sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
dba91afbf4e885f5f7cd7edc19cef6a4571e3153904a10cb2bf5e838955c59fc | Shell | 3,667 | 132 | #!/usr/bin/env bash
set -euo pipefail
# -------------------------
# Usage
# -------------------------
if [[ $# -lt 6 ]]; then
echo "Usage: $0 <subject_id> <session_id> <fa_file> <preprocess_t1w> <orig_t1w> <output_dir>"
exit 1
fi
subject_id="$1"
session_id="$2"
fa_file="$3"
preprocess_t1w="$4" # ACPC T1w (1mm) ... |
5438f2927a5901c9d49b3e95b10cbdc2bba2cec2f04118a623767306edf3e36e | Shell | 3,668 | 109 | #!/bin/bash -ex
eval "$(conda shell.bash hook)"
# Create and activate conda environment for this test
BINDING=$(echo "$1" | tr '[:lower:]' '[:upper:]')
QT_VERSION_VAR=${BINDING}_QT_VERSION
# pytest-qt >=4.5.0 doesn't support PySide2
if [ "${1}" = "pyside2" ]; then
PYTESTQT_VERSION="<4.5.0"
fi
# pytest-qt >=4 do... |
4a26d52d42c124e30636499e3b028aea8a1c87cd1f7f041914d7b856583961da | Shell | 3,672 | 102 | #!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --time=00:30:00
#SBATCH --output=/dev/null # suppress default output file
#SBATCH --error=/dev/null # suppress default error file
# code for transforms adapted fro... |
ac697c1c0e186229861429e6421245dcf0572163218e00bbc5d06ad704b2a647 | Shell | 3,680 | 115 | #!/bin/bash
subj=$1
dataDir=$2
TR=4.012
shiftFraction=0.5
curDir=$(pwd)
mkdir -p ${subj}
cd ${subj}
# import
importruns_vaso-split_reverse.sh \
func ${TR} ${dataDir}/${subj}/func/${subj}_task-layer_run-?_bold.nii.gz
# find out which tasks
find_task-runs.sh \
func ${dataDir}/${subj}/func/${subj}_task-laye... |
c01ad256739fd14adf59741d3729a73804fb4a0f494c6f99702bd967c46d072b | Shell | 3,708 | 67 | #!/bin/bash
# ============================================================================
# Developing brain Region Annotation With Expectation-Maximization (Draw-EM)
#
# Copyright 2013-2020 Imperial College London
# Copyright 2013-2020 Antonios Makropoulos
#
# Licensed under the Apache License, Version 2.0 (the "Lice... |
c6a68ea3d0bdbefe7120c060908f844f73368e8a586a4465a800ae9e2f2d1d82 | Shell | 3,737 | 135 | #!/bin/bash
declare -a volume_num_pool
declare -a voxel_num_pool
volume_num_pool[1]=1937
volume_num_pool[2]=1940
volume_num_pool[3]=1936
volume_num_pool[4]=1936
volume_num_pool[5]=1937
volume_num_pool[6]=1934
volume_num_pool[7]=1936
volume_num_pool[8]=1936
volume_num_pool[9]=1935
volume_num_pool[10]=1933
volume_num_poo... |
68bc4f2552f983ad384b5f136b084d739864c00d01517a776cbc552096fffcf1 | Shell | 3,747 | 115 | #!bin/bash
NC="\e[39m"
BLUE="\e[34m"
GREEN="\e[32m"
RED="\e[31m"
CYAN="\e[36m"
subjects_list=$1
subjects=( $(cat $subjects_list) )
root_dir=`pwd`
source_dir=$2
root_dir_target1=$3
root_dir_target2=$4
root_dir_target3=$5
echo -e "${BLUE}################################"
echo -e "##### Starting WMH Masking BIS ####... |
44b2312e7d1f3ef92057b1ae91fa4c8a665701ed64050a1d057b621e94d301fb | Shell | 3,760 | 116 | # ===== SET UP =====
set -ueo pipefail
if [ $# -ne 1 ]; then
echo -e "Usage: $0 <input_data_and_params>"
exit 1
fi
echo -e "#=====================\n#"
echo -e "# $(basename "$0") \n#"
echo -e "#=====================\n#"
# Read input config
neda=$(dirname $(dirname "$0"))
source $neda/scripts/process_input.sh... |
0e1ccd79be0b7c97d25a1725e10dbde8f1b427f6ff3914a6bdb84510a0475b39 | Shell | 3,766 | 135 | #!/bin/bash
declare -a volume_num_pool
declare -a voxel_num_pool
volume_num_pool[1]=1937
volume_num_pool[2]=1940
volume_num_pool[3]=1936
volume_num_pool[4]=1936
volume_num_pool[5]=1937
volume_num_pool[6]=1934
volume_num_pool[7]=1936
volume_num_pool[8]=1936
volume_num_pool[9]=1935
volume_num_pool[10]=1933
volume_num_poo... |
bd0a41553823d8f7051c6adcde2cd3e366168c88915ea0f8d59a974e80b7c5e3 | Shell | 3,766 | 135 | #!/bin/bash
declare -a volume_num_pool
declare -a voxel_num_pool
volume_num_pool[1]=1937
volume_num_pool[2]=1940
volume_num_pool[3]=1936
volume_num_pool[4]=1936
volume_num_pool[5]=1937
volume_num_pool[6]=1934
volume_num_pool[7]=1936
volume_num_pool[8]=1936
volume_num_pool[9]=1935
volume_num_pool[10]=1933
volume_num_poo... |
170edf21d392054ccc2b85da54d12cdebe89a02eff3b985c3a938869c02e84db | Shell | 3,772 | 89 | # train an ensemble of DeepSTARR models with standard training
ENSEMBLE_SIZE=10 # define number of models to trian
# ENSEMBLE_SIZE=25
# OUTDIR=../results/DeepSTARR_lr-decay
OUTDIR=../results/DeepSTARR_ensemble_NEW # define output directory
# OUTDIR=../results/DeepSTARR_ensemble_size
DATA=../data/DeepSTARR/Sequenc... |
8b3de2096fb89d737de0bee4cd41602b742dbab18000f3b4e0886df153175c55 | Shell | 3,779 | 107 | #!/bin/bash
# ============================================================================
# Developing brain Region Annotation With Expectation-Maximization (Draw-EM)
#
# Copyright 2013-2020 Imperial College London
# Copyright 2013-2020 Andreas Schuh
# Copyright 2013-2020 Antonios Makropoulos
#
# Licensed under the Ap... |
e129ccea9e396aca07fb9bbd3c5c59f0e109bd601e35c8808c40cf81ac3e64b7 | Shell | 3,779 | 89 | # trains distilled DeepSTARR models that predict epistemic uncertainty (stdev) and mean
OUTDIR=../results/DeepSTARR_ensemble_NEW # path to output directory
# OUTDIR=../results/DeepSTARR_lr-decay
# DATA_DIR=../data/DeepSTARR
DATA_DIR=../data/DeepSTARR_ensemble_NEW # path to training data
CONFIG=../config/DeepSTARR.yam... |
db743b21a171258fe83c928b9b5eec31c56b3158b2657c1e9173a37bedbe92a7 | Shell | 3,802 | 113 | #!/bin/sh
MASTER_PORT=10014
MASTER_IP=127.0.0.1
n_gpu=1
exp_name=singletarget
OMPI_COMM_WORLD_SIZE=1
OMPI_COMM_WORLD_RANK=0
# fold_path, data_path, and save_dir are set after CLI parsing
user_dir="./"
train_set="train"
valid_sets="valid"
# chemprop_pretrain set after CLI parsing
# Defaults (can be overridden by CLI... |
72a24b50e559565509998abe27492f3161f6e25f4dd4bff806767b80f93c153b | Shell | 3,809 | 71 |
#!/bin/bash
source /cbica/projects/luo_wm_dev/miniconda3/etc/profile.d/conda.sh
conda activate babs
########################
# PNC - act-hsvs
########################
if [ ! -d /cbica/projects/luo_wm_dev/input/PNC/derivatives ]; then
mkdir -p /cbica/projects/luo_wm_dev/input/PNC/derivatives
fi
babs-init --w... |
28292e7218302eeb33f31174bb0cf16c77975356aaa7c94de0dc438d539f89b4 | Shell | 3,821 | 125 | #!/bin/bash
#~ND~FORMAT~MARKDOWN~
#~ND~START~
#
# # Compile_MATLAB_code.sh
#
# Compile the MATLAB code necessary for running the MSMAll Pipeline
#
# ## Copyright Notice
#
# Copyright (C) 2019 The Connectome Coordination Facility (CCF)
#
# * Washington University in St. Louis
# * University of Minnesota
# * Oxford Univ... |
faa2b62abd77ae32462203481fdad85ae2f33981e5731148b3ea1aec67fdc730 | Shell | 3,845 | 91 | #!/bin/bash
# transformed a freesurfer brain to match qsiprep headers
# for glass brain plotting
########################################
# Set directories
########################################
dataset="PNC"
config_file="/cbica/projects/luo_wm_dev/two_axes/code/config/config_${dataset}.json"
data_root=$(jq -r '.... |
7648bb387c61711acb96c8b67d911e3ba165cb80e8467407594c201f66054ccb | Shell | 3,850 | 118 | #!/bin/sh
MASTER_PORT=10011
MASTER_IP=127.0.0.1
n_gpu=1
exp_name=multitarget
OMPI_COMM_WORLD_SIZE=1
OMPI_COMM_WORLD_RANK=0
user_dir="./"
train_set="train"
valid_sets="valid"
# Defaults (can be overridden by CLI)
pretrained_model="../unimol_plus_pcq_small.pt"
batch_size=16
batch_size_valid=16
lr=5e-4
end_lr=1e-9
... |
3956d8efa308eb80f42bf67e0b677ec3aa940bb24195ba4220cb427f893ef9c0 | Shell | 3,851 | 80 | #!/bin/bash
#Loop through subjects/visits in BIDs format
for img in `ls ../sub*/ses*/anat/*T1w.nii.gz`;do
hd=`pwd`
#Should be BIDS format
t1_basename_sub=`echo $img | awk -F "/" '{ print $2 }'`
t1_basename_ses=`echo $img | awk -F "/" '{ print $3 }'`
t1_basename_fname=`echo $img | awk -F "/" '{ print $5 }' | aw... |
fe58db7e03d90c00f033a652320f08bffbd5f5124c4617f656a030a6a3f3bf6a | Shell | 3,854 | 81 | #!/bin/bash
#-----------------------------------------------------------------------------#
# AFNI surface clustering for NumpRF tuning parameter maps
# AFNI <full_path_to_this_script> <sub> <ses> <model> <img> <anat>
#
# <full_path_to_this_script>
# = /data/hu_soch/ownCloud/MPI/EMPRISE/tools
# ... |
a46010d0af0b8d0d3f240c572b245a526dbb54459438f91fd5c417b156df8fdb | Shell | 3,862 | 113 | #!/bin/bash
# --------------------------------------------------------------------------------
# Usage Description Function
# --------------------------------------------------------------------------------
script_name=$(basename "${0}")
show_usage() {
cat <<EOF
${script_name}
Usage: ${script_name} StudyFolder S... |
35d55ed99663d1e967e55a34b7d8d8bcc87bff9337f3c78c829ef8433f267095 | Shell | 3,885 | 113 | #!/bin/bash
set -eu
pipedirguessed=0
if [[ "${HCPPIPEDIR:-}" == "" ]]
then
export HCPPIPEDIR="$(dirname -- "$0")/../.."
pipedirguessed=1
fi
source "$HCPPIPEDIR/global/scripts/newopts.shlib" "$@"
source "$HCPPIPEDIR/global/scripts/debug.shlib" "$@"
source "$HCPPIPEDIR/global/scripts/relativePath.shlib" "$@"
#... |
72f8fed49644a4ca01d0db808688de39fbaf0aa2ca105fd0fc1ffc573e1a067d | Shell | 3,885 | 109 | #!/bin/bash
set -e
# Order fdt eddy output files to another directory
process_subject() {
eddy_output_dir=$1
eddy_output_filename=$2
new_output_dir=$3
new_output_filename=$4
bval=$5
output_resolution=$6
mkdir -p "${new_output_dir}"
# find eddy corrected dwi and bvec files
eddy_d... |
187290c525cba0b1f28be0c6dd50e6ce539863b698e3b6855f7676ce98f4d048 | Shell | 3,888 | 120 | # Bethell and Taroni for CCDL 2019
# Run dimension reduction for all subsets of gene expression for both methods:
# RSEM and kallisto
#
# Usage: bash 01-dimension-reduction.sh
# Takes one environment variable, `BASE_SUBTYPING`, if value is 1 then
# uses pbta-histologies-base.tsv for subtyping if value is 0 runs all mo... |
a115c1d629e0d58ce27629dc509a2d0e045d77cbfcc5d5e863d4030478d2e272 | Shell | 3,891 | 124 | #!/bin/sh
MASTER_PORT=10015
MASTER_IP=127.0.0.1
n_gpu=1
exp_name=singletarget
run_name=bs_64_unfreeze_backbone
OMPI_COMM_WORLD_SIZE=1
OMPI_COMM_WORLD_RANK=0
data_path="./conformations/xtb_to_dft_implicit/"
user_dir="./"
train_set="train"
valid_sets="valid,test"
chemprop_pretrain="../models/chemprop/fold_0/model_1/m... |
3cd1fb57e7bcc19f1465ca5e71c2edab727f8bb746a4716413828f80abdef74a | Shell | 3,922 | 76 | #!/bin/bash
set -e
WDL=chip.wdl
VER=$(cat ${WDL} | grep "String pipeline_ver = " | awk '{gsub("'"'"'",""); print $4}')
DXWDL=~/dxWDL-v1.50.jar
# general
java -jar ${DXWDL} compile ${WDL} -project "ENCODE Uniform Processing Pipelines" -f -folder \
/ChIP-seq2/workflows/$VER/general -defaults example_input_json/dx/templ... |
7616e5ba765266c097bc2253f25ef33b9dd8e3c005217f3517084ec572162ab6 | Shell | 3,934 | 89 | # train an ensemble of ResidualBind models with train_lentiMPRA.py
### define variables
ENSEMBLE_SIZE=10 # number of models to train
OUTDIR=../results/lentiMPRA # path to output directory
DATA_DIR=../data/lentiMPRA # path to lentiMPRA data
CONFIG=../config/lentiMPRA.yaml # path to ResidualBind model config
PROJECT_NAM... |
9759ad70007104ee7c21179a205a09476b967f9fc58fb11648d651a8535a1899 | Shell | 3,935 | 67 | #!/bin/bash
# ============================================================================
# Developing brain Region Annotation With Expectation-Maximization (Draw-EM)
#
# Copyright 2013-2020 Imperial College London
# Copyright 2013-2020 Antonios Makropoulos
#
# Licensed under the Apache License, Version 2.0 (the "Lice... |
9e44727402863104ea565db269defc5e171687751f5be7afda9f46c86f03ca80 | Shell | 3,961 | 162 | #!/usr/bin/env bash
set -euo pipefail
usage() {
cat <<EOF
Usage:
$0 \
--t1w <T1w image> \
--t1w_to_mni_warp <T1w->MNI warp .nii.gz/.mgz> \
--qsm_to_t1w_affine <QSM->T1w affine .mat> \
--output_dir <Output directory> \
--input <in1.nii.gz [in2.nii.gz ...]> \
--output1 <out1_T1w.nii.gz [out... |
2da14cfd4a05631a952327eb2c6582f877324c23352fa8ccc649ea41177f32de | Shell | 3,971 | 100 | #!/usr/bin/env bash
set -euo pipefail # Will fail on error
# ==============
# How to run this script
# 1) Load the input data
# https://scilpy.readthedocs.io/en/latest/documentation/getting_started.html
# 2) Call this script with
# ---> bash aodf_scripts.sh path/to/your/data path/to/save/outputs
# ... |
efe34bf4983a2574802b3b8651be795af52217f604ebec0c211a8269899e45e8 | Shell | 3,986 | 110 | #!/bin/bash
#SBATCH --job-name=babs_mergeds_mapmri
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=5
#SBATCH --array=1-2
#SBATCH --time=6:00:00
#SBATCH --output=/dev/null
#SBATCH --error=/dev/null
# Pick dataset based on array ID
datasets=("HCPD" "HBN")
dataset=${datasets[$SLURM_ARRAY_TASK_ID-1]}
# Redir... |
a231bc2353cc19cb5bd216e0da59693faa6b97c5fee489daa23e20410e593448 | Shell | 4,022 | 102 | #!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --time=01:00:00
#SBATCH --output=/dev/null # suppress default output file
#SBATCH --error=/dev/null # suppress default error file
######################
# setup f... |
2a4cad8f4e089980c129f8202064afe50780d298e3069c84a311bce5aa462b94 | Shell | 4,033 | 110 | #!/bin/bash
# List of subjects
subjects=()
subject_ids=()
runs=("1" "2" "3" "4" "5" "6" "7" "8" "9" "10")
# Directories
data_pre_dir="preprocessed data directory"
data_out_dir="output directory"
feat_directory_decoding="decoding feat scripts"
feat_directory_ret="retinotopy feat scripts"
feat_directory_object="object ... |
4aebf0f39dcc2cdc4740d6eaf5edf853b4c13a6afdbe088b53f89f1edc342374 | Shell | 4,037 | 119 | #!/bin/sh
MASTER_PORT=10015
MASTER_IP=127.0.0.1
n_gpu=1
exp_name=singletarget
OMPI_COMM_WORLD_SIZE=1
OMPI_COMM_WORLD_RANK=0
user_dir="./"
train_set="train"
valid_sets="valid"
chemprop_pretrain="../models/chemprop/fold_0/model_1/model.pt"
batch_size=4
batch_size_valid=4
lr=6e-5
end_lr=1e-9
warmup_steps=10000
tota... |
4be5bc7a149352c242b63724df71d8b4fd17644b53500d285dd3933c8c3ffa9c | Shell | 4,040 | 77 | #!/usr/bin/env bash
set -e
bids_dir=$1
subject_id=$2
session_id=$3
# Search for already processed qsiprep output
qsiprep_dir=$bids_dir/derivatives/qsiprep/sub-${subject_id}/ses-${session_id}/dwi
# Find whether have a *space-ACPC_desc-preproc_dwi.nii.gz file
preproc_dwi_file=$(find $qsiprep_dir -type f -name "*space-... |
51287e63ba09ab29045e4e51f4c6063ec5bb9ab61b6cf2adfdeef3574a58c8d2 | Shell | 4,052 | 85 | #!/bin/bash
set -e # Stop on error
install_ucsc_tools_369() {
# takes in conda env name and find conda bin
CONDA_BIN=$(conda run -n $1 bash -c "echo \$(dirname \$(which python))")
curl -o "$CONDA_BIN/fetchChromSizes" "https://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64.v369/fetchChromSizes"
curl -o "$CONDA... |
98516b1b5c9ea030ff4266a02653118a9fc9725a4636222acfc83f54c81585fa | Shell | 4,066 | 128 | #!/usr/bin/env bash
[ ! -e "$FREESURFER_HOME" ] && echo "error: freesurfer has not been properly sourced" && exit 1
# check that the model file has been downloaded and installed
# if not, show instructions for downloading and installing
if [[ ! -f $FREESURFER_HOME/"models/WMH-SynthSeg_v10_231110.pth" ]]; then
ech... |
21a5c4f488c14b5ef3800ee485e0f4e7e313e4478329c00eff391e3f44adb1a8 | Shell | 4,073 | 143 | #!/usr/bin/env bash
set -e
# === Argument parsing ===
T1W_IMG=$1
DWI_IMG=$2
OUTPUT_DIR=$3
DWI_JSON=$4
FMAP_DIR=$5
if [[ $# -ne 5 ]]; then
echo "Usage: $0 <T1w.nii.gz> <DWI.nii.gz> <synb0_output_dir> <dwi.json> <fmap_output_dir>"
exit 1
fi
# === Path setup ===
INPUTS="${OUTPUT_DIR}/INPUTS"
OUTPUTS="${OUTPUT_DIR}/... |
d019df32e2a84523f8e5f3660ef9ff5424bf8230987a5fb4c44d5c562772b46c | Shell | 4,075 | 156 | #!/bin/sh
# Displays usage information
usage() {
echo "Usage: $0 --license LICENSE --python PYTHON INPUT OUTPUT"
echo "Arguments:"
echo " -l, --license LICENSE Path to FreeSurfer license (required)"
echo " -p, --python PYTHON Path to Python-executable to use (required)"
echo " INPUT ... |
b9d63fedf135fb592106b5dd0dfb0eed2bc040ac71eba830acf22ea679a83eee | Shell | 4,087 | 120 | #!/bin/sh
MASTER_PORT=10011
MASTER_IP=127.0.0.1
n_gpu=1
exp_name=multitarget
OMPI_COMM_WORLD_SIZE=1
OMPI_COMM_WORLD_RANK=0
user_dir="./"
train_set="train"
valid_sets="valid"
chemprop_pretrain="../models/chemprop/fold_0/model_1/model.pt"
batch_size=4
batch_size_valid=4
lr=6e-5
end_lr=1e-9
warmup_steps=10000
total... |
768d6921bd6af8c0b5470d17cadb3d0ec2980e063d4befd94c9811ec43367f31 | Shell | 4,088 | 73 | #!/bin/bash
# ============================================================================
# Developing brain Region Annotation With Expectation-Maximization (Draw-EM)
#
# Copyright 2013-2020 Imperial College London
# Copyright 2013-2020 Antonios Makropoulos
#
# Licensed under the Apache License, Version 2.0 (the "Lice... |
327789b0cc3d4bcf70a67974e5819b4455594a1011370d69b2d9149a9a122e02 | Shell | 4,129 | 119 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
command_line_specified_study_folder=""
command_line_specified_session=""
command_line_specified_run_local="FALSE"
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argume... |
c2df6e765a81b0d40fa42bde4a9ebb73d4d1eb19b0be8f18dff74d6020cc9e70 | Shell | 4,146 | 79 | # run ensemble_predict_lentiMPRA.py with both --distill and --eval flags set
# for ensemble of ResidualBind models with aleatoric uncertainty prediction
MODELS_DIR=../results/lentiMPRA_aleatoric # path to directory with ensemble of models
N_MODS=10 # number of models in ensemble
DATA_DIR=../data/lentiMPRA # path t... |
e2ef45a5a8e23f028de555f2d3111f26aa56b4d3a7ffb1eb6d1d54bdcec7866a | Shell | 4,154 | 86 | #!/bin/bash
#Before lauching please use conda activate RNAbulk
# to export the environment : conda env export --name RNAbulk --file environment.yml
NUM_PROC=$(nproc --all)
NUM_PROC_SMALL=$((NUM_PROC / 3)) #For tools that are limited by RAM capacity, can't use all cores
########################################## STEP ... |
d012ec1f2d864d4bce54780fe5afcc4f7dcad714652be52848241bce3c585cf4 | Shell | 4,159 | 137 | # #!/bin/bash
# #
# # motioncorrect.sh run1.nii run2.nii ...
# #
# # - runs motion correction on a list of runs, registering them all to a common robust volume
# # - uses afni and depends on run_afni_mc.sh
# # - writes output as run1_mc.nii run2_mc.nii ...
# # fileNames="$@"
# # Capture the last argument as the outp... |
430f8c2fad0ae0f4d462d667f128709422cbca0b90be5ab66c8cea2f4733db9d | Shell | 4,162 | 111 | #!/bin/bash
# C. Bethell and C. Savonen for CCDL 2019
# Run focal-cn-file-preparation module
#
# Usage: bash run-prepare-cn.sh
set -e
set -o pipefail
# Run original files - will not by default
RUN_ORIGINAL=${RUN_ORIGINAL:-0}
# Run testing files for circle CI - will not by default
IS_CI=${OPENPBTA_TESTING:-0}
# This... |
00ae2a5db66fea4ca1c3d483533123f6a5e75e1c1bdb452b76f7725a873ebd8d | Shell | 4,178 | 116 | #!/bin/bash
StudyFolder="<MyStudyFolder>"
#The list of subject labels, space separated
Subjects=(HCA6002236)
PossibleVisits=(V1_MR V2_MR V3_MR)
ExcludeVisits=()
Templates=(HCA6002236_V1_V2_V3)
EnvironmentScript="<hcp-pipelines-folder>/scripts/SetUpHCPPipeline.sh" #Pipeline environment script
# Requirements for this... |
613a6d18c987bb79f4e6446bb943a77865a3e6e3fbf753413f8a7038c3ba946a | Shell | 4,182 | 90 | # train an ensemble of MPRAnn models with heteroscedastic regression
### script params/variables
ENSEMBLE_SIZE=10
OUTDIR=../results/MPRAnn_heteroscedastic
DATA_DIR=../data/lentiMPRA
CONFIG=../config/MPRAnn.yaml
PROJECT_NAME=MPRAnn_heteroscedastic
DOWNSAMPLE_ARR=( 0.1 0.25 0.5 0.75 ) # used if downsample set to true
#... |
1fdc3c429c28bb6b5976bab3b9f9fd7d9223e7f5a22800e317d3966f2bfff43f | Shell | 4,184 | 127 | #!/bin/bash
# J. Taroni for CCDL 2019
# Updated by Eric Wafula for Pediatric Open Targets 2022
# Create subset files for continuous integration
set -e
set -o pipefail
# Set defaults for release and biospecimen file name
BIOSPECIMEN_FILE=${BIOSPECIMEN_FILE:-biospecimen_ids_for_subset.RDS}
RELEASE=${RELEASE:-v15}
NUM_M... |
a23c6f478cbd0affe6e1a82b3bd5a7081b35f727f6cc4d14531a291cf50e2695 | Shell | 4,188 | 147 | #!/bin/sh
#
# Before building a release:
#
# Make a place to work, grab the bits you want to release:
# git clone git@github.com:marbl/meryl meryl-release
# cd meryl-release
#
# Commit to master:
# Increase version in documentation/source/conf.py (not present in meryl)
# Increase version in scripts/ver... |
068dbf9674cbffb6275bc185b2f2374663bbb98414dcdc573a7c4eaa1c121db2 | Shell | 4,193 | 69 | #!/bin/bash
export PYTHONUNBUFFERED=1
# List of datasets:
# 1. More cell types
# 2. cell type removed in scRNA-seq
# 3. cell type removed in spatial
# 4. fewer reads in spatial
# 5. cell types per spot (maybe both can be combined?)
# Step 1: make dataset
export PATH_EXPERIMENT=/home/ubuntu/simu_runs/run_C
python ma... |
7ca1662db220d5160245e73beeccb5ce923aaa2b33984e023b6a1b0dc78a60f7 | Shell | 4,208 | 98 | #!/bin/bash
# --------------------------------------------------------------------------------
# Usage Description Function
# --------------------------------------------------------------------------------
script_name=$(basename "${0}")
show_usage() {
cat <<EOF
${script_name}: Sub-script of GenericfMRISurfacePr... |
4e17ce4b4a779861c8858b02d6adbe96b538d9ebdd65a13a22ddf711577af2b2 | Shell | 4,211 | 126 | #!/usr/bin/env bash
set -euo pipefail
###################### IMPORTANT NOTE ########################
# T1w and FLAIR should be aligned and skull-stripped already #
##############################################################
usage() {
echo "Usage (with FLAIR): $0 <FLAIR_IMG> <T1w_IMG> <BRAIN_MASK> <SynthSeg_IMG> ... |
bf70e7ef92dcbf466525d60c98417a901fa66fd83145037e8c4c61436cc50fdb | Shell | 4,213 | 113 | #!/bin/bash
#SBATCH --job-name=babs_mergeds_noddi
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=5
#SBATCH --array=1-2
#SBATCH --time=6:00:00
#SBATCH --output=/dev/null
#SBATCH --error=/dev/null
# Pick dataset based on array ID
datasets=("HCPD" "HBN")
dataset=${datasets[$SLURM_ARRAY_TASK_ID-1]}
# Redire... |
422c14f3809b19b55fa86b34056c236209977119e44406b602758c48a77fac3a | Shell | 4,215 | 92 | # train an ensemble of lentiMPRA models with aleatoric uncertainty prediction
### script params/variables
ENSEMBLE_SIZE=10
OUTDIR=../results/lentiMPRA_aleatoric
DATA_DIR=../data/lentiMPRA
CONFIG=../config/lentiMPRA.yaml
PROJECT_NAME=lentiMPRA_ensemble_aleatoric
DOWNSAMPLE_ARR=( 0.1 0.25 0.5 0.75 ) # used if downsampl... |
2bc978e773572b876082355565820f763a8e8e649d7f51c68610ecd33e3b2472 | Shell | 4,217 | 177 | #!/bin/bash
# Global default values
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJECT_LIST="100307"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/HCPpipelines/Examples/Scripts/SetUpHCPPipeline.sh"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_FIX_DIR="${HOME}/tools/fix1.06"
#
# Function Description
# Get the command ... |
3b2f286c7a7b8dfb5ad7d4f232acf30e91e94e7000ccdd4a1cc233cf3a186ec5 | Shell | 4,228 | 150 | #!/bin/bash
#Lucas Sancéré -
################ PARSE CONFIG ARGS
# Extract all needed parameters from mmsegmentation config
config_path=../configs/models/scc_segmenter.yml
# We need yaml lib so we reactivate histo-miner env if it was not done befre
conda deactivate
conda activate histo-miner-env
# We extract all p... |
c3bd9a7106b36156710268592b0475aa84415e26c6e6ae3482cc7875774acc3d | Shell | 4,235 | 89 | # train an ensemble of ResidualBind models with evidential regression
### script params/variables
ENSEMBLE_SIZE=10 # nr. of models to train
OUTDIR=../results/lentiMPRA_evidential # path to output directory
DATA_DIR=../data/lentiMPRA # path to directory containing data
CONFIG=../config/lentiMPRA.yaml # path to Residua... |
37960c0960b8c7da71b8d520f04eea7f98765630ee225b6a971283acfe25ba8f | Shell | 4,240 | 116 | #!/bin/bash
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC/
# Download command: bash data/scripts/get_voc.sh
# Train command: python train.py --data voc.yaml
# Default dataset location is next to YOLOv5:
# /parent_folder
# /VOC
# /yolov5
start=$(date +%s)
mkdir -p ../tmp
cd ../tmp/
# Download/u... |
51b92f2d22396249c2ac5465967af70d14a0babb87522002878007f4b619785e | Shell | 4,255 | 127 | #!/usr/bin/env bash
# run-yolo.sh -- self-bootstrapping wrapper for Ultralytics + apt OpenCV on Raspberry Pi OS
# Usage:
# ./run-yolo.sh # if BehaveAI.py exists in CWD, runs it
# ./run-yolo.sh script.py [args...] # runs a specific script with args
set -euo pipefail
# --- Config ---
VENV_DIR="${HOME}/u... |
bde8ede2a375a61627e2fa3db952d06ee0cf9d228899d1ba66f587ff44dc8995 | Shell | 4,265 | 107 | #!/bin/bash
set -euo pipefail
bids_dir=$1 # BIDS root directory
subject_id=$2 # Subject ID (e.g., HC0001)
session_id=$3 # Session ID (e.g., baseline)
#######################
# Prepare directories #
#######################
subject="sub-${subject_id}"
session="ses-${session_id}"
freesurfer_subjects_dir="${bids_... |
32411c2193c4b74c3a7bb017476e1018eb5b96761b07a1ee6662cfdb41165468 | Shell | 4,268 | 141 | #!/usr/bin/env bash
set -euo pipefail
t1w_image=$1
output_dir=$2
output_csv_filename=$3
mkdir -p "$output_dir"
############################################
# Auto-detect paths
############################################
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
# brainageR_custom.sh:
# D:/Codes/c... |
a175f7840c380bb46176164a81155cc1f1196764977c38291e3bd21021e78492 | Shell | 4,273 | 183 | #!/bin/bash
# ./run.sh gemm gemm_settings.txt
# ./run.sh lazy_gemm lazy_gemm_settings.txt
# ./run.sh gemv gemv_settings.txt
# ./run.sh trmv_up gemv_square_settings.txt
# ...
# Examples of environment variables to be set:
# PREFIX="haswell-fma-"
# CXX_FLAGS="-mfma"
# CXX=clang++
# Options:
# -up... |
d500027f3bdaa7507b56f88a76c0bb0ea06f759baa85793de44c075668e132a6 | Shell | 4,299 | 188 | #! /bin/bash
set -e
anterior_persistence() {
local m=$1
shift 1
sleep 10
python -m rscvp.statistic.persistence_agg.$m\
-D 210315,210401,210402,210416,210604,210519,211202,211203,211202,221018 \
-A YW006,YW006,YW008,YW008,YW010,YW017,YW022,YW032,YW033,YW048 \
-P 0,0,0,0,0,0,,,, \
"$@"
}
posterior_per... |
a92fea216888dd865edc4e54bcdc4878c7950c1464643512bc7fd427614f7bfd | Shell | 4,306 | 91 | # train an ensemble of ResidualBind models with heteroscedastic regression
### script params/variables
ENSEMBLE_SIZE=10
# ENSEMBLE_SIZE=20
OUTDIR=../results/ResidualBind_heteroscedastic
DATA_DIR=../data/lentiMPRA
CONFIG=../config/lentiMPRA.yaml
PROJECT_NAME=ResidualBind_heteroscedastic_logvar
DOWNSAMPLE_ARR=( 0.1... |
c30a130c168b1660097395ed37648e4061276ace5d4b0b1d2809edf32579fc31 | Shell | 4,337 | 164 | #!/bin/bash
# Description:
# This is the main run script for BSBT pipeline
# It combines all necessary preprocessing, ROI extraction, etc.
# Usage:
# ./run_bsbt.sh --dwi <dwi.nii.gz> --bvals <bvals.txt> --bvecs <bvecs.txt> [--out <outdir>] [--threads <num_threads>]
# Flags:
# --dwi <file> - Path to input D... |
ef706edca13601f31215f9621a0995cbdb602c54fbece8e4fdebc682b932bfe5 | Shell | 4,348 | 130 | #!/usr/bin/env bash
set -euo pipefail
# enable_venv_binding.sh
# Usage:
# source scripts/enable_venv_binding.sh /path/to/venv /path/to/build
# or (non-persistent activation in a subshell):
# scripts/enable_venv_binding.sh /path/to/venv /path/to/build
#
# This script does two things:
# 1) If sourced, it activates t... |
394d9c3773f6eeb9690633cbd6326debe24523920abff73b1bb5810b70752090 | Shell | 4,366 | 173 | #!/usr/bin/env bash
set -euo pipefail
############################################################
# Usage:
# bash repair_freesurfer_links.sh <bids_root>
#
# Example:
# bash repair_freesurfer_links.sh /mnt/f/BIDS/WCH_AF_Project
############################################################
if [ "$#" -ne 1 ]; then
... |
e8ba80c639d13ecd2a6e4019b551f4831ef06c540539c774eab38c7a30888465 | Shell | 4,393 | 120 | #!bin/bash
NC="\e[39m"
BLUE="\e[34m"
GREEN="\e[32m"
RED="\e[31m"
CYAN="\e[36m"
subjects_list=$1
subjects=( $(cat $subjects_list) )
root_dir=`pwd`
source_dir=$2
root_dir_target1=$3
root_dir_target2=$4
root_dir_target3=$5
echo -e "${BLUE}################################"
echo -e "##### Starting WMH Masking #####"
e... |
bdd335c3bcd1c92bedf88b5d052f886fa6abbada02967f8a05ad4561aa90074a | Shell | 4,419 | 115 | #!/bin/bash
#
# RUN_TAPAS_TEST_IN_ENVIRONMENT
#
# Clone/download tapas,spm and tapas-examples to temporal folder and
# run testing pipeline in 'isolated environment' (clean matlab).
#
# Authors: Matthias Müller-Schrader & Lars Kasper
# Created: 2023-05-08
# Copyright (C) 2023 TNU, Institute for Biomedical Engineering... |
97ca59b8319e8e449069ec1d0b96f7713b684a6cc96f0261873da2eafde13212 | Shell | 4,424 | 71 | #!/bin/bash
#SBATCH -p gidbkb
#SBATCH --nodes=1
#SBATCH --gpus-per-node=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-gpu=8
#SBATCH --mem=100G
#SBATCH -o /pollard/data/projects/sdrusinsky/enformer_fine_tuning/logs/eval/slurm_stdout/%j.out
#SBATCH -e /pollard/data/projects/sdrusinsky/enformer_fine_tuning/logs/eval/sl... |
d0097dd30d0661ae3934d2ed91f94ced6575583e89197c1cbe5052a0085ac98a | Shell | 4,445 | 98 | #!/bin/bash
set -e
set -x
#algo=ifod2act5Mfsl
#algostr=$algo
algo=sdstream
algostr=""
nemodata_s3root=s3://kuceyeski-wcm-temp/kwj2001/nemo2
mnitracks_s3root=s3://kuceyeski-wcm-temp/kwj2001/mnitracks
subjectfile=subjects_unrelated420_scfc.txt
refvol=MNI152_T1_1mm_brain.nii.gz
numtracks=5M
mnitracksdir=${HOME}/nemo... |
2e37d78b2c72e10a9eb6ae7696e94a69fa21cf01626f8f51a8c8bd468c9c1d3d | Shell | 4,457 | 88 | #!/bin/bash
export DATE=$(date +%Y%m%d_%H%M%S)
export MODEL_KEY="$4"
export JOB_NAME=generate_pkl_EIANN_"$MODEL_KEY"_"$DATE"
export CONFIG_FILE_PATH="$1"
export PARAM_FILE_PATH="$2"
export TASK="$3"
export OMP_NUM_THREADS=1
export MKL_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
mkdir ... |
5f3265bc88c3effbc9f400d168fdb3d56ab7948a1154dd0d7bdcdc4bbfe0c94e | Shell | 4,491 | 63 | #!/bin/bash
# Set your project directory path here (LYN-track-and-trace)
PROJECT_DIR="~/Documents/LPBS/codes/LYN-track-and-trace"
# Set the path for your input mask files should be one h5 file per movie.
DATA_PATH="~/Desktop/LPBS_track_and_trace/Data_budding_yeast/"
# Activate conda environment
# source activate ye... |
f22dd9c94dc9d97f3f435f07b49152608e44ffecacb704f990943ca4c876f594 | Shell | 4,501 | 156 | #!/bin/bash
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJ_LIST="102311"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/HCPpipelines/Examples/Scripts/SetUpHCPPipeline.sh"
#
# Function: get_batch_options
# Description:
# Retrieve the --StudyFolder=, --Subjlist=, --EnvironmentScri... |
b9f84ad77a3ece5cf96302959e67737867291cb040e8f4b624227d8180678c74 | Shell | 4,534 | 104 | #!/bin/bash
# Requirements for this script
# installed versions of: FSL, gradunwarp (HCP version)
# environment: HCPPIPEDIR, FSLDIR, PATH for gradient_unwarp.py
set -eu
pipedirguessed=0
if [[ "${HCPPIPEDIR:-}" == "" ]]
then
pipedirguessed=1
#fix this if the script is more than one level below HCPPIPEDIR
... |
632d706ca7510bfec40db2d793eb597d1ad6c1a4588fb6c0233b2a0604f47c28 | Shell | 4,560 | 156 | #!/bin/bash
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJ_LIST="102311"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/HCPpipelines/Examples/Scripts/SetUpHCPPipeline.sh"
#
# Function: get_batch_options
# Description:
# Retrieve the --StudyFolder=, --Subjlist=, --EnvironmentScri... |
bad2d6ca11b9fd2b48f6c0c18f2c0e5afef3f56c47b11864ee2dfe483777dd3b | Shell | 4,582 | 111 | #!/bin/bash
set -eu
pipedirguessed=0
if [[ "${HCPPIPEDIR:-}" == "" ]]
then
pipedirguessed=1
export HCPPIPEDIR="$(dirname -- "$0")/.."
fi
source "$HCPPIPEDIR/global/scripts/newopts.shlib" "$@"
source "$HCPPIPEDIR/global/scripts/debug.shlib" "$@"
opts_SetScriptDescription "average final transmit field files"
... |
c0e63aa975c0ef37184d0b108eca0853759b30609b27ca7942b9765d053dad33 | Shell | 4,600 | 129 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
command_line_specified_study_folder=""
command_line_specified_subj=""
command_line_specified_run_local="FALSE"
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argument=... |
ff86de344e647dbbdfe9dfd97293c64c38e0e4f4d0a6ab3271043173cf599328 | Shell | 4,628 | 110 | #!/bin/bash
StudyFolder="${HOME}/projects/HCPpipelines_ExampleData" #Location of Subject folders (named by subjectID)
Subjects=(HCA6002236) #list of subject IDs
PossibleVisits=(V1_MR V2_MR V3_MR)
ExcludeVisits=()
Templates=(HCA6002236_V1_V2_V3)
EnvironmentScript="${HOME}/projects/HCPpipelines/Examples/Scripts/SetUpH... |
627e2f8f9bcc1ba3153f7ac9b5f0d4fd1d4d8fbe5aa407eb8aa431855eaeb0ff | Shell | 4,643 | 192 | #!/bin/bash
#
# Author(s): Timothy B. Brown (tbbrown at wustl dot edu)
#
#
# Function description
# Show usage information for this script
#
usage() {
local scriptName=$(basename ${0})
echo ""
echo " Usage ${scriptName} --studyfolder=<study-folder> --subject=<subject-id> --taskname=<task-name> \\"
ec... |
ae189342e38cefdd6c58f2557617e2246bd6048662cd8662ee61d030a1888951 | Shell | 4,649 | 132 | #!/bin/bash
# Define the function to check mandatory variables
check_mandatory_vars() {
local vars_to_check=("$@") # Receive array elements as arguments
for var in "${vars_to_check[@]}"; do
if [ -z "${!var}" ]; then # Check if variable is unset or empty using indirect expansion
echo "Erro... |
188fb06383ef1602c308148e33b0e800d115795b9f9fac04a3a7d7ac08041e95 | Shell | 4,690 | 132 | #!/bin/bash
set -eu
pipedirguessed=0
if [[ "${HCPPIPEDIR:-}" == "" ]]
then
pipedirguessed=1
export HCPPIPEDIR="$(dirname -- "$0")/../.."
fi
source "$HCPPIPEDIR/global/scripts/newopts.shlib" "$@"
source "$HCPPIPEDIR/global/scripts/debug.shlib" "$@"
g_matlab_default_mode=1
#this function gets called by opts_Pa... |
3ed36492dd605794809c32dccac97c2a7b3702964df07b39f9f1c7177d75394a | Shell | 4,709 | 114 | #!/bin/echo This script should be sourced before calling a pipeline script, and should not be run directly:
#Don't edit this line
SAVEHCPPIPE="${HCPPIPEDIR:-}"
## Edit this line: environment variable for location of HCP Pipeline repository
## If you leave it blank, and $HCPPIPEDIR already exists in the environment,
#... |
9fba57d15fed5117d55320acdb51f504df84d3138868526719c7fd5743db4ac3 | Shell | 4,778 | 130 | #!/bin/bash
# C. Bethell and C. Savonen for CCDL 2019, J. Rokita for D3b 2023
# Run focal-cn-file-preparation module
#
# Usage: bash run-prepare-cn.sh
set -e
set -o pipefail
# Run original files - will not by default
RUN_ORIGINAL=${RUN_ORIGINAL:-0}
# Run testing files for circle CI - will not by default
IS_CI=${OPEN... |
f1fab7040029f64a2a3aa495ca7adee0edc3d2d442cddf858de560292517f7c9 | Shell | 4,783 | 183 | #!/bin/bash
#set -xv
# Global default values
DEFAULT_STUDY_FOLDER="${HOME}/data/HCPpipelines_ExampleData"
DEFAULT_SUBJECT_LIST="100307 100610"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/HCPpipelines/Examples/Scripts/SetUpHCPPipeline.sh"
DEFAULT_RUN_LOCAL="FALSE"
#
# Function Description
# Get the command line optio... |
148c4efce87b6edd836c3d1a96830df0bb7d6fb02ed745e179448ac35aec2333 | Shell | 4,784 | 89 | # train replicates of distilled ResidualBind models w/ aleatoric uncertainty prediction
### script params/variables
ENSEMBLE_SIZE=10 # nr. of models to train
ENSEMBLE_DIR=../results/lentiMPRA_aleatoric # path to directory containing teacher ensemble
DATA_DIR=../data/lentiMPRA # directory containing lentiMPRA data
CON... |
d36587b158a6f1c86a0ec90cca6a0879dca097edadd43ef76544e9233c1577f9 | Shell | 4,800 | 114 | #
# mexopts.sh Shell script for configuring MEX-file creation script,
# mex, to use NVCC for building GPU MEX files.
#
# usage: Do not call this file directly; it is sourced by the
# mex shell script. Modify only if you don't like the
# defaults after running mex. No s... |
446bacd561f736d7330ff09da9d73a0b7c57a43c3ffcaef2bda3a04ebe5175c6 | Shell | 4,825 | 185 | #!/bin/bash
# Script to run all plotting scripts for Space Mice SNC project
# Usage: bash run_all_plots.sh
set -e # Exit on error
echo "========================================"
echo "Space Mice SNC - Plot Generation Pipeline"
echo "========================================"
# Define directories
SCRIPT_DIR="$(cd "$... |
d4f96b1b94b23d0d18029a62891d41beefd44f6e8d0a26f5affb9ddfb4895836 | Shell | 4,825 | 88 | # run saliency analysis for top 500 Dev enhancers on an ensemble of DeepSTARR models
# set DISTILLED to perform attribution analysis for distilled models
# set METHOD as saliency or shap to define method of attribution analysis
DISTILLED=true # toggle flag
DOWNSAMPLED=true # toggle true/false
METHOD=saliency # set sal... |
c773c709991930f0f0c3cb2c705a5b324c43a3a09b312dd842731c128bf42369 | Shell | 4,836 | 130 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
command_line_specified_study_folder=""
command_line_specified_subj=""
command_line_specified_run_local="FALSE"
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argument=... |
edfc1423f09283caf2bcfdbd2195fa041448c69334b423ac2c55a1e58980ff42 | Shell | 4,847 | 101 | #must blocks
for i in {0..693}; do echo $i; ../../scripts/blocks.py $i -n > must/$i.txt; done
#have blocks
for i in {0..693}; do j=$(printf "%05d" $i); cat output_neighbors-*-$j.json | sort -n | sed -r -e 's/\[[^[]*\]/[]/' > have/$i.txt; done
#count line of code
find ../src \( -name "*.cpp" -o -name "*.h" \) -exec wc... |
bfbebc5815e0c7f73ce7f9f48489fffa0ebc73df4b62e6b398e935f0a0b02d99 | Shell | 4,873 | 129 | #!/bin/bash
# OPenPedCan 2022
# Eric Wafula
set -e
set -o pipefail
printf "Start QC and Summary checks...\n\n"
# This script should always run as if it were being called from
# the directory it lives in.
script_directory="$(perl -e 'use File::Basename;
use Cwd "abs_path";
print dirname(abs_path(@ARGV[0]));' -- "$... |
6a7b3ac77da116a5976b19cf786dc3bdd94ba29b5bf0bbe5026cb7832d294760 | Shell | 4,876 | 108 | #!/bin/bash
# Function to start a model with retries and logging
start_model() {
local model_name="$1"
local command="$2"
local log_file="$3"
local attempt_counter_var_name="$4" # Name of the counter variable
local max_attempts=2
local timeout=3600 # 1 hour
# Use eval for reading and incre... |
a910ac240272b1c9b5eb9b29748891988409b20685c6bedf407c8d6e492cae00 | Shell | 4,954 | 102 | #! /bin/bash
# Conf2GCAReg_FNIRTbasedNHP.sh
# The script registers the brain volume (nu.mgz) to GCA template using FNIRT and creates non-linear transformation warpfield (talairach.m3z).
#
# Takuya Hayashi, RIKEN BDR Brain Connectomics Imaging Lab
# Akiko Uematsu, RIKEN BDR Brain Connectomics Imaging Lab
set -eu
usag... |
00174edf1741657c4f57fb80469ef25ae9b33e09f0015ea3fd3af152d815c8dd | Shell | 4,960 | 140 | #!/bin/bash
set -u
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
functionsource="$DIR/../misc/bashfunc"
cat <<HEAD
Copyright (C) 2017 Brock University Cognitive and Affective Neuroscience Lab
Code written by Mae Kennedy
This program is free software; you can redistribute it and/or modify
i... |
76a7dca4ea95122a6f0a0442ea0f7fb31fe2cc3162aa530c8ec52d4d041e2a0d | Shell | 4,990 | 120 | #!/bin/bash -e
# Copyright (C) 2004-2011 University of Oxford
#
# SHCOPYRIGHT
Usage() {
echo ""
echo "Usage: mcflirt.sh <4dinput> <4doutput> [<scout_image> [<mcref_image>]]"
echo ""
echo " If neither <scout_image> nor <mcref_image> is specified, a reference image"
echo " will be generated a... |
317e3687177638b05486aca5c0ec551890b9d8fbc72a4f48ad2eb0c2e5c6a974 | Shell | 4,999 | 77 | #!/bin/bash
set -eou pipefail
zip -rv build-record/mri-dataset.zip \
$(for ses in ses-0{1..5}; do
echo mri_dataset/sub-01/${ses}/anat/sub-01_${ses}_T1w{.nii.gz,.json}
echo mri_dataset/sub-01/${ses}/anat/sub-01_${ses}_acq-looklocker_IRT1{.nii.gz,.json,_trigger_times.txt}
echo mri_dataset/sub-01/${ses}/mix... |
30c5705ab06f7968d6506dac4089a4fb84ccd9e5965cbf8989c9120dd523d9b3 | Shell | 5,003 | 139 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
command_line_specified_study_folder=""
command_line_specified_subj=""
command_line_specified_run_local="FALSE"
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argument=... |
3768f6944b8551830022541ff9cd07b80c8db121fb460f9ef66eaaa7e5beffef | Shell | 5,005 | 64 | #!/bin/bash
# var_array_1=(fe fe fe)
# var_array_2=(1 2 3)
# auto_cost_pyfile=(main_mpi_nc3 main_mpi_nc3_other main_mpi_nc3_no_auto_cost)
auto_cost_pyfile=(main_mpi_nc3)
arch_array=(fpfe fe_maxpool fe fe fe fe fe fe fe fe be be be be be be be be be be be be be be be fpwe we we we we we we we we)
workload_array_1=(fe f... |
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