sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0fb47968b7212afa50fef26df1780a313f1bf2d3fed1c214b20221e763ad53f2 | Python | 4,549 | 129 | import logging
import numpy as np
from copy import copy
from typing import Optional, List, Dict, Tuple, Union
from .parser import dataparser_mapping
from ase.io import read
import pytorch_lightning as pl
log = logging.getLogger(__name__)
class LitAtomsDataset(pl.LightningDataModule):
def __init__(self, p_dict)... |
6522f70ba92ec18d0ace9795352faf79a1d1e77da611e016de877b78465c009e | Python | 4,549 | 158 | import pandas as pd
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score, roc_auc_score, average_precision_score, precision_score, recall_score, \
f1_score
filename = 'data/western_china_tra... |
9573a06724e53a6e4798af2dc398b0d00dffe40eb0473b171ce690908bef9685 | Python | 4,549 | 136 | """Support functions for working with wheel files.
"""
import logging
from email.message import Message
from email.parser import Parser
from typing import Tuple
from zipfile import BadZipFile, ZipFile
from pip._vendor.packaging.utils import canonicalize_name
from pip._internal.exceptions import UnsupportedWheel
VER... |
905d52940fe2204eebaa8f4d9cbdd21c6d55c2e173925d5e48e67088fcdaa40f | Python | 4,552 | 151 | # Node-group asset "Visualize Chi Angle" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_CH... |
b17994a4fddea2516bba19186710f6afbd95377abff0d7f2261ddf580d4a4f5f | Python | 4,552 | 138 | #
# MIT License
#
# Copyright (c) 2024 GT4SD team
#
# 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,... |
c6c70bb5f6da26de86701becf6384c20e586eae961cb54689254ef1200c651a0 | Python | 4,552 | 126 | from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.nn.integer.ram.design import Ram
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.c... |
36a58fdac58a078608f18bcf642a3a24dd40b28e6821b964b0e2315898a4a3ab | Python | 4,554 | 133 | import os
import numpy as np
import pandas as pd
import argparse
import pyreadr
import scanpy as sc
import anndata
import sklearn
import umap
import annoy
import torch
def read_data(args):
"""
- Load csv preprocessed with scanpy or Seurat.
- Must be a csv with format n_cells x n_genes with normalized (no... |
7a1bbb135a223de375db9cc8b450f25e0f8339bde335b4ba1d10820040ac97fd | Python | 4,554 | 107 | # Copyright (c) 2022, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and t... |
fddc163caae01eae1fc127b5fd27e0a9e45b6c50b4874fcbd543df4172b81fe0 | Python | 4,554 | 115 | # Script to launch particle swarm optimization
# Requires an argument that is the directory with the settings files that specifies objectives/constraints
# Ex: settings_2013_31_120RMT, settings_2020_43_120RMT
# Must be run with at least 2 processors
import os
os.environ["OPENBLAS_NUM_THREADS"] = "1"
from os i... |
02e684b353fb482f622a7208443395c8c6c43fc109a0b8f6d24182df83b1f67e | Python | 4,555 | 141 | """Plot performance Medication OFF vs ON."""
from __future__ import annotations
import csv
from enum import Enum
from pathlib import Path
import numpy as np
import pandas as pd
import pte_decode
import scipy.stats
import motor_intention.plotting_settings
import motor_intention.project_constants as constants
import m... |
4be046104502e6ef07df5384127a4c1e6a2f72c30fe74f142dca64b718e98593 | Python | 4,555 | 156 | """Tutorial example for dipole current sources in cylindrical coordinates.
tutorial reference:
https://meep.readthedocs.io/en/latest/Python_Tutorials/Cylindrical_Coordinates/#nonaxisymmetric-dipole-sources
"""
from typing import Tuple
import meep as mp
import numpy as np
RESOLUTION_UM = 50
WAVELENGTH_UM = 1.0
N_SL... |
a550a882231d0155aaf57b1897a9f44392a26e99b6743deb273a590a51cf7f1b | Python | 4,557 | 128 | """
Unit tests for regtools/registration/core/config.py
Covers:
- HAS_ANTS flag
- DEFAULT_REGISTRATION_METHOD
- check_ants_environment
- estimate_registration_memory
- Color constants
"""
import numpy as np
import pytest
# ====================================================================... |
b126250e6178b7deeb63faead1708f0f6781ee1fc995200126e652e2664e1b95 | Python | 4,557 | 114 | from __future__ import division, print_function
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "7"
from Dataset.mydataset import Dataset
import argparse
import numpy as np
from BDNN_Model import BBP_Model
from BDNN_Model_Wrapper import BBP_Model_Wrapper
import time
import torch.utils.data
#%%
def mkdir(paths):
if ... |
ff407c59cd6f86240c61590dd9f0d4dfa6f3821154c895f372062e66c69346c9 | Python | 4,559 | 113 | import gc
import logging
import model.optimiser
import torch
from sklearn.preprocessing import MultiLabelBinarizer
from torch.utils.data import DataLoader
from src.utils import calc_measurements
logger = logging.getLogger(__name__)
class Client(object):
"""Class for client object having its own (private) examp... |
99056e23e4559937c8b4bce0ab765053c73c5887db9e8c424d5beb1bddb76727 | Python | 4,560 | 135 | import os
import logging
import json
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from sklearn.metrics import roc_curve, roc_auc_score, average_precision_score, f1_score, confusion_matrix
def eval_ddi_model(true_label, pred_score, threshold: float = 0.5, opt_thr:... |
711d14bfd68f1c4e19b3351c697bdd8b9b8ff1cbbac9615e066c7089f57bb8c3 | Python | 4,561 | 150 | from pathlib import Path
import yaml
import torch
import math
import os
import torch.nn as nn
from timm.models.helpers import load_pretrained, load_custom_pretrained
from timm.models.vision_transformer import default_cfgs
from timm.models.registry import register_model
from timm.models.vision_transformer import _create... |
8162f218d243a8b0f3b9ec2ee9d33ef535e9c5b2fcd3d49dcc0f90b5ccdd0acd | Python | 4,561 | 100 | import torch
from torch.optim.optimizer import Optimizer, required
class PIDAccOptimizer_SI(Optimizer):
r"""Implements stochastic gradient descent (optionally with momentum).
Nesterov momentum is based on the formula from
`On the importance of initialization and momentum in deep learning`__.
A... |
3d9d41c65eaaa2282e849334a54cbe8b3baea6f6119b0173c7e6a76ea80cdd7b | Python | 4,563 | 126 | import gzip
import xml.etree.ElementTree as ET
import numpy as np
from ..utils.orbutils import FracPolyRGD, ExpRGD, GridFunc, grid_overlap
class gpaw_psp:
def __init__(self, filename):
if filename.endswith('.gz'):
with gzip.open(filename) as f:
source = f.read()
else:
... |
4a14d9c806aafcfcf0c15b9708e18daeecd2d8997e2443290292c3ca479c8cf9 | Python | 4,563 | 120 | import sys, math
sys.path.append("../../../../../bin/")
from pybioshell.core.data.basic import Vec3
from pybioshell.core.data.io import Pdb
from pybioshell.std import vector_core_data_basic_Vec3
from pybioshell.core.calc.structural.transformations import *
from pybioshell.utils import LogManager
LogManager.INFO()
i... |
c7a3c63d54043b1130fc20cfb2752326f128f7aedfcd2e39372d318e532e9487 | Python | 4,563 | 145 | from scconfluence import model, unimodal
import anndata as ad
import numpy as np
import mudata as md
def create_synthetic_adata(n_obs, n_features, n_batch, dim_pca, obs_prefix=""):
"""
Create a synthetic AnnData object with the specified number of observations, features and batches.
:param n_obs: number o... |
67cbf46d547d8099926884a6cacd3435b1276a4f14731cda661b3db5c4693d24 | Python | 4,564 | 150 | import csv
import os
from typing import Dict, Optional, Union
import matplotlib.pyplot as plt
import numpy as np
import torch
from torch.utils.tensorboard import SummaryWriter
class CallbackSaveImage(object):
def __init__(
self, dataset, model, device, output_dir, num_sample=4, vmin=-2, vmax=6
):
... |
d1db5049fd8a888f119abf68d67105590c7bb837beca0376934d8ed074609f0b | Python | 4,564 | 129 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
1d4311f98187aa83ecd93107875e804ba7951cf641f0a23f1f53319a17556a7a | Python | 4,566 | 105 | # importing libraries
import tensorflow as tf
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras import Sequential
from tensorflow.keras.layers import Conv2D, MaxPooling2D
from tensorflow.keras.layers import Activation, Dropout, Flatten, Dense
from tensorflow.keras import backend ... |
0da010a895cae970cbbbfcf1fc95d7ffe6b6313b07415adcd7f920bb2e7b53eb | Python | 4,567 | 113 | from .cave import CaveDataset
from .ds_utils import (
BANC_CAVE_DATASTACK,
_load_live_banc_annotations,
_load_cave_banc_annotations,
)
__all__ = ["BANC"]
class BANC(CaveDataset):
"""Brain-and-Nerve-cord dataset.
Parameters
----------
label : str
A label used f... |
f0ce4e4734cca58fd6919603888b57eb3c15ec33c27a15479a04700eebdc2ec7 | Python | 4,567 | 112 | """
Utility functions for HED command-line scripts.
This module provides common functionality used across multiple HED scripts,
including logging configuration and argument handling.
"""
import json
import logging
import sys
from hed import __version__
from hed.errors import ErrorHandler, get_printable_issue_string,... |
07d47540a6aafd3c911bc091ce75fddb8b1a6fb816367ef946ce99bce510532f | Python | 4,568 | 125 | # Node-group asset "oxDNA Recover Vectors" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_... |
b83e8e1ebc4dfbc0dfc26ca523cd1605aac3bd4bc8be11a0360fec1090b62e62 | Python | 4,568 | 151 | """Euclidean layers."""
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
def get_dim_act(args):
"""
Helper function to get dimension and activation at every layer.
:param args:
:return:
... |
bd951aab5b8dfb8db65453d9ef285e09b3f077a3cc525cfd38de66277d2a9862 | Python | 4,569 | 156 | """Core recipes for the tblite code."""
from __future__ import annotations
from importlib.util import find_spec
from typing import TYPE_CHECKING
from monty.dev import requires
from quacc import job
from quacc.runners.ase import Runner
from quacc.schemas.ase import Summarize, VibSummarize
from quacc.utils.dicts impo... |
7a6787255637fe2aab61ab60b3fde2bd4eec320154c37d5cfff561abfe10d37a | Python | 4,570 | 109 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
3298924563ce2dfedc3f3fba26a5116bfdacd9d98c8099399e3fe8ed8caa4373 | Python | 4,571 | 76 | import warnings
warnings.simplefilter('ignore')
import numpy as np
import nibabel as nib
import matplotlib.pyplot as plt
import os
import subprocess
sub=['sub-010005' , 'sub-010009' , 'sub-010011' , 'sub-010014' , 'sub-010015' , 'sub-010016' , 'sub-010017' , 'sub-010018' , 'sub-010020' , 'sub-010021' , 'sub-010022... |
56a78e303263faf88a2e1ad0a914d411df0120d8581599f0400732d7e72fd79e | Python | 4,571 | 134 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
a898f3683f58ac6f481c3c19e9ebceaa527a06f842cb700f82112529f9bccc0f | Python | 4,571 | 108 | import pandas as pd
import os
from tqdm import tqdm
from tabulate import tabulate
import matplotlib.pyplot as plt
from matplotlib.lines import Line2D
import seaborn as sns
from src.utils import map_to_score_grid
from constants import N_ITEMS, DATA_DIR
from src.preprocessing2.process_ratings import merge_rating_file... |
3f15536a06215a856fe7a5e76628eb45a14e97af5cf922a90fd3975fbfe91fa4 | Python | 4,572 | 123 | import os
import tempfile
import pandas as pd
from tests.mock_data import MockTrainingData, MockCuppaClassifier, MockCvOutput
from cuppa.classifier.cuppa_classifier import CuppaClassifier
from cuppa.runners.prediction_runner import PredictionRunner
from cuppa.runners.training_runner import TrainingRunner
from cuppa.cl... |
970eb0b9b0f47a174b241ab7621bd3a8bb6b8635a01e6239c1b2e809dcecec31 | Python | 4,573 | 146 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 3 17:33:29 2024
@author: felipe
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal as signal
def plotStep(system,t,ax='None',show=False):
"""
Plot the step response of an LTI system (discrete time)
Parameters... |
9193dee745867657321e9656b213db9493016fdd370d3a20fab79a89b868736b | Python | 4,574 | 123 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: carlos atico ariza
"""
import os
import re
import tensorflow as tf
# import tflite_runtime.interpreter as tflite
import numpy as np
import pandas as pd
import sys
def tflite_img_class(image_dir=[], prediction_csv='malaria.csv',
trained_m... |
a2486eb86ade69f6d34a7e43620d5fa34f16ae89c2895fa42ef822471375d1f2 | Python | 4,574 | 119 | import os
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from datasets.SequenceDatasets import dataset
from datasets.sequence_aug import *
from tqdm import tqdm
#Digital data was collected at 50,000 samples per second
signal_size = 1024
#Three working conditi... |
b4da7ff0dd05f7171494f059c4ecc8a404783deecca29f7a522a6eb290cbc799 | Python | 4,574 | 142 | """Interactive Molecular Dynamics (IMD) streaming trajectory support.
Provides support for real-time trajectory streaming from molecular dynamics
simulations using the IMD protocol via MDAnalysis and imdclient.
"""
import logging
from pathlib import Path
from typing import Optional
import MDAnalysis as mda
from ..bas... |
5c1a09fe79448f33653a3f3df89582a3ee4b4786b54442d0843be84fa18e4ae3 | Python | 4,575 | 129 | """
Simulate effect of increased LTD
"""
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from src.constants import pink, green
from src import constants
from src.constants import lr, control_th, increased_th, min_th, max_th, Tplasticity
from src.constants import fi... |
681c080285a606bb2682eb418aaa6e2ce1839f9d2bc93875572605b06989b177 | Python | 4,575 | 141 | from pathlib import Path
from typing import Literal
import cocotb
import hypothesis
import pytest
import torch
import torch.nn as nn
from cocotb.clock import Clock
from cocotb.types import LogicArray
from hypothesis import strategies
from hypothesis.strategies import DataObject
from elasticai.creator import ir
from e... |
1f0fabdbdc8f51a4637d0ad343bac02ca93204f34a083a919829f3a453854091 | Python | 4,576 | 112 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
9d938b774f90425fe31ef53206b5f26ee715c007e1aff69abd8920ac61a01a25 | Python | 4,576 | 114 | import matplotlib.pyplot as plt
import numpy as np
from matplotlib.patches import Wedge
from matplotlib.collections import PatchCollection
def wedge_plot(ax, data, index, data_label, num_regions, num_zones, color_palette, start_degree, end_degree, show_index=True):
"""
Generate a wedge plot with data, index, ... |
30841f87b0e8f3d36412f4ee16b80d392c21fc640868d7b2f80136e76422eb41 | Python | 4,577 | 133 | from pyclamp.gui.pyplot import *
from pyclamp.dsp.fpfunc import *
import pyclamp.gui.pyqtplot as pq
class pywanim (pq.anim):
roi = None
roispec = None
fps = None
rcf = 1.
ind = None
Ind = None
Act = None
Anim = None
_i = None
def __init__(self, _obj = None):
self.setObj(_obj)
self.setRes()
... |
38acf213773b666e511df0c0f28b18f5c1bd3b860c6c505faf5a04264a8f5415 | Python | 4,577 | 88 | # 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
#
# ht... |
d2e9e9612a78d59b1a996f5889c791b4ffb43f71c7290f2d36411a9c0f10bae4 | Python | 4,577 | 111 | """
DeepLabCut2.0 Toolbox (deeplabcut.org)
copyright A. & M. Mathis Labs
https://github.com/AlexEMG/DeepLabCut
Please see AUTHORS for contributors.
https://github.com/AlexEMG/DeepLabCut/blob/master/AUTHORS
Licensed under GNU Lesser General Public License v3.0
"""
import os
#import yaml
from pathlib import Path
#impor... |
306bf6d3ee4feeb911f31a2b6624588fef50e723768b6c02ee2781a20469468e | Python | 4,578 | 106 | from bioimageio.spec import save_bioimageio_package
from bioimageio.spec import load_description
# import bioimageio.spec
from pathlib import Path
from ruamel.yaml import YAML
import tempfile
import zipfile
import re
import os
def export_bmz_notebook(notebook_id, output_path):
zerocostdl4mic_path = os.path.abspa... |
57a50611d54db8fec344042b61111c1aace03d5537e13395639ca99da74ebc6c | Python | 4,579 | 112 | # regtools/tests/test_batch_2d_points.py
import os
import numpy as np
import pandas as pd
import pytest
from regtools.registration.gui.batch_2d_model import BatchRow, BatchConfig
from regtools.registration.gui.batch_2d_points import (
resolve_points_per_image,
resolve_points_single_csv,
points_ro... |
32193bbf869a2018f3993ebbd575a2a6913d01a13c2346c923b927d59067bac3 | Python | 4,580 | 138 | # -*- coding: utf-8 -*-
import logging
import tensorflow as tf
import tensorflow_probability as tfp
from tfsnippet.distributions import Distribution
class TfpDistribution(Distribution):
"""
A wrapper class for `tfp.distributions.Distribution`
"""
@property
def is_continuous(self):
return... |
87be8480616cab47dd9c4dc2c54fa8caae3ca20722d3fd107f926878d1a00b50 | Python | 4,581 | 115 | from predictor import Predictor, SingleNail
from utils import *
import cv2
import random as rng
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from PIL import Image
# variabili da impostare
SOGLIA_AREA = 100
ITER_ERODE = 5
SOGLIA_REGIONE_UNGHIA = 0.95
class MyProcessing:
def __init__(self)... |
94bb1e963e9b1b00300828995cb8f2328559084b5323565fab043c59af1908f3 | Python | 4,581 | 135 | import json
import torch
import tqdm
import numpy as np
import torch.nn as nn
from pathlib import Path
from typing import Any
from ..prixfixe import Trainer, PrixFixeNet, DataProcessor, DEFAULT_METRICS
from .dataprocessor import UnlockDNADataProcessor
from .add_blocks import SequenceMaskLayer
class ScheduledOptim():
... |
b130cdc41ac64e5ba7ea19525ac9b80d6dc4ee5f257b094314b4b609a7d6a6b1 | Python | 4,581 | 127 | """Pure-Python status snapshot for the config menu GUI.
No Qt or matplotlib dependency - safe to import from tests and from
the matplotlib viewer. GUI code consumes these dataclasses/dicts.
"""
import json
import os
import platform
import re
import shutil
import subprocess
import sys
from dataclasses imp... |
78443a50341fdef05c84e6bda5f7c699d1c4e36f873061eef10fecc304b2d788 | Python | 4,584 | 109 | r"""Test ChemDoodle JSON format using the OpenBabel Python bindings
On Windows or Linux, you can run these tests at the commandline
in the build folder with:
"C:\Program Files\CMake 2.6\bin\ctest.exe" -C CTestTestfile.cmake
-R pybindtest -VV
You could also "chdir" into build... |
7feac4f5b4501b0dcde672c50d92e497b0f04ab5edeafc0e7c690bb9bf3d9fb6 | Python | 4,585 | 122 | """
Unit tests for regtools/cell_counting_legacy/points_converter.py
Covers:
- read_legacy_txt
- convert_txt_to_napari_csv
"""
import os
import tempfile
import shutil
import numpy as np
import pandas as pd
import pytest
DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
# ==========... |
c2441b9333a2adc36df2bd974f7c1caf094966a7d7c941ad90e417921059a2d4 | Python | 4,586 | 162 | # -*- coding: utf-8 -*-
#
# Helper functions for frontend test design
#
# The `run_` function signatures take a callable,
# the `method_call`, as 1st argument
#
# 3rd party imports
import itertools
import numpy as np
import os
import matplotlib.pyplot as plt
from syncopy.shared.errors import SPYValueError, SPYTypeErro... |
fe6a83c4c2a7aa2c1263a92c34ce19ffde5c3b6ae13e5a9caba8ef3bf96f97dd | Python | 4,586 | 164 | import torch
import math
from segm.utils.logger import MetricLogger
from segm.metrics import gather_data, compute_metrics
from segm.model import utils
from segm.data.utils import IGNORE_LABEL
import segm.utils.torch as ptu
import gc
import numpy as np
import torch.nn as nn
import torch.optim as optim
import matplotlib... |
0b92d1fdbcacce62a769286c7ddfc1e6c4f20ac41338c9307df564c8a038ece4 | Python | 4,588 | 1 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import scipy.sparse as sparse
class ConnectedGroups:
"""
Flexible class that gets string based definitions of neuron groups and connections (between layers)
as input and creates the net
"""
def __init__(self, net, topology, params, ... |
aebf23f65ac23d17b4b15e66bfec557f6c0d21dd2fce9ea220977572a3a4d0fe | Python | 4,588 | 190 | # Node group ".MN_peptide_chi_values" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# Shared by several assets, which import it; not an asset itself.
# _build_group() is the source of truth: the docstring, __init__ and accessors are r... |
25c7802b2c1ebbbbe701518e5b4643803e0f53f357f1bcb401ffb5bada2bea17 | Python | 4,589 | 130 | import random
import unittest
import torch.nn as nn
import torch
from torch.utils.data import Dataset
from torch.utils.data.dataloader import DataLoader
from torcheeg.trainers import CWGANGPTrainer, WGANGPTrainer
from torcheeg.models import BGenerator, BDiscriminator, BCGenerator, BCDiscriminator
class DummyDataset(D... |
31a7ee6e2b5b823394f7ea762341140631ce9d8b9869ee917df5ce5f36714c33 | Python | 4,590 | 128 | import pandas
import numpy as np
from merlin.core import analysistask
from merlin.util import spatialfeature
class PartitionBarcodes(analysistask.ParallelAnalysisTask):
"""
An analysis task that assigns RNAs and sequential signals to cells
based on the boundaries determined during the segment task.
"... |
59c02c886e67a44d51ed5831f894870299f65be27b65e6448e024f4f26d6f418 | Python | 4,590 | 133 | """
Cell detection and counting utilities.
Consolidated from cellAnalysis/cell_detection.py and gui/gui_shared.py
"""
import numpy as np
import scipy
import scipy.ndimage
import cv2
from skimage.feature import peak_local_max
from skimage.segmentation import watershed
from .io.tiff_io import read_tif_sec... |
4f0d6616dfa369d09f1536a0f70d35d8fc8b87d16e23b37104b2e0591bd96366 | Python | 4,591 | 148 | from __future__ import annotations
import pytest
torch = pytest.importorskip("torch")
from importlib.util import find_spec
import numpy as np
from ase.build import bulk
from ase.md.langevin import Langevin
from ase.units import fs
from quacc.recipes.mlip.md import md_job
libraries = []
if has_matcalc := find_spec... |
bbeb14e3766c859777a53c244be65659e547d2b317c19704fa6914899ecc4bed | Python | 4,591 | 140 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
6931f5b4d379aea5e1e81e6e3ead6443850b3e3046de32c31c1a702ad5eefcda | Python | 4,593 | 117 | '''
Description:
Basic neural networks.
Author:
Jiaqi Zhang <jiaqi_zhang2@brown.edu>
'''
import torch.nn as nn
import torch
# ===========================================
# Dictionary of activation functions
ACT_FUNC_MAP = {
"none": nn.Identity(),
"sigmoid": nn.Sigmoid(),
"tanh": nn.Tanh(),
"so... |
5b83d10ec11c861b7aad55c17946a2129b114325061f4918ed262c9f035650cb | Python | 4,594 | 107 | #!/usr/bin/env python
# coding: utf-8
import argparse
import pandas as pd
import random
import numpy as np
from keras import models, layers, regularizers
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
# Set up argument parser
parser = argparse.ArgumentParser(description="Ke... |
0cc00be002907aeb71012c568a277fac8c1974b4d12eb506a842280f1cfd2945 | Python | 4,595 | 119 | import os
from os import path
import sys
d = path.dirname(__file__)
parent_path = os.path.dirname(d)
sys.path.append(parent_path)
from BDNN_Model import BBP_Model
from BDNN_Model_Wrapper import BBP_Model_Wrapper
from Dataset.mydataset import Dataset
import torch
from Dataset.Environment import Environmen... |
17151bc3fc425d0018a2fea44d2597596e0c119a585152443a2458e4ba3bf102 | Python | 4,595 | 124 | import numpy as np
import h5py
from ..constants import hartree2ev
from ..io.bgwio import bgw_vsc
from .aodata import AOData
'''
This module implements several functions needed by real-space construction of AO Hamiltonian.
This includes reading local potentials, reading nonlocal part of pseudopotentials, and construct... |
fd4b9a18494288e5da0ca9be6615cf4673489a2b2c411d52fab3454888f74d55 | Python | 4,596 | 121 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2024 Clinic for Diagnositic and Interventional Radiology, University Hospital Bonn, 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 ... |
0835cc928d959df487c20de14341ab17ad9e4fe07bf469f0f5546f73f0b2dfc3 | Python | 4,597 | 97 | from ovito.io import import_file, export_file
from ovito.modifiers import LoadTrajectoryModifier
from ovito.modifiers import ClusterAnalysisModifier
from ovito.modifiers import UnwrapTrajectoriesModifier
from ovito.modifiers import CalculateDisplacementsModifier
from ovito.modifiers import SelectTypeModifier
from ovito... |
b335fe6a6841220eac8960d9376e12f3e42978eb2927759d7475b6edb057234e | Python | 4,597 | 150 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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,... |
c9c858a77e5f5c50a1f0b0aff1d208e436acb13646d0e3e93905637105286f9d | Python | 4,597 | 109 | # Helper functions for analyzing network gradients and comparing
# alignment between networks.
import numpy as np
import torch
from torch.func import vmap, jacrev
from torchmetrics.functional import pairwise_cosine_similarity
# local imports
from .helpers import apply_to_layers
def compute_jacobian(net, images: torch.... |
21bb68f4c34b1176ae7d69ab7a6be6315cea1410559deb8165e2babd2f8ee2ea | Python | 4,598 | 144 | import json
import sys
import os
import datetime
import numpy as np
from shutil import copyfile
import SimpleITK as sitk
from src.utils import file_utils as futils
from src.utils import sitk_utils as sutils
def get_paths(dir, extensions=list()):
paths = list()
files = os.listdir(dir)
... |
bba2f99c59037d8c5d374363db930410239bbf7d7dc02fbaadebd7122d274c12 | Python | 4,598 | 103 | import os.path as op
import numpy as np
import mne
from params import BIDS_ROOT as bids_root
from params import SUBJECTS as subjects
from utils import load_raw, load_df, laplacian_reference
def compute_R2(psd1, psd2):
psd = np.concatenate([psd1, psd2], axis=0)
n1, n2 = psd1.shape[0], psd2.shape[0]
rati... |
dc4d75f103580a27d3248dfd42747e63de377ff0db9742d5c6d87a1ab13bb498 | Python | 4,598 | 119 | # Copyright (c) 2020, Ko Sugawara
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and t... |
da1f45bd468427317e65bab775c59abfc18931ed13e087ffb70d69d9fdfab662 | Python | 4,599 | 108 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Aug 9 07:09:45 2022
@author: heavens
"""
import os
import csv
import toml
import itertools
from tqdm import tqdm
import numpy as np
class Profiler(object):
def __init__(self,data_f, config):
self.data_f = data_f
print("Loading chu... |
eed54cf25ce6ab99280a78594772fc2f06add654c941d25b30035493a949d0bf | Python | 4,599 | 123 | #
# MIT License
#
# Copyright (c) 2022 GT4SD team
#
# 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,... |
48c9e4118082e019bc563992364aad808ca6bea78fd0e01028621aec6efb8648 | Python | 4,600 | 189 | # This file is autogenerated by the command `make fix-copies`, do not edit.
from ..file_utils import requires_backends
class FlaxPreTrainedModel:
def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"])
@classmethod
def from_pretrained(self, *args, **kwargs):
requires_backen... |
5bd03f1c02be9c1edbd720f817f059e1d5c23d78234f88e4c0bc990942dd90a9 | Python | 4,600 | 155 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
cdf7b7b66c09df19c9feb40921b70f314ceb30b0d374a6a4f2e39d0f729e1bd9 | Python | 4,600 | 191 | #!/usr/bin/env python
# coding: utf-8
# ## Analysis of stratified drug response
# In[1]:
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import upsetplot as up
import pancancer_evaluation.config as cfg
import pancancer_evaluation.utilities.analysis... |
25750e943cdf840e4d05c28354b6b831fde02bc70f8456fd97aae70a7f3ef141 | Python | 4,601 | 131 | import logging
import tempfile
import time
from pathlib import Path
from zipfile import ZipFile
import pooch
import requests
from rich.progress import Progress, TaskID
logger = logging.getLogger(__name__)
pooch.get_logger().setLevel(logging.WARNING)
# Transient network failures that are worth retrying.
# ``urllib.er... |
df72588a8a68399de6c679b19910f7ae2de6741439669efba8ad2564fb535a61 | Python | 4,601 | 126 | import numpy as np
import pandas as pd
import scipy.sparse
from pandas import CategoricalDtype
from cirrocumulus.data_processing import handle_data
from cirrocumulus.embedding_aggregator import EmbeddingAggregator
def create_df(test_data, measures, dimensions, basis):
df = pd.DataFrame(test_data[:, measures].X.t... |
8a16cde334a8a34dd692689cb45b7a6ae3410aa06d68ee8a941d3d7015ac927f | Python | 4,602 | 113 | '''Preprocess events from the presentation logs to the BIDS events file for the
nback task.
Parameters
----------
path : str
path where the raw data is stored
savepath : str
BIDS folder
'''
import os, sys
import re
import pandas as pd
from glob import glob
path = '/m/cs/... |
0464da490af1990417e97d30e66aca81091881640fb334f752640970f5b310c7 | Python | 4,603 | 126 | import torch
import torchvision.transforms as transforms
import numpy as np
import cv2
from utils.ddfa import ToTensor, Normalize
from model_building import SynergyNet
from utils.inference import crop_img, predict_denseVert
import argparse
import torch.backends.cudnn as cudnn
cudnn.benchmark = True
import os
import os.... |
f9f933bc8fd87e8a6b31beaafe012677f6c85897f25b576b78172e4983ac6252 | Python | 4,603 | 146 | #!/usr/bin/env python
#******************************************
#
# SHARC Program Suite
#
# Copyright (c) 2023 University of Vienna
#
# This file is part of SHARC.
#
# SHARC is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
#... |
8597f825b3fabdad5f1673380db138ef33e26420b4607d2dda80d75781c45096 | Python | 4,604 | 131 | import glob
import os
import subprocess
from .ghdl_report_parsing import parse_report
class SimulationError(Exception):
pass
class GHDLSimulator:
"""Run a simulation tool for a given `top_design` and save whatever is written to stdout
for subsequent inspection.
This runner uses the GHDL tool.
... |
4aff9bf49b43e417aa1d223def74e04ee00543438b402bb642786d72ea8562d5 | Python | 4,605 | 152 | from typing import Dict, List, Union
import numpy as np
from ..base_transform import LabelTransform
class Binary(LabelTransform):
r'''
Binarize the label according to a certain threshold. Labels larger than the threshold are set to 1, and labels smaller than the threshold are set to 0.
.. code-bloc... |
4865d1a54e12d71d3f94ec4e2d879ecf48478a8266052fe10064a6e66a9e789f | Python | 4,607 | 125 | #
# Copyright Bradley Lowekamp
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0.txt
#
# Unless required by applicable law or agreed ... |
76d60fb8f8813d52ecd4bf61d6be848bb5fb8bdb5e061bd78e53ade97870e14b | Python | 4,607 | 125 | """Regenerate ICI reference data with R's survival package (no R needed by pytest)."""
import json
import subprocess
from pathlib import Path
import numpy as np
# RCS is the truncated-power basis from Hmisc::rcspline.eval, with explicit
# percentile knots. Supplying knots avoids Hmisc's small-sample/tie heuristics.
... |
19b31b4643614397a3b8efb65ee92aa439c1f1af57c285c2f50073515d28d061 | Python | 4,608 | 133 | # coding=utf-8
# Copyright 2026 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
1dea902a67e6870486e43b8843957566cd64924bce3d6ccb14dbc9de65c83664 | Python | 4,608 | 163 | import numpy as np
import numpy.testing as npt
import petsc4py
import pytest
from mpi4py import MPI
from scipy.sparse import coo_matrix
from astrovascpy.scipy_petsc_conversions import (
PETScMat2coo,
PETScVec2array,
array2PETScVec,
coomatrix2PETScMat,
distribute_array,
)
# pip install pytest-mpi
#... |
2d4f1db2d6b82030b64525e19f90b41db2f48d5646000f85f6769c442ff1224a | Python | 4,608 | 100 | from typing import Optional, Union, List
from segmentation_models_pytorch.encoders import get_encoder
from segmentation_models_pytorch.base import (
SegmentationModel,
SegmentationHead,
ClassificationHead,
)
from .decoder import MAnetDecoder
class MAnet(SegmentationModel):
"""MAnet_ : Multi-scale At... |
51e9e63853070178746d9adb8ec0da63b05b1a8b25a8e33da52f2655580a6ea0 | Python | 4,608 | 121 | # -*- coding: utf-8 -*-
"""
"""
import os
from nipype import logging
from nipype.interfaces.base import (
TraitedSpec,
File,
traits,
Directory,
BaseInterfaceInputSpec,
BaseInterface
)
__docformat__ = "restructuredtext"
iflogger = logging.getLogger("nipype.interface")
class ParseScannerDi... |
25e9e40e7ca2ec1c8eb49e75394e8180601af88d7ef646580b32cb4cd4e3b5f2 | Python | 4,609 | 143 | """Class for creating a tkinter-based progress bar in an external window."""
import tkinter
from tkinter import ttk
class ProgressBar:
"""Class for generating a tkinter-based progress bar shown in an external
window.
PARAMETERS
----------
n_steps : int
- The total number of steps in the pr... |
8555bd1b4acee8b6289c1ed71ad96452ba3111c101ed0060022fcc89a8aa14f4 | Python | 4,609 | 115 | import functools
from .models import resnet as rn
from .models import resnext as rx
from .models import senet as sn
from .models import densenet as dn
from .models import vgg16 as vgg16
from .models import vgg19 as vgg19
from .models import inception_resnet_v2 as irv2
from .models import inception_v3 as iv3
from .mode... |
da86e4c57dc63767759c388f91cd4635ee0527a49faba14620c9d936393595d9 | Python | 4,609 | 122 | # Copyright 2022 HYBRID Team INCIA, UMR5287, CNRS, Université de Bordeaux
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required b... |
6a0db5aaf65e3902a04cc0138aba8235e63de185d23d72b256e1bd5e01f93fc7 | Python | 4,611 | 115 | from elasticai.creator.file_generation.savable import Path
from elasticai.creator.file_generation.template import (
InProjectTemplate,
module_to_package,
)
from elasticai.creator.vhdl.auto_wire_protocols.port_definitions import create_port
from elasticai.creator.vhdl.code_generation.addressable import calculate... |
dc6b790f999d7225e430304c69c94bdc3b1e03cf723f2590f713406b1d73ccb5 | Python | 4,611 | 131 |
import os
from argparse import ArgumentParser
import yaml
from pytorch_lightning import Trainer
from ray import tune
from ray.tune import CLIReporter
from ray.tune import Stopper
from ray.tune.integration.pytorch_lightning import TuneReportCheckpointCallback
from ray.tune.schedulers import ASHAScheduler
from ray.tun... |
7410e427bfc9e1119da0d4e5dff0eca7dbed6c52f897bcafe6778cf024757790 | Python | 4,614 | 127 | import torch
import torchvision.transforms as transforms
import numpy as np
import cv2
from utils.ddfa import ToTensor, Normalize
from model_building import SynergyNet
from utils.inference import crop_img, predict_denseVert
import argparse
import torch.backends.cudnn as cudnn
cudnn.benchmark = True
import os
import os.... |
b031428c98beb5dfbad07f21ad16d97bc55c041c2ed0e9b6d52ac9149da1a9f3 | Python | 4,614 | 108 | import argparse
import copy
import os
import shutil
import os
import sys
args = argparse.Namespace(
inputlen = 2114,
outputlen = 1000,
ibam="chrombpnet_tutorial/data/downloads/merged.bam",
data_type="ATAC",
genome="chrombpnet_tutorial/data/downloads/hg38.fa",
peaks = "chrombpnet_tutorial/data/p... |
ce8b34476c0405ee3f3997afd6cf0c3c368cad11d63e2b1a951f8f4d37c5107e | Python | 4,614 | 138 | # Node-group asset "Transform Accumulate" (GeometryNodeTree), dumped by nodebpy.assets.dump_library.
# Rebuild the library with nodebpy.assets.build_library (nodebpy build).
# _build_group() is the source of truth: the docstring, __init__ and accessors are regenerated from it on the next dump.
from typing import TYPE_C... |
14a5ea6bcb2fe546405b5c8f78303932ed55c960b5dcbb85c9840f50f155a313 | Python | 4,615 | 66 | """SHIU_LATERAL_EXCITATION.py 2026-09-24. Pre-registration: 04-NOTES/PREREG-2026-09-24d-SHIU-LATERAL-EXCITATION.md
(+ Addendum 1: v783 >= 5-synapse network). Output 06-OUTPUT/shiu_lateral_excitation.txt, shiu_lateral_excitation.csv"""
import sys, os, re, time
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)... |
330e8b260daef9c29fee9396d9f1027630dc0481df8df5a697f011617d1a6a82 | Python | 4,615 | 157 | """Tests for cog.types module."""
import io
from dataclasses import is_dataclass
from cog import (
AsyncConcatenateIterator,
ConcatenateIterator,
File,
Path,
Secret,
URLFile,
streaming,
)
class TestSecret:
"""Tests for Secret type."""
def test_secret_creation(self) -> None:
... |
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