sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
6c2ee003aa5eec6ab3d43ccbf7816c725b2025f142a4635d261d674a1077af37 | Python | 1,682 | 35 | ###################################################################################################
# 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 free... |
6c9b90a4123a956c0c6e7a0fee9694efcecf53c63808b1684c47cecebd2aec17 | Python | 1,682 | 95 | from dataclasses import dataclass
from pathlib import Path
from typing import Any
from rdkit import Chem
TENSORBOARD_LOG_DIR = Path("tensorboard_logs")
"""Set of parameters for each atom."""
ALLOWED_ADDUCTS = [
"[M+H]+",
"[2M+H]+",
"[M+Na]+",
"[2M+Na]+",
"[M-H]-",
"[2M-H]-",
"[M+K]+",
... |
f25b6e7dac13ee2547f2c900e8d5a27670baa79883c81932dac6fe954591dbfa | Python | 1,682 | 61 | #!/usr/bin/env python3.7
"""Plot the waveform used for stimulation.
The copyrights of this software are owned by Duke University.
Please refer to the LICENSE and README.md files for licensing instructions.
The source code can be found on the following GitHub repository: https://github.com/wmglab-duke/ascent.
RUN THI... |
1b2b9dc54b7d01648cada062cea32647044d237dc6a96423ff7fedc6de52d8c1 | Python | 1,684 | 46 | def _get_starfysh_modules():
from ..external.starfysh import AA, _starfysh as sf_model, plot_utils, post_analysis, utils
return AA, utils, plot_utils, post_analysis, sf_model
class STARFYSH:
"""
STARFYSH spatial transcriptomics analysis class.
A comprehensive tool for analyzing spatial transc... |
6bff063892062bb1cfff00f6c483f2faaedb4a698bacbe19dfcea2800b3ff6f4 | Python | 1,685 | 39 | from torch import nn
from .modules import *
class MultiModalLayer(nn.Module):
def __init__(self, d_model, d_inner, n_head, d_k, d_v):
super().__init__()
self.peptide_attention_layer = MultiHeadAttention(n_head, d_model,
... |
f7695ce945a4115f2285896993c9230e047c3488888e4099538377f42560b292 | Python | 1,685 | 45 | #!/usr/local/bin/ipython -i
from mozaik.experiments import *
from mozaik.experiments.vision import *
from mozaik.sheets.population_selector import RCRandomPercentage
from parameters import ParameterSet
def create_experiments(model):
return [
# Lets kick the network up into activation
# Spontaneo... |
883bc96536fa40f9d0df9c6c658d6b2d0c055088e683870aa7596863085b9041 | Python | 1,686 | 40 | #Test multi_stage
from pytorch_lightning import Trainer
from src.models import multi_stage
from src.data import TreeDataset
from src import visualize
import numpy as np
import glob
def test_MultiStage(dm, config):
m = multi_stage.MultiStage(train_df=dm.train, test_df=dm.train,crowns=dm.crowns, config=config)
... |
e2fa72ca3d2bfa307aa11b2ba391ce4493fe118657f61015b4840da13560ac3a | Python | 1,686 | 46 | #!/usr/local/bin/ipython -i
from mozaik.experiments import *
from mozaik.experiments.vision import *
from mozaik.sheets.population_selector import RCRandomPercentage
from parameters import ParameterSet
def create_experiments(model):
return [
# Lets kick the network up into activation
# Spontaneo... |
53d8e4f925c821a3660c90cb9127765e80a6950cd7060d32f895d6f29b95a679 | Python | 1,687 | 75 | import pathlib
import numpy as np
import nose
from caiman import mmapping
from caiman.paths import caiman_datadir
TWO_D_FNAME = (
pathlib.Path(caiman_datadir())
/ "testdata/memmap__d1_10_d2_11_d3_1_order_F_frames_12_.mmap"
)
THREE_D_FNAME = (
pathlib.Path(caiman_datadir())
/ "testdata/memmap__d1_10_... |
a41c8a86b1daed60c06de3b7f10bf6c2dd9009aa57bca3c2bfba3b8e77635e3a | Python | 1,687 | 48 | """Shared memory-detection utilities for OmicVerse."""
from __future__ import annotations
import os
# Fraction of available CPU RAM that a single dense allocation may occupy.
# PCA and similar operations need ~2-3x the array size internally, so 0.3
# leaves headroom for temporaries.
AUTO_DENSE_CPU_MEM_FRACTION = 0.3... |
dad16361688421fd2f2bc4225ad16853d3cf49b2578738b3c629c8813df0409f | Python | 1,687 | 51 | import os
from pcntoolkit.normative_parallel import execute_nm, collect_nm, delete_nm
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.normative import predict, estimate
# globals
root_dir = '/project_cephfs/3022017.02/projects/hansav/Run8_f/'
proc_dir = os.path.join(root_dir)
w_dir = os.path.join(... |
14e082a8efbc648e21bd6beb8fc32096927804758a0d51ffc1e529ceb3350b74 | Python | 1,688 | 50 | import torch
import torch.nn as nn
from ..utils import create_norm
class ResMLPEncoder(nn.Module):
def __init__(self, num_hidden, num_layers, dropout, norm, covariates_dim=0):
super().__init__()
self.layers = nn.ModuleList()
assert num_layers > 1, 'At least two layer for MLPs.'
for ... |
180dd116790080adf8125283ab33bfa1a96caae3ee1f20b69a446e167ef446fd | Python | 1,688 | 42 | # Import modules
import cv2
import pandas as pd
import os
import shutil
import sys
image_size = int(sys.argv[1])
base_path = os.getcwd()
print(base_path)
source_path = f'{base_path}/ultra-mnist'
destination_path = f'{base_path}/ultra-mnist_{image_size}'
if os.path.exists(destination_path):
print("Directory already... |
f0b53ab6323e060ec20d7b375fc1b3a2bd5bb7fa549b4ac32eaa33cdfa5f47b5 | Python | 1,689 | 51 | import os
from pcntoolkit.normative_parallel import execute_nm, collect_nm, delete_nm
from pcntoolkit.dataio.fileio import load as ptkload
from pcntoolkit.normative import predict, estimate
# globals
root_dir = '/project_cephfs/3022017.02/projects/hansav/Run8_fs/'
proc_dir = os.path.join(root_dir)
w_dir = os.path.join... |
e8f95425d251101daaee62cb37b58d23e660d9bea155f81533f281d1a64b6d54 | Python | 1,690 | 68 | from pathlib import Path
import pandas as pd
import numpy as np
from collections import defaultdict
import random
from scipy.stats import multivariate_normal
from scipy.stats import wasserstein_distance
from scipy.stats import pearsonr
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.font_manager impo... |
463d94d4fa1756ec0053cdda6731b0f6d10a52bb09943b0d2b45eaeb17185251 | Python | 1,691 | 62 | from typing import Tuple
import pandas as pd
from data_profiling.config import Settings
from data_profiling.model.pandas.describe_categorical_pandas import (
length_summary_vc,
unicode_summary_vc,
word_summary_vc,
)
from data_profiling.model.summary_algorithms import (
histogram_compute,
series_ha... |
fd75512390cf585377a9dcf5784d94fcf4c9d31b01b1447698e35221ab48dbdb | Python | 1,691 | 51 | import glob
import argparse
import concurrent.futures
import numpy as np
from utils import mri_utils, metadata_utils
from config import config
parser = argparse.ArgumentParser()
parser.add_argument('--dir', type=str,
default="/gpfs/data/oermannlab/ObermannNeuro3/dicom/",
help=... |
5dfb4e2cb7033e33277471d8d201820c5283b864a02b36df6a450e9f0bd8652a | Python | 1,692 | 42 | import numpy as np
from lib.surface import isotonic_increasing, monotone_free_arcs
def test_isotonic_increasing():
y = np.array([0.1, 0.3, 0.2, 0.4, 0.35, 0.36, 0.9])
fit = isotonic_increasing(y)
assert np.all(np.diff(fit) >= 0)
assert np.isclose(fit.sum(), y.sum()) # pooling keeps the mean
asser... |
c60b0085bc50b997689f2882b795c7164f88e32108c7e036b572f768383461ba | Python | 1,692 | 50 | """Read BrainVoyager vmr and export nifti."""
import os
import nibabel as nb
import bvbabel
import pprint
import subprocess
subs = ['sub-08']
ROOT = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives'
for sub in subs:
folder = f'{ROOT}/rawdata_bv/{sub}/ses-01/anat'
inFile = f'{folde... |
dbbcf789a9df04a16fa6fb6f49191318e63b8362decb891758092303b79ad00f | Python | 1,692 | 48 | # built-in dependencies
from typing import Any, List, Union
# project dependencies
from deepface.commons.onnx_utils import build_session
from deepface.models.facial_recognition.onnx.OnnxFacialRecognition import OnnxFacialRecognition
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=line-... |
0bef0addb3a0abd5e82a90fe60443fb36fd739d3e2ab04a814904c6030a7ad4e | Python | 1,693 | 43 | # -------------------------------------------------------------------------------------------------------------------------------------
# Following code curated for Bio-Diffusion (https://github.com/BioinfoMachineLearning/bio-diffusion):
# --------------------------------------------------------------------------------... |
b8eaf977c4d6563589f7a1c6bcbe581eb1c93c68f3d809d719e9831ee1f6a8f4 | Python | 1,693 | 85 | #!/usr/bin/env python3
# vim: set ts=4 sw=4 tw=0 :
from tempfile import NamedTemporaryFile
import numpy as np
import cp2k
TEST_FILE_CONTENT = """
&FORCE_EVAL
METHOD Quickstep
&DFT
BASIS_SET_FILE_NAME BASIS_SET
POTENTIAL_FILE_NAME POTENTIAL
LSD
&MGRID
CUTOFF 140
&END MGRID
&QS
... |
16094f08f694ab854aef0fe23d5ff24cb895ddc9a75daa31e2f5a848b8de1c64 | Python | 1,694 | 56 | # flake8: noqa
# __begin_deploy_app_with_capacity_queue_router__
import ray
from ray import serve
from ray.serve.config import DeploymentActorConfig, RequestRouterConfig
from ray.serve.context import _get_internal_replica_context
from ray.serve.experimental.capacity_queue import (
CapacityQueue,
)
@serve.deploy... |
34064061adac4393f70e75642e889516e8f7517c24e6c6c5b92acb825b21130b | Python | 1,695 | 58 | '''
Correcting bias field of MP2RAGE images.
'''
import os
import glob
import subprocess
import ants
DATADIR = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti'
SUBS = ['sub-08']
for sub in SUBS:
# =========================================================================
# Brain extraction... |
54f93705e5830958428ec07905da2f16adfd49943f8937b0573b1121518599fa | Python | 1,695 | 55 | import copy
from ..distances import LpDistance
from ..reducers import DoNothingReducer, MeanReducer, MultipleReducers
from ..utils.module_with_records import ModuleWithRecords
class ModuleWithRecordsAndReducer(ModuleWithRecords):
def __init__(self, reducer=None, **kwargs):
super().__init__(**kwargs)
... |
c48483791d56e9307aa5f821a844d37f479ded093d6d0ec694607902c00300ab | Python | 1,695 | 58 |
import pdb
import numpy as np
from data_assimilation.particle_filter.base import BaseObservationOperator
class ObservationOperator(BaseObservationOperator):
def __init__(
self,
observation_state_ids: list,
observation_space_ids: list,
full_space_points: list = None,
... |
55157a6146152a2340cd1d9c418136ad42714388bb0abb7ce1551ad2c8f02825 | Python | 1,696 | 73 | import errno
import os
import platform
import shutil
import subprocess
def is_nvidia_installed():
installed = True
try:
subprocess.check_output('nvidia-smi')
except Exception:
installed = False
return installed
def is_windows():
return platform.system() == 'Windows'
def is_linu... |
af6c8ac7cb87081aadc1e83959d2fb7f9e7f1eb9efddf5813df9f4097b0c7bd7 | Python | 1,696 | 37 | """Vendored copy of SATURN (Species Alignment Through Unification of Rna and proteiNs).
SATURN is a deep-learning method for cross-species single-cell integration. Per
species it takes an AnnData of raw counts plus a precomputed protein-embedding
dictionary (gene symbol -> ESM2 embedding vector) and trains a "macrogen... |
df74a7fda6c8269f1b19619e3c15d3ff549f8f8dd868fd6ae57553c5bf41ff24 | Python | 1,696 | 52 | #!/usr/bin/env python
import platform
import setuptools
if (
platform.processor() == "arm" or platform.processor() == "i386"
) and platform.system() == "Darwin":
tensorflow_os = "tensorflow-macos>=2.10.0,<=2.20.0"
else:
tensorflow_os = "tensorflow>=2.12.0,<=2.20.0"
with open("README.md", "r") as fh:
... |
f17cf7611356f7fb9c459205163379556004fae519cd0f5b6f83a12b3753ca16 | Python | 1,696 | 49 | """ Full assembly of the parts to form the complete network """
import torch.nn.functional as F
import torch.nn as nn
from .unet_parts import *
class UNet_3(nn.Module):
def __init__(self, output_c = 1, bilinear=True):
super(UNet_3, self).__init__()
self.output_c = output_c
self.bilinear =... |
e9cda066e2861a6621fe7eac9ea351adaa1bb044d114695484bda548e165a2ee | Python | 1,697 | 63 | #!/bin/env python3
# usage: python _run-rnapromo-h0.py <rnapromo_out> <test.fa>
import sys
inf = float("inf")
ifname = sys.argv[1]
faname = sys.argv[2]
def get_correct():
correct = {}
with open(faname) as fi:
b,e=-1,-1
for l in fi:
if l.startswith(">"):
l=l[1:].str... |
687a21240ec9877a2f2213e6a8fd42ad34c976ea705d2dcdda1b2f86641c6107 | Python | 1,699 | 49 | import pandas as pd
import numpy as np
import os.path as osp
NAME_COLUMN = 'name'
FP_DELIM = '\t'
class FPDataset():
"""
Dataset class to load fingerprint data.
"""
def __init__(self, args):
self.num_workers = args.num_workers
self.data_path = args.data_path
self.fp_format = a... |
c3a48f90547883adf170939f62fdfb1262a8b2dc1ab8082eeb3ac373b77726d2 | Python | 1,699 | 57 | """
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 random
import numpy as np
import pytest
from fairchem.data.oc.core import Bulk, Slab
class Te... |
5fd2ad87aed661b04129f67feecc0be6e95fb4cdf0d22579749656690c1dbce6 | Python | 1,700 | 42 | import pandas as pd
import os
def main(db):
old_file = f'./1_output/old_method/{db}_introns.bed'
new_file = f'./1_output/{db}_introns.bed'
old_df = pd.read_csv(old_file, delimiter='\t', header=None, usecols=range(6),
names=['seqid', 'start', 'end', 'name', 'score', 'strand'])
new... |
b6736a99849bec2f00f7e5e4058fa508be9e889e82ea1b10ad1f5fcaceea752b | Python | 1,700 | 62 | #!/usr/bin/env python3
"""Extract features with pretrained model from RetCCL: Clustering-guided Contrastive Learning for Whole-slide Image Retrieval
https://github.com/Xiyue-Wang/RetCCL
use like this:
python -m marugoto.extract.xiyue_wang \
--checkpoint-path ~/Downloads/best_ckpt.pth \
--outdir ~/... |
4b5bcaa6443e8c6c21f7af803d08d47e26023fce5e2dbca849c1d5f48c6de0cd | Python | 1,701 | 59 | from ultralytics import YOLO
import os
import cv2
import numpy as np
import math
import tqdm
import copy
imgs_path = "test_images"
out_path = "test_results"
crop_image_path = 'cmb_results'
os.makedirs(out_path, exist_ok=True)
# Load a model
model = YOLO("CMB.pt") # load a custom model
# Predict ... |
5b5ff057cacc19934700ca8e183aaa0aaae23525fc7ddfca86a72ae9e473f8b7 | Python | 1,701 | 56 | from collections import Counter
import pandas as pd
from data_profiling.config import Settings
from data_profiling.model.table import get_table_stats
@get_table_stats.register
def pandas_get_table_stats(
config: Settings, df: pd.DataFrame, variable_stats: dict
) -> dict:
"""General statistics for the DataFr... |
5c0c9b6398b66e36ef1a56c8fb00d62b86a3797b770f0d0fa89d1ab9c565d299 | Python | 1,701 | 48 | #!/usr/bin/env python
import tflearn
import pyaudio
import speech_data
# Training Step: 544 | total loss: 0.15866
# | Adam | epoch: 034 | loss: 0.15866 - acc: 0.9818 -- iter: 0000/1000
# 98% Accuracy on training set in just a minute
# audio = pyaudio.PyAudio()
# # format=pyaudio.paFloat32
# format=pyaudio.paInt8
# ... |
9ebeea26c00e5622d8ea9fbde03e984bb221cc09ff3a0e4282e8d1398e8f24ff | Python | 1,701 | 48 | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Load data for BCI IV-2a
df_a = pd.read_excel('length.xlsx', sheet_name='2a')
# Load data for BCI IV-2b
df_b = pd.read_excel('length.xlsx', sheet_name='2b')
# Set token sizes that were experimented with
param_values = [12, 13, 15, 17, 2... |
6be8487e1e64ee2a94d85544258426f9aff9c225761109de5726bc0bd9602187 | Python | 1,702 | 56 | from spinnaker2 import snn, hardware
def run_model(spikes_per_timestep, timesteps):
n_pre = spikes_per_timestep
spike_times = dict()
all_timesteps = list(range(timesteps))
for i in range(spikes_per_timestep):
spike_times[i] = all_timesteps
stim = snn.Population(
size=... |
838a6a8c27a4656392bdffaca03292b116f0b114bf9a4c8e143fe510a8df4f58 | Python | 1,703 | 62 | import argparse
import glob
import matplotlib.pyplot as plt
def parse_log_line(raw_line):
line = raw_line.strip().split(":")
for i, v in enumerate(line):
if v.startswith("DEBUG"):
return line[i], line[i+1], line[i+2:]
def main(args):
input_logs = glob.glob(args.input)
if len(in... |
146189bd3736f8b6638f4834c4cee34117801bb7e5a687e09fe20908a86cc4b5 | Python | 1,704 | 48 | '''
Finds the exact times between consecutive triggers from logfiles and computes
average TR for SS-SI VASO acquisitions.
Takes logfile as input and assumes "Keypress: 5" as trigger in logfile.
'''
import re
import numpy as np
def findTR(logfile):
with open(logfile) as f: # Open file
f = f.readlines()... |
5f8866d98600e1fbb8ae1f239dcf93a63b6208ed94da02af3f96b41b0846ddc1 | Python | 1,704 | 46 | #!/usr/bin/env python3
"""Utility functions for correlation between covariates and PCs"""
import logging
import numpy as np
import pandas as pd
def vcorrcoef(X, y):
"""Vectorized correlation, matrix vs. vector."""
Xm = np.reshape(np.mean(X, axis=1), (X.shape[0], 1))
ym = np.mean(y)
r_num = np.sum(np.a... |
6b37ff7153abb1d20aaeeea6c045e442987aecf5de118e55dd30f896f66c7944 | Python | 1,704 | 44 | #!/usr/bin/env python3
import torch
from tqdm import tqdm
import numpy as np
try:
import tinycudann as tcnn
except:
pass
# This script stress-tests the GPU memory arena of tiny-cuda-nn with randomly sized allocations and helped
# find a bug in its interval arithmetic in the past.
class TcnnFCBlock(tcn... |
7008a8f63db63b14d1d4a499a13e975715126f7ad975a04a6db63b2f81bfc3e7 | Python | 1,705 | 62 | # flake8: noqa
"""
Example Ray Serve LLM application for a multi-host TPU slice.
"""
# __serve_tpu_multihost_start__
from ray import serve
from ray.serve.llm import LLMConfig, LLMServingArgs, build_openai_app
llm_config = LLMConfig(
model_loading_config=dict(
model_id="google/gemma-4-31B-it",
mode... |
e065aced80d839b128eadf4dadadbdb4c7426bd57cbd619cedb372fdc7cabb25 | Python | 1,705 | 48 | # built-in dependencies
from typing import Any, cast
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.models.Demography import Demography
from deepface.commons.onnx_utils import run_session
from deepface.commons.logger import Logger
logger = Logger()
# Notice that facia... |
81baf681d70349ef2bf33d7f056e5d18d35fe7b41e1d4cff2ca0e0c51849d5e9 | Python | 1,706 | 62 | """
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 random
import numpy as np
import pytest
import torch
from ase.build import bulk, molecule
from ... |
602f5d43eff02f9dadfdcaab6f27a016af8137482d061d68f6ffb93626275cb4 | Python | 1,707 | 63 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import sys
import pandas as pd
import pysam
import svtk.utils as svu
def main():
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('vcf')
... |
74ca773f2878fcb54dd254c0d1a7cf501face60b367cca8e46c83626251a38bc | Python | 1,707 | 48 | from __future__ import annotations
import itertools
from typing import List, Union
import numpy as np
import pyarrow as pa
import pyarrow.compute as pc
def _counts_to_offsets(counts: pa.Array) -> pa.Array:
"""Convert per-row counts to list offsets via cumulative sum."""
cumsum = pc.cumulative_sum(counts)
... |
b748cace6d8dcd52c09a9c929f43be90b3e169d3d6d2cc80ed452ea34f1b3c21 | Python | 1,707 | 57 | # -*- 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.
#... |
d0752b4e47e11fa8f77fea17c1c27902e464a516158415c52be7a3d00dd50483 | Python | 1,707 | 56 | import torch
from torch.autograd import Function
class DiceCoeff(Function):
"""Dice coeff for individual examples"""
def forward(self, input, target):
self.save_for_backward(input, target)
eps = 0.0001
self.inter = torch.dot(input.view(-1), target.view(-1))
self.union = torch.... |
8f9558e4673944526eda0e36dc9f18eacf63bbc7a1451b66cbe71d61a0603832 | Python | 1,710 | 44 | # 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 required by applicabl... |
c8b9987ca2a98d96d524a9324978e7704689cb2ebd32d2f2f5d4bb3fc9367a5f | Python | 1,711 | 51 | import pandas as pd
from data_profiling.utils.cache import cache_file
def test_dataset_schema():
file_name = cache_file("auto2.dta", "http://www.stata-press.com/data/r15/auto2.dta")
df = pd.read_stata(file_name)
metadata = {
"creator": "Firstname Lastname",
"author": "Firstnam... |
4ccdfed19119b67ed1fba5b07724dda5bf7c70b1e4869e3232ddab3413c7f6c7 | Python | 1,712 | 43 | import torch
import ecg_augmentations as ea
FS = 250
ECG, PEAKS = ea.synthetic_ecg(duration=10, fs=FS, n_leads=12, seed=0)
NOISE = torch.randn(3, 4000, generator=torch.Generator().manual_seed(0))
def detector(signal, fs):
return PEAKS[PEAKS < len(signal)].numpy()
TRANSFORMS = {
"RandomCrop": lambda: ea.Ra... |
4c6e9e6192c08239e72af84af029ebf66d6e040319ee9caa102001f7424f5777 | Python | 1,714 | 54 | from typing import Any, Dict, Optional, Sequence, Tuple
import pyspark.sql.functions as F
from pyspark.sql import DataFrame
from data_profiling.config import Settings
from data_profiling.model.duplicates import get_duplicates
@get_duplicates.register
def get_duplicates_spark(
config: Settings, df: DataFrame, su... |
add34a023d186277e354fb63353c2bc70ea0f6dd0faca3223b3165eabf87ea06 | Python | 1,714 | 50 | from torch import nn
from lop.utils.miscellaneous import net_init, fc_body, register_hook, kaiming_init, xavier_init, lecun_init
class VF(object):
def value(self, x, to_log_features=False):
self.to_log_features = to_log_features
val = self.v_net(x)
self.to_log_features = False
retu... |
2e757263e1ce12c66f8c3890702ef182d7aef2ef8744d23e1a4cfb1ac0d284a2 | Python | 1,715 | 46 |
from src.commons.process_number import cal_eccentricity
from src.display_properties.properties import Properties
def get_sub_posi_list_at_given_e(eccentricty, display_posis):
"""
:param eccentricty: in pixel
:param posilist: display position
:return: the sub-display positions (within the given eccen... |
a69e889a3ac182b485ca8848160d71b692d4cae6e65d05ce6b8e6ab9c74b60ff | Python | 1,715 | 91 | #!/usr/bin/env python
'''
Brian2 example for lif neuron
'''
from brian2 import *
import numpy as np
defaultclock.dt = 1*ms
dt = defaultclock.dt
print(dt)
n_in = 1 # number of stimuli
n_out = 1 # number of output neurons
duration = 1*second
v_th = 1.
alpha_decay = 0.9
tau = dt/(1-alpha_decay)
print(f"tau: {tau}")
... |
68285bc7032b4df4914a2c817cf6b82451dda56f0d1861036e9f3c12fb5fb3b1 | Python | 1,718 | 52 | import dataclasses
from typing import Iterable
def _validate_allowed_keys_exist(
dataclass_name: str, data_dict: dict, allowed_keys: set
):
keys_not_in_dict = allowed_keys.difference(data_dict)
if keys_not_in_dict:
raise ValueError(
f"Key(s) {sorted(keys_not_in_dict)} are not present i... |
c375cce93010687f75fa5eca930dd5eb1540e1015172f5684c7e491a97f18fe7 | Python | 1,719 | 54 | import struct
from spinnaker2.neuron_models.application import BaseApplication
from spinnaker2.configuration import PEConfig
from spinnaker2.neuron_models.common import add_log_memory_region
from spinnaker2.coordinates import ByteAddr, align_addr_to_next_multiple_of_other
class SpikeReceiverApplication(BaseApplicati... |
d5cc0547481a7dbd15e90a0fd7908a9fa032fe963b020ad1be62251bae89f5fd | Python | 1,720 | 45 | # 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 required by applicabl... |
dab7ceb564cff94edbecb9d89c80a63ded0122983d7fef5e055a231c15c72a14 | Python | 1,721 | 49 | # 3rd party dependencies
import pytest
import numpy as np
# project dependencies
from deepface import DeepFace
from deepface.commons.logger import Logger
logger = Logger()
def test_enabled_enforce_detection_for_non_facial_input():
black_img = np.zeros([224, 224, 3])
with pytest.raises(ValueError):
... |
1742af6c598ce636b41ba9058cdf1590d3b28a5d8a7c6b7ecf3dadf963848794 | Python | 1,722 | 60 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
499efdcc93c0e771d9e1655920181ab6ba3ca9cb54874d97de03d3b0645bd3d8 | Python | 1,722 | 73 | from nltk import bleu
from rouge import Rouge
import jsonlines
import json
import sys
def read_gold_data(path):
fi = jsonlines.open(path, 'r')
explanations = {line['index']: line['conceptual_explanation'] for line in fi}
return explanations
def evaluation_bleu(golds, predictions):
bleu_socre = 0
... |
bf56be4f746c892469c172d664a7f1848dd7d10dbc33353a8af46a29102403ec | Python | 1,722 | 36 | from .trainer import train_vae
from .trainer_nogcn import train_vae_nogcn
from .trainer_anvi import train_anvi
from .trainer_anvi_nogcn import train_anvi_nogcn
#from .trainer_atac import train_atac
def train(model, adata, epochs = 50, learning_rate = 1e-2, batch_size = 200, grad_clip = 1000, shuffle=True, test=0.1, na... |
cbf5038d00768bf2032fa14e7a7079b70db9fa233e98d2e4b89a28d4d5e7357d | Python | 1,722 | 52 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri May 3 15:48:55 2019
@author: epnevmatikakis
"""
from caiman.paths import caiman_datadir
from caiman.utils.utils import load_graph
import os
import numpy as np
try:
os.environ["KERAS_BACKEND"] = "tensorflow"
from keras.models import model_from_... |
6b54d84f48f95825df9ffb03f577270d18ec9f7266fd122b12c126661757c641 | Python | 1,723 | 56 | import numpy as np
import gzip
import pandas as pd
import os
def gen_GCTA_GRM(M, GRM, outpath):
"""
Generate the lower triangle indexed GRM text files for GCTA or OSCA reml analysis.
Parameters:
- info: A dictionary to store relevant information.
- M: Number of SNPs/Vertices used for calculati... |
bfddd5d4302688e29182cdaf3ce0f521445c062a01301229cc2c1efcdcbb7b54 | Python | 1,723 | 69 | '''
Distributed training related functions.
From DeiT.
'''
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
def is_dist_avail_and_initialized():
if not dist.is_available():
return False
if not dist.is_in... |
e20483a090dcd45111559e5eb0690a59fe57626b1394f32c0c75d7d1d52348b5 | Python | 1,724 | 64 | import numpy
import torch
import scipy
import scipy.sparse as sp
import logging
from six.moves import xrange
from collections import OrderedDict
import sys
import pdb
from sklearn import metrics
import torch.nn.functional as F
from torch.autograd import Variable
from pdb import set_trace as stop
def compute_aupr(all... |
12b6bd324f4b2c1f3da716b2886dc9f14a4170bdb6b353519bcdcbdbb31cd114 | Python | 1,725 | 53 | import torch
from torch import nn
import torch.nn.functional as F
class CNN_LSTM(nn.Module):
def __init__(self, num_hiddens, num_layers=1, bidirectional=False, **kwargs):
super(CNN_LSTM, self).__init__(**kwargs)
self.conv = nn.Conv1d(1, 32, kernel_size=20, padding=5, stride=5)
self.bn = nn.BatchNorm1d(32)
se... |
1e12b14a2ddc4dc8dbb7e9fa711e6bcb6ea0b22235b7a1838733ac8a90952c20 | Python | 1,725 | 49 | #!/usr/bin/env python
#!/usr/bin/python
import speech_data
import layer
from layer import *
# Training Step: 544 | total loss: 0.15866
# | Adam | epoch: 034 | loss: 0.15866 - acc: 0.9818 -- iter: 0000/1000
# 98% Accuracy on training set in just a minute
# audio = pyaudio.PyAudio()
# # format=pyaudio.paFloat32
# form... |
790a5f0d0f24bbf446a6affa4b6938e450f2874f003d68aa8bf539750706e342 | Python | 1,727 | 80 | from ray import serve
import time
import os
# __updating_a_deployment_start__
@serve.deployment(name="my_deployment", num_replicas=1)
class SimpleDeployment:
pass
# Creates one initial replica.
serve.run(SimpleDeployment.bind())
# Re-deploys, creating an additional replica.
# This could be the SAME Python scr... |
48bad8512ffbbf81a653222d9402b3f24f7bf3c07e392bf53bb360233eff3d7f | Python | 1,728 | 52 | from __future__ import print_function
import argparse
import glob
import numpy as np
import os
def parse_args():
parser = argparse.ArgumentParser("Summarize VCFEval summaries")
parser.add_argument('--input', '-i', dest='input', default=None, required=True, type=str,
help='Glob matching s... |
9a0a6e8e3a1510322ac20503742ca662df139c58c98025575fc520272f6da381 | Python | 1,728 | 67 | import os
import matplotlib.pyplot as plt
import boto3
from neuron_morphology.morphology import Morphology
from neuron_morphology.swc_io import (morphology_from_swc, morphology_to_swc)
s3 = boto3.client("s3")
def collect_morphology(bucket: str,
swc_key: str):
swc_response = s3.get_objec... |
b67f31a4c2d88c0dc044f6ff8eb9445f3b64863779bcbd443ca88cd16528784e | Python | 1,728 | 55 | class Params(object):
def __init__(self, **kwargs):
self.inhibition = None
self.n_days = 30
self.record_on_days = [0, 29]
self.neuron = {
'N_E': kwargs.get('N_E', 20000),
'N_I': kwargs.get('N_I', 5000),
'c': kwargs.get('c', 0.04),
'g': ... |
40fe74c945337a8b5d56c6c9c176ad18ff729819951322fa3c996a26d3bdd86b | Python | 1,729 | 44 | from typing import TYPE_CHECKING, Iterator
from ray.data._internal.object_extensions.arrow import raise_on_pickle_object_columns
from ray.data.block import Block
from ray.data.datasource.file_based_datasource import FileBasedDatasource
if TYPE_CHECKING:
import pyarrow
import pyarrow.fs
class ORCDatasource(F... |
d16dd5dff5e2ef0393e70176cca76b34d0851106e8ec4f8ef523e9415bd8f9ca | Python | 1,729 | 56 |
import os
import swap_errors.figures as swf
if __name__ == "__main__":
fig_data = {}
save_fig_templates = ("fig-{}.svg", "fig-{}.pdf")
os.chdir("/burg/home/wjj2109/analysis")
fig_key = "pro_lm"
fig = swf.ProLMFigure(data=fig_data.get(fig_key))
fig.panel_color_cue()
fig_data[fig_key] = fig... |
3eede96274fa73c31cf309e82b07d91753fed3f8a3ff0718acf9053d487e3c46 | Python | 1,730 | 67 | # flake8: noqa
# __import_start__
from starlette.requests import Request
import ray
from ray import serve
# __import_end__
# __model_start__
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
@serve.deployment(num_replicas=2, ray_actor_options={"num_cpus": 0.2, "num_gpus": 0})
class Translator:
def... |
512a832976f842edb0e350258778ef72036f98292c5bb75fe047e429d1e611f5 | Python | 1,730 | 53 | '''
check if we can cluster the scene vectors
in particular, can we derive good clustering parameters from the training set
and generalize to the validation set
this is essential for the clustering based shortcut model to work
'''
import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
imp... |
5fa9a125a5dbd0663deb03e41d2ba260f5ed24cc9e4bb263d7929fdfa976e9cb | Python | 1,730 | 57 | from sklearn.linear_model import LinearRegression
import pandas as pd
import argparse
import os
parser = argparse.ArgumentParser()
masks = ["true", 'false']
parser.add_argument('-k', '--mask', type=str, choices=masks, required=False, default="false",\
help='whether to use masked dataset. default=f... |
8df7accaf224dc4d7cac007c6f8934ab1213190b2b87c273d7565cbf1012191a | Python | 1,731 | 42 | from timm.loss import LabelSmoothingCrossEntropy, SoftTargetCrossEntropy
from torch.nn import CrossEntropyLoss as CE
import torch
from torch.nn import MSELoss as MSE
from .losses import FocalLoss, FocalLoss_L2, dice_loss, CE_dice, CE_L1, DecadeCELoss, HuberLoss
def criterions(cfg):
criterion_type = cfg.crit... |
b9dbfd625a3011b545457b5f17cdb30e517955ae17492cb13a218fb7393a17cc | Python | 1,731 | 41 | from model import (IntraEncoder, InterEncoder, ProteinInteractionNet, Tester)
from uncertaintyAwareDeepLearn import VanillaRFFLayer
from utils import (
load_configuration,
set_random_seed,
get_computation_device,
evaluate
)
import torch
def main():
# --- Pre-Training Setup ---
# Load configs. ... |
07ea2d76fcce673ba45195b688f28bbe46a09bada5af514afe80e0e8359ed79e | Python | 1,732 | 50 | """FAISS padding is not an identity when the requested gallery is too small."""
from unittest.mock import MagicMock
import numpy as np
import pytest
faiss = pytest.importorskip("faiss")
from deepface.modules import datastore
@pytest.mark.parametrize("normalized", [False, True])
@pytest.mark.parametrize("similarit... |
cd093a00d1266ddf36137d6ab1f313149920909b6c753b9f71a90f64376aebf7 | Python | 1,733 | 36 | ####################################################################################################
# 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... |
1213014aaa74eb8325709f982da6dabc960c04af4e879db1c317497148b3ed84 | Python | 1,735 | 62 | from pathlib import Path
import spectral as sp
from siapy.entities import SpectralImage
from siapy.entities.images import SpectralLibImage
# 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 da... |
4218b0cf5f555abd0996dc8f9ab6289d0efc5f9f6201a11ed9899d882b193cfb | Python | 1,736 | 44 | import csv
import neuron_morphology.constants as constants
from neuron_morphology.validation.result import InvalidMarkerFile
from neuron_morphology.validation.result import MarkerValidationError
class Marker(dict):
""" Simple dictionary class for handling reconstruction marker objects. """
def __init__(self,... |
9249dd305fa42f4a36d0d534bd14bae07e3b11bf852e63300aabe18c74e7a064 | Python | 1,736 | 61 | import time
import ray
from ray.util.metrics import Counter, Gauge, Histogram
ray.init(_metrics_export_port=8080)
@ray.remote
class MyActor:
def __init__(self, name):
self._curr_count = 0
self.counter = Counter(
"num_requests",
description="Number of requests processed b... |
b3cbe86b0fdf636596aa42098338a4ab33c70f6d967fe9a84bbb98cf859d4c71 | Python | 1,736 | 46 | import json
import logging
from datetime import datetime
from agent.data.entities.config import ROOT_LOGGER_ID
from agent.data.sql.sql_mgmt import get_connection
from agent.crawlers.snopes_crawler import crawl as crawl_snopes
from agent.crawlers.politifact_crawler import crawl as crawl_politifact
from agent.crawlers.... |
edb61426f2c985d4159964a6c2b7a982a4cd8528e1ec13d09c8591ec7926a1a4 | Python | 1,736 | 46 | from setuptools import setup
short_description = "AP-Net is an atomic-pairwise neural network framework for modeling interaction energies"
try:
with open("README.md", "r") as fp:
long_description = fp.read()
except FileNotFoundError:
long_description = short_description
setup(
name="apnet",
v... |
edbc5bd4dd5000ea61fdcecebdb0d8e13fcddcef7f9ac7c79638be021ba14d5a | Python | 1,737 | 61 | """
This script is used to clean up state after running test scripts, including
on external services. For instance, this script can be used to remove the runs
from WandB that have been saved during unit testing or when running examples.
TODO: can we remove this file?
"""
import sys
def clear_wandb_project():
imp... |
2989f960613822c29303fd5728805f2566cfb9acc626012b232bc125a8c7d452 | Python | 1,738 | 39 | ####################################################################################################
# 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... |
e3d66f528d65f88a742fee851d455666c050b1ade2ef8d94675206f6768ef76e | Python | 1,738 | 74 | import numpy as np
import pandas as pd
import pdb
import matplotlib.pyplot as plt
from scipy.interpolate import interp1d
def main():
#sensors_locations = [
# '02', '04', '05', '10', '12', '13', '14', '15', '17', '19', '21'
#]
sensors_locations = [
'04', '10', '13', '14', '15', '17', '19', '... |
856f13003dd92cf507d1f81968ea02fa3bc7e57e938fccd05bea4f40ca0370f7 | Python | 1,739 | 42 | import timeit
import argparse
from Bio import SeqIO
from pyrosetta import *
parser = argparse.ArgumentParser(description="Perform FastRelax on predicted protein structure")
parser.add_argument("--input", type=str, help="input unrelaxed model")
parser.add_argument("--output", type=str, help="output model (.pdb f... |
af9d0757ec1c7f09e59db18260cdd0fadba65156ea9c058db04200d3309767c0 | Python | 1,739 | 52 | import warnings
from typing import Union
from mmengine.config import ConfigDict
from mmengine.dataset import (ClassBalancedDataset, ConcatDataset,
DefaultSampler, InfiniteSampler, RepeatDataset)
ConfigType = Union[dict, ConfigDict]
def process_debug_mode(cfg: ConfigType) -> ConfigType:... |
1f5eee80264cf1649e984c4ee5d668243c93c4e2c08dfe19c3ce383b5173eac0 | Python | 1,740 | 77 | import torch
import collections
import pdb
import csv
from kipoi.data import Dataset
import math
import numpy as np
class HMData(Dataset):
# Dataset class for loading data
def __init__(self, input_file, bin_size=100):
self.hm_data = self.loadData(input_file, bin_size)
def loadData(self,filename,windows):
with... |
2bae153b4f3a339038dba0ec630c2ce3bedad3766240efe6c72074e238b93183 | Python | 1,740 | 40 | """Read BrainVoyager vmr and export nifti."""
import os
import numpy as np
import nibabel as nb
import bvbabel
import pprint
FOLDER = '/Users/sebastiandresbach/data/neurovascularCouplingVASO/Nifti/derivatives/rawdata_bv/sub-05/ses-01/anat'
# FILE = f"{FOLDER}/sub-05_ses-01_uni_part-mag_run-01_MP2RAGE_denoised_IIHC_p... |
3d57a2b18d13399b76258937e4a35567546e75882e8c9adce8b9c272eb64792d | Python | 1,741 | 51 | import os
from importlib import resources as impresources
from pathlib import Path
import pandas as pd
from ... import bids
from ...bids.convert2bids import BidsConverter
from ...load_annotations.siena import loadAnnotationsFromEdf
BIDS_DIR = impresources.files(bids)
DATASET = BIDS_DIR / "siena"
def convert(root: ... |
f4b84c76302bc6a094d313f001430bedad91e1b8855c79a78f90c0c9da243e4f | Python | 1,741 | 49 | import intel_extension_for_pytorch as ipex
import torch
from PIL import Image
from diffusers import StableDiffusionPipeline
def image_grid(imgs, rows, cols):
assert len(imgs) == rows * cols
w, h = imgs[0].size
grid = Image.new("RGB", size=(cols * w, rows * h))
grid_w, grid_h = grid.size
for i, ... |
58479f1ad112e2fa68190cf05b006de2f11ddeb81605d6ebbb2726f58967dcf3 | Python | 1,742 | 53 | """
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 typing import TypeVar
import pandas as pd
from fairchem.core.components.benchmark import JsonDFR... |
e8854b795ea4b38c608ef4b8c46672303bb16e53afd20a2a229cc9eba0b639f6 | Python | 1,742 | 47 | import os
import numpy as np
import nibabel as nib
import IVIMNET.deep as deep
from hyperparams import hyperparams as hp
root = '/mnt/d/fc-ivim-estimation'
input_root = os.path.join(root, 'data')
output_root = os.path.join(root, 'results')
subs = os.listdir(input_root)
times = []
for sub in subs:
input_folder = ... |
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