sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
dd970577888d98fa0ebf91db2e9f2e22932cc4b5ff9cd8af681fb247cadd32a0 | Python | 3,353 | 109 | #!/usr/bin/env python3
# Copyright 2004-present Facebook. All Rights Reserved.
import torch.nn as nn
import torch
import torch.nn.functional as F
class Decoder(nn.Module):
def __init__(
self,
latent_size,
dims,
dropout=None,
dropout_prob=0.0,
norm_layers=(),
... |
753913dfbcd23bbf3e2849dfe5d98311451b46955a80037f5788086b435486f1 | Python | 3,354 | 88 | # -*- 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.
#... |
26f01a461ba708d954888a36b0ae135d6bc48c6e615f26e98a03553259631ec9 | Python | 3,355 | 95 | # Copyright (c) 2017-present, Facebook, Inc.
#
# 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 applicable law or agreed... |
61fa92c5141324ed9ec1d9a1484c683394405e37b0235cddcb9339f686c721ab | Python | 3,358 | 97 | # -*- coding: utf-8 -*-
"""
Created on Thu Dec 10 18:19:00 2020
@author: ju-bar
Functions related to work with crystal structures
This code is part of the 'emilys' repository
https://github.com/ju-bar/emilys
published under the GNU General Publishing License, version 3
"""
import numpy as np
from emilys.optics.econs... |
9bc66ce763609ef1c54884d1f23c836d69e90f6461ba02a543ce31d87a917f7e | Python | 3,358 | 92 | # Ultralytics YOLO 🚀, GPL-3.0 license
import contextlib
import glob
import os
import urllib
from datetime import datetime
from pathlib import Path
class WorkingDirectory(contextlib.ContextDecorator):
# Usage: @WorkingDirectory(dir) decorator or 'with WorkingDirectory(dir):' context manager
def __init__(self... |
445b1b8013fd1fffc9b994cd88b01d41fed9634f9567a76cc7d9c2eaf7efd0e8 | Python | 3,360 | 115 | # -*- coding: utf-8 -*-
"""
"""
import numpy as np
import os, sys
import re
import pytest
import vtkplotlib as vpl
from matplotlib import cm
pytestmark = pytest.mark.order(0)
# Target output. Everything below should normalise to this.
RGB, A = (np.array([0.00392157, 1., 0.02745098]), .5)
paramet... |
b20a0b2116d8659e74b0cddeace44f290a49d17de953e74c11c55445afb59950 | Python | 3,360 | 100 | from __future__ import annotations
import asyncio
import time
from dataclasses import dataclass, field
from typing import Dict, List, Optional
from .models import ConversationRoute, MessageEnvelope, RuntimeTaskState
@dataclass
class _RegistryEntry:
route: ConversationRoute
task: Optional[asyncio.Task] = Non... |
408d8eccfa2f974f6a8627d7133af0f8d801d17060aa589a3a2bf5eaba4bc036 | Python | 3,362 | 136 | import pdb
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import torch
import yaml
from scipy.interpolate import interp1d
from data_assimilation.particle_filter.observation_operator import ObservationOperator
from data_assimilation.true_solution import TrueSolution
TEST_CASE = 'wave_submerged_... |
dfb2c20fa85da9e8ff578e0f3140a91696c356a1cc87c067795269af6ae19a00 | Python | 3,362 | 66 | __author__ = "Simon Andermatt"
__copyright__ = "Copyright (C) 2017 Simon Andermatt"
from tensorflow_extra_ops import caffebicgru
import tensorflow as tf
from helper import get_modified_xavier_method
def CaffeBiCGRU3D(inp,dimension,outC,form,dropconnectx=None,dropconnecth=None,filterx=None,filterh=None,bias=None,fsy=... |
9f4fadc7d4e21a30443da97e4285c0c4c56a7f54c55c2a682f92655717b9888b | Python | 3,363 | 60 | #--------------------------------------------------------------------
# Author: Brandon Coventry, PhD Wisconsin Institute for Translational Neuroengineering
# Date: 12/23/23
# Purpose: This is to demonstrate Bayesian Estimation Supercedes the T-Test in PyMC
# For group comparisons. See the original Kruscke paper: https... |
8c0bcb423cffdf2cbe6299e65b613bad6edeb8f754d70d27cc27bbb799b9f44e | Python | 3,365 | 134 | import os
import subprocess
seed_list = [2222, 3333, 4444]
snn_ratio = [0.05, 0.15, 0.25, 0.35, 0.45, 0.5, 0.55, 0.65, 0.75, 0.85, 0.95]
log_folder_path = "./log/"
dataset = "nmnist"
rnn_type = "rnn"
def extract_one_performance(model, seed, ratio=None):
if model == "rnn" or model == "lstm" or model == "snn":
... |
f2172e3bceefb72fa8f3c6e70ce46d09e5de6fea2589a47d886177545957d118 | Python | 3,365 | 111 | import ipywidgets
import exputils as eu
class CodeProducerWidget(ipywidgets.Box):
@staticmethod
def default_config():
dc = eu.AttrDict()
dc.code_templates = []
dc.main_box = eu.AttrDict()
dc.title = 'Code Production'
dc.accordion = eu.AttrDict(
selected_... |
220dbfec2eb122a4434c5fef4f837063b1cc900be2e1fe05541027f252016b46 | Python | 3,366 | 102 | """load annotations from the TUH Sz Corpus dataset https://isip.piconepress.com/projects/tuh_eeg/downloads/tuh_eeg_seizure/ to a Annotations object."""
import os
from pathlib import Path
import pandas as pd
import pyedflib
from ..annotations import Annotation, Annotations, EventType, SeizureType
def _loadSeizures(... |
2458602ac6c126f729953e48f4cfb8bbdec4b367eca6f259e2af77732400067c | Python | 3,367 | 106 | import matplotlib.pyplot as plt
filenames = {
"STYP.w_filter": "C:\\Users\\psinitcyn\\Desktop\\Experiments\\STYP.w_filter\\20230927_152846_STYP_HEK293_w\\STYP_HEK293_w_-PTMSiteReport.tsv",
}
aas = "YTSP"
mod_title = "Phospho (STYP)"
aas_colors = {
"Y": "#A8A9AD",
"T": "#6D6D70",
"S": "#3F3F... |
07168625633ff98118c6e15818499272604f29c6e10100cc623f7ee10d67194d | Python | 3,368 | 78 | import argparse
import mrcfile
import sys
import torch
import numpy as np
from numpy.typing import NDArray
from pathlib import Path
from .ode_net import ODENet
from .particles import particles
from .gridding import Gridding
def parse_args():
parser = argparse.ArgumentParser(description = 'CryoTRANS: Predicting hig... |
5eb53a65589cbaec6fa5e9fae9433e9d05f6f7dc833440a5a9a3e0b22fffb2fd | Python | 3,368 | 117 | # Copyright (c) 2021 Qualcomm Technologies, Inc.
# All Rights Reserved.
# pylint: skip-file
# type: ignore
from torch import nn
from aihwkit.simulator.digital_low_precision.base_quantized_classes import (
QuantizedModule,
_set_layer_learn_ranges,
_set_layer_fix_ranges,
_set_layer_estimate_ranges,
... |
9c10826f178c241aa09a60a89647061e52abe1d37dbe563a98d51d282b25d39c | Python | 3,370 | 94 | # -*- coding: utf-8 -*-
import numpy as np
from scipy.optimize import linear_sum_assignment
import wandb
def acc(y_true, y_pred):
"""
Calculate the accuracy of clustering results by finding the best match
between the cluster labels and the true labels.
Args:
y_true (numpy.ndarray): The true l... |
f3cdd585d4a893736bd0ca0f0045aac17dfa256ee0d3d1fa821c0c1579089a00 | Python | 3,370 | 61 | import numpy as np, pandas as pd, json, itertools
from scipy.optimize import minimize
from scipy.special import gammaln, logsumexp
import os
R=os.environ.get("CAZALE_RAWDATA", os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "data", "Cazale-Debat-Scheunemann-et-al", "RAWDATA"))+os.sep
STAGE={"orientated":... |
26963ff3b5a57713f253d600e20c1dded493b564df0d62c45b196102e1d7292b | Python | 3,371 | 84 | """
Compare first FA loading to the delta mu axis
for each target (vs. catch)
"""
import os
rdir = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
import sys
sys.path.append(rdir)
from settings import RESULTS_DIR
from helpers.path_helpers import local_results_file
import scipy.stats as ss
import pandas as... |
3aabc1a81e8b55341be7a291faf9c0bfea2a872027d07e601957c4bed19cd260 | Python | 3,373 | 109 | r"""
PopV: Population-level Variation analysis for single-cell data.
PopV is a framework for analyzing population-level variation in single-cell data,
focusing on automated cell type annotation, batch integration, and algorithm
benchmarking. It provides a unified interface for comparing and evaluating
different singl... |
c1cc150d249944d7c0e9ce01243cc94c9e26bb98dae61e9c754a747392f2a6b5 | Python | 3,373 | 123 | import logging
import re
import shutil
import subprocess
import tempfile
from pathlib import Path
from pokeformer.utils.pdb_utils import (get_biopdb_struct, read_pqr,
write_clean_pdb)
logger = logging.getLogger(__name__)
def run_fpocket(
pdb_path,
print_info=False,
... |
f01fa1b893559ea73f3aeeaf0b803e1753923648d14bc4b317976a5b3952928f | Python | 3,373 | 105 | """Single source of truth for modules mocked during API doc generation.
Three consumers import from here so they agree on what "not installed in the
docbuild image" means:
- ``conf.py`` -- Sphinx ``autodoc_mock_imports`` for the full ``make html``
build.
- ``api_autogen.py`` -- the standalone autosummary stub gener... |
401bf828f3b448b16a816e79b0f637336f819ffef9db6fb77de49115a5805a07 | Python | 3,374 | 80 | from dataclasses import dataclass, field
from typing import Any, Dict, Optional, Tuple
import pyarrow as pa
from ray.data._internal.datasource_v2.common.arrow_file_scanner import ArrowFileScanner
from ray.data._internal.datasource_v2.formats.parquet.parquet_file_reader import (
ParquetFileReader,
)
from ray.data.... |
8957946a573ef90414f42f15f110e8b36fcfdaf176064a9f09517d82764e7c87 | Python | 3,376 | 125 | # Import the task(s) you want to use.
import torch
from tqdm import tqdm
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from m2snn.multisensory import (
DetectionTask,
ClassicalTask,
ComodulationTask,
BalancedComodulationTask,
)
from m2snn.spikes import SpikingMultimodal
from... |
8d6be7b5a703211183ebe76ee88a590b96c526738b25af2944e5b0385034e4ee | Python | 3,377 | 111 | # -*- encoding: utf-8 -*-
from __future__ import division, print_function
from scipy.linalg import toeplitz
import numpy as np
from .core.scoring import aggregate_by_segment
from .core import scoring as _scoring
from .utils import where_diagonal
sums_by_segment = aggregate_by_segment
def _corner_matrices(A):
Hup... |
409e321416bbbccd4ebe718ac759327653c96b75210d85af92fec5250ad366a7 | Python | 3,378 | 105 | # flake8: noqa
# fmt: off
# __task_exceptions_begin__
import ray
@ray.remote
def f():
raise Exception("the real error")
@ray.remote
def g(x):
return
try:
ray.get(f.remote())
except ray.exceptions.RayTaskError as e:
print(e)
# ray::f() (pid=71867, ip=XXX.XX.XXX.XX)
# File "errors.py", lin... |
9c6b0edfc0876f2fa93fe5c812bcd924ecabf1fbcefb7a0ee2dab343cec63c70 | Python | 3,379 | 105 | import os
import json
from io import BytesIO
import boto3
from neuron_morphology.transforms.tilt_correction.compute_tilt_correction \
import (run_tilt_correction, read_soma_marker)
from neuron_morphology.swc_io import (morphology_from_swc)
from neuron_morphology.transforms.affine_transform \
import (AffineTra... |
c20741b9c42d771089729a8d6c70e4463b6e5051c8476222f0fc19538f2558bf | Python | 3,379 | 131 | import pandas as pd
import numpy as np
import pickle
import nltk.stem as ns
import pdb
from tqdm import trange
ALPHA = 0.66
LAMBDA = 1
def tokenize(sent):
sent = sent.lower()
sent = sent.strip('.')
lemmatizer = ns.WordNetLemmatizer()
sent = sent.replace("'s", '')
sent = sent.split(' ')
for it... |
12686c691d98fe8eb37c8a9b190f8e0d8cb8cd1b0e4c8603efb5f8a17d33b0c8 | Python | 3,382 | 92 | # Copyright 2021 Division of Medical Image Computing, German Cancer Research Center (DKFZ)
# and Applied Computer Vision Lab, Helmholtz Imaging Platform
#
# 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 L... |
1d5536a2d01d2909cee38b085c7072391bfa6787b407c0884300c7ef26c61b8e | Python | 3,383 | 75 | ####################################################################################################
# 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... |
7b24b1d38b14d9ff9e94e1f5a62755f78e8e2cc08139029202fd2b1fc44cd510 | Python | 3,383 | 113 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import sys
import pandas as pd
import pysam
import svtk.utils as svu
def final_filter(vcf, bed, chrom=None):
bed = bed.set_index('name')
new_variant = ((bed.operation == 'add-mosaic-variant') |
(bed.operation == 'add... |
b2c756852c81b750e7e55e66209bb804696efe808a13e9cdd06c4bb957c79947 | Python | 3,383 | 95 | """
STEP ONE
data_pth needs to be customised
Export mov.csv from angle.mat files
Save envelopes of EMG data and raw EMG data
"""
import os
import pickle
import sys
import numpy as np
import pandas as pd
import scipy.io as sio
from scipy import signal
# subject and protocol info
subject_id = sys.argv[1]
protocols ... |
b41d8b3d04bf847df2d659f9a90caf898a19483c31a19dce50fdb11b47983c5f | Python | 3,385 | 90 | # Copyright 2023 Google Brain and 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 requ... |
20637048dd347c328b61e0173d38b69b7239b0e0c46090599d8b9f036b845090 | Python | 3,388 | 116 | # flake8: noqa
import os
from filelock import FileLock
import torch.nn as nn
import torch.nn.functional as F
from torchvision import datasets, transforms
EPOCH_SIZE = 512
TEST_SIZE = 256
def train_epoch(model, optimizer, train_loader, device=None):
device = device or torch.device("cpu")
model.train()
fo... |
a680a3abf59775dd6644d10eee22e96786d2e9d0ba0a70be7076db4afdc262f5 | Python | 3,388 | 86 | import numpy as np
import pytest
import xarray as xr
from flyvis.analysis.moving_bar_responses import (
angular_distance_to_known,
correlation_to_known_tuning_curves,
peak_responses,
preferred_direction,
)
from flyvis.utils import groundtruth_utils
CELL_TYPES = ["T4a", "T4b", "T4c", "T4d", "T5a", "T5b... |
cb1ef5e53420c9204cbc899dab08e33629393729e8fa4eaad16c7b8e27148db0 | Python | 3,388 | 109 | """Dataset for cells"""
from itertools import zip_longest, product, chain
import random
import numpy as np
import torch
from torch.utils.data import Dataset
from torchvision.transforms.functional import (pad, to_tensor, normalize,
hflip, vflip, crop)
from PIL import Image... |
1b8fb8012e02e8d86b449607fce44fdab1da24efe98dd75d7e11d44dc49bf19d | Python | 3,390 | 116 | #!/bin/env /usr/local/package/python/3.10.5/bin/python3
# usage: python _run-cmfinder-h0.py <cmsearch_output> <test.fa>
import sys
from util import *
ifname = sys.argv[1]
faname = sys.argv[2]
def get_correct():
correct = {}
with open(faname) as fi:
for l in fi:
if l.startswith(">"):
... |
448093de386eee5593ded91a2ecb43010d6fdda1b6b9dad92545f7238704a223 | Python | 3,390 | 101 | """
Create a cluster of GPU nodes to perform parallel prediction of tiles
"""
import argparse
import sys
import socket
import subprocess
from dask_jobqueue import SLURMCluster
from dask.distributed import Client
import gc
def collect():
gc.collect()
def args():
parser = argparse.ArgumentParser(
descri... |
be5df373dac80a3ea34375c6a46da7ef5bd1dca1a2099b2077837daef0cb66f6 | Python | 3,391 | 114 | from collections.abc import Sequence
import numpy as np
from .typing import Types
def parse_shape_argument(x: Types, key: str):
"""Parse the shape argument of a NIR node."""
if isinstance(x, np.ndarray):
return {key: x}
elif isinstance(x, Sequence):
return {key: np.array(x)}
elif isi... |
74379bf15a6a75d8d695f9dc423f45bf3dd1ee8a651970bff7a8b2b593546d4b | Python | 3,393 | 95 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
"""Helper for retrieving Metrics of an Experiment."""
from datetime import datetime
from typing import Dict, List
class LocalMetric:
"""Metric for local e... |
ee33053398601f3663ae002810440979500a37c44269d60bbde9d260a9b1ea96 | Python | 3,393 | 104 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
def plot_dense_sensordata(dense_data, ax=None, show=True, show_missing=False, time=None, text=None, ylabels=True):
"""view single patient's worse of dense sensordata, a ndarray or df
where the columns are: heart_rate, activity_rank, resp_pa... |
1e72976600cc6654597d21ee75ef0d775a8b5f63ffc55d42eca665066c6f899a | Python | 3,394 | 90 | from typing import Optional, Union
import torch
from .lif import LIF
from .reshape import SqueezeMixin
class ExpLeak(LIF):
"""Leaky Integrator layer which is a special case of :class:`~sinabs.layers.LIF` without
activation function.
Neuron dynamics in discrete time:
.. math ::
V_{mem}(t+1)... |
dbc874e683cb7941de777cabdca701b42e7100c10174cb2182d9b789e2719487 | Python | 3,394 | 124 | from scipy.io import loadmat
from scipy.special import erfcinv
import numpy as np
import pandas as pd
from scipy.stats import kruskal
from itertools import combinations
def star(p_val):
assert 0 <= p_val <= 1
if p_val >= 0.05:
return 'ns'
if p_val >= 0.01:
return '*'
if p_val >= 0.... |
e5e23c56ffcfed501e4b48c67c75f7f1c3d2cd0c97efff02bb7eef46d8bb7570 | Python | 3,394 | 109 | # docs/source/conf.py
from __future__ import annotations
import os
import sys
# -- Path setup --------------------------------------------------------------
# If your package uses a src/ layout, add it so autodoc can import flowsig.
sys.path.insert(0, os.path.abspath("../../src"))
# -- Project information ----------... |
293df0d681113458c4adf6b333a26036738c905df74c48f5b50f95eb1177045e | Python | 3,396 | 134 | import os
import subprocess
seed_list = [1111, 2222, 3333, 4444]#, 5555]
snn_ratio = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9]
log_folder_path = "./log/"
dataset = "ptb"
rnn_type = "rnn"
def extract_one_performance(model, seed, ratio=None):
if model == "rnn" or model == "lstm" or model == "snn":
fi... |
93ab3891fdcc6039e4594daa982cf70947f5d97ba1e39da2ec33b69b763dcd28 | Python | 3,396 | 138 | #!/usr/bin/env python
import subprocess
import skimage.io
import traceback
import numpy
import numpy as np
import os
import sys
from os import system
from platform import system as platform
import skimage.io
import wave
import pyaudio
import matplotlib.pyplot as plt
plt.matshow([[1,0],[0,1]], fignum=1)
plt.draw()
if... |
b2d5789cf42c9b1e3e6333f3e92eb2f147dde268ca784e0d084a595c044a26dc | Python | 3,396 | 85 | import pandas as pd
import os
import sys
project_root = '/ccb/cybertron/khchao/splam-analysis-results/'
output_dir = f'{project_root}train/results/RefSeq_ALTS/BAM_REF_Intersection/'
def get_hg38_chrom_size():
f_chrs = open("../hg38_chrom_size.tsv", "r")
lines = f_chrs.read().splitlines()
chrs = {}
fo... |
de53a93ec1490183914b26206f52ec211826d6a8e3d5a42de62ccc4dd78db18a | Python | 3,396 | 100 | # -*- 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.
#... |
7d7ea986f5258360198482f03dc5f9ababa4b2790c3b0b5b75b5d68b27c5c3f7 | Python | 3,397 | 79 | import os
import sys
import argparse
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
from torch_pgn.train.run_training import run_training
from torch_pgn.train.hyperopt import hyperopt
from torch_pgn.args import TrainArgs, HyperoptArgs
DATASETS = ['pdbbind_general', 'pdbbind_refined', 'd4']
# SPLIT_TYPES = ['rando... |
3dbff3d9e7e85dfb2b4c6806a0ee8de60b08283a92857dfe5d348296cf4c6185 | Python | 3,398 | 109 |
import numpy as np
import scipy.stats as sts
import scipy.special as spsp
def fit_dprime_pts(
col_rep_dists,
col_diffs,
bhv_errs,
renorm_dists=True,
n_bins=10,
min_d=0,
max_d=5,
n_ds=1000,
filt=True,
n_samps=10000,
):
"""
Fit the dprime that best fits the behavioral re... |
3ab0bf8ad4d3ae418d7a4883aa3fac946018a533fa45f8b68be395ee0bf50955 | Python | 3,399 | 95 | import glob
import pathlib
import pickle
import endstate_correction
import mdtraj as md
import numpy as np
from endstate_correction.equ import calculate_u_kn
from openmm import unit
from openmm.app import CharmmParameterSet, CharmmPsfFile
from pymbar import MBAR
from openmm.app import Simulation
from typing import Tup... |
947aa0bb205f4e3af7b978c149310b9729e96b419bd4693f674b389823717c73 | Python | 3,400 | 92 | #!/usr/bin/python
"""Functions for merging multiple graphs."""
# Updated: 12/04/21
import numpy as np
import leidenalg as la
def compute_graphs(mod, plist, keep_all_z=True):
"""Compute graphs along a list of eigenvalue-power values."""
for power in plist:
graph_id = f'p{power}'
if graph_id not... |
ea15fdb1278cdd6c30a62f6f83ecc19664a7acd48f94b664476af90a4e682262 | Python | 3,401 | 84 | #!/usr/bin/env python
# Runs "mean absolute deviation" QC metrics on two long-RNA-seq gene quantifications
import os, subprocess, json
import dxpy
def divide_on_common(str_a,str_b):
'''Divides each string into [common_prefix,variable_middle,common_ending] and returns as set (parts_a,parts_b).'''
parts_a = [''... |
16f0bfdee4d853e0f761e2334367b50ef708ba474735031602e40e2284f693b0 | Python | 3,402 | 94 | """
To plot distribution of visit interval.
"""
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
version = "processed_data_2019-9-30"
info_df = pd.read_csv("../"+version+"/patient_visit_info.csv")
patient_df = pd.read_csv("../"+version+"/patient_info.csv")
entire_cohort = list(patient_df.PAT... |
3a33f02b871152e175dbd9f6ae0618d86ec55b96185fc732a8007cf7dd96c7ad | Python | 3,402 | 95 | # -*- coding: utf-8 -*-
from mozaik.storage.datastore import PickledDataStore
from mozaik.controller import Global
from parameters import ParameterSet
import mozaik
from mozaik.controller import setup_logging
import sys
from msa_analysis_plotting import *
from mozaik.storage.queries import *
# Usage: python run_analys... |
d11ea15ade40eddb79f6db367401622b764b36f90d526e143bed20c9855c488e | Python | 3,402 | 108 | import numpy as np
import torch
from scipy.sparse import csc_matrix, csr_matrix, issparse
from sklearn.utils import sparsefuncs
from torch.utils.data import Dataset, DataLoader, BatchSampler, SequentialSampler, RandomSampler
"""
Data streamlining.
"""
def streamline_count_matrix(x_raw, gene_names_raw, gene_names_mo... |
e5293163de5cf06c5424e40275480af7a11a6e2dd4da68b4f00b143b5d9328e9 | Python | 3,402 | 48 | import numpy
from mozaik.analysis.data_structures import SingleValue
from parameters import ParameterSet
from mozaik.storage import queries
import mozaik
from mozaik.analysis.analysis import Analysis
from mozaik.storage import queries
import quantities as qt
import logging
logger = logging.getLogger("mozaik")
class S... |
f5507a40dbddfacad9c1cfd1bd33bf4735f3fc6c8adfa7935483846f22a323c9 | Python | 3,402 | 118 | '''
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... |
6fbdecd6560c3dc8a59a5154e369cf086e4a956f65f667e1ae46e9623979b8af | Python | 3,403 | 91 | import os
import sys
from rdkit import Chem
from rdkit import DataStructs
def compare_molecules_inchi_match(
input_file_path: str, reference_directory: str
) -> None:
"""This function checks if the molecules in the DECIMER results to a set of
reference mol-files using Standard InChI.
Args:
... |
702552ab3568634358f89a63adae8dd53c895a67f9c158e13853930027549745 | Python | 3,404 | 81 | """
This script computes segmentation metrics (Dice, ...) using the MetricsReloaded package for nnUNetv2 results and saves
them as CSV files. One CSV file is generated for each GT-prediction pair.
It is necessary to download the MetricsReloader package from https://github.com/ivadomed/MetricsReloaded.git
Usage: pytho... |
819899d53adcb8d2f07914ea8fb83754f41cecb5deda7bfff4c3b5309b20f074 | Python | 3,404 | 123 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Retrieved from https://raw.githubusercontent.com/talkowski-lab/rCNV2/a8849b880e2c1e1d2c51f055d85fec07384886a2/data_curation/CNV/defragment_cnvs.py
# on May 14, 2020 and adapted for gatksv pipeline
"""
Perform local defragmentation of a CNV BED file
"""
import pybedt... |
9d5e2e8c7aae8989300389cb1957d415cf888bc166f10cb2df47cf08096f36f1 | Python | 3,404 | 105 | from collections import deque
import numpy as np
from gym import spaces
from pfrl.env import VectorEnv
from pfrl.wrappers.atari_wrappers import LazyFrames
class VectorEnvWrapper(VectorEnv):
"""VectorEnv analog to gym.Wrapper."""
def __init__(self, env):
self.env = env
self.action_space = se... |
c80e69b4fd75bc6c367bad76db402d77996cd8b5bf2dd49347eb3245ba7dbb00 | Python | 3,405 | 86 | # coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# 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 applicable law or ag... |
f601c89594d0ee91ba601c3427ae1a0d0c8bfacff13753be61a7d8863a4fb549 | Python | 3,405 | 89 | from Bio import SeqIO
import random
import os
import sys
from pathlib import Path
import pandas as pd
def get_hg38_chrom_size():
f_chrs = open("../src/hg38_chrom_size.tsv", "r")
lines = f_chrs.read().splitlines()
chrs = {}
for line in lines:
eles = line.split("\t")
chrs[eles[0]] = int(e... |
9ff7a4c02349eca773a8317f07b0bf726dafce84685a55d96883ef04875f417c | Python | 3,406 | 94 | """The built-in synthesized columns: ``path`` and ``row_hash``.
The interface they implement, :class:`SynthesizedColumn`, and its input
:class:`ReadUnitPosition` live in
:mod:`ray.data._internal.datasource_v2.interfaces.synthesized_columns`.
"""
import hashlib
from dataclasses import dataclass
import numpy as np
imp... |
ce30f7df03b9b879baa92e02cb12826d2c4a7b619873ee6180bc44afdf5a3fc7 | Python | 3,406 | 111 | """
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
import multiprocessing as mp
import os
import pickle
import ase
import ase.io
import n... |
e56722bdb7ee447cd4c380663be35cc5a6fc1e7b093c14366cc409db8d131e7b | Python | 3,408 | 136 | import sys
import pytest
from ray._common.retry import (
call_with_retry,
retry,
)
def test_call_with_retry_immediate_success_with_args():
def func(a, b):
return [a, b]
assert call_with_retry(func, "func", [], 1, 0, "a", "b") == ["a", "b"]
def test_retry_immediate_success_with_object_args... |
2cb3b1825835c809f09107035f4c99aa7a6d851c47027cee91b937e8fddd0b31 | Python | 3,410 | 91 | # Copyright (c) 2017-present, Facebook, Inc.
#
# 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 applicable law or agreed... |
6a6ad3b4a6dffe0265d4e6629ae79498f80360d8c8ee32caf19332d744874a8c | Python | 3,410 | 116 | import sys
import numpy as np
from multiprocessing import Pool
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation as kp # Import custom utility functions
def setting_ps():
"""
Define the ps (perco... |
a997b8b1bc64b3c9b19f6500088d4098b2366215c8e96ecc55d36cfc5294e068 | Python | 3,410 | 76 | import re
import sys
import os
# polyA
colname = ["", "base_s", "base_p", "exon_s", "exon_p", "intron_s", "intron_p", "intron_chain_s", "intron_chain_p", "transcript_s", "transcript_p", "locus_s", "locus_p", "matching_intron_chain", "matching_transcripts", "matching_loci", "missed_exons", "novel_exons", "missed_intron... |
13c679fbc18873769dc75681973c355049d63f5da502b49ee3697d0b9a0644ff | Python | 3,411 | 96 | # built-in dependencies
import os
from typing import Any, cast
# third-party dependencies
import numpy as np
from numpy.typing import NDArray
# project dependencies
from deepface.commons import folder_utils
from deepface.commons.onnx_utils import build_session
from deepface.commons.logger import Logger
from deepface.... |
e0a9c57218bffd44b23e6a90d22d3f300ccc848fc3cbd2b9b2e4dd36a78303ee | Python | 3,411 | 72 | import numpy as np
import tensorflow as tf
class Dataset:
def __init__(
self,
data_name,
logging_dir,
flatten,
ttfs_convert,
ttfs_noise=0,
):
self.name = data_name
self.flatten=flatten
self.noise=ttfs_noise
self.logging_dir=loggin... |
0b26eb5cfbbd59b1fead21f6f87eca7fe0bbdb801d5346ca823fb5545d929d37 | Python | 3,413 | 96 | import importlib
import inspect
from types import ModuleType
from typing import List
from ci.ray_ci.doc.api import API, AnnotationType, CodeType, _is_directly_annotated
class Module:
"""
Module class represents the top level module to walk through and find annotated
APIs.
"""
def __init__(self, ... |
886eea52e7c57dcb7aad6ab291a01e658d0222d7304f7720a8927253c852f7c5 | Python | 3,413 | 106 | # built-in dependencies
from typing import List, Dict, Any
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.commons import weight_utils
from deepface.models.Detector import Detector, FacialAreaRegion
from deepface.commons.logger import Logger
logger = Logger()
WEIGHTS_U... |
fccd68cecb91368aafa9f0b6e03c5596b844237a029325e22dee8462d703e4ce | Python | 3,414 | 100 | import os
import pickle
import sys
# with open("./spliceai_result_"+SPLICEAI_VERSION+"/"+output_file+"/d_scores_"+TYPE+".pkl", 'rb') as fw:
# pickle.dump(donor_scores, fw)
# with open("./spliceai_result_"+SPLICEAI_VERSION+"/"+output_file+"/a_scores_"+TYPE+".pkl", 'rb') as fw:
# pickle.dump(acceptor_scores, fw... |
6a5a8d89b2225dfe4a49c6292bab2d48f8b34eeeeb0997f79fb3208d6e9bd843 | Python | 3,416 | 93 | import time
import torch
import torch.nn as nn
import pytorch_lightning as pl
from pytorch3dunet.unet3d.model import UNet3D
device = torch.device("cuda:0")
class MyModelLightning(pl.LightningModule):
def __init__(self, train_dataloader, val_dataloader, lr, weights, gamma1, gamma2):
sup... |
10907a76b7956d07062476069be812e244ac231d46aaec2b41f7a7549e05bdc5 | Python | 3,417 | 124 | from ci.ray_ci.doc.api import _OVERRIDE_HOOK_MARKER, AnnotationType
from ci.ray_ci.doc.mock._internal import ( # noqa: F401
MockInternalOnlyClass,
MockReexportedClass,
)
# Mirrors a library head module such as ray.data: the declared public surface
# names a class whose implementation lives in a private module... |
4461f4f8dfe230e6f8c5cdb0ac293d11769bb4cbb37a71e650bf5344f318b924 | Python | 3,418 | 68 | import pytest
from sklearn.pipeline import Pipeline
from siapy.core.exceptions import InvalidInputError
from siapy.features.helpers import (
FeatureSelectorConfig,
feature_selector_factory,
)
from tests.utils import assert_pipelines_parameters_equal
def test_feature_selector_factory_regression_pipeline():
... |
607444377568d31c854b1979d9de8cddab07d4d0622b1be46aa968ef0e99724f | Python | 3,418 | 98 | #Plot abundance distribution
import numpy as np
import pandas as pd
import glob
import geopandas as gpd
import traceback
import math
from distributed import wait
def run(tile, confusion_path="data/processed/confusion_matrix.csv", overlay_bounds="/home/b.weinstein/DeepTreeAttention/data/raw/OSBSBoundary/OSBS_boundary.... |
1893b30191cfacb2955c8e3a246cf44dda18726bb3c1c2ed22f29d5e9dd9c1f5 | Python | 3,419 | 93 | # Ultralytics YOLO 🚀, GPL-3.0 license
import requests
from ultralytics.hub.auth import Auth
from ultralytics.hub.session import HUBTrainingSession
from ultralytics.hub.utils import PREFIX, split_key
from ultralytics.yolo.engine.exporter import EXPORT_FORMATS_LIST
from ultralytics.yolo.engine.model import YOLO
from u... |
8f28b6ffccbc258b20b0ec873d2a82102e6f6ed034bd12dece35534921257cd1 | Python | 3,419 | 100 | import numpy as np
import os
import json
import math
from scipy.stats import chi2_contingency, wilcoxon, mannwhitneyu, shapiro, linregress
from ..io import SAVED_DIR, RESULTS_DIR, load_network, load_params, load_responsiveness
from ..analysis import find_response_range, parse_activity, find_stimulus_range, find_respons... |
2daf3066b334a64e3b1387e2d555b69928f77d174ef688eb475c8ecffc01966d | Python | 3,420 | 136 | from collections import namedtuple
from dataclasses import dataclass
from typing import Dict
from unittest.mock import Mock
from wandb.util import json_dumps_safer
import ray
from ray.air.integrations.wandb import WandbLoggerCallback, _WandbLoggingActor
class Trial(
namedtuple(
"MockTrial",
[
... |
0f235fab7d95cac2adf113e2769bf94b72a39415cff804c2bc07f83d67c25d9c | Python | 3,421 | 89 | import torch
from typing import Union, Tuple
from torch_geometric.typing import OptPairTensor, Adj, Size
from torch import Tensor
from torch.nn import Linear
import torch.nn.functional as F
from torch_sparse import SparseTensor, matmul
from torch_geometric.nn.conv import MessagePassing
class SAGEConvCat(M... |
917e6bf7ff721bf83b553c8986649a80c1ff7a188ab97da4b3c7ba53a25c6f78 | Python | 3,422 | 72 | #!/usr/bin/python
import os
def create_key(template, outtype=('nii.gz',), annotation_classes=None):
if template is None or not template:
raise ValueError('Template must be a valid format string')
return template, outtype, annotation_classes
def infotodict(seqinfo):
"""Heuristic evaluator for de... |
a07cb15e6a2844c429af177ee49aa7516249c2e441820bd633789b91e64b9171 | Python | 3,422 | 94 | import re
import json
import h5py
import torch
import argparse
import numpy as np
import os
from tqdm import tqdm
from src.data.load_data import load_params
from src.tools import load_model
from src.models.predict_model import predict_horizon
SUBS = [f"sub-0{i}" for i in range(1, 7)]
HORIZON = 6
def main(args):
... |
0abf57bc5361b4af773075aa96285c80a86948542cfae8ce7137a16490c0e0b9 | Python | 3,423 | 102 | """
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.
"""
# example how to use checkpoint fixtures
from __future__ import annotations
import os
from functools import partial
import torch
from e3n... |
226321ade7c1a9fd99cf53a6ba947aa7f5604cfe3656a9d57540d3665d444b35 | Python | 3,425 | 77 | ####################################################################################################
# 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... |
74d498d4c28e8b89cfc5584d6fc086e2a2b802101d5f3ac21ce7e0573c87a9ac | Python | 3,425 | 66 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'thumbass.ui'
#
# Created by: PyQt5 UI code generator 5.15.2
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, QtG... |
9363bd9d763bb24a32fc42e09ed8d053ce13aa9c87c730d0d46945aa214a943b | Python | 3,428 | 103 | # 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, ... |
cf4eaef9790b9cda6c2f7317153f8619f86e3c1d1938080f5c140da38c0e3057 | Python | 3,428 | 112 | # Source:
# https://github.com/kubernetes-client/python/blob/master/kubernetes/utils/quantity.py
from decimal import Decimal, InvalidOperation
from typing import Optional, Union
from ray._private.accelerators.tpu import (
get_num_chips_from_topology,
get_tpu_cores_per_chip,
)
# Mapping used to get generation ... |
de404ac635bf2c0083d720a170c772e4d4e303b263a6dec8293f2c79cc43f47a | Python | 3,428 | 91 | import hashlib
import logging
import os
import tarfile
from pathlib import Path
import requests # type: ignore[import]
#################################################################
# TEST DATA CONFIGURATION #
#################################################################
... |
509848994d058b0482bc7b55e8cf8fafa11d5c1c218338082d25c00b3073f97f | Python | 3,430 | 114 | from typing import Sequence, Union
import numpy as np
from .typing import Types
def parse_shape_argument(x: Types, key: str):
"""Parse the shape argument of a NIR node."""
if isinstance(x, np.ndarray):
return {key: x}
elif isinstance(x, Sequence):
return {key: np.array(x)}
elif isins... |
5f8d92ebcde73e845c138e69f1f7b4a2f6221117583655d829d3024eb09acd38 | Python | 3,430 | 64 | import tensorflow as tf
class Activations:
class ASU(tf.keras.layers.Layer):
def __init__(self, trainable=True, lower_asymptote=0., upper_asymptote=1., alpha_init=1., bias_init=None):
super(Activations.ASU, self).__init__()
self.trainable = trainable
self.lower_asymptote... |
a0b1eec72550a20721148f8f937d2a75ff241a6d6137d12052d6e757f82eec5a | Python | 3,431 | 106 | # -*- 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.
#... |
c6aee64430fdef2f8405bd88db73e3fe733758803bdcbb0ee3af11ef59c38f36 | Python | 3,431 | 111 | """Find peak layer for each stim duration"""
import numpy as np
import nibabel as nb
import glob
import pandas as pd
import seaborn as sns
subs = ['sub-05', 'sub-06', 'sub-07', 'sub-09']
subList = []
peakList = []
durList = []
for sub in subs:
print('')
print(sub)
folder = f'/Users/sebastiandresbach/da... |
dc5c94f274a8aa20dd1bdc04793a056972943382cb18cdff0f8647c2ca9c72a8 | Python | 3,431 | 77 | import unittest
from neuron_morphology.morphology_builder import MorphologyBuilder
from neuron_morphology.feature_extractor.feature_extractor import FeatureExtractor
from neuron_morphology.feature_extractor.data import Data
from neuron_morphology.feature_extractor.marked_feature import (
specialize
)
from neuron_m... |
b9ddf0bf4a22d8d3e3761da68b48aea4327fb33bd3a2b77f632793189ecc6345 | Python | 3,432 | 110 | from __future__ import division
from time import sleep
from time import time
import numpy as np
import scipy as s
import sys
from ..core.nodes import *
def mask_data(data, mask_fraction):
"""Method to mask data values, mainly used to evaluate imputation
PARAMETERS
----------
data: ndarray
mask_fr... |
0b16ae231c61d53a0cb3d449d87564fef02098240febaa959c5b005ac310f4da | Python | 3,433 | 78 | import argparse
import scipy.stats as sts
import numpy as np
import pickle
import functools as ft
from datetime import datetime
import general.utility as u
import swap_errors.auxiliary as swaux
import swap_errors.analysis as swan
def create_parser():
parser = argparse.ArgumentParser(description='naive forgetting ... |
53ac6e695ed1c3e656d21a26bab7e3c5e432e7e2ebcdf7b75a7e819e1172e98e | Python | 3,433 | 79 | import torch
import torch.nn.functional as F
def precompute_feedback_exp_args(stacked_feedback_filters: torch.Tensor,
all_observed_spikes: torch.Tensor) -> torch.Tensor:
'''
:param stacked_feedback_filters: shaep (n_cells, n_bins_filter)
:param all_observed_spikes: shape ... |
7667964ff9b1c994091d6586ee4fb4ea580c19213de96c4e2095bc9d821ee393 | Python | 3,433 | 103 | import numpy as np
# from utils import random_ortho_mat
class SimpleUniformContext():
def __init__(self, context_dim, pseudo_count=10, stickiness=10):
self.context_dim = context_dim
self.pseudo_count = pseudo_count
self.stickiness = stickiness
self.init_context()
def init_co... |
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