sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d7c112d3a18d149a86375dcdd5fc3ded8bf1e9d9256c9675012122086e498445 | Python | 10,944 | 223 | from zigzag.classes.hardware.architecture.accelerator import Accelerator
from zigzag.classes.hardware.architecture.core import Core
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.operational_array import OperationalArray
from zigzag.utils impo... |
8759d8fcb4de6228d40c91be48727750efbd37c6c9ea27cd21a3ac421573d588 | Python | 10,947 | 261 | import numpy as np
import pytest
import nelpy as nel
def test_valueeventarray_construction():
events = [[0.1, 0.5, 1.0], [0.2, 0.6, 1.2]]
values = [[1, 2, 3], [4, 5, 6]]
veva = nel.ValueEventArray(events=events, values=values, fs=10)
assert veva.n_series == 2
assert all(n > 0 for n in veva.n_valu... |
4f2769366ccaaf0a7474454378f9ce725c56fe9355ac0d2b801de7caee8a4c8d | Python | 10,949 | 303 | #!/usr/bin/env python
# Python version of the evaluation script from CoNLL'00-
# Intentional differences:
# - accept any space as delimiter by default
# - optional file argument (default STDIN)
# - option to set boundary (-b argument)
# - LaTeX output (-l argument) not supported
# - raw tags (-r argument) not support... |
41df96355eaa2ceefe3f296917fbc0a63ebd008e1fa4726858e887a93a29ab79 | Python | 10,950 | 376 | """Building blocks for ResNet."""
import numpy as np
import torch
from torch import nn
from modules.activation import LIF
from modules.conv2d import SpikingConv2d, SpikingEiConv2d
from modules.norm2d import SpikingBatchNorm2d, SpikingEiNorm2d
from utils.dim import MergeTemporalDim, SplitTemporalDim
class SpikingStan... |
80ec24f1f9e4eddf26a074d0e34f53b8c084bba0ba9cda1d9e818519c220c42e | Python | 10,950 | 310 | import argparse
import sys
sys.path.insert(0, '../')
sys.path.insert(0, '../../')
sys.path.insert(0, '../../../')
sys.path.insert(0, '../../../../ogb')
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
import torch_geometric.transforms as T
from torch_geometric.nn import GCNConv, SAG... |
ac762385f5f4ba3ab7ce171b4ba0c7964ac1a3683914076fa868689b6a8069e6 | Python | 10,951 | 303 | import abc
import matplotlib.colors as mcolors
import numpy as np
from matplotlib.axes import Axes
from matplotlib.image import AxesImage
from typing import Literal, Iterable
from argclz import argument, AbstractParser, as_argument
from neuralib.plot import plot_figure, scatter_binx_plot
from neuralib.plot.colormap im... |
ebe0edd476c8c3519cfd414ee3e564d3c4b5edf4944867475b36b3efc8398135 | Python | 10,952 | 347 | """Contains vcf scoring functions."""
import os
import re
import numpy as np
import pysam
def score_geno(record, variant_row, samples, mode):
effect_allele = variant_row["effect_allele"]
beta = variant_row["beta"]
if isinstance(record, dict):
if record.get("type") != "synthetic_ref":
... |
6ee8d2a0b8561bc8fdea0b487f0d96b1bc8c1a4afcadb8d86a4e8eb61278d9d5 | Python | 10,953 | 223 | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Compute response functions for multi-shell multi-tissue (MSMT) constrained
spherical deconvolution from DWI data.
The script computes a response function for white-matter (wm),
gray-matter (gm), csf and the mean b=0.
- In the wm, we compute the response function i... |
4b2e378ddf4249b6a1eac58a5a7d18a902c109903557ee857f5a83945de8e68d | Python | 10,956 | 267 | from brainscore_vision.model_helpers.check_submission import check_models
import functools
from brainscore_vision.model_helpers.activations.pytorch import PytorchWrapper
from brainscore_vision.model_helpers.activations.pytorch import load_preprocess_images
import torch
import numpy as np
from brainscore_vision.model_he... |
2159318fa0634715d37fdfe44ede96d0911cf78ef84f9aec5aca272bd67ce53b | Python | 10,957 | 315 | """
Test the sensitivity of nest results on input parameters
"""
import numpy as np
import scanpy as sc
import pandas as pd
import os
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import jaccard_score, normalized_mutual_info_score
from scipy.optimize import linear_sum_assignment
import sy... |
57d2c7870ade53c484dc860151e09e26d764236d9691c049e0f47f1f78e3db7c | Python | 10,957 | 330 | # The ImpedanceFitter is a package to fit impedance spectra to
# equivalent-circuit models using open-source software.
#
# Copyright (C) 2021 Julius Zimmermann,
# julius.zimmermann[AT]uni-rostock.de
#
# This program is free software: you can redistribute it and/or modify
# ... |
9d5ee42f205258c49120587f2266ac4eaec7a82525227af5fc3ae60e62e3962f | Python | 10,963 | 380 | # Kai Sandbrink
# 2024-03-08
# This script aggregates settings for import by the various analysis scripts.
# %% LIBRARY IMPORT
import os
# %% HUMAN DATA
human_data_file_base = '../data/humans'
# %% TASK 1 MODELS
#### WITH BIAS = 0.4
## 04/08/24
pepe_nn_ape_models = [
20230922164924,
20230922164923,
2... |
d42a44a93a6a8a9e3d84fd936e13dd5fb9093ce3c4dc0da0627ea354a93e21e1 | Python | 10,964 | 264 | #!/usr/bin/env python3
import os
import sys
import time
import json
import getopt
import numpy as np
import pandas as pd
import scipy.ndimage as nd
from skimage import io as skio
from skimage import img_as_ubyte
def apply_registration_usage():
print("""
Usage : GEM_toolkit.py apply_registration \\
-o ... |
51799c05915b076245051f03e8667e41f1b18eee6ec5d3c609d99d82631e426b | Python | 10,965 | 250 | # add the path of custom functions
import sys
from pathlib import Path
import os
script_dir = Path(__file__).parent
project_root = script_dir
while not (project_root / 'Deps').exists() and project_root.parent != project_root:
project_root = project_root.parent
# Add project root to the Python path if it's not alre... |
1fa21dc7c4bb410b93f8bffd139a31ce7021b6f4c46fdaeb0ca2014eef090244 | Python | 10,968 | 239 | #!/usr/bin/env python
"""
HAL module to interface with the W1 Spinning Disk from Yokogawa/Andor.
Jeffrey Moffitt 5/16
Hazen 5/17
"""
import storm_control.hal4000.halLib.halMessage as halMessage
import storm_control.sc_hardware.baseClasses.hardwareModule as hardwareModule
import storm_control.sc_hardware.andor.w1Spin... |
269ea434c7fa0edab070632cda6a684d23ef06eae14f914a5716492fcf4c797d | Python | 10,969 | 257 | import torch
import os, sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from preTrain_IT_network.IT_NN import IT_NN
from Value_lNN import Striatum_lNN
import logging
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import numpy as np
from torch.distributions import Be... |
58d147211ddcf04d8b8c0ada091f9d9704a9612571ee404b68956bc6eff6ef77 | Python | 10,970 | 376 | """Building blocks for ResNet."""
import numpy as np
import torch
from torch import nn
from modules.activation import LIF
from modules.conv2d import SpikingConv2d, SpikingEiConv2d
from modules.norm2d import SpikingBatchNorm2d, SpikingEiNorm2d
from utils.dim import MergeTemporalDim, SplitTemporalDim
class SpikingStan... |
c48e3006523594f38b7421411fee9629aa4883c0e32811079d70d4dcbbd98f15 | Python | 10,970 | 275 | import pandas as pd
import re
from pyhpo.ontology import Ontology
import numpy as np
import itertools
import math
ontology=Ontology()
NullList=["none", "none documented", "nil", "(borderline)", "no concerns"]
def check_and_set_nan(strg: str, NullList: list = ["none", "none documented", "nil", "(borderline... |
2d32795b01ea4d892be0be715045d9d67cadc0e98aa03c71a9d098cf40291868 | Python | 10,971 | 245 | import pytest
import torch
import SimpleITK as sitk
import numpy as np
from pathlib import Path
import logging
from torch.profiler import profile, record_function, ProfilerActivity
from typing import Dict, Any, List, Tuple
from fireants.registration.greedy import GreedyRegistration
from fireants.registration.syn impor... |
7a5ce617b1050e76c4a3d289844bdf0c444b3398952f2f3a0070b8ff88352aa5 | Python | 10,972 | 355 | #!/usr/bin/env python3
"""
Fig4Sup1_DecoyTitrations.py
Analyzes EC50 dose-response curves for GABA and various decoy ligands.
Reads CSV/Excel files, fits 4-parameter sigmoid, and saves figures + EC50 table.
Usage:
python Fig4Sup1_DecoyTitrations.py # Process all CSV/XLS files
python Fig4Sup... |
7d3a0dc953aa1e32427625d221b730609636c45f5b67d11a92dc39ea9dfbd911 | Python | 10,974 | 303 | """Row-mapping strategies for AddIntensities windows.
Both AddIntensitiesSingleExp and AddIntensitiesMultipleExp need to translate
a table row index into an image name, a FileManager index, and vice versa.
The mapping rules differ:
* **SingleRowMapper** – identity mapping where ``row == fm_index`` and the
image nam... |
9a9e5fec84033ef3993b14a8c412eb656f0b48a196ab7c95247453efedc5aeda | Python | 10,981 | 288 | """Tests of the fixture factory itself.
If the factory is wrong, every test built on it is wrong in the same direction
and none of them notice. These check that the structural properties the rest of
the suite relies on actually hold, and that an invalid override fails with a
readable message rather than deep inside li... |
b5c6a198fc2d5443e783146e4f098b937db6e4602148e2d1ab64136e6b6da480 | Python | 10,981 | 191 | import os
import zipfile
from glob import glob
from pathlib import Path
import boto3
import pandas as pd
import xarray as xr
import mkgu_packaging
from brainscore_core.supported_data_standards.brainio.assemblies import BehavioralAssembly
from brainscore_core.supported_data_standards.brainio.stimuli import StimulusSet... |
d234cc3bd4f9bfc843db96a8fb4fa62fa5000a1fea06cfc475a3573969d0fd0a | Python | 10,982 | 252 |
import numpy as np
import xarray
from brainscore_core.supported_data_standards.brainio.packaging import package_data_assembly
import h5py
from brainscore_core.supported_data_standards.brainio.assemblies import DataAssembly
DATA_DIR = '/braintree/data2/active/users/tmarques/bs_datasets/FreemanZiemba2013_V1V2data.mat'
... |
974ebceaea2645ef689dfbe935fecdda0efda3df93cc49293173e4ddde0b8927 | Python | 10,983 | 311 | # SMIntegration: Spatial Multi-omics Integration Platform
# ==============================================================================
#
# Purpose:
# Performs KNN-based interpolation to align metabolomics data with spatial
# transcriptomics spots. It constructs a network relationship between the two
# modal... |
555a6d37484e374b441c5cf6867def0def488d944086d6bb328818da55d5aaf8 | Python | 10,985 | 303 | from typing import Tuple, List, Dict, Optional
import torch
from torch import Tensor
import torch.nn.functional as F
from yacs.config import CfgNode
def make_gaussian_kernel_1d(sigma: float, device: torch.device):
"""
Generates a one dimmensional guassian kernel based on a single parameter - sigma.
The ... |
f04b70946b6461da627c45c941c96d5b31a50b08874e3ab84a2950da92e4d5be | Python | 10,991 | 300 | from logging import raiseExceptions
import os.path as osp
import warnings
from collections import OrderedDict
from functools import reduce
import mmcv
import numpy as np
from mmcv.utils import print_log
from prettytable import PrettyTable
from torch.utils.data import Dataset
from depth.core import pre_eval_to_metrics... |
e362df1103307a0ced3766716a072b3cfb3f2d5b2ea2fc3a1725121197d08f58 | Python | 10,993 | 232 | import logging
import numpy as np
from tqdm import tqdm
from typing import Union
from brainscore_vision.utils import fullname
# do not import tensorflow at top level to avoid forcing users to install it if they don't use this metric
class MaskRegression:
"""
Klindt et. al, NIPS 2017
https://papers.nip... |
ae870c44a92f81c94d82292cd3e8d9d5efc647c2dd9feaebaa59913cec524e1e | Python | 11,002 | 287 | #This is just a hacky version of the evalClassification.py script to generateImages
import imgRetrivalUtil
import torch
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
from tqdm import tqdm
from PIL import Image
import torchvision
from torchvision.transforms import v2
from pytorch_grad_cam impo... |
f04d2775a091879163eaa357af6829b7c17aec0798a98de22839305c95b8e99f | Python | 11,005 | 254 | #!/usr/bin/env python
# author: Jannes Spangenberg
# e-mail: jannes.spangenberg@uni-jena.de
# github: https://github.com/JannesSP
# website: https://jannessp.github.io
import h5py
import numpy as np
import read5_ont
import pysam
import pywt
import multiprocessing as mp
import sys
from argparse import ArgumentDefaultsH... |
ac2651af09f0c86b639e368da3f78a8b0cef1141aca527045c087f40e4adcb47 | Python | 11,006 | 325 | from typing import List
import torch
from ..scatter import scatter
from mlcg.data import AtomicData
from mlcg.data._keys import ENERGY_KEY
from mlcg.neighbor_list.neighbor_list import (
atomic_data2neighbor_list,
validate_neighborlist,
)
from ..blocks import RANGEInteractionBlock
from ..utils import calc_wei... |
4fb2b31c0ca5c3525dc59da773ca36c3fc4670a493aa965bc7bfab2b9f02f3e2 | Python | 11,011 | 302 | """Spawn per-rank MCP server subprocesses, wait for readiness, connect."""
from __future__ import annotations
import asyncio
import contextlib
import logging
import os
import shlex
import socket
import subprocess
import time
from pathlib import Path
from typing import Any
import httpx
from langchain_core.tools impor... |
e42457a66d155596f6d9f30f6cc31da90821f7b45888a8948191aade1afb19bc | Python | 11,011 | 283 | import math
from typing import Optional
import torch
from torch import Tensor
from torch.nn import Parameter
from torch_geometric.nn.aggr import Aggregation
from torch_geometric.utils import softmax
class SumAggregation(Aggregation):
r"""An aggregation operator that sums up features across a set of elements.
... |
cbfd1adcac3f0f7f03b434d18d169c613547a31437398e5d5669d92d9e133fb1 | Python | 11,012 | 216 | # Datasheet of EXTRACT_Profile detected from a folder (dmrifiberprofile run -i <folder>, make-datasheet)
#
# The files are found anywhere below the folder and grouped by case id, the part of the file name before '_dwi'
# (e.g. sub-100619_ses-017m_acq-dir79select_dir_run-004). Known names, after <id>_dwi[...]:
#
#... |
466f85f2ddd63ca07068e5e68bf9724a640b09dc76164e3ab14827330d906515 | Python | 11,013 | 322 | from langgraph.graph import StateGraph, START, END
from langchain_core.messages import ToolMessage
import json
from langchain_openai import ChatOpenAI
from langgraph.checkpoint.memory import MemorySaver
from chemgraph.tools.ase_tools import (
run_ase,
save_atomsdata_to_file,
file_to_atomsdata,
)
from chemgr... |
d683c6fabc05941e503657079dd2b3c36e2e9a2037cbf30a38ab7dd3fa47058e | Python | 11,013 | 340 | from dataclasses import dataclass
import os
import pandas as pd
from sklearn.metrics import (
make_scorer,
accuracy_score,
roc_auc_score,
f1_score,
precision_score,
recall_score,
)
from sklearn.utils import compute_class_weight
from sklearn.ensemble import RandomForestClassifier
from sklearn.ne... |
d9432bcec2843c48ca3eb51548ec785811dc74e63f6fa491c42076c065635c3f | Python | 11,018 | 313 | # coding: utf-8
import difflib
import filecmp
import os
import pickle
from functools import lru_cache
from inspect import cleandoc, getfullargspec
from pathlib import Path
import cloudpickle
import joblib
import numpy as np
import sklearn.datasets
from sklearn.utils import check_random_state
import lightgbm as lgb
S... |
99eaa25d0047cdef45fb052f680eaf8538edcd8038c9130d4401eeada7847a8d | Python | 11,019 | 336 | """Atomistic LIne Graph Neural Network.
A prototype crystal line graph network dgl implementation.
"""
from typing import Tuple, Union, List
import dgl
import dgl.function as fn
import numpy as np
import torch
from dgl.nn import AvgPooling
# from dgl.nn.functional import edge_softmax
from pydantic.typing import Lite... |
486c741f43613ac83b84cbf897b0b9b9583df6b0b14c71ebcfa505fdbaaf4348 | Python | 11,022 | 276 | import logging
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage import zoom, gaussian_filter1d
from .base import Model
from nems.registry import layer
from nems.layers.tools import require_shape, pop_shape
from nems.layers import (
WeightChannels, WeightChannelsGaussian, FiniteImpulseResponse... |
c41ad4c211caa0dec7825fa0f26ffc24ff1fbf79d7861dd06728684a86a25481 | Python | 11,022 | 292 | """
Support for reading and writing genomic intervals from delimited text files.
"""
from bx.bitset import (
BinnedBitSet,
MAX,
)
from bx.tabular.io import (
ParseError,
TableReader,
TableRow,
)
class MissingFieldError(ParseError):
pass
class FieldFormatError(ParseError):
def __init__(s... |
6e0cac90b6be300c3be26e78f3a2e6e6bcdc1c8dc7fd5b52836be41f1370a14e | Python | 11,025 | 279 | import torch
from torch import nn
from eir.models.input.array.models_cnn import CNNResidualBlock
from eir.models.layers.mlp_layers import MLPResidualBlock
from eir.models.layers.projection_layers import (
get_1d_projection_layer,
get_lcl_projection_layer,
)
from eir.models.tensor_broker.projection_modules.cnn ... |
baef6c4e3271b158eb0c16005a07c7607cb6c41678601a96f5bc8b68ec7882c1 | Python | 11,026 | 336 | import os
import string
from distutils import dir_util
from typing import NamedTuple, Optional
import anndata as ad
import numpy as np
import pandas as pd
import pytest
import scanpy as sc
from numpy.typing import NDArray
from scipy import stats
from scipy.sparse import csr_matrix
class SimulatedData(NamedTuple):
... |
82249eb4b2e28472a1c3613a60175dbd6f11f996c626e2c8454d35fec22074d7 | Python | 11,030 | 299 | """VGG
Adapted from https://github.com/pytorch/vision 'vgg.py' (BSD-3-Clause) with a few changes for
timm functionality.
Copyright 2021 Ross Wightman
"""
from typing import Any, Dict, List, Optional, Union, cast
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAUL... |
04416dffa4d0a916fd4cccb2b6babd5ec2aaa396bb9ced6e6841eaeca201d795 | Python | 11,031 | 254 | #!/usr/bin/python
# ----------------------------------------------------------------------------------------
# pumpControl: A wrapper class for the a generic pump
# ----------------------------------------------------------------------------------------
# Jeff Moffitt
# 2/15/14
# jeffmoffitt@gmail.com
# ---------------... |
4f82112dc2d55a9af3fb219737c0ff11262d0a51cd3849354b83686e7ef5d8b6 | Python | 11,043 | 337 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jun 19 14:51:07 2017
@author: ajaver
Get the food contour using thresholdings and morphological operations.
"""
import tables
import numpy as np
import cv2
from skimage.transform import hough_circle, hough_circle_peaks
from skimage.morphology import ... |
3dfcc1df0954b125fa91d8e51052dfebaee014bec72290884debb40a2908181d | Python | 11,045 | 256 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
from sklearn.cluster import KMeans
import torch.optim as optim
from random import shuffle
import pandas as pd
import numpy as np
import scanpy as sc
from . layers import... |
13a4ee56ca8a138af933f140cb0161f0cfaaef2d0804831c5aa963ebc0214a97 | Python | 11,048 | 269 | """Search Space Macro-architecture."""
import torch
import torch.nn as nn
import torch.nn.functional as F
import operator
import functools
def round_(filter):
return round(filter / 3)
class ResidualBranch(nn.Module):
def __init__(self,
in_channels,
out_channels,
... |
402db3f5998917c22d97d0190e2423d375228aec11a7a2779911a2625ed3be7c | Python | 11,049 | 265 | import numpy as np
import task_setups as setup
import matplotlib.pyplot as plt
import matplotlib as mpl
from scipy.stats import multivariate_normal
from scipy.stats import scoreatpercentile as sap
from scipy.stats import percentileofscore as pofs
def complete_input(cond_dict,reg_prob_dict,cat_labels):
cats_in_con... |
281b616a795d17ae517d048a48da2b75db247f7b691b6761f724bd12d8f85255 | Python | 11,051 | 313 | # Copyright 2014-2015 Numenta Inc.
#
# Copyright may exist in Contributors' modifications
# and/or contributions to the work.
#
# Use of this source code is governed by the MIT
# license that can be found in the LICENSE file or at
# https://opensource.org/licenses/MIT.
from collections import namedtuple
import logging
... |
b5171608653ca44d3b25c125365363f70fc0b8081384d279f2fe7ade698040e1 | Python | 11,056 | 244 | # %%
import pandas as pd
from torch_geometric.data import HeteroData
import torch
import torch_geometric.transforms as T
import numpy as np
import random
# %%
SEED = 666
random.seed(SEED)
np.random.seed(SEED)
torch.manual_seed(SEED)
torch.cuda.manual_seed(SEED)
torch.backends.cudnn.deterministic = True
# Extracting ... |
ee8aed167f59db0b2e50abedd2a4959e6dd334e051c7ccd7d20b981b5c453aae | Python | 11,056 | 350 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
import json
import os
import zipfile
from pathlib import Path
import pytest
from cvat_sdk.api_client import exceptions
from cvat_sdk.core.proxies.tasks import ResourceType, Task
from PIL import Image
from sdk.util import generate_coco_json
from sha... |
ffdc2d8e1b5205bafb73a2f309b7317a5ab7c6a536a8e97e06ad6ae4473efd50 | Python | 11,063 | 185 | import os
import yaml
import argparse
import torch
seed_list = [0, 1004, 911, 2021, 119]
### CONFIGURATIONS
parser = argparse.ArgumentParser()
# General Parameters
parser.add_argument('--seed', type=int, default=10)
parser.add_argument('--seed-list', type=list, default=[0])
# parser.add_argument('--seed... |
91c5d1f6e5c34407d59d377b05dd662faae5c2a9fa9350933c02ec4d995e3c89 | Python | 11,065 | 306 | #############################################################################
# Copyright (C) 2020-2026 MEmilio
#
# Authors: Patrick Lenz, Annette Lutz
#
# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance ... |
c05e965e0487272b514df02331c3a3d5dcac8334c60f606d3df976b5229acb8d | Python | 11,067 | 238 | # These imports are tricky because they use c++, do not move them
from rdkit import Chem
try:
import graph_tool
except ModuleNotFoundError:
pass
import os
import pathlib
import warnings
import torch
import wandb
import hydra
import omegaconf
from omegaconf import DictConfig
from pytorch_lightning import Train... |
1809f698bad1a0123490ba6561e539df1da09d1ed7ab2d8e00f6c2642cb4d75e | Python | 11,068 | 295 | import argparse
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torch_geometric.data import NeighborSampler
from torch_geometric.nn import SAGEConv
from torch_geometric.utils import to_undirected
from ogb.linkproppred import PygLinkPropPredDataset, Eval... |
7cf79234e64d71d43b26a49e067246821f355f984ef2b7409a58f3808cd0d82f | Python | 11,068 | 338 | #!/usr/bin/env python
import defopt
import logging
from pathlib import Path
from typing import Optional
import pandas as pd
import polars as pl
import numpy as np
import polars.selectors as cs
import gzip
import sys
# from numba import njit
ROLLING_FIRE_SCORE_WINDOW_SIZE = 200
def is_gzipped(path):
with open(pat... |
a1880009a0572238f7657d43cddd20d6afc4209d5c56ef18782bc2f05f27bc14 | Python | 11,068 | 264 | import time
import sys
from nab.detectors.base import AnomalyDetector
from nab.detectors.earthgecko_skyline.algorithms import (
histogram_bins,
first_hour_average,
stddev_from_average,
mean_subtraction_cumulation,
median_absolute_deviation,
stddev_from_moving_average,
least_squares)
####
#... |
7af0cafd530866a103b4582eac0bfca5c07874c2065da2431178e24daf23b602 | Python | 11,076 | 299 | """
This script makes a plot of the rate differences between 1R, 1NR, and 2NR
conditions for Actor and Observer trials.
"""
import sys
import os
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd... |
1faf58d3511073bce7ab11210d827ebad84e20ce736ee5b0a2848bdece09cd64 | Python | 11,077 | 265 | #!/usr/bin/env python
"""
Listview containing a variable number of elements representing
all of the currently available parameters files.
Hazen 04/17
"""
import os
from PyQt5 import QtCore, QtWidgets
import storm_control.sc_library.parameters as params
import storm_control.hal4000.halLib.halDialog a... |
2b0001c6133174aa23a58ef01ed24ddc7334cead631a6cd38b7d31890af056ee | Python | 11,080 | 274 | import torch
import torch.nn as nn
from torchsummary import summary
from collections.abc import Sequence
import numpy as np
from .utils import ConvLayer, SkipConnection, ParallelConnection, DoubleSkipConnection
from .unets import EncoderBlock, DecoderBlock, InputBlock3d
device = torch.device("cuda:0") if torch.cuda.i... |
d1fe23b85e8f7a447f9e8ee4f2834a628e6683b19517432964f0f7857cc18770 | Python | 11,086 | 351 | import math
from collections.abc import Iterable, Sequence
from dataclasses import dataclass, field
from typing import (
TYPE_CHECKING,
Any,
Literal,
)
import torch
from sklearn.preprocessing import LabelEncoder, StandardScaler
from torch import nn
from eir.models.layers.mlp_layers import MLPResidualBlock... |
a5588723d69b6fd61dddf8a635eba97b1256e019066e0a82b5710d5df98983d2 | Python | 11,092 | 333 | """Tile-grid layout helpers for rigid-overlap stitching."""
from __future__ import annotations
from dataclasses import dataclass
from enum import Enum
from typing import Mapping, Sequence
import numpy as np
TILE_SIZE_PX = 2048
# This is intentionally a fixed compatibility value, not recalculated at run time.
TILE_... |
c28c21caec9eadb3a1dddebb854e1b20329339f078237a08afae4f09ad745534 | Python | 11,093 | 314 | """
Data processing utility functions.
Author: florian.birk@tuebingen.mpg.de
"""
import numpy as np
from pathlib import Path
import sys
from scipy.ndimage import gaussian_filter
# Add the parent fop to the path for imports
sys.path.append(str(Path(__file__).resolve().parent.parent))
# Import required modules
try:
... |
6f7f57ec497d89a665b153a084d085352649ea67917538f56c48ab3c1a05f387 | Python | 11,095 | 294 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn import SAGEConv
from torch_geometric.data import Data
import torch.nn as nn
class SetConv(torch.nn.Module):
def __init__(self, nb_feat_in, nb_feat_out):
super(SetConv, self).__init__()
self.fc1 = torch.nn.C... |
9b7a3233702ceccfd0c09745b043fa1b8d30029593c44f10a313e671ea83099e | Python | 11,096 | 228 | from zigzag.utils import pickle_deepcopy
from zigzag.classes.hardware.architecture.operational_array import OperationalArray
from zigzag.classes.hardware.architecture.memory_hierarchy import MemoryHierarchy
from zigzag.classes.hardware.architecture.accelerator import Accelerator
from zigzag.classes.hardware.architectur... |
845cdf0023153506e0a752672f128a8202f87f75bba6a1710b779ecc35510e55 | Python | 11,097 | 320 | """
Copyright 1999 Illinois Institute of Technology
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 the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publis... |
180d06fa86d22ff3e9d14cd744d926b75b7480679ec59c2ea75cb00fc69fe8cd | Python | 11,103 | 195 |
import argparse
import os
import pathlib
import time
import datetime
import h5py
import csv
import numpy as np
from enum import Enum
from helper_functions.get_dendritic_current import STEADY_STATE_CURRENT
from helper_functions.multiprocessing_chunks_complete import all_chunks_complete
from helper_functions.load_cell_... |
73831318a7c9118b5f303c9dfeb1212dfdd5fad72113bede75849539f6e5bf4d | Python | 11,106 | 286 | #!/usr/bin/python
#
# Utility for calculating z calibration curves.
#
# Hazen 02/13
#
import os, sys
from PyQt5 import QtCore, QtGui, QtWidgets
# UIs.
import storm_control.zee_calibrator.mainwindow_ui as mainwindow_ui
# Plotting
import storm_control.zee_calibrator.plot as plot
# Calibration fitting
import storm_con... |
35a6518d9b950c4ffbe051affa22d7c4cccbfc9ed26bae4bfa12ff3e2dd349cc | Python | 11,108 | 300 | """
OutputDirDialog: Qt dialog for confirming or selecting the output directory.
Copyright 1999 Illinois Institute of Technology
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 the Software without restrictio... |
086c9c295881078291b238a3e9e3a30d8bf16555b9a901e9839f51fcd695e28e | Python | 11,109 | 261 | import argparse
import logging
import multiprocessing
import os
import pickle
import time
from functools import partial
import h5py
import numpy as np
import pandas as pd
import tensorflow as tf
from data_reader import DataReader_mseed_array, DataReader_pred
from model import ModelConfig, UNet
from postprocess import ... |
17911e51c415ab511920153922d341ff0d21064036346ccb6dfc3c5a2aad3449 | Python | 11,110 | 324 | from copy import copy
import argparse
from tqdm import tqdm
import torch
import torch.nn.functional as F
from torch.nn import ModuleList, Linear, ParameterDict, Parameter
from torch_sparse import SparseTensor
from torch_geometric.utils import to_undirected
from torch_geometric.data import Data, ClusterData, ClusterLoa... |
65069f8f8131e2a637f9d4d460e63515314068ced59ecf3249986cafd77a3864 | Python | 11,110 | 274 | # -*- coding: utf-8 -*-
"""
MPM <-> MP2RAGE registration
The purpose of the following script is to compute the deformation field for the
registration between MPM and MP2RAGE T1-maps. The script consists of the
following steps:
1. make folder structure
2. scale PD-map (MPM)
3. skullstrip MP2RAGE and MPM
... |
685f0b47664848cb73596678c1400ec8203e3f539f14edde5a2a46f179d416a8 | Python | 11,110 | 366 | #!/usr/bin/python
# file: matdocparser.py
# author: Andrea Vedaldi
# description: Utility to format MATLAB comments.
# Copyright (C) 2014-15 Andrea Vedaldi.
# All rights reserved.
#
# This file is part of the VLFeat library and is made available under
# the terms of the BSD license (see the COPYING file).
"""
MatDocP... |
70b164c4d4570d211e4a016041c0491e0ae653d3b5e4420f758054642ac9f12a | Python | 11,110 | 301 | from argparse import Namespace
from pathlib import Path
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
import torch
from eir.setup.output_setup_modules.survival_output_setup import (
ComputedSurvivalOutputInfo,
)
from eir.setup.schemas import SurvivalOutputTypeConfig
from eir.train_utils.... |
7b7e3f04fff59cc616a4010898a49a94ec1c3baa1ee7121209de340d77467f55 | Python | 11,110 | 366 | #!/usr/bin/python
# file: matdocparser.py
# author: Andrea Vedaldi
# description: Utility to format MATLAB comments.
# Copyright (C) 2014-15 Andrea Vedaldi.
# All rights reserved.
#
# This file is part of the VLFeat library and is made available under
# the terms of the BSD license (see the COPYING file).
"""
MatDocP... |
2ef1fc1b2de5a62a0ee3a83a70ef8d16af8bf2c79e3700cdd095bf1cb1f52096 | Python | 11,112 | 350 | import scanpy as sc
import numpy as np
from typing import List
import anndata
from typing import Optional, Union
from sklearn.neighbors import kneighbors_graph
import scanpy as sc
import numpy as np
from scipy.sparse import issparse
from sklearn.utils.extmath import randomized_svd
from scipy.sparse import csc_matrix, c... |
53dc7c4f14a750a93f859cc56e1f8449669f9fa731d0a3348edc6846e60b3da9 | Python | 11,112 | 262 | '''
Author: Laurent Guerard
Group: IMCF
Email: laurent.guerard@unibas.ch
Email bis: l.guerard42@gmail.com
Creation Date: Monday, 21st October 2019 4:39:24 pm
-----
Last Modified: Wednesday, 20th November 2019 18:50:35
Modified By: Laurent Guerard
-----
HISTORY:
Date By Comments
---------- -- ... |
7cbe7f1fe1891ac178b9ce4a0a39a428c3de81f7d1d6fbb95ff8b7bab14eab80 | Python | 11,112 | 343 | # -*- coding: utf-8 -*-
"""Skull stripping tools."""
import os
import nibabel as nb
import numpy as np
from scipy.ndimage import binary_fill_holes
from scipy.signal import argrelextrema
from .. import execute_command
from ..io.filename import get_filename
from ..registration.transform import apply_header
from ..segm... |
931f9a602283b043936ae63ce260158eceb822ad44fd38b389e4bbef8327919c | Python | 11,114 | 353 | """RAG (Retrieval-Augmented Generation) tools for ChemGraph.
Provides tools to load documents (.txt and .pdf) into a FAISS vector
store and query them for relevant context. Supports OpenAI and
HuggingFace embeddings with automatic fallback.
"""
import os
import logging
from typing import Optional
from langchain_core... |
b865006173ab25d2fd8823918fc24e38fe5a015a16dbefdaaa53de1a9ef72051 | Python | 11,116 | 243 | #Lucas Sancéré -
import os
script_dir = os.path.dirname(os.path.abspath(__file__))
import joblib
import numpy as np
import yaml
from attrdictionary import AttrDict as attributedict
from histo_miner.feature_selection import SelectedFeaturesMatrix
#############################################################
## Load... |
65c9eb0ed84bc1696d03328df423eaceee2fdf664d21007a4800614971de4962 | Python | 11,118 | 288 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
"""
Ultralytics YOLO26 Pose Estimation with optional Multi-Object Tracking using Axelera Voyager SDK.
Standalone example using the axelera-rt pipeline API.
No ultralytics dependency at runtime.
Exported with nms=False, YOLO26 is NMS-free: the model o... |
3325b504549ccb6cfb67b6a68895526e7d6b56a1d5239d345fe555a54a52c6ef | Python | 11,122 | 307 | from __future__ import annotations
from typing import Any
import numpy as np
import obspy
import torch
from obspy.core import Trace
import seisbench
from .base import GroupingHelper
from .phasenet import PhaseNet
from seisbench.util.dkpn_shared import (
_DKPN_ANNOTATE_DEFAULTS,
_DKPN_FEATURE_DEFAULTS,
_... |
df9e9b76f0906c74d2a760d01a73c7fb0688638239fae078280fada63581350f | Python | 11,126 | 388 | # -*- coding: utf-8 -*-
"""EPI <-> EPI
The purpose of the following script is to compute the deformation field for the
registration between different epi time series. The script consists of the
following steps:
1. set output folder structure
2. n4 correction epi
3. clean ana (remove ceiling and normalise)
... |
ddaa619e5aa00bcb1902c5e6b42f2ebc227b4f0818d03c423f99b1107db6dd67 | Python | 11,127 | 223 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
# from PyQt5.QtPrintSupport import QPrintDialog
from PyQt5.QtWidgets import QMessageBox, QMainWindow, QMenu, QAction, QFileDialog, QApplication
from napari_dmc_brainmap.registration.sharpy_track.sharpy_track.view.ModeToggle import ModeToggle
from napari_dmc_brainmap.registrat... |
9d3e010b746f8c6af7ad6ddda81aefa504d1ef567b661f7b0605b5f26ab0281a | Python | 11,129 | 285 | """
HCTSA
"""
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap
from palettable.colorbrewer.sequential import (PuBuGn_4,
PuRd_4,
... |
4ac8318db1ef393dd909d44a1dd4f91258d58a34963db3d5ff3357cf3517e305 | Python | 11,131 | 353 | import os
import numpy as np
import pandas as pd
from scipy.optimize import least_squares, minimize
from typing import Dict, Tuple, Optional, List
import matplotlib.pyplot as plt
from dataclasses import dataclass
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
from config.physi... |
ef171b2a6e8ca6fac8ac11f894795caf4a99d4322d89aac73f13c7b522aa7d17 | Python | 11,131 | 293 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author: Yong Bai, yong.bai@hotmail.com
@License: (C) Copyright 2013-2022.
@Desc:
"""
import numpy as np
import pandas as pd
import scanpy as sc
from scipy.stats import ranksums
from statsmodels.stats.multitest import multipletests
from tqdm import tqdm
def detect_... |
8d5c4ee30667c97e67beb32462b8eb99119f63fbf77c8cbed0e8c86b4eb41c6e | Python | 11,133 | 341 | import os
from collections import defaultdict, namedtuple
from datetime import datetime, timedelta
from json import dumps
from typing import Any, AnyStr, Dict, List, NamedTuple, Union, Optional
import numpy as np
import requests
import tensorflow as tf
from fastapi import FastAPI, WebSocket
from kafka import KafkaProd... |
9901f0259346a002c865a3234687d90d7ad03c42664d3d7897764d7bd0a5a5d2 | Python | 11,133 | 268 | # %% [markdown]
# # Prediction of Foraging States of *P. pacificus*
#
# The single steps of this pipeline are the following:
# 1. additional feature calculation
# 2. pipeline loading
# 3. prediction
# 4. analysis and plotting
# %% IMPORTS
# lib imports
import os
import time
import tqdm
import sys
import numpy as np
... |
8a4b42fab5eebffb402abe47506866cb308432917655fabf73e941c75159756e | Python | 11,142 | 334 | """Skill inference task.
Project for Setayesh Radkani and Michael Yoo.
"""
#pylint: disable=import-error, no-name-in-module
import numpy as np
import pdb
from moog import action_spaces
from moog import observers
from moog import physics as physics_lib
from moog import game_rules
from moog import tasks
from . import... |
d8d2d2a7c723e7ac76e5649ca45aa484f5336021e5afae95faa65de0fa8616f7 | Python | 11,142 | 328 | # -*- coding: utf-8 -*-
import logging
from matplotlib.font_manager import findfont
import numpy as np
from PIL import Image, ImageDraw, ImageFont
from scilpy.viz.color import generate_n_colors
def any2grayscale(array_2d):
"""
Convert an array to `uint8` grayscale so that it can be appropriately
handled... |
2a93d1b6ed4e7cfdaa617ef3a11f0586a7f72172f1e6d152980ab07d52036937 | Python | 11,143 | 334 | """Skill inference task.
Project for Setayesh Radkani and Michael Yoo.
"""
#pylint: disable=import-error, no-name-in-module
import numpy as np
import pdb
from moog import action_spaces
from moog import observers
from moog import physics as physics_lib
from moog import game_rules
from moog import tasks
from . import... |
9322bb3ade29e15e112980fc020cd3c26b049461532f3cad956be4f7a96ae38e | Python | 11,143 | 372 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import matplotlib
import matplotlib.colors as mcolors
import numpy as np
from skimage.morphology import disk
def get_registration_parameters(
metrics,
affine_iterations,
syn_iterations,
shrink_factors,
smoothing_sigmas,
th... |
9d7e151ad7a91987c5794472fcdf6d90dc1d707cd2b24ca059bbdad9b61cb2c5 | Python | 11,143 | 342 | # Copyright (C) CVAT.ai Corporation
#
# SPDX-License-Identifier: MIT
from __future__ import annotations
import argparse
import textwrap
from collections.abc import Sequence
import cvat_sdk.auto_annotation as cvataa
from cvat_sdk import Client, models
from cvat_sdk.core.helpers import DeferredTqdmProgressReporter
fro... |
cfb8158c9ff46356816748ea4de594b045418cff2c6b6049344c55f248461728 | Python | 11,146 | 231 | from dataclasses import dataclass
from neuron_interface.neurosim.cells import L23_PC_cADpyr, L4_LBC_dNAC, L4_LBC_cSTUT, L4_LBC_cACint, \
L4_NBC_dNAC, L4_NBC_cACint, L4_SBC_bNAC, L4_SBC_cACint, \
L5_TTPC2_cADpyr
i... |
8fe99a1bca3d07d35afd8cebfab0d4e666f8e623b05ec166b1174f863ddf5fad | Python | 11,147 | 261 | from dtiplayground.dmri.common.tools.base import ExternalToolWrapper
from dtiplayground.dmri.common import measure_time
import dtiplayground.dmri.common
from pathlib import Path
import subprocess as sp
import os
import re
_options_cache={} # binary path -> set of option names listed in its usage text
class FSL(Ex... |
dcacba12d1839ff5a521604edaf96be8d3c0af64078c64beb8f78df0f41a49bb | Python | 11,147 | 312 | """
Hypergraph Neural Network (HGNN) for learning node and hyperedge embeddings.
This module implements the HGNN architecture for disease-hypergraph representation
learning, where diseases are modeled as hyperedges connecting metabolites, proteins,
and GO terms.
References
----------
.. [1] Feng Y, You H, Zhang Z, et... |
8708c98a0be4a595ebe43ab20591377547ec5039fd382eaa8bbe42a1d9ba02e1 | Python | 11,150 | 305 | from scipy import stats
import torch
from tqdm import tqdm
from smart.model import SMART
from smart.layer import SAGEConv_Decoder, SAGEConv_Encoder
import torch.nn.functional as F
import numpy as np
def laplacian_regularization(x, edge_index):
"""
Compute Laplacian regularization loss.
This loss enforces... |
b46f1a08b4d75f83d0ad20fbed9c4e6ec581a5ce825e4546f66afa9253fb31dd | Python | 11,151 | 278 | # -*- coding: utf-8 -*-
import os
import re
import sys
def extract_reference_values(ref_pcr_path):
values = {
'zero': '',
'bg_coeffs': [],
'scale': '',
'u': '',
'v': '',
'w': ''
}
try:
with open(ref_pcr_path, 'r') as file:
lines = file.... |
b4eb548c739602753eff434e3b2022fd31948728127f6178e0fd3693813fd3fc | Python | 11,151 | 311 | import numpy as np
from scipy.sparse import issparse, lil_matrix
from scipy.spatial import Delaunay, distance
try:
import cupy as cp
except ImportError:
cp = None
def pre_cal1(N):
degree = np.diag(np.sum(N, axis=1))
L = degree-N
L_inv = np.linalg.pinv(L, rcond=np.finfo(float).tiny)
n = len(N)
... |
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