sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
71e4f87aff7a40ac52336fe4ff848649ad11ee37744a33eaa2d970caa53ec73c | Shell | 1,196 | 40 | #!/bin/bash
curr_dir=`pwd`
sample=abcd # abcd, ahrb or mls
task=MID
ses=2YearFollowUpYArm1
type=session # run or session
run=1 # 1 or 2, not used here
subj_list=${1}
a_mod="mod-Saturated" # mod-Saturated mod-CueYesDeriv mod-CueNoDeriv
b_mod="mod-CueYesDeriv" # same above
inpfold=/scratch.global/${USER}/mid_rt_mod/firs... |
6f7b8dcc17875043197a09d3de3e8b127e00e92e20e8abe420502c84e1f638ef | Shell | 1,197 | 40 | #!/bin/bash
curr_dir=`pwd`
sample=abcd # abcd, ahrb or mls
task=MID
ses=2YearFollowUpYArm1
type=session # run or session
run=1 # 1 or 2, not used here
subj_list=${1}
a_mod="mod-Saturated" # mod-Saturated mod-CueYesDeriv mod-CueNoDeriv
b_mod="mod-CueYesDeriv" # same above
inpfold=/scratch.global/${USER}/mid_rt_mod/firs... |
dac6511be42bb5caa7dcea9f4e11ab39bd1d04bad47b4b24c55c5efbe73736b5 | Shell | 1,200 | 37 | torchrun --rdzv-backend=c10d --rdzv-endpoint=localhost:0 repl/scripts/greedy.py \
--dataset animals \
--spritevid_max_sprites 8 \
--spritevid_noise_type gaussian \
--spritevid_noise_level 0.1 \
--sprite_noise_on_top \
--seq_len 32 \
--num_sequences 16000 \
--n_areas 6 \
--area_encode... |
fcc985ab88124090544453896483912fd0e40888a56d866eaa03b03f5d716483 | Shell | 1,207 | 23 | #!/bin/bash
set -euo pipefail
export ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=${THREADS_PER_COMMAND:-$(nproc)}
movingfile=$1
fixedfile=$2
outputdir=$3
shift 3
fixedmask=$(dirname ${fixedfile})/$(basename ${fixedfile} _t1.nii.gz)_mask.nii.gz
movingmask=$(dirname $movingfile)/$(basename $movingfile _t1.nii.gz)_mask.nii.gz... |
a1936089e52131f7851f87c3504fb2fcf7ad3c6a5051c16e66b006b5452bee3b | Shell | 1,212 | 32 | #!/bin/bash
#-----------------------------------------------
# Filter: unique Tn5 site
#-----------------------------------------------
# Filter out variants with multiple Tn5 sites (under the same barcode pair)
SAMPLE_ID=$1
SAMPLE_DIR=$2
OUTPUT_SUFFIX=filtered_tn5
# Filter ds calls
# extract variants with a unique ... |
d11bcb658757b4bce34686ace7e7c2ed06b913edb07f9b3ca6d410946f8c4c4d | Shell | 1,216 | 35 | #!/bin/bash
CROMWELL_NAME="fg-cromwell_fresh"
CROMWELL_ID=$1
OUT_PATH=$2
echo $CROMWELL_ID $OUT_PATH
mkdir -p $OUT_PATH/release/data/
mkdir -p $OUT_PATH/release/documentation/
mkdir -p $OUT_PATH/munged_rsid/
# SCORES & LOGS
echo "LOGS"
wc -l < <(gsutil ls gs://$CROMWELL_NAME/prs_cs/$CROMWELL_ID/call-scores/**/fin... |
37ad04d3f699f3ae740a509f2d6b41259647f37533637b6bba20e6ec83720f8e | Shell | 1,224 | 41 | #!/bin/bash
# transforms the Wang template to individual subject surface space
set -x -u -e
echo "$0" "$@" # print function call
subject_label=$1
path_derivatives=$2
path_anat_data=$3
path_func_data=$4
path_output_data=$5
path_HCPtemplates_standardmeshatlases=${6}
path_fsaverage=${7}
path_newmsm=${8}
path_wbcommand=${... |
89cd7d1e6958f927303709148f3983f3c56c60dcd89d839a1a3e5e3d7c0ae64b | Shell | 1,227 | 22 | #!/bin/bash -ef
set -x
# Bootstrap uv and use it for all installs: its resolver and hardlink-based
# installs are dramatically faster than pip, and the venv is recreated each run
# so this "Get Python running" step reinstalls everything every time. uv's
# download cache lives in ~/.cache/uv (cached separately in the C... |
052cd901bf4bb5aa625de195676de493b718fd94d88b54c30782e5f5bfc6198e | Shell | 1,230 | 38 | #!/bin/bash
set -ev
# 01. Set up environment
exec_dir=$( pwd )
cd "${exec_dir}"
sud_dea_dir="${exec_dir}/scripts"
# 02. Set up config files
# 02a. Specify config file path
cfg="${exec_dir}/configs/config_run_DESeq2_example_SUD_DEA.yaml"
echo "${cfg}"
# 02b. Add root directory to config file if not specified
if ! $( ... |
0289df228ed2c6d9532bbed81aff610ce7da77ace26a86156ea0599f7a15b567 | Shell | 1,231 | 38 | #!/bin/bash
# PreToolUse Hook - Bash Safety Check
# Prevents dangerous commands and provides helpful reminders
set -e
TOOL_NAME="$1"
COMMAND="$2"
# Only run for Bash tool
if [[ "$TOOL_NAME" != "Bash" ]]; then
exit 0
fi
# Check for potentially dangerous commands
if [[ "$COMMAND" == *"rm -rf outputs"* ]] || [[ "$... |
46b484a9507335684c29bd08851139976be976e02e81e707f56ed715e4418ae0 | Shell | 1,236 | 42 | #!/usr/bin/env sh
#
# Flattens a downloaded RODA database into the format expected by OpenFold
# Args:
# roda_dir:
# The path to the database you want to flatten. E.g. "roda/pdb"
# or "roda/uniclust30". Note that, to save space, this script
# will empty this directory.
# output_d... |
6a80a166c22f426c494f6c30aabf71ff2b8243c672815e0f39339efb6e086d4a | Shell | 1,237 | 28 | wget https://cqsweb.app.vumc.org/download1/annotateGenome/TIGER/20220406_spcount.tar.gz
tar -xzvf 20220406_spcount.tar.gz
wget https://cqsweb.app.vumc.org/download1/annotateGenome/TIGER/TIGER.v202211.tar.gz
tar -xzvf TIGER.v202211.tar.gz
wget https://cqsweb.app.vumc.org/download1/annotateGenome/TIGER/20170206_Group1.... |
09d09985c42035aa06ab38f0d3bff21d2b28bbfd11f12ee4c53b24c1268f74f9 | Shell | 1,239 | 37 | #! /bin/bash
set -e
TARGET_DIR="$(pwd)"
REPO_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && cd .. >/dev/null 2>&1 && pwd )"
BUILD_DIR="$(mktemp -d)"
cleanup () {
rm -rf "$BUILD_DIR"
}
trap 'cleanup' EXIT
cd "$BUILD_DIR"
echo "Building AppImage in $(pwd)"
cmake -DCMAKE_BUILD_TYPE=Release -DCMA... |
082e8f30ddf8fe975c1813a9a192a09304da1d752dc809696df974b949eec0ac | Shell | 1,240 | 34 | #!/bin/bash
dx login --token TOKEN
subset_num1=$1
subset_num2=$2
my_cmd="wget https://www.kingrelatedness.com/Linux-king.tar.gz && \
tar -xzvf Linux-king.tar.gz && \
./king -b subset${subset_num1}.bed,subset${subset_num2}.bed \
--kinship --proj 93967 --degree 3 --cpus 90 --prefix subset${su... |
6235ee971b69d6aaa0a34db16f2085abe935566059f62b2433859fc3751967e7 | Shell | 1,243 | 41 | #!/bin/sh
# Copyright (C) 2009-2022, Ecole Polytechnique Federale de Lausanne (EPFL) and
# Hospital Center and University of Lausanne (UNIL-CHUV), Switzerland, and CMP3 contributors
# All rights reserved.
#
# This software is distributed under the open-source license Modified BSD.
# Build the docker image of Connectom... |
624cd10d5840f8d7b8902a66e010d7de89188e0dbc0a7bceae8f932e41e91f23 | Shell | 1,245 | 33 | #!/bin/sh
# simple script to call chexpert labeler on many files
REPORT_PATH=$1
CHEXPERT_PATH=$2
if [ -z "$REPORT_PATH" ]
then
echo "You must call this script as: ./run_chexpert_on_files.sh FOLDER_WITH_DATA_CSVS CHEXPERT_GIT_PATH"
exit 1
else
echo "Source of data: $REPORT_PATH"
fi
if [ -z "$CHEXPERT_PATH... |
48bab0ebd4dd76de56cbc971f897fac5da5043b6633d9084a778026781a4c2c1 | Shell | 1,248 | 42 | #!/bin/bash
#
# Collects the pull-requests since the latest release and
# aranges them in the CHANGES.rst.txt file.
#
# This is a script to be run before releasing a new version.
#
# Usage /bin/bash update_changes.sh 1.0.1
#
# Setting # $ help set
set -u # Treat unset variables as an error when substituti... |
19273277aedfecd21d4aa580a41bddd2ef7fddd0ca62e224b8c2b13fd9820720 | Shell | 1,251 | 36 | #!/bin/bash
# Resample ccf results from fsLR space to fsaverage space
set -u -x -e
sub=$1
path_anat_data=$2
path_output_dir=$3
path_HCPtemplates_standardmeshatlases=$4
path_fsaverage=$5
path_wbcommand=$6
threshold="00"
for hemi in L R; do
sphere_native="/data/p_02915/templates/fs_LR_32-master/fs_LR.32k.${hemi}... |
9837c4afa90b2fee1c34463b3d25046535952e03dcad6ba60eff563b6809e477 | Shell | 1,258 | 53 | #!/bin/bash
# Siwei 30 Jun 2021
# use conda env aligners
# make sure R has been installed
# flow
# convert each bam (bamCoverage) bigwig
# bigwig (ComputeMatrix reference-point) .gz (for plotHeatmap)
# .gz (plotHeatmap) output/pdf
for eachfile in *.bam
do
echo $eachfile
## convert bam to bigwig
bamCoverage \
... |
a3c6d6600e49dc175a597901b6a3b6191dfe0455dba980bbcfefe275d0161938 | Shell | 1,259 | 22 | #!/bin/bash
# 4 fingers
./venv/bin/python ./LFCNNm_decoder.py -cmb "RI" "RM" "LI" "LM" --prefix LFCNN --model lfcnn
./venv/bin/python ./LFCNNm_decoder.py -cmb "RI" "RM" "LI" "LM" --prefix EEGNet --model eegnet
./venv/bin/python ./LFCNNm_decoder.py -cmb "RI" "RM" "LI" "LM" --prefix FBCSP_ShallowNet --model fbcsp
./venv... |
b8de318db5b8900db1cc5731d8a56c06c3af5146c90c6201ed209f07bfe40ce8 | Shell | 1,260 | 31 | cd E:\R\diagnose_torch_models\pytorch\grid_search_b1
conda activate torch2.1.2_M40_cu12.1
python E:\R\diagnose_torch_models\pytorch\train_b1.py
cd E:\R\diagnose_torch_models\pytorch\grid_search_b2
conda activate torch2.1.2_M40_cu12.1
python E:\R\diagnose_torch_models\pytorch\train_b2.py
cd E:\R\diagnose_torch_models\... |
f62a41e7591190f2640566e9aca358c045d3b0dd5cfa192f4c17948b9dcbe05c | Shell | 1,264 | 38 | #!/bin/bash
#
# Copyright 2021 AlQuraishi Laboratory
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... |
6338ce43444e58d2f451663a4e782fc34a2e040f6038b936f2debf1ac3041396 | Shell | 1,266 | 43 | #!/bin/bash
# This script performs skull-stripping i.e. removes extra-brain tissues
#
# -----------------------------------------------------------
# Script written by Ludovico Coletta
# NILAB, FBK (2022)
# -----------------------------------------------------------
######## main code starts here
export FREESURFER... |
e66a96618da82a0c270d69f6adadb9204fc9782d475a8ac3ffc63406df31aa4b | Shell | 1,267 | 35 | #!/bin/bash
# STAR v2.7.9a
# Cell Ranger Reference, 2020-A
# Mouse reference, mm10 (GENCODE vM23/Ensembl 98)
# Input: single-cell RNA-seq data generated using 10x Genomics Chromium Next GEM Single-Cell 3’ Reagent Kits for v2 chemistry
# Generate genome indices
STAR --runThreadN 6 \
--runMode genomeGenerate \
--genome... |
a1639eb7ecdd16a98a1f40b63d7acf3a1b13b8cc35725c6f5a572f359fa08740 | Shell | 1,269 | 31 | #!/bin/bash
if [ -z "$GAZEBO_MODEL_PATH" ]; then
bash -c 'echo "export GAZEBO_MODEL_PATH=$GAZEBO_MODEL_PATH:"`pwd`/../assets/models >> ~/.bashrc'
else
bash -c 'sed "s,GAZEBO_MODEL_PATH=[^;]*,'GAZEBO_MODEL_PATH=`pwd`/../assets/models'," -i ~/.bashrc'
fi
# add modular scara environment variables
if [ -z "$GYM_GAZEB... |
7476bfb6ce55bcc6999505ddb4f591d82fcbf12babf51be2dc69c12cd28e6820 | Shell | 1,271 | 46 | #!/bin/bash
#$ -cwd
#$ -l bluejay,mem_free=2G,h_vmem=2G,h_fsize=400G
#$ -N move_bulk_round1
#$ -o logs/move_bulk_round1.$TASK_ID.txt
#$ -e logs/move_bulk_round1.$TASK_ID.txt
#$ -m e
#$ -t 1-2
#$ -tc 2
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job ... |
7546cccda464bf7170f6e15d4d9c96c9b3eb978517c4f2e75700185c43af1f61 | Shell | 1,271 | 46 | #!/bin/bash
#$ -cwd
#$ -l bluejay,mem_free=2G,h_vmem=2G,h_fsize=400G
#$ -N move_bulk_round2
#$ -o logs/move_bulk_round2.$TASK_ID.txt
#$ -e logs/move_bulk_round2.$TASK_ID.txt
#$ -m e
#$ -t 1-2
#$ -tc 2
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo "Job ... |
bb1b815a238bf4e98712cf35c60eaa4e585072b24762561c1560300cfa76d973 | Shell | 1,274 | 46 | #!/bin/bash
#Submit to the cluster, give it a unique name
#$ -S /bin/bash
#$ -cwd
#$ -V
#$ -l h_vmem=1.9G,h_rt=20:00:00,tmem=1.9G
#$ -pe smp 2
# join stdout and stderr output
#$ -j y
#$ -R y
if [[ ( $@ == "--help") || $@ == "-h" ]]; then
echo "Usage: source submit.sh SMK_NAME RUN_NAME"
echo "SMK_NAME - Nam... |
40c1431ea55fd2ceee792234f9acf600fa36d9349aa856bdc59f9f033d676ae6 | Shell | 1,277 | 64 | #!/bin/bash
# Siwei 11 Aug 2023
# revised, first down-sample every sample to 20M to ensure all samples have the same weight
# Siwei 04 Jul 2023
# merge and downsample rs1532278 het bams to 100M reads for peak plotting
cell_type="NGN2"
temp_folder="/home/zhangs3/NVME/package_temp/downsample_100M_"$cell_type
ref_fast... |
e4f51043fcbdd4d2d6c3c959a59f1ff872cd039aede45689ac6e023abdb07fb5 | Shell | 1,277 | 14 | export FILES="EURqc_chr8_chunk125_plink_100K EURqc_chr8_chunk5_plink_100K EURqc_chr15_chunk86_plink_100K EURqc_chr9_chunk68_plink_100K EURqc_chr8_chunk217_plink_100K EURqc_chr2_chunk136_plink_100K EURqc_chr2_chunk15_plink_100K EURqc_chr2_chunk14_plink_100K EURqc_chr1_chunk20_plink_100K EURqc_chr8_chunk126_plink_100K EU... |
5b094301c81cdf34652f17d7967581f982b03820d1dfb21f3011c0260c85ed7d | Shell | 1,279 | 46 | #!/bin/bash
#$ -cwd
#$ -l bluejay,mem_free=2G,h_vmem=2G,h_fsize=400G
#$ -N move_bulk_round2-1
#$ -o logs/move_bulk_round2-1.$TASK_ID.txt
#$ -e logs/move_bulk_round2-1.$TASK_ID.txt
#$ -m e
#$ -t 1-2
#$ -tc 2
echo "**** Job starts ****"
date
echo "**** JHPCE info ****"
echo "User: ${USER}"
echo "Job id: ${JOB_ID}"
echo... |
b50c13574e5fc8fd26eda0028af8043d920ba0f3f5c0cd5bd12b0f4d9bcb1c27 | Shell | 1,280 | 42 | #!/bin/bash
# Define the cell lines array
# cell_lines=("A549" "A375" "BT20" "HA1E" "HELA" "HT29" "MCF7" "MDAMB231" "PC3" "VCAP")
cell_lines=("A549" "BT20" "MCF7" "MDAMB231" "PC3" "VCAP")
# Iterate over each cell line
for cell_line in "${cell_lines[@]}"
do
# Create a job submission script for each cell line
echo... |
21c44145a399eec754a0d7bc98f7958519a361ec694cc3826a6c59d0126a4e2d | Shell | 1,281 | 21 | source ./config.sh
source activate proteinnpt_env
export model_config_location=$ProteinNPT_config_location # [ProteinNPT_config_location|Embeddings_MSAT_config_location|Embeddings_Tranception_config_location|Embeddings_ESM1v_config_location|OHE_config_location|OHE_TranceptEVE_config_location]
export sequence_embedding... |
f07880478a1bd92eb3ad4e4f579c4bfe860e02a64757e9fbe622324f3521dc33 | Shell | 1,282 | 58 | #!/bin/bash
function reg_network_to_subj {
path_to_sub=$1
netw=$2
sub_id=$(basename $path_to_sub)
net_name=$(basename $netw _1mm_flirt.nii.gz)
mkdir -p ${path_to_sub}/anat/to_MNI_flirt/reg_networks
flirt \
-in $netw \
-ref ${path_to_sub}/anat/${sub_id}__T1w.nii.gz... |
d3ad0afe980810824ab212c41c4b4ac20c90301912dfba9ee55ad3f192202d2f | Shell | 1,284 | 35 | #!/bin/bash
### Install the package with a given type in a defined conda environment with a define python version,
### and call it to check if it works
### example usage:
### ./pip_install.sh stable my_env 3.9
set -e -u
INSTALL_TYPE=$1 # stable, loose, etc..
ENV_NAME=${2:-alpharaw}
PYTHON_VERSION=${3:-3.9}
DOTNET_RUNT... |
98fe5075505faedba503a7a8005e7161504c69cbba2e01e18f4d391346fa739b | Shell | 1,288 | 39 | #!/bin/bash
#
# Copyright 2021 AlQuraishi Laboratory
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law ... |
78b64ee619599a49722073bdbaf9782f347fa100fb612991db4593b0a2e0e70f | Shell | 1,294 | 38 | set -e
SCRIPT_PATH=$(dirname $(realpath -s $0))
if [ ! $# -eq 2 ]; then
echo "${SCRIPT_PATH}: Params error, installation of tensorflow libraries failed!"
exit 1
fi
PYTHON_SITE_PACKAGE_PATH=$(realpath -s $1)
TENSORFLOW_ROOT=$(realpath -s $2)
TF_INSTALL_PATH=${PYTHON_SITE_PACKAGE_PATH}/tensorflow
if [ ! -d ${TF_INST... |
b8efa6c6c26c4b19351ba20e2b58c2db4b3e4cd1ae5212624c80afaed33bb165 | Shell | 1,297 | 38 | #!/usr/bin/env bash
#
# This script downloads the required input data (bigWig tracks and BED peak
# sets) from the public S3 bucket where they are hosted.
#
# You must have the AWS CLI installed and configured for this to work.
#
set -euo pipefail
# Public S3 bucket URL where the data is hosted
BUCKET_URL="s3://iceqr... |
79c9bfea9544f493cf23d76f1a3e5488abb6480fb1d996b52c81c13bf5286826 | Shell | 1,298 | 30 | #!/bin/bash
#SBATCH --job-name=roi_split # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=02:00:00 # Max time for job (2 hours)
#SBATCH --nodes=1 # Number of nodes
#SBATCH --... |
d44745e41935df3c5154c79f4ed0af32c0b70c45991e14a04c0cddd870cfb8f3 | Shell | 1,299 | 40 | #!/bin/bash
#
# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
9f8ee7dcb36586db71efbb043cf254702538a541f031c7029714de1ec2b39a95 | Shell | 1,300 | 28 | #!/usr/bin/env bash
## This script loops through all scaffolds in the dunnart genome and
## generates a separate command for each scaffold
## These commands are then used in a slurm array script to run jobs in parallel
TRA=($(for file in *.maf; do echo $file |cut -d "." -f 1-2;done))
echo ${TRA[@]}
for tr in ${TRA[... |
c6b79bbc0d4b73962117c9acb753b3eaebd57bced350054370bce225a5d0f29d | Shell | 1,305 | 30 |
numof_category=1000
fillrate=0.2
weight=0.4
imagesize=362
numof_point=100000
numof_ite=200000
howto_draw='patch_gray'
numof_thread=40
arch=resnet50
# Parameter search
python param_search/ifs_search.py --rate=${fillrate} --category=${numof_category} --numof_point=${numof_point} --save_dir='./data'
python param_search/... |
8d1e3e1cee9225ea5463b27c73a046a32b6d86d1b7dc26b25355a38152780338 | Shell | 1,306 | 40 | #!/bin/bash
# STAR v2.7.9a
# Cell Ranger Reference, 2020-A
# Mouse reference, mm10 (GENCODE vM23/Ensembl 98)
# Input: single-nucleus RNA-seq data generated using 10x Genomics Chromium Next GEM Single-Cell 3’ Reagent Kits for v3.1 chemistry
# Generate genome indices
STAR --runThreadN 6 \
--runMode genomeGenerate \
--... |
16123e6a9a2cdc71d39ba3c8ae3ed44287d7e9fe032ec49cf70266f56cfd9a00 | Shell | 1,307 | 38 | #!/bin/bash
# File: generateBuildInfo.sh
# SPDX-License-Identifier: GPL-3.0
# This file is part of NetInf (https://github.com/neuro8000/NetInf),
# developed by Peter M. Rasmussen, Aarhus University, Denmark.
# It is distributed under the terms of the GNU General Public License v3.0.
# See the LICENSE file or https://ww... |
394b5fcac6365e12267f267d37af672a3627efa79ed3d88a85074c02093ad4d3 | Shell | 1,307 | 38 | #!/usr/bin/env bash
# Run alphadia with custom quantification directory. The point here is to use
# the slurm_index to find the proper chunk folder.
#SBATCH --job-name=alphaDIA
#SBATCH --time=21-00:00:00
#SBATCH --output=./logs/%A_%a_%x-slurm.out
# Save initial directory (where sbatch was called from)
initial_direct... |
fc35d96d5d3c7d3e3ea38fcec54a92cf0b8e821c796d4716a3850ad98c0fbee6 | Shell | 1,307 | 50 | #!/bin/bash
#SBATCH -p shared
#SBATCH --mem=8G
#SBATCH --job-name=09_hspe_donor_subset
#SBATCH -c 1
#SBATCH -t 4:00:00
#SBATCH -o /dev/null
#SBATCH -e /dev/null
#SBATCH --array=1-998%20
## Define loops and appropriately subset each variable for the array task ID
all_n_donors=(3 4 5 7 10 14 19 27 37 52)
n_donors=${all_... |
5c8063d95e8717f2036361abf7576670c7a231c0d4522a38a39aa6d40b15cef0 | Shell | 1,309 | 33 | #!/bin/bash
#SBATCH --job-name=match # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=05:00:00 # Max time for job (5 hours)
#SBATCH --nodes=1 # Number of nodes
#SBATCH --ntas... |
59ad3afb16dcc6a6b411ac54d280b27bfb473aca7d1e974d67d27292bde76453 | Shell | 1,318 | 33 | # USAGE
# customize Line 15
# sh run_analysis.sh sbatch_file_for_preproc
# RUN THE FOLLOWING SEQUENTIALLY
# 1. preprocess anatomical (customize Line 13)
# sh run_analysis.sh 1.anat_preproc.sh
# 2. reorient functionals (customize Lines 14-15)
# sh run_analysis.sh 2.func_reorient.sh
# 3. run slice timing cor... |
6d995bebdb24fd0b29466e0112f8a648977d852587354d7083028830b90c1d95 | Shell | 1,321 | 41 | #!/bin/bash
source /data_st01/drug/itosho/.bash_profile
pyenv shell miniconda3-latest/envs/kmol
train_base_path="/data_st01/drug/itosho/ADMET/configs/accuracy_drug/adme/finetuning_learning_rate/train/fup_human/*"
run_path="/data_st01/drug/itosho/kmol/"
cd $run_path
for folder in $train_base_path; do
if [ -d "$f... |
f0225b91f0139d42b87cb9c35c9f29f17b135700b490ea32ed431da4c59ca38a | Shell | 1,322 | 53 | #!/bin/bash
# This script is meant to be called in the "deploy" step defined in
# circle.yml. See https://circleci.com/docs/ for more details.
# The behavior of the script is controlled by environment variable defined
# in the circle.yml in the top level folder of the project.
MSG="Pushing the docs for revision for b... |
21976fb93c4ba287f74327142af63e4525c16f84b09bbb8641d64f818c1be9e9 | Shell | 1,327 | 33 | # runVignette06.sh - Forward simulation, path tracking
# --------------------------------------------------
# This vignette demonstrates forward simulation of
# blood flow through a vascular network.
# The ESL viscosity model is used, hematocrit is
# non-uniform throughout the network (the phase separation
# effect is ... |
e7bcb9b14b49144c4f645a3692904f088460f221b35796bbea1bb6fbf99d8730 | Shell | 1,327 | 37 | # Runs evaluation on manually selected model checkpoint
# (note: on different architecture layouts might need some extra args, ideally the same as the used training script)
eval_all_disasters () {
for event in floods fires hurricanes landslides
do
rm -rf /data/cache
rm -rf $HOME/cache/
... |
04103616f73dd44e10dcaf7ff9da3fe32e8ca0a06a6e95bf3478b1c1ac82db18 | Shell | 1,328 | 33 | #!/bin/bash
#SBATCH --job-name=lab_upd1 # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=03:00:00 # Max time for job (5 hours)
#SBATCH --nodes=1 # Number of nodes
#SBATCH --n... |
799652764c19db8499247ae797139d1de3edbc01d3f787e97b68c52b0b9eb32b | Shell | 1,328 | 21 | FILE=$1
if [[ $FILE != "ae_photos" && $FILE != "apple2orange" && $FILE != "summer2winter_yosemite" && $FILE != "horse2zebra" && $FILE != "monet2photo" && $FILE != "cezanne2photo" && $FILE != "ukiyoe2photo" && $FILE != "vangogh2photo" && $FILE != "maps" && $FILE != "cityscapes" && $FILE != "facades" && $FILE != "iphon... |
68ee57aaa44266379139a72e21512fbe9267bb73b066f2c5210375f5a980af46 | Shell | 1,330 | 50 |
#index reads
nanopolish index --directory=control_1/fast5/pass --sequencing-summary=data/fastqs/sequencing_summary.txt control_1.fastq
# call polyA tails
nanopolish polya --threads=8 --reads=control_1.fastq --bam=sort_dmel-all-transcript-r6.43_control_1_Nanopore.bam --genome=dmel-all-transcript-r6.43.fa > polya_re... |
db486d3d2635e521bc6f269657e57a330c4d9c5124e4e590290ea36aabcc6042 | Shell | 1,331 | 30 | #!/bin/bash
#SBATCH --job-name=sample_hyp_tune # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job
#SBATCH --nodes=1 #... |
9a339f243285b094153531b92d968a0b1791945cbeea2899370072f3e5bbc4f5 | Shell | 1,333 | 31 | #!/bin/bash
# Script to process subject images.
# Subject ID
subject="S007"
# CT image filename
ct_filename="Images-CT_10.10_Low_Dose_head_-_Trial_setup_MB_HHedit_30.03.23_20240129140700_301.nii.gz"
# MR planning images
mr_foldername_planning="F3T_2023_008_007"
t1_ax_filename="images_010_t1_mpr_ax_1mm_iso_withNose_3... |
69b9e33e2757e72a5e4eba4d34364b53655d12ed182d9778b0d093a13b72c356 | Shell | 1,335 | 68 | #!/bin/bash -l
#SBATCH --job-name="EEG_2_CoordsV"
#SBATCH --partition=prod
#SBATCH --nodes=39
##SBATCH -C clx
#SBATCH --cpus-per-task=2
#SBATCH --time=24:00:00
##SBATCH --mail-type=ALL
#SBATCH --account=proj85
#SBATCH --no-requeue
#SBATCH --output=EEG_1_CoordsV.out
#SBATCH --error=EEG_1_CoordsV.err
#SBATCH --exclusive
... |
e677d16d503ce88aba7e78927492f5fb6df75bd81f9235cd2a7fda79d2581adb | Shell | 1,335 | 47 | #!/bin/bash
# This script smooths the ts with a gaussian kernel of 4mm
#
# -----------------------------------------------------------
# Script written by Ludovico Coletta, NILAB, FBK (2022)
# -----------------------------------------------------------
function smooth {
ts=$1
study_folder=$2
subject... |
608a812dafdffd07fd23dc0c049ef6fa74b2dc42f4195a7ef6cb77b4bfe46f08 | Shell | 1,336 | 53 | #!/bin/bash
# 26 Sept 2017 Siwei
# modified 26 Oct 2017 Siwei
# modified 1 Nov 2017 Siwei
# modified 9 Nov 2017 Siwei
# modified 24 Jan 2020 Siwei
# modified 05 May 2021 Siwei
# updated to GATK version 4
# modified 26 May 2021 Siwei
# updated to dbsnp version 154
gatk="/home/zhangs3/Data/Tools/gatk-4.1.8.1/gatk"
ref... |
ac166684907578b14457e832a5513a67ce85273f46f8c7388f965b6cbc9574d9 | Shell | 1,336 | 37 | #!/bin/bash
# This script copies the concepts in the BigQuery table mimiciv_derived to mimiciv_${VERSION}_derived.
if [ -z "$1" ]; then
echo "Usage: $0 <version>"
exit 1
fi
export SOURCE_DATASET=mimiciv_derived
export TARGET_DATASET=mimiciv_$1_derived
export PROJECT_ID=physionet-data
# check if the target dataset ... |
e2727636e0a2e0a891198e433bc14b3424af116b99ac8c63db987630d7b32250 | Shell | 1,336 | 44 | #!/bin/bash
# Define the cell lines array
# cell_lines=("A549" "A375" "AGS" "BICR6" "ES2" "HT29" "MCF7" "PC3" "U251MG" "YAPC")
cell_lines=("A549" "MCF7" "PC3")
# Iterate over each cell line
for cell_line in "${cell_lines[@]}"
do
# Create a job submission script for each cell line
echo "#!/bin/bash
#BSUB -J gene... |
3937727e1616d9dbf6607f78de8c332150aa8cd0006f10661e23a042dc148f07 | Shell | 1,338 | 30 | #!/bin/bash
#SBATCH --job-name=frcnn_val_eval # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job
#SBATCH --nodes=1 #... |
27e0db30bacf6df06d5f814ae3e20e33826caa7239d55df53dd1160d3dd69068 | Shell | 1,341 | 44 | #!/usr/bin/env bash
set -e
# Get the directory where the current script is located
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
# Source the common setup file
source "$SCRIPT_DIR/common_setup.sh"
test_signmaps() {
common_init
echo "[DEBUG]: Visual field sign maps generation"
# Setu... |
be37c05fd057b0d566962e0f2b25eea6fc0e6df1e6d9e31b77f2136f1a75e9f4 | Shell | 1,341 | 52 | #!/bin/bash
##
## route header (sourced by route scripts)
##
# script filename (0 for actual script, 1 for sourced from)
script_path="${BASH_SOURCE[1]}"
# show route info
script_name=$(basename "$script_path")
route_name=${script_name/%.sh/}
echo -e "\n ========== ROUTE: $route_name ========== \n" >&2
# check if ... |
7d2c924c40023a6386dc807445ce0c79f052d4c82961d859c5334bd86c4c7070 | Shell | 1,342 | 22 | #!/bin/bash
set -ev
SCRIPT_PATH=$(dirname $(realpath -s $0))
# .savedmodel is the JAX/JAX2TF output suffix. .savedmodeltf is the TF2 output
# suffix. The C++ API loads both SavedModel artifacts through the TensorFlow C
# API loader historically named DeepPotJAX.
dp convert-backend ${SCRIPT_PATH}/deeppot_sea.yaml ${S... |
79e3fa42c2c8a2a096949fe784dec85d4f0af47f0814323e00b6b9e91eca59c6 | Shell | 1,343 | 41 | #!/bin/sh
# Copyright (C) 2009-2022, Ecole Polytechnique Federale de Lausanne (EPFL) and
# Hospital Center and University of Lausanne (UNIL-CHUV), Switzerland, and CMP3 contributors
# All rights reserved.
#
# This software is distributed under the open-source license Modified BSD.
# Build the documentation using BASH... |
92639528daaab52006493a20763480cd85a5df8655a0af83a74d5298afba2994 | Shell | 1,345 | 49 | #!/usr/bin/env bash
cd ./data
# Get image data
if ! [[ -d ./images ]]; then
mkdir ./images
cd ./images
echo "Downloading 'train_val_images.zip'"
curl https://zenodo.org/records/10009966/files/train_val_images.zip?download=1 --output train_val_images.zip
echo "Extracting image directories"
unzip train_val_... |
ae395907cf13d0c646a80fa49664b5a3edf4b179934e3766cb39155d41fa0ef5 | Shell | 1,357 | 46 | #!/bin/bash
#SBATCH --partition=all
#SBATCH --job-name=MLNI
#SBATCH --array=0-6
#SBATCH --mem-per-cpu=24G
#SBATCH --output=<output_log_dir>/MLNI_%A_%a.out
#SBATCH --error=<output_log_dir>/output/MLNI_%A_%a.err
numbers=(brain adipose heart kidney liver pancreas spleen)
organ=${numbers[$SLURM_ARRAY_TASK_ID]}
# === Load... |
d11e417bc38490b5ea576219d5c465c50f39b02dd43e78a30390c85c355fcaf1 | Shell | 1,362 | 34 | #!/bin/bash
#$ -l mem_free=40G,h_vmem=40G,h_fsize=800G
#$ -o ./SPEAQeasy_output.log
#$ -e ./SPEAQeasy_output.log
#$ -cwd
# After running 'install_software.sh', this should point to the directory
# where SPEAQeasy was installed, and not say "$PWD"
ORIG_DIR=/users/lhuuki/SPEAQeasy
module load nextflow
export _JAVA_OP... |
8a6ec37fa907aef2eb7ab36ce6e93048a5c71eec5a818408f23a214fbd6918fd | Shell | 1,364 | 40 | #!/bin/bash
echo "Combining signal and parameter arrays"
python combine_arrays.py
echo "Finding closest protocol, getting the subsets and processing .nii files"
python get_closest_scheme.py \
--protocol-name MOUSE_BREAST_EXVIVO \
--ref-signal all_signals_all_substrates.npy \
--dwi zenodo_mouse_data/dwi_... |
463e1522f72eaa1ee35fc336adceb5b0abae5f3dbf0268c6fabd00a27972e2cd | Shell | 1,366 | 33 | #!/bin/bash
#SBATCH --job-name=lab_upd3_val_test_misc # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2:00:00 # Max time for job (5 hours)
#SBATCH --nodes=1 # Number of node... |
f0566a109f3cd54f91a935a257dd1b56eb95af6650f6489f4b088a2fdbf1d742 | Shell | 1,367 | 46 | #!/bin/bash
ml freesurfer/7.3.2
# this script converts all created .mgz files to .gii files
subjects_dir=""
subject_id=""
while getopts s:i: flag
do
case "${flag}" in
s) subjects_dir=${OPTARG};;
i) subject_id=${OPTARG};;
?)
echo "script usage: $(basename "$0") [-s path to subs]" ... |
7f855a38ad99668a286c847aae6f09a8a31b4d448255ad9a4d123cae9eb6acea | Shell | 1,370 | 33 | #!/bin/bash
#SBATCH --job-name=lab_upd4_all_misc # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=10:00:00 # Max time for job (5 hours)
#SBATCH --nodes=1 # Number of nodes
#S... |
de2ae5a4a6d49a181306f954f43311bc7ac4ef48c2dada2d2b2a9f4a4dabcbaf | Shell | 1,371 | 47 | #!/bin/bash
# This script performs skull-stripping i.e. removes extra-brain tissues
#
# -----------------------------------------------------------
# Script written by Ludovico Coletta
# NILAB, FBK (2022)
# -----------------------------------------------------------
function brain_mask_subject {
$ts=$1
fil... |
1f2f623f5771a4e04e1a15bee687222d27d929fcb17a1a30b8637ac3114053b1 | Shell | 1,373 | 33 | #!/bin/bash
#SBATCH --job-name=frame_extraction # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=10:00:00 # Max time for job (2 hours)
#SBATCH --nodes=1 # Num... |
43ec2f9e5f58ecf00cbe3a016c0dda8c2c5b8d7e12a1c743531300d2c055b249 | Shell | 1,374 | 38 | # Runs evaluation on manually selected model checkpoint
# (note: on different architecture layouts might need some extra args, ideally the same as the used training script)
eval_all_disasters () {
for event in floods fires hurricanes landslides
do
rm -rf /data/cache
rm -rf $HOME/cache/
... |
7772b5c4680d772574b0d87fd3eb217a20c4c7d0a61562e7fc0322d7bfe29a96 | Shell | 1,377 | 33 | #!/bin/bash
#SBATCH --job-name=lab_upd2_valtest_misc # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=3:00:00 # Max time for job (5 hours)
#SBATCH --nodes=1 # Number of nodes... |
0d610b4b04b154b886caa91c19f9aaa78cb819c6051ac478c5a2256446840ea2 | Shell | 1,378 | 29 | #!/bin/bash
#SBATCH --partition=prod
#SBATCH --nodes=32
#SBATCH -C cpu
#SBATCH --time=24:00:00
#SBATCH --output=pax.log
#SBATCH --error=paxerr.log
#SBATCH --account=proj85
#SBATCH --no-requeue
#SBATCH --exclusive
# SPDX-License-Identifier: Apache-2.0
ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=2560
export moving_nii='../in... |
009f4229a59613f7d1f98304bca593bb996fa83b201ef46477ff7b8edcb42ae8 | Shell | 1,379 | 44 | #!/bin/bash
# BytesAndFlops
cd build/bytes_and_flops
USE_CUDA=`grep "_CUDA" KokkosCore_config.h | wc -l`
if [[ ${USE_CUDA} > 0 ]]; then
BAF_EXE=bytes_and_flops.cuda
TEAM_SIZE=256
else
BAF_EXE=bytes_and_flops.exe
TEAM_SIZE=1
fi
BAF_PERF_1=`./${BAF_EXE} 2 100000 1024 1 1 1 1 ${TEAM_SIZE} 6000 | awk '{print $1... |
b52c291f9bfc640a309eff137dc21a98f4a0b992193d70f736b2628d222cef14 | Shell | 1,381 | 11 | for i in {1..3}; do
bash bash_scripts/moving_animals.sh --seed $i --experiment_name animals_cts_noiseOnTop0.1_pred_$i --loss pred --prediction_target enc --pred_lr_mult 10;
bash bash_scripts/moving_animals.sh --seed $i --experiment_name animals_cts_noiseOnTop0.1_inv_sg_$i --loss inv --prediction_target pred --p... |
ac518449c32ac0b9e12ace4715789a7277c4aca6be68d9404c84ac76760cfbe7 | Shell | 1,385 | 30 | #!/bin/bash
set -euo pipefail
export ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=${THREADS_PER_COMMAND:-$(nproc)}
movingfile=$1
fixedfile=$2
outputdir=$3
shift 3
fixedmask=$(dirname ${fixedfile})/$(basename ${fixedfile} _t1.nii.gz)_mask.nii.gz
movingmask=$(dirname $movingfile)/$(basename $movingfile _t1.nii.gz)_mask.nii.gz... |
1d7c23ba502d80d49d5e95c710a0f0cc1d5eea7b9b232c6ba9748486f30d3ada | Shell | 1,386 | 25 | #!/bin/bash
set -euo pipefail
export ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=${THREADS_PER_COMMAND:-$(nproc)}
movingfile=$1
fixedfile=$2
outputdir=$3
shift 3
fixedmask=$(dirname ${fixedfile})/$(basename ${fixedfile} _t1.nii.gz)_mask.nii.gz
movingmask=$(dirname $movingfile)/$(basename $movingfile _t1.nii.gz)_mask.nii.gz... |
76d067c174e785816737a9029df92eb980b4cc7b594011e82633b8c5a9a06610 | Shell | 1,387 | 19 | source ./config.sh
source activate proteinnpt_env
export model_location="Path to model checkpoint (e.g., $DATA_PATH/checkpoint/model_name_BLAT_ECOLX_Jacquier_2013_fold-1/final/checkpoint.t7)"
export assay_data_location="Path to assay file with train/test sequences (e.g., $CV_subs_singles_data_folder/BLAT_ECOLX_Jacquie... |
616d6c7108a1d3f8e3feea63e6538dbc101227ce54ba6b0aa5adbf32385726a5 | Shell | 1,388 | 33 | #!/bin/bash
#SBATCH --job-name=eval_lstm_test # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job (2 days)
#SBATCH --nodes=1 # ... |
c120252da1eeb6ffe49f25e7707e13220f3eea9967589ceda6c2cf1614469cd9 | Shell | 1,389 | 43 | #! /bin/bash
for drug in $(cat datasets/4i/drugs.txt); do
for model in cellot cae scgen identity random; do
if [ $model == cae ]; then
model_config=./configs/models/cae-4i.yaml
elif [ $model == scgen ]; then
model_config=./configs/models/scgen-4i.yaml
else
model_config=./configs/mod... |
b412b77b70578301d37f38e0181cf19e59a6744ea80ce39d1a1088d7529ccad8 | Shell | 1,392 | 28 | #!/bin/bash
#SBATCH --time=120:00:00
#SBATCH --ntasks=1
#SBATCH --cores 1
#SBATCH --mem-per-cpu 128GB
mkdir Sestan_DLPFC_Subsamples_subtype
mkdir Sestan_DLPFC_Subsamples_subclass
python process_for_ctp_Sestan_DLPFC.py rhesus subtype Sestan_DLPFC_Subsamples_subtype
python process_for_ctp_Sestan_DLPFC.py chimp subtype ... |
2835eb4e6127ff8bde1922058f8ca1cef81b66a575e574ca105fd56637e00416 | Shell | 1,394 | 41 | #!/bin/bash
#
# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
17be5b34b0c34d5c2c3ef618dbcf1a3df84f41ad8700c61ce9f9ecc7b989ce45 | Shell | 1,396 | 33 | #!/bin/bash
#SBATCH --job-name=train_lstm_grid_US # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job (2 days)
#SBATCH --nodes=1 ... |
e59cb57f5162cad4f54f3e2c27cf2c01752951e036bdd66c0b779ed2d1239c30 | Shell | 1,396 | 40 | #!/bin/bash
#SBATCH --partition=prod
#SBATCH --nodes=1
#SBATCH -C cpu
##SBATCH --ntasks-per-node=36
#SBATCH --time=24:00:00
#SBATCH --account=proj85
#SBATCH --no-requeue
#SBATCH --exclusive
#SBATCH --mem=0
# SPDX-License-Identifier: Apache-2.0
ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=9000
source ../../environments/atlasE... |
964af7fc7b0af8960d1f83f07d1e5ce90bd62d020031c423313c10a7de6fe782 | Shell | 1,397 | 33 | #!/bin/bash
#SBATCH --job-name=train_lstm_full # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job (2 days)
#SBATCH --nodes=1 ... |
dc0ebb4c56ae87daba590a5ee5af96409561a8d9bd3294c0d30f311802480537 | Shell | 1,398 | 52 | #!/bin/bash
function seed_subject_correlation_map {
ts=$1
seed=$2
brainmask=/home/ludovico/Projects/NeuSurPlan/REMAP_subcortical/templates_and_masks/MNI152_T1_2mm_brain_mask.nii.gz
# Calculate seed time course for subject/session
subj_name=$(basename $ts .nii.gz)
seed_name=$(basename $seed... |
c38b643f0274dfcb9fe3b0742c1a81c9b430fdf6c16603c855ef1d378a468ce7 | Shell | 1,400 | 33 | #!/bin/bash
#SBATCH --job-name=lstm_overlap_cv # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job (2 days)
#SBATCH --nodes=1 #... |
25a57e5163df01bb14ded16abc580e4318ff54ac632909b2b3a551121f554851 | Shell | 1,401 | 30 | #!/bin/bash
#SBATCH --job-name=frcnn_test_eval_map # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=2-00:00:00 # Max time for job
#SBATCH --nodes=1 ... |
82f06002f067b493474a55c0c12928d4f52d75fd99849d404525958031ae3ab9 | Shell | 1,401 | 57 | #!/bin/bash
set -e
cp /staging/bcjohnson7/eve.tar.gz ./
ENVNAME=eve
# if you need the environment directory to be named something other than the environment name, change this line
ENVDIR=$ENVNAME
# these lines handle setting up the environment; you shouldn't have to modify them
export PATH
mkdir $ENVDIR
echo "un ta... |
f32478f3000d9d946d7e725b2f6e494a458aff5036bfe20ae7a508024a057899 | Shell | 1,403 | 23 | source ./config.sh
source activate proteinnpt_env
export model_config_location=$ProteinNPT_config_location #[ProteinNPT_config_location|Embeddings_MSAT_config_location|Embeddings_Tranception_config_location|Embeddings_ESM1v_config_location|OHE_config_location|OHE_MSAT_config_location]
export sequence_embeddings_folder... |
12bb588920c880a0a1eab105103ac99c43ba1b401c45f8ffb5908be111529d05 | Shell | 1,410 | 41 | #!/bin/sh
# wrapper for bundled executables
# reset locale to avoid problems with decimal numbers
export LC_ALL=C
BASEDIR="$(dirname "$0")"
EXENAME="$(basename "$0")"
# save old settings (for restoring them later)
OLDPATH="${PATH}"
OLDLDLIB="${LD_LIBRARY_PATH}"
# prepend path to find our custom executables
PATH="${... |
277a0c466a9f30cdcc5eba70fd21f307cca0d92f8b2259077f786228e54cccf5 | Shell | 1,410 | 33 | #!/bin/bash
#SBATCH --job-name=eval_lstm_val_overlap_new # Job name
#SBATCH --output=/dev/null # Suppress the default SLURM log file
#SBATCH --error=/dev/null # Suppress the default SLURM error file
#SBATCH --time=1-00:00:00 # Max time for job (2 days)
#SBATCH --nodes=1 ... |
1cfeb7dc9b6a6367a6648ebb7e98e91d835c0da75b88b28eedc24906fc1c7300 | Shell | 1,414 | 41 | #!/bin/bash
#
# Copyright 2021 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
d209bcc12e15ac884eac919d4d96b9dbd9ca743879132198b48742af9c9d7f50 | Shell | 1,416 | 42 | #!/bin/bash -l
# run using fx:
# rm -rf results; sbatch --job-name mc-prediction --output=/dev/null --cpus-per-task 2 --mem 8G --wrap "apptainer exec --no-home --cleanenv mc-prediction.sif conda run -n mc-prediction bash ./run.bash"
set -eu
#set timezone
export TZ="Europe/Copenhagen"
export TF_CPP_MIN_LOG_LEVEL=2 #sile... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.