sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
2fc5a3750b6a0ea4bdff59edc8138956658ff9950a92f007389b478d9d6e1228 | Shell | 552 | 4 | #!/bin/bash
## Script to quickly turn uBAM into FASTQ with appropriate filenames
## Tested on "_test2" per readgroup "RevertSam" output uBAM files
for i in *.bam; do ID="_test2"; SM=`samtools view -H $i | grep '^@RG' | sed "s/.*SM:\([^\t]*\).*/\1/g"`; FC=`samtools view -H $i | grep '^@RG' | sed "s/.*PU:[^_]*_[^_]*_[^_]... |
adf1f34d6b56d347089ddffaf219f3e2316edd5908586f53116975d67413ad12 | Shell | 553 | 23 | #!/bin/bash
#SBATCH --job-name=multinode-example
#SBATCH --nodes=4
#SBATCH --ntasks=4
#SBATCH --gpus-per-task=1
#SBATCH --cpus-per-task=4
nodes=( $( scontrol show hostnames $SLURM_JOB_NODELIST ) )
nodes_array=($nodes)
head_node=${nodes_array[0]}
head_node_ip=$(srun --nodes=1 --ntasks=1 -w "$head_node" hostname --ip-a... |
592d99675782f951213477aa278de1fb301b96776fd99c0295b37e35a81f053c | Shell | 554 | 19 | #!/bin/sh
set -o allexport
sta_N_std=1
end_N_std=21 #21 #29 for I0~I1
sta_N_batch=1
end_N_batch=20
for i_std in $(eval echo "{$sta_N_std..$end_N_std}")
do
echo "$i_std"
for i_batch in $(eval echo "{$sta_N_batch..$end_N_batch}")
do
echo " $i_batch"
... |
767fa977dbf84ba5004bfdd4c1014b42c29302b2971aef612a0b3de52836a3a2 | Shell | 555 | 18 | #!/bin/bash
#SBATCH --nodes 1
#SBATCH --ntasks 1
#SBATCH --job-name=demuxlet_cellline
#SBATCH --mem 128G
#SBATCH -c 20
#SBATCH --time=2-00:00:00
source /work/upzenk/source_softwares_setup
module load bzip2
cd /scratch/hhu/scMethCnT/mpi-epfl-combined
demuxlet --sam /scratch/hhu/scMethCnT/mpi-epfl-combined/outs/possorte... |
b89dcaa640c369b108643a485850a4f6b55a38423cf651da772ed7828e0559f2 | Shell | 556 | 10 | # Extract model parameters from onnx to binary files
# prepare ENAMINE synthons to binary files
cd ../s2_lab_sw/chip/app-pe/s2app/qsar_19bill
uv run python get_params.py mol2d ../../../../../../virtual_screening_preparation/2_model_training/models/model_int8+bitshift_quant.onnx --gen_syn_arr_only
# prep only for veri... |
47fcfa3cf75678835d183bb8af3e1c3a6107c343601a3988ebecc7dd69446ffd | Shell | 557 | 19 | #!/bin/sh
set -o allexport
sta_N_std=1
end_N_std=24 #24 #26 for I0~I1
sta_N_batch=1
end_N_batch=20 #20
for i_std in $(eval echo "{$sta_N_std..$end_N_std}")
do
echo "$i_std"
for i_batch in $(eval echo "{$sta_N_batch..$end_N_batch}")
do
echo " $i_batch"
... |
697b587bb93e457c635dfbd2ba89aecab3ed26bbd0c51ae3a1d074c9f3c57539 | Shell | 557 | 17 | #slurm job
#!/bin/bash
#SBATCH --job-name=ipsc_3110_331_321_342_up
#SBATCH --output=my_job_ipsc_3110_331_321_342_up.out
#SBATCH --error=my_job_ipsc_3110_331_321_342_up.err
#SBATCH --time=300:00:00
#SBATCH --mem-per-cpu=2G
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=40
echo "Running job..."
#source /o... |
6f3e8de7f7aa7fa3e8b6b5588520dc79261c7b64d5c1c9ee60709c882fc41f52 | Shell | 558 | 22 | #!/bin/bash
#
# This is a script to build the FLAIR brainAGE container
# This small script specifies the version of the container,
# puts that same version in the tag of the container image
#
# If you don't have space run this command: docker builder prune -a
#
# Define version
version='v1.0'
# Get directory of this ... |
64011a5acfdbfafed597c5fb7711e4b1ae269c9de69c559bb1167b8fb2c015b6 | Shell | 559 | 19 | #!/bin/sh
set -o allexport
sta_N_std=1
end_N_std=26 #28 for I0~I1
sta_N_batch=1
end_N_batch=20
for i_std in $(eval echo "{$sta_N_std..$end_N_std}")
do
echo "$i_std"
for i_batch in $(eval echo "{$sta_N_batch..$end_N_batch}")
do
echo " $i_batch"
sbat... |
0ffc12bea2ed137b8d8c8fb0cebfa30e3aeb0f5e04aa2b605d780eb3279926d0 | Shell | 560 | 13 | #!/bin/bash
#source /home/h.bi/anaconda3/etc/profile.d/conda.sh
#
#conda deactivate
mamba activate new_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_Cognition/Codes/ENIGMA_Sleep_... |
5db3508570cf1741608033c8b16fd450daf35dbb919764833066d160e2d23b7f | Shell | 560 | 19 | #!/bin/bash
# Written by Jianzhong Chen and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
model=$1
input_dir=$2
outstem=$3
score=$4
perm_start=$5
N_per_job=$6
group=$7
outdir=$8
scripts_dir=`dirname "$(readlink -f "$0")"`
LF=${outdir}/logs/perm_test_score${score}_perm_start${perm... |
749f6f4d64b166a76e3435ef27ff71cab7b9d6a996585a9a69bd8f6a58360c00 | Shell | 560 | 17 | #!/bin/bash
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Download ImageNet100 dataset https://image-net.org (first 100 classes of ILSVRC2012 train/val)
# Example usage: bash data/scripts/get_imagenet100.sh
# parent
# ├── yolov5
# └── datasets
# └── imagenet100 ← downloads here
# Make dir... |
463a4be5103a7281c897d13999b3fdcc05b523fa6dc08ccf57c22fbefc0a8af1 | Shell | 561 | 19 | #!/bin/bash
#SBATCH --job-name=symbolic-model-%a
#SBATCH --output=logs/symbolic-model/cross-validation/subject-%a.out
#SBATCH --error=logs/symbolic-model/cross-validation/subject-%a.err
#SBATCH --array=1-20%20
#SBATCH --time=00:40:00
#SBATCH --cpus-per-task=1
#SBATCH --mem=4G
module load Julia
# Run the Julia script
... |
b663c51b742bc4d7c227c6a3f931884966ed0b4d74cb454236ae7036c588ef27 | Shell | 561 | 26 | #!/bin/bash
#SBATCH -p short
#SBATCH -t 1-00:00:00
#SBATCH -n 1
#SBATCH -c 16
#SBATCH --gpus-per-node=1
#SBATCH -J test
#SBATCH --mem=20G
#SBAYCH --mem-per-gpu=30G
#SBATCH -o out.log
#SBATCH -e error.log
# Load the modules
module purge
module load Python/3.7.4-GCCcore-8.3.0
module load libs/cuda/10.1.243
module loa... |
6de4e561dc14f632ea786753ba12d9651246f9ca0c45ed45354e3246f514dded | Shell | 562 | 19 | #!/bin/sh
set -o allexport
sta_N_std=1
end_N_std=26 #26 #26 for I0~I1
sta_N_batch=1
end_N_batch=20
for i_std in $(eval echo "{$sta_N_std..$end_N_std}")
do
echo "$i_std"
for i_batch in $(eval echo "{$sta_N_batch..$end_N_batch}")
do
echo " $i_batch"
... |
77c481336b3dceb044b0b05cc2baee8156f8cc6375c0cfb2a7be518a4dc8e30c | Shell | 564 | 17 | #!/bin/bash
# define project directory and working directory
pd=/your/project/directory/
input_dir=$pd/data/validations/ATAC_seq_BAM
output_dir=$pd/data/validations/ATAC_seq_BAM_nameSorted
mkdir -p $output_dir
# name sort all BAMs (except the human NPC samples mapped to gorGor6)
for i in `ls $input_dir`
do
if [[ ... |
a98fe6a8967aa22ac0d2232da5b60f1b1f59fb160656d366a24e4193e594b65d | Shell | 564 | 21 | #!/bin/bash
set -e # Stop on error
SH_SCRIPT_DIR=$(cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd)
SRC_DIR=${SH_SCRIPT_DIR}/../src
PIPELINE_CONDA_ENVS=(
encd-atac
encd-atac-macs2
encd-atac-spp
encd-atac-py2
)
chmod u+rx ${SRC_DIR}/*.py
echo "$(date): Updating WDL task wrappers on each Conda environment..."
fo... |
be7b3d43ab887056c0320bb55223f12dbe101d8a8a712884781b124a682f3862 | Shell | 564 | 28 | #!/bin/bash
##
## Runs ARMOR on SRP281230 (not present in recount3)
##
## 11th May 2023
## Izaskun Mallona
WD=~/avillani_microglia
cd $WD
git clone https://github.com/csoneson/ARMOR.git
mv ARMOR/config.yaml{,.original}
cd ARMOR
ln -s ../config_mcquade.yaml config_mcquade.yaml
ln -s ../metadata_mcquade_only.tsv m... |
09c15bf625663f7fc4a2cc312338c0623712dffb1bd521a2d796286734258f5e | Shell | 565 | 19 | #!/bin/bash
tools_dir=$(realpath $(dirname $(command -v $0)))
[[ -d $tools_dir/pkg/freesurfer ]] && rm -rf $tools_dir/pkg/freesurfer
mkdir -p $tools_dir/pkg
pushd $tools_dir/pkg > /dev/null
# download freesurfer
if [[ ! -f freesurfer-linux-ubuntu22_amd64-7.3.2.tar.gz ]]; then
wget https://surfer.nmr.mgh.harvard.e... |
b9530733aabe9ad6006c71e613c37b7f9c6837d364c88da84e327445cb57d24d | Shell | 565 | 21 | #!/bin/bash
#PBS -q batch
#PBS -l walltime=24:00:00 -l nodes=1:ppn=32 -l mem=200G
#PBS -N preprocess_each
#PBS -j oe
#PBS -o /home/whe/qsub_opt/${PBS_JOBID}.${PBS_JOBNAME}.log
script="/home/whe/script/multiomics/withPars/preprocess.R"
conda_env="r4_bio"
_CONDA_ROOT="/home/whe/Programs/miniconda3"
source ${_CONDA_ROOT... |
c5e33457e43bc49fb220f6a0012b1d7911ab88b377860feab5d863df9ddf6b7e | Shell | 565 | 15 | #!/usr/bin/env bash
# Builds the MLflow Javadoc and places it into build/html/java_api/
set -ex
pushd ../../mlflow/java/client/
# the MAVEN_JAVADOC_ARGS env var is used to dynamically pass
# args to the mvn command. this can be used to direct maven to use
# a mirror, in case we encounter rate limiting from maven cent... |
ab388a132b7fe2b448f5b57c6b8d3b5d0504895d3eb648958400d72670ed765c | Shell | 566 | 24 | #!/usr/bin/env bash
set -x
PARTITION=$1
JOB_NAME=$2
CONFIG=$3
CHECKPOINT=$4
GPUS=${GPUS:-8}
GPUS_PER_NODE=${GPUS_PER_NODE:-8}
CPUS_PER_TASK=${CPUS_PER_TASK:-5}
PY_ARGS=${@:5}
SRUN_ARGS=${SRUN_ARGS:-""}
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
srun -p ${PARTITION} \
--job-name=${JOB_NAME} \
--gres=gpu:${GP... |
c28dc4b93ec60d85cc5f696603b6b3df957c5eb434cb9981ca54f50df3828136 | Shell | 566 | 23 | #!/bin/bash
# input and output are separated by comma
IN="$1"
OUT="$2"
# inputFullpaths=($(echo $IN | tr "," "\n"))
# outputPaths=($(echo $OUT | tr "," "\n"))
IFS=',' read -r -a inputFullpaths <<< "$IN"
IFS=',' read -r -a outputPaths <<< "$OUT"
for i in "${!inputFullpaths[@]}"; do
# echo $i
echo ${inputFul... |
55681bbfcaa5815fce6af3115269a21728b9c0bbe6ad756cad9d99bc7f1600b5 | Shell | 567 | 17 | #!/bin/bash
# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
# Download ImageNet1000 dataset https://image-net.org (1000-image subset of ILSVRC2012 train/val)
# Example usage: bash data/scripts/get_imagenet1000.sh
# parent
# ├── yolov5
# └── datasets
# └── imagenet1000 ← downloads here
# Make ... |
9c7e1aecabeb756a43dee09c15c4d207fc7f161e6b2dd9bdc016d3ea380b57e1 | Shell | 567 | 23 | #!/usr/bin/bash
# cd ~/raid/proj/mmcortex
mkdir output
cd output
mkdir paper_figs
cd ..
Rscript scripts/pl/figures/Fig1.r
Rscript scripts/pl/figures/FigS1.r
Rscript scripts/pl/figures/Fig2.r
Rscript scripts/pl/figures/FigS2.r
Rscript scripts/pl/figures/Fig3.r
Rscript scripts/pl/figures/FigS3.r
Rscript scripts/pl/fig... |
d52d6cfc500d1443dd64211f5c50df3059fbc04315a8486f5d1a4f8cce22ffd1 | Shell | 567 | 26 | #!/bin/sh
#required tools
apt-get update && apt-get install -y --no-install-recommends apt-utils\
python3 \
python3-pip \
tar \
wget \
unzip \
git \
libgsl0-dev \
perl \
less \
parallel \
&& \
rm -rf /var/lib/apt/lists/*
# R
apt-get update && apt-get install -y r-bas... |
edae37a75dd07841d879fe37ea2d5b68e6868f966ffd51b7103d3ee5a4591019 | Shell | 567 | 20 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
# Read subject-session pairs from text file
# Replace "subjects_sessions.txt" with your actual filename
while read -r sub ses; do
# Skip empty lines
[[ -z... |
9c1b331547d585d4412bec2ba9d402b8205ecee3f10079be9da1228274238a79 | Shell | 568 | 5 | rm -rf build && mkdir build && cd build
export CC=mpicc
export CXX=mpicxx
cmake .. -DCMAKE_C_FLAGS:STRING="-lrt -g -O0 -mp -mno-abm -acc" -DCMAKE_CXX_FLAGS:STRING="-lrt -std=c++17 -g -O0 -mp -mno-abm -acc" -DCOMPILE_LIBRARY_TYPE=STATIC -DCMAKE_INSTALL_PREFIX="$PWD/../../../install" -DADDITIONAL_MECHPATH="$PWD/../../../... |
828bf596a7acea486a3d21b93da01b5cca5f7ed80fa23e0aeb829a58c6d1bce1 | Shell | 569 | 30 | #!/usr/bin/env bash
# Creates a set of test data for the Funcotator test suite based on
# a COSMIC sqlite3 database file.
LIMIT=500
COSMIC_DB="Cosmic.db"
OUT_CSV_FILE="CosmicTest.csv"
OUT_DB_FILE="CosmicTest.db"
[ -f ${OUT_CSV_FILE} ] && rm ${OUT_CSV_FILE}
[ -f ${OUT_DB_FILE} ] && rm ${OUT_DB_FILE}
sqlite3 Cosmic.... |
290799454bda27c9cb1c79e2ff56b6d197d910cde417386f2d3b8ca9cdb15981 | Shell | 570 | 11 | #!/bin/bash
# this script exports labels from the glasser atlas in the same order they're in in the atlas. We will use this to
# confirm the nifti atlas parcels are ordered correctly. This should be run before
# create_CANLab2023_atlas_unrestricted.m or create_CANLab2023_atlas_cifti.sh scripts
wb_command -label-expor... |
8f7701cd0c0216fb93be7bb6938ef34c20931c1090b0d0c05b4815746e7de9f9 | Shell | 571 | 14 | #!/bin/bash
# This script's purpose is for use with jitpack.io - a repository to publish snapshot automatically
# This script downloads git-lfs and pull needed sources to build GATK in the jitpack environment
GIT_LFS_VERSION="2.5.1"
GIT_LFS_LINK=https://github.com/github/git-lfs/releases/download/v${GIT_LFS_VERSION}/... |
4eea5276bea096e48b7297b3bdd8cc3cb0329f740e7f0d151195d051a5074a88 | Shell | 573 | 19 | #!/bin/bash
#
# Retrieve data for hg38/GRCh38 validation
# https://bcbio-nextgen.readthedocs.org/en/latest/contents/testing.html#example-pipelines
set -eu -o pipefail
mkdir -p config
cd config
wget -c https://raw.githubusercontent.com/bcbio/bcbio-nextgen/master/config/examples/NA12878-hg38-validate.yaml
cd ..
mkdir ... |
22bf5eb5996d97ff92b85b0efe5650e99c0a7d1fc99b2a1cd034deae5b62c8bd | Shell | 574 | 19 | #!/bin/bash
TORCH=$1
CUDA=$2
# 10.2 -> cu102
MMCV_CUDA="cu`echo ${CUDA} | tr -d '.'`"
# MMCV only provides pre-compiled packages for torch 1.x.0
# which works for any subversions of torch 1.x.
# We force the torch version to be 1.x.0 to ease package searching
# and avoid unnecessary rebuild during MMCV's installatio... |
4a390e535ebe111367046c1958d778c8834df68a2f1d3ca6902a65b7321e6c07 | Shell | 574 | 24 | #!/usr/bin/env bash
set -x
PARTITION=$1
JOB_NAME=$2
CONFIG=$3
WORK_DIR=$4
GPUS=${GPUS:-8}
GPUS_PER_NODE=${GPUS_PER_NODE:-8}
CPUS_PER_TASK=${CPUS_PER_TASK:-5}
SRUN_ARGS=${SRUN_ARGS:-""}
PY_ARGS=${@:5}
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
srun -p ${PARTITION} \
--job-name=${JOB_NAME} \
--gres=gpu:${GPUS... |
60a9cae4ac3db7b29830a8a9c2bb0c4cacdfb68401a4334a73d21169c51835f9 | Shell | 574 | 15 | #!/bin/bash
MARKER=$1
NOVIRTUALENV=$2
OTHER_ARGS=${@:3}
# Check if the second argument is provided and if it is equal to --no-virtual-env
if [ -z "$NOVIRTUALENV" ] || [ "$NOVIRTUALENV" != "--no-virtual-env" ]; then
source $GITHUB_WORKSPACE/test_env/bin/activate
fi
pytest -m "$MARKER" -vv -ra --durations=0 --durati... |
e626d60b9752eeb1e55177402350a03fc225236debdf42bc8c79950bfa11754a | Shell | 574 | 14 | #!/bin/bash
source /home/h.bi/miniforge3/etc/profile.d/conda.sh
conda deactivate
#conda activate new_autogluon
conda activate gpu_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_C... |
1e7a2777000ea723608537445c49024efc6bda2818019e61d3005ba68b8c3aa6 | Shell | 576 | 13 | fslroi HarvardOxford-sub-prob-1mm.nii.gz AmygdalaLeft9 9 1
fslroi HarvardOxford-sub-prob-1mm.nii.gz AmygdalaRight19 19 1
# does not work in flirt - use SPM instead
#flirt -in AmygdalaLeft9 -ref mean_func -applyxfm -init IDtfm.mat -out AmygdalaLeft9_lores
#flirt -in AmygdalaRight19 -ref mean_func -applyxfm -init IDtfm... |
ca814ec0493fd2e5ff4a362e37565b795052d1458dde570ba2ec04a7755dc5b0 | Shell | 576 | 21 | #!/bin/bash
echo "Enter the patient folder location: "
read patient
if [ ! -d "$patient" ]; then
echo "Error: Patient folder '$patient' does not exist."
exit 1
fi
echo "Enter the patient group's preprocessed scan subfolder: "
read patient_subfolder
patient_dir="${patient}/${patient_subfolder}"
if [ ! -d "$pa... |
d5976ae427d8ffc37b809a408a2db14fa41c9c873906f8df57b4ffd1e579754c | Shell | 576 | 24 | #!/usr/bin/env bash
umask u+rw,g+rw # give group read/write permissions to all new files
set -e # stop immediately on error
# ------------------- #
# GENERAL DEFINITIONS
# ------------------- #
source $MRCATDIR/setupMrCat.sh
dicomDir="/Volumes/rsfMRI/anaesthesia/dicom"
origDir="/Volumes/rsfMRI/anaesthesia/orig"
ins... |
b7772b902b808ad25b4446e97877989a055d93be45936417ef31dacd486c7ad6 | Shell | 580 | 5 | glmdir=$1 ; contrast=$2 ; hemi=$3 ; fsaverage=$4
## tmin=1.3010: p < 0.05; tmin=1.6021: p < 0.025 (corrected with two hemispheres)
cd ${glmdir}/${contrast}
mri_surfcluster --in sig.cw.pos.mgh --thmin 1.6021 --no-adjust --sign abs --subject ${fsaverage} --hemi ${hemi} --annot aparc.a2009s --mask ../mask.mgh --cwsig sigc... |
7897426504cac87ce8ee0f7e4c9a5e0f75e51915c3c75b1adb1c39f03a3d312f | Shell | 581 | 21 | #!/bin/bash
#conda activate allcools
chrom_size=sorted.hg38.chrom.sizes
bed_path=Dx_peaks_bed
bed_gz=bvFTD.odc.C7.sorted.bed.gz
bedname=peak
echo $bedname
allcools generate-dataset\
--allc_table test_allc_table.tsv\
--output_path /geschwindlabshares/RexachGroup/Xia_Data/heterchromatin/scripts/DxPeak_mC.mcds\
--ch... |
30c7b67fbe1f2f51cf57c665a0fb4acf71de87e9e11d3b8b7676de6d1d64e634 | Shell | 583 | 14 | #!/bin/bash
source /home/h.bi/miniforge3/etc/profile.d/conda.sh
conda deactivate
#conda activate new_autogluon
conda activate gpu_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_C... |
58f7fb325d8bb66780dbfdb817853d55b6980c01afd5f00bbd0b2aa539306d70 | Shell | 583 | 14 | #!/bin/bash
source /home/h.bi/miniforge3/etc/profile.d/conda.sh
conda deactivate
#conda activate new_autogluon
conda activate gpu_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_C... |
a1933b8dc85d00dc9bb085e5b963bcc6eacf81592d403f4c2157110f12d134a4 | Shell | 583 | 14 | #!/bin/bash
source /home/h.bi/miniforge3/etc/profile.d/conda.sh
conda deactivate
#conda activate new_autogluon
conda activate gpu_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_C... |
cb403f0569d17d28e593ab2be0dee188087351d2590b36f705b33ccac99a2579 | Shell | 583 | 31 | #!/bin/bash
[ $# -lt 3 ] && { echo 'Usage :
$1 = folder path
$2 = spreadsheet name(it will not overwrite)
$3 = input suffix (ad/ar/fa etc ...)
[Optional] $4 = roi1 suffix
[Optional] $5 = roi2 suffix';
exit 1; }
folder=$1
name=$(basename $1)
suffix=$3
roi1="6roi"
roi2="7roi"
if [[ $4 != '' ]];
then
ro... |
cb34c897e0f1456587b035abf8bdc0cecd7ce9a763d20b6c2e6eb6e9d7c89a9d | Shell | 584 | 15 | #!/usr/bin/env bash
# Writes the git hash into a generated module and exports the package version and
# git hash. Source it (`source scripts/generate_version.sh`) to reuse the exported
# GIT_HASH / PACKAGE_VERSION in the calling shell.
TARGET_FILE=body_organ_analysis/_githash.py
GIT_HASH=$(git rev-parse --short HEAD)... |
1652f45fa727aa48d187a38dd7fc273173f59cd094b87e66143b3a564e6f2100 | Shell | 585 | 15 | #!/usr/bin/env bash
ver=$(fgrep '#define VERSION ' gffcompare.cpp)
ver=${ver#*\"}
ver=${ver%%\"*}
pack=gffcompare-$ver
echo " preparing source $pack.tar.gz"
echo "------------------------------------"
/bin/rm -rf $pack $pack.tar.gz
mkdir -p $pack/gclib
cp Makefile LICENSE README.md gffcompare.cpp gtf_tracking.{h,cpp} t... |
db232f25d6911cfce12c25d6cd5b74a278d89151f5698d75a7775c31be73e6f3 | Shell | 585 | 8 | #!/usr/bin/env bash
nohup python -m sample_qc.platform_pca --mt_input_path 'file:///home/ubuntu/data/hail_data/mts/chd_ukbb_split_v2_09092020.mt' \
--ht_output_path 'file:///home/ubuntu/data/hail_data/sample_qc/chd_ukbb.platform_pca.ht' \
-... |
30db96b7130bb3d0deb71590e38904d1d1ec5a149f6a66f423e2e6ea22ce91a2 | Shell | 587 | 17 | #!/bin/bash
#SBATCH -c 10 # cores
#SBATCH -t 2-00:00 # 2 days (LR script took similar)
#SBATCH -p medium
#SBATCH --mem-per-cpu=8G # 80G total — banc.dps for ~173k neurons is large
#SBATCH -o jobs/banc_native_%j.out
#SBATCH -e jobs/banc_native_%j.err
start=$(da... |
57aaf55f5a5c9251c7f1559593f99e6c26140977e2d109d7a49f837df5184ccc | Shell | 587 | 19 | #!/bin/bash -e
RUNS=$1
if [[ ! -f $RUNS ]]
then
>&2 echo "ERROR: file $RUNS not found!"
exit 1
fi
KK=`cat $RUNS`
for i in $KK
do
>&2 echo "Processing run ID $i.."
curl "https://www.ebi.ac.uk/ena/portal/api/filereport?accession=$i&result=read_run&fields=study_accession,secondary_study_accession,sample_access... |
d1006ca428f597474bbfef51bdbe417d9ef9b9aa70f4ad491285270718396a06 | Shell | 588 | 20 | # first argument is the directory where freesurfer is installed
# second argument is path to volume (e.g., .mgz) file
# third argument is path to subject directory (not the one in freesurfer)
# set up freesurfer in shell
export FREESURFER_HOME=$1
source $FREESURFER_HOME/SetUpFreeSurfer.sh
# get and store the xfrm ma... |
9567bf1e2072b43d9344e38c95cd1033fb491490f72b7f2ee4d61ee24a6c42d8 | Shell | 589 | 20 | #!/bin/bash
while getopts ":i:g:o:h" opt; do
case $opt in
i) infile="$OPTARG" ;;
g) groupfile="$OPTARG" ;;
o) outfile="$OPTARG" ;;
h) echo "Usage: $(basename "$0") [-i infile] [-g groupfile] [-o outfile]" >&2; exit 0 ;;
\?) echo "Unknown option: -$OPTARG" >&2; exit 1 ;;
... |
a536993413062b7c94aaa81e60af04d8694afce3559654e295ec274808d5882d | Shell | 589 | 20 | #!/bin/bash
#SBATCH --mem=40G
#SBATCH --ntasks=6
#SBATCH -p short
#SBATCH --gres=gpu:1
#SBATCH -t 2-00:00:00
#SBATCH -o //data/scratch/avanhilten/GenNet_logs/out_%j.log
#SBATCH -e //data/scratch/avanhilten/GenNet_logs/error_%j.log
# Load the modules
module purge
module load Python/3.7.4-GCCcore-8.3.0
module load libs... |
2b0eff20826107bda3332e317e12eeb4e20238519cf8c36da67d9cff903cbdd3 | Shell | 590 | 24 | # Freesurfer demo
# test FS
cd ~/Desktop
cp $FREESURFER_HOME/subjects/sample-001.mgz .
mri_convert sample-001.mgz sample-001.nii.gz
# if 'bert' doesn't exist yet
recon-all -i sample-001.nii.gz -s bert -all
# if 'bert' already exists
recon-all -s bert -all
# view results
cd $SUBJECTS_DIR
freeview -v \
bert/mri/T... |
d75ac1296fc785fad9704de10955f2f9415d558639a9ebededed2070d0fd9d37 | Shell | 590 | 25 | #!/bin/sh
module load cesga/2020
module load gcccore/system shapeit4/4.2.1
# pop
pop=${1}
# chr
chr=${2}
# vcfdir
vcfdir=/mnt/netapp2/Store_csebdjgl/lynx_genome/lynx_data/mLynRuf2.2_ref_vcfs
# i_vcf
i_vcf=${vcfdir}/lynxtrogression_v2.autosomic_scaffolds.filter4.${pop}_pop.${chr}.ps.vcf.gz
# gmap
gmap=data/phasing/${c... |
6fbaed8e233ba02491e414ac0b18146b1901fde9e09948d12f89f339ef61ffce | Shell | 591 | 21 | #!/bin/bash
#SBATCH --get-user-env
#SBATCH --job-name=gencode_cov2db
#SBATCH --chdir=/projects/verhaak-lab/USERS/johnsk/glass4
#SBATCH --output=/projects/verhaak-lab/USERS/johnsk/glass4/logs/gencode_cov2db/gencode_cov2db_glss_lx_batch2.log
#SBATCH --mail-type=FAIL
#SBATCH --mail-user=kevin.c.johnson@jax.org
#SBATCH --... |
2ac1687992ebd98b3ac1edf844eebe85c9fc52e3d560d6d9cbcd7f4d5d372e6f | Shell | 592 | 19 | #!/bin/bash
# Get base_name from command line argument
base_name="$1"
# Specify the directory
DIRECTORY="./STEP4.LDproxy_Testing_Geno/LD_output"
output_file="$DIRECTORY/$base_name.vcor"
# Check if the output file already exists
if [[ -f "$output_file" ]]; then
echo "Skipping $base_name: $output_file already ex... |
368f0b0db68ba37f029062095bda742232c49d06253ebb86ed24364897717ec6 | Shell | 593 | 29 | #!/bin/bash
key=$1
if [[ -z "$key" ]]; then
echo "Usage: $0 {strs|snps|combined}" >&2
exit 1
fi
case "$key" in
strs|snps|combined) ;;
*)
echo "Error: key must be one of strs, snps, combined" >&2
exit 1
;;
esac
plink_ressources="--memory 32000 --threads 2"
basedir=data/heritab... |
7d854f2dae68d5ab2b5b85d91e3aff1e8a3555c9d63e5e95134a46e57bc60ee9 | Shell | 593 | 25 | dir=***
tfs=$dir/hs_hgnc_tfs.txt
feather=$dir/hg19-tss-centered-10kb-10species.mc9nr.genes_vs_motifs.rankings.feather
tbl=$dir/motifs-v9-nr.hgnc-m0.001-o0.0.tbl
input_loom=$dir/sample.loom
ls $tfs $feather $tbl
pyscenic grn \
--num_workers 10 \
--output adj.sample.tsv \
--method grnboost2 \
sample.loom \
$tfs
pyscen... |
aa2ccc133a14da67e6be985cc597c2079e70d149320be648e04b7229c90c4ad8 | Shell | 593 | 20 | #!/bin/bash
# Finetune generator with hybrid approach: log_k predictor + regex carbanion filter
python finetune_generator_carbanion_hybrid.py \
--train ./data/seed_carbanions.smi \
--vocab ./data/chembl_vocab.txt \
--generative_model ./hgraph2graph/ckpt/chembl-pretrained/model.ckpt \
--chemprop_model ./models/... |
61c7dcec57514e1da08b21cca1b43b1d365daa4a9631d9abffd125de7fad0f8f | Shell | 594 | 22 | #!/bin/bash
#SBATCH --get-user-env
#SBATCH --job-name=liftovervcf-%a
#SBATCH --chdir=/projects/verhaak-lab/USERS/johnsk/glass4
#SBATCH --output=/projects/verhaak-lab/USERS/johnsk/glass4/logs/mutect2/liftover/liftover-b37tohg38-%a.log
#SBATCH --mail-type=FAIL
#SBATCH --mail-user=kevin.c.johnson@jax.org
#SBATCH --ntasks... |
b20a572f0b0d86eb44931dfd61ac0c36a59f6d4d21d55fc53903161cbb8ab0ba | Shell | 594 | 14 | #!/bin/bash
source /home/h.bi/miniforge3/etc/profile.d/conda.sh
conda deactivate
#conda activate new_autogluon
conda activate gpu_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/sleep_ENIGMA_C... |
0701163434d51c6331c71e18adfc78ea438c001cda6934b8ab74021ac05a9731 | Shell | 595 | 13 | #!/bin/bash
#source /home/h.bi/miniforge3/etc/profile.d/conda.sh
#mamba deactivate # harmless if nothing is active
mamba activate new_autogluon
# Set the environment variables
export MKL_NUM_THREADS=1
export OPENBLAS_NUM_THREADS=1
export NUMEXPR_NUM_THREADS=1
export OMP_NUM_THREADS=1
python3 /data/project/s... |
6eb29721f5dfe7d8f6cec8be1145a8819b4f6812e43687c388a90e6c0553a17a | Shell | 597 | 20 | #!/bin/sh
set -o allexport
sta_i_pCaLs=1
end_i_pCaLs=24
sta_i_batch_KM=1
end_i_batch_KM=16
n_batch_KM=1
for i_pCaLs in $(eval echo "{$sta_i_pCaLs..$end_i_pCaLs}")
do
echo " $i_pCaLs"
for i_batch_KM in $(eval echo "{$sta_i_batch_KM..$end_i_batch_KM..$n_batch_KM}")
do
... |
20f2c29d8f46ab32b35dec689573123124c4b0580b1e3015e89be9f6ef7a6fbc | Shell | 598 | 26 | #!/bin/bash
#SBATCH --gres=gpu:1
#SBATCH --cpus-per-task=2
#SBATCH --mem=10G
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --time=7-00:00:00
#SBATCH --account=def-qingrunz-ab
#SBATCH --job-name=pro
#SBATCH --error=%N-%j.error
#SBATCH --output=%N-%j.out
###Cedar
#module load StdEnv/2020 #cudnn/8.2.0, cuda/11.4
#module ... |
233843e9864a3619b5f12a25398d8be7e3cae0cd00d92b6ce9cc5070c0f0ec7b | Shell | 598 | 22 | #!/bin/bash -l
#SBATCH --job-name=modelbuild
#SBATCH --time=1:00:00
#SBATCH --account=proj83
#SBATCH --partition=prod
#SBATCH --mem=0
#SBATCH --exclusive
#SBATCH --constraint=cpu
source ../venv/bin/activate
python -u run_batch_modelling.py ./adj_r0c10.npz ./nodes_r0c10.h5 ./run_batch_modelling.json $1 $2
# EXAMPLES ... |
0a33c139119c187386c3e23f7085b3966c8964ecb0a775318a265aec13b83a03 | Shell | 603 | 25 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
basedir="$(dirname "$scriptdir")"
for subinfo in "105 01" "105 02" "105 03" "105 04" "105 05" "105 06" "105 07" "105 08" "105 09" "105 10" "105 11" "105 12"... |
41036f88acd5f592b5d7d7687448d919f97968b0e2db3745ef44827f0655a5c5 | Shell | 605 | 31 | #!/bin/bash
echo Running tests
source tools/ci/activate.sh
source tools/ci/env.sh
set -eu
# Required variables
echo CHECK_TYPE = $CHECK_TYPE
set -x
if [ "${CHECK_TYPE}" == "test" ]; then
pytest --capture=no --verbose --doctest-modules -c nipype/pytest.ini \
--cov-config .coveragerc --cov nipype --cov-... |
f44c7df9632c3ecfade09e4914b58ddff272cce4b134094038b6b33991ade2f8 | Shell | 605 | 21 | #!/bin/sh
set -o allexport
sta_i_pCaLs_d=1
end_i_pCaLs_d=3
sta_i_Kir_s=1
end_i_Kir_s=3
n_batch_Kir_s=1
for i_pCaLs_d in $(eval echo "{$sta_i_pCaLs_d..$end_i_pCaLs_d}")
do
echo "$i_pCaLs_d"
for i_Kir_s in $(eval echo "{$sta_i_Kir_s..$end_i_Kir_s..$n_batch_Kir_s}")
do
... |
1edc53ebb429d267932bc6c40013ceb908a36f5ea638e237878c1ddf70f3fdf2 | Shell | 606 | 27 | #ATAC correct Tobias - subsample and then perform tn5 shift
#conda activate tobias_env
INDIR=bam
GENOME=GRCh38.primary_assembly.genome.fa
OUTDIR=subc_specific_peaks
PEAKDIR=ldsc/data/cluster_specific_atacPeak
groups=("ast.C1" "mg.C4")
for group in ${groups[@]}
do
prefix=${group//./} # astC1 mgC4
bam="Subtype_"$pre... |
5b958b878d47d6c9ee4fcfac27ab5aead14075a8a6f29995e877a8618aaffab2 | Shell | 607 | 26 | #!/bin/bash
input_dir="/opt/notebooks/extract_tmp"
output_dir="/opt/notebooks/extract_tmp"
export input_dir
export output_dir
export FSLDIR
# Function to process a single NIfTI file
process_file() {
input_file="$1"
base_name=$(basename "$input_file" _00.nii.gz)
affine_mat="${output_dir}/${base_name}_affine.ma... |
20c391cac1a38eab2fb21cc04c3580dd302160944c1542685c2887033c2865b1 | Shell | 610 | 15 | apt-get -qq update && apt-get -qq -y install curl bzip2 \
&& curl -sSL https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh -o /tmp/miniconda.sh \
&& bash /tmp/miniconda.sh -bfp /usr/local \
&& rm -rf /tmp/miniconda.sh \
&& conda install -y python=2 \
&& conda u... |
a9283cda38b139ce8c84d44c7d6fb3205492accaa8ec047cae96ac6d6ca0fac8 | Shell | 610 | 11 | #!/bin/bash
cd /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_nopreproprcessing/
var=0;
for filename in `ls -d *`
do
echo $filename
echo $var
sh /lustre/atlas/proj-shared/nro101/BigNeuron/gen_bench_job_text_scripts.sh aniso /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_nopreproprcessi... |
0fa5bb59cb51a02fed6ff64cf0b49f699758d4b11dc8fb69e2613e0a249788c0 | Shell | 612 | 17 | SETUP_REQUIRES="pip setuptools>=30.3.0 wheel"
# Minimum requirements
REQUIREMENTS="-r requirements.txt"
# Minimum versions of minimum requirements
MIN_REQUIREMENTS="-r min-requirements.txt"
# Numpy and scipy upload nightly/weekly/intermittent wheels
NIGHTLY_WHEELS="https://pypi.anaconda.org/scipy-wheels-nightly/simpl... |
0f0b8c255988e96d1480c5bb11adc2c26067e68d9d90b65dc6cbe1b649a089eb | Shell | 613 | 22 | #!/bin/bash
# ensure paths are correct
maindir=/gpfs/scratch/tug87422/smithlab-shared/night-owls #this should be the only line that has to change if the rest of the script is set up correctly
scriptdir=$maindir/code
mapfile -t lines < "$scriptdir/sublist-ses.txt"
pairs=()
for line in "${lines[@]}"; do
# split into ... |
07210cebce4be8e23268c84ef43d50ae42773fdb44d224ece885ea0b6ff0c9e8 | Shell | 614 | 20 | #!/bin/bash
# Set project directories
project_dir="/project/normative_cerebellum"
input_dir="${project_dir}/data"
output_dir="${project_dir}/segmentations/acapulco"
# Subject list
subject_list="${project_dir}/all_subjects.txt"
# Loop through each subject in the list and run ACAPULCO via Singularity container
while... |
afdc177e304d36200af11b27dfb1f85fd43a8737a83baa6308d597fd2cde808f | Shell | 615 | 12 | #!/bin/sh
# Written by Pansheng Chen and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
# This script is specific to CBIG HPC cluster.
rep_dir="$CBIG_CODE_DIR/stable_projects/predict_phenotypes/Chen2024_MMM/replication/"
log_dir="${rep_dir}/log"
mkdir -p ${log_dir}
cmd="cd ${rep_di... |
da18ae7239f50e8631c7f4dc2b60ff515be9e25ffb4a1ba50efc1fa767e91bef | Shell | 615 | 11 | #!/bin/bash
cd /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_nopreproprcessing/
var=0;
for filename in `ls -d *`
do
echo $filename
echo $var
sh /lustre/atlas/proj-shared/nro101/BigNeuron/gen_bench_job_text_scripts.sh smooth /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_nopreproprcess... |
456723579370c2acbd57be26699b06bc07fa19f23ab7fa99ceb372d10db50d9c | Shell | 617 | 21 | #!/usr/bin/env bash
set -euo pipefail
DGX_USER="${USER:-$(id -un)}"
JOB_NAME="${JOB_NAME:-wbp-subject-metrics}"
PROJECT="${PROJECT:-${DGX_USER}}"
IMAGE_TAG="${IMAGE_TAG:-aicregistry:5000/${DGX_USER}:nnunet-wbp-metrics}"
RUN_SCRIPT="${RUN_SCRIPT:-/nfs/home/${DGX_USER}/nnunet-tree-semantic-extension/scripts/dgx/run_wbp_... |
5861abe6d487a54f589b5363c26eb48ddea80679e167f2a797c23678d0e3e8c9 | Shell | 617 | 21 | #!/bin/sh
set -o allexport
sta_i_pCaLs_d=1
end_i_pCaLs_d=31
sta_i_Kir_s=1
end_i_Kir_s=41
n_batch_Kir_s=1
for i_pCaLs_d in $(eval echo "{$sta_i_pCaLs_d..$end_i_pCaLs_d}")
do
echo "$i_pCaLs_d"
for i_Kir_s in $(eval echo "{$sta_i_Kir_s..$end_i_Kir_s..$n_batch_Kir_s}")
do
... |
9cafd0cf674e098e9fff763dcf38b692a61e53c86b48cdcd7b8032a8e4f0e849 | Shell | 617 | 31 | #!/bin/bash
# build, test and generate docs in this phase
set -ex
. "$(dirname $0)/utils.sh"
main() {
# Test a normal debug build.
cargo build --target "$TARGET" --verbose --all
# Show the output of the most recent build.rs stderr.
set +x
stderr="$(find "target/$TARGET/debug" -name stderr -prin... |
dd9d18b41dc9441679221057ddd7dac36f05e676181d7478c21734c31e15320f | Shell | 617 | 28 | #!/bin/bash
echo "Building archive"
source tools/ci/activate.sh
set -eu
# Required dependencies
echo "INSTALL_TYPE = $INSTALL_TYPE"
set -x
if [ "$INSTALL_TYPE" == "sdist" ]; then
python setup.py egg_info # check egg_info while we're here
python setup.py sdist
export ARCHIVE=$( ls dist/*.tar.gz )
elif... |
0dd31210016cb1f561ebbc746fcaf4153f032b538c9813c3dbe7d1147574f80b | Shell | 618 | 15 | #!/bin/bash
# Written by Yapei Xie and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
# load config
source ${CBIG_CODE_DIR}/stable_projects/predict_phenotypes/Xie2025_LBC/replication/config/CBIG_LBC_tested_config.sh
# run longitudinal ComBat on cognition data
Rscript "${CBIG_CODE_... |
34ec0d0818dbcee7cddab0145a118ac84293d15a1a50bd74f4399920153e92a8 | Shell | 618 | 21 | #!/bin/sh
set -o allexport
sta_i_pCaLs_d=20
end_i_pCaLs_d=25
sta_i_Kir_s=1
end_i_Kir_s=41
n_batch_Kir_s=1
for i_pCaLs_d in $(eval echo "{$sta_i_pCaLs_d..$end_i_pCaLs_d}")
do
echo "$i_pCaLs_d"
for i_Kir_s in $(eval echo "{$sta_i_Kir_s..$end_i_Kir_s..$n_batch_Kir_s}")
do
... |
5ee023202d93c7c9c0e963af5ccce971c11087be2bacc852dbb16d8d0407158a | Shell | 618 | 27 | #!/bin/bash -e
echo "Running tests"
echo CHECK_TYPE = $CHECK_TYPE
xvfbrun=
if [[ "$OPTIONAL_DEPENDS" == *"pysurfer"* ]]; then
xvfbrun='/usr/bin/xvfb-run --auto-servernum'
fi
if [ "$CHECK_TYPE" == "style" ]; then
flake8 netneurotools
elif [ "$CHECK_TYPE" == "doc" ]; then
cd docs
make html && make doct... |
8b5b9a6f9c596b39ef7dd7bc2d8049af8a50e0a72741239ee503188cd55e11f2 | Shell | 619 | 20 | #ATAC correct Tobias - subsample and then perform tn5 shift
#conda activate tobias_env
OUTDIR=/geschwindlabshares/RexachGroup/Xia_Data/atac_cellrangerOut/tobias/subc_specific_peaks
groups=("ast.C1" "mg.C4")
for group in ${groups[@]}
do
PEAK=/geschwindlabshares/RexachGroup/Xia_Data/ldsc/data/cluster_specific_atacPeak... |
46e43e8405f77ce11ccd2eb02f2d7e7512ba417a2792fd769ca03f252de04a51 | Shell | 620 | 35 | #!/bin/sh
#NETSCAPE='/u3/local/hines/netscape/netscape'
NETSCAPE=`which netscape`
help='http://neuron.yale.edu/neuron/help'
#help="file:$NEURONHOME/html/help"
#dict=$NEURONHOME/lib/helpdict
#echo "$*"
#url=`sed -n '/^'"$*"'/{
# s/.* //p
# q
#}' $dict`
url=$1
if [ -z "$url" ] ; then
echo "|$*|"
url='contents.h... |
48e44dfb75c148d63c464666077d972ea111bc19f56ebd614e5469de609b0811 | Shell | 620 | 20 | #!/bin/bash
#SBATCH --job-name=symbolic-model_%a
#SBATCH --output=logs/symbolic-model/stanfit/hierarchical/%A_%a.out
#SBATCH --error=logs/symbolic-model/stanfit/hierarchical/%A_%a.err
#SBATCH --array=1-20%20
#SBATCH --time=12:00:00
#SBATCH --cpus-per-task=4
#SBATCH --mem=32G
# Run the Julia script
module load Julia
mo... |
d6e2a573bc7ced2d2b00d2556214aab6e64fe73f7df33f57108a9244556b61fc | Shell | 620 | 19 | #!/usr/bin/env bash
# Create BigQuery tables for running performance tests against.
#
# This script is intended to be run once, and the tables are intended to be reused without modification by the performance tests.
# Note that this script takes about 5 minutes to run.
set -exu
dataset=${GE_TEST_BIGQUERY_PEFORMANCE_... |
21336af002d6069e87665799c1f147eeb457f0ed224add6e808f99df4864d534 | Shell | 622 | 19 | #!/bin/bash
# Copyright (c) Meta Platforms, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
set -ex
# MKL
mkdir -p /opt/intel/lib
pushd /tmp
wget -q https://anaconda.org/intel/mkl-static/2019.4/download/linux-64/mkl-... |
41bdc235e527b0496159ddf0e7d8e6683f3665834b2e6692f22ea86b40e7e929 | Shell | 622 | 22 | #Path of individual brain images
DataPath=$1
#Path of Age-Specific Templates (Output path in last step)
ASTPath=$2
#Age group or prefix of ASTs
age=$3
#Individual ID
sub=$4
#output Path
outputPath=$5
mkdir -p ${outputPath}
Indiimage=`ls ${DataPath}/${sub}*`
##fast segmentation
fast -n 3 -g -b -o ${outputPath}/${sub} -... |
1943267b3233bed0b3a44644bda0c37bea23caa74ab3993bcdae1c05ee5a4c3f | Shell | 626 | 21 | #! /bin/bash
step=1
## Extract TIV data
if [[ $step -eq 1 ]]
then
sour_dir=/Data/sharehome/huyang/HuYang/HY_20250709/PROCDATA/NIIDATA/T1
targ_dir=/Data/sharehome/huyang/HuYang/HY_20250709/PROCDATA/STATS/T1/TIV
mkdir -p ${targ_dir}
sublist=/Data/sharehome/huyang/HuYang/HY_20250709/PROCDATA/LIST/sublist_i... |
5de47c48744f2ebec9e263fc3a1d3ce32dedef100afda8cd4274764887883ae6 | Shell | 626 | 26 | #!/bin/bash
export OMP_NUM_THREADS=48
# export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
torchrun --nnodes=1 --nproc_per_node=8 run_vqhbr_training.py \
--output_dir checkpoints/vqhbr/MIMIC-IV/ \
--log_dir log/vqhbr/MIMIC-IV/ \
--model vqhbr \
--codebook_n_emd 8192 \
--codebook_emd_dim 128 \
--quan... |
ae632744d647cc9e58426c99ada623d041581336a5f5bb64c7e68c715eb7447d | Shell | 627 | 20 | #!/bin/bash
# Script to build and push the devcontainer image to GitHub Container Registry
# This allows caching the image between Codespace sessions
# You'll need to run this with appropriate GitHub permissions
# gh auth login --scopes write:packages
REGISTRY="ghcr.io"
OWNER="apache"
REPO="superset"
TAG="devcontaine... |
4babbd43d1747895ae91bd2811472eb5162ab3c9f80dcf013126275a5877d9be | Shell | 630 | 27 | #!/bin/bash
# Ensure paths are correct irrespective from where user runs the script
projectdir=/gpfs/scratch/tug87422/smithlab-shared/night-owls
scriptdir=$projectdir/code
basedir="$(dirname "$scriptdir")"
mapfile -t myArray < "${scriptdir}/sublist.txt"
# grab the first n elements
ntasks=1
counter=0
while [ $co... |
6569a295fa507bf3a08e9da60b9cb450b23bb5947d7c63c7d005c2b828da1a87 | Shell | 630 | 18 | #!/usr/bin/env bash
set -euo pipefail
echo ">>> RUN: Brain × Stroop"
bash run_AutoGluon_SHIP_Stroop_NAI_no_DK.sh Brain Stroop 20 0
echo ">>> RUN: Sleep_Cov_Brain_Shuffle × Stroop"
bash run_AutoGluon_SHIP_Stroop_NAI_no_DK.sh Sleep_Cov_Brain_Shuffle Stroop 20 0
echo ">>> RUN: Brain × Memory"
bash run_AutoGluon_SHIP_St... |
8d65747367560048245b23e249a3aa2b629cb84c24397ea1171ad0df927433f0 | Shell | 633 | 20 | #!/bin/bash
#SBATCH --job-name=adni_preprocess
#SBATCH --ntasks=24
#SBATCH --mem-per-cpu=16G
#SBATCH --time=12-24:00:00
#SBATCH --output=slurm_%j.out
module load anaconda3
module load matlab
export LC_ALL=en_US.UTF-8
export LANG=en_US.UTF-8
export MATLAB_HOME=HOME/TO/MATLAB
export PATH=${MATLAB_HOME}:${PATH}
export M... |
afc1df80867f3c62d8538c613925ea0d72e56909708e2283a6e9a9c2860b73b7 | Shell | 635 | 13 | #!/bin/bash
# uncomment next line for interactive checking of generated output
PYTHON="ipython2 --pylab -i"
# non-interactive shell. Check results afterwards
PYTHON="python2.7"
# One neurite with two branches. Both branches grow straight to the pia.
time PYTHONPATH=to_pia/:$PYTHONPATH python ../Admin.py 8 to_pia/to_p... |
b3ded9e4964c2d3c76ff52c8752315bc1c374cbd5bf9a19de2070cefe49a8c13 | Shell | 636 | 22 | #!/usr/bin/env bash
set -euo pipefail
DGX_USER="${USER:-$(id -un)}"
IMAGE_TAG="${IMAGE_TAG:-aicregistry:5000/${DGX_USER}:nnunet-wbp-metrics}"
TORCH_INDEX_URL="${TORCH_INDEX_URL:-https://download.pytorch.org/whl/cu121}"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
REPO_ROOT="$(cd "${SCRIPT_DIR}/../.." &&... |
3dfee521a66d2b9a47d194eb9462f2d107298b1933e8994820f9367c0c12cfee | Shell | 639 | 32 | #!/bin/bash
shopt -s extglob
TUNING_DIR="./calibration/forcepss/tune"
SIM_DIR="./results/sim"
ENS_DIR="./results/ens"
ENS_DIR="./results/png"
if [ -d $TUNING_DIR ]; then
rm -vr $TUNING_DIR
echo "Removed tuning directory ..."
fi
if [ -d $SIM_DIR ]; then
rm -vr $SIM_DIR
echo "Removed simulation directory ..."... |
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