sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
62c49d5a823aa715b918bd7f4ad2082d155c3f8da7dc280b10935bc3463244de | Shell | 332 | 9 | #!/bin/bash
# Tag each rev with a simple log entry
for SHA in $( grep -v "^#" .git-blame-ignore-revs ); do
git log --pretty=format:"# %ad - %ae - %s%n$SHA%n" -n 1 --date short $SHA
done > git-blame-ignore-revs
# Two-step to avoid the original getting truncated before it's read
mv git-blame-ignore-revs .git-blame-... |
fe11ec5e407e27b8b7a5c8612db7f1d6626d695f5bcea6c273fb0e8539f1b5d7 | Shell | 332 | 14 | #!/bin/bash
#SBATCH -c 1
#SBATCH -t 5-00:00
#SBATCH -p gpu
#SBATCH --mem=64G
#SBATCH --gres=gpu:1
#SBATCH -o examples/tuning_%j.out
#SBATCH -e examples/tuning_%j.err
module load python/3.10.11
module load gcc/9.2.0 cuda/11.7
source "venv/bin/activate"
/n/cluster/bin/job_gpu_monitor.sh & python3 examples/hyperparamete... |
98d80915a6e0f19b27fa6684002c44089291fc4e9f12dfbb214e075addd5ab4e | Shell | 333 | 11 | #!/usr/bin/bash -i
#SBATCH -n 1
#SBATCH -c 64
#SBATCH -p hgx
#SBATCH --gres=gpu:01
#SBATCH -t 48:00:00
source ~/.bashrc
conda activate gnn
python main_rna_pdb_single.py --dataset RNA-bgsu-hl-cn --epoch=1 --batch_size=32 --dim=256 --n_layer=6 --lr=1e-5 --timesteps=5000 --mode=coarse-grain --knn=20 --wandb --lr-step=20... |
f453dad94bce627fa02abf2695c1c58188e0efe745c2820e87cd0a7728a7ecec | Shell | 333 | 11 | #!/bin/sh
# This entrypoint exists as we need to infer the user ID from the bind mount to
# re-assign ownership of the output db file from root to the user.
set -eu
give_output_to_host_user() {
chown -R --reference=/out /out 2>/dev/null || true
}
trap give_output_to_host_user EXIT
/mimic/buildmimic/duckdb/build_m... |
c95b96a1bc58f69a0766d01a4b28531826f6ad2fc4f37a656830746b4557e185 | Shell | 335 | 17 | #!/bin/bash -e
lmpbin=$1
if [ ! -f $lmpbin ]; then
echo "LAMMPS binary '$lmpbin' is not a file"
exit 1
fi
for file in in.*; do
echo "$file"
echo "1 proc"
$lmpbin -i $file > /dev/null
grep ' 1.2 ' log.lammps
echo "2 procs"
mpirun -np 2 $lmpbin -i $file > /dev/null
grep ' 1.2 ' l... |
84192617b1136b44872225805a16ffb486603e39a04c9ff6c286defd9d08f6de | Shell | 337 | 11 | #!/bin/bash
export PYTHONPATH="$PWD"
if [ -z "${DEV_FILES}" ]; then
# Production
exec uvicorn app.main:app --workers 1 --host 0.0.0.0 --port 5000 --access-log --use-colors
else
# Development
exec uvicorn app.main:app --workers 1 --host 0.0.0.0 --port 5000 --access-log --use-colors --reload --forwarded... |
3a56e4691a96cc83b80d8e96a57b7a036343e6496b76babca4325a036d161b9d | Shell | 339 | 10 | FILE=$1
echo "Note: available models are edges2shoes, sat2map, map2sat, facades_label2photo, and day2night"
echo "Specified [$FILE]"
mkdir -p ./checkpoints/${FILE}_pretrained
MODEL_FILE=./checkpoints/${FILE}_pretrained/latest_net_G.pth
URL=http://efrosgans.eecs.berkeley.edu/pix2pix/models-pytorch/$FILE.pth
wget -N $... |
7b702e9256341680216d7204fd6566ffe9f4868bcb160543984927141bdaa4bd | Shell | 339 | 8 | s="sample-prefix"
mm10="path-to-mm10-ref"
mm10_5k="path-to-your-5kb-bin-reference"
trim_galore ${s}_BC_cov.fq.gz
bowtie2 -x ${mm10} -U ${s}_BC_cov_trimmed.fq.gz --no-unal -p 8 -S ${s}_mm10.sam
samtools sort ${s}_mm10.sam ${s}_mm10_sorted.bam
reachtools rmdup2 ${s}_mm10_sorted.bam
reachtools bam2Mtx2 ${s}_mm10_sorted_rm... |
0d028debe6a5915103223c63a594d41cda0a264e6b1fa6e66b0d6d0ce163510a | Shell | 340 | 13 | #!/bin/bash
#all gexprs
DIRECTORY="data"
for file in "$DIRECTORY"/*
do
echo "Processing $file"
base=$(basename "$file" .mat)
newfile="${file%/*}/$base""_grnboost.tsv"
echo $newfile
python ~/anaconda3/envs/pyscenic/bin/arboreto_with_multiprocessing.py "$file" allTFs_hg38.txt --method grnboost2 --output $newf... |
8fa67ad94e9ceef1ee4589838a8f42337a24804dc400a075c0c577627670e2d9 | Shell | 340 | 12 | #!/bin/bash
# A script to install everything needed to run MOSES in a new environment
set -e
git clone https://github.com/pcko1/Deep-Drug-Coder.git --branch moses
cd Deep-Drug-Coder
python setup.py install
cd ..
git clone https://github.com/EBjerrum/molvecgen.git
cd molvecgen
python setup.py install
cd ..
pip install t... |
0d2d296e3edf67cc9b0f32b0ce81a76c2b9415ea6f11438b92cb00a1f1323103 | Shell | 341 | 8 | #!/bin/bash
# For the GO dataset
python go.py --pretrain 'False' --gpu 6 --level 'cc' --batch-size 64 --ckpt-path './ckpt_finetune' --lr 1e-3 --wd 5e-4 --num-epochs 300 \
--base-width 32 --kernel-channels 24 --lr-milestone 300 400
# For the EC dataset
python ec.py --pretrain 'False' --gpu 6 --batch-size 24 --ckpt-pa... |
9e5673d84cc7b619f8f35b26b9ecd88f298c836ba74c21b27cd3c90f16d30638 | Shell | 346 | 19 | #!/bin/bash
type -a docker > /dev/null
if [ $? -ne 0 ] ; then
echo "UNCONFIGURED: No docker executable" 1>&2
exit 1
fi
if [ $# -gt 0 ]; then
tag_id="$1"
for docker_name in q_validation q_metrics q_consolidation ; do
docker build -t cjh4zavolab/"$docker_name":"$tag_id" "$docker_name"
done
else
echo "Usage: $... |
f60fbb236a5e47ac45b9a958d546922c8c35be16eb729d8ff20643a9167abb20 | Shell | 346 | 19 | #!/bin/bash
type -a docker > /dev/null
if [ $? -ne 0 ] ; then
echo "UNCONFIGURED: No docker executable" 1>&2
exit 1
fi
if [ $# -gt 0 ]; then
tag_id="$1"
for docker_name in i_validation i_metrics i_consolidation ; do
docker build -t cjh4zavolab/"$docker_name":"$tag_id" "$docker_name"
done
else
echo "Usage: $... |
f8140b2182bb851e03efba15b538f3eb744c2fd17fc9ceb2d4b25219a6ab62c8 | Shell | 346 | 9 | #!/bin/bash
# Launcher target for the desktop/menu entry. MITK already auto-starts via supervisord, so if a
# window is already up we just raise it instead of spawning a second instance; otherwise we start
# it (fullscreen handling lives in startMITK.sh).
if wmctrl -l | grep -q 'Research'; then
wmctrl -a 'Research'
el... |
106fad31ee3e251b4ba375da285ea03f92c8ad889b22a96af1145e342068546a | Shell | 347 | 18 | #!/bin/bash
# Siwei 29 Jun 2021
# Use Picard from GATK 4.1.8.1
picard_path="/home/zhangs3/Data/Tools/gatk-4.1.8.1/picard2_25_4.jar"
for eachfile in *.bam
do
java -jar $picard_path CollectInsertSizeMetrics \
-I $eachfile \
-O size_dist/${eachfile/%_new_WASPed\.bam}.txt \
-H size_dist/${eachfile/%_new_WASPed\.... |
0413b89571f7272349289c2641fcdeaca8adbe4676a3c9d87ad227e31651377e | Shell | 348 | 15 | #!/bin/bash
set -eu
echo minio path: ${S3_PATH}
rclone_s3_args=(
--s3-provider Other
--s3-endpoint "http://${S3_SERVICE}"
--s3-access-key-id "${S3_USER}"
--s3-secret-access-key "${S3_PASSWORD}"
)
rclone mkdir "${rclone_s3_args[@]}" ":s3:/${S3_PATH}"
rclone copy "${rclone_s3_args[@]}" /files/analysis... |
292453c147f48cbc53a36ac33d4b6e73af3a2878a0b73ca625b3028f3db8834a | Shell | 348 | 3 | wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/datasets/KAGGLE_training_disguised_combined_full.csv.gz
wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/datasets/KAGGLE_test1_disguised_combined_full.csv.gz
wget -c http://deepchem.io.s3-website-us-west-1.amazonaws.com/datasets/KAGGLE_test2_dis... |
682580166c1ad6efa4974f90f6802b183ffb5ab723007ff41e220a7abcf56bfa | Shell | 353 | 13 | #!/bin/bash
#SBATCH --partition=GPU-a100s
#SBATCH --gres=gpu:a100s:1
#SBATCH --nodes=1
#SBATCH --job-name=train_test_all_splits
#SBATCH --output=%x-%j.out
uv run flow_train.py -m \
data.split_file="rxn_core_split.pkl","barrier_split.pkl","random_split.pkl" \
model.num_steps=25 \
model.num_samples=25 \
... |
cb0c5efd850840edb5391e808b9418fcb2328ef3977ff70952a32e69ca4f929e | Shell | 353 | 21 | #!/bin/bash
echo "$@"
INPUT=$1
OUTPUT_PATH=$2
SMOOTHING=$3
NAME=$4
MIN=$5
MAX=$6
mkdir -p $OUTPUT_PATH
OUTPUT_VOL=$OUTPUT_PATH/$NAME.mgz
OUTPUT_SURF=$OUTPUT_PATH/$NAME.stl
mri_binarize --i $INPUT \
--min $MIN \
--max $MAX \
--surf-smooth $SMOOTHING \
--surf $OUTPUT_SU... |
f127ccae2f72542751dab59be26b3a26187af00b1a44ca3ebf1adb7273a1b0f3 | Shell | 353 | 9 | #Note: some runs (when controlling for tau or expression level for high clustering resolution for Sestan_DLPFC or Allen_MTG) did not finish in 7 days
#In that case, we reran starting at the first unfinished iteration and combined the two files to make a complete file
python make_scripts.py
for file in run1-*.sh;
do
... |
5bd80c21357f8f005eda09910809fb61ef6c99a8adb04864a1739294ac238f08 | Shell | 354 | 20 | #!/bin/bash
set -e
. env/bin/activate
echo ${pwd}
cd ../..
PDB_FN=$1
NUMBER_VARIANTS=$2
MAX_NUM_SUBS=$3
MIN_NUM_SUBS=$4
SEED=$5
# Run the Python script with the specified parameters
python code/variants.py subvariants --pdb_fn="$PDB_FN" --target_num="$NUMBER_VARIANTS" --max_num_subs="$MAX_NUM_SUBS" --min_num_s... |
dfde975c4b9fa72d20a383c19376ea8aee4374898b6743683a3fef134a26b479 | Shell | 354 | 12 | #!/bin/bash
set -e -u
# Build the wheel for all os (on a linux runner).
# This script must be run from the root of the repository.
# If you want OS-specific wheels, add the respective scripts to the OS-specific folders,
# the alphashared workflow will use those then:
# e.g. release/linux/build_wheel_linux.sh
rm -rf d... |
66aaa2f4968609909cb1b380d8cb983aca0b840090a2626b368a2dead03e6c93 | Shell | 356 | 21 | #!/bin/bash
echo "Installing dependencies"
set -eu
# Required variables
echo OS_TYPE = $OS_TYPE
if [ "$OS_TYPE" = "ubuntu-latest" ]; then
sudo apt update
sudo apt install -y graphviz
elif [ "$OS_TYPE" = "macos-latest" ]; then
brew install graphviz
else
echo "Unknown OS_TYPE: $OS_TYPE"
fi
set +eux... |
b1740bcb00d6e138e278b2e38a1690a27d1c692d886dcfb4c4a8a51e4c20b46c | Shell | 357 | 21 | #!/bin/bash
echo "**** Job starts ****"
date
## Clean up older files
# rm -fr trash
## Could be fancier and use the date or something
mkdir -p trash
mv logs/build_bims_NAc_genes_*.txt trash/
rm -r trash/NAc_gene
mv NAc_gene trash/
## Create logs dir if needed
mkdir -p logs
## Submit new job
qsub build_bims_NAc_gene... |
26d495f13d56b94843a38075060b713b02738de9e1fbd67ef5d05f5fadd4d11c | Shell | 358 | 19 | #! /bin/bash
set -e
TARGET_DIR="$(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"
cmake -DCMAKE_BUILD_TYPE=Release "$REPO_DIR"
make package_source
cp labe... |
0687599cb8780850c3db305af2dcb933207640a29a7ff957dd02d2228c588a4c | Shell | 359 | 6 | #!/bin/sh
# Large virtual screen + RANDR so Selkies can set the display resolution to match the
# client's browser window live (replaces the old one-shot resize backend). The framebuffer
# size is the max RANDR mode; sized generously to cover hi-DPI/retina windows (devicePixelRatio 2).
exec /usr/bin/Xvfb :1 -screen 0 ... |
b73eeb551be9fe9be4f7b12d9dd493d7e0071978801f49d516a2df39ec54a0b4 | Shell | 362 | 18 | #!/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
source ../../../environments/atlasEnv/bin/activate # Needs to be set by th... |
202b0a72b4d2d162168b91bf38123b482eb0855699fc2aca9e456b7adc8c36ba | Shell | 364 | 9 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr/p1-network1
GPU_ID=0
echo "Running Caffe using GPU" $GPU "In Directory " $OUTDIR
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log.txt \
--solver $OUTDIR/trainval-test-solver.prototxt --weights models/bvlc_reference_caffenet/bvlc_ref... |
a844ab0eba1b3240fa43a46e1df976e72e9ec54b07abba1d729293655f11e940 | Shell | 364 | 4 | for i in {1..3}; do
bash bash_scripts/hRPL.sh --seed $i --experiment_name animals_greedy_cts_noiseOnTop0.1_pred_$i --loss pred --prediction_target enc --pred_lr_mult 10;
bash bash_scripts/hRPL.sh --seed $i --experiment_name animals_greedy_cts_noiseOnTop0.1_freeze_pred_$i --loss pred --prediction_target enc --pr... |
8a5d2517be91ede6036faddb08c4e048d5ff3cef4f7e857d064c98a54c30bf4b | Shell | 365 | 17 | #!/bin/bash -l
# Set SCC project
#$ -P vkolagrp
#$ -N wandb_nAD_sweep # Give job a name
#$ -j y # Merge the error and output streams into a single file
#$ -pe omp 8
#$ -l gpus=1
#$ -l gpu_c=6
#$ -m bes
#$ -l h_rt=2:00:00
module load miniconda
conda activate mri_radiology
python /usr4/ugrad/sp... |
9a74674ec214f45da65a13f135d49bef092bd2e84554ae813199a91b4613341e | Shell | 366 | 14 | #!/bin/bash
SCRIPT_PATH=$1
KOKKOS_DEVICES=$2
KOKKOS_ARCH=$3
COMPILER=$4
if [[ $# < 4 ]]; then
echo "Usage: ./run_benchmark.bash PATH_TO_SCRIPTS KOKKOS_DEVICES KOKKOS_ARCH COMPILER"
else
${SCRIPT_PATH}/checkout_repos.bash
${SCRIPT_PATH}/build_code.bash --arch=${KOKKOS_ARCH} --device-list=${KOKKOS_DEVICES} --compiler=... |
99677b1a7fe8c9a56ae700c0f239cfa19c35fe1df5a8044dda983c23e1472fab | Shell | 368 | 17 |
conda create -n infer-subc python=3.10
conda activate infer-subc
pip install napari[all]
pip install scipy scikit-learn matplotlib
pip install aicsimageio
pip install aicspylibczi
pip install aicssegmentation
pip install napari-aicsimageio
pip install vispy
pip install matlab
pip install centrosome
pip install in... |
0ba14b4966990b06535a59cabd518597116d1370c50cfc557a1bb7fc60518b53 | Shell | 371 | 7 | #!/bin/bash
#10x single cell sequencing - convert base calls to fastq files
#Author: Kate Castellano
# ----------------------------
/data/app/cellranger-6.1.2/cellranger mkfastq --id=Lv_scRNA --run=/data/prj/urchin/cell-culture/2022Jan_10xscSeq/KCastellano_GMGI_10xsc_10Jan2022/Files \
--samplesheet=cellranger_sa... |
f8ad347ce22d9b1a4c29e74a04f1c9df82696b8cc46c18f1463a43ca1527e87e | Shell | 371 | 9 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr-simple/p1-network1
GPU_ID=0
echo "Running Caffe using GPU" $GPU "In Directory " $OUTDIR
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log.txt \
--solver $OUTDIR/trainval-test-solver.prototxt --weights models/bvlc_reference_caffenet/b... |
839be68eb161b997afa2bec7adc5662b422b58453c770223f12fc5a11c0775df | Shell | 372 | 18 | #!/bin/bash
set -eu -o pipefail
buildah bud \
--isolation=chroot \
--no-cache \
-t "${BUILD_DESTINATION}" \
--root /storage \
--runroot /storage/run/containers/storage \
--tls-verify=${TLS_VERIFY} \
"${BUILD_CONTEXT}"
buildah push \
--root /storage \
--runroot /storage/run/containers/storage \
--... |
8f5d04505cd69827aa4d2cd141e0311613ffbcfd5fbc9d10b72d993ead5cf60a | Shell | 375 | 17 | DATA=cifar10
DATAROOT={/path/to/cifar10}
CKTP=outputs/{pretrain_date}/{filename}.pth
python finetune.py \
ckpt=$CKPT \
data=$DATA \
data.set.root=$DATAROOT \
data.transform.re_prob=0 \
data.loader.batch_size=96 \
model=deit_tiny_patch16_224 \
model.drop_path_rate=0.0 \
optim=momentum \
optim.args.lr=0.01 \
optim.args... |
0c1c1359c4bb98e7f0ca86da8028608685698583ae184fe0b8c70decb60b9abf | Shell | 377 | 25 | #!/bin/bash
# Siwei 05 Jul 2023
# cut up/downstream of rs10792832 (chr11:86156833) of 1 MB each
output_dir="rs10792832_1MB"
mkdir -p $output_dir
for eachfile in *.bam
do
echo $eachfile
samtools view \
-h \
-@ 20 \
$eachfile \
chr11:85156833-87156833 \
| samtools sort \
-l 9 \
-m 5G \
-@ 20 \
-o ... |
52b3638e29c2fbccae8e52d117c3c1f2b4e78a2cd5b8c2c96a313b13850dee6d | Shell | 379 | 4 | ln -s ../3a.predict_local_phase1_Score0.05/virus.phase1a_final.CON ./
rm -rf tmp.* log.* debug.txt
perl 1.Heuristics_predict.useRNAstructure.contain_input_Constraints.pl ../2.Loop_by_VCsqrt/out3.onlyPart.enriched_pixels.resolution5.score0.03.bedpe ../2.Loop_by_VCsqrt/out6.onlyPart.loops_or_enriched_pixels.resolution5.s... |
e3d51701c7d68c3f140205d1feab8a290c033fabd5fe41e96e409c32c077c902 | Shell | 380 | 11 | #!/bin/bash
cd app
sudo dpkg -i veyon_1.1.0_amd64.deb
sudo veyon-cli config clear
sudo veyon-cli config import default.config
sudo veyon-cli config set Authentication/Method 1
sudo veyon-cli config set Master/ConfirmUnsafeActions true
sudo veyon-cli authkeys import tpp/public key.pem
sudo veyon-cli authkeys import tpp/... |
2b5dbf1df7a3e49177e2c65cde13ae4959a94fe23398e18f7d22bdf9f54d6457 | Shell | 382 | 25 | #!/bin/bash
# Siwei 05 Jul 2023
# cut up/downstream of rs10792832 (chr11:86156833) of 1 MB each
output_dir="rs1532278_CLU_1MB"
mkdir -p $output_dir
for eachfile in *.bam
do
echo $eachfile
samtools view \
-h \
-@ 20 \
$eachfile \
chr8:26608798-28608798 \
| samtools sort \
-l 9 \
-m 5G \
-@ 20 \
-... |
e4149bcf63fb038c7825a545439f9de32a4dc3f8a25bdaec3a0fd9cc372ba494 | Shell | 382 | 10 | #!/bin/bash
# run server via ../../boot.sh first
echo "Running test_server.py"
python -m pytest -s tests/test_server.py
echo "Running test_install_delete.py"
python -m pytest -s tests/test_install_delete.py
echo "Running test_file_upload.py"
python -m pytest -s tests/test_file_upload.py
echo "Running test_file_upload_c... |
45fbf74caaa9c2f4b8515725359184602a417e567423f0ced590a9c88db05995 | Shell | 383 | 13 | #!/bin/sh
docker run -it \
--user $(id -u) \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro"... |
74d35db93bf59e1aedf2bab93741f707607700934a2a3cd34480f0b9363ac528 | Shell | 383 | 24 | #!/bin/bash
echo Installing dependencies
source .maint/ci/activate.sh
source .maint/ci/env.sh
set -eu
# Required variables
echo EXTRA_PIP_FLAGS = $EXTRA_PIP_FLAGS
echo CHECK_TYPE = $CHECK_TYPE
set -x
if [ -n "$EXTRA_PIP_FLAGS" ]; then
EXTRA_PIP_FLAGS=${!EXTRA_PIP_FLAGS}
fi
pip install $EXTRA_PIP_FLAGS "fmrip... |
b1904f6ce752ea497ca445d44d845cfa8edc4918eeb72470d24e4d6ae14685b9 | Shell | 383 | 10 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr/p4-network2
GPU_ID=0
ITER=10000
echo "Resuming Caffe using GPU" $GPU "In Directory " $OUTDIR "Starting from iteration " $ITER
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log-resume.txt \
--solver $OUTDIR/trainval-test-solver.prototxt --sna... |
755b4f4be32895aa442b4804678ca584967847b7ea5e22bf8ba53ae75ff5d4ec | Shell | 384 | 15 | #!/bin/bash
# Create dataset splits
DATA_PATH="data/RDB7"
FULL_CSV="$DATA_PATH/raw_data/rdb7_full.csv"
RXN_CORE_CSV="$DATA_PATH/raw_data/reaction_types.csv"
python split_preprocessed.py \
--input_rxn_csv "$FULL_CSV" \
--output_rxn_indices_path "$DATA_PATH/splits" \
--random \
--rxn_core_clusters \
... |
baad28d2cd29e48eb17dcfd588c1f484b4e1bff929c555ca3e6f0e2ad41e68f9 | Shell | 384 | 17 |
#SBATCH -o out/%x_%A_%a.out
#SBATCH -e err/%x_%A_%a.err
#SBATCH -p all
#SBATCH --mail-type FAIL
#SBATCH --mail-user tafazoli@princeton.edu
echo "In the directory: `pwd` "
echo "As the user: `whoami` "
echo "on host: `hostname` "
echo "Num Cores: ${NUM_CORES}"
echo "Array Allocation Number: $SLURM_ARRAY_JOB_ID"
echo ... |
ed5bbfa30b52ab7af2d211919f577baf7a2235e931c0b39da201cfbe79fb96d6 | Shell | 384 | 10 | #!/bin/sh
set -e
export PYTHONPATH="$PWD"
if [ -z "${DEV_FILES}" ]; then
exec uvicorn app.main:app --workers $WORKERS --host 0.0.0.0 --port $PORT --root-path $APPLICATION_ROOT --access-log --use-colors
else
exec uvicorn app.main:app --workers $WORKERS --host 0.0.0.0 --port $PORT --root-path $APPLICATION_ROOT ... |
fb91119636aac0d93814b2e77a02358469f5815dc84f0be580e35b605508d94a | Shell | 385 | 25 | #!/usr/bin/env bash
set -e
SRC=$1
BUILD=$2
CPUS=$(nproc)
mkdir -p $BUILD
cd $BUILD
cmake -DCMAKE_TOOLCHAIN_FILE=$SRC/cmake/modules/AndroidToolchain.cmake \
-DANDROID_NDK=/opt/android/ndk \
-DANDROID_ABI="arm64-v8a" \
-DANDROID_TOOLCHAIN_MACHINE_NAME="aarch64-linux-android" \
$SRC
echo Building on $CPUS CPUs
i... |
d9bf5394a3bdaf0a6fccb0b72348797e7e2ab15117ecbcb414be2a30eb8e4437 | Shell | 387 | 11 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr/p1-network1
GPU_ID=0
ITER=15000
echo "Resuming Caffe using GPU" $GPU "In Directory " $OUTDIR "Starting from iteration " $ITER
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log-resume.txt \
--solver $OUTDIR/trainval-test-solver.prototxt -... |
ec0f593729a386866c292cae8e0e42880f60785a9059224cb103e20952b67647 | Shell | 387 | 25 | #!/usr/bin/env bash
set -e
SRC=$1
BUILD=$2
CPUS=$(nproc)
mkdir -p $BUILD
cd $BUILD
cmake -DCMAKE_TOOLCHAIN_FILE=$SRC/cmake/modules/AndroidToolchain.cmake \
-DANDROID_NDK=/opt/android/ndk \
-DANDROID_ABI="armeabi-v7a" \
-DANDROID_TOOLCHAIN_MACHINE_NAME="arm-linux-androideabi" \
$SRC
echo Building on $CPUS CPUs
... |
25d1b51e61c185b38af3c233dfa48555853dde28f874adc8135bfa55d8da9561 | Shell | 388 | 17 | #!/bin/bash
PATTERN=$1
TARGET=$2
OUT=$3
mkdir -p $OUT
for IMG in $PATTERN; do
if [ "$IMG" != "$TARGET" ]; then
filename=$(basename -- "$IMG")
filename="${filename%.*}"
mkdir -p $OUT/$filename
# You may want to run this on a cluster with multiple threads
antsRegistrationSy... |
8d2a78eb4235fd6f9f1bb6476ae9996c55a4e20eca4f7e9eacebc67de9f10155 | Shell | 389 | 12 | #!/bin/bash
SOURCE=<id_jeanzay>@jeanzay:/gpfsscratch/rech/zaj/<id_jeanzay>/code/2021.04_experiments/
for file in $(find . -type d -name "experiment_*")
do
echo $file
rsync -azvh --include "*repetition_*/" --include "*data/" --exclude "*.py" --exclude "*__pycache__/" --exclude "*.slurm" --exclude "*.scs" -e "ssh -i ... |
181b85dd5fa44f95146a192e3e18b9a309cd9c5003fa5bc0198205175854b408 | Shell | 390 | 10 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr-simple/p4-network2
GPU_ID=0
ITER=10000
echo "Resuming Caffe using GPU" $GPU "In Directory " $OUTDIR "Starting from iteration " $ITER
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log-resume.txt \
--solver $OUTDIR/trainval-test-solver.prototx... |
c252a50260c1e15020c6e2f08732c9ecf670432453929d5f53b6fd3c1bc4abc7 | Shell | 391 | 10 | #!/usr/bin/env bash
# This is to run the check_UMIs script over a list of CBCs
# The list has to be provided as a text file with one CBC per line
while read fraction;
do
echo $fraction
java -jar $PICARD DownsampleSam I=gene_function_tagged.bam P=$fraction M=downsample_metrics.txt O=/dev/stdout | python $HOME/nas_1/... |
097f95e22091a99be3bc7a8edc55b233762ee4c8ae509092097a59d1f06e2b84 | Shell | 394 | 12 | #!/usr/bin/env bash
# Two modes:
# (default) Ephemeral: run the agent once on $PROMPT, print the result, exit.
# serve Start the FastAPI server on :8000.
set -euo pipefail
if [[ "${1:-}" == "serve" ]]; then
exec uvicorn hosting.server:app --host 0.0.0.0 --port 8000
fi
# Ephemeral: run the research agent f... |
3ffd654e17b04857b78e128399d6d4b251b008e2c1f0e3e77a9be33d96f5322f | Shell | 394 | 23 | #!/bin/bash
#Siwei 14 Feb 2018
# Siwei 22 Dec 2019
# Genotype RERE rs301791
date > RERE_genotyping.txt
echo "All genomic coordinates are based on GRCh38p7." >> RERE_genotyping.txt
for EACHFILE in *.bam
do
echo $EACHFILE >> RERE_genotyping.txt
echo $EACHFILE
printf "rs301791\t" >> RERE_genotyping.txt
samtools... |
53ee23a05fa3237a6c924841a482ecb74da4a25f2da902c8b820cbbbe1d0e7ef | Shell | 394 | 4 | ln -s ../3b.predict_local_phase1_Score0.03/virus.phase1b_final.CON ./
perl creat_resolved_region_from_CON.pl virus.phase1b_final.CON > log.resolved_bases.phase1b_final.real.bed
perl 0.creat_bedpe_from_region.pl log.resolved_bases.phase1b_final.real.bed > out1.loops_for_solved.bedpe
perl 1.fill_local_blanks.useRNAstruct... |
c904c306eece2cb7c2b8d19aa2672cbac9e355c262865e381bae0bff09f0fd09 | Shell | 394 | 11 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr-simple/p1-network1
GPU_ID=0
ITER=15000
echo "Resuming Caffe using GPU" $GPU "In Directory " $OUTDIR "Starting from iteration " $ITER
./build/tools/caffe train 2> $OUTDIR/z_trainval-test-log-resume.txt \
--solver $OUTDIR/trainval-test-solver.protot... |
da378c793dc7f3d662e6f161dadb31f563039ca62fff308e3d2550fb8b53bcdf | Shell | 394 | 17 | #!/bin/bash
# cd /home/traaffneu/margal/code/multirat_se/asset
# ./flip_RL.sh
# Flip the scans in the x-axis
#cd /project/4180000.19/multirat_stim/scratch/rabies_test/flip/
cd /project/4180000.19/multirat_stim/scratch/flip/
nifti_file="sub-0200406_ses-1_run-1_minus5sec_bold_combined.nii.gz"
fslhd $nifti_file
fsl... |
3b7e4f39405fba16d7486411890d19cb95d261ca4ba748458176eb2bea8bb0fd | Shell | 395 | 25 | #!/bin/bash
# Siwei 10 May 2022
# use the improved method as in
# https://www.biorxiv.org/content/10.1101/496521v1
for eachfile in *.bam
do
echo $eachfile
samtools index -@ 20 $eachfile
done
macs2 callpeak \
-t *.bam \
-f BAMPE \
-g 2.7e9 \
-q 0.05 \
--keep-dup all \
--nolambda \
--min-length 100 \
--max... |
8d10fa097f1ecd33c74b3f5d9ef18acc50ad0c4bc389fadb25308c4b82c6a083 | Shell | 396 | 11 | rm -rf _build
conda env remove -n alpharawdocs -y
conda create -n alpharawdocs python=3.11 -y
# conda create -n alphatimsinstaller python=3.10
conda activate alpharawdocs
# call conda install git -y
# call pip install 'git+https://github.com/MannLabs/alphatims.git#egg=alphatims[gui]' --use-feature=2020-resolver
# brew ... |
ef9b47ca48de511f488d0d1ab782ae5ec7fa95ca1ccaeb5d938ceddf880aa694 | Shell | 397 | 17 | #!/bin/bash
dx login --token TOKEN
# Define the range of values for c and lf
c_values=({1..22}) #(21 22)
ancestry=("eur" "sas" "afr" "eas" "amr" "mid" "oth")
# Iterate over c and lf values
for c in "${c_values[@]}"; do
echo $c
for a in "${ancestry[@]}"; do
echo $a
# Call the helper script with c and lf ... |
0ffe67586c62845b532fbd43290ff692f0a94fc9d4a94a283c5d6ed83a044204 | Shell | 398 | 14 | #!/bin/bash
# Run inside calls.sort.bam folder
# Get the directory where the script is located
SCRIPT_DIR=$(dirname "$0")
echo $SCRIPT_DIR
# Check for new bam files every 5 seconds
while true; do
ls -1 | grep ".bam$\|.pred.pdf$" | sed 's/.pred.pdf$//' | uniq -c | awk '{if($1==1){print $2}}' | xargs -I {} bash $SCRI... |
c6be31ef4f2a65ee7d76133a907ec90fdbb894de809f71776f4927c6bbe07034 | Shell | 401 | 15 | #!/bin/bash
echo "Activate <conda_env> conda environment ..."
export PYTHON_EXEC="$WORK/miniconda3/envs/<conda_env>/bin/python"
echo "Start experiments via slurm ..."
$PYTHON_EXEC -c "import exputils
exputils.start_slurm_experiments(directory='./experiments/',
start_scripts='run_experiment.slurm',
is_para... |
3c1b1da6b4ff78a50e30fcfd0413c905a01d1b38c3ac6bc73860329f099c9b80 | Shell | 405 | 11 | #!/bin/bash
#SBATCH --partition=GPU-a100s
#SBATCH --gres=gpu:a100s:1
#SBATCH --nodes=1
#SBATCH --job-name=test_ablate_steps
#SBATCH --output=%x-%j.out
MODEL_PATH="logs/train_test_error_bar/multiruns/2025-04-11_09-32-05/2/checkpoints/epoch_294.ckpt"
uv run flow_train.py -m model.num_steps=1,3,5,10,25,50 model.num_sam... |
bd7e763fb7b5e75adc9dc3f5e60f6612c7e94198a074d47cff3fe782c86efb2e | Shell | 409 | 11 | #!/bin/bash
#SBATCH --partition=GPU-a100s
#SBATCH --gres=gpu:a100s:1
#SBATCH --nodes=1
#SBATCH --job-name=test_ablate_samples
#SBATCH --output=%x-%j.out
MODEL_PATH="logs/train_test_error_bar/multiruns/2025-04-11_09-32-05/2/checkpoints/epoch_294.ckpt"
uv run flow_train.py -m model.num_samples=1,3,5,10,25,50 model.num... |
d32493c04573fb47830d18c146a25cf296a41f901c1bf18c9217a05315e1bde1 | Shell | 410 | 24 | #!/bin/bash
echo Creating isolated virtual environment
source .maint/ci/env.sh
set -eu
# Required variables
echo SETUP_REQUIRES = $SETUP_REQUIRES
set -x
python -m pip install --upgrade pip virtualenv
virtualenv --python=python virtenv
source .maint/ci/activate.sh
python --version
python -m pip install -U $SETUP_R... |
a2406b0dcdd75660d9070513319b0cd5e0c030b880bae1114fc0fd2e4b18178f | Shell | 412 | 19 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr/p4-network2
WINDOW=10
GPU_ID=0
TEST_EXAMPLES=1337
ITER=20000
LAYER=prop
examples/deep-activity-rec/exePhase4 \
$WINDOW \
GPU $GPU_ID \
$OUTDIR/z_snapshot_iter_$ITER.caffemodel \
$OUTDIR/trainval-test-window-evaluation-network.prototxt \
$LAYER... |
a471bcaefb3585293eb8fef1cc7957091f0d85c6e0e6f9b79eb28117ab222abd | Shell | 412 | 19 | #!/usr/bin/env sh
OUTDIR=examples/deep-activity-rec/ibrahim16-cvpr-simple/p4-network2
WINDOW=10
GPU_ID=0
TEST_EXAMPLES=7
ITER=2
LAYER=prop
examples/deep-activity-rec/exePhase4 \
$WINDOW \
GPU $GPU_ID \
$OUTDIR/z_snapshot_iter_$ITER.caffemodel \
$OUTDIR/trainval-test-window-evaluation-network.prototxt \
$LAYER... |
c22440ec00946ce9f3fa83e8db6ecbff3b879cda744a6b280ed45fe747b19641 | Shell | 415 | 6 | export SUBJECTS_DIR=/Volumes/server/Projects/attentionpRF/derivatives/freesurfer
cd /Volumes/server/Projects/attentionpRF/labels/lh/sub-wlsubj127
mris_label2annot --s sub-wlsubj127 --h lh --ctab /Volumes/server/Projects/attentionpRF/BIDS/labels/lh/lh.NYUret.annot.ctab.rtf --a NYUretannot --l lh.ROIs_V1-4.V1.label --l... |
59ceedcf280557ba39bc63452cf74da43d5d17287af7131b3609385b0535ccc0 | Shell | 416 | 16 | #!/bin/bash
ENV_NAME="dockbiotic"
CURRENT_DIR=$(dirname "$(readlink -f "$0")")
MODELS_DIR=$CURRENT_DIR/../../saved_models
export DEEPCHEM_DATA_DIR="$CURRENT_DIR"/../../deepchem_data_dir
COMMAND="""
python $CURRENT_DIR/script.py \
--random_seed 42 \
--dataset dockstring \
--num_epochs 20 \
--model_d... |
21477cf5ff2c3e246e27c695a04a3ea89227329e46f19719f4ab0a09a92fc948 | Shell | 417 | 26 | #!/bin/bash
echo Running tests
source .maint/ci/activate.sh
set -eu
# Required variables
echo CHECK_TYPE = $CHECK_TYPE
set -x
if [ "${CHECK_TYPE}" == "doc" ]; then
cd doc
make html && make doctest
elif [ "${CHECK_TYPE}" == "tests" ]; then
pytest --doctest-modules --cov fmriprep --cov-report xml \
... |
8218036b9107c69b30a79e426f72ee944c0343773d5eda59c9c441d1836dfc41 | Shell | 417 | 18 | #!/usr/bin/env bash
set -e
file_in=${1?"error: parameter FILE_IN missing"}
dir_out=${2?"error: parameter DIR_OUT missing"}
if [ ! -f "$file_in" ]; then
>&2 echo "error: '$file_in' does not exist"
exit 1
fi
if [ ! -d "$dir_out" ]; then
>&2 echo "error: '$dir_out' is not a directory"
exit 1
fi
set -x
... |
bd1a1f8c350d276806c428c70967e53300abb52d5e5aa307089021ac6bbacc15 | Shell | 417 | 6 | for i in {1..3}; do
bash bash_scripts/mouse.sh --seed $i --experiment_name mouse_pred_$i --loss pred --prediction_target enc --pred_lr_mult 10;
bash bash_scripts/mouse.sh --seed $i --experiment_name mouse_inv_sg_$i --loss inv --prediction_target pred --pull_coef 1.0 --push_coef 20.0 --decorr_coef 200.0;
done
b... |
380a74e3ba98050fc132cd8433d9623c29c3ceae50062e7f26d8b0d03642964a | Shell | 420 | 13 | #!/usr/bin/env bash
# Customise the terminal command prompt
echo "export PROMPT_DIRTRIM=2" >> $HOME/.bashrc
echo "export PS1='\[\e[3;36m\]\w ->\[\e[0m\\] '" >> $HOME/.bashrc
export PROMPT_DIRTRIM=2
export PS1='\[\e[3;36m\]\w ->\[\e[0m\\] '
# Update Nextflow
nextflow self-update
# Update welcome message
echo "Welcome... |
a758ae1a9c61bf2bd71a86a555143efe812d43a51c85a808820d49763b46b7a6 | Shell | 420 | 17 | #!/bin/bash
# Siwei 7 Nov 2018
# remove chromosomes of alternative assembly,
# decoy, chrUn. Anything with chr name includes "_",
# and sex chromosomes
for EACHFILE in *.bed
do
echo $EACHFILE
cat $EACHFILE | grep -v "_alt" | grep -v "_random" | \
grep -v "decoy" | grep -v "chrUn_" | grep -v "chrX" | \
grep -... |
f1278e60006e4d1f1de3e093bcedf615a452a566bf704182ba0361491db27854 | Shell | 420 | 22 | #!/usr/bin/env bash
IFS=$'\n'
cd $(dirname $0)
rm data.csv/*
for file in data.in/*; do
echo "converting $file to .csv"
./bin/xlsx_to_csv.sh "$file" data.csv/
done
rm data.resampled/*
for file in data.csv/*; do
echo "resampling $file"
./bin/resample.py "$file" data.resampled
done
for file in data.r... |
eee9797a6cfb47ad05b695bc3abd3917e752e83f38651ed36a6a3974f99154fd | Shell | 421 | 21 | #!/bin/bash
# run in the folder:
# ./md5.sh checksum_md5_zipped.txt
# OR
# ./md5.sh checksum_md5_unzipped.txt
while read -r p; do
A="$(echo "$p" | cut -d' ' -f1)"
B="$(echo "$p" | cut -d' ' -f2)"
if [ ! -f "$B" ]
then
echo "ERROR: $B does not exist"
continue
fi
read -r C < <(md5 -q "$B")
echo "$... |
a001ea324dce3ddae53fbb894ea8642460fd84496c7e250ca9878158f5301f79 | Shell | 423 | 18 | #!/usr/bin/env bash
# Script to install / update and clean unwanted package in one command
set -e
export DEBIAN_FRONTEND=noninteractive
/usr/bin/apt-get update
if [ "$1" == "--purge" ]; then
shift
/usr/bin/apt-get -y purge $*
else
/usr/bin/apt-get -y install --no-install-recommends $*
fi
/usr/bin/apt-get... |
c32370d81c9065d278ddf71bbd47fa308ab78ca29d5689289687640622b63813 | Shell | 424 | 9 | #!/bin/bash
module add miniconda3-4.5.11-gcc-8.2.0-oqs2mbg
conda create -p /home/data/nbc/misc-projects/Peraza_large-scale-ibma/env/nv-ibma_env pip python=3.10 -y
conda config --append envs_dirs /home/data/nbc/misc-projects/Peraza_large-scale-ibma/env
source activate /home/data/nbc/misc-projects/Peraza_large-scale-ib... |
90d78368a83f69aba9133e060d85145bc7ab7913d898e8da4c2c8b6cabd931dc | Shell | 426 | 14 | #!/bin/sh
### Minimum requirements to run script: ImageMagick(6.8)
# Input: cropped rectangular strips of full IHC images, spanning the apicobasal axis of the developing cortex
mkdir sliced
for f in $PWD/*.tif; do
name=`echo "$f" | sed s/\.tif$//`
filename=$(basename $f .tif)
convert ${f} -resize "1000x1000>" ... |
b677af513cd0fb195943d69e6f7b403be0d17d702cb5ec5a9f637d1d19234ea5 | Shell | 426 | 10 | #!/bin/sh
cd 3rdparty/ultravnc
find -name "*.vcproj" -o -name "*.vcxproj" -o -name "*.vdproj" -o -name "*.sln" | xargs rm
rm -rf avilog translations old vncviewer zipunzip_src libjpeg-turbo-win winvnc/winvnc/res setcad setpasswd lzo* xz* zlib* zstd* JavaViewer repeater uvnc* *.iss *.zip
cd DSMPlugin
rm -rf MSRC4Plugin... |
5a3437b3dad0fb5f5dcf57222f045c28139034730646d77d2bd5cf43f6cbb865 | Shell | 427 | 23 | #!/bin/bash
#$ -S /bin/bash
#$ -cwd
#$ -V
#$ -l h_vmem=6G,h_rt=20:00:00,tmem=6G
# join stdout and stderr output
#$ -j y
#$ -R y
#$ -N single_steps_conda_envs
# This one uses the default/universal single steps conda env
smk="single_steps/sort_pull.smk"
snakemake \
-p \
-s $smk \
--conda-prefix "/SAN/vyplab/vyplab_re... |
cdae8c3582c6921678e4daeabe440229a1dfbc2f6cf41bff50acfa038a9e5491 | Shell | 427 | 23 | #!/bin/bash
# Siwei 06 Jun 2023
# Siwei 07 Jun 2022
mkdir -p annot_file
for eachfile in output_bed4/*.bed
do
base_bed_name=$(basename -- $eachfile)
base_bed_name=${base_bed_name/%.bed/}
echo $base_bed_name
parallel -j 23 \
python ..//make_annot.py \
--bed-file $eachfile \
--bimfile ../1000G_EUR_Phase... |
30e136e485f88f27ec148649d34c1947a8e291432f3a1becefae0a228a7d1b0e | Shell | 428 | 6 |
# python test-stDiff.py --sc_data 'dataset16_seq_118.h5ad' --sp_data 'dataset16_spatial_118.h5ad' --document 'dataset16_stDiff_test' --batch_size 2048 --hidden_size 512
python test-baseline.py --sc_data 'dataset5_seq_915.h5ad' --sp_data 'dataset5_spatial_915.h5ad' --document 'dataset5_base_test'
# python test-base... |
31b0db39873790c51253e36dea71594b95daa713b67c1180dabc171a1066d8fd | Shell | 429 | 14 | #!/usr/bin/bash -i
#SBATCH -n 1
#SBATCH -c 64
#SBATCH -p hgx
#SBATCH --gres=gpu:06
#SBATCH -t 168:00:00
source ~/.bashrc
conda activate gnn_test
torchrun \
--standalone \
--nproc_per_node=6 \
src/grapharna/main_rna_pdb.py --dataset RNA-PDB-clean --epoch=1000 --batch_size=16 --dim=256 --n_layer=6 --lr=1e-3... |
44502d9d14b649d7cbb09dd77598389a787dca4cff099823a801c030a53675c0 | Shell | 429 | 23 | #!/bin/bash
# Siwei 06 Jun 2023
# Siwei 07 Jun 2022
mkdir -p annot_file
for eachfile in output_bed4/DN*.bed
do
base_bed_name=$(basename -- $eachfile)
base_bed_name=${base_bed_name/%.bed/}
echo $base_bed_name
parallel -j 23 \
python ..//make_annot.py \
--bed-file $eachfile \
--bimfile ../1000G_EUR_Pha... |
21c4b393480eb96813e09d638264434fab1c6138690aa55c2ea460c474cb3418 | Shell | 430 | 10 | #!/bin/sh
gource -c 4 -b 000000 -1280x720 --auto-skip-seconds .1 \
--hide mouse,progress --title "Connectome Mapper Development History" \
--output-ppm-stream - | \
ffmpeg -y -f 30 -r 28 -f image2pipe \
-vcodec ppm -i - -vcodec libx264 -preset veryslow \
-crf 28 -threads 0 -o - | \
ffmpeg -i - -filt... |
6bde0972b45c97a5bc504a87b5ebe310479b41735b2aeb578dc9fc4d4f9bbe79 | Shell | 430 | 10 | #!/bin/bash
cd app/vpn
./vpncmd /server 156.35.95.36 /password:'e9Ep!SH5Zu*5' /in:get_tables.txt /out:temp.txt
cat temp.txt | grep -v "VPN Server" | grep -v "SoftEther" | grep -v "Compiled" | grep -v "Version" | grep -v "command" | grep -v "Virtual Hub" > ../../input.txt
cd ..
cd ..
python3 parse.py
sudo veyon-cli netw... |
da47c1e115438d5eabb2c1ba6eed04ea21900b2df63bf966cb0a560cd48e2e8e | Shell | 430 | 18 | #!/usr/bin/env zsh
#SBATCH -o slurm_output.txt
#SBATCH -e slurm_error.txt
#SBATCH -J seq2seq
#SBATCH --partition gpu_p
#SBATCH --cpus-per-task 6
#SBATCH --mem=16G
#SBATCH --exclude=supergpu05
#SBATCH --gres=gpu:1
#SBATCH --gres=mps:40
#SBATCH --qos=gpu
#SBATCH --time 05:00:00
#SBATCH --nice=10000
echo "Started runnin... |
1b942ccaac5eec467b6d42348f6219ad3f3bdca80982ff76b443a7fe8fd25722 | Shell | 431 | 5 | awk '{print $3,$4,$4+length($5)-1,$5,$6,$7,$8,$9,$10,$11,$12,$13,$2,$1}' snv_list.combined.txt > annovar_annotation/snv_list.combined.avinput
annotate_variation.pl -build hg19 snv_list.combined.avinput humandb/
awk '{print $3,$4,$4+length($5)-1,$5,$6,$7,$8,$9,$10,$11,$12,$13,$2,$1}' indel_list.combined.txt > annovar... |
211032b284fd9afb47a055c61cb733fcc01394ce4d3a6b56c68d09a2bb89511b | Shell | 432 | 12 | #!/bin/bash
# File: buildNetInf.sh
# SPDX-License-Identifier: GPL-3.0
# This file is part of NetInf (https://github.com/neuro8000/NetInf),
# developed by Peter M. Rasmussen, Aarhus University, Denmark.
# It is distributed under the terms of the GNU General Public License v3.0.
# See the LICENSE file or https://www.gnu.... |
bda65f5cf722e4a525fa2bb34a22b96f6d01b60088df8f0962280e60d3ec5ace | Shell | 432 | 12 | #!/usr/bin/env bash
# Local mirror of .github/workflows/lint_sqlfluff.yml for changed concept SQL.
set -euo pipefail
BASE_REF="${1:-origin/main}"
files="$(git diff --name-only --diff-filter=AM "${BASE_REF}...HEAD" -- 'mimic-iv/concepts/' \
| grep -E '[.]sql$' || true)"
if [[ -z "${files}" ]]; then
echo "No changed ... |
9f4f8b96386dc968cb7bce6fd0396a0190ba35c042dbc90aa1bebac4b2ca177c | Shell | 434 | 18 | #!/usr/bin/env bash
echo "removing old files..."
rm -rf build
rm -rf dist
# Check if error introducing packages are still there
pip uninstall enum34
pip uninstall imagecodecs
echo "building app..."
#onefile
pyinstaller -y --clean aydin.spec
mkdir -p dist/aydin/numba/experimental/jitclass
cp /PATH/TO/numba/experime... |
a322f30764e943b54dbb13696fb0d604a332120f7a51a10b6e5aafd3dc3ef363 | Shell | 438 | 11 | #! /bin/bash
set -eu -o pipefail
ROOT_INPUT_DICOM_DIR="/kaapana/app/dicom"
ROOT_OUTPUT_NRRD_DIR="/kaapana/app/nrrd"
for INPUT_DICOM_DIR in $( find ${ROOT_INPUT_DICOM_DIR} -mindepth 1 -maxdepth 1 -type d); do
IDENTIFIER=$( basename ${INPUT_DICOM_DIR} )
mkdir -p ${ROOT_OUTPUT_NRRD_DIR}/${IDENTIFIER}
/kaapan... |
497a87594e3b0f134b217147c863ec9261192fee2ede20917d4ed83e814903a7 | Shell | 439 | 21 | #! /bin/bash
# Siwei 18 May 2021
# Call peaks use MACS2
# use conda environment encode-atac-seq-pipeline (python 3.7)
# appearently there are compatibility issues with python 3.8.8
## list all .bam files
shopt -s nullglob
bam_array=(*.bam)
echo "${bam_array[@]}"
macs2 callpeak \
-t ${bam_array[@]} -f BAMPE -g 2.7e... |
2b1287d7a6520ce726394e17fd90c17d4d1e5464d4bf014354ca4c494148a701 | Shell | 440 | 23 | #!/bin/bash
function mul_by_minus_one {
original_image=$1
im_name=$(basename $original_image .nii.gz)
fslmaths $original_image -mul -1 $PWD/inverted_subject_maps/${im_name}_mul_by_minus_one
}
export -f mul_by_minus_one
mkdir inverted_subject_maps
echo $PWD/subject_maps/*_z.nii.gz | ... |
4bc027ea977fe6635aff59478d734b52cf2e0bfde59d1327af7083e6e46fb963 | Shell | 440 | 18 | #!/usr/bin/env bash
echo "removing old files..."
rm -rf build
rm -rf dist
# Check if error introducing packages are still there
pip uninstall enum34
pip uninstall imagecodecs
echo "building app..."
#onefile
pyinstaller -w -F -y --clean aydin.spec
mkdir -p dist/aydin/numba/experimental/jitclass
cp /PATH/TO/numba/ex... |
aa0f29cd834ce5e561cb712f471f4479039a576deb9720973580fa2c50ed7e32 | Shell | 441 | 19 | #!/bin/bash
# Siwei 04 Jul 2023
# move all BAM files of Het 10792832 to downsample folder
target_folder="downsample_100M/MG"
mkdir -p $target_folder
het_list_file="MG_rs10792832_het_list.list"
readarray -t het_file_names_array < $het_list_file
for ((i=0; i<${#het_file_names_array[@]}; i++ ))
do
echo ${het_file_na... |
e6d946d594d1afd495fffd31de53f1e059fe7ed8a0b268820f8d2cc07e8ff65c | Shell | 442 | 26 | #!/usr/bin/env bash
set -e
CPUS=$(nproc)
BASEDIR=$(pwd)
BUILDDIR=/tmp/build-$1
$BASEDIR/.ci/common/strip-ultravnc-sources.sh
rm -rf $BUILDDIR
mkdir $BUILDDIR
cd $BUILDDIR
cmake $BASEDIR -DCMAKE_TOOLCHAIN_FILE=$BASEDIR/cmake/modules/Win${1}Toolchain.cmake -DCMAKE_MODULE_PATH=$BASEDIR/cmake/modules/
echo Building o... |
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