sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
b294f173fa81de0ac555621cc56d192ffba28dd87ffa4bda685c5e4f97ee3ae9 | Shell | 1,738 | 66 | #!/bin/bash
# Create the destination directory if it doesn't exist
mkdir -p $dest_dir
# Define the subject ID and threads
sub="$1"
threads="$2"
echo "Processing subject: $sub with FastSurfer..."
# Check if the segmentation already exists
if [ ! -e "${dest_dir}/${sub}/stats/aseg+DKT.stats" ]; then
# Locate the... |
37e330146ab19926dc8f8d731e1f2ab70917ccdd12ad4e1928e01a98b14aa378 | Shell | 1,740 | 31 | #!/usr/bin/env bash
# Write config files
set -ev
export CATMAID_PATH=$(pwd)
cd django
cp configuration.py.example configuration.py
sed -i -e "s?^\(abs_catmaid_path = \).*?\1'$(echo $CATMAID_PATH)'?g" configuration.py
sed -i -e "s?^\(abs_virtualenv_python_library_path = \).*?\1'$(echo $VIRTUAL_ENV)'?g" configuration.py... |
7e545a0f25db9add4111767ee57c1688004acfd3d7efcb8502abdc18ed29b835 | Shell | 1,760 | 71 | #!/bin/bash
# Copyright 2013-2023, Derrick Wood <dwood@cs.jhu.edu>
#
# This file is part of the Kraken 2 taxonomic sequence classification system.
# Download NCBI taxonomy information for Kraken 2.
# Designed to be called by kraken2-build
set -u # Protect against uninitialized vars.
set -e # Stop on error
TAXONOM... |
f8ac33b4f35bd906d3d2a369fb27061d0869f592fa3749fdd72352b2235626e8 | Shell | 1,764 | 37 | #!/bin/bash
# location of bert or biobert model
# Note that if you use biobert as your base model, you'll need to change init_checkpoint to be biobert_model.ckpt
BERT_BASE_DIR=/PATH/TO/BERT/MODEL
# folder where you want to save your clinical BERT model
OUTPUT_DIR=/PATH/TO/CLINICAL/BERT/OUTPUT/DIR
# folder that conta... |
edb40f91ff3f6e2faba3663be0d6111afbe98c73f9e087a2cf04852dad656d6f | Shell | 1,771 | 46 | #!/bin/bash
set -xe
if [[ ! -e ./ERR3240275/ERR3240275_1.fastq.gz ]]; then
mkdir -p ERR3240275
cd ERR3240275
echo "null" > null.txt
ls | grep -v -E 'ERR3240275_1.fastq.gz' | grep -v -E 'ERR3240275_2.fastq.gz' | xargs rm -r
cd ..
fi
if [[ ! -e ./SRR8315715/SRR8315715_1.fastq.gz ]]; then
mkdir -p SRR8315715
cd S... |
5390f1fcde140d1626a66aa72b42b578e8f6ff60ca946d609ab11c6614c8e6c8 | Shell | 1,794 | 78 | #!/bin/bash
#SBATCH --array=1-9
#SBATCH -p 3090-gcondo
#SBATCH --gres=gpu:1
#SBATCH --gres-flags=enforce-binding
#SBATCH --exclude=gpu2262,gpu2112
#SBATCH -N 1
#SBATCH --mem=64G
#SBATCH --time=48:00:00
#SBATCH --output=grid_tradeoff_mask.%j.%A.%a.out
# Load modules
module load anaconda/2023.09-0-7nso27y
module load cu... |
92010ed28a3fb50959bcd16dc3b746c5f3e1d960f568b5a63d95a32969903272 | Shell | 1,795 | 84 | while getopts "g:o:s:l:" opt
do
case "$opt" in
g ) parameterG="$OPTARG" ;;
o ) parameterO="$OPTARG" ;;
s ) parameterS="$OPTARG" ;;
l ) parameterL="$OPTARG" ;;
? ) helpFunction ;; # Print helpFunction in case parameter is non-existent
esac
done
# This script needs to run with R
#... |
8b4c2a47f282ab144f8f6f12499d46cfcf62faa7e8f46487ec4c56c607824c92 | Shell | 1,796 | 35 | #! /bin/bash
model=ScaleDense
batch_size=32
test_dirpath=./data/test/
excel_dirpath=./data/dataset.xls
sorter_path=./TASN/Sodeep_pretrain_weight/best_lstmla_slen_${batch_size}.pth.tar
model_dirpath=./pretrained_model/second_stage_test/
first_stage_net=./pretrained_model/ScaleDense/ScaleDense_best_model.pth.tar
# -----... |
eea56aae0795f291b0724d8e2f68892bfa20b936080c6850a0c0f9fa4a5f30fa | Shell | 1,799 | 78 | #!/bin/bash
#SBATCH --array=1-9
#SBATCH -p 3090-gcondo
#SBATCH --gres=gpu:1
#SBATCH --gres-flags=enforce-binding
#SBATCH --exclude=gpu2262,gpu2112
#SBATCH -N 1
#SBATCH --mem=64G
#SBATCH --time=48:00:00
#SBATCH --output=grid_tradeoff_noise.%j.%A.%a.out
# Load modules
module load anaconda/2023.09-0-7nso27y
module load c... |
d3e3e06060c1203e3e9a8b9d3acc3478e4345ddbf58f4a83cdb78e37dce34820 | Shell | 1,802 | 78 | while getopts "g:o:s:" opt
do
case "$opt" in
g ) parameterG="$OPTARG" ;;
o ) parameterO="$OPTARG" ;;
s ) parameterS="$OPTARG" ;;
? ) helpFunction ;; # Print helpFunction in case parameter is non-existent
esac
done
# This script needs to run with R
# Settings --------------------------... |
7b1d9f869913a5648600614193b8785a0675676c063142955ed3bcfc6e058f4d | Shell | 1,807 | 30 | #!/bin/bash
set -eu
# Define the rename function (assuming it's located at ../../../code/rename_file)
RENAME_FUNC="/Users/h/Documents/projects_local/1076_spacetop/code/rename_file"
# Define the base file name pattern
SUBPATH="/Users/h/Documents/projects_local/1076_spacetop/sub-0075/ses-01/func"
PATTERN="sub-0075_ses-... |
e83b17c089e49e81448262ac4e6815c96d7d908cd706b3a569c554f0a5dd1817 | Shell | 1,810 | 60 | #!/bin/bash
#PBS -l select=1:ncpus=4:mem=8gb
#PBS -l walltime=8:00:00
#PBS -N primary_jobs
#PBS -J 0-79
# Primary scripts do not depend on other scripts.
# Each base job is run with 10 different seeds (0-9).
# Load environment
module load anaconda3/personal
source activate graphtrip
cd ~/projects/graphTRIP/scripts
... |
4d752b81268949517af1e43aa137d090b52f81f16e70e514e191128292effada | Shell | 1,817 | 60 | #!/bin/bash
mkdir -p data
cd data
# ------------------ Download CSV files ------------------
echo "Downloading parsed_questions_mass.csv..."
wget -q "https://osf.io/download/vyr5n" -O parsed_questions_mass.csv
echo "Downloading parsed_questions_stiff.csv..."
wget -q "https://osf.io/download/27skd" -O parsed_questio... |
9529fb27772c3ef13ffe29cf43e936427b5e8f2bb3fdc8f497fb30bc44e177f6 | Shell | 1,823 | 44 | #!/bin/bash
#SBATCH --job-name=trainAdd400resnet
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --nodes=1
#SBATCH --gres=gpu:1
#SBATCH --time=840
#SBATCH --mem=200G
#SBATCH --partition=gpu
#SBATCH --error=/private/groups/brookslab/gabai/projects/yeastMeth/log/lsf_%j_%x.err # error file
#SBATCH --output=/priv... |
8edb044bd1b4b92d47ee8c8491de1c5a0d5caf8bbd5dfaedc015152b6c504273 | Shell | 1,829 | 58 | #!/bin/sh -e
fail() {
echo "Error: $1"
exit 1
}
notExists() {
[ ! -f "$1" ]
}
# check number of input variables
[ "$#" -ne 4 ] && echo "Please provide <queryDB> <targetDB> <outDB> <tmp>" && exit 1;
# check if files exist
[ ! -f "$1.dbtype" ] && echo "$1.dbtype not found!" && exit 1;
[ ! -f "$2.dbtype" ] && e... |
4fe9fc537ec0579184f13b2494c43752b27e0a1cb275a7ce7a4b19609886e83f | Shell | 1,834 | 79 | #!/bin/bash
#SBATCH --array=1-9
#SBATCH -p 3090-gcondo
#SBATCH --gres=gpu:1
#SBATCH --gres-flags=enforce-binding
#SBATCH --exclude=gpu2262,gpu2112
#SBATCH -N 1
#SBATCH --mem=20G
#SBATCH --time=24:00:00
#SBATCH --output=cat_tradeoff_noise.%j.%A.%a.out
# Load modules
module load anaconda/2023.09-0-7nso27y
module load cu... |
6d200627c435923e10af83e70b38675106ee71de58febd01d5c9bf1aa813f062 | Shell | 1,837 | 63 | #!/bin/sh -e
fail() {
echo "Error: $1"
exit 1
}
notExists() {
[ ! -f "$1" ]
}
# check number of input variables
[ "$#" -ne 2 ] && echo "Please provide <sequenceDB> <tmp>" && exit 1;
# check if files exist
[ ! -f "$1.dbtype" ] && echo "$1.dbtype not found!" && exit 1;
[ ! -d "$2" ] && echo "tmp directory $2 n... |
aed516802885428053184b87048f4816d0ba5945b03d37ba9b7b5b728a56fc10 | Shell | 1,840 | 49 | #! /bin/bash
cwd=/mnt/h/Experiments/Experiment2-Blink_Tic/SPFM/Tedana/MaskOutputs/Reclassified
sdir=/mnt/h/Experiments/Experiment2-Blink_Tic/SPFM/02_Statistics/GrayPlots
for SBJ in Sub01 Sub03 Sub04 Sub05 Sub06 Sub07 Sub09 Sub10 Sub11 Sub12 Sub13 Sub14 Sub15 Sub16 Sub17 Sub18 Sub19 Sub20 Sub21 Sub22;
do
for r... |
0bce3c6a834b363a94c9c98aeb55170aa4918d998ef7297c11b24ea9809504b9 | Shell | 1,851 | 79 | #!/bin/bash
#SBATCH --array=1-11
#SBATCH -p 3090-gcondo
#SBATCH --gres=gpu:1
#SBATCH --gres-flags=enforce-binding
#SBATCH --exclude=gpu2262,gpu2112
#SBATCH -N 1
#SBATCH --mem=20G
#SBATCH --time=24:00:00
#SBATCH --output=cat_tradeoff_mask.%j.%A.%a.out
# Load modules
module load anaconda/2023.09-0-7nso27y
module load cu... |
60ae26a5d0bce589c5ab5752c69ae55c414750cd66be556131ce6dd28dd94859 | Shell | 1,864 | 51 | #!/bin/bash
# Usage parse_log.sh caffe.log
# It creates the following two text files, each containing a table:
# caffe.log.test (columns: '#Iters Seconds TestAccuracy TestLoss')
# caffe.log.train (columns: '#Iters Seconds TrainingLoss LearningRate')
# get the dirname of the script
DIR="$( cd "$(dirname "$0")"... |
dda703598aaee9593e384261d239dd78f237be748a4019a49a4781ed4c30abbb | Shell | 1,864 | 63 | #!/bin/bash
# Build Python wheels, CPU variant (no federated learning)
set -euo pipefail
if [[ -z "${GITHUB_SHA:-}" ]]
then
echo "Make sure to set environment variable GITHUB_SHA"
exit 1
fi
if [[ "$#" -lt 2 ]]
then
echo "Usage: $0 {manylinux2014,manylinux_2_28} {x86_64,aarch64}"
exit 1
fi
manylinux_target="... |
26b991c9389868275f844749f1bf9966757fe67f71a864fc8c8a245c5249f760 | Shell | 1,887 | 44 | # Make sure an aggregator is up somewhere, and it is configured to
# accept admin@example.com as an admin and to allow any endpoints you are willing to test
# Uncommend and test
DIR=$(dirname "$(realpath "$0")")
# GET EXPERIMENT STATUS
env_arg1="MEDPERF_ADMIN_PARTICIPANT_CN=col1@example.com"
mount_arg1="output_statu... |
4ae6189174cfbb48725b729c56507036c623e5b9b000b31cee69d2f1d618549c | Shell | 1,888 | 46 | git clone https://github.com/mayukhmondal/ABC-DLS.git
imp=0
touch Narrowed.csv All.csv
cp Startrange.csv Oldrange.csv
while [ "$(echo "$imp < 0.90"| bc -l)" -eq 1 ]
do
snakemake -q -s ABC-DLS/src/SFS/Snakefile --configfile ~/PycharmProjects/png_xOOA/ABC-DLS/ParameterEstimation/config.yml -j 5 -kp
imp=$(cut -f4 -d... |
042a83dafb8aa10ac3fbd40e205c392ae1709674e1a7ab3af274daea2e541c2f | Shell | 1,903 | 51 | #!/bin/bash
# Load environment (or replace with your Singularity execution if dependencies require it)
module load anaconda3_cpu
# Ensure the output directory exists
mkdir -p labels
LABEL=bin/utils/generate_FalseLabels.py
# ==========================================
# 1. Generate MNIST Labels
# =====================... |
02125f5fb1a4c8904dadf947e593a701478a577713ac0d603b2c1df346db06f9 | Shell | 1,908 | 32 | #!/bin/bash
#SBATCH --job-name=bc190819neg
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=2
#SBATCH --nodes=1
#SBATCH --gres=gpu:2
#SBATCH --time=1440
#SBATCH --mem=200G
#SBATCH --partition=gpu
#SBATCH --error=/private/groups/brookslab/gabai/projects/Add-seq/scripts/sbatch/log/lsf_%j_%x.err # error file
#SBATCH --outp... |
d74b12bd5effc9b4d3cfcaee409e3b76fe4f5c6f001b20c56f6c7eb000cfc85c | Shell | 1,909 | 45 | #!/bin/bash -l
#SBATCH --job-name=WASABI_boldmeans
#SBATCH --nodes=1
#SBATCH --cpus-per-task=4
#SBATCH --mem-per-cpu=100gb
#SBATCH --time=24:00:00
#SBATCH -o boldmeans_%A_%a.o
#SBATCH -e boldmeans_%A_%a.e
#SBATCH --account=DBIC
#SBATCH --partition=standard
# Find out how many files are needed to process by running file... |
c9b197b1327c9c1f2e2217d6f39f0362d4a2cfa7af86cac144a01a5f4537bfd9 | Shell | 1,917 | 75 | #!/usr/bin/env bash
# Glide docking ensemble executor
# 1. Pass the mae or maegz files with the pre-aligned protein structures.
# 2. Grid generation and docking calculation
# Use as
# ./ensemble_docking_001.sh /path-to-structures/*.maegz
# or if you rather to release the console use as:
# ./ensemble_docking_001.sh ... |
f6867626fe5ff40f3f070a741a9a579dbcb4cf6b0c5c66422e83689c357b33f1 | Shell | 1,920 | 64 | #!/bin/bash
export FREESURFER_HOME='/usr/local/freesurfer/7.4.1'
source $FREESURFER_HOME/SetUpFreeSurfer.sh
# Freesurfer v7 stats
export SUBJECTS_DIR="/media/raid/ibrazug/Dokumente/KindersegV2/Ibra/derivatives/Freesurfer7"
subs=($(ls -1d $SUBJECTS_DIR/sub*))
cd $SUBJECTS_DIR
#echo ${subs[@]}
stats_dir="$HOME/dat... |
fdbbd1453de3684b93c0d3084eeea189a9e0a135dc3f020d4ad73da16484b00d | Shell | 1,920 | 15 | #!/bin/bash
samplename=$1
tar czf ${samplename}_battenberg_segmentation.tar.gz *egmented*txt *_segment_chr*png *RAFseg*png && rm *egmented*txt *_segment_chr*png *RAFseg*png
tar czf ${samplename}_battenberg_haplotyping.tar.gz *heterozygousMutBAFs_haplotyped.txt *_heterozygousData.png *impute_input* *_allHaplotypeInfo.t... |
c043471ab8c28515b21b9c64e39d941d78a58b6cbcfd5d1f0c20094817e37e82 | Shell | 1,929 | 84 | while getopts "g:o:s:l:" opt
do
case "$opt" in
g ) parameterG="$OPTARG" ;;
o ) parameterO="$OPTARG" ;;
s ) parameterS="$OPTARG" ;;
l ) parameterL="$OPTARG" ;;
? ) helpFunction ;; # Print helpFunction in case parameter is non-existent
esac
done
# This script needs to run with R
#... |
5025d1553d8f628b6f565b54afac86f039b776e9a7494618ed0cc27a67e5b38e | Shell | 1,934 | 71 | #!/bin/bash
## Companion script for ops/pipeline/test-python-wheel.sh
set -eo pipefail
if [[ "$#" -lt 1 ]]
then
echo "Usage: $0 {gpu|mgpu|cpu|cpu-arm64}"
exit 1
fi
suite="$1"
# Cannot set -u before Conda env activation
case "$suite" in
gpu|mgpu)
source activate gpu_test
;;
cpu)
source activate l... |
bd338e0b3239e8180c809c3c77e4e145f3656fd05a590fa6ae5135cf96a5bd0a | Shell | 1,935 | 72 | #!/bin/bash
export JAVA_HOME=/usr/lib/jvm/java-11-openjdk-amd64/
# Change to the DfAnalyzer directory
cd /opt/dlprov/DfAnalyzer
# Start and restore the MonetDB database
echo "Restoring the database..."
#./restore-database.sh # Uncomment if you need to restore the database
monetdbd stop data || { echo "Failed to sto... |
9af3fc9ace2217337b818a97f8c4d2da1e7658875b629eef474002c2eb3baab5 | Shell | 1,939 | 88 | #!/bin/bash
# To run the script you need to install rename
cd result_clusters_sdf
# The cycle creates the hypotheses of pharmacophores for each file
echo ::::: Create hypotheses of pharmacophores :::::
echo
for dir in $(ls)
do
echo Creating pharmacophores in: $dir
cd /home/pvalenzuela/01_test/result_clusters_sdf/... |
a93eeb9d4f176d0dcc340ee4c108eafaea9a7675c62d502d8265f8c3ca59d48e | Shell | 1,944 | 50 | #!/bin/bash
#a demo for simulation with Spanki.
home_dir=/home/yuanhua/research
hisatDir=$home_dir/tool/hisat-0.1.6-beta
anno_dir=$home_dir/splicing/data/Annotation
hisatRef=$anno_dir/human/hisatRef/GRCh38.p2.genome
junc=$anno_dir/human/junc.v22.tsv
#### Generate reads ####
anno_file=$anno_dir/human/AS_event/SE.fil... |
7892a791a5f4fdde2f21db6171723f7af6beb25e4f81f4d197eeecdceae1040a | Shell | 1,946 | 48 | # Demo for WGS data from a cancer patient
: ex: set ft=markdown ;:<<'```shell' #
The following CHISEL demo represents a guided example of the CHISEL pipeline starting from the computed RDRs and BAFs (typically the file `combo.tsv` in the folder `combo`) for tumor section E of breast cancer patient S0. Simply run this ... |
7a98abe909e0ba1cb6362c2ae11b6db0aca9df013507dd6ef0a7aae9235f7cee | Shell | 1,961 | 54 | #!/bin/bash -e
REPO="$(readlink -f $1)"
BUILD="$(readlink -f $2)"
BINARY_NAME="${3:-mmseqs}"
if [ ! -d "$REPO" ]; then
echo "${BINARY_NAME} repository missing"
exit 1
fi
mkdir -p "$BUILD/build_sse41" && cd "$BUILD/build_sse41"
cmake -DCMAKE_BUILD_TYPE=Release -DHAVE_TESTS=0 -DHAVE_MPI=0 -DHAVE_SSE4_1=1 -DBUIL... |
5516956b34c538ca497d705e8c36c19a1622e963677805aae586ad29be4a54c8 | Shell | 1,962 | 74 | #!/bin/bash
# requires morbidmap.txt from OMIM in datadir
# requires genemap2.txt from OMIM in datadir
function usage {
echo -e "omim_download.sh\n\nParse and import omim genemap2 and morbidmap data.\n"
echo -e "Usage: omim_download.sh -d <DATA_DIR> -s <SCRIPT_DIR> -u <DB_USER> -r <DB_HOST> -p <DB_OWD>\n"
... |
490ad29539a85edb0b24fb458fc785998d3bf69b8d4962437b9ae83a19439ee5 | Shell | 1,970 | 73 | #!/bin/bash
BAM_DIR="/cluster/projects/epigenomics/Aminnn/CNR/EpigenomeLab/EPI_P003_CNR_MM10_07172022/analysis/02_alignment/bowtie2/target/adjusted_replicated"
OUTPUT_DIR="${BAM_DIR}/results/LANCEOTRON"
BIGWIG_DIR="${OUTPUT_DIR}/bigwig_files"
mkdir -p "$OUTPUT_DIR" "$BIGWIG_DIR"
run_lanceotron() {
local bam_f... |
9196a0801331a43c1e29ed29a371b50a0f53219d321a168fa313a0561d6da0df | Shell | 1,971 | 78 | #! /bin/bash
# Tips: test the scripts block by block
SCR_DIR=`pwd`
DAT_DIR=~/splicing/germ
cd $DAT_DIR
#### Download ####
mkdir $DAT_DIR/fastq
i=1
while IFS=$'\t' read -r -a myArray
do
test $i -eq 1 && ((i=i+1)) && continue
echo "${myArray[1]}" "${myArray[2]}"
wget "${myArray[2]}" -O $DAT_DIR/fastq/"${m... |
06b5742d64b19526ed563dbf62d814a6c64135eb6f22bc953e7db4bf719ac8a3 | Shell | 1,982 | 60 | #!/bin/bash
# format_cpp.sh — format the C++/CUDA sources with clang-format
# Usage: ./format_cpp.sh [update|check]
# Default: check
#
# src/dlpack.h is vendored and deliberately excluded; see VENDORED_PRUNE below.
set -u
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
REPO_ROOT="$(cd "${SCRIPT_DIR}/.." &&... |
354926363eb375f64bbe147340ebcd25c69d0057fbde690959baaf7d622a52be | Shell | 1,989 | 36 | #!/bin/bash
#SBATCH --job-name=pred0819
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=6
#SBATCH --nodes=1
#SBATCH --gres=gpu:1
#SBATCH --time=1440
#SBATCH --mem=1500G
#SBATCH --partition=gpu
#SBATCH --error=/private/groups/brookslab/gabai/projects/Add-seq/scripts/sbatch/log/lsf_%j_%x.err # error file
#SBATCH --output... |
1cdd61595b63d22117eb58c1eac3e329893b51323fab89599ade45ea874a5429 | Shell | 1,991 | 83 | #!/bin/bash
# Read arguments
# --ca_config: config file of the CA containing address, port, and root cert fingerprint
# --pki_assets: output path to store the CA root cert
while [ "${1:-}" != "" ]; do
case "$1" in
"--ca_config"*)
ca_config="${1#*=}"
;;
"--pki_assets"*)
pki_assets="... |
dc5a86b1a54c36678cfdce392b2e29d947a766c658c269519b0b204fd038f00c | Shell | 1,992 | 92 | #!/bin/bash
set -eo pipefail
# Default values
INPUT_DATA=""
INPUT_LABELS=""
MODEL_FILES=""
OUTPUT_RESULTS=""
# Parse arguments
while [[ $# -gt 0 ]]; do
case $1 in
--input-data)
INPUT_DATA="$2"
shift 2
;;
--input-labels)
INPUT_LABELS="$2"
... |
2f100d96089535f607c66c77739d2a9f544e716ed23baf44a0e79eb272b453a4 | Shell | 1,998 | 58 | #!/bin/bash
# script to start multiple training runs with different configurations
# run with: nohup bash train_multiple.sh &
# Get the current date and time
timestamp=$(date +"%Y-%m-%d_%H-%M-%S")
# Set the relevant directories
code_directory="INSERT/PATH/TO/PHIMO-MRM/CODE/DIRECTORY"
anaconda_directory="INSERT/PATH/... |
39d5ab10daeeb4643fa962b329e9fcb8532bcea090ad1a6d32dd0279cfcbfc37 | Shell | 2,002 | 77 | #!/bin/bash
#SBATCH --job-name=slurm-test # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=30 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=3G # memory per cpu-core (4G is default)
#SBATCH --gr... |
e3a4fef459313b9935d63c02a00f8311bafb3b68460594b7bf0cdae0801ecb18 | Shell | 2,018 | 48 | # Demo for WGS data from a cancer patient
: ex: set ft=markdown ;:<<'```shell' #
The following CHISEL demo represents a guided example of the CHISEL pipeline starting from the inferred copy numbers (typically the file `calls.tsv` in the folder `calls`) for tumor section E of breast cancer patient S0, and thus identifi... |
2f4fe047c22de7f1f7385f0b561363007293b382e3be626e0a4e612274358113 | Shell | 2,020 | 75 | #!/bin/bash
# A script which is for now very ad-hoc and to be ran outside of this codebase and
# be provided with two repos of heudiconv,
# with virtualenvs setup inside under venvs/dev3.
# Was used for https://github.com/nipy/heudiconv/pull/129
#
# Sample invocation
# $> datalad install -g ///dicoms/dartmouth-phantom... |
d2cbddbe69c65441c79d242c8499f1a301b3df0534ebd0695f86daaac87a8e22 | Shell | 2,027 | 62 | #!/bin/bash
# turn on bash's job control
set -e
# load libs
. /sh_libs/liblog.sh
# write the password
info "Running tests in EncoderMap's SLURM node."
echo $LDAP_ADMIN_PASSWORD > /etc/ldap.secret
echo $LDAP_ADMIN_PASSWORD > /etc/pam_ldap.secret
echo $LDAP_ADMIN_PASSWORD > /etc/libnss-ldap.secret
unset LDAP_ADMIN_PAS... |
afd2d24dab30c195adeec2c2fb665c6130ddfbfe2fe2840a09d6a1bb0cdea028 | Shell | 2,029 | 47 | #!/bin/bash
sbatch <<EOF
#!/bin/bash
#SBATCH --job-name=babel-${BABEL_VERSION:-current}
#SBATCH --output=babel_outputs/logs/sbatch-${BABEL_VERSION:-babel-current}.out
#SBATCH --error=babel_outputs/logs/sbatch-${BABEL_VERSION:-babel-current}.err
#SBATCH --time=${BABEL_TIMEOUT:-24:00:00}
#SBATCH --mem=16G
#SBATCH --node... |
4f4ca9fd712a2bf204c16f70b3a7677a82fb8d9e7e21a1133ae8900f4813b3da | Shell | 2,037 | 44 | #!/usr/bin/env bash
echo "Preparing local medperf server..."
# we are located at /workspaces/medperf/ where repo is cloned to
pip install -r server/requirements.txt
pip install -r server/test-requirements.txt
pip install -e ./cli
medperf profile activate local
bash tutorials_scripts/setup_webui_training_tutorial.sh
cd ... |
5f7ed66ce5e66347005cbad53fe1713c00e0100a9d145dbdcde5312f5242b50e | Shell | 2,044 | 90 | MODEL_NAME="IDEA-CCNL/Erlangshen-Roberta-110M-NLI"
TEXTA_NAME=sentence1
TEXTB_NAME=sentence2
LABEL_NAME=label
ID_NAME=id
BATCH_SIZE=32
VAL_BATCH_SIZE=32
ZERO_STAGE=1
config_json="./ds_config.json"
cat <<EOT > $config_json
{
"train_micro_batch_size_per_gpu": $BATCH_SIZE,
"steps_per_print": 1000,
"gradient_clipp... |
d218f6ff15c014ddd1942945633f08283ade677d87171ca52ed6ef05a25d4e01 | Shell | 2,047 | 75 | #!/bin/bash
# A script which is for now very ad-hoc and to be ran outside of this codebase and
# be provided with two repos of heudiconv,
# with virtualenvs setup inside under venvs/dev3.
# Was used for https://github.com/nipy/heudiconv/pull/129
#
# Sample invocation
# $> datalad install -g ///dicoms/dartmouth-phantom... |
67fecbe6fc56e23f7f05e5c5484d9c2daecac695d51ccf2b20487e5eeb4b6812 | Shell | 2,052 | 54 | #!/bin/sh
# version.sh -- Script to build the htslib version string
#
# Author : James Bonfield <jkb@sanger.ac.uk>
#
# Copyright (C) 2017-2018 Genome Research Ltd.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Softwar... |
595f2af2a3761142c473b9fdcc36d090066f7784611569ef29829a31447781b2 | Shell | 2,058 | 86 | #!/bin/bash
# Read arguments
while [ "${1:-}" != "" ]; do
case "$1" in
"--predictions"*)
predictions="${1#*=}"
;;
"--labels"*)
labels="${1#*=}"
;;
"--output_path"*)
output_path="${1#*=}"
;;
"--parameters_file"*)... |
7def944d015c2cba2a3c973b5e197a62353927117be71b834b910c13b4f6d2d5 | Shell | 2,061 | 76 | #!/bin/sh
#
# Downloads sequence for the GRCh38 release 84 version of H. sapiens (human) from
# Ensembl.
#
# Note that Ensembl's GRCh38 build has three categories of compressed fasta
# files:
#
# The base files, named ??.fa.gz
#
# By default, this script builds and index for just the base files,
# since alignments to ... |
5ff75b7bf5dd5596c0a574fc47d034de3760ebd9d6d43ea1ca4f4946365c12bb | Shell | 2,068 | 67 | #!/bin/bash
export CUDA_VISIBLE_DEVICES=0
# activate you conda env if not
# conda activate your_env_name
# run the training
## single gpu start
python main.py \
--task diffusion_digital \
--num_gpu 1 \
--data_path ./data/your_datapath \
--output_dir ./logs/exp \
--sample_size 32 \
--in_channe... |
8acc7a83597e21aea8706e3cc83c7ffc3eebbd9107c5f21ed607d6fb795bfc73 | Shell | 2,082 | 96 | #!/usr/bin/env bats
setup () {
name="abricate"
bats_require_minimum_version 1.5.0
dir=$(dirname "$BATS_TEST_FILENAME")
cd "$dir"
exe="$dir/../bin/$name"
cpus=$(nproc)
}
@test "Script syntax check" {
run -0 perl -c "$exe"
}
@test "Version" {
run -0 $exe --version
[[ "$output" =~ "$name " ]]
}
@test "... |
14ee6248069ea95cb95cfb46302c221c82b3928abd8ddbed0a9ba538f1e3b766 | Shell | 2,083 | 85 | #!/bin/bash
: '
- Algorithm
1. User edits the configure file (*.cfg).
2. User runs this script with configure file.
> sh 0_Configure_Setting.sh this_config_file.cfg
3. Read config file and store TOOL_ID, TOOL_PATH in variables.
4. Initialize by removing existing pipeline scripts (*_ps_*.sh), and
... |
62497063d418c826600d4f5be5ab1d036805f9eed05df785059c9d64170eef13 | Shell | 2,086 | 75 | #!/bin/sh
#
# Downloads sequence for the HG38 version of H. spiens (human) from
# UCSC.
#
# The base files, named ??.fa.gz
#
# By default, this script builds and index for just the base files,
# since alignments to those sequences are the most useful. To change
# which categories are built by this script, edit the CH... |
d88949444e86cb16a2fca077de276cd1bffb0378ef08bb54d9cff16425569389 | Shell | 2,092 | 75 | #!/bin/sh
#
# Downloads sequence for the HG38 version of H. spiens (human) from
# UCSC.
#
# The base files, named ??.fa.gz
#
# By default, this script builds and index for just the base files,
# since alignments to those sequences are the most useful. To change
# which categories are built by this script, edit the CH... |
1ca72910f183eb8412d3875c022679c5c2d02f186adb7c37f1a294141899fbe0 | Shell | 2,094 | 79 | #!/bin/bash
## Build and test JVM packages.
## Companion script for ops/pipeline/build-test-jvm-packages.sh.
##
## Note. This script takes in all inputs via environment variables.
INPUT_DOC=$(
cat <<-EOF
Inputs
- SCALA_VERSION: Scala version, either 2.12 or 2.13 (Required)
- USE_CUDA: Set to 1 to enab... |
1da20dad03cad014192068cc51d507611c0b482829fbb51a137653ddbbaff7b6 | Shell | 2,100 | 41 | #!/bin/bash -c
# PREPROCESSING
subjects=("sub-001" "sub-002" "sub-003" "sub-004" "sub-005" "sub-006" "sub-007" "sub-008" "sub-009" "sub-010" "sub-011" "sub-012" "sub-013" "sub-014" "sub-015" "sub-016" "sub-017" "sub-018" "sub-019" "sub-020" "sub-021" "sub-022" "sub-023" "sub-024" "sub-025" "sub-026" "sub-027" "sub-02... |
5a678012b68d83f073ab8525390fbab90b0d775242f1fce679d585e591f20812 | Shell | 2,107 | 45 | #!/bin/bash
#SBATCH --job-name=test
#SBATCH --cpus-per-task=128
#SBATCH --nodes=4
#SBATCH --tasks-per-node=1
#SBATCH --partition=all
module load cuda/cuda-11.0
source ~/venv/bin/activate
let "worker_num=(${SLURM_NTASKS} - 1)"
# Define the total number of CPU cores available to ray
let "total_cores=${SLURM_NTASKS} ... |
f9faafbc660c94a37bc5006489eae86b3408b6b9c66658785ca21beae78a395c | Shell | 2,108 | 59 | #!/bin/bash
SIF=/storage/group/bfp2/default/wkl2-WillLai/Adversarial_Project/Adversarial_Observation/manuscripts/POISON25/pytorch-captum.sif
WORKINGDIR=/storage/group/bfp2/default/wkl2-WillLai/Adversarial_Project/Adversarial_Observation/manuscripts/POISON25
# ==========================================
# CONFIGURATION... |
0d582a62dcd1a2c7a2dce7b59944793f85de300700d1d292035f71e165ba79b2 | Shell | 2,115 | 98 | #!/bin/bash
set -e
usage() {
cat <<EOF
usage: $0 options
Set up environments for scib-pipeline
OPTIONS:
-h Show this message
-r R version to determine which environments should be installed
-m Command to install conda packages, either 'mamba' or 'conda' (default: mamba)
-q Quiet install... |
4cc0acdb72844e566eae10daeec4e788494cdf26abefaf3252b614bbdeb09f6d | Shell | 2,129 | 51 | #!/bin/bash
## Effect size maps for the smg contrast ##
## Formula: SD_pooled = square_root{[(n1-1)SD1_square + (n2-1)SD2_square]/(n1+n2-2)} ##
cd /path
ez="/path/Effect_size"
# Create group files of the pAF
fslmaths af_l_post_all_densityNorm_smoothed6mm.nii.gz -thr 0.0005 $ez/af_l_post_all_densityNorm_smoothed6mm_t... |
99b086ee57f8cf21f6bae54a830cf471b92a74109bf54a665c444b26adaf2c69 | Shell | 2,144 | 74 | #!/bin/bash
if [ -z ${DBPASS+x} ]; then
echo "DBPASS is unset";
exit 1
else
echo "DBPASS is set";
fi
if [ -z ${DBNAME+x} ]; then
DBNAME=eicu
echo "DBNAME is unset, using default '$DBNAME'";
else
echo "DBNAME is set to '$DBNAME'";
fi
if [ -z ${DBUSER+x} ]; then
DBUSER=postgres
echo "User is unset, usin... |
fa7f615846c9be0e15d26ac1cfd0bb947c8c716a0757f55b4df911dfede44714 | Shell | 2,147 | 45 | #!/usr/bin/bash
# ==============================================================================
# SCRIPT INFORMATION:
# ==============================================================================
# SCRIPT: RUN BIDS VALIDATOR COMMAND LINE TOOL THROUGH SINGULARITY
# PROJECT: ZOO
# WRITTEN BY LENNART WITTKUHN, 2020
# ... |
9fee47b8e4fc081c88dc1af2722a15e0dc5cc4427c45d53840f310e1c0125e54 | Shell | 2,150 | 69 | #!/bin/sh -e
fail() {
echo "Error: $1"
exit 1
}
notExists() {
[ ! -f "$1" ]
}
#pre processing
[ -z "$MMSEQS" ] && echo "Please set the environment variable \$MMSEQS to your MMSEQS binary." && exit 1;
# check number of input variables
[ "$#" -ne 4 ] && echo "Please provide <queryDB> <targetDB> <outDB> <tmp>"... |
60e130da8393efc12b9101930359d4c0d0403b7f449bbd67a417021d84a20111 | Shell | 2,155 | 52 | #!/bin/bash
set -euo pipefail
## Install Docker
# Add Docker's official GPG key:
sudo install -m 0755 -d /etc/apt/keyrings
sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
sudo chmod a+r /etc/apt/keyrings/docker.asc
# Add the repository to Apt sources:
echo \
"deb [arch=$(... |
285879956747df345394854842755067a2c2d0012b0d679bb0ba44b614f268c7 | Shell | 2,156 | 70 | #!/bin/bash -l
#SBATCH --job-name=spctp_fmriprp
#SBATCH --nodes=1
#SBATCH --ntasks=16
#SBATCH --mem-per-cpu=8gb
#SBATCH --time=2-00:00:00
#SBATCH -o ./log/preproc_%A_%a.o
#SBATCH -e ./log/preproc_%A_%a.e
#SBATCH --account=DBIC
#SBATCH --partition=standard
#SBATCH --array=11,12,15,16
## --array=1-17%5
#source /optnfs/... |
93cdd4ffd762b530aa2839b953c55c91cdce00050850516f4548c9d9010b2814 | Shell | 2,163 | 64 | #!/bin/sh
# Check that zgrep is terminated gracefully by signal when
# its grep/sed pipeline is terminated by a signal.
# Copyright (C) 2010-2016 Free Software Foundation, Inc.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by... |
35823af80d9fb5e57f06d3f0e4600a559e19efddb94d6b8747f1f300b0a4add3 | Shell | 2,165 | 52 | # Demo for WGS data from a cancer patient
: ex: set ft=markdown ;:<<'```shell' #
The following CHISEL demo represents a guided example of the CHISEL pipeline starting from the inferred copy numbers (typically the file `calls.tsv` in the folder `calls`) and identified clones (typically the file `mapping.tsv` in the fol... |
5d0473eae91937cd102a22dd0cd16217116ecae82b9c431cdd9180387d3afacd | Shell | 2,172 | 43 | #!/bin/bash -c
# Variability in Autoreject seed: test with different seeds, preprocessing and EEGNet
# PREPROCESSING
subjects=("sub-001" "sub-002" "sub-003" "sub-004" "sub-005" "sub-006" "sub-007" "sub-008" "sub-009" "sub-010" "sub-011" "sub-012" "sub-013" "sub-014" "sub-015" "sub-016" "sub-017" "sub-018" "sub-019" ... |
5e847b43b72d089c05e44b84df6cef95b26322a6de7c86a9f92546ce6aa1e84b | Shell | 2,180 | 68 | #!/bin/sh
# Ensure that gzip -cdf handles mixed compressed/not-compressed data
# Before gzip-1.5, it would produce invalid output.
# Copyright (C) 2010-2016 Free Software Foundation, Inc.
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as p... |
e787c995c788aa9239501ec9e6ec531c0ae1164d5a15cafcf599c900f99f5f70 | Shell | 2,189 | 75 | #!/bin/bash
#SBATCH --job-name=taiyi-sd-dreambooth # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks-per-node=1 # number of tasks to run per node
#SBATCH --cpus-per-task=30 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --gres=gpu:1 # number of gpus per node
#SBATCH -o %x-%j.... |
7d4eba8399f16d656ea99b39e1a2ae1391b0207e54b7b7914db4d379b0f3b357 | Shell | 2,196 | 67 | #!/bin/bash -l
#SBATCH --job-name=spctp_prprc
#SBATCH --nodes=1
#SBATCH --ntasks=16
#SBATCH --mem-per-cpu=8gb
#SBATCH --time=06:00:00
#SBATCH -o ./log/preproc_%A_%a.o
#SBATCH -e ./log/preproc_%A_%a.e
#SBATCH --account=DBIC
#SBATCH --partition=standard
#SBATCH --array=1-17%5
## --array=1-17%5
#source /optnfs/common/mi... |
7f6b34e16eea4d67434c43542fd70df67a5af5dc16c2b3374b17792508f4f2de | Shell | 2,202 | 72 | #!/bin/bash
#SBATCH --job-name=eval_llama-7B # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks-per-node=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=12 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=16G # memory per cpu-core (4G is default)... |
615b3ac4ee304c6a5a0101cf06d54eaacd0c1f70600dfe451bd058cda68546c4 | Shell | 2,210 | 73 | #!/bin/bash
#SBATCH --job-name=eval_llama-7B # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks-per-node=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=12 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=16G # memory per cpu-core (4G is default)... |
31d0e2884e619df5651b5b67f7b26eb435531467f1313ac16e41996396f09191 | Shell | 2,216 | 37 | #!/bin/bash
set -eu
v=2024.1.4
generate() {
# unused ATM
# [ "$1" == singularity ] && add_entry=' "$@"' || add_entry=''
ndversion=1.0.1
# Thought to use conda-forge for this, but feedstock is not maintained:
# https://github.com/conda-forge/psychopy-feedstock/issues/64
# --miniconda version=py31... |
f117ca9ba23af0191686c25638b9ad573c90f4d12b53e811050a2977ce1d4488 | Shell | 2,246 | 54 | #!/bin/bash
clear
echo "Setting up environment variables"
SIMULATION_DIR=`pwd`
DFA_PROPERTIES=$SIMULATION_DIR/DfA.properties
DI_DIR=$SIMULATION_DIR
DB_CONFIG_FILE=database.conf
DFANALYZER_VERSION=1.0
echo "--------------------------------------------"
echo "Removing data from previous executions"
rm $DFA_PROPERTIES
# o... |
100136ef5a72b55565122c802ff476e5886d5fe94c8dded85149f923c1187c6b | Shell | 2,251 | 75 | #!/bin/bash
#SBATCH --job-name=slurm-test # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=2 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=16G # memory per cpu-core (4G is default)
#SBATCH --gr... |
a07f0f99199636f03146030e0893dc8b4775d5f2c69265a9d6f77667457de450 | Shell | 2,251 | 42 | #!/usr/bin/env bash
#
# Description:
#
# This script is used to generate a Singularity container that can be used
# to run all the analyses reported in our manuscript.
#
# This script was initially written to be used on a Linux box running
# Ubuntu 18.04.
#
# Usage:
#
# $ bash container/gen_simg.sh
... |
35c3af45f81557453f99280b5aae19e97a5aceaa0b278985d67d00084a8d59ea | Shell | 2,261 | 76 | #!/bin/bash
#SBATCH --job-name=slurm-test # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=30 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --mem-per-cpu=4G # memory per cpu-core (4G is default)
#SBATCH --gr... |
bc2f483d08bdc1e4aa19e189cdd8a2578a3f40f1c044613657a669c357fe28f1 | Shell | 2,269 | 65 | #!/bin/bash
set -e
rm -fr ./*.pem /tmp/nvflare/poc
world_size=2
# Generate server and client certificates.
openssl req -x509 -newkey rsa:2048 -days 7 -nodes -keyout server-key.pem -out server-cert.pem -subj "/C=US/CN=localhost"
openssl req -x509 -newkey rsa:2048 -days 7 -nodes -keyout client-key.pem -out client-cer... |
a42b855576d619ce33ecdbf27cac0e2d71b47a88b8fd24fb86ea1e80b5fc6831 | Shell | 2,270 | 50 | #!/bin/bash
## Effect size maps for the stg constrast ##
## Formula: SD_pooled = square_root{[(n1-1)SD1_square + (n2-1)SD2_square]/(n1+n2-2)} ##
cd /path
ez="path/Effect_size"
# Create group files of the pAF
fslmaths contrast_aflp_all_fdt_pathsNorm_smoothed6mm.nii.gz -thr 0.01 $ez/contrast_aflp__all_fdt_pathsNorm_sm... |
1a4b4f04562bd57e2e36930fca7bd8d4064fe2d72b67c85a63730ad12d64d275 | Shell | 2,307 | 92 | #!/usr/bin/env bash
# Script to set up Venv environments for multiple Python versions
HELP="
Create Venv environments for multiple Python versions.
Arguments:
-h: Show help and exit.
-d [path]: Path to folder where the new venv directory will be placed.
Defaults to \"../venvs\".
"
venv_dir="../venvs"
OPTIN... |
689cd19263e49316329e866564ad5b082c7744c31514849f57a01efbb48e5344 | Shell | 2,317 | 82 | #!/bin/bash
############################################################################
# Script Name : buildFleX.sh
# Description : build FleX executables for each scene.
# Env :
# Args : --build=true|false
# Date : 30/... |
ee9b055a0e305e8c5f266056d3ef9f057d514120b8b80a8c27368c3ced09f112 | Shell | 2,330 | 70 | #!/bin/sh -e
fail() {
echo "Error: $1"
exit 1
}
notExists() {
[ ! -f "$1" ]
}
if notExists "${TMP_PATH}/query.dbtype"; then
# shellcheck disable=SC2086
"$MMSEQS" createdb "$@" "${TMP_PATH}/query" ${CREATEDB_PAR} \
|| fail "query createdb died"
fi
if notExists "${TARGET}.dbtype"; then
i... |
a30bdd2a0f1c48245218399901537b0174f4efd20eeed5749dff88650f23f4e5 | Shell | 2,343 | 51 | #!/bin/bash
model=ScaleDense
loss=mse
batch_size=32
lbd=10
beta=1
save_path=./pretrained_model/ScaleDense/
label=./data/dataset.xls
train_data=./data/train
valid_data=./data/val
test_data=./data/test
sorter_path=./TSAN/Sodeep_pretrain_weight/Tied_rank_best_lstmla_slen_${batch_size}.pth.tar
# ------ train and set th... |
fea7f4bc652fffce06970790650d49c7145562caf50a3bd70ea5fd6560827e08 | Shell | 2,343 | 74 | #!/bin/bash
vercomp () {
if [[ $1 == $2 ]]
then
echo 0
exit
fi
local IFS=.
local i ver1=($1) ver2=($2)
# fill empty fields in ver1 with zeros
for ((i=${#ver1[@]}; i<${#ver2[@]}; i++))
do
ver1[i]=0
done
for ((i=0; i<${#ver1[@]}; i++))
do
if [[ ... |
eda61202f5c6cef4c0b384ec4d6eb75abb042cc7aad76940d2ae86c8b8e4be71 | Shell | 2,344 | 78 | #!/bin/sh
#
# Downloads sequence for the GRCm37 release 81 version of M. Musculus (mouse) from
# Ensembl.
#
# By default, this script builds and index for just the base files,
# since alignments to those sequences are the most useful. To change
# which categories are built by this script, edit the CHRS_TO_INDEX
# var... |
edfe6ebd62bd2e33dd5e92b0f503ff99f520b3b34668ec353ea5d30a1f247997 | Shell | 2,349 | 80 | #!/bin/bash
### Line above tells to use the bash
### User fill in HERE
### If #SBATCH, not a comment but a directive for the slurm command.
###
### directives:
#
## Required batch arguments
#SBATCH --job-name=ID_63_local_refine
#SBATCH --partition=HighFreq
#SBATCH --ntasks=1
#SBATCH --nodes=1
##SBATCH --tasks-per-node=... |
45ffd0ce33f83937328240624eeb1bd8bea7a048bb10bca0becfcb6a036c3957 | Shell | 2,353 | 77 | #!/bin/bash
# Save this as run_GliODIL.sh
# Check for directory argument
if [ "$#" -ne 1 ]; then
echo "Usage: $0 <directory>"
exit 1
fi
directory=$1
# Source the configuration file for static options
source config.sh
# Find files in the given directory with either .nii or .nii.gz extension
seg_path=$(realpa... |
ed0656b774e3b588d3c42b7c9095ffbfc91cc90cfaf6c5e19b957bf22321c08f | Shell | 2,353 | 83 | #!/bin/bash
#SBATCH --job-name=zen2_base_cmeee # create a short name for your job
#SBATCH --nodes=1 # node count
#SBATCH --ntasks-per-node=1 # total number of tasks across all nodes
#SBATCH --cpus-per-task=30 # cpu-cores per task (>1 if multi-threaded tasks)
#SBATCH --gres=gpu:1 # number of gpus per node
#SBATCH --mail... |
f1c01fb2c93aab2fce96697b4f0608f8fdb9c31763fb6565489d6f2081b4495d | Shell | 2,369 | 30 | # getting Ancestral allele
mkdir -p ancestral
cd ancestral
wget https://ftp.ensembl.org/pub/release-105/fasta/ancestral_alleles/homo_sapiens_ancestor_GRCh38.tar.gz -nc
tar -xzvf homo_sapiens_ancestor_GRCh38.tar.gz
seq 1 22 |awk '{print "cat homo_sapiens_ancestor_GRCh38/homo_sapiens_ancestor_"$1".fa |tail -n+2|fold -w1|... |
5bcd5d1401179886c53af4abb10f351781de70393fdef07ecb7a7e5fe38b9497 | Shell | 2,380 | 67 | #!/bin/sh -e
fail() {
echo "Error: $1"
exit 1
}
notExists() {
[ ! -f "$1" ]
}
if notExists "${TMP_PATH}/input.dbtype"; then
# shellcheck disable=SC2086
"$MMSEQS" createdb "$@" "${TMP_PATH}/input" ${CREATEDB_PAR} \
|| fail "query createdb died"
fi
if notExists "${TMP_PATH}/clu.dbtype"; the... |
ab3ee1b4aeac73d0c2255f5cf89ab75d9d4b33f257b218d22c90ab4f5d7ce7b3 | Shell | 2,395 | 88 | #!/bin/bash -ex
COMMIT="$1"
RELEASE_ID="$2"
RELEASE_MSG="$3"
if [ -z "${GITHUB_TOKEN}" ]; then
echo "Please set GitHub Token"
exit 1
fi
function hasCommand() {
command -v "$1" >/dev/null 2>&1 || { echo "Please make sure that $1 is in \$PATH."; exit 1; }
}
hasCommand github-release
hasCommand echo
hasCommand date... |
6a9c56f92bc933e0e867ff63e631d54267487ff2d827feb99e86f90dd0f3441b | Shell | 2,400 | 48 | ###
# @Date: 2022-11-29 13:42:46
# @LastEditors: yuhhong
# @LastEditTime: 2022-11-29 13:43:51
###
for VARIABLE in {0..17}
do
if [[ "$VARIABLE" =~ ^(4|16|7|10)$ ]]; then
echo "python main_chir_kfold.py --config ./configs/molnet_train_l.yaml --k_fold 5 --csp_no $VARIABLE \
--log_dir ./logs/molnet_chirali... |
70130eeb4119cf853d3fa6467ed8fb8f9862418bf354abee4da9931261045d6e | Shell | 2,411 | 115 | #!/bin/bash
#SBATCH --job-name=mbart_en_zh
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
#SBATCH --gres=gpu:8 # number of gpus
#SBATCH --cpus-per-task=32
#SBATCH -o %x-%j.log
set -x -e
echo "START TIME: $(date)"
MODEL_NAME=deltalm_en_zh
MICRO_BATCH_SIZE=16
ROOT_DIR=../../workspace
MODEL_ROOT_DIR=$ROOT_... |
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