sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
928629a0819878167e01af5b066624ce2a94c107942af82aae54750389cd25d3 | Shell | 737 | 11 | #!/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="${CBIG_CODE_DIR}/stable_projects/predict_phenotypes/Chen2024_MMM/replication/"
rep_dir="$CBIG_CODE_DIR/stable_projects/predict_phenotypes... |
00a1ab76c245ca364dba984894422aefa5c0660a4e20478d4e5d40b49f5d3f39 | Shell | 738 | 22 | #!/bin/bash
#SBATCH -c 1 # Request cores
#SBATCH -t 00-12:00 # Runtime in D-HH:MM format
#SBATCH -p short # Partition to run in
#SBATCH --mem-per-cpu=250G # Memory per core
#SBATCH -o jobs/manc_skel_%j.out # File to which STDOUT will be ... |
031d2293e0bb962e08949c6cdc9f842519efd53413f2d8b38e8dd346bfa2d45f | Shell | 738 | 28 | #!/bin/bash
#SBATCH -p gpu
#SBATCH -t 5-00:00:00
#SBATCH -n 1
#SBATCH -c 16
#SBATCH --gpus-per-node=1
#SBATCH -J GenNet_classification
#SBATCH --mem=128G
#SBAYCH --mem-per-gpu=127G
#SBATCH -o /home/ahilten/repositories/GenNet/GenNet_utils/SLURM_logs/out_%j.log
#SBATCH -e /home/ahilten/repositories/GenNet/GenNet_utils/... |
f44c5b73e43a33f385a7f442e2b7419ee242521f6ea19f99829f8d6f94f5e653 | Shell | 738 | 10 | #!/bin/bash
# A script to generate physical regions so that I can write a pytest for the
# python version
# Assume that chr is at 1, start_pos is at 2 and tab delimited
REGION="${1:-10000}"
tail -n+2 |
sort -k1,1 -k2,2n -t$'\t' |
awk -vregion="$REGION" 'BEGIN{FS="\t"; OFS="\t"; nsites=0; nchr=0; last_start=0; i... |
a3943970ec3c819e8af6b155f230db8b407bf74d87996115c7ba03eb2452edad | Shell | 744 | 24 | #!/bin/bash
# Author: Andrew Hamel
# Affiliation: Massachusetts Eye and Ear, Harvard Medical School
# Date: June 2022
#
#
# This script prepares a gene set input file from a given resource
# to be used when running GeneEnrich
#
# Input files can be downloaded from GENCODE website
# example symbols and entrez files dow... |
0182296ab38f58d1926b9ce6a063e07865bc35de522a27f96834d7b7969dbe8a | Shell | 747 | 22 | #!/bin/bash
#SBATCH -c 1 # Request cores
#SBATCH -t 00-120:00 # Runtime in D-HH:MM format
#SBATCH -p medium # Partition to run in
#SBATCH --mem-per-cpu=250G # Memory per core
#SBATCH -o jobs/malecns_%j.out # File to which STDOUT will be ... |
10943ffead46bd44ea75103e583d8c6e4a3cd4bc434d5e029f0d8ce444ccaf1e | Shell | 750 | 23 | #!/bin/bash
export SUBJECTS_DIR=... # Set your SUBJECTS_DIR here.
fsgd_base_dir=... # Set your fsgd_base_dir here.
fsgd_file=${fsgd_base_dir}/fsgd_increase.fsgd
for hemi in lh rh; do
for smoothness in 10; do
for meas in volume thickness area; do
mri_glmfit \
--y ${hemi}.${meas}.${smoothness}.mgh... |
114ac7711f9ccea2c7d0471b9b3858ff6a96d5b7f73ebcc9bafd25189bdcbe66 | Shell | 750 | 33 | #!/bin/bash
#
# performancetest_lorenz_2.py with several different settings on a SLURM batch system.
# Submit using command "sbatch".
#
#SBATCH -A cidbn
#SBATCH -p cidbn
#SBATCH --job-name=te_mp
#SBATCH --output=performancetest_lorenz_2_mpi_%A.txt
#SBATCH --time=24:00:00
#SBATCH --ntasks=64
#SBATCH --cpus-per-task=1
#S... |
efa17dbed2975fb3f5fd7dff0e431c09e9ce0494157b20a0a345979410a66d5e | Shell | 750 | 21 | #!/bin/bash
#SBATCH --job-name=myeloid-%a
#SBATCH --chdir=/vast/palmer/scratch/verhaak/kcj28/
#SBATCH --output=/vast/palmer/pi/verhaak/kcj28/care_mut/logs/nmf_2026/myeloid_no_parallel/nmf_2026_myeloid_nopar_caremut-%a.log
#SBATCH --error=/vast/palmer/pi/verhaak/kcj28/care_mut/logs/nmf_2026/myeloid_no_parallel/nmf_2026... |
3a8bd29704e592b2bf847b26d27ea93a9ed9a59fa5ce52da4cae5bab83faae0c | Shell | 752 | 30 | #!/bin/bash
conda activate cyclegan_ulf
python test.py \
--image ../data/CycleGAN/ULF/test \
--result ../output/cyclegan_output \
--batch_size 1 \
--patch_size 128 128 128 \
--netG resvit \
--name cyclegan_model_1 \
--checkpoints_dir ../models/ \
--input_nc 2 \
--output_nc 2 \
-... |
8579a9a0148588a555155c1a2bc6efb5dae2edd9ab7680545df04032b0b4750b | Shell | 753 | 28 | if [ "$1" == "imagenet32" ]; then
echo "downloading imagenet32"
wget http://www.image-net.org/small/train_32x32.tar
wget http://www.image-net.org/small/valid_32x32.tar
tar -xvf train_32x32.tar
tar -xvf valid_32x32.tar
python files_to_npy.py train_32x32/ imagenet32-train.npy
python files_to_npy.py valid_32x32/ imagenet... |
8b5677a7a9b0656452ad0df5e10f19b73b5924669e8c32ffc469a1d11dea9baf | Shell | 753 | 17 | #!/bin/bash
set -e # this will stop the script on first error
# get the name of the current conda environment
ENV_NAME=$(basename "$CONDA_PREFIX")
# print the name of the current conda environment to the terminal
echo "Building flowmol into the environment '$ENV_NAME'"
mamba install pytorch=2.2.0 torchvision torchau... |
61137f5720f850e51707dca7fbc39589ca48098981e6457552e3690d0b3aaa8e | Shell | 754 | 32 | #!/bin/bash
# you can run this script to initialize the evo2 environment on a cluster. or ssh to the cluster and run it there.
dt=$(date '+%d_%m_%Y_%H_%M');
git clone --recurse-submodules https://github.com/ArcInstitute/evo2.git
cd evo2
# require python 3.11.11 and cuda 12.6
# set python enviroment
python -m venv .v... |
a35d8c6b70e2d220fd9718f13aa160843437ebb9d8b172c093b6ce9211638b77 | Shell | 754 | 28 | #!/bin/bash
#SBATCH --job-name=caremut-archr
#SBATCH --chdir=/vast/palmer/pi/verhaak/kcj28/care_idh_mut/results/atac
#SBATCH --output=/vast/palmer/pi/verhaak/kcj28/care_idh_mut/logs/archr/caremut-create-arrow.log
#SBATCH --mail-type=FAIL,END
#SBATCH --mail-user=kevin.c.johnson@yale.edu
#SBATCH --ntasks=1
#SBATCH --cpus... |
efea7ef8f0773af05a6fcb7ac59724dc927a0fd8b2f9ab2d32b120d69e24cc06 | Shell | 754 | 40 | #!/bin/bash
########################################
#OMEGA
########################################
export path_htsa_dir=$1
export path_pipeline=$2
export omega_work_dir=$3
export PAIR1=$4
export PAIR2=$5
cd $project_work_dir
echo "starting omega assembly..."
if [ -d $omega_work_dir ];
then
rm -r $omega_work_di... |
969ce5f9f3360929a4073cc52f95eaaac5cd65e996b9657e56cd01f947d4ed4d | Shell | 756 | 12 | #!/usr/bin/env bash
# Run the pipeline (ReadsPipelineSpark) on exome data in HDFS.
. utils.sh
time_gatk "ReadsPipelineSpark -I hdfs:///user/$USER/exome_spark_eval/NA12878.ga2.exome.maq.raw.bam -O hdfs://${HDFS_HOST_PORT}/user/$USER/exome_spark_eval/out/NA12878.ga2.exome.maq.raw.vcf -R hdfs://${HDFS_HOST_PORT}/user/$... |
6fd50ca54ed0575719730e7028c69e38cc803050c713797a1d9404fbe2064bd9 | Shell | 759 | 34 | for i in {0}
do
python ./train_space.py \
-gpu_ids '0,1' \
-wandb_entity [your_wandb_entity] \
-wandb_project [your_wandb_project] \
-net_teacher 'resnet18' \
-net_student 'resnet18' \
-downsample_factor 1.0 \
-alpha 0.3 \
-temp 3.0 \
-lr 0.01 \
-interval_rate 0.0 \
-b 128 \... |
c520901a56cde0174de1105ad92042886740ad4097825d9d678eff5935aacfa8 | Shell | 760 | 26 | #!/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
LOG="/data/project/sleep_ENIGMA_Cogn... |
26a27cd68652f72bb866e4500f7e60d8d6d8e53001f8fce15cc48819db7044fe | Shell | 761 | 23 | #!/bin/bash
#SBATCH -J banc_synapse_prop_plot
#SBATCH -c 4
#SBATCH -t 0-04:00
#SBATCH -p priority
#SBATCH --mem=64G
#SBATCH -o /home/ab714/bancpipeline/jobs/banc_synapse_proportion_plot_%j.out
#SBATCH -e /home/ab714/bancpipeline/jobs/banc_synapse_proportion_plot_%j.err
# Standalone plot regeneration for banc_synapse_p... |
1fdd933adc7d698712862f5d029636167720e93c5cdb1b8b93905ed38ffcd970 | Shell | 762 | 21 | #!/bin/bash
set -xe
echo "Activating test environment:"
conda activate testenv
which python
# Show python version and build information (e.g. free-threaded or not)
python -VV
python -c "import multiprocessing as mp; print('multiprocessing.cpu_count():', mp.cpu_count())"
python -c "import joblib; print('joblib.cpu_co... |
366d53df7ff1580f0c5f2d57e541bae895303013adb8cab815774c6d2c4755d9 | Shell | 762 | 11 | #!/bin/bash
cd /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_anisosmooth/
var=0;
for filename in `ls -d *`
do
echo $filename
echo $var
mkdir /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/reconstructions_for_img_anisosmooth/$filename
sh /lustre/atlas/proj-shared/nro101/BigNeuron/Vaa3D_s... |
45d287f73608b3408941c3deec35f9b054c78e7e0b650252adb81024e02a0816 | Shell | 764 | 26 | #!/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
LOG="/data/project/sleep_ENIGMA_Cogn... |
e280abd25bd365a036ce58358d9de587e6b11c52486a5795b8ee75f0241df995 | Shell | 764 | 34 | #!/bin/bash
#conda activate allcools
chrom_size=sorted.hg38.chrom.sizes
mC_path=03_bgzip_tbi
bed_path=Dx_peaks_bed
input_mC=sort.hg38.allc_Astro.tsv.gz
oprefix=${input_mC#*.hg38.}
oprefix=${oprefix%.tsv*}
echo $oprefix
declare -A bed_paths
declare -A group_names
id=0
for i in `cat list.tbi`
do
path=$bed_path... |
bf604fc2c1990c98e8cbd7cc7bc6773b5e286f1c4d71197c5cd254803473c77d | Shell | 765 | 23 | #!/bin/bash
mkdir temp_annot # make a temporary directory to host the intermediate files
Data_File="/data1/meaneylab/eamon/MAGMA/MAGMA_aux_files/1000_genomes_euro/g1000_eur"
Annot_File="/data1/meaneylab/eamon/MAGMA/MAGMA_aux_files/H-MAGMA_aux_files/HMAGMA_Protocol/Annotation_Files/Adultbrain.transcript.annot"
SNP_P... |
80827016ff48c32dc492b5a45822451b1c442b96357b5c34493f1440383481a9 | Shell | 768 | 13 | #!/bin/bash
set -eu -o pipefail
# Genome data
wget -O NA12878_1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR194/ERR194147/ERR194147_1.fastq.gz
wget -O NA12878_2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR194/ERR194147/ERR194147_2.fastq.gz
wget -O NA12891_1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR194/ERR1... |
cba7a85dbcf26e76c444903800115b60a99bd486c346d43e376c572f2e245246 | Shell | 768 | 25 | #!/bin/bash
export SUBJECTS_DIR=/mnt/y/PROJECTS/GMmicrostructure/DATA
basedir="/mnt/y/PROJECTS/GMmicrostructure/DATA"
cd ${basedir}
mapfile -t allsubs < /mnt/y/PROJECTS/GMmicrostructure/DATA/Batch_N.txt
fs_dir="/mnt/z/fs_long"
#fs_dir="/mnt/y/home_study_2017_data/fs_long_S3"
HEMIS=("lh" "rh")
for sub in ${allsubs[@... |
0f37a0d29614069d13ecb5729912c32204989df6003b12b98604243aa1702b2e | Shell | 769 | 21 | #!/bin/bash
# define project directory and working directory
pd=/your/project/directory
input_dir=$pd/data/neural_differentiation_dataset/Spearman_network_inference_and_analysis/input
output_dir=$pd/data/neural_differentiation_dataset/Spearman_network_inference_and_analysis/output
mkdir -p $output_dir
# infer networ... |
49da6c32652f945f8e56f0e78a6f7eb2316735cdab755441a0037da4db272ba5 | Shell | 769 | 18 | #!/bin/bash
experiment=cosmx_dct
python -m cellcontrast --image_preprocess \
--preprocess_dir "data/raw/${experiment}/" \
--channel_names SKIP PanCK CD45 CD3 DAPI \
--cell_cutout 100 \
--foundation_model 'deepcell' \
... |
30d3da251e2482867dfde3db7e24f479c10c7b570da0e250999eb74b3fca21c9 | Shell | 770 | 11 | #!/bin/bash
cd /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/img_gaussiansmooth/
var=0;
for filename in `ls -d *`
do
echo $filename
echo $var
mkdir /lustre/atlas/proj-shared/nro101/BigNeuron/data/taiwan16k/reconstructions_for_img_gaussiansmooth/$filename
sh /lustre/atlas/proj-shared/nro101/BigNeuron/V... |
515e9a95143fe9f9ca1593c9d67c749c4a058a0fc0944e35cd9f45805abc2268 | Shell | 770 | 27 | #!/bin/bash
#SBATCH -c 1 # Request cores
#SBATCH -t 00-120:00 # Runtime in D-HH:MM format
#SBATCH -p medium # Partition to run in
#SBATCH --mem-per-cpu=250G # Memory per core
#SBATCH -o jobs/manc_%j.out # File to which STDOUT will be wri... |
8892225f3dd2e64bebf99ff5f8d0a7acdff54841778ecb9a6dd560b73f5ecc6a | Shell | 770 | 20 | #!/bin/bash
cd /data/mat/zhi/human_cell_penglab_test/raw_testing_images/
j=1;
for i in {1..27}
do
var=1;
echo $i
for foldername in `ls -d *`
do
cd $foldername
mkdir /data/mat/zhi/human_cell_penglab_test/reconstructions/$foldername
for image in $(ls *.v3dpbd *.v3draw)
... |
30c50a04409ed6a41136e48f70793aee1fe5dbc5fa6c48aeccb86d8d127f70a0 | Shell | 773 | 34 | #path of Age-Specific Template
AST=$1
#path of standard template(i.e., MNI152)
target=$2
#output path
OutputPath=$3
#prefix of output
prefix=$4
source=`ls ${ASTPath}/AST*`
mkdir -p ${OutputPath}
antsRegistration \
-d 3 \
--float 1 \
--verbose 1 \
-u 1 \
-w [0.01,0.99] \
-z 1 \
-r [${target},${source},1] \
-t Rigid[0.1... |
8c039a9d6d8540872242c98c61bfe7035d760305fd9306b5d3040318263a692c | Shell | 776 | 24 | OMP_NUM_THREADS=32
# export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
torchrun --nnodes=1 --master_port 49207 --nproc_per_node=8 run_heartlang_pretraining.py\
--output_dir checkpoints/pretrain/MIMIC-IV \
--log_dir log/pretrain/MIMIC-IV \
--model HeartLang \
--tokenizer_model vqhbr \
... |
65b45d9215aa7230bbed90dc77197f0ca3ff50d6864cc11ec9663a7e91359d38 | Shell | 779 | 31 | #!/bin/bash
# Ensure the script stops on first error
set -e
# Source profile
source "$HOME/.bash_profile"
source "$(dirname "${BASH_SOURCE[0]}")/_log.sh"
# Check if the environment variable is a valid conda environment
if [[ $(conda env list | awk '{print $1}' | grep -Fx "$1") == "" ]]; then
log "Error: $1 is no... |
1eedca09ecadd67c7f383927d1854d2115f9aefaaf8df4fa201b5aedc9120f2f | Shell | 780 | 27 | #!/bin/bash
#SBATCH --job-name=cleanData
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=19cm51@queensu.ca
#SBATCH --qos=privileged # or SBATCH --partition=standard
#SBATCH --cpus-per-task=1
#SBATCH --mem=10GB # Job memory request
#SBATCH --time=0-1:00:00 # Day-Hours-Minutes-Seconds
#SBATCH --output=cleanData.out
#S... |
e2427f16cd4605da32ec4ed758f5f45921f4836f313bf58614aa9491f48f9895 | Shell | 780 | 26 | #!/bin/sh
set -o allexport
sta_N_i_pCaLs=1
end_N_i_pCaLs=3
sta_N_i_Kir=1
end_N_i_Kir=3
sta_N_i_batch=1
end_N_i_batch=1
for i_pCaLs in $(eval echo "{$sta_N_i_pCaLs..$end_N_i_pCaLs}")
do
echo "$i_pCaLs"
for i_Kir in $(eval echo "{$sta_N_i_Kir..$end_N_i_Kir}")
do
ec... |
a440713615de61ad6f1c6420547f870399a971c09afa5f2201a93fa3a0ad578b | Shell | 781 | 26 | #!/bin/sh
set -o allexport
sta_N_i_pCaLs=1
end_N_i_pCaLs=3
sta_N_i_KM=1
end_N_i_KM=3
sta_N_i_batch=1
end_N_i_batch=1
for i_pCaLs in $(eval echo "{$sta_N_i_pCaLs..$end_N_i_pCaLs}")
do
echo "$i_pCaLs"
for i_KM in $(eval echo "{$sta_N_i_KM..$end_N_i_KM}")
do
echo " ... |
171ff9ba50a8979e6b088547c690cdd09731fc2552414aed44b60be39d67af97 | Shell | 782 | 13 | #!/usr/bin/env bash
bash ./build.sh
#docker load --input reg_model.tar.gz
#jchen245/transmorph_brain_mri_registration:transmorph_brain_mri_t1_v0
docker run --rm \
--ipc=host \
--memory 256g \
--mount type=bind,source=/scratch/jchen/python_projects/TransMorph_brain_registration/test_dataset.json... |
5f798e09b8b0aa01443e937bf9ae7e0d0d47edbb7ac2fe5e85ddee8339afdb99 | Shell | 783 | 16 | # An optional install script that does all installation steps
echo "Creating medpseg environment..."
eval "$(conda shell.bash hook)"
conda create --name medpseg python=3.9
conda activate medpseg
echo "Installing PyTorch with GPU support..."
# Note this install torch with cuda 11.3. If you need to use a different CUDA ... |
6b866babb77aa98042bed15185b40a960b9a1a128088934eac138eefea171b87 | Shell | 783 | 25 | #!/bin/bash
rm -rf /data/data/prostata.roi/stage2/checkpoints
mkdir -p /data/data/prostata.roi/stage2/checkpoints
# python3 ./prepareTrainData.py
CUDA_VISIBLE_DEVICES=0
for cfg in rotated_retinanet_r50 redet_r50 roi_trans_r50
do
for f in 0 1 2 3 4
do
for lr in 0.08 0.04 0.02 0.008 0.004
do
wd=../da... |
6d243ec094e54d6a11d21bcf346be529597c89275c7f8e0c32d98c88eea7bb8f | Shell | 783 | 29 | conda activate Numbat
pileup_and_phase="pileup_and_phase.R"
gamp="genetic_map_hg38_withX.txt"
snpvcf='genome1K.phase3.SNP_AF5e2.chr1toX.hg38.vcf'
hg38_1000g="1000G_hg38"
ncores=16
myPath=/media/MaleBRCA
OUTdir=$myPath/result/OUT_Numbat
mkdir -p $OUTdir
cd $OUTdir
cat $myPath/Numbat.list | while read id
do
SAMPLEID=$(ec... |
962d64956b7a74ece3a6de6b41b1f375eecf842f6ad3c70739f113cf221dd6d9 | Shell | 783 | 21 | #!/bin/bash
#SBATCH --job-name=down_nmf-%a
#SBATCH --chdir=/vast/palmer/pi/verhaak/kcj28/care_mut/processed_data/nmf_2026/
#SBATCH --output=/vast/palmer/pi/verhaak/kcj28/care_mut/logs/nmf_2026/malignant/downsampled_nmf_malignant_n10_2026-%a.log
#SBATCH --error=/vast/palmer/pi/verhaak/kcj28/care_mut/logs/nmf_2026/malig... |
bf6667fab995d4a7b6fc80d7d3f407fa130b75dee28ca6f67255972c475f16ab | Shell | 783 | 31 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
maindir="$(dirname "$scriptdir")"
declare -A SKIP=(
["101:04"]=1
["101:05"]=1
["101:12"]=1
["103:12"]=1
)
#for sub in 101 103 104 105; do
for sub ... |
af6e526ac28a07cea4a1d5cde548c508eeaffe3f0627470ae5530eda76483fea | Shell | 785 | 15 | #!/bin/bash
# uncomment next line for interactive checking of generated output
PYTHON="ipython2 --pylab -i"
# non-interactive shell. Check results afterwards
PYTHON="python2.7"
# Follow a gradient. Attraction depends on the distance from the attractor.
# The randome xcursions of the neurite become smaller as the neur... |
d46889e0d852ed50e2fda033549fc1f22fd195a81d7344e6db7bce26d213dffe | Shell | 785 | 31 | #!/bin/bash
# Stage 1: Low-resolution ROI detection with 5-fold cross-validation.
# See paper Section "Stage 1: ROI finder (detection)" for details.
python -m train.train \
--train \
--target -1 \
--dataset_name kits23_large_processed \
--dataset_path "data/{}/*" \
--min_hu -53.4 \
--max_hu 283... |
073072db7a6e64bfd475bf9fca2c7ffccfd494b825e2d688b2a0375bfeb2358d | Shell | 786 | 30 | #!/bin/bash
# Ensure paths are correct irrespective from where user runs the script
projectdir=/gpfs/scratch/tug87422/smithlab-shared/night-owls
scriptdir=$projectdir/code
basedir="$(dirname "$scriptdir")"
mapfile -t myArray < "${scriptdir}/sublist.txt"
# grab the first n elements
ntasks=1
counter=0
while [ $co... |
b1ec4da29716f8d80a2d76f930d751a7042e197b9d038bfe07f351d2a413f51c | Shell | 786 | 12 | #!/usr/bin/env bash
docker pull jchen245/transmorph_brain_mri_registration:transmorph_brain_mri_t1_v2
docker run --rm \
--ipc=host \
--memory 256g \
--mount type=bind,source=/scratch/jchen/python_projects/TransMorph_brain_registration/test_dataset.json,target=/input_dataset.json \
--mo... |
00006cf46db1c41670f93528f9cb1623c2965c18958d76bc5fd50c13df4f659b | Shell | 787 | 26 | #! /bin/bash
[ $# -lt 3 ] && { echo 'Usage :
$1 = input folder (With the / after the name)
$2 = seed mask name
$3 = target mask name
$4 = result folder
$5 = other mask name (Will mask both seed and target)
...'; exit 1; }
###############################################################################
# Her... |
bbf87cd814316cb3251d10d51fe1c9f4eca05a415577c29e928574cee5940b7e | Shell | 787 | 37 | #!/bin/bash
SCRIPTS_PATH="$(dirname "$(realpath "$0")")"
INSTALL_PATH=$SCRIPTS_PATH/../../pymeshlab
QT_DIR_OPTION=""
MAC_M1_OPTION=""
#checking for parameters
for i in "$@"
do
case $i in
-i=*|--install_path=*)
INSTALL_PATH="${i#*=}"
shift # past argument=value
;;
-qt=*|--qt_dir=*)
... |
d1c0ab5487f8aa3f1328561c6a522644f43fc0d98d3ccba1b9e8218b429b966a | Shell | 789 | 22 | #!/bin/bash
#SBATCH -c 10 # Request cores
#SBATCH -t 0-96:00 # Runtime in D-HH:MM format
#SBATCH -p medium # Partition to run in
#SBATCH --mem-per-cpu=10G # Memory per core
#SBATCH -o jobs/banc_meshes_%j.out # ... |
9f864a1870be7aa38c495b3e9dc7a4aeec570bf80972084d72899f47b995616c | Shell | 791 | 22 | #!/bin/bash
set -eu -o pipefail
# Data retrieval script for validation comparing alignment methods, preparation approaches
# and variant callers for an NA12878 exome dataset from EdgeBio.
#
# See the bcbio-nextgen documentation for full instructions to
# run this analysis:
# https://bcbio-nextgen.readthedocs.org/en/la... |
d44504fe837be3ee84e02201d42670eaaf1e76dcda2703f9958ad03aefb1e58b | Shell | 792 | 28 | #!/bin/bash
#SBATCH -p gpu
#SBATCH -t 5-00:00:00
#SBATCH -n 1
#SBATCH -c 16
#SBATCH --gpus-per-node=1
#SBATCH -J GenNet_regression
#SBATCH --mem=100G
#SBAYCH --mem-per-gpu=39G
#SBATCH -o /home/ahilten/repositories/GenNet/GenNet_utils/SLURM_logs/out_%j.log
#SBATCH -e /home/ahilten/repositories/GenNet/GenNet_utils/SLURM... |
edc531e70c89e6b3c2b576fae1e91e6784a38874eb18598150b0ad280b4ecbd4 | Shell | 792 | 19 | #############################################################################################
# 超参数设置
# GPU_ID: '0','1','2','3','4','5','6','7'
# DATASET: 'CIFARFS','CUB','FC100','StanfordDog','StanfordCar','MiniImagenet','TieredImagenet'
################################################################################... |
df90c6f946b6305e00d27cdb587cc924b06ce7cfe8e7f24fe5d1a639330014e7 | Shell | 794 | 32 | #!/bin/bash
# Stage 2: High-resolution segmentation with 5-fold cross-validation.
# See paper Section "Stage 2: Full segmentation" for details.
python -m train.train \
--train \
--stage2 \
--target -1 \
--dataset_name kits23_processed_highres \
--dataset_path "data/{}/*" \
--min_hu -300 \
-... |
22ff21eece972abcad976a6d10ff85381409fd5bea9c42006b1ee2a6dc48b88c | Shell | 795 | 29 | #!/bin/bash
#SBATCH --job-name=SPLiT_Seq_Demultiplexing
#SBATCH --time=72:00:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=10
#SBATCH --mem=50G
python splitseqdemultiplex_onlyAlign.py \
-t 10 \
-e 2 \
-m 10 \
-1 Round1_barcodes_new5.txt \
-2 Round2_barcodes_new4.txt \
-3 Round3_barcodes_new4.txt \
-f /mnt/isil... |
f946e7b0c326014316fd00b0d17881344bed1c9add67d883a284daa1529e591b | Shell | 796 | 25 | #!/bin/bash
#SBATCH -c 4
#SBATCH -t 0-03:00
#SBATCH -p short
#SBATCH --mem=24G
#SBATCH -o jobs/banc_export_skeletons_%j.out
#SBATCH -e jobs/banc_export_skeletons_%j.err
# Exports per-neuron SWCs for compiled_data/banc_<ver>/.
# Detailed skeleton (banc/swc/<id>.swc) preferred; falls back to L2
# (banc/l2/<id>.swc); SWC... |
dd344c2d16798ac5bab2a45112aee927bbaac7f451e1d0d9a20d9f5e3c9d710a | Shell | 798 | 24 | # this function will generate the chord diagrams for the TRBPC project
# Written by Nanbo Sun, Angela Tam & CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
# path to input and outputs
datadir=$1
code_dir=$CBIG_CODE_DIR/stable_projects/predict_phenotypes/ChenTam2022_TRBPC/figure_ut... |
5eef8981a1017638e942d96c767da4009c909a969120e9f33042d37e24933526 | Shell | 799 | 16 | #!/bin/sh
juliapath=`which julia`
compiled_code="./SimplicialTS/Simplicial.so"
input_file="./SimplicialTS/data/TS_Schaefer60S_gsr_bp_z.mat"
output_file_scaffold="HO_scaffold_frequency"
scaffold_flag=2 # Flag 1-> frequency, Flag 2 -> persistence
output_file_triangles="HO_triangles"
###Launching the code for the compu... |
b54bc6438c0440b086a73c75ccb150223cb3006c0b0b6dc96e866cba007d7b7b | Shell | 799 | 38 | #!/bin/bash
########################################
#OMEGA
########################################
export path_htsa_dir=$1
export path_pipeline=$2
export omega_work_dir=$3
export diginorm_work_dir=$4
cd $project_work_dir
echo "starting omega assembly..."
if [ -d $omega_work_dir ];
then
rm -r $omega_work_dir
fi
... |
3e63ee7fb0dea95008e40db7fa8b6cabe81296ebd70249b4f7b5829708696bd9 | Shell | 800 | 36 | #!/bin/bash
codedir="/home/antonio/Codes/bronchinet/"
basedata="./EXACT_Testset_Testing/"
ln -s $basedata "./BaseData"
# 1: DISTRIBUTE DATA
modeldir="./Models_TestEXACT/"
python3 "${codedir}/src/scripts_experiments/distribute_data.py" \
--basedir=. \
--type_data="testing" \
--type_distribute="original" \
--pr... |
f3b08082fd8faa1a44e054571a4bd71252c1bb1efb2604a784cfc2cc65974e1e | Shell | 800 | 23 | #subject ID
sub=$1
#individual brain parcellation, output of DT4_Standard_to_Indi.sh
mask=$2
#path of partial volume estimates(PVE) of individual brain gray matter, output of DT2_Individual_Segmentation.sh
gm=$3
#path of output directory
outputdir=$4
maskdir=${outputdir}/mask
mkdir -p ${maskdir}
resultdir=${outputdir}... |
e57eb9ae084d691c9c9cecd9dff84ffb46fceb96b274320a7b25377252e6c2b6 | Shell | 803 | 38 | #!/bin/bash
#$ -cwd
#$ -S /bin/bash
ID=$1
ConfigFile=$2
source ${ConfigFile}
#####
IndexPath=${IndexPath_50}
DataPath=${FastpPath}
FASTQ0=${FASTP0} # this script is for FASTQ filtered by FASTP
OutPath=${AlignPath}
AllOutPath=${AlignAllPath}
Read_len=50
#####
make_dir ${OutPath}
make_dir ${AllOutPath}
#####
STAR \
... |
365ef7a1b5a10203b5e76fadf44e414f07b2fa9cfb03853f8d46c01168e8d404 | Shell | 804 | 51 | #!/bin/sh
# to be executed by retrieve_audit
auditprogpath=`dirname $0`
pid=ret
id=$1
auditdir=$2
tmpdir=$auditdir/$pid
tardir=$auditdir/TAR
if [ -d $tmpdir ] ; then
exit 1;
fi
mkdir $tmpdir
zcat $tardir/$id.tar.Z | ( cd $tmpdir ; tar xf - )
cd $tmpdir
n=0
echo $tmpdir
read cmdfile str < savefile
cp $cmdfile $cmd... |
7159e2599f5c8ffaeb81f75661d17c67a13c498fc1312c2fd4a802749ce96c20 | Shell | 804 | 24 | #!/bin/bash
# This script creates a file indicating the source with the best coverage per gene and species (either genome of transcriptome BAM).
# Paths
folder_gn="Data/05.Coverage/out/cov_genomes/"
folder_tr="Data/05.Coverage/out/cov_transcriptomes/"
# Arrays
genes=( $( cat "Data/arrays/transcripts.txt" ) )
spp_file... |
c1155dd5e07bc8f05b7ebc00cc10833c3d4ac02a266481940ef27bebe8239406 | Shell | 804 | 41 | #!/bin/sh
# set up module environment
. /etc/profile.d/modules.sh
module load anaconda
source activate pyscenic
cd ./scenic/library$1/
rm -r dask-worker-space
## expression matrix
f_ex_matrix_csv=data.loom
## referrence databases
f_db_names=../hg38_10kbp_up_10kbp_down_full_tx_v10_clust.genes_vs_motifs.rankings.fe... |
ffdfa89d39d8f02266361f81c4f0de8a7fa8b0029e859bdfdb3bb1f2e3761d39 | Shell | 804 | 32 | #!/bin/bash
#SBATCH --job-name=st
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=16amz1@queensu.ca
#SBATCH --qos=privileged # or SBATCH --partition=standard
#SBATCH --cpus-per-task=1
#SBATCH --mem=5GB # Job memory request
#SBATCH --time=0-1:00:00 # Day-Hours-Minutes-Seconds
#SBATCH --output=st
#SBTACH --error=st
#... |
764e82ca95eed86bb12e5d363bfbec72896dbc3cd766717efede6b50c059be14 | Shell | 805 | 28 | #!/bin/bash
echo "Running fusion ai training..."
source ./.venv/bin/activate
DATASET_DIR="../test_data"
OUTPUT_FOLDER="models_output"
EPOCHS=2
python train_fusionai.py \
--epochs $EPOCHS\
--train-path "$DATASET_DIR/fusionai_test_sim.txt" \
--train-target "$DATASET_DIR/fusionai_test_target.csv" \
--tes... |
9cb58ce787043f0a915bdf58eb6b830443c98ab654dd33cb3fc1b2e1570e30c8 | Shell | 807 | 37 | echo "Dir = $1"
echo "Var = $2"
# Regrid to 5.625 degrees
python ../src/regrid.py \
--input_fns "$1"/raw/"$2"/*.grib \
--output_dir "$1"/5.625deg/"$2" \
--ddeg_out 5.625 \
--is_grib 1
## Convert to netcdf
#for file in "$1"/raw/"$2"/*.grib; do
# cdo -f nc copy "$file" "${file%.grib}.nc"
#done
#
#mkdir "$1"/netcdf
#... |
8cdb4b5e7dd7f09de806c1239d4cb2f59977ae66198e38ab896d0b752ff3f136 | Shell | 808 | 29 | #!/usr/bin/env bash
# Install Python dependencies for banc-spectral-clustering.py
# Checks for each package first and only installs what's missing.
set -e
PACKAGES=(numpy pandas scipy scikit-learn umap-learn plotly pyarrow)
missing=()
for pkg in "${PACKAGES[@]}"; do
# Map pip package names to Python import names... |
0d44c435d9daae1680ef9442d458478dd12c46074fbcdf6dc0cad68dcc9de63f | Shell | 809 | 38 | #!/bin/bash
# The density.cub is saved in the same folder as molden.input
# Define the base directory
base_dir="molden"
# Change to the base directory
cd "$base_dir"
# Loop through all molecule_ directories in the base directory
for dir in */
do
# Change to the current molecule directory
cd "$dir"
for ... |
f2a16d51b213633cf5a6f1e6ca0f585b58276b7c4b7ca89567c85e503aea87ad | Shell | 810 | 22 | #!/bin/bash
# this function runs replication of all results in our paper
#
# Written by Jianzhong Chen and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
outdir=$1
root_dir=`dirname "$(readlink -f "$0")"`
# replicate regression models of main analysis
$root_dir/CBIG_TRBPC_regressi... |
a9a33f4fe87ab7a81c013588d3f7656fe1db1ef052707d700fd31e7d828f7e6e | Shell | 815 | 29 | #!/bin/bash
set -e
# checks for correct installation
if [ ! $(docker -v | grep -c -w version) -eq 1 ]; then
echo "docker not found."
exit 1
fi
if [ ! $(groups | grep -c -w docker) -eq 1 ]; then
echo "add current user $(whoami) to docker group!"
exit 1
fi
top_level=$(git rev-parse --show-toplevel)
list_of_files=... |
3edb90904730bcf4bdc914bd535bd1c873b7781cdde62fed50eb9f0a1f708c76 | Shell | 816 | 15 | #!/bin/bash
# uncomment next line for interactive checking of generated output
PYTHON="ipython2 --pylab -i"
# non-interactive shell. Check results afterwards
PYTHON="python2.7"
# Straight to pia: one front runs straight to the pia.
# The pia is a point-cloud, see cfg file and online documentation
mypython=/home/wpken... |
76bb501c345b2eaf04b8c6f8ae8dc9f0d308ec284ca9d2490d8fcda55194ad99 | Shell | 817 | 20 | #!/bin/bash
#SBATCH -c 2
#SBATCH -t 0-01:00
#SBATCH -p short
#SBATCH --mem=8G
#SBATCH -o /home/ab714/bancpipeline/jobs/banc_publish_segprop_%j.out
#SBATCH -e /home/ab714/bancpipeline/jobs/banc_publish_segprop_%j.err
###############################################################################
# Standalone publisher f... |
2ef4f79ff9b0ae60b4a8c3eaa3799de976bee18f595dc2113d22e93d9264c3fd | Shell | 819 | 31 | #!/bin/bash
# ensure paths are correct irrespective from where user runs the script
scriptdir="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
maindir="$(dirname "$scriptdir")"
declare -A SKIP=(
["101:04"]=1
["101:05"]=1
["101:12"]=1
["103:12"]=1
)
#for sub in 101 103 104 105; do
for sub ... |
ce8ef5cd422946b6a6c9edf38cce21ea9808a55dc256ec2c356dde49a34eea91 | Shell | 820 | 38 | #!/bin/bash
CONDA_EV=~/miniconda3
SCRIPT_DIR="$(
cd -- "$(dirname -- "${BASH_SOURCE[0]}")" >/dev/null 2>&1 && pwd
)"
WORK_ROT="$(
cd -- "$SCRIPT_DIR/.." >/dev/null 2>&1 && pwd
)"
cd ${WORK_ROT} || exit
RUN_NAME=optimizing
SRCP_DIR=src
RUN_MODE=optimize_conf
BASE_DIR=${WORK_ROT}/data/references
RESL_DIR=${WORK... |
0f4c79d183a00d057f28906ead9456d5a2edc26de20102d2213ac5e02da35ddf | Shell | 821 | 30 | #!/bin/bash
set -e
nextIssue=$(curl -X GET -sL -H "Accept: application/vnd.github.v3+json" \
https://api.github.com/repos/AllenInstitute/MIES/issues?state=all \
| jq '[.[] | .number] | max + 1')
nextPR=$(curl -X GET -sL -H "Accept: application/vnd.github.v3+json" \
https://api.github.com/repos/AllenInstitute/M... |
64cb64e3920fba3e829ed8694233058c007892bf4295a38eb3f7a2df99a4b164 | Shell | 821 | 35 | #!/bin/bash
########################################
#MEGAHIT
########################################
export path_htsa_dir=$1
export path_pipeline=$2
export megahit_work_dir=$3
export PAIR1=$4
export PAIR2=$5
cd $project_work_dir
echo "starting megahit assembly..."
if [ -d $megahit_work_dir ];
then
rm -r $megahi... |
d6ce29b50090823efedf243925a516c6e2abececfe4c5567ded60369756ccf86 | Shell | 822 | 33 | #!/bin/bash
#SBATCH --job-name=st
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=16amz1@queensu.ca
#SBATCH --qos=privileged # or SBATCH --partition=standard
#SBATCH --cpus-per-task=1
#SBATCH --mem=5GB # Job memory request
#SBATCH --time=0-1:00:00 # Day-Hours-Minutes-Seconds
#SBATCH --output=st
#SBTACH --error=st
#... |
4c6d42c7c6627d0a4824b1c6f735afeeb26ef16a74a61b7f0f4b8b8f6252a222 | Shell | 825 | 35 | #!/bin/bash
# Author: Andrew Hamel
# Affiliation: Massachusetts Eye and Ear, Harvard Medical School
# Date: June 2022
#
# This is a shell script
# with a sample run of GeneEnrich
#
# List of significant genes of interest
significant_file=""
# Background list of genes expressed in given tissue
null_file=""
# File wi... |
c6378dc54c9a81a96fdf9f9f1797c512bdfb55c67969417a9bdfc8dd9b7b2a46 | Shell | 825 | 23 | #!/bin/bash
#
# Prepare a run directory for evaluations against
# Genome in a Bottle truth sets.
#
# https://bcbio-nextgen.readthedocs.org/en/latest/contents/testing.html#example-pipelines
#
set -eu -o pipefail
mkdir -p config
cd config
wget -c https://raw.githubusercontent.com/bcbio/bcbio-nextgen/master/config/exam... |
7edd0f6d0c663476fd87ffa80ec9e8f7cd79153151e90345952af0aeb0ebed06 | Shell | 826 | 33 | #!/bin/bash
#if nrniv does not work then see if we can fix the problem
if nrniv -c 'quit()' >& /dev/null ; then
true
else
orig_pythonhome="$PYTHONHOME"
orig_pythonpath="$PYTHONPATH"
orig_ldlibpath="$LD_LIBRARY_PATH"
orig_path="$PATH"
eval "`nrnpyenv.sh`"
if nrniv -c 'quit()' >& /dev/null ; then
true
... |
38b8e220782125eb6742586f733567fafc569c9d2f92e3f1bde10105028561b5 | Shell | 827 | 21 | #!/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
# Anaconda
wget -q https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod +x Miniconda3-latest... |
6f496aec55dde837be229066b8b1e1f3f94eafe1c1d4a2964cf18fffb2d93def | Shell | 830 | 13 | #!/usr/bin/env bash
bash ./build_GPU.sh
#jchen245/transmorph_brain_mri_registration:transmorph_brain_mri_t1_v0
#-it --entrypoint "/bin/bash"
docker run --rm \
--ipc=host \
--memory 256g \
--gpus "device=0"\
--mount type=bind,source=/scratch/jchen/python_projects/TransMorph_brain_registra... |
7f57d6c3e16c31cd8d488bc474f50a90d17e381b7f9a3f1d1c30ccbec25cb9bb | Shell | 831 | 33 | #!/bin/bash
#SBATCH -t 01:00:00
#SBATCH --mem=8GB
#SBATCH -n 1
#SBATCH -p evlab
#SBATCH --array=0-60
#SBATCH -o Slurm/slurm-%A_%a.out
source /etc/profile.d/modules.sh
module load mit/matlab
# Read subjects using mapfile to preserve lines
mapfile -t subjects < <(
awk -F, 'NR > 1 {
for (i=2; i<=7; i++) {
gs... |
f1adf3d5ec3023aa29d761148af3fd53496f167d0e1cd83cb74b38020bb0684c | Shell | 832 | 16 | resloc='/hihg/studies/AD/analysis/projects/ADGC/Neuropath/GWAS_Results'
# M1 results
for i in ADNC AMY_A AMY_CERAD AMY_THAL B_SCORE BRAA CVD_ART CVD_ATH CVD_CAA LEWY_full LEWY_grp REAG TDP_3 WMR ;
do awk '{if ($8<=1e-6) print $0 }' ${resloc}/Ordinal/${i}/METAL/${i}.M1.final.tbl -i
done >> ${resloc}/all.M1.final.tbl
fo... |
94b74da688660ff9582d5c9f6c09f6d200bc57a0fb90903d634d25cc5815a3b5 | Shell | 833 | 18 | #!/bin/bash
set -euo pipefail
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd $SCRIPT_DIR/..
NEW_VERSION="${1}"
echo "Bumping version: ${NEW_VERSION}"
perl -pi -e "s/\bminijinja v.*? /minijinja v$NEW_VERSION /" README.md
perl -pi -e "s/^version = \".*?\"/version = \"$NEW_VERSION\"/" minijinja-py/py... |
31236206b8fa1cf735764653aa6fc06b2ce27ddaabcd6d94ef4dab595f7f851c | Shell | 834 | 36 | #!/bin/bash
set -e # exit if a command fails
# assumes first argument is a folder with multiple T1's
in_fld=$1
startpath=pwd;
subj=${PWD##*/} # get monkey name from the folder we're in
cd ${in_fld} # go to the specified folder
mkdir -p output
# define a preprocessing routing
preprocess_indiv () {
mri_convert -i $... |
a19a0433997781bc96b2af6c466956f1c3c3e568a48b37c97145878d030cc34a | Shell | 837 | 34 | #!/usr/bin/env bash
set -euo pipefail
build_dir="${1:-build-benchmark}"
results_dir="${2:-benchmark-results}"
min_time="${PQ_BENCHMARK_MIN_TIME:-3s}"
benchmark_dir="${build_dir}/benchmarks/src"
benchmarks=(
benchmark_linearAlgebra
benchmark_box
benchmark_pairPotentials
benchmark_cellList
benchmar... |
6ff04c5e59738ab67e20c4d22cc7548a0e61825cf70989ab6d1c252c035db2dc | Shell | 838 | 24 | #!/bin/bash -x
#SBATCH --account=inm7
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=1
#SBATCH --time=1:00:00
#SBATCH --partition=dc-cpu
#SBATCH --output=logs/outputs/%x_%j.out
#SBATCH --error=logs/errors/%x_%j.err
source /p/project/cinm-7/bi1/miniconda3/etc/profile.d/conda.sh
conda deactivate
... |
409fe7b2cd172a443036337eda84b2513b2b9a0c9401b4f327612dce1c6855cc | Shell | 840 | 34 | #!/bin/bash
#SBATCH --job-name=gc
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=16amz1@queensu.ca
#SBATCH --qos=privileged # or SBATCH --partition=standard
#SBATCH --cpus-per-task=1
#SBATCH --mem=5GB # Job memory request
#SBATCH --time=0-5:00:00 # Day-Hours-Minutes-Seconds
#SBATCH --output=gc
#SBTACH --error=gc
#... |
a0cb8289d8a69fd6675bd2b48c8795ab845a8cdc53094affa57d50a04d9dcfec | Shell | 840 | 42 | #!/bin/bash
#SBATCH --nodes=1
#SBATCH --partition=cuttlefish
#SBATCH --time=100:00:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=32
#SBATCH --job-name=soBAMSRT
#SBATCH --error=error_%j.txt
#SBATCH --output=output_%j.txt
echo $SLURM_SUBMIT_DIR
echo "Running on `hostname`"
reportElapsedTime() {
eval "echo elapsed ... |
693b93e167b1d95d5245dcaafecf21da50bde9cef72285dd6221d5e7345c5379 | Shell | 841 | 18 | #!/bin/sh
juliapath=`which julia`
compiled_code="./SimplicialTS/Simplicial.so"
nthreads=6
input_file="./SimplicialTS/data/TS_Schaefer60S_gsr_bp_z.mat"
maxT=10
output_file_scaffold="HO_scaffold_frequency"
scaffold_flag=2 # Flag 1-> frequency, Flag 2 -> persistence
output_file_triangles="HO_triangles"
###Launching the... |
1386ffcf52f206611ad378e8f7f2cf4a72228d31199220585eaca9dfd6bb9854 | Shell | 842 | 12 | #!/usr/bin/env bash
docker pull jchen245/transmorph_brain_mri_registration:transmorph_brain_mri_t1_v2_gpu
docker run --rm \
--ipc=host \
--memory 256g \
--gpus "device=0"\
--mount type=bind,source=/scratch/jchen/python_projects/TransMorph_brain_registration/test_dataset_monkey.json,targ... |
9ed9383abc058ac7fd6282b523a7e8a3eefc1dc08b4e88cd91b1e84cd3b52dfe | Shell | 844 | 13 | working_dir=$(cd "$(dirname "$0")" && pwd -P)
echo "Compiling formatting scripts"
g++ "$working_dir"/Promoter_Windows.cpp "$working_dir"/STARE_MiscFunctions.cpp -std=c++11 -O3 -o "$working_dir"/Promoter_Windows
g++ "$working_dir"/ReplaceInvalidChars.cpp -std=c++11 -O3 -o "$working_dir"/ReplaceInvalidChars
g++ "$workin... |
6a3f194a5fe54e16ad6be13ce10a11de72a9ccd1b2866612924d9cb037a876f8 | Shell | 845 | 48 | #!/bin/sh
# used by the libload command in hoc to find an instance of a procedure,
# function, or template
# uncomment following line for use with DOS
#NEURONHOME=`d2uenv NEURONHOME`
if [ $TEMP ] ; then
tmpdir=$TEMP
else
tmpdir="/tmp"
fi
curdir=`pwd`
names=$tmpdir/oc"$3".hl
if [ ! -f $names ] ; then
paths=". $HO... |
6c894140af22bd376f3c9925042ccd5c21cfd44d4a9350a7a250d28615044496 | Shell | 846 | 31 | #!/bin/bash
#SBATCH --job-name=fq
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=16amz1@queensu.ca
#SBATCH --qos=privileged # or SBATCH --partition=standard
#SBATCH --cpus-per-task=1
#SBATCH --mem=10GB # Job memory request
#SBATCH --time=0-12:00:00 # Day-Hours-Minutes-Seconds
#SBATCH --output=fq
#SBTACH --error=fq
... |
95cae977145d0e5d2698e91917c4178303ca691cf42225451bef3a939034215c | Shell | 846 | 24 | #!/bin/bash
# Define the feature combinations and targets
feature_combs=("Sleep_APOE" "Sleep_APOE_Shuffle"
"Sleep_Cov_APOE" "Sleep_Cov_APOE_Shuffle"
"Cov_APOE" "Cov_APOE_Shuffle"
"Brain_APOE" "Brain_APOE_Shuffle"
"Subcor_APOE" "Subcor_APOE_Shuffle"
... |
c39375f2fc889703f540d393665670eae1b44042e5efe8b4abe699a5bc2475cd | Shell | 846 | 16 | #!/bin/bash
cd /lustre/atlas2/nro101/proj-shared/BigNeuron/data/taiwan16k/img_gaussiansmooth/
var=0;
for filename in `ls -d *`
do
echo $filename
echo $var
i=24;
# mkdir /lustre/atlas/proj-shared/nro101/BigNeuron/taiwan_16k_valid_batch_run/gaussiansmooth/results/$filename
for i in {25..27}
do
sh /lustre/atlas2/n... |
7e8edb4cd8b9e80e7a435e46665e580df3dae965d132baf5f698d449dd3c7d37 | Shell | 847 | 28 | #!/bin/bash
# This script is used to generate gene trees from the alignments produced in script 08, using both nucleotide and amino acid sequences.
# iqtree version 2.0.3
# Paths
path_aln="Data/08.Alignments/out/"
path_trees="Data/10.Gene_Trees/out/"
# Array genes
genes=( $(cat "Data/arrays/transcripts.txt") )
cd "${... |
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