import Adam
import torch.nn.functiona... |
cb2617ad5ce0f4dc0bcbbd378810f893993b3997c444e219983b29df4ba2410a | Python | 44,618 | 1,313 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import itertools
import math
from abc import ABCMeta
from collections import Counter
from copy import deepcopy
from enum import StrEnum
from functools import cached_property, lru_cache
from io import StringIO
from ... |
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