sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
19a75afa31711b10124740d4e654a8b418ad7d00cee5854c1af3871093309662 | Shell | 125 | 6 | #!/usr/bin/env sh
set -e
TOOLS=./build/tools
$TOOLS/caffe train --solver=examples/siamese/mnist_siamese_solver.prototxt $@
|
444e482874c57f33d657e425f88f5469ed17297820832c5d112587fccf124ad1 | Shell | 126 | 6 | rm -rf ./workspace_agg
rm -rf ./workspace_col1
rm -rf ./workspace_col2
rm -rf ./workspace_col3
rm -rf ./ca
rm -rf ./for_admin
|
0c3501a2538ce0f5055f09c34865e096e333e9c97c71cd8a9d54ec86adf690a9 | Shell | 127 | 2 | docker build -t mlcommons/medperf-test-cc-benchmark:0.0.0 -f Dockerfile .
docker push mlcommons/medperf-test-cc-benchmark:0.0.0 |
8f60c29fef13d625600f0fceb91e0e80a28c7fc8b30c41d06754599cdde6cdf4 | Shell | 127 | 2 | #!/bin/bash
wget -q -O - --no-check-certificate "https://genome.ucsc.edu/cgi-bin/hgBlat?userSeq=$1&type=DNA&db=$2&output=json"
|
b58e04fcdd1c1a75162bee90a5dbd984bf8ecfa8268dd38cdd139565b3b143b5 | Shell | 129 | 6 | #!/bin/bash
set -m
docker build -t modules-test --build-arg ENVIRONMENT_MODULES_VERSION="5.2.0" .
docker run --rm modules-test
|
f9630eccf681d02d856b16780057edc037ab133ad8c0b761e47839862a428531 | Shell | 131 | 7 | source $HOME/.bashrc
for((i=1;i<=5;i++));
do
python3 run.py --func LunarLander --dims 100 --iterations 10000 --method DANTE
done
|
a52e20f5ffdf41448fb355e83492ecd46d23eac27b0526d8d4320da2c3935532 | Shell | 134 | 5 | #!/bin/bash
# go interactive before doing anything on the hpc
srun -I30 -p sandbox -N 1 -c 1 --mem=6G -t 0-01:00:00 --pty /bin/bash
|
d27e74a1b3f288be9527bf228ef19b710016f62776961fcee0f2d122f5f4a3bd | Shell | 135 | 6 | ldapmodify -Y EXTERNAL <<EOF
dn: cn=user01,ou=users,dc=example,dc=org
changetype: modify
replace: loginShell
loginShell: /bin/bash
EOF
|
329530211b8edff33fe3dafe90fb4845cf7bc885b21e206dc67fd99369ec56a1 | Shell | 137 | 2 | docker build -t mlcommons/medperf-cc-rano-modelonly:0.0.0 -f Dockerfile.modelonly .
docker push mlcommons/medperf-cc-rano-modelonly:0.0.0 |
12b5221e47b703c5671546958954177eea83cf930fd04fb9c9b2be28a24bc2d7 | Shell | 138 | 4 | # starts the DeepEthoProfiler application.
# the only parameters is the maximum number of Docker instances
python3 ui/pheno_ui.py 2
|
6f422e697c62300fe74b55d10b19974125443744496e8662010d5434dca1977b | Shell | 138 | 6 | rsync -avuP \
--include='*_final.cif' \
--include='*/' \
--exclude='*' \
rsync://rsync.pdb-redo.eu/pdb-redo
./PDB_REDO |
dfed053060e7516c4772719a1fb1ba02e04d06e7627f8370acbcc0fa15c2387b | Shell | 139 | 8 | #!/usr/bin/env sh
set -e
TOOLS=./build/tools
$TOOLS/caffe train \
--solver=examples/cifar10/cifar10_full_sigmoid_solver.prototxt $@
|
bd1686e87c47dc2646c1fc67d0b46961d1e4adb5cf50a1e6dc3c4b41436d36b8 | Shell | 140 | 3 | #!/bin/bash
glslangValidator -V -x -o glsl_shader.frag.u32 glsl_shader.frag
glslangValidator -V -x -o glsl_shader.vert.u32 glsl_shader.vert
|
6b457d08f7f5378d426a36cd77173eb7210cc548287946ef8b16c71d7764292a | Shell | 141 | 11 | #!/bin/bash
## Select pipeline
pipline=0.0_ps_Pipeline_v4.sh
## User varibles (Example)
expID=SRR3304509
# Sent pipeline
$pipline $expID
|
d7acb72563fe0d6ea25632d2d276ddf1dac7b1519a3e8cd36dc092b1361a4bb5 | Shell | 142 | 8 | #!/usr/bin/env sh
set -e
TOOLS=./build/tools
$TOOLS/caffe train \
--solver=examples/cifar10/cifar10_full_sigmoid_solver_bn.prototxt $@
|
a9b4784f0814372eeca4f67629df2086698fb1fa6f5d9a94ebffd50487ff70b6 | Shell | 145 | 6 | #!/usr/bin/env bash
if [[ $OSTYPE == linux-gnu ]]; then
sed -i "s/static const/static/g" $1
else
sed -i ".bak" "s/static const/static/g" $1
fi
|
d7c7c9b00cebc16722dc2e78028278df14fda67441f22caaccd96b069cacbdb3 | Shell | 146 | 8 | #!/bin/bash
export LC_ALL=C.UTF-8
export LANG=C.UTF-8
echo "starting ray worker node"
ray start --address $1 --redis-password=$2
sleep infinity
|
84c0423804b75af9fdea70bf9c44d9a5f0bc9d66f3969681c038d4e7f825007a | Shell | 147 | 2 | docker build -t mlcommons/medperf-confidential-benchmark-base:0.0.0 -f Dockerfile .
docker push mlcommons/medperf-confidential-benchmark-base:0.0.0 |
c27d38e4751bf1f1cee0361101b27126d2991b55cb4ed2bb6e68b55838889c57 | Shell | 147 | 8 | # self-driving virtual lab for Electron Ptychography reconstruction
source $HOME/.bashrc
conda activate tf_25 #your environment
python3 run.py
|
fe7c67e97cf3dca5b560161d9b83c169f83bff88f6656b8bef84109c7da2f0a0 | Shell | 147 | 2 | docker build -t mlcommons/medperf-cc-chestxray-modelonly:0.0.0 -f Dockerfile.modelonly .
docker push mlcommons/medperf-cc-chestxray-modelonly:0.0.0 |
7755cf9a778326ca1525e7214f3e3f7616d0196f154b5a4368b40195c75ddba2 | Shell | 148 | 8 | # self-driving virtual lab for architected materials design
source $HOME/.bashrc
conda activate tf_25 #your environment
python3 run.py --iter 1
|
86c0fa1cf0af2e996cea4001f5dbe719a270e907d119c2effaa4e21cf379b3a1 | Shell | 150 | 2 | # creates the image containing the software environment needed for processing
docker build --tag ethoprofiler_nn_base_av -f ./nn/Dockerfile_base ./nn
|
435e538136a8483c1cb235df4c71462ad71dbde965e829301215c6dbfaeeb848 | Shell | 151 | 5 | #!/bin/bash
# Launch celery worker
cd /home/django/projects/
exec /home/env/bin/celery -A mysite worker -l info --pidfile=/var/run/catmaid/celery.pid
|
41936c081cfd7724e1998a3f39c10cf2f6af61e8441b1891b10aaa8e66c71172 | Shell | 152 | 8 | #!/bin/bash
python scripts/generate_features.py -n 16 \
-i '/your/eeg/dir/with/hdf5files/' \
-c 'configs/baruto.yml' \
-o 'features/' \
-a 1
|
d4499ee78b270e624e9fdc7e670c04a2191ca941915963012cc56b49da713879 | Shell | 152 | 4 | #!/bin/bash
sphinx-apidoc -f -P -o source ../encodermap/ ../encodermap/examples/ -V 3.0.0 -H EncoderMap --templatedir _templates
# make html
# make pdf
|
f052511f24665ba0cfba507e54d8bf034c57690c5ec828aba3856380c09c9cce | Shell | 152 | 2 | docker run --rm -u $(id -u):$(id -g) -it -p 6006:6006 -p 8888:8888 -v $(pwd)/notebooks:/tf/notebooks --name emap encodermap
# docker exec -it emap bash
|
174bbe9e8bc747ab8e509abac365ae6d7b57b2feb2610de4fc7a9073c17f1f3f | Shell | 153 | 5 | #!/usr/bin/env bash
CONFIG=$1
python -m torch.distributed.launch --nproc_per_node=8 --master_port=4321 basicsr/train.py -opt $CONFIG --launcher pytorch |
114ada5baac9ce331db6dd366913f4aaef281f5e51919a6bc8be634a31fa5927 | Shell | 154 | 1 | CARGO_TARGET_WASM32_WASI_RUNNER="wasmtime --wasm-features simd --" cargo test --target=wasm32-wasi --all-targets --features simd_wasm -- --nocapture "$@"
|
7b40324d6d084d4111184286d5390b026dfdb9c67032b589ae89fd715b02b1ec | Shell | 156 | 1 | CARGO_TARGET_WASM32_WASI_RUNNER="wasmtime --wasm-features simd --" cargo run --target=wasm32-wasi --example accuracy --release --features simd_wasm -- "$@"
|
5bac0dbaa50ab66a36f0fce266ce8d625481ac5effe05c8f293cf71c00de66f4 | Shell | 160 | 8 | #!/bin/bash
echo "Rename in all .m files " + $1 + " to " + $2
#find . -type f -name '*.m' -exec sed -i '' s/$1/$2/ {} +
perl -pi -w -e 's/'$1'/'$2'/g;' *.m
|
97dd20d88ff76b6c426f774eabf48539c6ff15afdb5e341f592806352048bcb9 | Shell | 160 | 5 | medperf auth logout
medperf auth login -e testbo@example.com
medperf association approve -b 1 -d 1
medperf auth logout
medperf auth login -e testdo@example.com
|
94e3c774ce9d595c01bf79a2f189296c2a7b4d8805af4e48b593ce76e6bdee70 | Shell | 162 | 8 | #!/usr/bin/env bash
set -ex
echo "Installing Python 3.6"
sudo add-apt-repository -y ppa:deadsnakes/ppa
sudo apt-get update -q
sudo apt-get install -y python3.6
|
04eee7a81f975d594df542dee8c81da107b3373ec47196d567c04a59fd044b79 | Shell | 163 | 6 | #!/bin/bash
source activate sartools_env;
cd /scripts
R -e "if(length(.libPaths())>1) .libPaths(.libPaths()[-1]); shiny::runApp(port=$port_num)"
conda deactivate
|
4f510d9bcfda4f01aa74f81d5002e964fea37dd729d6a0fee3bf606316abbdad | Shell | 163 | 7 | # self-driving virtual lab for cyclic peptide design
source $HOME/.bashrc
conda activate tf_25 #your environment
python3 ./scripts/DOTS_Cyclic_Peptide_Design.py |
3fb693e9ec6cb1da524d38322decf9aac45beec1d3795292f57844c56a697c57 | Shell | 164 | 8 | #!/bin/bash
echo "Rename in all .m files " + $1 + " to " + $2
#find . -type f -name '*.m' -exec sed -i '' s/$1/$2/ {} +
perl -pi -w -e 's/'$1'/'$2'/g;' ./*/*.m
|
c2af039b46ebab81cf0ca50a4ca7817c302e9ba8d4847b92fa979401b94d648d | Shell | 165 | 6 | # self-driving virtual lab for NasBench
source $HOME/.bashrc
conda activate tf_25 #your environment
python3 run.py --samples 200 --method random --random_seed 44
|
57e004d91b62fc53b9320569ab68814d105f0ca1996f5bb8023fb718f96cf036 | Shell | 170 | 11 | #!/bin/bash -e
CFGFILE="default.conf"
. "$CFGFILE"
for i in "${!PATHS[@]}"
do
printf "export %s=\"%s\"\n" "${i}" "${PATHS[$i]}"
export "${i}=${PATHS[$i]}"
done |
7899a7f831a90f914b96e3b25d30a758a97fe4e3e76c2f6ae2926dc5bb1d3dd6 | Shell | 170 | 4 | ## Update the following line to test changes to CI images
## See https://xgboost.readthedocs.io/en/latest/contrib/ci.html#making-changes-to-ci-containers
IMAGE_TAG=main
|
941bec25592c42eb37b14e0330199950ddae1a459da4e4199b0bc3892cbe9014 | Shell | 170 | 5 | #!/bin/sh
samtools view -h ${1} | \
grep -v "AAAAAAAAAAAAAAAAAAAA" | grep -v "TTTTTTTTTTTTTTTTTTTT" | grep -v "TGTGTGTGTGTGTGTGTGTGTGTGTGTGTGTG" | \
samtools view -bS - |
bcd791784b748a20f8eab401cebe1dc0a6f2252a5b1fde641b6e865f20d9bfda | Shell | 177 | 12 | #!/bin/bash
## Select pipeline
pipline=0.0_ps_Pipeline_v4.sh
## User varibles (Example)
expID=SRR3304509
fastqDIR=../fastq
# Sent pipeline
$pipline $expID is-dump $fastqDIR
|
5fbcbb9cfc3fbc6bbbf002c7d366960d86c8819777365e10b62400ab9e697032 | Shell | 185 | 5 | #!/bin/bash
script_path="fengshen/utils/llama_convert/hf_to_fs.py"
input_dir="llama13b_hf"
output_dir="llama13b_fs"
python $script_path --input_path $input_dir --output_path $output_dir |
8f6868c56fe5cd8d677a52a1b557d5493bc0e1e86ca3b82909ea8483116ac2d7 | Shell | 185 | 6 | #!/usr/bin/env bash
if [[ $OSTYPE == linux-gnu ]]; then
sed -i -r 's/^case ([0-9]+)/goto case; case \1/g' $1
else
sed -i -r '.bak' 's/^case ([0-9]+)/goto case; case \1/g' $1
fi
|
19ecf646a2e1678046ed81c7854bee0e0152d28d3248b0cdba35b8ec43874c53 | Shell | 186 | 5 | rm -rf mlcube_agg/workspace/final_weights
rm -rf mlcube_agg/workspace/logs
rm -rf mlcube_agg/workspace/plan.yaml
rm -rf mlcube_col*/workspace/logs
rm -rf mlcube_col*/workspace/plan.yaml
|
a4430a964580c781003c26823acc9aebd8150b42fe178770bb019f1bab9d04d8 | Shell | 192 | 8 | #!/bin/bash
cd "$(dirname "$0")"
set -e
source_files=`find miniscope/ src/ python/ -type f \( -name '*.c' -o -name '*.h' -o -name '*.cpp' -o -name '*.hpp' \)`
clang-format -i $source_files
|
230a9cf2a3527f8089f5592fb69e2400a748780989f291d62998fb0c54450743 | Shell | 193 | 7 | mkdir -p $PREFIX/bin
cp $SRC_DIR/BUSCO_phylogenomics.py $PREFIX/bin/
cp $SRC_DIR/count_buscos.py $PREFIX/bin/
chmod +x $PREFIX/bin/BUSCO_phylogenomics.py
chmod +x $PREFIX/bin/count_buscos.py
|
44f9b3ae3ff70689047972765269f57393269c053211ca2c18ff1b486d288e19 | Shell | 194 | 10 | #!/bin/bash
#SBATCH --job-name=run_samtools_merge
#SBATCH --partition=general
module load SAMtools/1.15
set -x
samtools merge - $infiles | samtools sort -o $outfile -
samtools index $outfile
|
c6772734bda4781d1cb7806b94da90ef1d9124880c9bd1264dfc1956039a6aec | Shell | 194 | 9 | #!/bin/bash
export LC_ALL=C.UTF-8
export LANG=C.UTF-8
echo "starting ray head node"
# Launch the head node
ray start --head --node-ip-address=$1 --port=6379 --redis-password=$2
sleep infinity
|
f4f394d10b45729d4b345a19bd2b51a7dd0f27efd51f4ca7cfb001c81c2fb9ac | Shell | 200 | 5 | mkdir -p SKEMPI_v2
cd SKEMPI_v2
wget https://life.bsc.es/pid/skempi2/database/download/skempi_v2.csv
wget https://life.bsc.es/pid/skempi2/database/download/SKEMPI2_PDBs.tgz
tar -xzvf SKEMPI2_PDBs.tgz
|
5ad13109abd34dae1fee3c77ca6dbf03993b105f7265dc87982196b9dc56232d | Shell | 201 | 13 | '''
Compile IMC source code and build executable mex file
Author: Yunan Luo
Date: July 29, 2018
'''
unzip leml-imf-src.zip
cd leml-imf
make matlab
cp matlab/train_mf.mexa64 ../
cd ..
rm -r leml-imf
|
36719df6b407e02356ed0a84f1f6926aebed4f25beafb8df0e808d01c226116e | Shell | 203 | 2 | "/Applications/MATLAB_R2024b.app/toolbox/shared/coder/ninja/maca64/ninja" -t compdb cc cxx cudac > compile_commands.json
"/Applications/MATLAB_R2024b.app/toolbox/shared/coder/ninja/maca64/ninja" -v "$@"
|
44a4ed656ab3debfa8f6f6fc4539da6bacc29289b5b35e0b5b97ed83427f41bd | Shell | 203 | 9 | set -eo pipefail
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
if [[ -v MEDPERF_ON_PREM ]]; then
bash "$SCRIPT_DIR/entrypoint_dev.sh"
else
bash "$SCRIPT_DIR/entrypoint_prod.sh"
fi
|
60881cfd8080fc686a177698283e9be9e1059f2043a4322affd24c6bf7f6066f | Shell | 207 | 7 | #!/usr/bin/env sh
set -e
./build/tools/caffe train \
--solver=models/bvlc_reference_caffenet/solver.prototxt \
--snapshot=models/bvlc_reference_caffenet/caffenet_train_10000.solverstate.h5 \
$@
|
8421b40037a9ae963d426870d2475396b61ab64853ab7d7b9669b5131b2e433b | Shell | 209 | 11 | #!/bin/bash
# Script to run a benchmark optimisation on CSCS viz cluster
LOGFILENAME=logs/l5pc_benchmark.stdout
rm -rf ${LOGFILENAME}
sbatch -A proj37 l5pc_benchmark.sbatch
tail -f --retry ${LOGFILENAME}
|
5cc27a3e0856babffec26870426eceb924b04efd074289ceaf120df1ac72d063 | Shell | 211 | 11 | #!/bin/bash
#SBATCH --job-name=nam
#SBATCH --cpus-per-task=128
#SBATCH --nodes=1
#SBATCH --partition=all
module load cuda/cuda-11.0
source ~/venv/bin/activate
python3 -u ray_train.py -m --config=$1 --name=$2
|
8d0ae93cd9f3ef75be935d5d5c209dac3101a78f4b2f99f94b05f9ba78807d20 | Shell | 212 | 8 | #!/bin/bash
#SBATCH --cpus-per-task=1
#SBATCH --job-name=RunPerCell
nextflow run PC.nf \
-profile singularity \
--human_fa '/path/to/downloaded/genome.fa' \
--mouse_fa '/path/to/downloaded/genome.fa' |
055a99453f52fc417bcde6d6dc6eed31a56fc00d1b49180ac3a31dabc60873c1 | Shell | 216 | 12 | #!/bin/bash
#SBATCH --job-name=test
#SBATCH --output=res.txt
#SBATCH --partition=debug
#SBATCH --time=10:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=100
srun hostname
srun pwd
srun sleep 2
|
e6bbba21b575b6bafcf9f2076b831f90defe4f918813a376b1a62cca90af8409 | Shell | 222 | 5 | #!/bin/bash
script_path="fengshen/utils/llama_convert/convert_fs_llama_tp.py"
input_dir="llama13b_fs"
output_dir="llama13b_fs_tp8"
python $script_path --input_dir $input_dir --output_dir $output_dir --model_parallel_size 8 |
73a92bd3320ad4c1797ebb20cbaed22f507216e31094c0c0cf52392011f1adae | Shell | 223 | 11 | #!/bin/bash
## Test installing Python XGBoost from source distribution
set -euox pipefail
cd python-package
python --version
python -m build --sdist
pip install -v ./dist/xgboost-*.tar.gz
cd ..
python -c 'import xgboost'
|
ac26bc963daad936c67f7153fd77b2e376bcc0e5b9e741b9679808558c9ef236 | Shell | 227 | 12 | #!/bin/bash
# Software
fastqdump="/opt/ohpc/Taiwania3/pkg/biology/SRAToolkit/sratoolkit_v2.11.1/bin/fastq-dump"
# User vars
SRA_file=$1
fastq_Path=$2
# Program
$fastqdump --split-files --gzip --outdir $fastq_Path $SRA_file
|
7d54d7a8121b29acd49384da96f2a7a9f6349df744ab5ea82d34f408a540e3d5 | Shell | 230 | 10 | files=`find $1 -type f -size +1024M`
for p in $files
do
echo "processing $p"
name=`basename $p .json`
file=`dirname $p`
split -a 2 -C 300M $p $file/$name- && ls|grep -E "(-[a-zA-Z]{2})" |xargs -n1 -i{} mv {} {}.json
rm -f $p
done |
7c0bc1bcfac3cfa2956d24571d613d83e6deafd9f8a27e2351b548c4def104ae | Shell | 231 | 8 | #!/bin/bash
rm -rf runs/
# form some reason --clear-ouput is broken
# It will be fixed in v6.0 of jupyter_contrib_extensions
for file in *.ipynb ; do
nbstripout $file
# jupyter nbconvert --clear-output --inplace $file
done
|
84c14d45cebe8424e93cab561d127ae4be219d415d64b8fa98ffd1467bc9baaa | Shell | 234 | 14 | #!/bin/bash
#SBATCH -J privileged
#SBATCH -p cpu_p
#SBATCH --qos cpu_normal
#SBATCH --mem=32G
#SBATCH -t 48:00:00
#SBATCH --nice=1000
#SBATCH --cpus-per-task=32
source activate new_python
cd ../generalization/
python privileged.py
|
b93f6c1203706be3e0d5b8db123d1cfb05a1329aca096e63a953720a12490ad5 | Shell | 236 | 7 | #!/usr/bin/env bash
# Configure and start postgres, create database
set -ev
psql -c 'CREATE DATABASE catmaid;' -U postgres
psql -c 'CREATE EXTENSION postgis;' -U postgres catmaid
psql -c 'CREATE EXTENSION pg_trgm;' -U postgres catmaid
|
5eb70c541d04aff789d6603d4c2a767716d2c3820d9e5f0f041d9426f7ca19a1 | Shell | 239 | 14 | #!/bin/bash
BAM_DIR=$1
suffix=".sorted.bam"
samList=$BAM_DIR/../cell_bams.tsv
## Make cell list
echo "" > $samList
for sample in `ls $BAM_DIR/*$suffix`
do
NAME=$(basename $sample $suffix)
echo $sample$'\t'$NAME >> $samList
done
|
df3a7c595e534eab6778e25e46e7936ffe1e55f841a4cc0bac998e3b2c8031f5 | Shell | 239 | 6 | #!/bin/bash
# go interactive before doing anything on the hpc
# srun -I30 -p kill-shared --gpus-per-node=8 -N 1 -c 8 --mem=32G -t 0-01:00:00 --pty /bin/bash
srun -I30 -p gpu --gres=gpu:8 -N 1 -c 8 --mem=32G -t 0-06:00:00 --pty /bin/bash
|
4b632080c9da1a6f9d71dc75a34abebd90e731e7fc4b927dfa8a678d802750e3 | Shell | 240 | 5 | #!/bin/bash
script_path="./Fengshenbang-LM/fengshen/utils/llama_convert/convert_fs_llama_tp.py"
input_dir="llama13b_fs"
output_dir="llama13b_fs_tp4"
python $script_path --input_dir $input_dir --output_dir $output_dir --model_parallel_size 4 |
a1de8b96d5d79a957a4a6870a83105b25130f1613b4a21edcbe7073b0e290862 | Shell | 240 | 6 | #!/bin/bash
set -x
# deleting existing profile to prevent it from being locked.
rm -rf ~/.config/google-chrome/Singleton*
singularity exec $img_dir/$img_name bash -c "source activate chrome_env; \
google-chrome http://127.0.0.1:$port_num"
|
b570f750f887a9022f6b86880926db0ff0831d310d99d4fa26d4da479de13155 | Shell | 242 | 8 | python3 ../../src/plot.py \
--plot aggregate \
--pred ../output/ang_test_r10.tsv \
--bed ../input/sacCer3_plus1_nuc.bed \
--ref ../input/sacCer3.fa \
--label ys18_ang \
--outpath ../output/ \
--prefix ang_test_r10 |
a159c7e1520948399c638a329ef491552301f9dc9b998b9837308607afaa0452 | Shell | 245 | 5 | #!/bin/bash
ls ../examples/*.csv.gz |awk -F "/" '{system ("zcat "$0"|head -n 6 > "substr($NF,1,length($NF)-3))}'
cat ../examples/Model.info |awk -F "/" '{print $NF}' |awk '{print substr($1,1,length($1)-3)"\t"$2}' > Model.info
#python --version
|
30fcc82fe2fb25ff9d9bc1ba4b377349d67fe1af99290711a921ec099c51343e | Shell | 250 | 13 | #!/bin/sh
FLAGS="$(grep -m 1 '^flags' /proc/cpuinfo)"
case "${FLAGS}" in
*avx2*)
exec /usr/local/bin/mmseqs_avx2 "$@"
;;
*sse4_1*)
exec /usr/local/bin/mmseqs_sse41 "$@"
;;
*)
exec /usr/local/bin/mmseqs_sse2 "$@"
;;
esac
|
903f67d2d6358e5cd0c5d38baeaade5260a72f728196552a8c586315e89c3139 | Shell | 250 | 15 | #!/bin/bash
# Program
SRA_prefetch="/opt/ohpc/Taiwania3/pkg/biology/SRAToolkit/sratoolkit_v2.11.1/bin/prefetch"
# User vars
SRRID_file=$1
outDIR=$2
# Download
while read line
do
$SRA_prefetch ${line} -o ${outDIR}/${line}.sra &
done < $SRRID_file
|
62274f6a208ba3211737f40cdb6ca339188b5355a510a1dde092068b597a9108 | Shell | 251 | 9 | #!/usr/bin/env bash
#
# rsync-to-server.sh - use rsync to copy the necessary files to another server.
#
# SYNOPSIS
# bash rsync-to-server.sh username@ssh.server.org:/location/to/write/to
rsync -avP --exclude '/duckdb/duckdbs/' babel_outputs/ "$1"
|
edca29f8b2d7e0c59c53229045aeb3f206e990c1b6bf5f9890c0ab507dd3621b | Shell | 251 | 15 | #!/bin/bash
# install extra Python dependencies
# (must come after setup-venv)
BASEDIR=$(dirname $0)
source $BASEDIR/defaults.sh
if ! $WITH_PYTHON3 ; then
# Python2
:
else
# Python3
pip install --pre protobuf==3.0.0b3
pip install pydot
fi
|
a2e28f21cedb71b12ab13c150a582333704e0224cdb913e1d6846c5ce1445c3b | Shell | 259 | 11 | url=https://storage.googleapis.com/medperf-storage/chestxray_tutorial/cnn_weights.tar.gz
filename=$(basename $url)
if [ -x "$(which wget)" ] ; then
wget $url
elif [ -x "$(which curl)" ]; then
curl -o $filename $url
fi
tar -xf $filename
rm $filename
|
6670b6ce64c0f8a496ac20eb5f66aa4710d84d0ecdf83ffd72540504623e9c07 | Shell | 261 | 13 | #!/bin/sh
if [ $# -ne 1 ]
then
echo "Usage: $0 <DATABASE-NAME>"
exit 1
fi
pg_dump --no-privileges --schema-only --no-owner \
--no-tablespaces $1 -U catmaid_user | \
egrep -v '^--' | \
egrep -v '^ *$' | \
sed -e '/CREATE FUNCTION connect/,+2d'
|
7770b19f45b71dd536812eb4ce0b59368c514784fa55e082fcc5326c6e0cc276 | Shell | 266 | 5 | # multivar
python -u train.py electricity forecast_multivar --loader forecast_csv --repr-dims 320 --max-threads 8 --seed 42 --eval
# univar
python -u train.py electricity forecast_univar --loader forecast_csv_univar --repr-dims 320 --max-threads 8 --seed 42 --eval
|
b377f0798c75406a5eb205fb0713e7c63f91e7ffac4b5247ae578dfb3b01f6d3 | Shell | 267 | 11 | url=https://storage.googleapis.com/medperf-storage/chestxray_tutorial/mobilenetv2_weights.tar.gz
filename=$(basename $url)
if [ -x "$(which wget)" ] ; then
wget $url
elif [ -x "$(which curl)" ]; then
curl -o $filename $url
fi
tar -xf $filename
rm $filename
|
20af12a65148e94d332cb4344a25dd6bf7f374bbc539c4a727c908f0b74486fd | Shell | 268 | 16 | #!/bin/bash
set -e
cd $(dirname "$BASH_SOURCE")
cd ..
LYX_DOCUMENTS=docs/data-model.lyx
for f in $LYX_DOCUMENTS
do
p=${f%.lyx}.pdf
rm -f "$p"
lyx -e pdf "$f"
scp "$p" longair@incf-staging.ini.uzh.ch:/var/www/incf/docs/catmaid-"$(basename $p)"
done
|
8b85c14a85e30f7da5eed4c57bf32c017b62119b8c80fb54d2843b398651a795 | Shell | 269 | 9 | rm -rf workspace_agg/final_weights
rm -rf workspace_agg/logs
rm -rf workspace_col1/logs
rm -rf workspace_col2/logs
rm -rf workspace_col3/logs
rm -rf workspace_agg/plan.yaml
rm -rf workspace_col1/plan.yaml
rm -rf workspace_col2/plan.yaml
rm -rf workspace_col3/plan.yaml
|
aa8683f9acbfc424c14141ff2f54a6a661fd7106648a36427cd2ae8ea3d80363 | Shell | 269 | 14 | '''
Download IMC source code and build executable mex file
Author: Yunan Luo
'''
wget http://www.cs.utexas.edu/~dshin/software/IMC/leml-imf-src.zip
unzip leml-imf-src.zip
cd leml-imf
make matlab
cp matlab/train_mf.mexa64 ../
cd ..
rm leml-imf-src.zip
rm -r leml-imf
|
2026b44937fb14c84db47daf0e04aa3b6c916f030cd16f75e4f7a398f1a022f3 | Shell | 275 | 12 | #!/usr/bin/env bash
#
# GDAL installation for travis from:
# https://stackoverflow.com/questions/55877882/
set -ex
echo "Installing GDAL"
sudo apt-get remove -y libgdal
sudo add-apt-repository -y ppa:ubuntugis/ppa
sudo apt-get update -q
sudo apt-get install -y libgdal-dev
|
ce963f992daa009d46a800670115aa47bc8e1902994f77c4cdefa622e1bb2c97 | Shell | 275 | 18 | #!/bin/sh -e
[ "$#" -ne 2 ] && echo "Please provide <shellcheckBinary> <inputPath>" && exit 1;
SHELLCHECK="$1"
if [ ! -x "$SHELLCHECK" ]; then
exit 0
fi
INPUT="$2"
INPUT_EXT="${INPUT##*.}"
if [ "${INPUT_EXT}" = "sh" ]; then
${SHELLCHECK} "$2"
else
exit 0
fi
|
995c27d59d914db90a800f400a34daf9680546b18ec50c1bee6a3926f4f92071 | Shell | 277 | 10 | #!/bin/bash
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
bash $SCRIPT_DIR/setup_benchmark_tutorial.sh
# medperf auth logout
cd $SCRIPT_DIR/..
bash $SCRIPT_DIR/setup_model_tutorial.sh
# medperf auth logout
cd $SCRIPT_DIR/..
bash $SCRIPT_DIR/setup_data_tutorial.sh |
c37d8f49706ba1c87f378eb424e2d6a291baff725774a9a9a66c3d28a23ebe2c | Shell | 280 | 3 | #!/bin/sh
# Changing the line below? Update https://cloud.docker.com/u/commonworkflowlanguage/repository/docker/commonworkflowlanguage/cwltool
exec docker run -v /var/run/docker.sock:/var/run/docker.sock -v /tmp:/tmp -v "$PWD":"$PWD" -w="$PWD" commonworkflowlanguage/cwltool "$@"
|
d28c10a3bca63eb5e9489301371aded459b90878628ec29af9349d860b099358 | Shell | 280 | 1 | singularity run -B /dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop/dartmouth:/dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop/dartmouth /dartfs-hpc/rc/lab/C/CANlab/modules/bidsvalidator-1.7.2.sif /dartfs-hpc/rc/lab/C/CANlab/labdata/data/spacetop/dartmouth > bids_validator.txt
|
339fb4c7b0dbecaa363a0ed7f0eac3f60cac259c1da4f81601068a8e9d059eb2 | Shell | 287 | 12 | #!/usr/bin/env sh
# Compute the mean image from the imagenet training lmdb
# N.B. this is available in data/ilsvrc12
EXAMPLE=examples/imagenet
DATA=data/ilsvrc12
TOOLS=build/tools
$TOOLS/compute_image_mean $EXAMPLE/ilsvrc12_train_lmdb \
$DATA/imagenet_mean.binaryproto
echo "Done."
|
0e986250d49e9c5606e75733d1896aa73784245908f36370a0241c977750ab86 | Shell | 291 | 18 | # self-driving virtual lab for CCAs design
source $HOME/.bashrc
conda activate tf_25 #your environment
current_dir=$(pwd)
echo $current_dir
# DOTS BCC
dir="/DOTS-BCC"
cd "$current_dir$dir"
python3 run.py --iter 1
# DOTS FCC
dir="/DOTS-FCC"
cd "$current_dir$dir"
python3 run.py --iter 1
|
77866aa2c9bc02f23c9547f07dd84e2478e28b0299f0cda2a0687cc0d00ee41d | Shell | 292 | 9 | #!/bin/sh
# download shunit2 in order to run tests:
# curl -L "https://dl.dropboxusercontent.com/u/7916095/shunit2-2.0.3.tgz" | tar zx --overwrite
echo "Running tests for $1..."
./test/test_suite.sh $1 2>&1 | tr '\r' '\n' > test.log
cat test.log
cat test.log | grep -q 'success rate: 100%'
|
4c755d491e5541d0f765ce7a805af36a4c8eaec24c65f4ad09f13ded2cd56ddb | Shell | 295 | 5 | set -e
jupyter nbconvert --to notebook --inplace --execute block_aligner_bench_vis.ipynb --allow-errors
jupyter trust block_aligner_bench_vis.ipynb
jupyter nbconvert --to notebook --inplace --execute block_aligner_accuracy_vis.ipynb --allow-errors
jupyter trust block_aligner_accuracy_vis.ipynb
|
c4a3a30c55f16602e68d7ac43c771b8066056d9337e38eb1661dc760529a52e6 | Shell | 295 | 9 | #!/bin/bash
nChannels=15
increment=1
# Loop through channels
for (( ch=1; ch<=$nChannels; ch=$ch+1 )); do
echo $ch
sbatch --job-name="${ch}_multidose" --output="logs/multidose_${ch}.out" --error="logs/multidose_${ch}.err" sbatch_hctsa_2_multidose.bash $ch
echo "submitted channel ${ch}"
done
|
dfd7bd3e528c304e9b949a9638228ebfe9e17468d5e3184f805ece75072e57dc | Shell | 296 | 13 | #!/bin/bash
# turn on bash's job control
set -m
# load libs
. /sh_libs/liblog.sh
# print uid
info "Running a test docker container with environment-modules installed."
info "Sourcing /usr/share/Modules/init/profile.sh"
source /usr/share/Modules/init/profile.sh
info "Finished. Happy Testing."
|
745ab1e5b2bae13c11b6e34325de9ddbfc236600a75ded322dbd7d3104718945 | Shell | 297 | 11 | #!/bin/bash
set -xe
DIR_VIRTUS=$HOME/Programs/VIRTUS2
DIR_INDEX_ROOT=$HOME/reference/VIRTUS_2.0
python3 VIRTUS_wrapper.py input.csv \
--VIRTUSDir $DIR_VIRTUS \
--genomeDir_human $DIR_INDEX_ROOT/STAR_index_human \
--genomeDir_virus $DIR_INDEX_ROOT/STAR_index_virus \
--nthreads=4 |
6d6218d7aeeee354d1f34ae3b4e434ffc4e358f998a4b1a81e59934e912b964c | Shell | 300 | 13 | while getopts n: flag; do
case "${flag}" in
n) CONTAINER_NAME=${OPTARG} ;;
esac
done
CONTAINER_NAME="${CONTAINER_NAME:-postgreserver}"
docker container stop $CONTAINER_NAME
docker container rm $CONTAINER_NAME
sh run_dev_postgresql.sh -n $CONTAINER_NAME
sleep 6
python manage.py migrate
|
ba4237ef966b427e3be3023c4488179796c9c428e823606cdafdc25fa15eab75 | Shell | 301 | 9 | #!/bin/bash
# Define the parent directory (on HPC)
study="psilodep1"
session="before"
parent_dir="/rds/general/user/hmt23/home/data/${study}/${session}"
# Find all .nii.gz files in subdirectories and save their paths to subject_list.txt
find "$parent_dir" -type f -name "*.nii.gz" > subject_list.txt |
b13c9566c9f201b216b02b33d960e0f125585a1c29ebc798d603d6ee454ecfdd | Shell | 302 | 10 | rm -rf workspace_agg/final_weights
rm -rf workspace_agg/report.yaml
rm -rf workspace_agg/logs
rm -rf workspace_col1/logs
rm -rf workspace_col2/logs
rm -rf workspace_col3/logs
rm -rf workspace_agg/plan.yaml
rm -rf workspace_col1/plan.yaml
rm -rf workspace_col2/plan.yaml
rm -rf workspace_col3/plan.yaml
|
13cb356a419e8806d6f86f46ac429393d05376eb05fe12257def58306475dbb7 | Shell | 304 | 14 | #!/bin/bash
set -euo pipefail
cmake_files=$(
find . -name CMakeLists.txt -o -path "./cmake/*.cmake" \
| grep -v dmlc-core \
| grep -v gputreeshap
)
cmakelint \
--linelength=120 \
--filter=-convention/filename,-package/stdargs,-readability/wonkycase \
${cmake_files} \
|| exit 1
|
7ae7bdd69693c43269311da4135bc05616787897c774f84620733b281e33ef9c | Shell | 311 | 11 | #!/bin/bash
set -xe
DIR_VIRTUS=$HOME/Programs/VIRTUS2
DIR_INDEX_ROOT=$HOME/reference/VIRTUS_2.0
python3 VIRTUS_wrapper.py input.fastq.csv \
--VIRTUSDir $DIR_VIRTUS \
--genomeDir_human $DIR_INDEX_ROOT/STAR_index_human \
--genomeDir_virus $DIR_INDEX_ROOT/STAR_index_virus \
--nthreads=4 --fastq |
df31541825527262b86077b059c2a4efce31f828e74e913d183109274fb77933 | Shell | 314 | 10 | #--func can be: ackley rastrigin rosenbrock schwefel michalewicz griewank levy
#--method can be: DOTS DOTS-Greedy DOTS-eGreedy Random DualAnnealing DifferentialEvolution CMA-ES
source $HOME/.bashrc
conda activate tf_25 #your environment
python3 run.py --func ackley --dims 100 --samples 10000 --method CMA-ES
|
10526df1c32c40dd90c590cd2a066bd4f2bc3427d11c1632a5e43502e3926d90 | Shell | 315 | 12 | #!/bin/bash
ml purge
ml singularity/3.3.0
#set your subjects
subjects=("sub-01" "sub-02" "sub-03" "sub-04" "sub-05" "sub-06" "sub-07" "sub-08" "sub-09" "sub-10")
#loop over your subject
for subj in ${subjects[*]}; do
sbatch fmriprep_singularity.sh ${subj}
sleep 1 # pause to be kind to the scheduler
done
|
a19a15a9299d1f8967cfb241a5dfaa0f34e83c4ed230818978fb97df8ec248bd | Shell | 317 | 14 | #!/bin/bash
## Run C++ tests for i386
set -euo pipefail
source ops/pipeline/get-docker-registry-details.sh
source ops/pipeline/get-image-tag.sh
IMAGE_URI="${DOCKER_REGISTRY_URL}/xgb-ci.i386:${IMAGE_TAG}"
set -x
python3 ops/docker_run.py \
--image-uri ${IMAGE_URI} \
-- bash ops/pipeline/test-cpp-i386-impl.sh
|
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