sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
59608090617d4604b846ce986d98185dc64fd96a142bc2c2a2867422784140b4 | Shell | 318 | 3 | export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
python graphcare.py --dataset mimic3 --task mortality --kg GPT-KG --batch_size 4 --hidden_dim 512 --epochs 100 --lr 1e-5 --weight_decay 1e-5 --dropout 0.5 --num_layers 1 --decay_rate 0.01 --freeze_emb False --patient_mode joint --edge_attn True --attn_init False --device 1 |
9a906d73d66f12c1c559b0ec99780931aeeb989db915fcf7357c72b984b87bf6 | Shell | 319 | 15 | #!/bin/bash
set -x
set -e
D=$(dirname $(readlink -nf $BASH_SOURCE))
INDEX_FILE="$D/../httpdocs/index.html"
if [ -e "${INDEX_FILE}.DOWN" ]
then
mv "${INDEX_FILE}.DOWN" "$INDEX_FILE"
else
mv "$INDEX_FILE" "${INDEX_FILE}.DOWN"
echo "<html><h2>CATMAID is down for maintenance</h2></html>" > "$INDEX_FILE"
fi
|
adecf628472398f0dffc6a65ce39401c1c901f2d61fe480a7df5f7cb05af5c95 | Shell | 319 | 6 | #!/bin/bash
for i in "$@"; do
CONTENT_LENGTH=`ls -la "$i" | awk '{ print $5}'`
curl --request PUT --header "Content-Length: "${CONTENT_LENGTH}"" --header "Content-Type: multipart/mixed" --data-binary "@"$i"" "https://api-content.dropbox.com/1/files_put/sandbox/$i?access_token="${ACCESS_TOKEN}""
printf "\n"
done
|
f3797124a695a20012553b51f5427de3b217619d4eb318597cba06091614707e | Shell | 321 | 14 | #!/bin/bash
# turn on bash's job control
set -m
# print uid
id
# wait for the nodes to spin up and create passwordless ssh
# /wait-for-it.sh openldap:636 --strict -- echo "openldap.example.org 636 is up"
# use this, if the docker container automatically terminates, but you want to keep it running
tail -f /dev/null... |
3c279638a4716c6d0fe8fc06af973ea36edb02b095a422e7ae401c1b2ac80ab6 | Shell | 322 | 9 | #!/bin/bash
for t in 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5; do
for a in 0.01 0.02 0.03 0.04 0.05 0.1 0.2 0.3 0.4 0.5; do
for social_factor in 0.0 0.01 0.02 0.03 0.04 0.05 0.1 0.2 0.3 0.4 0.5; do
echo "$t\t$a\t$social_factor" >> "./grid_simulation_group_parameters.txt"
done
done
do... |
d5971a34c2b40aa8ff89eed01f2d5d0dd39ad9bd690c419bf9d793351aab0345 | Shell | 324 | 16 | #!/bin/bash
## Softwares
htseq="/staging/biology/ls807terra/0_Programs/anaconda3/envs/RNAseq_quantTERRA/bin/htseq-count"
## User variable
BAM=$1
GTF=$2
ncore=$3
outFile=$4
# Run HTseq-count
$htseq -f bam -s reverse -t exon --idattr gene_name \
-m intersection-nonempty --nonunique all -n $ncore \
$BAM $GTF > $outFi... |
ef12768f9b949ac5fc218abf2bd24f27df26402359d1e31bd4d570045d67cf31 | Shell | 326 | 10 | set -eo pipefail
# run benchmark
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
bash $SCRIPT_DIR/benchmark/entrypoint.sh \
--input-data /mlcommons/volumes/data \
--input-labels /mlcommons/volumes/labels \
--model-files /mlcommons/volumes/model_files \
--output-results /mlcommons/volumes/re... |
bb0481590672eece346b26b82eda8d7214cd58f8fdf90f0a6e3880070f834b70 | Shell | 328 | 13 | export STEPPATH=$(step path)
python /setup.py
step-ca --password-file=$STEPPATH/secrets/pwd.txt $STEPPATH/config/ca.json &
if [[ -n "$USE_PROXY" ]]; then
STATUS="1"
while [ "$STATUS" -ne "0" ]; do
sleep 1
step ca health --ca-url 127.0.0.1:8000
STATUS="$?"
done
nginx -g "daemon o... |
34b843c643d6e5a37e639d7e7dd376a4e19843b67f76dbe1dcb471db7c5f1b96 | Shell | 332 | 15 | #!/bin/bash
set -eu
export PS4=+
datalad wtf -S datalad -S dependencies -S extensions
# verify that datalad-container is available in the environment
if ! datalad containers-run --help >/dev/null 2>&1; then
echo "datalad-containers extension seems to be NA here"
exit 1
fi
"$(dirname "$0")/create_singularit... |
7dfc15dfddca4553e4cb376ac283037ce003fbd0b26cd931b78969fe55fa8614 | Shell | 334 | 14 | #!/bin/bash
set -euo pipefail
source ops/pipeline/get-docker-registry-details.sh
source ops/pipeline/get-image-tag.sh
IMAGE_URI=${DOCKER_REGISTRY_URL}/xgb-ci.clang_tidy:${IMAGE_TAG}
echo "--- Run clang-tidy"
set -x
python3 ops/docker_run.py \
--image-uri ${IMAGE_URI} \
-- python3 ops/script/run_clang_tidy.py --... |
bbccfc26ef2ebb9cd7c77c7d2aa042fc86679c89ca4c31cc86077f69c90bf71e | Shell | 338 | 12 | #!/usr/bin/env sh
set -e
TOOLS=./build/tools
$TOOLS/caffe train \
--solver=examples/cifar10/cifar10_quick_solver.prototxt $@
# reduce learning rate by factor of 10 after 8 epochs
$TOOLS/caffe train \
--solver=examples/cifar10/cifar10_quick_solver_lr1.prototxt \
--snapshot=examples/cifar10/cifar10_quick_iter_40... |
03ecdb5307f317e06f7cd0f36d6f9e94fbca50c8722be49c7adbf2d426f176da | Shell | 344 | 18 | #!/usr/bin/bash
source activate porechop_abi_v0.5.0
t=1
s=test
ln -s ../reads.fastq.gz $s.fastq.gz
/usr/bin/time porechop_abi \
--ab_initio \
--verbosity 1 \
--threads $t \
--input $s.fastq.gz \
--output $s.trimmed.fastq.gz \
--temp_dir ${s}_tmp \
>$s.porechop_abi.stdout 2>$s.porechop_ab... |
f84771e490c23e052428a76c3bce68a5986630fdf76e983a9b05472147f65f45 | Shell | 347 | 12 | python3 ../../src/eventalignTosigalign.py \
--bam ../input/test_reads.bam \
--ref ~/tools/ref/yst/sacCer3.fa \
--eventalign ../input/test_eventlaign.txt \
--outpath ../output/ \
--prefix test \
--region all
# 89.7618,88.1159,87.7501,86.8357,87.933,86.2871,90.4934,97.8087,96.1627,95.6141
# 95.... |
a2601c13088627c6f78726abf1057565c3348dcc5cd7c0d8d6267e25f68e681e | Shell | 348 | 15 | #!/usr/bin/env sh
set -evx
env | sort
mkdir build || true
mkdir build/$GTEST_TARGET || true
cd build/$GTEST_TARGET
cmake -Dgtest_build_samples=ON \
-Dgmock_build_samples=ON \
-Dgtest_build_tests=ON \
-Dgmock_build_tests=ON \
-DCMAKE_CXX_FLAGS=$CXX_FLAGS \
../../$GTEST_TARGET
make
CTEST_OU... |
7d92ff2bf476d65b6b49d5dbea180c242635f2ad73659adc8760f46237fbe913 | Shell | 350 | 13 | #!/usr/bin/bash
reads=../reads.fastq.gz
genome=../genome_chr22.fa
ref_annot=../annot_reduced.gtf
n_threads=1
# Clean results before test
rm -r isorefiner_refined.gtf isorefiner_trans_struct_wf_work &>/dev/null
# Run the workflow.
# Final result: isorefiner_refined.gtf
isorefiner trans_struct_wf -r $reads -g $genom... |
7e3d01c83fa7b78bcfd1aee29067f16887c985875882348713fd1a6614dae630 | Shell | 350 | 13 | #!/bin/bash
# Define the path to the zip file and the directory to extract to
zip_file_path="results/models/4prl_pretrained.zip"
extract_to_path="results/models/"
# Create the directory if it doesn't exist
mkdir -p $extract_to_path
# Unzip the file
unzip -o $zip_file_path -d $extract_to_path
echo "File unzipped suc... |
933520fdf07b4cea68be142eea8d4ddad5c8d0093ccdf8bc9f80e40fe9cb22a9 | Shell | 354 | 15 | #!/bin/bash
#BSUB -o logs/nfcore.%J.out
#BSUB -e logs/nfcore.%J.err
#BSUB -n 12
#BSUB -R rusage[mem=50]
mkdir -p logs
. /usr/share/Modules/init/bash
module load modules modules-init
module load java/18
module load singularity/3.9.2
~/bin/nextflow run nf-core/atacseq -r 2.1.2 -c lsf.config -profile singul... |
a411d0eb5e79916ea1965e1d32ea2de87f80b92623ff941b7ad6b9d006a22ccb | Shell | 355 | 8 |
#PACKAGE_DIRECTORY="/path/to/cwlroot"
# This shouldn't need to use bash-isms - but we don't know the full path to this file,
# so for testing it is setup this way. For actual deployments just using full paths
# directly would be preferable.
PACKAGE_DIRECTORY="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)/"
export PAT... |
d5ad1368a841c786e132a2e368a8dcb759de51f2934742d4e12062798f8891ce | Shell | 355 | 19 | #!/bin/bash
#SBATCH -A MST109178
#SBATCH -J BAM_merge
#SBATCH -p ngs92G
#SBATCH -c 14
#SBATCH --mem=92g
#SBATCH -o ./reports/bw_merge.out.txt
#SBATCH -e ./reports/bw_merge_err.txt
# Software
bamtool="/staging/biology/ls807terra/0_Programs/bamtools/build/bin/bamtools"
# User vars
BAM_list=$1
output=$2
# Program
$bamt... |
db191d2d20459853c8864de9a1e25f9be7ee7538d874296c87a2f8bc874a22bd | Shell | 355 | 16 | #!/bin/bash
if [ $# -ne 1 ]
then
echo "Usage: $0 <DATABASE-NAME>"
exit 1
fi
D=$(dirname $(readlink -nf $BASH_SOURCE))
pg_dump --no-privileges --inserts --data-only --no-owner --no-tablespaces --column-inserts \
$1 -U catmaid_user | \
egrep -v '^--' | \
egrep -v '^ *$' | \
egrep -v 'INSERT INTO se... |
59dfa94a244d0fa80c3348f7cc2a651a9b7bc92d47fa08392920cf949fb31400 | Shell | 356 | 14 | # Create a workspace
mkdir -p medperf_tutorial
cd medperf_tutorial
# Copy the container to be used
cp -r ../examples/chestxray_tutorial/model_mobilenetv2 model_mobilenetv2
## download model weights
cd model_mobilenetv2/workspace/additional_files
sh download.sh
rm download.sh
# ## Login locally as model owner
# medpe... |
36e3d09a1dbb7528ff8ac16e48464e9b4a2a6c8218d0a4389b37fd6d39ad740c | Shell | 360 | 8 | mkdir ./workspace_admin
# Get your node cert folder and ca cert folder from the aggregator setup. Modify paths as needed.
cp -r ../fl/for_admin/node_cert ./workspace_admin/node_cert
cp -r ../fl/for_admin/ca_cert ./workspace_admin/ca_cert
# Note that you should use the same plan used in the federation
cp ../fl/for_adm... |
c9c7b661a82c8d32febfbe5104c71912511b57860cd2a72ec632acc79b67be97 | Shell | 364 | 14 | #!/bin/bash
# remove all #pragma's that suppress compiler warnings
set -e
set -x
for file in xgboost/src/dmlc-core/include/dmlc/*.h
do
sed -i.bak -e 's/^.*#pragma GCC diagnostic.*$//' -e 's/^.*#pragma clang diagnostic.*$//' -e 's/^.*#pragma warning.*$//' "${file}"
done
for file in xgboost/src/dmlc-core/include/dmlc/*... |
936e9b184836d792a7551a6c13cab38b691f67eaa9732ed00d332a66d25b5702 | Shell | 366 | 18 | # Make sure the dependencies of XGBoost don't appear in directly downstream project.
# Pass the executable as argument for this script
if readelf -d $1 | grep "omp";
then
echo "Found openmp in direct dependency"
exit -1
else
exit 0
fi
if readelf -d $1 | grep "pthread";
then
echo "Found pthread in dire... |
9a34cea952bb8a032cd84ebd6338deb1c91b8b0e1c441bab96e3b118f645a5aa | Shell | 368 | 12 | #!/bin/bash
#
# This script copies babel-private from a remote location
# into input_data/private/
#
export USERNAME='username'
export HOSTNAME='hostname'
export BABEL_PRIVATE="${USERNAME}@${HOSTNAME}:~/babel-private/"
export SCRIPT_DIR=$( cd -- "$( dirname -- "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )
rsync -avp $... |
f5f86b88266010287e48e896d5af2b6ce4e3dadcdbef803a256a371ad75010b8 | Shell | 368 | 13 | ingularity/3.3.0
#set your subjects
subjects=("01" "02" "03" "04" "05" "06" "07" "08" "09" "10" \
"11" "12" "13" "14" "15" "16" "17" "18" "19" "20" \
"21" "22" "23" "24" "25" "26" "27" "28" "29" "30" \
"31" "32" "33")
#loop over your subject
for subj in ${subjects[*]}; do
sbatch mriqc_singularity.sh ${subj}
s... |
191bd2f6893d0c61d76f60a5e67def01f88c6c7987db162d530b1bcda442880f | Shell | 369 | 10 | cp mlcube/workspace/training_config.yaml mlcube_agg/workspace/training_config.yaml
cp mlcube/mlcube.yaml mlcube_agg/mlcube.yaml
for dir in mlcube_col*/; do
if [ -d "$dir" ]; then
cp mlcube/mlcube.yaml $dir/mlcube.yaml
rm -r $dir/workspace/additional_files
cp -r mlcube/workspace/additional_f... |
91bed16488c32dbde1d5570edfb1a5e274195dee315017e923deb6ef0d40512e | Shell | 370 | 19 | #!/bin/bash
#SBATCH --job-name=run_encode_atac
#SBATCH --time=12:00:00
#SBATCH --partition=general
#SBATCH --output=run_encode_atac_ctrl_%j.out
#SBATCH --account=gdkendalllab
#ml ENCODE/caper/2.1.0
ml ENCODE/caper/2.3.2
ml Java/18
set -x
INPUT_JSON="ctrl_atac.json"
caper hpc submit atac.wdl -i "${INPUT_JSON}" --... |
ba221832786f377ca834229aa24e445da75a9cd8ccc554fd30001f065f727f6c | Shell | 370 | 18 | #$ -V
#$ -S /bin/bash
#$ -e ~/log
#$ -o ~/log
#$ -cwd
#$ -j y
#$ -l mem_free=20G # job requires up to 1 GiB of RAM per slot
#$ -l scratch=20G # job requires up to 2 GiB of local /scratch space
#$ -l h_rt=23:59:59
#$ -e ~/log
#$ -o ~/log
cd ~/src/scripts
module load CBI
module load r
#Rscript graph_test.R --c... |
016dfeeab514a19fd82d46af8196546760c131fd5e4afd66300496bb40b52f36 | Shell | 371 | 19 | #!/bin/bash
## Ensure that XGBoost can function with OpenMP disabled
set -euox pipefail
mkdir -p build
pushd build
cmake .. \
-GNinja \
-DUSE_OPENMP=OFF \
-DHIDE_CXX_SYMBOLS=ON \
-DGOOGLE_TEST=ON \
-DUSE_DMLC_GTEST=ON \
-DENABLE_ALL_WARNINGS=ON \
-DCMAKE_COMPILE_WARNING_AS_ERROR=OFF \
-DBUILD_DEPRECAT... |
8985d98930142b3a9388055b244edafb1c19ffeadb35b19f50db2727b094ae5a | Shell | 372 | 8 | cp -r ./workspace ./workspace_admin
# Get your node cert folder and ca cert folder from the aggregator setup. Modify paths as needed.
cp -r ../fl/for_admin/node_cert ./workspace_admin/node_cert
cp -r ../fl/for_admin/ca_cert ./workspace_admin/ca_cert
# Note that you should use the same plan used in the federation
cp .... |
2468e4df2ea1dd140def149d8c63b0c2f6d3091353e905c4d1613a54d666af53 | Shell | 373 | 19 | #!/bin/bash
#SBATCH --job-name=run_encode_atac
#SBATCH --time=12:00:00
#SBATCH --partition=general
#SBATCH --output=run_encode_atac_p3f_%j.out
#SBATCH --account=gdkendalllab
#ml ENCODE/caper/2.1.0
ml ENCODE/caper/2.3.2
ml Java/18
set -x
INPUT_JSON="pax3foxo1_atac.json"
caper hpc submit atac.wdl -i "${INPUT_JSON}... |
f72295cab4b31b2481b9100159ebe3cf80ba3276338b50752014844a2911e9c0 | Shell | 375 | 8 | # Install h5py in a convenient way for frequent reinstallation as you work on it.
# This disables the mechanisms to find and install build dependencies, so you
# need to already have those (Cython, pkgconfig, numpy & optionally mpi4py) installed
# in the current environment.
set -e
H5PY_SETUP_REQUIRES=0 python3 setup.... |
1875b372fe546cd186bc633404a64f957ba9d4e692ba9695c4bbdab31507df45 | Shell | 376 | 10 | DEPTH_DATA_URL="https://www.dropbox.com/s/qtab28cauzalqi7/depth_data.tar.gz?dl=1"
DATA_EXTRACT_DIR="./data"
PRETRAINED_URL="https://www.dropbox.com/s/356r36lfpyzhcht/pretrained_models.tar.gz?dl=1"
PRETRAINED_EXTRACT_DIR="./"
wget -c $DEPTH_DATA_URL -O - | tar -xz -C $DATA_EXTRACT_DIR
mkdir $PRETRAINED_DIR
wget -c $P... |
b24de42a7b971db82ee31695ab138a2796f66fd878d873d9bb354d5a0bb6fdad | Shell | 376 | 13 | python3 ../../src/predict.py \
--bam ../input/chrom_ang_500.sorted.bam \
--ref ../input/sacCer3.fa \
--parquet ../output/chrom_ang_500-sigalign.parquet \
--region all \
--seq_len 400 \
--step 200 \
--weight ../output/ang_test_r10_resnet_best_model.pt \
--thread 4 \
--outpath ../outp... |
ff6211104c1a6c00c1d8ab310f1a0647a0ba45b52789665083b00bfbbfb69c90 | Shell | 376 | 16 | #!/bin/bash
#BSUB -J nfcore_rnaseq
#BSUB -o logs/nfcore.%J.out
#BSUB -e logs/nfcore.%J.err
#BSUB -n 12
#BSUB -R rusage[mem=50]
mkdir -p logs
. /usr/share/Modules/init/bash
module load modules modules-init
module load java/18
module load singularity/3.9.2
~/bin/nextflow run nf-core/rnaseq -r 3.14.0 -c lsf... |
31f3e5263314b7cf1b24fadd9c757f41c4cee829640b774588cb231094ac8bfe | Shell | 378 | 18 | #!/bin/bash
set -eu
export PS4=+
# for 'uv'
export PATH=/usr/local/bin/:$PATH
datalad wtf -S datalad -S dependencies -S extensions
# verify that datalad-container is available in the environment
if ! datalad containers-run --help >/dev/null 2>&1; then
echo "datalad-containers extension seems to be NA here"
... |
69022959754a782404cbb0b16d8968314a8abfbf4fd75dd2d0d6bc6eee820d51 | Shell | 378 | 18 | #$ -V
#$ -S /bin/bash
#$ -e ~/log
#$ -o ~/log
#$ -cwd
#$ -j y
#$ -l mem_free=20G # job requires up to 1 GiB of RAM per slot
#$ -l scratch=20G # job requires up to 2 GiB of local /scratch space
#$ -l h_rt=23:59:59
#$ -e ~/log
#$ -o ~/log
cd ~/src/scripts
module load CBI
module load r
#Rscript graph_test.R --c... |
4ccd60f9f141b7ce00e9e73403bb37be81d1a395393357417a128176c762a3de | Shell | 380 | 14 | # soccertrack root directory
git_root=$(git rev-parse --show-toplevel)
# date
dt=$(date '+%Y-%m-%d_%H-%M-%S')
python $git_root/external/yolov5/train.py \
--project $git_root/logs/yolov5 \
--name $dt \
--data $git_root/data/yolov5/soccertrack_data.yaml \
--weights $git_root/models/yolov5/yolov5s.pt \
... |
41b4592800481440617e600d0a08ab7716001b193d9f911496ac2e08fac83e03 | Shell | 381 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 25:00
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse080_10class... |
764005da7296864382470134d64f7917d4d97bc204477199ef26f41918687288 | Shell | 381 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 25:00
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse080_10class... |
84607125c2e00b4fde55d92e4d36f2b641d9e6192ee685f9b1c918e9e31b88f1 | Shell | 381 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 25:00
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse080_10class... |
55b9ed2fca25fdb9bad8843798f7036cab3e4c62a43e22a3c8c0ca3071860a53 | Shell | 382 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 29:59
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse050_10class... |
f18228de79e0fe65b0efbe9e893895c968af07953bf6eade90b5aa40fa87adc5 | Shell | 382 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 29:59
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse050_10class... |
f262c57386b42ebe6d6dd6329599b98c96e3a65cb4528a4d2d55f629dc917d32 | Shell | 383 | 14 | #!/bin/bash
#SBATCH -o LOG%j.out
#SBATCH -e LOG%j.out
#SBATCH -p nano
#SBATCH -N 1
#SBATCH -D /lustre/groups/adamgrp/joey-ICONS-2023/surrogate-learning
#SBATCH -J Surr_training
#SBATCH --export=NONE
#SBATCH -t 25:00
#SBATCH --nice=100
module load python3/3.7.2
python3.7 scripts/generateReport.py -r sparse080_10class... |
1cdcdba7ed793c156ecb45fa18358ecbe0909e49038e84948b6b5202713b4ca9 | Shell | 385 | 18 | #!/bin/bash
#BSUB -o logs/samtools.%J.out
#BSUB -e logs/samtools.%J.err
#BSUB -n 12
#BSUB -R rusage[mem=50]
mkdir -p logs
. /usr/share/Modules/init/bash
module load modules modules-init
module load samtools
# go through each filtered BAM file in the current directory
for file in *_filtered.bam; do
# index ... |
b5d8f65d566e0d4c5f5580236547cac20f4a3cc993c31d1b4542493202bb6703 | Shell | 392 | 18 | #!/bin/bash
#BSUB -o logs/samtools.%J.out
#BSUB -e logs/samtools.%J.err
#BSUB -n 12
#BSUB -R rusage[mem=50]
mkdir -p logs
. /usr/share/Modules/init/bash
module load modules modules-init
module load samtools
# go through each filtered BAM file in the current directory
for file in *_filtered_merged.bam; do
#... |
170ec84827dc0c9af69a9fb7a8645e3a28de943f742cedbbcdb41ad66bb9c54d | Shell | 395 | 12 | #!/bin/bash
# TODO: ideally we should figure it out
v=3.0.15.20190401.dfsg1-1~nd100
v=$(echo $v | tr '~' '+')
neurodocker generate singularity \
--base neurodebian:buster-non-free \
--ndfreeze date=20190915 \
--pkg-manager apt \
--install {octave,matlab}-psychtoolbox-3{,-nonfree} octave-{image,optim,signa... |
70c9f543204493c54475e2f9f02b37fd53483b28c698a035f862a2491866f72e | Shell | 395 | 6 | find . -type f -name '*dup-01*' -delete
datalad get .
BIDS_DIRECTORY="/dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop/dartmouth"
GUID_MAPPING="/dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop_data/scripts/spacetop_prep/nda/GUIDMAPPING.txt"
OUTPUT_DIRECTORY="/dartfs-hpc/rc/lab/C/CANlab/labdata/projects/spacetop_proje... |
b5823dc7e9ab6d0afb3487c45e3780ce48706c84cf60ff710b3f6480a54a3cff | Shell | 395 | 12 | #!/bin/bash
echo $run
if [[ $run == "debug" ]];then
set -x
fi
singularity exec $img_dir/$img_name bash -c "source activate firefox_env; \
firefox --no-remote --new-window -CreateProfile shiny_${port_num}; \
firefox --no-remote --new-window -P shiny_${port_num} http://127.0.0.1:$port_num"
# remove the shiny profile ... |
b41ee97f8d3b938321ba926e64a2498aa8fa5fcbc31739770643128eafdbb878 | Shell | 396 | 13 | #!/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
cd server
cp .env.local.local-auth.sqlite .env
medperf aut... |
37df4785f6c6581330fbc5091ea01085dbdc9f05b21ab4a1ab619bb83df368c9 | Shell | 398 | 24 | #!/bin/bash
#SBATCH --job-name=r_homer_motif
#SBATCH --time=12:00:00
#SBATCH --partition=general
#SBATCH --output=r_homer_motif_%j.out
#SBATCH --account=gdkendalllab
#SBATCH --cpus-per-task=10
ml homer/4.11.1
set -x
echo $peakfile
echo $outdir
findMotifsGenome.pl \
$peakfile \
/gpfs0/home/gdkendalllab/lab/refe... |
8e4140e0404fac7a96cbd9bb2efc04dace4398b0b06ef8cd522e6495a1f431ab | Shell | 400 | 14 | #!/usr/bin/env bash
sphinx-apidoc -o docs provdbconnector
sphinx-build -q -a -b html -d docs/build/doctrees docs/ docs/build/html &> travis-doc-test.txt
TEST=$(grep 'failed' travis-doc-test.txt | LC_ALL=C.UTF-8 wc -m)
echo "Lenght of errors = $TEST"
if test $TEST -gt 0
then
echo "Error during build docs "
grep... |
94c9e2a06d737eb87d5697a245dabc1fe208dc8e27914837093743dff1007ab5 | Shell | 403 | 12 | #!/usr/bin/env bash
cd /workspaces/medperf/server
bash ./setup-dev-server.sh < /dev/null &>server.log &
docker pull mlcommons/chestxray-tutorial-prep:0.0.1
docker pull mlcommons/chestxray-tutorial-metrics:0.0.1
docker pull mlcommons/chestxray-tutorial-cnn:0.0.1
docker pull mlcommons/chestxray-tutorial-mobilenetv2:0.0.... |
5245d737ed62a5b3ac99dcf16851531a27262429945e9497105fcbb586a99c08 | Shell | 405 | 19 | #!/bin/bash
set -euo pipefail
if [[ -z ${BRANCH_NAME:-} ]]
then
echo "Make sure to define environment variable BRANCH_NAME."
exit 1
fi
source ops/pipeline/get-docker-registry-details.sh
IMAGE_URI=${DOCKER_REGISTRY_URL}/xgb-ci.cpu_build_r_doc:main
echo "--- Build R package doc"
set -x
python3 ops/docker_run.py ... |
aaffc223fa59da8b1bde05c0dc5be4282e1cbfefe8c90076a52c247dd9c15164 | Shell | 408 | 15 | #!/usr/bin/env sh
# This scripts downloads the mnist data and unzips it.
DIR="$( cd "$(dirname "$0")" ; pwd -P )"
cd "$DIR"
echo "Downloading..."
for fname in train-images-idx3-ubyte train-labels-idx1-ubyte t10k-images-idx3-ubyte t10k-labels-idx1-ubyte
do
if [ ! -e $fname ]; then
wget --no-check-certific... |
ded8c5320ab5a67133469680d930bef99d84a1f9e7b6f24d40b12b596f12617c | Shell | 412 | 12 | #!/usr/bin/env bash
# install ubuntu and python requirements
set -ev
source `dirname ${BASH_SOURCE[0]}`/travis_functions.sh
travis_retry sudo apt-get install -y -qq $(< packagelist-ubuntu-apt.txt)
travis_retry python -m pip install -U pip
travis_retry travis_wait 60 pip install -q -r django/requirements.txt
pip list
... |
44ddd98d5f49d78a1e63088757ab7bd63eea5df7103b01eaa71283a3471bcbdb | Shell | 414 | 8 | kz -k 2 < unmapped.fq > kz.txt
SCRIPT_DIR=$(cd $(dirname $0); pwd)
python3 $SCRIPT_DIR/kz_list_SE.py
list=(`cat kz_filter_list.txt`)
samtools view virusAligned.filtered.sortedByCoord.out.bam | egrep -v "`echo $(IFS="|"; echo "${list[*]}")`" | cut -f3 | sort | uniq -c > virus_counts_kz.txt
samtools view virusAligned.... |
8165911212a08564fae5a7983a9d0c9642cd96ff7084f1d3d4596037baad26cc | Shell | 421 | 17 | CONFIG=$1
GPUS=$2
NNODES=${NNODES:-1}
NODE_RANK=${NODE_RANK:-0}
PORT=${PORT:-29500}
MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
python -m torch.distributed.launch \
--nnodes=$NNODES \
--node_rank=$NODE_RANK \
--master_addr=$MASTER_ADDR \
--nproc_per_node=$GPUS \
... |
8b7e54a566fdb0b85eb2d85893fca50650524b44bc889869251359e69dd4b94d | Shell | 422 | 14 | DB_FARM=./data
SQL_PATH=./monetdb/sql
monetdbd create $DB_FARM
# rm -rf data
# unzip data-local.zip
monetdbd stop $DB_FARM
monetdbd start $DB_FARM
monetdb destroy -f dataflow_analyzer
monetdb create dataflow_analyzer
monetdb release dataflow_analyzer
monetdb status
# running SQL scripts
mclient -p 50000 -d dataflow_ana... |
b674ed0d8a7a13f1b8ff31b13976c950d0e7ab52ba49b7eba228fdb7005dba97 | Shell | 425 | 12 | #!/bin/bash
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
set -ex
mkdir -p packaging/out
version=$(python -c "exec(open('fvcore/__init__.py').read()); print(__version__)")
build_version=$version.post$(date +%Y%m%d)
export BUILD_VERSION=$build_version
conda build -c defaults -c conda-forge ... |
dbba8576290201ef53d7596fd80d49650dec66a8a74ddc81b194cd0fe5d35b6d | Shell | 426 | 16 | #!/bin/bash
#SBATCH --job-name=train_reactome_graph
#SBATCH --mail-type=BEGIN,END,FAIL
#SBATCH --mail-user=jgburk@hawaii.edu
#SBATCH --partition=gpu
#SBATCH --time=3-00:00:00
#SBATCH --nodes=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=32G
#SBATCH --gres=gpu:8
module purge
module load lang/Python/3.9.5-GCCcore-10.3.0
mod... |
60449e414f211ff314c213259a181eff2286b7095726ad782a686f7eb0e0cee5 | Shell | 427 | 18 | # Create a workspace
mkdir -p medperf_tutorial
cd medperf_tutorial
# Download a dataset
url=https://storage.googleapis.com/medperf-storage/chestxray_tutorial/sample_raw_data.tar.gz
filename=$(basename $url)
if [ -x "$(which wget)" ]; then
wget $url
elif [ -x "$(which curl)" ]; then
curl -o $filename $url
fi
t... |
81db821c0890ba332a0c7178354b16148733e08bd50899c4f4cd7779cb4d7c50 | Shell | 427 | 17 | #!/usr/bin/bash
source activate stringtie_v2.2.1
t=4
bam_dir=../map_genome
sample_list=(test)
for s in ${sample_list[@]}
do
bam_list+=($bam_dir/$s.sorted.bam)
done
ln -s ../annot_reduced.gtf annot.gtf
/usr/bin/time stringtie -o out.gtf -G annot.gtf -L ${bam_list[@]} >stringtie.stdout 2>stringtie.stderr
perl -F... |
ec112afe340ff64c221b3266864ff6d76a088e051eb294b9f144d0ba6801ed9e | Shell | 428 | 22 | #!/usr/bin/bash
t=4
s=test
ln -s ../genome_chr22.fa genome.fa
ln -s ../porechop_abi/test.trimmed.fastq.gz $s.fastq.gz
/usr/bin/time minimap2 \
-t $t \
-a \
-x splice \
-ub \
-k14 \
--secondary=no \
genome.fa \
$s.fastq.gz \
2> $s.stderr \
| samtools view -Sb > $s.bam
/usr/bi... |
147f5a826dc6ef8c79d9ef1fdd38c36bf5c360d7e50599d08ce5a98857f0e42f | Shell | 434 | 16 | while getopts b flag; do
case "${flag}" in
b) BUILD_BASE="true" ;;
esac
done
BUILD_BASE="${BUILD_BASE:-false}"
if ${BUILD_BASE}; then
git clone https://github.com/hasan7n/openfl.git
cd openfl
git checkout ce923fc932d45a05c232697d218cb719dd074b72
docker build -t local/openfl:local -f openfl-... |
368a009380ef4f7b0b6863463c10ae34ab6d9a72658f3e26ad57129490f4a4d4 | Shell | 438 | 2 | scp -r f0042x1@discovery7.dartmouth.edu:/dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop_data/derivatives/fmriprep/results/fmriprep/sub-0002/\*/func/\*task-social\*preproc_bold.nii.gz /Users/h/Documents/projects_local/sandbox/fmriprep_bold
scp -r heejung@rolando.cns.dartmouth.edu:/inbox/BIDS/Wager/Wager/1076_spacetop/... |
3ca78ead5723263ff303205a53e83777dc27bfe8456e15b25b1ab8e2f62f841c | Shell | 440 | 17 | step certificate create "MedPerf Root CA" \
./root_ca.crt \
./root_ca.key \
--template ./rsa_root_ca.tpl \
--kty RSA \
--not-after 175320h \
--size 3072
step certificate create "MedPerf Intermediate CA" \
./intermediate_ca.crt \
./intermediate_ca.key \
--ca ./root_ca.crt \
--ca-... |
4df7ad394d97e13216929cd958f853f37eb4c3b730a7a3857c7d6511a43e7968 | Shell | 440 | 16 | while getopts b flag; do
case "${flag}" in
b) BUILD_BASE="true" ;;
esac
done
BUILD_BASE="${BUILD_BASE:-false}"
if ${BUILD_BASE}; then
git clone https://github.com/hasan7n/openfl.git
cd openfl
git checkout ce923fc932d45a05c232697d218cb719dd074b72
docker build -t local/openfl:local -f openfl-... |
5d969194e282caecea911b1a1fd9ba1451f961917b45eeedd8c78223132e3400 | Shell | 440 | 21 | while getopts "d:" opt
do
case "$opt" in
d ) parameterD="$OPTARG" ;;
? ) helpFunction ;; # Print helpFunction in case parameter is non-existent
esac
done
plink_file=$parameterD
# Download hg19 genome build
wget http://hgdownload.soe.ucsc.edu/goldenPath/hg19/database/snp151Common.txt.gz
gunzip snp15... |
118fc3a4cb8fc313342106c96c55905bed8ae3214c49303bf94fbf4ac2e1bca1 | Shell | 442 | 16 | while getopts b flag; do
case "${flag}" in
b) BUILD_BASE="true" ;;
esac
done
BUILD_BASE="${BUILD_BASE:-false}"
if ${BUILD_BASE}; then
git clone https://github.com/hasan7n/openfl.git
cd openfl
git checkout ce923fc932d45a05c232697d218cb719dd074b72
docker build -t local/openfl:local -f openfl-... |
375982c85ad591f12f4d4acbc29a7adefa687569267516a25f24cbee735c0dd2 | Shell | 444 | 18 | #!/bin/bash
_mmseqs() {
local cur
COMPREPLY=()
cur="${COMP_WORDS[COMP_CWORD]}"
if [[ ${COMP_CWORD} -eq 1 ]] ; then
COMPREPLY=( $(LC_COLLATE=C compgen -W "$(mmseqs shellcompletion 2> /dev/null)" -- "${cur}") )
return 0
fi
if [[ ${COMP_CWORD} -gt 1 ]] ; then
COMPREPLY=( $(LC_COLLATE=C compgen -f -W "$(mmseq... |
2a0adfd454aa391ec422b3831b4742e3d800c52feeabaa9a08d02b8c76e30766 | Shell | 449 | 26 | #!/usr/bin/env bash
# build the docs
cd docs
make clean
make html
cd ..
# commit and push
git add -A
git commit -m "building and pushing docs"
git push origin master
# switch branches and pull the data we want
git checkout gh-pages
rm -rf .
touch .nojekyll
git checkout master docs/build/html
mv ./docs/build/html/* .... |
7cd29fe56086a2ae2ccb6d11c4122ce6c4cbe8d523c1912788f691259d0e8233 | Shell | 454 | 20 | #!/bin/bash -e
#requires existing installation of miniconda3 in home directory
usage() { echo "Usage: $0 <path_to_miniconda_installation>" 1>&2; exit 1; }
[ $# -ne 1 ] && usage
miniconda_install_dir=$1
export PATH="${miniconda_install_dir}/bin:$PATH"
conda env create -f ./environment.yml --solver libmamba
cp cor... |
64e6f7dd847dcf7e591cdc08c859d45282a13a62f7259c992437cc37dca8dccc | Shell | 457 | 28 | #!/bin/sh
CFLAGS=$CFLAGS_OLD
export CFLAGS
unset CFLAGS_OLD
LDFLAGS=$LDFLAGS_OLD
export LDFLAGS
unset LDFLAGS_OLD
# Unset rpy2 library path
LD_LIBRARY_PATH=$LD_LIBRARY_PATH_OLD
export LD_LIBRARY_PATH
unset LD_LIBRARY_PATH_OLD
QT_QPA_PLATFORM=$QT_QPA_PLATFORM_OLD
export QT_QPA_PLATFORM
unset QT_QPA_PLATFORM_OLD
#... |
f659d93114654da3e82e894056479a9d10fddefa815a0b1a0aadcc595eca7607 | Shell | 458 | 20 | CONFIG=$1
CHECKPOINT=$2
GPUS=$3
NNODES=${NNODES:-1}
NODE_RANK=${NODE_RANK:-0}
PORT=${PORT:-29500}
MASTER_ADDR=${MASTER_ADDR:-"127.0.0.1"}
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
python -m torch.distributed.launch \
--nnodes=$NNODES \
--node_rank=$NODE_RANK \
--master_addr=$MASTER_ADDR \
--nproc_per... |
3a335fe9deca8d6be87ebd50a7bc8e2527b3735145f7282451171af84ed6f7de | Shell | 460 | 11 | # This is the example script to run distributed xgboost on AWS.
# Change the following two lines for configuration
export BUCKET=mybucket
# submit the job to YARN
../../../dmlc-core/tracker/dmlc-submit --cluster=yarn --num-workers=2 --worker-cores=2\
../../../xgboost mushroom.aws.conf nthread=2\
... |
dec4e865bd8ecf22ff09c126606becc3264e16f0fcb7794b524ec8f2e6b34c47 | Shell | 460 | 22 | #!/bin/bash
#Go Interactive
#sh ~/go_interactive_gpus.sh
#unzip ./zsl_validation.zip -d zsl_validation/
#cd ~/zsl_validation/
module purge
module load lang/Python/3.9.5-GCCcore-10.3.0
module load system/CUDA/11.0.2
python ReactomeGraphClassificationZSLValidationGTEX_Mana.py
#Editing
#module purge
#module load tools... |
a6318e19af4fba5697feec9a27fd4c132128017033907c0d742ad8c8a5d2abb8 | Shell | 464 | 15 | #!/bin/bash
for i in {1..10}
do
python3 run_baseline.py --setting interpolation --fold $i --cpus 128 --model MuSyC --scale
python3 run_baseline.py --setting interpolation --fold $i --cpus 128 --model Zimmer --scale
done
for i in {1..10}
do
python3 run_baseline.py --setting extrapolation --fold $i... |
d6047594afffe0c6cd30af3676716b5fd2fde049356295437a45d677ec0debd9 | Shell | 464 | 9 | DATA_PATH=/home/hasan_kassem/rano_data/testdata_small/data
LABELS_PATH=/home/hasan_kassem/rano_data/testdata_small/labels
MODEL=/home/hasan_kassem/additional_files
RES=/home/hasan_kassem/rano_data/tmppp_results
rm -rf $RES
mkdir -p $RES
GPUS="1"
medperf --gpus=$GPUS container run_test --container ./container_config.yam... |
b2a224e8b347224ed376ddf9fc9355aeecd2bc5eb1229712a4a11bbc266ab121 | Shell | 466 | 11 | ## Log into AWS ECR (Elastic Container Registry) to be able to pull containers from it
## Note. Requires valid AWS credentials
set -euo pipefail
source ops/pipeline/get-docker-registry-details.sh
echo "aws ecr get-login-password --region ${ECR_AWS_REGION} |" \
"docker login --username AWS --password-stdin ${DOCK... |
00ce4911a364e88d4e861a49b8e4d7ff7a9170b9d077054573e796bfae7ac4de | Shell | 467 | 10 | #!/bin/bash
python train.py --dname=mimic3 --epochs=100 --cuda=1 --num_labels=25 --num_nodes=100 --num_labeled_data=500
python train.py --dname=cradle --epochs=100 --cuda=1 --num_labels=1 --num_nodes=200 --num_labeled_data=all
python train.py --dname=mimic3 --epochs=100 --cuda=1 --num_labels=25 --num_nodes=100 --num_... |
3477b69c839a78e75619cbe0c6790aa9f53600fe520affcc2a79e169bafbbdf4 | Shell | 467 | 20 | #!/usr/bin/env sh
# This script converts the cifar data into leveldb format.
set -e
EXAMPLE=examples/cifar10
DATA=data/cifar10
DBTYPE=lmdb
echo "Creating $DBTYPE..."
rm -rf $EXAMPLE/cifar10_train_$DBTYPE $EXAMPLE/cifar10_test_$DBTYPE
./build/examples/cifar10/convert_cifar_data.bin $DATA $EXAMPLE $DBTYPE
echo "Comp... |
a243fef9f323157a9cb00537aeee4831b5d14ce232d31838b5e0157d5c649329 | Shell | 467 | 22 | #!/bin/bash
## Run C++ tests for i386
## Companion script for ops/pipeline/test-cpp-i386.sh
set -euox pipefail
export CXXFLAGS='-Wno-error=overloaded-virtual -Wno-error=maybe-uninitialized -Wno-error=redundant-move -Wno-narrowing'
mkdir -p build
pushd build
cmake .. \
-GNinja \
-DGOOGLE_TEST=ON \
-DUSE_DMLC_G... |
65c35870ff14390250bfac07aa2a30570a2e8ee880d4733b8d11887c73826294 | Shell | 468 | 18 | #!/usr/bin/bash
source activate bambu_v3.4.0
t=4
bam_dir=../map_genome
sample_list=(test)
for s in ${sample_list[@]}
do
bam_list+=($bam_dir/$s.sorted.bam)
done
ln -s ../genome_chr22.fa genome.fa
ln -s ../annot_reduced.gtf annot.gtf
/usr/bin/time Rscript --slave --vanilla bambu.R $t genome.fa annot.gtf ${bam_li... |
13cf6d35b2af130a16574345d44f6f401b5263e0f1095ec104da94b27d2df432 | Shell | 481 | 14 | RECIPES=~/github/bioconda-recipes # location of the cloned fork
REMOTE=bioconda # bioconda/bioconda-recipes remote
UPDATED_RECIPE=/tmp/sambamba.yaml
python3 bioconda_yaml_gen.py > $UPDATED_RECIPE
VERSION=`grep version $UPDATED_RECIPE | cut -d\' -f2`
cd $RECIPES
git checkout master
git pull $REMOTE m... |
90b5dfa7fe1b519f00bbfda498706a74e1e3c4f5ef43906267b617c4f3944085 | Shell | 481 | 14 | # creates a Docker image that will perform the processing
# as the NN model file is not present on the GitHub repository, it will be downloaded if it is not present
model_file=./nn/mouse_v5.model
if test -f "$model_file"; then
echo "$model_file already present"
else
#retrieve NN model
curl -o "$model_file" "https:... |
153dfb87b73d3003f82ba0855e198dd3d5b872a116ea7ef64bcf2bef2c0f04d4 | Shell | 483 | 10 | kz -k 2 < unmapped_1.fq > kz_1.txt
kz -k 2 < unmapped_2.fq > kz_2.txt
SCRIPT_DIR=$(cd $(dirname $0); pwd)
python3 $SCRIPT_DIR/kz_list_PE.py
list=(`cat kz_filter_list_1.txt` `cat kz_filter_list_2.txt`)
samtools view virusAligned.filtered.sortedByCoord.out.bam | egrep -v "`echo $(IFS="|"; echo "${list[*]}")`" | cut -f... |
1a4894893ea6e7720f98d03bab8284cf48bdd8cbd8f42dd1350c8615a903daa8 | Shell | 486 | 23 | #!/bin/bash
# Build documentation for display in web browser.
PORT=${1:-4000}
echo "usage: build_docs.sh [port]"
# Find the docs dir, no matter where the script is called
ROOT_DIR="$( cd "$(dirname "$0")"/.. ; pwd -P )"
cd $ROOT_DIR
# Gather docs.
scripts/gather_examples.sh
# Split caffe.proto for inclusion by lay... |
13629034762fdc2b1fbc3604d0452a726826924066d4cd9d83e53a6109bd7ce7 | Shell | 495 | 20 | #!/bin/sh
#SBATCH -a 1-1100
#SBATCH --mem-per-cpu 4g
#SBATCH -J job_grid_simulation_group
#SBATCH --output=%x_%j.out
#SBATCH --error=%x_%j.err
ulimit -s unlimited
echo running on `hostname`
echo starting at
date
CONDITION=`cat ./grid_simulation_group_parameters.txt | awk -v line=$SLURM_ARRAY_TASK_ID '{if (NR == line)... |
efdd60c9f32e94b841b7c51d828896b9905b11870532f8cc725e35531e3dc528 | Shell | 495 | 24 | #!/bin/bash
#
#SBATCH -J mriqc
#SBATCH --array=1
#SBATCH --time=24:00:00
#SBATCH -n 1
#SBATCH --cpus-per-task=16
#SBATCH --mem-per-cpu=4G
#SBATCH -p <partitions>
# Outputs ----------------------------------
#SBATCH -o log-ng/%A-%a.out
#SBATCH -e log-ng/%A-%a.err
#SBATCH --mail-user=<email>
#SBATCH --mail-type=ALL
# --... |
077167fc9bc0adb64a776c096db21ba20810653d1b8612ee74020612ae9e594c | Shell | 500 | 19 | #!/bin/bash
set -eo pipefail
if [[ "$1" == "" ]] ; then
echo "Usage: $0 <PROJECT_PATH>"
exit 1
fi
PROJECT_PATH="$1"
ARCH=$(uname -m)
export HDF5_VERSION="2.2.0"
export HDF5_DIR="$PROJECT_PATH/cache/hdf5/$HDF5_VERSION-$ARCH"
source $PROJECT_PATH/ci/get_hdf5_if_needed.sh
if [[ "$GITHUB_ENV" != "" ]]; then
... |
5705994a37baabc1c2105dc9a90b9eb73ac5ed2455623e46ee385ce35e2bc331 | Shell | 500 | 18 | #!/bin/bash -l
#SBATCH --job-name=glm
#SBATCH --nodes=1
#SBATCH --ntasks=4
#SBATCH --mem-per-cpu=8gb
#SBATCH --time=01:00:00
#SBATCH -o ./qc/qc_%A_%a.o
#SBATCH -e ./qc/qc_%A_%a.e
#SBATCH --account=DBIC
#SBATCH --partition=standard
#SBATCH --array=1-10%10
#33%10
conda activate spacetop_env
echo "SLURMSARRAY: " ${SLURM_... |
8030ae9df46fbf728251f74da8a08286132aedb6989483d01e6334e80823e74d | Shell | 500 | 14 | #!/usr/bin/env bash
# name of partition with high memory
high_mem_partition=general
# name of partition for general use
general_partition=general
# memory in GB for jobs that require high memory like STAR
high_mem=128
# memory in GB for jobs that require medium memory like feature counts
med_mem=32
# memory in GB for ... |
edfad10eaa9e387b710604f0ddfc54b68f4ad20249c12cea7d195607f9e94976 | Shell | 501 | 33 | #! /bin/bash
unset -v EMAIL
while getopts e: flag
do
case "${flag}" in
e) EMAIL=${OPTARG};;
esac
done
: ${EMAIL:?Missing -e}
get_url() {
while read -r line <&"$1"; do
if [ $(echo $line | grep "^https://") ]; then
echo $line
break
fi
done
}
coproc medperf auth login -e $... |
7364ea16f3a3dab616244a4304b7c49ab651148da2a87d07713fc6978e23208a | Shell | 506 | 19 | #!/usr/bin/env sh
# This scripts downloads the CIFAR10 (binary version) data and unzips it.
DIR="$( cd "$(dirname "$0")" ; pwd -P )"
cd "$DIR"
echo "Downloading..."
wget --no-check-certificate http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz
echo "Unzipping..."
tar -xf cifar-10-binary.tar.gz && rm -f cifar-1... |
fb016add6c89e4cc9e0d8f4ec8d6121b1e2bfcded2aa777b685cd12bbcfc1bb7 | Shell | 508 | 17 | #!/bin/bash
#PBS -l select=1:ncpus=4:mem=8gb
#PBS -l walltime=0:30:00
#PBS -N posthoc_analysis
# Script for running the post-hoc analysis after primary and secondary scripts have been run.
# Load environment
module load anaconda3/personal
source activate graphtrip
cd ~/projects/graphTRIP/scripts
# Run post-hoc anal... |
368bdd6060a122b7cbdb29a9fc2c6d25f5cc2cb9e983ff912278db64394e7eb1 | Shell | 509 | 11 | #!/bin/bash -l
#SBATCH --job-name=infphio.HLA.ILMN.extract.genome
#SBATCH --nodes=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=80G
#SBATCH --partition=shared
#SBATCH --time=166:0:0
#SBATCH --workdir=/home-1/dkim136@jhu.edu/infphilo/hisat2/evaluation/tests/HLA_novel
/home-1/dkim136@jhu.edu/infphilo/hisat2/evaluation/test... |
be2bf3509da890f3753a697db3dbbc0097b5bd66047e6da2b987dda47739b6ce | Shell | 511 | 14 | python3 ../../src/ref/bampod5kmersig-witharrow-sigalign.py \
-b ../input/ang_0.sorted.bam \
-p ../input/ang_0_downsampled.pod5 \
-o ../output/ang_0
python3 ../../src/ref/bampod5kmersig-witharrow-sigalign.py \
-b ../input/ang_500.sorted.bam \
-p ../input/ang_500_downsampled.pod5 \
-o ../output/a... |
985b1128120ef918b44f1e9ba2bdb2f2634656dcf01d2bf1050fb81d986daa32 | Shell | 515 | 22 | #!/bin/bash
#PBS -l select=1:ncpus=4:mem=16gb
#PBS -l walltime=02:00:00
#PBS -N preprocessing
#PBS -J 1-6
module load anaconda3/personal
source activate graphtrip
cd ~/projects/graphTRIP/
atlases=('schaefer100' 'schaefer200' 'aal')
studies=('psilodep2' 'psilodep1')
# Calculate indices for the current job
atlas_idx... |
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