sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
257777e88c74e8ec0ed3e2960504963cdaef96b1820b9d9688c347b0f62a9d21 | Python | 1,200 | 38 | import pytest
import numpy as np
from deepface.modules import verification as target
@pytest.mark.parametrize("dim", [2, 7, 8, 128])
@pytest.mark.parametrize("sign", [1, -1])
def test_single_parallel_vectors(dim, sign):
a = np.ones(dim, dtype=np.float32)
with np.errstate(invalid="raise"):
actual = tar... |
3dbb73c064f151a3c029c25074c7db556677e436c601eb548663df100856616c | Python | 1,200 | 30 | # built-in dependencies
from typing import Optional
# project dependencies
from deepface import DeepFace
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=too-few-public-methods
class ModelService:
def __init__(
self,
face_recognition_models: Optional[str] = None,
... |
48f97c83792618255b9accf50e5db489a6fd99681e3269a652519605716e181a | Python | 1,200 | 31 | import logging
from agent.data.sql.sql_mgmt import get_connection, update_text_field
logging.basicConfig(format='%(levelname)s : %(message)s', level=logging.INFO)
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
TABLE = "annotate_sentence"
def do_preliminary_fc_classification(external=False):
... |
94bb408bedf55f09996f3b26e6a49bb4b382ba936b8162fb516ec4bf87681cd5 | Python | 1,200 | 46 | # __serve_example_begin__
import json
import tempfile
from ray import serve
from ray.serve.config import AutoscalingConfig, AutoscalingPolicy
# Create a JSON file with the initial target replica count.
# In production this file would be written by an external system.
scaling_file = tempfile.NamedTemporaryFile(
mo... |
eeb2b3c254d122fd1c56d7e6fc67fa9ef0c7c509742f1db4b3624c3140096f21 | Python | 1,200 | 41 | #!/usr/bin/env python
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... |
bb3a1d30ffbdaf96642c940b9465d2e52fd52ab24db900f125e083d2014dc054 | Python | 1,201 | 43 | """Main module of ydata-profiling.
.. include:: ../../README.md
"""
# ignore numba warnings
import warnings # isort:skip # noqa
import importlib.util # isort:skip # noqa
from warnings import warn
from data_profiling.compare_reports import compare # isort:skip # noqa
from data_profiling.controller import pandas_de... |
86b438650280eb64e469530cf077a59a881402197a5eb8056b77957b0e8a8f06 | Python | 1,203 | 43 | import json
import os
import subprocess
import numpy as np
import torch
def get_sample_weights(target, class_weight):
return torch.Tensor([class_weight[t.int()] for t in target])
def correct_negative_edges(target):
return target - 1, [i for i, t in enumerate(target) if t.item() != 0]
def ... |
f946e6b91a084c72fb44bde99c8cb6ec69e29f070e3148739a2e38d769bcc2d4 | Python | 1,203 | 42 | from Prediction import ddpred
from Para import parameter
import numpy as np
import torch
import os
trainday = 30
target = 'pHVAC_estimation'
zones = 'Single'
par = parameter()
par.get_para(tar=target, zone=zones)
ddp = ddpred()
adj = np.array([[1]]).astype('float32')
ddp.data_ready(num_zone=1,
... |
aaf7fbd2e676f9d08836b8c3420bfb1929eeae74ad1ae1af81aab698c7c83c44 | Python | 1,204 | 24 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
101525e3b6019b23300a4ca4e4c5deb49213df6fc879967c80c4f0ed26de9aa7 | Python | 1,205 | 35 | """High level manager for refining and summarizing project scope."""
from __future__ import annotations
from typing import List
from .brief import BriefGenerator, ProjectBrief
from .clarifier import Clarifier
class ScopeManager:
"""Coordinate clarification and brief generation steps."""
def __init__(self,... |
d4ab2bab983657a8b6eb762b29d57d1d83d5788911f6a01bd05477daa8cb0f6d | Python | 1,206 | 43 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import argparse
from fairchem.core.models.equiformer_v2.eqv2_to_eqv2_hydra import (
convert_checkp... |
fef72a096937b255941705a624d6894845f8099f860e109e9efddbfe685d9325 | Python | 1,206 | 22 | import sys
sys.path.insert(1,'../src_simulation/')
from sim_helper import sim_helper
if __name__ == '__main__':
sim_ = sim_helper(n_sim = 200, heritability_l = [0.8, 0.5, 0.25],
percent_causal_l = [0.1,0.3],
beta_var_l = [0.1], image_modality = None, random_seed ... |
2cdffa53c276906deffd6e96d773249877a364e3d9162201408d4bf53b0cb0e2 | Python | 1,207 | 34 | """Test AIR internal utilities (under ray.air._internal)."""
import os
import pytest
import ray
from ray.air._internal.filelock import RAY_LOCKFILE_DIR, TempFileLock
def test_temp_file_lock(tmp_path, monkeypatch):
"""Test that the directory where temp file locks are saved can be configured
via the env vari... |
88916221514a6c901488c4b89f30c5f4d3f5ea4327cc8eedf64cb789ca44e9ae | Python | 1,207 | 25 | from projectmetis.python.models.model_dataset import ModelDataset
class LearnerTrainer(object):
def __init__(self, model_ops_fn, model_pb):
"""
The initial state of the model for every other trainer instance is unique. Therefore,
we initialize the model once during the trainer object cons... |
5bd5e096b876c999a998cf42d11acbeec27687d1ebcdc7443879df5c24baf055 | Python | 1,208 | 51 | """This is the script for `ray clusterbenchmark`."""
import time
import numpy as np
import ray
from ray.cluster_utils import Cluster
def main():
cluster = Cluster(
initialize_head=True,
connect=True,
head_node_args={"object_store_memory": 20 * 1024 * 1024 * 1024, "num_cpus": 16},
)
... |
5e6671411aa80811935e7e7b9acb20b7309c34d842fa2fec5b1187e765eccc19 | Python | 1,208 | 42 | # -*- coding: utf-8 -*-
"""
Created on Mon Jun 3 14:00:28 2024
@author: jpv88
"""
from setuptools import setup
setup(
name='DCISIv',
version='0.1',
description='Decoding Cross-contamination using Inter-Spike-Interval violations',
url='https://github.com/economolab/DCISIv',
author='Jack Vince... |
c5da2565983adf3494344560b43c493dbb011301ac0192dddab71d07e41b20a4 | Python | 1,209 | 37 | """Find the number of volumes we acquired for long vs short ITI sessions"""
import nibabel as nb
import glob
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives'
SUBS = ['sub-05', 'sub-06', 'sub-07', 'sub-08', 'sub-09']
for sub in SUBS:
print('')
# =========================... |
f134fed15cb6ef0f02484b70110a53e6f1c609d21b77876c856742d023ee446d | Python | 1,210 | 37 | with open("/tmp/eLife_Metrics.tsv") as in_file:
in_file.readline()
image_dict = {}
for line in in_file:
line_items = line.split("\t")
path_parts = line_items[1].split("-")
image_unique_key = f"{path_parts[1]}____{path_parts[2]}"
image_version = path_parts[3]
if im... |
12e47c2f1d178b7fd63f16b42959a9567b0d40e468f340bb74a3d2e496e60649 | Python | 1,211 | 25 | import argparse
import torch
def parse_args():
parser = argparse.ArgumentParser()
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
parser.add_argument('--device', type=str, default=device)
parser.add_argument('--path', type=str,
default='C:\\Users\... |
d9063ca210f44b6bfe4e8510a56f851665dca2fd030b80f7d5536985244b0f01 | Python | 1,211 | 51 | # -*- coding: utf-8 -*-
"""
Created on Sat Jan 23 15:15:47 2016
@author: matt
"""
# show movement of a particular trajectory, time color coded
tra = traj[0,:,:]
x = plt.scatter(tra[:,1],tra[:,0],c = xs)
cbar = plt.colorbar(x)
cbar.set_label('Time (d)', rotation=90)
plt.show()
# zoom out to the entire image
x = plt.s... |
e037c192e692bf5e3bfea6786b5329fecf46ff73a6c9274cdd4a80a3adb43a88 | Python | 1,211 | 55 | from abc import ABCMeta, abstractmethod
class Env(object, metaclass=ABCMeta):
"""RL learning environment.
This serves a minimal interface for RL agents.
"""
@abstractmethod
def step(self, action):
raise NotImplementedError()
@abstractmethod
def reset(self):
raise NotImpl... |
451b090d80602150b64120702461579139c6e78d0f98fd57a456033db73c8d4e | Python | 1,212 | 27 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
6bda1a09422605d1eaac3f7681fa418342e37a16a25b5227839d1ad6bddccba1 | Python | 1,212 | 24 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
6bdaae809c217351c9fce47158d0aca35027978ef5daa3816d5ac026bbd12b4f | Python | 1,212 | 36 | import unittest
import torch
from rising.transforms.functional.channel import one_hot_batch
class TestChannel(unittest.TestCase):
def test_one_hot_batch_1dim(self):
inp = torch.tensor([0, 1, 2]).long()
outp = one_hot_batch(inp)
exp = torch.eye(3)
self.assertTrue((outp == exp).all... |
2bb0d2fc9b2d5065c41824b28924ac0f3ee654061a15c0efcee87c42a34351f6 | Python | 1,213 | 46 | """
test for the 'i_offset' parameter of the LIF neuron
"""
from spinnaker2 import snn, hardware, brian2_sim
def test_lif_curr_exp_i_offset():
params = {
"threshold":1.,
"alpha_decay":1.,
"i_offset":0.123,
"v_reset":0.0,
"reset":"reset_by_subtraction",
... |
8f78c12022d5d9dc9c7a827701bca36ec272225c1848006614217cd31b67c8f5 | Python | 1,213 | 22 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This library is fre... |
199ca5f62b865e707fc23b4ab10f04ba96216bb96afacda64abd92ab12adcede | Python | 1,214 | 52 | import os
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set_theme(style='whitegrid')
filename = os.path.splitext(os.path.basename(__file__))[0]
df = pd.read_csv('../data/paperdiff.csv',
index_col=1,
parse_dates=True,
)
df['Environment'] = df['Environment'].str.ca... |
d4a8ac0e2f9bf18648897017fb3fa4f22148e5981b9c9beecddd4c032eed60be | Python | 1,214 | 25 | import pandas as pd
file = "MetS_GWAS_MetS.csv"
df_ukb = pd.read_csv(file, sep=",", index_col=False)
df_ukb = df_ukb[['SNP', 'CHR', 'BP', 'A1', 'A2', 'MAF', 'est', 'SE', 'Pval_Estimate']]
n_init = len(df_ukb)
df_ukb = df_ukb[df_ukb['MAF'] > 0.01]
print("Number of SNPs dropped by MAF filter (> 0.01): {:,}".format(n_ini... |
0086b5ede44bc1a572e89a4363150bdbc5fb943b84c4eef965ff7628280875cb | Python | 1,215 | 40 | #!/usr/bin/env python3
import argparse
import nbformat
def convert_notebook(input_path: str, output_path: str) -> None:
"""
Read a Jupyter notebook and write a Python script.
Cells that load or autoreload extensions are ignored.
"""
nb = nbformat.read(input_path, as_version=4)
with open(output... |
5a2f46f0430645d5adc23dfe9752f7283431c1c8c694142728d7787b63cce572 | Python | 1,215 | 36 | import unittest
from spinnaker2.mla.mla_config import Conv2DConfig
class TestStride(unittest.TestCase):
def test_base(self):
c = Conv2DConfig()
# stride_x
for n in range(4):
c.set_stride_x(2**n)
self.assertEqual(c.stride_x_2_power_n, n)
self.assertEqua... |
236bb4e21ebe5769718852045aae4b2880c5b635b45507e70bc15e3b7c86738b | Python | 1,216 | 51 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Custom Exceptions for aihwkit."""
class AihwkitException(Exception):
"""Base class for exceptions related to aihwkit."""
class ModuleError(AihwkitExce... |
483e4d8e1217ae88b44a2767468337a284b0d45ec48c5d6e1cd69a02073a834e | Python | 1,216 | 34 | import pandas as pd
from sklearn.datasets import make_classification
from siapy.features import AutoSpectralIndicesClassification
from siapy.features.helpers import FeatureSelectorConfig
from siapy.features.spectral_indices import get_spectral_indices
# Create spectral-like data
X, y = make_classification(n_samples=3... |
ad8a1c17d60dcd043b7601e4d56100a453b083b2a5d4c8294bbefbea8185152e | Python | 1,216 | 49 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import pandas as pd
def explode(df, idx_cols, list_col):
"""
Explode a column of lists into one row per list element
"""
df = df.set_index(idx_cols)
df[list_col] = df[list_col].str.split(',')
df = df[list_col].apply(pd... |
dfe7aac15ab044bb325f025b6b1ca2f7c43de59af4f64d419c7cc47b67f20b5b | Python | 1,217 | 38 | from pathlib import Path
from siapy.entities import SpectralImageSet
# Set the path to the directory containing the data
# !! ADJUST THIS PATH TO YOUR DATA DIRECTORY !!
data_dir = "./docs/examples/data"
# Find all header and image files in the data directory
header_paths = sorted(Path(data_dir).rglob("*.hdr"))
image... |
6fee65398bc2bcc71dc3fd9c6145c36279b60cafa092130b01aac1750e6d83ec | Python | 1,218 | 42 | import numpy as np
import pandas as pd
from data_profiling.config import Settings
from data_profiling.visualisation.missing import (
plot_missing_bar,
plot_missing_heatmap,
plot_missing_matrix,
)
def missing_bar(config: Settings, df: pd.DataFrame) -> str:
notnull_counts = len(df) - df.isnull().sum()
... |
c26476933f7021f1d2abdac4d542fdf1947a000a994b6e6938f04887954f97a5 | Python | 1,220 | 34 | import unittest
import numpy as np
from neuron_morphology.features.layer.reference_layer_depths import \
ReferenceLayerDepths
class TestReferenceLayerDepths(unittest.TestCase):
def test_thickness(self):
depths = ReferenceLayerDepths(1, 2)
self.assertEqual(depths.thickness, 1)
def test_... |
31a3abbd72b5dd01d228bea772c346066fec5c79cb3ceef702f60b12f825e076 | Python | 1,221 | 38 | import torch
from torch.nn import Embedding, Linear, LeakyReLU, PReLU, Parameter
class NTD(torch.nn.Module):
def __init__(self, n_x, n_y, n_g, rank, random_state=1234567):
super().__init__()
torch.manual_seed(random_state)
# Define embedding layer along x, y, g modes
self.e... |
80a72b37379a65d85d11a9539c5a1bcab91a233886420497f76d00f969b2354d | Python | 1,221 | 41 | """
Flavours registry information
"""
from data_profiling.report.presentation.core import Root
from data_profiling.report.presentation.core.renderable import Renderable
_FLAVOUR_REGISTRY: dict = {}
def register_flavour(name: str, mapping: dict) -> None:
_FLAVOUR_REGISTRY[name] = mapping
def get_flavour_map... |
c9885254a4ac6bedd25b186991703f851b080cdddeec5c8bd5ccd15d23534982 | Python | 1,221 | 41 | import argparse
import numpy as np
from spiking_readout.dataset import SpikingDataset
from spiking_readout.readout import Readout
def predict(dataset_path, model_path, output_file=None):
# Load data
dataset = SpikingDataset.from_file(dataset_path)
# Assert data is not empty
empty_dataset = np.any([sa... |
4a3fb448ae613a19d621143fa44ba2762d69c73ac4da521abf05048b839fc5bb | Python | 1,222 | 45 | from Load_prediction import ddpred
from Para import parameter
import numpy as np
trainday = 30+30
zones = 'Single'
modes='Cooling'
par = parameter()
par.para_load(zone=zones)
ddp = ddpred()
adj = np.array([[1]]).astype('float32')
ddp.data_ready(num_zone=1,
enLen=par.paradic["encoLen"],
... |
07346088e696bb6bc87ec8ceb99a661fa1fa3265500f0b3dc0ca12b906191289 | Python | 1,223 | 38 | import inspect
import yaml
def pprint_dict(d):
"""
Pretty print a dictionary.
"""
print(yaml.dump(d, default_flow_style=False))
def print_help_for_function_arguments(func, arg_names=None, print_only_required=False):
"""
Prints the help text of arguments of the DeepDeWedge commmands.
"""... |
80366f9fc290fe950ad4e6b2ff16b92432a22463a7911f4931c0bc6c7eddc7da | Python | 1,223 | 43 | # 3rd parth dependencies
try:
from flask import Flask
from flask_cors import CORS
from dotenv import load_dotenv
except ImportError as import_err:
raise ImportError(
f"{import_err.name} is required to run the deepface api. "
'Please run `pip install "deepface[api]"` to install it.'
)... |
a13caa9a4beadc232e3c547b908ef357e434150fc485f7f5dbbc6d9568075aac | Python | 1,223 | 34 | import torch.nn as nn
from optuna import Trial, Study
from .base import BaseModelConfig
from argparse import Namespace, ArgumentParser
from nyumets.networks.nets.sttunet import STTUNet
class STTUNetConfig(BaseModelConfig):
model_name = "unet_stt"
def setup_search_space(self, trial: Trial, args: Namespace)... |
bb5617bb2515273f529b6c19274ef1c07ef11f3c00c63f973fe649e55bdf720b | Python | 1,223 | 26 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
f46cb6320ec492ec0ea4d521eda61dad8b6bd7089199c23bb12bc9f0a813aaf4 | Python | 1,223 | 66 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
import tempfile
import pytest
import yaml
from fairchem.core.common.utils import UniqueKeyLoader
@p... |
756f8cf35da3ebe7a1f4c5d5448341b222bab977f75400d1eb3dc0e9fdb70d77 | Python | 1,224 | 46 | import sys
import pytest
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
from ml4h.arguments import parse_args
from ml4h.test_utils import TMAPS as MOCK_TMAPS
from ml4h.test_utils import build_hdf5s
def pytest_configure(config):
pytest.N_TENSORS = 100
config.addinivalu... |
369d66bb8d85432ff331b6511aeb174649bb710267875482efaf15be7480fee4 | Python | 1,225 | 23 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
67681e4637546d6694141885b33d77ecee69bbfa075d56f6f1fa0f0608acd9e9 | Python | 1,225 | 37 | import logging
from ray._private.ray_constants import DEBUG_AUTOSCALING_STATUS_LEGACY
from ray.experimental.internal_kv import _internal_kv_initialized, _internal_kv_put
"""This file provides legacy support for the old info string in order to
ensure the dashboard's `api/cluster_status` does not break backwards
compat... |
dc6c7755974a7a7dc1ada103efbcbd133475da0e260331cdbbad1f8e676db321 | Python | 1,225 | 42 | import os
import click
from ci.ray_ci.tester_container import TesterContainer
from ci.ray_ci.utils import ci_init, logger
from ray_release.configs.global_config import get_global_config
@click.command()
@click.argument("team", required=True, type=str)
@click.argument("bazel_log_dir", required=True, type=str)
def m... |
2e33cd9e15b2b8be969d4af39870219b4abe1bb535e44c8884af5db3c3a6fc1c | Python | 1,226 | 39 | import os
try:
print('SlURM_JOB_ID',os.environ["SLURM_JOB_ID"])
except:
print("no slurm id")
import matplotlib
matplotlib.use('agg')
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import tensorflow as tf
import tensorflow.keras as K
import tables
import gc
import argparse
import scipy
t... |
4033e3169f7aadc0eb0a058d9352c0f8ed260495b3df2220715df8353217c4e6 | Python | 1,226 | 49 | import sys
import click
from ci.ray_ci.automation.docker_tags_lib import list_image_tags
from ci.ray_ci.docker_container import (
ARCHITECTURES_RAY,
ARCHITECTURES_RAY_LLM,
ARCHITECTURES_RAY_ML,
PLATFORMS_RAY,
PLATFORMS_RAY_LLM,
PLATFORMS_RAY_ML,
PYTHON_VERSIONS_RAY,
PYTHON_VERSIONS_RAY... |
2ee85b50d128bbc62b8c31087930a75a75d1993f90f014e4f9d26058d0a243db | Python | 1,227 | 47 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from numbers import Number
from typing import TYPE_CHECKING, Protocol, overload, runtime_checkable
if ... |
effc8b91eddc9a957b2e870efd484b9ded06b270cfb078ccc2511136e91a0c8f | Python | 1,227 | 32 | from .performance import F1_score, d_prime, performance_curve, calculate_performance
from .statistics import test_responsiveness
from .convergence import test_convergence
from .responsiveness import calculate_responsiveness
from .weights import analyze_weights, import_W_signed, import_W_force, import_W_force_embedded
... |
5c508602274d58a404cf3f37b2fd9a9c479f8121ce616b873f5603c5d78d3249 | Python | 1,228 | 46 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
a5ea285c3932a3f27132b59023ed393ae0c230272c6735b84418fe6b392a5214 | Python | 1,228 | 34 | import torch.nn as nn
from optuna import Trial
from argparse import Namespace, ArgumentParser
from .base import BaseModelConfig
from monai.networks.nets import SwinUNETR
class SwinUNETRConfig(BaseModelConfig):
model_name = "swinunetr"
def setup_search_space(self, trial: Trial, args: Namespace) -> Namespace... |
ea537fe3169ec6091428a7f00a5d151461b74594eb39fea43f842fc3f6f7d448 | Python | 1,229 | 36 | import sys
import pandas as pd
def Pair_mr():
d1 = pd.read_csv(qtl1, sep='\t', header=None, usecols=[0,1], names=['Phenotype', 'SNP']).groupby('Phenotype')
d2 = pd.read_csv(qtl2, sep='\t', header=None, usecols=[0,1], names=['Phenotype', 'SNP']).groupby('Phenotype')
dict1, dict2 = {}, {}
for Phe1, s1 in... |
32a9d6bfb06b932e57426f20a4ec2dc258f96e9ab74122a4b63d423c731e78f8 | Python | 1,231 | 41 | import pytest
import torch.nn as nn
import sinabs.layers as sl
@pytest.mark.parametrize(
("pooling", "layer_type", "expected_pooling", "expected_scaling"),
[
(2, sl.SumPool2d, [2, 2], 1),
((2, 2), sl.SumPool2d, [2, 2], 1),
(3, sl.SumPool2d, [3, 3], 1),
((4, 4), sl.SumPool2d, [... |
51bd6544e8b43d5526be8d149618981a5d7577ba52827808dd978afe807e6725 | Python | 1,231 | 47 | from pathlib import Path
from siapy.entities import SpectralImage
from siapy.transformations.image import (
add_gaussian_noise,
area_normalization,
random_crop,
random_mirror,
random_rotation,
rescale,
)
# Set the path to the directory containing the data
# !! ADJUST THIS PATH TO YOUR DATA DIR... |
e4922c6d4fe73ce715c5d32a257a416342d0b3540a162bb68d2c9d9ae190f8ec | Python | 1,232 | 24 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
7f9aa4a992916f88a00684bdd9faf862360d51bb652a4b0b64dc8cbec3f3a7a9 | Python | 1,234 | 44 | """
Test for issue 437:
https://github.com/Data-Centric-AI-Community/data-profiling/issues/437
"""
import numpy as np
import pandas as pd
from data_profiling import ProfileReport
def test_issue437():
try:
# pd.NA does not exist in some pandas versions
_ = pd.NA
except: # noqa: E722
p... |
c768874927c83a6e3dc2c67532dcd13f7e5030f11dbbbc78a8eb1c499583ff71 | Python | 1,234 | 36 | from typing import Any, Callable, Dict, Optional
import pyarrow
from ray.data.block import BlockAccessor
from ray.data.datasource.file_based_datasource import _resolve_kwargs
from ray.data.datasource.file_datasink import BlockBasedFileDatasink
class CSVDatasink(BlockBasedFileDatasink):
def __init__(
sel... |
ee43dab1dcc9e476fa4734fa4d7a818f50c72325e77749279e3eab83228bd3f0 | Python | 1,234 | 36 | from typing import Any, Callable, Sequence
import torch
from torch.utils.data._utils.collate import default_collate
def _to_recursive(batched: Any, device: torch.device) -> Any:
if isinstance(batched, torch.Tensor):
return batched.to(device)
elif isinstance(batched, list):
return [x.to(device... |
12d04875b1dbce106aa207219d6a1f0e3c2996fbda3e267500b920ed6b46b13e | Python | 1,235 | 38 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
from matplotlib import pyplot as plt
from lifelines import KaplanMeierFitter
from figures.sim_tools import *
from lifeli... |
dc0f1a1360576123ff8ec21be19f67e8009b2bc26da1338714fc67cba20f4cf4 | Python | 1,235 | 36 | import torch.nn as nn
import torch.nn.functional as F
from pfrl.initializers import init_chainer_default, init_lecun_normal
class MLP(nn.Module):
"""Multi-Layer Perceptron"""
def __init__(
self, in_size, out_size, hidden_sizes, nonlinearity=F.relu, last_wscale=1
):
self.in_size = in_size... |
3bd67eaa26f2e2fcacc660090e3e395169184b4c852c2b32a28764547fd30953 | Python | 1,236 | 44 | # flake8: noqa
# fmt: off
# __actor_creator_failure_begin__
import ray
import os
import signal
ray.init()
@ray.remote(max_restarts=-1)
class Actor:
def ping(self):
return "hello"
@ray.remote
class Parent:
def generate_actors(self):
self.child = Actor.remote()
self.detached_actor = Act... |
3e7fd1239714fff4411a8cc8a8896b96b9868789b7cd246ac460da0628232d0a | Python | 1,236 | 46 | #%%
import timeit
import numpy as np
import os
import caiman.external.houghvst.estimation as est
from caiman.external.houghvst.gat import compute_gat, compute_inverse_gat
import caiman as cm
from caiman.paths import caiman_datadir
#%%
def main():
fnames = [os.path.join(caiman_datadir(), 'example_movies', 'demoMov... |
8634e945c393238d3f7b5e657b76dfbf41ce547b6fc96552dfe3c765de577c70 | Python | 1,237 | 42 | # -*- coding: utf-8 -*-
"""
This is implementation of model of corresponding to the article `Large scale model of cat primary visual cortex`.
Antolík, J., Cagnol, R., Rózsa, T., Monier, C., Frégnac, Y., & Davison, A. P. (2024).
PLOS Computational Biolology.
https://pmc.ncbi.nlm.nih.gov/articles/PMC11371232
"""
import m... |
05c5c6cbd3682d611c52fcae8296cf1254bf13d33b8d1e2a05dbfe4145019dfd | Python | 1,238 | 41 | from typing import Union, List
from torch.nn import Module
from torch.nn.modules.loss import _Loss
from src.losses.adversarial.utils import AdversarialLosses
from src.losses.adversarial.adversarial import AdversarialLoss
def get_discriminator_loss(config: dict) -> Union[_Loss, Module]:
d_losses = [d_loss.value ... |
2e81c1125040571344ca6eb31b2728eebdac822b33c4a144721c48806981d032 | Python | 1,238 | 26 | from monai.losses import (
DiceLoss,
DiceFocalLoss,
FocalLoss,
GeneralizedDiceLoss,
GeneralizedDiceFocalLoss,
DiceCELoss,
TverskyLoss
)
def get_loss_function(loss_function: str = 'dice'):
if loss_function.lower() == 'dice':
loss_function = DiceLoss(include_background=False, to_o... |
91ff2b11934e5ae896b1bcff09fedaf691116a5343c92fa690b1b626254c33c0 | Python | 1,238 | 48 | """
script to test spike routing in lif_neuron apps.
"""
import os
from spinnaker2 import hardware, snn
def test_routing_with_lif():
neuron_params = {
"threshold": 1.0,
"alpha_decay": 0.9,
}
n_stim = 1
stim = snn.Population(1, "spike_list", params={0: [1, 2, 3]}, name="stim")
pop... |
3966488c8f7e6ea49bb789f3d6cc7554dbbaae1e064c6ff4945c060789348ad2 | Python | 1,239 | 29 | import torch
import os
import esm
def load_model_and_alphabet(device):
"""Load the ESM model and alphabet."""
model, alphabet = esm.pretrained.esm2_t30_150M_UR50D()
model.to(device)
return model, alphabet
def get_protein_embeddings(model, alphabet, sequence, device):
"""Get protein embeddings from... |
52c98f64ac17bcbc6411845a3f78f7990f8a0545958824cd4c4d00c27c7dfc1c | Python | 1,240 | 36 | import os
import matplotlib.pyplot as plt
def main():
LOG_DIR = "./MODEL/SPLAM_v11/LOG/"
OUT_DIR = LOG_DIR + "IMG/"
os.makedirs(OUT_DIR, exist_ok=True)
##########################################
# Plotting train & test separately
##########################################
for target in ["T... |
dd5ba01cef47429427e9d8c6b87417fc269ce5b05787dbd4dea3ea7b49c98a83 | Python | 1,240 | 45 | import marshmallow as mm
from argschema.schemas import ArgSchema, DefaultSchema
from argschema.fields import (
InputFile, List, Float, Int, Nested
)
from neuron_morphology.transforms.affine_transformer._schemas import (
AffineDictSchema
)
class InputParameters(ArgSchema):
swc_path = InputFile(
des... |
7a9dba6e06b9ac2293fa5bffee65aaf17c4986b911fb0fabd331073828902a95 | Python | 1,241 | 34 | import torch.nn as nn
from optuna import Trial, Study
from .base import BaseModelConfig
from argparse import Namespace, ArgumentParser
from monai.networks.nets import BasicUnet
class STTUNetBackboneConfig(BaseModelConfig):
model_name = "unet_sttbackbone"
def setup_search_space(self, trial: Trial, args: Na... |
b232ed3d846dc020eab073362f2f19d06725e267e076dd85906cdfa306f03b91 | Python | 1,241 | 60 | # 3rd party dependencies
import cv2
import matplotlib.pyplot as plt
# project dependencies
from deepface.modules import streaming
from deepface import DeepFace
img_path = "dataset/img1.jpg"
img = cv2.imread(img_path)
overlay_img_path = "dataset/img6.jpg"
face_objs = DeepFace.extract_faces(overlay_img_path)
overlay_i... |
bcc792853b8dfeb2d40736be08f2a75eda489dc11df9c7aec140ba52e6e9df77 | Python | 1,241 | 40 | import torch
import soft_rank_pytorch
from metrics import _rank_data
def spearman_loss(pred, true, regularization_strength, regularization):
assert pred.device == true.device
assert pred.shape == true.shape
assert pred.shape[0] == 1
assert pred.ndim == 2
device = pred.device
soft_pred = sof... |
b0ef91c0bf679b51f7bcb275af6bec0ead066f01d9b68f32b75f9f8e0f30a72f | Python | 1,243 | 29 | import numpy as np
from ray.data._internal.datasource_v2.interfaces.file_manifest import FileManifest
from ray.data._internal.datasource_v2.interfaces.in_memory_size_estimator import (
InMemorySizeEstimator,
)
from ray.util.annotations import DeveloperAPI
# Default Parquet encoding ratio: in-memory is ~5x on-disk... |
00321f29dd7ad9d989c693f38971dba56deb386f51ea4b61d96888e5fa0e0167 | Python | 1,244 | 25 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
176de0141be3b6554286510823c9da65754b99c585da5dd9483093f054abb551 | Python | 1,244 | 40 | import os
import warnings
warnings.filterwarnings("ignore")
# load in directories
from language.constants import DATA_DIR
from language.preprocess import Task, Prescreen
def run(data_type='task'):
"""preprocess task or prescreen data
Args:
data_type (str): default is 'task'. other option is 'prescr... |
455556842a2851284e594b648f9aa8a213d4bcbc4429e5f30fba8ffa9f0c3086 | Python | 1,245 | 38 | from ._version import get_versions
__version__ = get_versions()["version"]
del get_versions
__author__ = "Justus Schock, Michael Baumgartner"
__author_email__ = "justus.schock@rwth-aachen.de"
__license__ = "MIT"
__copyright__ = "Copyright (c) 2019-2020, %s." % __author__
__homepage__ = "https://github.com/PhoenixDL/r... |
a5cf65927a4516bf3a637818224fbdcc04ede2d8ac7de3c26b17133d67d0285d | Python | 1,245 | 41 | import pathlib
import urllib.request
import numpy as np
import pytest
from cebra.integrations.sklearn.cebra import CEBRA
MODEL_VARIANTS = [
"cebra-0.4.0-scikit-learn-1.4", "cebra-0.4.0-scikit-learn-1.6",
"cebra-rc-scikit-learn-1.4", "cebra-rc-scikit-learn-1.6"
]
@pytest.mark.parametrize("model_variant", MO... |
ab9817f22d2b2352d89d60289cc932572cae93ebdada8722fbafea58b7e6426f | Python | 1,245 | 42 | # -*- coding: utf-8 -*-
"""
This is the implementation of the model corresponding to the pre-print `Iso-orientation bias of layer 2/3 connections: the unifying mechanism of spontaneous, visually and optogenetically driven V1 dynamics`
Rózsa, T., Cagnol, R., Antolík, J. (2024).
https://www.biorxiv.org/ TODO: Update
"""
... |
1d1ace2113e55e3b1089df182dcda8026213c6cf677b1e712d4bdccb566f52ff | Python | 1,246 | 31 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
386a60bde844c48732ed517019f144693f6309d833a419aa766e06a6adf0b029 | Python | 1,246 | 34 |
import os
import sys
import copy
from datetime import datetime
import argparse
import numpy as np
from aptnn.io.xyz import Trajectory, write_frame, write_conf
parser = argparse.ArgumentParser(description='Takes a trajectory XYZ file and displaces the respective atom identified with "atom_id" in the comment line')
p... |
5a6f937a74075074dc451e1ba7ce1f444926ea3386f247dc210850f39f9b1748 | Python | 1,246 | 31 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for Bio-Diffusion (https://github.com/BioinfoMachineLearning/bio-diffusion):
# --------------------------------------------------------------------------------... |
615c71f0ca013e36739e0678094c5d1cb8cc5c2deac7df592909cc4d2503e0be | Python | 1,246 | 40 | # Luis del Peso
# Modified by A. Mathelier
# Vancouver, Jan 2012
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq
from Bio.Alphabet import generic_dna
from Bio import SeqIO
from altschulEriksonDinuclShuffle import dinuclShuffle
from utils import *
def shuffle_window(ss, wl, step):
bs = ss[:]
for i in r... |
baf91c8b087c053da7b81319de0c7f516100bd04ccd87a4af74d42f65516d89b | Python | 1,246 | 41 | from pfrl.agents import dqn
from pfrl.utils import evaluating
from pfrl.utils.recurrent import pack_and_forward
class DoubleDQN(dqn.DQN):
"""Double DQN.
See: http://arxiv.org/abs/1509.06461.
"""
def _compute_target_values(self, exp_batch):
batch_next_state = exp_batch["next_state"]
... |
1f840de6f4c1e2885fbb8078a4a51f360251080abfad68fd37641f6002ed0351 | Python | 1,247 | 40 | from typing import Any, Callable, Optional
from data_profiling.report.presentation.core.item_renderer import ItemRenderer
from data_profiling.report.presentation.core.renderable import Renderable
class Variable(ItemRenderer):
def __init__(
self,
top: Renderable,
bottom: Optional[Renderabl... |
b025138a9a6342942c8a1c6993ef03c2d853333e480da30802deb968bd469447 | Python | 1,248 | 44 | import numpy as np
from sklearn.decomposition import PCA
from umap import UMAP
def reduce_dim(
x, n_components, method='pca',
pre_normalize=False, post_normalize=False):
if n_components >= 1:
n_components = int(n_components)
isfin = np.isfinite(x).all(-1)
if pre_normalize:
... |
312e790efe1b748d54012f448132db19731c2f3fe6c8fbe6559bade161086852 | Python | 1,249 | 41 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
from model import utils
from matplotlib import pyplot as plt
from lifelines import KaplanMeierFitter
from figures.sim_to... |
b0876d38f57adef620b1ddcc115c2e6d3dbee892a348256e2c01c56aeeb81e49 | Python | 1,249 | 47 | # -*- coding: utf-8 -*-
"""
"""
from setuptools import setup, find_packages
import runpy
from os.path import dirname, join
HERE = dirname(__file__)
with open(join(HERE, 'README.md'), "rb") as f:
long_description = f.read().decode("utf-8")
setup(
name='vtkplotlib',
version=runpy.run_path(join(HERE, "vtkp... |
f0328ade9844d3a81acd4a6af337bc87cc003aa105d9f538af01c87094118367 | Python | 1,249 | 38 | import numpy as np
import torch
def clip_l2_grad_norm_(parameters, max_norm):
"""Clip gradient L2 norm.
This function works in the same way as `torch.nn.utils.clip_grad_norm_`
with `norm_type=2`, but more efficiently on CPU as of PyTorch 1.4.0.
Args:
parameters (torch.Tensor or Iterable[torc... |
32caceae449cd0fc6067e56ceb157cc02683bdda80d1585acfee4d5c31fe8ab8 | Python | 1,250 | 22 | """Vendored Bonsai-scout tree layout (upstream v1.0.0), CC BY-NC 4.0.
Only ``my_tree_layout`` is carried, not the Dash application around it. The file
is self-contained upstream (stdlib + numpy/pandas, no Bonsai imports);
:func:`omicverse.external.bonsai.scout_layout` builds its ``Layout_Tree``
straight from an edge l... |
647f40e3f72a81428f00d87e190e91e6df9d5375e9f4eee99dc253c2b5e348d0 | Python | 1,251 | 35 | from typing import Callable, Iterable
from ray.data._internal.datasource.sql_datasource import Connection, _connect
from ray.data._internal.execution.interfaces import TaskContext
from ray.data.block import Block, BlockAccessor
from ray.data.datasource.datasink import Datasink
class SQLDatasink(Datasink[None]):
... |
bf18cfac88c517d319b97e93a65167ebff87acd3c0c6403b8496c0ba8d3015f6 | Python | 1,251 | 44 | from typing import Tuple, Union
class CellInteraction:
def __init__(self, type1: str, type2: str):
self.type1 = type1
self.type2 = type2
self.interactions = tuple(sorted([type1, type2]))
def torch_str_key(self):
return self.interactions.__str__()
def interaction_types(... |
77cba10b644e0e91b0579ce9748f2bc814f4089c8e028ae1fee6b9d35558d417 | Python | 1,253 | 42 | # Copyright 2023 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, sof... |
fdee022eff9ecd39dae0eb5a3ec9695d25a2cd49ed8fbcdf8ee5309b01cbe276 | Python | 1,253 | 59 | import numpy as np
import matplotlib.pyplot as plt
from spinnaker2 import snn, hardware
neuron_params = {
"threshold": 60.,
"alpha_decay": 0.9,
"i_offset": 0.0,
}
stim = snn.Population(
size=2,
neuron_model="spike_list",
params={0: [1, 5, 10, 15, 20, 26], 1: [2,... |
1b2cb4fce41a693abbea3ba9143962d34e7aa7ea00d7b385e075b7cfca98ac83 | Python | 1,255 | 48 | """skorch base imports"""
import sys
import warnings
import importlib.metadata
from .history import History
from .net import NeuralNet
from .classifier import NeuralNetClassifier
from .classifier import NeuralNetBinaryClassifier
from .regressor import NeuralNetRegressor
from . import callbacks
from ._version import ... |
1e6bc4bebdd41b542fe05e54f25482d8a5698ae9069a3a4f4d4cb90f9210f67e | Python | 1,255 | 38 | enhance_model = dict(
_scope_='lqit',
type='BaseEditModel',
destruct_gt=True,
data_preprocessor=dict(
type='EditDataPreprocessor',
mean=[0.0, 0.0, 0.0],
std=[255.0, 255.0, 255.0],
bgr_to_rgb=False,
gt_name='img'),
generator=dict(
type='TIENetGenerator'... |
d2647b9479117b77dae9d0f6c826438479e5c02a3c9a88245bb4142aa51a2728 | Python | 1,255 | 41 |
import os
import argparse
import cv2
import numpy as np
def getImageRepetitive(fp):
repetitiveMask = cv2.imread(fp,0)
repetitiveMask = (repetitiveMask!=0)
return repetitiveMask
if __name__=="__main__":
print "check"
row_folders = ['row001_auto_out','row002_auto_out','row002_auto_out']
parser... |
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