sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 17k | content stringlengths 1 200k |
|---|---|---|---|---|
42a75b33a8f312be91581f3f8a3710bf3fa377a1085f8cd3b7389e7357b559f6 | Shell | 1,193 | 31 | #!/usr/bin/env bash
set -euo pipefail
# Run SQANTI3 QC/curation on IsoQuant transcript models.
# Run this script from the repository root. Docker must be available.
SQANTI3_IMAGE="anaconesalab/sqanti3:latest"
ISOQUANT_GTF="results/isoquant_3BAMs_sensitive_fl_noUnspliced_v1_output/OUT/OUT.transcript_models.gtf"
ISOQU... |
a4720df666b1b726967a1e80cfccd5637fbce92b5df5f754a9ca02c49ce9e039 | Shell | 1,196 | 36 | #!/bin/sh
# create MNI 1mm mask
mask_MNI1mm=SubcorticalLooseMask_MNI1mm
mri_binarize --i ${CBIG_CODE_DIR}/data/templates/volume/FSL_MNI152_FS4.5.0/mri/aparc+aseg.mgz --match 16 --match 8 --match 9 --match 10 --match 11 --match 12 --match 13 --match 17 --match 18 --match 26 --match 27 --match 28 --match 47 --match 48... |
8e052b80c3ffce2860638c6c0b11e25561085f140f963e6023825d2b900b40dd | Shell | 1,205 | 33 | #!/bin/bash
#
# CBIG_check_whether_function_used_in_other_functions.sh $input_function_name $folder
# Search for all instances of a function name inside a given folder and give a warning
input_function_name=$1
folder=$2
# function to join array into string
function join_str { local IFS="$1"; shift; echo "$*"; }
# ... |
10973bc6fc70ad143d1dde8afe4b7b194531289452198d4d1e0c0fed5c773193 | Shell | 1,206 | 45 | #!/usr/bin/env bash
#
# copyright (c) 2017-present, facebook, inc.
# all rights reserved.
#
# this source code is licensed under the MIT license found in the
# license file in the root directory of this source tree.
#
# script for FB15k237
DIR=data/Release/
FASTTEXTDIR=../../
# compile
pushd $FASTTEXTDIR
make opt
pop... |
3da34ca943ad05970c405bde325f815237c423dc14f3c56e4e6bffade1b4e06d | Shell | 1,209 | 36 | #!/bin/bash
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
if [ -z $WORKDIR_ROOT ] ;
then
echo "please specify your working directory root in environment variabl... |
02bad228ee9a8213c302db1626a403b7372e9ca27b96b279ed299ae9ff6e360d | Shell | 1,222 | 35 | #!/usr/bin/env bash
##
# @file train_baseline.bash
# @author Simon Yu
# @date 12/06/2024
# @brief Script for training baseline models.
##
# Go to script directory
cd "$(dirname $0)"
# Go to source directory
cd "../../src/npc-models"
./train_baseline.py -m "abm" -b 256 -e 150 -s 42
./train_baseline.py -m "abm" ... |
26a329040b1f91c87cb1e39a00772ff376479ec21a266dfff20276eea033c4bd | Shell | 1,222 | 30 | # Path of the folder containing all data
dir="/root/dir"
# List of subjects
declare -a sub=("sub-SPAIN01" "sub-SPAIN02" "sub-SPAIN04" "sub-SPAIN06" "sub-SPAIN07" "sub-SPAIN08" "sub-SPAIN11" "sub-SPAIN13" "sub-SPAIN15" "sub-SPAIN16" "sub-SPAIN19" "sub-SPAIN20" "sub-SPAIN21" "sub-SPAIN24" "sub-SPAIN25" "sub-SPAIN26" "su... |
6da950069aa6ffa14cce1d35fecfd2c26fe521a8a6885a7bca84c5501f411a65 | Shell | 1,226 | 44 | #!/bin/bash
# Written by Xiuming Zhang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
###########################################
# Usage and Reading in Parameters
###########################################
# Usage
usage() { echo "
Usage: $0 -v <4DVolume> -s <sigma> -o <outD... |
4a1cf828a7216964ea0f9f654a24dd0a9503c86a3c34695c77fb4de3fa21b135 | Shell | 1,228 | 29 | # Path of the folder containing all data
dir="/root/dir"
sct_dir="/sct/dir/6.5"
# randomise_parallel is a wrapper for fsl_sub
# The default memory parameters might be too low and cause an out of memory error on SLURM
# To avoid this set a memory requirement before running this:
# setenv FSLSUB_MEMORY_REQUIRED "10G"
f... |
970d7f661fd22779a2938bf842182a7339ec0b06e0a55e73a3d6d32f46f9dd42 | Shell | 1,230 | 40 | #!/bin/bash
# Written by Xiuming Zhang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
###########################################
# Usage and Reading in Parameters
###########################################
# Usage
usage() { echo "
Usage: $0 -l <brainNameList> -d <brainDir>
... |
46c46aa9f1899a489827cd6e0bace80f7cc7eaee41e4f64d4c1ea8472bc54506 | Shell | 1,232 | 39 | #!/bin/bash
# Stop on error
set -e
CONDA_ENV=encode-atac-seq-pipeline
CONDA_ENV_PY3=encode-atac-seq-pipeline-python3
SH_SCRIPT_DIR=$(cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd)
REQ_TXT=${SH_SCRIPT_DIR}/requirements.txt
REQ_TXT_PY3=${SH_SCRIPT_DIR}/requirements_py3.txt
if which conda; then
echo "=== Found Conda ... |
5210571265f46ba2ba965acd7481d25b017e8656a80fc4467a1faa1a04019bb9 | Shell | 1,237 | 40 | #!/bin/bash
#SBATCH --account=nn9114k
#SBATCH --time=24:00:00 --cpus-per-task 16 --mem-per-cpu=3936M
i_hsq=$1
i_coding=$2
i_noncoding=$3
i_s2coding=$4
i_repeat=$5
CFG_FILE="optimize.e1.hsq_${i_hsq}.coding_${i_coding=}.noncoding_${i_noncoding=}.s2coding_${i_s2coding=}.${i_repeat}.cfg"
LOG_FILE="cmm_${SLURM_JOBID}.optim... |
f5632cf4ff52d800bd0a6feac7599a2976ac2d06ecd6204804d7f0c5a13a1441 | Shell | 1,239 | 26 | # Path of the folder containing all data
dir="/root/dir"
# List of subjects
declare -a sub=("sub-SPAIN01" "sub-SPAIN02" "sub-SPAIN04" "sub-SPAIN06" "sub-SPAIN07" "sub-SPAIN08" "sub-SPAIN11" "sub-SPAIN13" "sub-SPAIN15" "sub-SPAIN16" "sub-SPAIN19" "sub-SPAIN20" "sub-SPAIN21" "sub-SPAIN24" "sub-SPAIN25" "sub-SPAIN26" "su... |
f4bf3d5608c8e79c68fa4419e206f4c09700f4112d008a117a7521fd227a4058 | Shell | 1,240 | 44 | #!/bin/bash
workdir=/Volumes/public/Backup/horiDir/qst/TauLNM/analysis_PSP_VBM/
sigma=1.6986 # FWHM=4 -> sigma=1.6986
cd ${workdir}
for roi_subj in `ls ../PET_SUVR/PSP_GMandWM/`;do
for thr in 3.27;do
cd ${workdir}
mkdir -p ./FCmaps_gsp/
cd ./FCmaps_gsp/
cp /Applications/NHPPipelines-master/global/templates/MNI... |
409b411bfcb67787950ae6b58525439d8b087865283e6f57c94526b1d8c68add | Shell | 1,248 | 46 | #!/bin/bash
# Florian Bénitière 16/03/2025
# Download, bgzip-compress, and index GRCh38 reference genome for VEP pipelines
# Check if htslib is available
if ! command -v htslib &> /dev/null; then
echo "htslib not found — loading module..."
module load htslib
else
echo "htslib already available."
fi
# Chec... |
52f864ac5e9abb34415e3ef0304464e2d3d6fe2bc67e68b4923c55feb1d59042 | Shell | 1,251 | 46 | #!/bin/bash
FAIRSEQ= # Setup your fairseq directory
config_dir=${FAIRSEQ}/examples/mr_hubert/config
config_name=mr_hubert_base_librispeech
# Prepared Data Directory
data_dir=librispeech
# -- data_dir
# -- test.tsv
# -- test.ltr
# -- dict.ltr.txt
exp_dir=exp # Target experiments directory (where you... |
ca3b2a83184b94badd85930f5d3ece5940ca7595d4528eda1ecb207144174722 | Shell | 1,251 | 46 | #!/bin/bash
FAIRSEQ= # Setup your fairseq directory
config_dir=${FAIRSEQ}/examples/mr_hubert/config
config_name=mr_hubert_base_librispeech
# override configs if need
max_tokens=3200000
max_sample_size=1000000
max_update=50000
# Prepared Data Directory
data_dir=librispeech
# -- data_dir
# -- train.tsv
# -- ... |
9a699540daa83bf739c56c430b0638fad7743ff72bf17bd371e4468a8f375de1 | Shell | 1,257 | 24 | #!/usr/bin/env bash
rm -rf fsdp_dummy
mkdir -p fsdp_dummy
CUDA_VISIBLE_DEVICES=0,1,2,3 fairseq-train /private/home/sshleifer/data-bin/stories_mmap \
--ddp-backend fully_sharded --fp16 --fp16-init-scale 4 \
--cpu-offload --checkpoint-activations \
--task language_modeling --tokens-per-sample 256 --batch-size... |
e69c15103516747349c497afa7874c552ff4c28ede18cd9edf25962aa4c14c54 | Shell | 1,257 | 39 | #conda create --name ERICA python=3.6 tensorflow=2.1.0 plotnine=0.6.0
#conda env create --file environment.yml
#source activate ERICA
# three taxa
python vcf2MSA.py \
-i test/pop_test.vcf.gz \
-r test/pop_test.fasta \
-o test/pop_test \
-f diplo \
-P1 H_m_aglaope_1,H_m_aglaope_2,H_m_aglaope_3,H_m_aglaope_4 \
-P2 H_m_a... |
ab0a6203e849544a7e360935cb008195c5646148282e0c2da2c985142c8570d2 | Shell | 1,260 | 39 | #!/bin/bash
set -e # stop on error
#~/my_bsub.sh PeaksPart1_AngL_fold0
#~/my_bsub.sh PeaksPart1_AngL_fold1
#~/my_bsub.sh PeaksPart1_AngL_fold2
#~/my_bsub.sh PeaksPart1_AngL_fold3
#~/my_bsub.sh PeaksPart1_AngL_fold4
#~/my_bsub.sh PeaksPart1_AngL_fold5
#~/my_bsub.sh PeaksPart2_AngL_fold0
#~/my_bsub.sh PeaksPart2_AngL_f... |
02d2bdbde9ce6e1b76a000849032360442ddf96444edf0f8ecd200faa041aee7 | Shell | 1,263 | 29 | #!/bin/bash
# Load MRIQC (adjust depending on your system/environment)
module load mriqc # depends on system settings
# ==== CONFIGURATION ====
Cohort='Cohort1' # adjust as needed
Timepoint='T1' # adjust as needed
ROOTDIR=/MyWorkingDirectory
# Swarm file to store job commands
SWARMFILE=${RO... |
100a22ebc2e444ae0ae3abd61156e49e86d73154b83b21ac2ac9887cc1f4ff58 | Shell | 1,265 | 40 | #!/bin/bash
#SBATCH --job-name=expB-ext
#SBATCH --gres=gpu:1
#SBATCH --mem=32G
#SBATCH --time=08:00:00
#SBATCH --output=/lustre/grp/gglab/liut/logs/expB_ext_%j.out
# Args: MODEL TEST_CONFIG SAMPLE_SIZE SEED LR BATCH
MODEL=$1
TEST_CONFIG=$2
SAMPLE_SIZE=$3
SEED=$4
LR=$5
BATCH=$6
CONDA_BASE=$(conda info --base 2>/dev/nu... |
57ffa3ec88af5865835ef27b57a401b36c4982ea5c80f97b621e798bcb5a477d | Shell | 1,271 | 27 | #!/bin/bash
# Job name:
#SBATCH --job-name=plsareal
#SBATCH --account=csd635
#SBATCH --time=2:00:00
#SBATCH --partition=shared
#SBATCH --cpus-per-task=20
#SBATCH --mem-per-cpu=5000M
#SBATCH --nodes=1
#SBATCH --array=1-20
#
## Set up job environment:
source /cluster/bin/jobsetup
module purge # clear any inherited m... |
b94a9a2a98a09ea3528f934d5b99c4a0af7be1d6c27d3f1b2f21651e9e20fb54 | Shell | 1,274 | 54 | #!/bin/bash
## Usage:
# sh bamtofastq.sh
## Create the logs directory
mkdir -p logs_bamtofastq
for sample in 151507 151508 151509 151510 151669 151670 151671 151672 151673 151674 151675 151676; do
## Internal script name
SHORT="bamtofastq_${sample}"
# Construct shell file
echo "Creating script bamt... |
12cf8a994e343f3030a53a2fd0d54d5c5a97eb2dd222ed6df87bb70e258ea5b5 | Shell | 1,283 | 40 | #!/bin/bash
#SBATCH --job-name=expD-tf
#SBATCH --partition=gpu2
#SBATCH --gres=gpu:1
#SBATCH --mem=32G
#SBATCH --time=08:00:00
#SBATCH --output=/lustre/grp/gglab/liut/logs/expD_%j.out
MODEL=$1
N=$2
SEED=$3
# Activate conda environment (must come before env var overrides)
CONDA_BASE=$(conda info --base 2>/dev/null || ... |
7eeada8430637cbba2a39de3c9e7ea35d562dad6a3ece4bfa8c733e222907830 | Shell | 1,284 | 18 | #!/usr/bin/env bash
# Create the Giotto conda environment named giotto_env
#conda env create -f giotto.yml
# Activate the environment
#conda activate giotto_env
# Install the required R packages
Rscript -e "remotes::install_version('colorRamp2', version = '0.1.0', repos = 'https://cran.r-project.org/')"
Rscript -e "... |
af93db0763ac47c428f8c1b4c42752196ec098190eaec6e0deadb859260e293b | Shell | 1,284 | 40 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_7.out
source activate mlfold
folder_with_pdbs="../PDB_complexes/pdbs/"
output_dir="../PDB_complexes/example_7_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_parsed_chains=$out... |
cad030b74c4406468fc11c05ec4df6e433a2995e3a7c8534a97bd86a0d76460b | Shell | 1,285 | 44 | #!/bin/bash
# Written by Xiuming Zhang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
###########################################
# Usage and Reading in Parameters
###########################################
# Usage
usage() { echo "
Usage: $0 -d <docs> -m <model> -o <outName>... |
f393361b41f026abfa0638d84045df5b84516ab50d48aa1b898c9a0130ece4c4 | Shell | 1,296 | 47 | module load GCC/8.2.0 OpenMPI/3.1.4
module load pandas/0.24.2
# read in the tissue gtex reference files for each parallel process from sourcefile
for line in $(cat $HOME/Code/dbnms.txt )
do
dbd=${line%__x__*}
covd=${line#*__x__}
while read gwasline; do
read -r gwas_path snp_col effect_allele noneffect_allele ... |
fd483d21da1a3dc523560f14fe9167c45f7c3cfbf5259feeab9a135d87b1ae48 | Shell | 1,301 | 28 | #!/bin/bash
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
path_2_data=$1 # <path to data> which contains binarized data for each directions
lang_list=$2 # <path to a f... |
f1e0ccaae7d09657adf5137f4558eb966792bc10b04d16e5592f1bf5b0cd23f5 | Shell | 1,303 | 45 | #!/bin/bash
workdir=/Volumes/public/Backup/horiDir/qst/TauLNM/analysis_PSP_tau/
sigma=1.6986 # FWHM=4 -> sigma=1.6986
cd ${workdir}
for roi_subj in `ls ../PET_SUVR/PSP_tau/`;do
#for roi_subj in s8SUVRwRM_F200_mcPMPBB3_FL_LE_16_036_AP009_1_1;do
for thr in 3.27;do
cd ${workdir}
mkdir -p ./FCmaps_gsp/
cd ./FCmaps... |
f80808b70ce5b5c34befaebd6395b017a660e56a61746e1fb84d4d40dd6b51b5 | Shell | 1,305 | 49 | #!/bin/bash
# Nov 2023 TReNDS
# Regular FreeSurfer processing
# A job array was set up with a size of 100. 190 subjects successfully completed analysis.
# QC was carried out visually.
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --array=0-37
#SBATCH --mem=20g
#SBATCH -p qTRD
#SBATCH -t 1440
#SBATCH -J <PET_... |
eef14c2e20c4590e2da5f375f44e7438d4107068bbe7a97a5bf678588ef32852 | Shell | 1,310 | 51 | #!/bin/bash
# Exp D (192.168.3.17): KNET_rc on Simu16 (random_rand) learning curve
# 5 sample sizes x 3 seeds = 15 runs, 3-parallel
# Run from: Kattn-sim-dev/src/simulation/
# Usage: bash run_expD_192.sh > /tmp/expD_knet.log 2>&1 &
source env_setup.sh
PYTHON=/rd1/liut/miniconda3/envs/kattn-sim/bin/python
MAX_JOBS=3
M... |
c6fa5d0263a1f047e9bad47e903ae6d17a456c82fbeac64a616613dfcece70c7 | Shell | 1,314 | 39 | #!/bin/bash
# Florian Bénitière 16/03/2025
# This script downloads and sets up the necessary resources for running LOFTEE with VEP.
# It creates a dedicated directory for LOFTEE resources, downloads the LOFTEE repository,
# and fetches essential files, including the GERP conservation scores, SQL database,
# and human... |
d87402b6be0e330871201ac5bba59b293ce15a2128ffeaaaf705f6ff9416556e | Shell | 1,329 | 28 | #!/bin/bash
# This simple script creates a list that contains the full paths to example subjects' surf data. Each line represents one subject with different runs.
# Assume the folder structure of CBIG respository is preserved
# Written by CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE... |
19078c6071ac20be25ea028a4cb67b4caa90ff0f86c83378c94f624dbe790520 | Shell | 1,336 | 50 | #!/bin/bash
# Settings
counter=1
dir=$(pwd)
reduce_exe=$dir/pdb_parser_scripts/reduce/reduce_src/reduce
pdb_dir=$1
pdbs=$pdb_dir/raw/*.pdb
n_pdbs=$(echo $pdbs | wc -w)
# Create data directories
mkdir -p $pdb_dir/cleaned
mkdir -p $pdb_dir/parsed
# Clean pdbs
for pdb in $pdbs;
do
python $dir/pdb_parser_scripts/cle... |
f0f21087ad10b237fa873b0eb019bafeb972d525057204745f5b62fd07bb756e | Shell | 1,339 | 33 | # make a temporary environment for profiling only the extension module
cp ../skfmm/base_marcher.cpp .
cp ../skfmm/base_marcher.h .
cp ../skfmm/distance_marcher.cpp .
cp ../skfmm/distance_marcher.h .
cp ../skfmm/heap.cpp .
cp ../skfmm/heap.h .
g++ -O2 base_marcher.cpp distance_marcher.cpp heap.cpp prof.cpp -g -pg -o ... |
d06958233d5060946be7896498d1fe0af6244d4636d8de2562cd22882b8f400c | Shell | 1,347 | 34 | #!/bin/bash
# Verify both script checkers still catch what they were written to catch.
#
# Each control is POSITIVE for its own checker and NEGATIVE for the other, so a
# correct run reports exactly one case per checker, naming the matching file.
# Both checkers exit non-zero when they find something, which here is SUC... |
b8ffbc76c8d257a8068e4d830fe6fba146848cd4d9c8d709230674342a995807 | Shell | 1,351 | 27 |
nnUNetv2_train $1 3d_fullres 0 -tr nnUNetTrainer_5epochs --npz
nnUNetv2_train $1 3d_fullres 1 -tr nnUNetTrainer_5epochs --npz
nnUNetv2_train $1 3d_fullres 2 -tr nnUNetTrainer_5epochs --npz
nnUNetv2_train $1 3d_fullres 3 -tr nnUNetTrainer_5epochs --npz
nnUNetv2_train $1 3d_fullres 4 -tr nnUNetTrainer_5epochs --npz
nn... |
fe93762679796a7b03a40d264b0ee7feeb3f96515934888192a9b30f20fd30b5 | Shell | 1,358 | 26 | #!/bin/sh
# This script generate a "super inflated" surface from very_inflated surface.
# This surface is more inflated than the very_inflated version, which cannot
# show the insula very well. You can load the output files in wb_view.
# See https://www.humanconnectome.org/software/workbench-command/-surface-inflatio... |
229a1ee034756b99a77d23cc401acf7cf63321db8d829e5c5de3a8a5d610a84e | Shell | 1,360 | 44 | #!/bin/bash
CXX=`which g++`
SRC=$1
mkdir -p eigen2/out
if expr match $SRC ".*\/examples\/.*" > /dev/null ; then
# DST=`echo $SRC | sed 's/examples/out/' | sed 's/cpp$/out/'`
DST=`echo $SRC | sed 's/.*\/examples/eigen2\/out/' | sed 's/cpp$/out/'`
INC=`echo $SRC | sed 's/\/doc\/examples\/.*/\//'`
if ! test -e... |
0c3ec7b84ac68b07b7736111443e923a97cd0dd2875c8562d4e472b4ee872547 | Shell | 1,364 | 51 | #!/bin/sh
#
# Script to submit jobs to cluster to perform NBS for comparing RSFC between all ASD & all controls in ABIDE-I
#
# Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
tThresh=$1
id_asd=$2
id_con=$3
sub_info_file=$4
Nperm=$5
output_name=$6
output_dir... |
e6d38276f67f5e306f0bd3941f349f259a7356842e3452893d2d35391f59a851 | Shell | 1,365 | 32 | #!/usr/bin/env bash
# MIT License
#
# Copyright 2025 Broad Institute
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, c... |
b923846de4b1909ef3e2543ac890ea9a8fcaa847963ee56f94bda3a72496f2ab | Shell | 1,372 | 48 | #!/usr/bin/env bash
set -euo pipefail
ROOT="ismb26"
OUT_TABLE="puffin_best_table.tsv"
OUT_APR_AUPR="puffin_best_apr_aupr.tsv"
# Reset outputs
: > "$OUT_TABLE"
echo -e "file\tmetric\tvalue" > "$OUT_APR_AUPR"
# We will write the table header only once (with "file" prepended)
header_written=0
# Process in a stable ord... |
8000d42571de1a52aa60d0aeb4397b9bffa4620683acc8a681ad2a7bc83d54db | Shell | 1,374 | 36 | #!/bin/bash
# Written by Nanbo Sun and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
out_dir=$1
workspace="${CBIG_TESTDATA_DIR}/stable_projects/\
disorder_subtypes/Sun2019_ADJointFactors/step3_PET_preprocess"
# reference directory
ref_dir=${workspace}/results
id_list=${workspac... |
592ca58ca2ee3da7b0ff11e607443e8d6f551b48ad259e574b65a0b66d019304 | Shell | 1,377 | 38 | # Path of the folder containing all data
dir="/root/dir"
tsnr_dir="${dir}/derivatives/tsnr/"
output_csv="${tsnr_dir}/tsnr.csv"
# List of subjects
declare -a sub=("sub-SPAIN01" "sub-SPAIN02" "sub-SPAIN04" "sub-SPAIN06" "sub-SPAIN07" "sub-SPAIN08" "sub-SPAIN11" "sub-SPAIN13" "sub-SPAIN15" "sub-SPAIN16" "sub-SPAIN19" "su... |
151e29c2950c8f47b13217c076a5cfceffadc0a655916468624756fc4dd2e624 | Shell | 1,401 | 49 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test_atac.sh [INPUT_JSON] [GCLOUD_SERVICE_ACCOUNT_SECRET_JSON_FILE] [DOCKER_IMAGE](optional)"
exit 1
fi
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_IMAGE=quay.io/encode-dcc/atac-seq-pipeline:test-v1.1.7
fi
INPUT=$1
GCLOUD_SERVICE_ACC... |
cff4a14c102d661f8d7d5212f2eafe3e113728aae84cad646566b5d7261392fb | Shell | 1,401 | 67 | #!/bin/bash
#SBATCH --job-name=vlpp_{{participant}}
#SBATCH --nodes=1
#SBATCH --mem=0
#SBATCH --time={{walltime}}
#SBATCH --account={{RAPid}}
#SBATCH --output={{logDir}}/%x-%j.out
export VL_QUARANTINE_DIR="/project/ctb-villens/quarantine"
module use ${VL_QUARANTINE_DIR}/modulefiles
module load VilleneuveLab
{% if de... |
7fc8cee9caccb2b1c59c9d32876be0394b0f8226950f58f357086de05fb00c9d | Shell | 1,403 | 31 | #!/bin/bash
# Load Fmriprep (adjust depending on your system/environment)
module load fmriprep
# ==== CONFIGURATION ====
Cohort='Cohort1' # adjust as needed
Timepoint='T1' # adjust as needed
ROOTDIR=/MyWorkingDirectory
# Swarm file to store job commands
SWARMFILE=${ROOTDIR}/slurm/swarm_fmrip... |
eb3abaea6625947ee7fabcd5f3d3b815407c622f6172e832673731d8efc32a36 | Shell | 1,405 | 36 | #!/bin/sh
curr_dir=`pwd`
for folder in */
do
echo "[TEST](start) $folder"
cd $curr_dir
rsync -az $folder $CBIG_CODE_DIR/stable_projects/
git add $CBIG_CODE_DIR/stable_projects/$folder/*
cd $CBIG_CODE_DIR
sh $CBIG_CODE_DIR/hooks/pre-commit
git reset
rm -r $CBIG_CODE_DIR/stable_projects/... |
b260e6f75785dca0ba56118fdb9534d01875e2e7db8ce9f61930e133ad2240f1 | Shell | 1,408 | 51 | #!/bin/usr/env sh
# Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
set -e
s=${1:-en}
t=${2:-es}
echo "Example based on the ${s}->${t} alignment"
if [ ! -d data/ ]; then
mkdir ... |
18b9541cf07526f5b86177950054bf6f1a4b3d3a2829aeb08058691118cac17e | Shell | 1,420 | 47 | #!/usr/bin/env bash
# Exit if anything fails.
set -eux
HERE=$PWD
# Override gcc version to $GCC_VER.
# Put an appropriate symlink at the front of the path.
mkdir -pv $HOME/bin
for g in gcc g++ gcov gcc-ar gcc-nm gcc-ranlib
do
test -x $( type -p ${g}-$GCC_VER )
ln -sv $(type -p ${g}-$GCC_VER) $HOME/bin/${g}
done
... |
ecc90dd1649dd755b0700d8b6f7c891c3dbc6ff93ae3f50e30d5ad33d4c5cd0a | Shell | 1,423 | 48 | #!/usr/bin/env bash
export PYTHONPATH=/home/rowanz/code/fakenewslm
learning_rate=1e-4
init_checkpoint=""
max_seq_length=1024
save_checkpoint_steps=1000
# You can customize the training here
# mega, medium, or base
model_type="base"
OUTPUT_DIR="gs://" # put your output directory here
input_file="gs://" # put your inp... |
917fe29db0fea34fc9cc89230d16ade36d8ed1b7d0bf0b60b407b2e7d54908bc | Shell | 1,425 | 41 | #!/usr/bin/env bash
#
# Copyright (c) 2016-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
myshuf() {
perl -MList::Util=shuffle -e 'print shuffle(<>);' "$@";
}
normalize_text() {
tr '[:up... |
6ef3a707c1b53910a5401a264952357a9b6c7ba25bc8cb607b88e4dea136e08d | Shell | 1,426 | 54 | #!/bin/bash
# TReNDS 12/4/2025 Cyrus Eierud
# Script that works if each subject has its own PET file.
# subject nii-files has to be under a directory called input_sbm,
# and supports that each subject may be in a sub-directory
# (e.g., BIDS standard). All subjects have to have a unique
# file name.
# Note ... |
47503165e4995fbaa5e9a3673edf6d2427ed82f1127c3bc908a35f9c343ae51f | Shell | 1,429 | 44 | #!/bin/bash
source ../scripts/config.py
test -d output || mkdir output
## generate in silico mutagenesis data
if [ -e ./output/insilico_mutation_in_transcripts.pkl ]; then
echo "found insilico_mutation_in_transcripts.pkl, skip"
else
../scripts/insilico_mutagenesis_in_transcripts.py &> ./output/insilico_mutati... |
55fc885167612c205ab358ca67ff4223894214acc627881b72158c1afb8d6c3c | Shell | 1,429 | 50 | set -xe
device_id=7 # which device to run the program, for multi-gpus, set params like device_id=0,2,5,7. [Note that] the device index in python refers to 0,1,2,3 respectively.
# params
data_dir=./data/
data_name=demo
split=simulation
result_dir=./results
seed=1
epochs=1
batch_size=2
accumulation_steps=1
test_batch_... |
9a17c24ca24afee865c653267827ef60f06e4c680f2319404b3e67fc85e5a328 | Shell | 1,440 | 37 | mkdir -p ./data
# Download pfam
while true; do
read -p "Do you wish to download and unzip the pretraining corpus? It is 7.7GB compressed and 19GB uncompressed? [y/n]" yn
case $yn in
[Yy]* ) wget http://s3.amazonaws.com/songlabdata/proteindata/data_pytorch/pfam.tar.gz; tar -xzf pfam.tar.gz -C ./data; rm ... |
d7e4d0e2ebdfd3af58aa544adc38c68408b384208ffce743aab4cd0eaf243ff0 | Shell | 1,444 | 44 | #!/bin/bash
test -d ./output || mkdir ./output
source ../scripts/config.py
model=$SPLICEBERT_510
prefix="finetune_rnafm_on_spliceator"
batch_size=16
for group in "donor" "acceptor"; do
run_name="./output/${prefix}_GS-GS_1_${group}_cv"
test -e ${run_name}.log && continue
./train_rnafm_cv.py \
-lr... |
cee3bddd5e8b7c99c78e1b9f8cf0a880d309ee9990a03dae0e367f3e8114c484 | Shell | 1,445 | 52 | #!/bin/bash
split="dev_other"
ref_data=""
get_best_wer=true
dec_name="decode"
graph_name="graph"
. ./cmd.sh
. ./path.sh
. parse_options.sh
exp_root=$1
set -eu
echo "==== WER w.r.t. pseudo transcript"
for x in $exp_root/*/${dec_name}_${split}*; do grep WER $x/wer_* 2>/dev/null | utils/best_wer.sh; done
if [ ! -z ... |
01a8438b3c06bdd9bb78e9483d3d959f5d75ca6f4d3ccc97a039cad4d495e1fa | Shell | 1,452 | 67 | #!/bin/bash
#PBS -l nodes=1:ppn=32:hw
#PBS -l walltime={{walltime}}
#PBS -A {{RAPid}}
#PBS -o {{logDir}}
#PBS -e {{logDir}}
#PBS -N vlpp_{{participant}}
source /software/soft.computecanada.ca.sh
export VL_QUARANTINE_DIR="/sf1/project/yai-974-aa/quarantine"
module use ${VL_QUARANTINE_DIR}/modulefiles
module load Ville... |
ad7e411fe1df146971fe6917197a167febb675828e67f9daf1b64676fb015185 | Shell | 1,452 | 55 | #!/bin/sh
#
# Script to submit jobs to cluster to perform NBS for comparing RSFC between ASD & controls in subgroups
#
# Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
tThresh=$1
id_asd_subgrp=$2
id_con_subgrp=$3
id_asd=$4
id_con=$5
sub_info_file=$6
Nperm=$... |
3920ea4260a864e1f44ba4c98d74db218f3acf67c5c995c0f26c10cbfbb3d63b | Shell | 1,454 | 50 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test_atac.sh [INPUT_JSON] [GCLOUD_SERVICE_ACCOUNT_SECRET_JSON_FILE] [DOCKER_IMAGE](optional)"
exit 1
fi
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_IMAGE=quay.io/encode-dcc/atac-seq-pipeline:test-v1.4.2
fi
INPUT=$1
GCLOUD_SERVICE_ACC... |
c10cfdcc98a486eb46c3456e8fc0108236096443bc4420f0a4cebe971de7f31f | Shell | 1,454 | 32 | #!/bin/bash
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
path_2_data=$1 # <path to data> which contains binarized data for each directions
lang_list=$2 # <path to a f... |
c8ef81e86cfcbc04f8c1f4ffce711da4031ccb7c028d3ad6e7d585c2bb470ba8 | Shell | 1,472 | 53 | #!/bin/bash
# run_expC_markov_nomask2.sh
#
# Exp C 补充：Markov 任务 P2P约束✅ + mask❌ 条件（完成2x2消融）
# KNET_nomask = 有 groups (P2P约束) + 无 band mask
#
# 在 192.168.3.17 上运行：
# cd /rd1/liut/K-attention/K-attention/Kattn-sim-dev/src/simulation
# bash run_expC_markov_nomask2.sh
set -e
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
... |
f871d0e5144e67888e175e8ac957dadbf0775c3f9d83bc0fdb22c0ba8a2e9469 | Shell | 1,473 | 55 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test.sh [WDL] [INPUT_JSON] [DOCKER_IMAGE](optional) [NUM_TASK](optional)"
echo "Make sure to have cromwell-31.jar in your \$PATH as an executable (chmod +x)."
exit 1
fi
WDL=$1
INPUT=$2
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_I... |
e3bfabf01e907057ebddad427f2fe51922db3b172f49ea228a8d923997a2b331 | Shell | 1,481 | 56 | #!/bin/bash
workdir=/Volumes/public/Backup/horiDir/qst/TauLNM/PET_SUVR/
roidir=/Volumes/public/Backup/horiDir/qst/TauLNM/ROI/ROI/
outcsv=${workdir}/tau_binary_matrix.csv
cd ${workdir}
# --- subject 一覧（自動取得） ---
subjects=($(ls ${workdir}/PSP_tau/))
# subjects=("s8SUVRwRM_F200_mcPMPBB3_FL_LE_16_036_AP009_1_1") # テスト用... |
549099b95fb7715793d6c9d011ffae32531f9affbf8887606e7550705843610d | Shell | 1,482 | 46 | #!/bin/bash
test -d ./output || mkdir ./output
source ../scripts/config.py
model=$SPLICEBERT_510
prefix="finetune_splicebert_on_spliceator"
batch_size=16
for group in "donor" "acceptor"; do
run_name="./output/${prefix}_GS-GS_1_${group}_cv"
test -e ${run_name}.log && continue
./train_splicebert_cv.py \
... |
f0b90892c200b9288bc7be07030e40e7ff5906ce0dc4b6b4fc859edf05cebe0e | Shell | 1,482 | 43 | #!/bin/bash
set -eu
w2v_dir= # contains features `{train,valid}.{npy,lengths}`, real transcripts `{train,valid}.${label}`, and dict `dict.${label}.txt`
lab_dir= # contains pseudo labels `{train,valid}.txt`
out_dir= # output root
arpa_lm= # phone LM
arpa_lm_bin= # (binary) phone LM for KenLM, used in unsupervised... |
0435559303d5acaafe7f8859658ff72d075925ae5b3aad1cd56bc14612f0acdc | Shell | 1,484 | 33 | mkdir -p ./data
# Download pfam
while true; do
read -p "Do you wish to download and unzip the pretraining corpus? It is 7.7GB compressed and 19GB uncompressed. [y/n]" yn
case $yn in
[Yy]* ) aws s3 cp s3://songlabdata/proteindata/data_pytorch/pfam.tar.gz .; tar -xzf pfam.tar.gz -C ./data; rm pfam.tar.gz;... |
6b24afa2af622617c5315b68af855101dab3617396cbfe276f0f993b2fff2804 | Shell | 1,487 | 57 | #!/bin/bash
# Copyright (c) Facebook, 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 -eu
train_json=$1
valid_json=$2
test_json=$3
n_units=$4
hop_size=$5
sr=$6
f0_quantizer=$7
out_dir=$8
meta_path="$out_dir/data... |
ccf0df032080b45e2def73c7a1d92396d4bbc5c6c340ded8ef14dbbf8c185962 | Shell | 1,490 | 44 | #!/usr/bin/env bash
# This hook is used to block commits if they include staged files inside a directory
# which also contains a subdirectory called `pipeline_info`. The purpose of this is to
# prevent users from inadvertently committing output from pipeline test runs inside the
# development directory.
set -e
status... |
e2de3f555d505c49fc1603e81a29bb344152b5cdcd9ea2b84d55a993614297a8 | Shell | 1,494 | 56 | #!/bin/bash
workdir=/Volumes/public/Backup/horiDir/qst/TauLNM/PET_SUVR/
roidir=/Volumes/public/Backup/horiDir/qst/TauLNM/ROI/ROI/
outcsv=${workdir}/atrophy_binary_matrix.csv
cd ${workdir}
# --- subject 一覧（自動取得） ---
subjects=($(ls ${workdir}/PSP_GMandWM/))
# subjects=("s8SUVRwRM_F200_mcPMPBB3_FL_LE_16_036_AP009_1_1")... |
734f27c83924bfeb6e28ae6769cfc81eff10673c5b534044781c3bf18e593c87 | Shell | 1,500 | 35 | dir="/root/dir"
declare -a data=("sub-SPAIN01_ses-B_task-squeeze_run-2_bold.nii.gz"
"sub-SPAIN02_ses-A_task-squeeze_run-1_bold.nii.gz"
"sub-SPAIN02_ses-A_task-squeeze_run-2_bold.nii.gz"
"sub-SPAIN02_ses-B_task-squeeze_run-1_bold.nii.gz"
"sub-SPAIN02_ses-B_task-squeeze_run-2_bold.nii.gz"
"sub-SPAIN04_ses-A_task-squeeze... |
92b50d7d9c58944b69fe47ede57fed8b63cfdfc40e6f15109f518e12a33cf222 | Shell | 1,501 | 52 | export KMER=3
export MODEL_PATH=<PATH_TO_YOUR_MODEL>
export ORIGINAL_SEQ_PATH=<PATH_TO_YOUR_ORIGINAL_SEQUENCE_FILE>
export MUTATE_SEQ_PATH=<PATH_TO_YOUR_MUTATED_SEQUENCE_FILE>
export PREDICTION_PATH=<PATH_TO_STORE_PREDICTION>
export WT_SEQ=<THE_SEQUENCE_USED_FOR_MUTATION>
export OUTPUT_PATH=<PATH_TO_YOUR_OUTPUT_DIRECTO... |
4bbb2e47a29255bc4c2bc2edada5022518c17b295aa7ba280bcbabd643487d77 | Shell | 1,503 | 55 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test_atac.sh [INPUT_JSON] [GCLOUD_SERVICE_ACCOUNT_SECRET_JSON_FILE] [DOCKER_IMAGE](optional)"
exit 1
fi
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_IMAGE="conda"
fi
INPUT=$1
GCLOUD_SERVICE_ACCOUNT_SECRET_JSON_FILE=$2
PREFIX=$(basenam... |
5e51bdc1e66707844098a3b4e7524e6741225c2bd75af65da3c1447cf73ecb17 | Shell | 1,505 | 37 | #!/bin/bash
test -d output || mkdir -p output
SPLICEBERT_510="../../models/SpliceBERT.510nt/"
./finetune_for_bp_prediction.py \
-m $SPLICEBERT_510 \
-o ./output/train_mercer_bp &> ./output/train_mercer_bp.log
cat ./output/train_mercer_bp/fold*/test_results.txt > ./output/train_mercer_bp.all_prediction.txt #... |
8a289cdc77e662cc7f89888a898cf100572643654346d8a2e712e06c140d66aa | Shell | 1,507 | 37 | #!/bin/bash
# This script sets up project-specific environment variables.
# It should be sourced, not executed directly (e.g., '. ./set_env.sh').
# Get the absolute path to the directory containing this script.
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
# Define the paths relative to... |
400382afde7a9ce6b2312a4d3ba9f6f751e5905912147f6ed764ef499f8b2b03 | Shell | 1,512 | 45 | # created by DebarpanB
# date 25th August, 2022
stage=0
annotationdir='annotations/LABELS/'
#audiodir='/data1/srikanthr/Coswara/data_preparation/Coswara-Data-Extracted'
pathfile='path_files/wav.scp'
audiocategory=$1
datadir_name='data'
datadir=$datadir_name/$audiocategory
feature_dir_name='feats'
feature_dir=$featur... |
6de70726137f28937518988c6d26c8e873efe97e5eea674e40c7700e9c1f4867 | Shell | 1,512 | 42 | #!/bin/bash
# Florian Bénitière 16/03/2025
# This script downloads and sets up the necessary resources for running SpliceAI with VEP.
# It creates a directory for SpliceAI resources, downloads the BaseSpace CLI from Illumina,
# and fetches SpliceAI VCF files for both GRCh38 genome assembly (command lines commented for... |
51feaac4d8a1e0e31afbbc1b31bb1a1ba8cf2059980290d2d2a217314b1b7287 | Shell | 1,516 | 46 | #!/bin/bash
#
# CBIG_check_whether_function_used_in_other_functions_wrapper.sh $file_path "silent"
# Wrapper function to search for all instances of a function name
# inside a predefined set of directories
# Input can be the function name, a file name, or full path of a file
file_name=$(basename "$1")
verbose=$2
#... |
26393cac04f1db238c380e8b877152e557cb62a8122c4577e3a2eb21a3cb7d71 | Shell | 1,520 | 55 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test.sh [WDL] [INPUT_JSON] [DOCKER_IMAGE](optional) [NUM_TASK](optional)"
echo "Make sure to have cromwell-31.jar in your \$PATH as an executable (chmod +x)."
exit 1
fi
WDL=$1
INPUT=$2
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_I... |
46be180c71a2205b6562ef8a4e8fabd51afb02f8bb2fb876de21af587e247b5c | Shell | 1,520 | 55 | #!/bin/bash
set -e # exit on error
if [ $# -lt 2 ]; then
echo "Usage: ./test.sh [WDL] [INPUT_JSON] [DOCKER_IMAGE](optional) [NUM_TASK](optional)"
echo "Make sure to have cromwell-31.jar in your \$PATH as an executable (chmod +x)."
exit 1
fi
WDL=$1
INPUT=$2
if [ $# -gt 2 ]; then
DOCKER_IMAGE=$3
else
DOCKER_I... |
85bbac99a5ec5878e1f32f8b7fbd5be96e164edce530fc686d7a81dadfaff8ad | Shell | 1,537 | 39 | #!/bin/bash
#SBATCH -p gpu
#SBATCH --mem=32g
#SBATCH --gres=gpu:rtx2080:1
#SBATCH -c 3
#SBATCH --output=example_4.out
source activate mlfold
folder_with_pdbs="../PDB_complexes/pdbs/"
output_dir="../PDB_complexes/example_4_outputs"
if [ ! -d $output_dir ]
then
mkdir -p $output_dir
fi
path_for_parsed_chains=$out... |
23f4c62372566c428cb0242e95198433c38b07ef890e5b2b1dc204939d11212a | Shell | 1,559 | 50 | #!/bin/bash
# Written by Xiuming Zhang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
###########################################
# Usage and Reading in Parameters
###########################################
# Usage
usage() { echo "
Usage: $0 -g <GMToStdTmpList> -o <outDir>
... |
8c0e43754b51e7a0026ac931d51eaaac6c531a602691f570d800fb2d15ea2852 | Shell | 1,560 | 63 | #!/usr/bin/env bash
set -euo pipefail
BASE_DIR="ismb26/models"
OUT_DIR="ismb26/results/func_eval"
mkdir -p "$OUT_DIR"
# Same split files as clustering (edit if needed)
TRAIN_FILE="data/GeneOntology/nrPDB-GO_train.txt"
VAL_FILE="data/GeneOntology/nrPDB-GO_val.txt"
TEST_FILE="data/GeneOntology/nrPDB-GO_test.txt"
# GPU... |
a2d8bf8f1e94d833813ce41eb415d424a7cef0e32f9801de561794faa54d3b86 | Shell | 1,561 | 54 | #!/bin/bash
#SBATCH --job-name=crispr_cnn_tf
#SBATCH --gres=gpu:1
#SBATCH --mem=16G
#SBATCH --time=02:00:00
# NOTE: --output is set dynamically by submit_crispr_cnn_tf.sh
# Positional args: DS MODEL SET VERSION
DS=$1
MODEL=$2
SET=$3
VERSION=${4:-0}
CODE_BASE=/lustre/grp/gglab/liut/K-attention/K-attention/Kattn-sim-de... |
e5e851623f14a5925d2e6c1ad2918ae74a6c4ab6533caef59f6265536c2081b4 | Shell | 1,561 | 48 | #!/bin/sh
# Wrapper script to infer factor compositions of new participants with polarLDA model
# Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
###################
# Input variables
###################
corpusDir=$1 # document corpus
modelDir=$2 # learned... |
5b538d887172ace9bad8faa99deaf9e4e96fe034dd62610e7b37c1b854d4d69a | Shell | 1,563 | 57 | #!/bin/usr/env sh
# Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
set -e
# Set this variable to the crawl you want to process.
WET_PATHS_URL="https://commoncrawl.s3.amazona... |
fd18e75b55cf01a07bd2b89d47332a64436abdf6c23c936139d7e939a6c8b7d3 | Shell | 1,564 | 68 | #!/usr/bin/env zsh
# Copyright (c) Facebook, 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.
source_dir=$1
tgt_dir=$2
model=$3
if [ -z "$4" ]
then
dim=64
else
dim=$4
fi
echo "using $dim clusters for aux... |
64b9a8eedaed778a8f4526aadf001d6aa27a825693c7a9d3869ecfc6ec0e5517 | Shell | 1,569 | 54 | #!/bin/bash
# Define directories
input_dir="data/SFARI_data" # Directory containing FASTQ files
genome_dir="${GENOMIC_DATA_DIR}/GENCODE/STAR_index_v47" # STAR genome index directory
output_dir="STAR_results" # Output directory for STAR results
sbatch_dir="scripts/STAR_scripts" # Directory to store generated sbatch... |
c1520491165607fc29240995f727bce445fa5fc0aab60f150caf42a8b51cf8a4 | Shell | 1,573 | 40 | myshuf() {
perl -MList::Util=shuffle -e 'print shuffle(<>);' "$@";
}
normalize_text() {
tr '[:upper:]' '[:lower:]' | sed -e 's/^/__label__/g' | \
sed -e "s/'/ ' /g" -e 's/"//g' -e 's/\./ \. /g' -e 's/<br \/>/ /g' \
-e 's/,/ , /g' -e 's/(/ ( /g' -e 's/)/ ) /g' -e 's/\!/ \! /g' \
-e 's/\?/ \? /g'... |
0f76605744f84503aee057cc04bc6b9b30c5aa270c1906604d763119420d50a2 | Shell | 1,577 | 33 | #!/bin/bash
# Example usage of simulate-for-posterior.py for different models
# Example 1: VariablePopulationSize model (21 epochs)
# Parameters: log10(N1), log10(N2), log10(N3), ..., log10(N21), recomb_rate
echo -e "\nSimulating VariablePopulationSize model (21 epochs)..."
python simulate-for-posterior.py \
--mod... |
6723075f51f0a305d2e9f1e280415faf8850b10a38a9c744e936b0b8551beb83 | Shell | 1,579 | 45 | # created by DebarpanB
# date 25th August, 2022
stage=0
annotationdir='annotations/LABELS/'
#audiodir='/data1/srikanthr/Coswara/data_preparation/Coswara-Data-Extracted'
pathfile='path_files/wav.scp'
audiocategory=$1
datadir_name='data'
datadir=$datadir_name/$audiocategory
feature_dir_name='feats'
feature_dir=$featur... |
aa29ba51be323c700e451631bf1046bf2d6cee7499dd70edbb7b333fef6f5153 | Shell | 1,579 | 49 | #!/usr/bin/env bash
#
# copyright (c) 2017-present, facebook, inc.
# all rights reserved.
#
# this source code is licensed under the MIT license found in the
# license file in the root directory of this source tree.
#
# script for WN11
DIR=data/wordnet-mlj12/
FASTTEXTDIR=../../
# compile
pushd $FASTTEXTDIR
make opt
p... |
5e07b67772656b0f7ce5b31066bcd1b42d5f1c3f94040ce91c8ba9e95ed2a24f | Shell | 1,585 | 49 | #!/bin/bash
# Download and prepare all reference resources required for variant annotation
set -e # Exit immediately if a command exits with a non-zero status
set -o pipefail # Properly propagate errors through pipelines
# ============================
# Check dependencies
# ============================
if ! comma... |
74fc5807ac50a794aed4fe95b01f9123fba164a23a15fbf7822da6437133fff5 | Shell | 1,592 | 46 | #!/bin/bash
# prepare word WFSTs, reference data, and decode
set -eu
w2v_dir= # same as in train.sh
out_dir= # same as in train.sh
lexicon= # word to phone mapping
wrd_arpa_lm= # word LM
wrd_arpa_lm_bin= # word LM for KenLM, used in unsupervised selection
dec_exp= # what HMM stage to decode (e.g., tri3b)
dec_... |
a7b7c4bd3cea0ed5b750f29f79876af256ba3975c7b545b7dfe808b94e0b161c | Shell | 1,599 | 53 | #!/bin/bash
dataset=$1
fold=$2
trainer=$3
# Get the original current directory
ORIGINAL_DIR=$(pwd)
# Get the directory of the script
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
# Change to the script's directory so we can use ralative paths
cd "$DIR"
# Install the required library
pip3 install --no-use... |
790cdb6a330be430756def04dd0e4f60089a8c47998cb3373d54a3ea97d2159d | Shell | 1,601 | 53 | #!/bin/bash
# Phase 2: RBP 全量 CNN-TF 参数匹配版批量实验
# 172 RBPs × cnn_transformer_pm × 3 seeds × adamw (~130 GPU-hours)
# 已完成的 run 自动跳过（基于 Report_*.pkl 存在判断）
BASE=/rd1/liut/K-attention/K-attention
HDF5_ROOT=$BASE/Kattention_aten_test/external/RBP/HDF5
SCRIPT_DIR=$BASE/Kattention_aten_test/scripts/RBP
RESULT_ROOT=$BASE/Katte... |
2870186993dfd5956a3f6e75e9086cc63d5763479444748d966c960b081f9ffb | Shell | 1,602 | 52 | ### =========================================================================
### SGE variables
### -------------------------------------------------------------------------
###
#$ -l mem_free=8G,h_vmem=10G
#$ -l bluejay
#$ -m n
#$ -l h_fsize=500G
#$ -o ./logs/
#$ -e ./logs/
#$ -pe local 2
#$ -cwd
#$ -t 1-68
### ===... |
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