sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
9f3bb43dc5bdca774d284489635b8a4987943ee0ac8c5117d43d5b8f317a6ff4 | Shell | 359 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kg.o
#SBATCH -J DeepG
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beocat_eigendecomposition.R --kernel1 results/05.deep_kernel/deep_Kg.rds --outfile r... |
a59a2a53101527921ad5acbcc235e6b7ca1f330735f974f803112a1cb84e5913 | Shell | 359 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Ks.o
#SBATCH -J DeepS
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beocat_eigendecomposition.R --kernel1 results/05.deep_kernel/deep_Ks.rds --outfile r... |
4c2fb7056ebedac010aeb8ffba785394301d0d815ddb6c5acd121d951f05c6fe | Shell | 363 | 7 | #!/bin/zsh
Rscript 08.DNNs/03f.train_soil.R --seed 42024 > train_soil_42024.log
Rscript 08.DNNs/03f.train_soil.R --seed 16408 > train_soil_16408.log
Rscript 08.DNNs/03f.train_soil.R --seed 633452 > train_soil_633452.log
Rscript 08.DNNs/03f.train_soil.R --seed 573144 > train_soil_573144.log
Rscript 08.DNNs/03f.train_so... |
db4f2d64a7a98c418da5d1b78e2caa2ec44138fdf09094d8732c2f107ea21d48 | Shell | 363 | 7 | #!/bin/zsh
Rscript 08.DNNs/03f.train_soil.R --seed 3483 > train_soil_3483.log
Rscript 08.DNNs/03f.train_soil.R --seed 498320 > train_soil_498320.log
Rscript 08.DNNs/03f.train_soil.R --seed 851889 > train_soil_851889.log
Rscript 08.DNNs/03f.train_soil.R --seed 151773 > train_soil_151773.log
Rscript 08.DNNs/03f.train_so... |
4d264117bb40cbea99acd29a3f0a73ee65e92ce0c83b6000e7aaf855843dd31b | Shell | 366 | 16 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kw_sum.o
#SBATCH -J DeepWsum
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beocat_eigendecomposition.R --kernel1 results/05.deep_kernel/deep_Kw.rds --ou... |
fde82c6320e6b8064c8019a8905f59b5de52b7bb8a87fbb9a3239e370dee6253 | Shell | 368 | 12 | #!/bin/bash
#Copyright 2025. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR
bart extract 10 660 730 ../02_data_realtime/ksp ksp
time $BART_TOOLBOX_PATH/scripts/rtreco.sh -G ksp img
time $BART_... |
09d170a2f13a65cbc613d2dacdac243ac453e93d2427c1c903bb249847d5a8be | Shell | 369 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kd.o
#SBATCH -J DeepD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Kd.rds --out... |
1badc2c43cfc775fcf6038426293e844c1e76620f70f602a9c92de857777a400 | Shell | 369 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Ka.o
#SBATCH -J DeepA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Ka.rds --out... |
d4120a45c4f49fff0353ade84cc457444528c97febcec1ad24bc22d88bd3fc48 | Shell | 373 | 11 | #!/bin/bash
if [ -z "${BUILD_ENVIRONMENT}" ] || [[ "${BUILD_ENVIRONMENT}" == *-build* ]]; then
# shellcheck source=./macos-build.sh
source "$(dirname "${BASH_SOURCE[0]}")/macos-build.sh"
fi
if [ -z "${BUILD_ENVIRONMENT}" ] || [[ "${BUILD_ENVIRONMENT}" == *-test* ]]; then
# shellcheck source=./macos-test.sh
sour... |
4109b8e94621191da612a2ec58bc4d282a56b8a502107c0616a7f83640694e6a | Shell | 376 | 10 | #!/bin/bash
echo 'Create new environment named non_attribute_movement_and_EEG'
conda create -n non_attribute_movement_and_EEG python=3.6
source $(conda info --base)/etc/profile.d/conda.sh
conda activate non_attribute_movement_and_EEG
conda install pandas
conda install -c anaconda keras-gpu
conda install matplotlib
cond... |
639fb0391a22aa9d9274a9d7627ae4ec7244301011aa2233e542c0b59ddbc8a0 | Shell | 377 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Kd.o
#SBATCH -J LinearD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Kd.rds... |
9509d29ecc0b8af36a9a6407f53a54bd8befa49f7ede8b5a7a9d1f8308f76a3d | Shell | 377 | 15 | #!/usr/bin/env bash
declare -a links=(
"schnorb_hamiltonian_water.tgz"
"schnorb_hamiltonian_uracil.tgz"
"schnorb_hamiltonian_malondialdehyde.tgz"
"schnorb_hamiltonian_ethanol_hf.tgz"
"schnorb_hamiltonian_ethanol_dft.tgz"
)
for l in "${links[@]}"; do
echo "Working with $l"
wget http://quantum-machine.org... |
ecdde86161dee2f4fdba2844afe67f9468e8e1fc2a218e7d91ba397f2656e27e | Shell | 377 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Ka.o
#SBATCH -J LinearA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Ka.rds... |
c83da38bb471c45429d953552c4b10d5de41fb0c3772faa42718f7e2261e204e | Shell | 379 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Kd.o
#SBATCH -J GaussD
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Kd.rds... |
d73790e6fd3bcb2ce62cb6c7d560a25b59e1b3e1e598950c64c723b3a48e5913 | Shell | 379 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=48:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Ka.o
#SBATCH -J GaussA
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Ka.rds... |
a9865d5aed4dca4ac057ad9cbd0ddf74a56763db2207b737f5f28ecde54ace4a | Shell | 382 | 13 | #!/bin/bash
#Copyright 2025. TU Graz. Institute of Biomedical Imaging.
#Author: Moritz Blumenthal
set -eu
SCRIPT_DIR=$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )
cd $SCRIPT_DIR
bash run.sh
cfl2png -CC -x1 -y0 -u0.5 col col
cfl2png -CC -x1 -y0 scale scale
python fig.py col scale $(basename $SCRIPT... |
b30a9d4578420319f7f7a24207630d1d14a67bce8cca2f6d589c858c66021eee | Shell | 386 | 16 | #cd to FA folder
tbss_1_preproc *nii.gz
cd origdata
for a in *
do
subname=`imglob $a`;
fslmaths ../FA/${subname}_FA -bin ../${subname}_mask;
Atropos -d 3 -a ${a} -x ../${subname}_mask.nii.gz -i Kmeans[2] -m [${mrf},1x1x1] -o [../segmentation.nii.gz,../${subname}_%02d.nii.gz]
fslmaths ../${subname}_mask -sub ../..... |
5787b9633741bd4612ee060748cbfce43327b5268b4bbd249c935c73c19f8363 | Shell | 392 | 7 | #!/bin/zsh
Rscript 08.DNNs/02f.train_gPCs.R --seed 296226 > logs/train_gPCs_296226.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 938747 > logs/train_gPCs_938747.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 219460 > logs/train_gPCs_219460.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 166621 > logs/train_gPCs_166621.log
Rscr... |
f6d600314164a5ebcffce8ecf76532a0c303196af0f1156d54fd6c74d2df321c | Shell | 392 | 7 | #!/bin/zsh
Rscript 08.DNNs/02f.train_gPCs.R --seed 234493 > logs/train_gPCs_234493.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 361352 > logs/train_gPCs_361352.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 653804 > logs/train_gPCs_653804.log
Rscript 08.DNNs/02f.train_gPCs.R --seed 640542 > logs/train_gPCs_640542.log
Rscr... |
a752f8fd809aec5434158287bbeb6a18fb8365922ab262b6c718bcfb37e7f8cd | Shell | 397 | 10 | for isimu in '_d_2_r_1_noise_1.0'
do
python simu_poi_data.py ${isimu}
cp simu_poi_data.py data/simu_100${isimu}/
cp simu_poi_fit.R data/simu_100${isimu}/
Rscript --no-save --no-restore --verbose simu_poi_fit.R ${isimu} &> out${isimu}_fit.txt
mv out${isimu}_fit.txt results/
python simu_poi_plot.... |
2adab74d37d2ae7936a7876a8c4861e3de0a19ddf864703fa9a2e6205310b974 | Shell | 398 | 10 | #!/bin/bash
sudo apt-get update
# also install ssh to avoid error of:
# --------------------------------------------------------------------------
# The value of the MCA parameter "plm_rsh_agent" was set to a path
# that could not be found:
# plm_rsh_agent: ssh : rsh
sudo apt-get install -y ssh
sudo apt-get install ... |
86475cf3919a6cd4f913cae2ae19f6de91c40c53c64e3fff309ad9aa2cc4e454 | Shell | 398 | 10 | #!/bin/sh
. "$(dirname "$0")/lib.sh"
announce "iad two-sphere MC smoke case"
out="$TEST_TMP/two_sphere_mc.out"
"$IAD_EXECUTABLE" -V 0 -r 0.2 -t 0.1 -u 0.0049787 -S 2 -M 1 -p 1000 \
-1 "200 13 13 2 0.95" -2 "200 13 0 2 0.95" > "$out" 2>&1
"$PYTHON" "$CLI_DIR/compare_numeric.py" --extract-last "$out" > "$TEST_TMP/t... |
bd75ac558e7491acaeb03e567239c460a0e08f4af272e52d2af39bd21e5c7b0b | Shell | 398 | 10 | #!/bin/sh
. "$(dirname "$0")/lib.sh"
announce "iad one-sphere MC smoke case"
out="$TEST_TMP/one_sphere_mc.out"
"$IAD_EXECUTABLE" -V 0 -r 0.2 -t 0.2 -u 0.0049787 -S 1 -M 1 -p 1000 \
-1 "100 13 13 2 0.95" -2 "100 13 0 2 0.95" > "$out" 2>&1
"$PYTHON" "$CLI_DIR/compare_numeric.py" --extract-last "$out" > "$TEST_TMP/o... |
c0aef8cd575437df8260d960caee03ebd46818b6a33389cea8f7ab289b7a869e | Shell | 398 | 9 | while read x; do
echo ""$x" <- \"hoskens_"$x".bed\"
bed."$x" <- import("$x", genome = \"hg19\")
job_"$x" = submitGreatJob(bed."$x",
genome = \"hg19\")
"$x".tbl = getEnrichmentTables(job_"$x")
"$x"_gene_regions = getRegionGeneAssociations(job_"$x", verbose = great_opt$verbose)
"$x"_genes <- unique(... |
dcf4c4b6416679e126b00b0933aee433f2d56f7b460e8cccdce21db909e1dd46 | Shell | 398 | 21 | #!/bin/bash
set -euxo pipefail
# Download requirements
cd llm-target-determinator
pip install -q -r requirements.txt
cd ../codellama
pip install --no-build-isolation -v -e .
pip install numpy==1.26.0
# Run indexer
cd ../llm-target-determinator
torchrun \
--standalone \
--nnodes=1 \
--nproc-per-node=1 \
... |
8b1de85611a1a388bb25857d36e0caede867bbfc3edc0b9c5befad190b21374e | Shell | 400 | 17 |
#!/usr/bin/env bash
set -e
echo "🔪 Killing any old processes…"
pkill -u "$(whoami)" gunicorn || true
pkill -f "python -m app.main" -u "$(whoami)" || true
echo "🚀 Starting main API server…"
nohup \
poetry run gunicorn -w 1 --timeout 300 \
-k uvicorn.workers.UvicornWorker app.main:app \
--bind 0.0.0.0:102... |
af998d7ddeb266adb97269d3dde595f934af0097dfd11a61146759bd8e47cfd0 | Shell | 405 | 21 | buildah build \
--format oci \
-t "radar/riab:0.0.64" \
-f ../Dockerfile
podman run \
--rm \
-it \
-v ./riab.ini:/riab.ini \
-v .:/cdm_folder \
-e RIAB_CONFIG=/riab.ini \
localhost/radar/riab:0.0.64 -r /cdm_folder -t cdm_source
podman run \
--rm \
-it \
-v ./riab.ini:/riab.ini \
-v .:/cdm_fo... |
6e32baf46a065d9ed68d4a26b74338df1b216580cbcbe55861fc182151867680 | Shell | 406 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Khs.o
#SBATCH -J DeepHS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/deep_hPCs.rds --kerne... |
a7ba7b9c17edb3017460f602fe80d454ec7c6ba0fc1ddf91e17fe047427983b0 | Shell | 406 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Khw.o
#SBATCH -J DeepHW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/deep_hPCs.rds --kerne... |
1104b143517b973cf15a6aa3d60eb132d99e6c739972b1c1c89538de728fa3e8 | Shell | 407 | 11 | ##############################################################################
## PoissonSimulation_main.py
## by Yasuhiro Tsubo modified ver. 2023.10.09
## iMacPro: 8 m 27 s
## [in]
## [out]
## DATAID_PoissonSim_rate_*.pkl 6 m
########################################################################... |
681d44b0ca74fdb1770158de7d6413a7fc5899119474f94d9666f6bb3266413b | Shell | 407 | 16 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kgs.o
#SBATCH -J DeepGS
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beocat_eigendecomposition.R --kernel1 results/05.deep_kernel/deep_Kg.rds --kernel2... |
459d8e868e954b73e754cc07aa7244913f53f6a140af02c14ecd905f7f1e10ac | Shell | 408 | 17 | #!/bin/sh
curr_dir=`pwd`
for folder in */
do
echo "[TEST](start) $folder"
cd $curr_dir
cp -r $folder $CBIG_CODE_DIR/stable_projects/
git add $CBIG_CODE_DIR/stable_projects/$folder/*
git commit -m "test"
cd $CBIG_CODE_DIR
yes | $CBIG_CODE_DIR/hooks/pre-push
git reset HEAD~1
rm -r $CBIG_CODE_DIR/stable_project... |
4286ac0a202be43e0bb49b7b9b4561714ed65dfb9e39c36227cae95abc0f61f0 | Shell | 410 | 12 | CUDA__VERSION=$(nvcc --version|sed -n 4p|cut -f5 -d" "|cut -f1 -d",")
if [ "$CUDA__VERSION" != "$DESIRED_CUDA" ]; then
echo "CUDA Version is not $DESIRED_CUDA. CUDA Version found: $CUDA__VERSION"
exit 1
fi
mkdir build
cd build
cmake .. -DUSE_FORTRAN=OFF -DGPU_TARGET="All" -DCMAKE_INSTALL_PREFIX="$INSTALL_DIR" ... |
b443c9efc45018d3c459e05eb6e61e1053e5a7234e4da906b209f479b042c9ce | Shell | 410 | 16 | #!/bin/bash
#SBATCH --mem=24G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kgw.o
#SBATCH -J DeepGWsum
#SBATCH --mail-type=ALL
module reset
module load R
Rscript --vanilla $HOME/kernels_in_GP/beocat_eigendecomposition.R --kernel1 results/05.deep_kernel/deep_Kg.rds --kern... |
c8fd645c11a80fa624ae754a4c18fe8d102978b52602bdbf5bc25b5f3e752a7c | Shell | 412 | 5 | #! /bin/bash
arch_flags=""
py_dir="/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/"
../../configure --enable-module --disable-dependency-tracking --prefix=${py_dir}/stfio CPPFLAGS="-DH5_USE_16_API" CFLAGS="" CXXFLAGS="-I/opt/local/include" LDFLAGS="-headerpad_max_install_names ... |
2a007cc8749c137f96d4c8dff12a74a9c3005b34c1226b73474de031fbed35bc | Shell | 413 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=TanhHPCs.o
#SBATCH -J TanhHPCs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-foss-2022... |
699be0377fc9e9e317f78b91557305f32975da37afb6ddfbf4f5414c87a462ab | Shell | 414 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=TanhSNPs.o
#SBATCH -J TanhSNPs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-foss-2022... |
af1e40ea506d8e28d614e3c0d4770f290b147876b7d451e8df28b961816d9b81 | Shell | 415 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=DenseHPCs.o
#SBATCH -J DenseHPCs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-foss-20... |
325dbe7faf583110058f5cf2f222eb1da4f1b12920e6de608a9421beaa82d7de | Shell | 416 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=DenseSNPs.o
#SBATCH -J DenseSNPs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-foss-20... |
0aeca31673f30e79daf46f46bb29af61b14ce1a2fe48c7a1da629736f4b458f4 | Shell | 417 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kas.o
#SBATCH -J DeepAS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Ka.rds --k... |
244db23009687ce6e97849e489bd202a2fb6718e9d18cb67e73c6f8ae60e4f67 | Shell | 417 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Khw.o
#SBATCH -J LinearHW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/linear_hPCs.rds -... |
525b504644a327244568c660381d1640edc07c4a62cd7c3c0ab957a42cec7f5c | Shell | 417 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kdw.o
#SBATCH -J DeepDW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Kd.rds --k... |
88b8caab43027f53c5f8a0ac4b330a6b2514fd499760f5e6ef76c1ad225368d1 | Shell | 417 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kaw.o
#SBATCH -J DeepAW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Ka.rds --k... |
cb3d3d0d429d70e1a72a6d3a6c814efd0d0a796b0ae76c578799cddfa9c980f1 | Shell | 417 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=deep_Kds.o
#SBATCH -J DeepDS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/deep_Kd.rds --k... |
993d1edce5620610595d88d35c78e259519e7e9a5c9b9384fbff25d340f4bec7 | Shell | 418 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Khs.o
#SBATCH -J LinearHS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/linear_hPCs.rds -... |
57aeaad092c41f9739c3eb011c7a0deb69bdde0b588c22df7b53d45ea23ac7ad | Shell | 420 | 14 | #/bin/bash
sample_name=$(basename $1)
reference_name=$2
for genotyper in freebayes gatk bcftools
do
bcftools norm --fasta-ref $reference_name --multiallelics - $1-${genotyper}.vcf | \
bcftools query -f "${genotyper},[%SAMPLE],%CHROM,%POS,%ID,%REF,%ALT,%QUAL,[%AD],[%DP],[%GT]\n" | \
sed "s/,\.,/,,/g"... |
30729433f91c16d3681218b7bbf0935ed2a452c0e074ceffabface5ff1b36258 | Shell | 422 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=SigmoidHPCs.o
#SBATCH -J SigmoidHPCs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-fos... |
0836ca54f20a8d4856d6b30873c313b5905da021e329de9cb7cb7f25bbadcf07 | Shell | 423 | 19 | #!/bin/bash
#SBATCH --mem-per-cpu=10G
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=SigmoidSNPs.o
#SBATCH -J SigmoidSNPs
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load TensorFlow/2.11.0-fos... |
5a6264c2da5a767af3ce22970695b08381942a9b43c36a901053d529bb9c4363 | Shell | 424 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Khs.o
#SBATCH -J GaussHS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/gaussian_hPCs.rds -... |
aa21bf649a17239ad8e9b991359ac61042cfcfa7f40e0a6157f672bcb678de2d | Shell | 424 | 15 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Khw.o
#SBATCH -J GaussHW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/hPCs_kernels/gaussian_hPCs.rds -... |
9d6e76894603051624875015210cd0254b0652d27c9598553650dfda19777166 | Shell | 425 | 23 | #!/bin/bash
# shellcheck disable=SC1090
set -eux -o pipefail
source "${BINARY_ENV_FILE:-/c/w/env}"
export CUDA_VERSION="${DESIRED_CUDA/cu/}"
export VC_YEAR=2022
if [[ "$DESIRED_CUDA" == 'xpu' ]]; then
export VC_YEAR=2022
export XPU_VERSION=2026.1
fi
pushd "$PYTORCH_ROOT/.ci/pytorch/"
if [[ "$OS" == "window... |
77110fa12f8567c9820713409bd010fc3d4f771f3638eda4adbd787a7f7ffa26 | Shell | 426 | 3 | #! /bin/bash
/Users/cs/wxPython-src-2.9.2.4/configure --enable-unicode --with-osx_cocoa --prefix=/Users/cs/wxbin --with-opengl --enable-sound --enable-graphics_ctx --enable-mediactrl --enable-display --enable-geometry --enable-debug_flag --enable-optimise --disable-debugreport --enable-uiactionsim --enable-monolithic ... |
5e9478c82e9ccfae91f575a10d6cf4c5349de1dceeb7013fb745b7995cd3c804 | Shell | 427 | 18 | #!/bin/bash
#SBATCH -J MACEH
#SBATCH --time=02:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=32
#SBATCH --mem-per-cpu=3850
#SBATCH --cpus-per-task=1
#SBATCH --output=%j.out
#SBATCH --partition=compute
#SBATCH --account=su007-rjm
module purge
module load GCC/13.2.0 CUDA/11.8.0
python_path="/home/c/chenqian3/.conda... |
6b4954f2fed755851c6caaa8cf59227cc59bd64c561b7b5e1c14bad1d4130c8e | Shell | 428 | 14 |
for ps_model in "random_forest_cv"
do
# DE test
Rscript --no-save --no-restore --verbose 2-DE.R ${ps_model} > out.txt 2>&1
mv out.txt results/${ps_model}/DE/out.txt
# GO analysis
Rscript --no-save --no-restore --verbose 3-GO.R ${ps_model} > out.txt 2>&1
mv out.txt results/${ps_model}/GO/out.... |
76bfa6c888e207b0a38b340255765dba2f69f131e447a72f922e4bb06ac66719 | Shell | 428 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Kdw.o
#SBATCH -J LinearDW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Kd.r... |
c517e1445101ac6ea7e98e7eb544272a9d1ac7895bccfd189b6d24af2d3c1467 | Shell | 428 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Kaw.o
#SBATCH -J LinearAW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Ka.r... |
5742cf8024177a0048eb50a3b597a118d9b0e6d3cd72855bd7f7b929aa099e7c | Shell | 429 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Kds.o
#SBATCH -J LinearDS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Kd.r... |
eb67c7e37df744f27dda818060689f3c60805e8402358aba8ee94cc207c469ed | Shell | 429 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=linear_Kas.o
#SBATCH -J LinearAS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/linear_Ka.r... |
de17be9462125be554e83f7bd5715e8865c905bf80194d98134a159b0a3a2cea | Shell | 431 | 11 | #!/bin/bash
#SBATCH --job-name=spyking-circus
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=128G
#SBATCH --cpus-per-task=24
#SBATCH --output=/network/lustre/iss01/charpier/analyses/stephen.whitmarsh/slurm/%A-%a-%x-output.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/stephen.whitm... |
3204421b9fa7d2619d72f912c69427847f2032af0f3a09acdcd10700b7accf6e | Shell | 433 | 11 | #!/bin/bash
#SBATCH --job-name=spyking-circus_normalmem
#SBATCH --partition=normal
#SBATCH --time=99:99:99
#SBATCH --mem=64G
#SBATCH --cpus-per-task=24
#SBATCH --output=/network/lustre/iss01/charpier/analyses/stephen.whitmarsh/slurm/%A-%a-%x-output.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/stephen.whi... |
b24ece6f26eee2ce94a72def0acc11fa52ce0d99d93f7064ea18ba305421d2cf | Shell | 433 | 29 | #!/bin/bash -e
if [ "$#" -ne 1 ]; then
echo "usage: ${0} <path to docs>"
exit 1
fi
path_to_docs=$1
echo "Prefetch datasets"
python scripts/prefetch_docs_datasets.py
cd ${path_to_docs}
echo "Building example notebook"
cd examples
make -j 2 notebooks
echo "Building html documentation"
cd ..
make clean
sphi... |
c9e87b825147ed1b3289bbb0f4a0215b1cfb3aa6f93cbaaeb7a7d514b5be661f | Shell | 435 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Kas.o
#SBATCH -J GaussAS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Ka.r... |
e6729b5e946e5e90096b1354324ead4814f9767d825763d9a20dbe293c592347 | Shell | 435 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Kdw.o
#SBATCH -J GaussDW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Kd.r... |
f5f24906c3ac93dbe9fe191f67ee829238e1ebdad61dd486152a9cd83be6f248 | Shell | 435 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Kds.o
#SBATCH -J GaussDS
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Kd.r... |
fd2bb666804f9f73eb3f80d9f8bd747a19dd0243c51305756a40b7a923772374 | Shell | 435 | 16 | #!/bin/bash
#SBATCH --mem=36G
#SBATCH --time=24:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --output=gauss_Kaw.o
#SBATCH -J GaussAW
#SBATCH --mail-type=ALL
module reset
module load R/4.2.1-foss-2022a
Rscript --vanilla $HOME/kernels_in_GP/beocat_evd.R --kernel1 results/07.genomic_kernels/gaussian_Ka.r... |
32c37e875bb79a1ea67faf470b63576ecf51911a89492bedba7aade5190a6edf | Shell | 436 | 9 | #!/bin/bash
set -xe
# Script used in Linux x86 and aarch64 CD pipeline
# Workaround for exposing statically linked libstdc++ CXX11 ABI symbols.
# see: https://github.com/pytorch/pytorch/issues/133437
LIBNONSHARED=$(gcc -print-file-name=libstdc++_nonshared.a)
nm -g $LIBNONSHARED | grep " T " | grep recursive_directory_... |
aaf11acb652257714874b9d75431a1c4443022ec1240bec87b0b05bc94b158cf | Shell | 439 | 15 | #!/usr/bin/env bash
# versions list: https://repo.anaconda.com/archive/
# should be a Python3.7 version thanks to `apsw`
ANACONDA=Anaconda3-2020.02-Linux-x86_64.sh
echo "Getting Anaconda3-2011.11..."
wget https://repo.anaconda.com/archive/$ANACONDA
echo "Running installation; do whatever the instruction says."
bash ... |
ecee7c73f75be55f0a389b0035f32386e366d3331e43df70c2d304108cee6c47 | Shell | 440 | 11 | #!/bin/zsh
# The purpose of this script is generate a 3D contour map (boundary map) of the tissue
# in question. This will be used in later scripts to exclude (?anomolous) cells which
# are identified outside the boundary of the tissue and to generate the final grid
# for the spatial dataframe.
$file=INPUT.tiff
$o... |
09c78bf49e3eff0cd018e49545a14513af741d1c9dabf16504bcf09b3d686cd7 | Shell | 448 | 17 | #!/bin/bash
#SBATCH -J DeepH-E3
#SBATCH --time=02:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=12
#SBATCH --mem-per-cpu=3850
#SBATCH --cpus-per-task=1
#SBATCH --output=%j.out
#SBATCH --partition=compute
#SBATCH --account=su007-rjm
module purge
module load GCC/13.2.0 CUDA/11.8.0
python_path="/home/c/chenqian3/.co... |
1667da8325002e94415ab8a2f296055f8b1f1ed42ed440ab8f001d92c305c79a | Shell | 448 | 10 | #!/usr/bin/bash
imgdir="/home/alma/Documents/PhD/papers/STSC/rsc/mob_data/resized_imgs"
tdir="/home/alma/Documents/PhD/papers/STSC/rsc/mob_data/tmats"
wdir="/home/alma/Documents/PhD/papers/STSC/res/molb/try_1"
odir="/home/alma/Documents/PhD/papers/STSC/res/molb/try_1/he_overlay"
for ii in {9..12}; do
./map2he.py ... |
78e028805074d6195ccbd86d373cad8ed0fbba819382534fea8fa396f25b750a | Shell | 455 | 13 | #!/bin/bash
# This is so kludgy, but this the input files just need to be based through as arguments
input_file=$1
sample_key=$2
model_history=$3
merged_rna_anndata=$4
model=$5
# Load module
module load singularity
# Run
singularity run --nv --bind /data/CARD_singlecell/PFC_atlas envs/single_cell_gpu.sif python /dat... |
ae433fadaefad12d02f9fd37d0ac64a995525170e99d05260e09c4188a6dd34a | Shell | 457 | 12 | #!/bin/bash
data_dir="./example_data/"
source_omics1_filename="source_omics1_example_X.csv"
source_omics2_filename="source_omics2_example_X.csv"
source_class_info_filename="source_example_y.csv"
target_omics1_filename="target_omics1_example_X.csv"
target_omics2_filename="target_omics2_example_X.csv"
python3 moDAmix... |
a8c47ce94e7e64ad08dc0e4d360904b4bf9b0181a1b3afc72218e22aaf7db08f | Shell | 460 | 11 | #!/bin/bash
#SBATCH --job-name=spyking-circus
#SBATCH --partition=bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=128G
#SBATCH --cpus-per-task=24
#SBATCH --output=/network/lustre/iss01/charpier/analyses/vn_pnh/slurm/%j_%A-%a-%x-output.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/vn_pnh/slurm/%j_%A-%a-%x-err... |
1a6fe95516af36affa235a9a5a4d6e91d35b00297c83e489c029967d145e471f | Shell | 462 | 11 | #!/bin/bash
#SBATCH --job-name=spyking-circus
#SBATCH --partition=bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=128G
#SBATCH --cpus-per-task=24
#SBATCH --output=/network/lustre/iss01/charpier/analyses/vn_pnh/slurm/%j_%A-%a-%x-output.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/vn_pnh/slurm/%j_%A-%a-%x-err... |
8e50cf43e21f7bbb5666ee7d2fb07457c0d4b45cf1ac1e97a08817ab3cf06c52 | Shell | 463 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=10G
#SBATCH --time=7-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=TanhCV-%A_%a.o
#SBATCH -J TanhCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module load T... |
f3582052e470158999c47af0c0b1442ccdc62f5a4f4f0abcfc799655265aeb47 | Shell | 466 | 19 | #!/bin/bash
#SBATCH -J DeepH-E3
#SBATCH --nodes=1
#SBATCH --time=48:00:00
#SBATCH --partition=gpu
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=42
#SBATCH --mem-per-cpu=3850
#SBATCH --gres=gpu:ampere_a100:1
#SBATCH --output=%j.out
#SBATCH --account=su007-rjm-gpu
module purge
module load GCC/13.2.0 CUDA/11.8.0
p... |
61f3469acfe6e7ee6b6fa48b1f12debaea05a86694982d5bbeb8e66a05d6dadd | Shell | 469 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=25G
#SBATCH --time=7-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=WeatherCV-%A_%a.o
#SBATCH -J WeatherCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module ... |
491e2ac4a4cc3ce55b2ac99aaea7889f622a876c08b8c9481971b808c9833a46 | Shell | 470 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=TanhHPCsCV-%A_%a.o
#SBATCH -J TanhHPCsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module... |
97f2214f7f3d27084a973cc6dcf4c90bcea826cfc47f0bf50c7f95f62c37a6fb | Shell | 471 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=TanhSNPsCV-%A_%a.o
#SBATCH -J TanhSNPsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module... |
49073623f1117885c39e203d8e0c50710df285fd9e6af96af5f37ffaf8aecba1 | Shell | 472 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=DenseHPCsCV-%A_%a.o
#SBATCH -J DenseHPCsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
modu... |
a70436bc5353cd912aba6d57c61e06576cc82b2f3bf20ba6b907039e1af9d6bb | Shell | 472 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=10G
#SBATCH --time=7-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=SigmoidCV-%A_%a.o
#SBATCH -J SigmoidCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
module ... |
28fab7019cb641b338b536a1ed1f00415b5bc270d408559b8eb26bf24dd2a1d1 | Shell | 473 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=DenseSNPsCV-%A_%a.o
#SBATCH -J DenseSNPsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
modu... |
7ab5bd19c23501e40c1d0231a52ac1e7c3f0ca65d9eb32408869149cd0cb578a | Shell | 478 | 16 | #!/bin/bash
if [[ ${#} -ne 1 ]]
then
echo "usage: source NMF-batch.sh sample_name"
fi
sample_name=${1}
script_dir=/n/scratch/users/s/sad167/EPN/scRNAseq/scripts
log_dir=/n/scratch/users/s/sad167/EPN/scRNAseq/logs/NMF
FILE=${log_dir}/rank6_${sample_name}.out
if [ ! -f "$FILE" ]; then
sbatch -o ${log_dir}... |
13eba90dbcd0c7bf50c6a319a9d6527be46ef3ea78f33e81d04997559301e83b | Shell | 479 | 16 | #!/bin/bash
# this example uses a single node (`NUM_NODES=1`) w/ 4 GPUs (`NUM_GPUS_PER_NODE=4`)
export NCCL_P2P_LEVEL=NVL
export NUM_NODES=1
export NUM_GPUS_PER_NODE=2
export NODE_RANK=0
export WORLD_SIZE=$(($NUM_NODES * $NUM_GPUS_PER_NODE))
# launch your script w/ `torch.distributed.launch`
python -m torch.distribut... |
29c5bfc5b5b57056637ed04f0bfc1b5bcdf555a51f2eafbf74238a140bd84a43 | Shell | 479 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=SigmoidHPCsCV-%A_%a.o
#SBATCH -J SigmoidHPCsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
... |
d1948f9c82ffea4ea524fc0abbd81f3315766a1ef148d86bf448504cb10d3db5 | Shell | 479 | 21 | #!/bin/bash
#SBATCH --array=1-10:1
#SBATCH --mem-per-cpu=25G
#SBATCH --time=2-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=WeatherTrain-%A_%a.o
#SBATCH -J WeatherTrain
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
m... |
7ee82320ffd489651b7ae039c46e0ea7d17bbafce90216fe43b0aae072742542 | Shell | 480 | 21 | #!/bin/bash
#SBATCH --array=0-39:1
#SBATCH --mem-per-cpu=2G
#SBATCH --time=5-00:00:00
#SBATCH --nodes=1
#SBATCH --tasks-per-node=16
#SBATCH --output=SigmoidSNPsCV-%A_%a.o
#SBATCH -J SigmoidSNPsCV
#SBATCH --mail-type=ALL
source $HOME/virtualenvs/keras_new/bin/activate
export PYTHONDONTWRITEBYTECODE=1
module reset
... |
dd36bd11aaa36fff15bd843a777b14076669a56c191940e9e1899d3587a1feac | Shell | 484 | 18 | #!/bin/bash
#SBATCH --cpus-per-task 1
#SBATCH --mem-per-cpu=32G
#SBATCH --time 24:00:00
#SBATCH --partition=gpu
#SBATCH --gres=gpu:v100x:1
"""
This takes all of the transferred Cellranger output files and runs cellbender
"""
# Load modules
module load cellbender
module load CUDA/12.1
export TMPDIR=$2
echo $TMPDIR
# I... |
1cbcf32cc6e16f6cb8066ac46bd3eb65c1f923c50d64ae473e95f700a1301fa9 | Shell | 492 | 21 | #!/bin/sh
seed_max=10
#for seed in `seq ${seed_max}`;
#do
# echo "seed is ${seed}:"
# python train.py
# kill Main_Thread
#done
#seed_max=10 # 设置最大的种子值，这里假设为10
#for./run, seed in $(seq 1 $seed_max); do
# echo "seed is $seed:"
# python train.py --seed $seed # 将当前种子值作为参数传递给 train.py
#done
python train.p... |
b711de8ac8e46c9a8bcdebbd497322fe5bba6f107438239dbeeaeb1e8bac6c37 | Shell | 492 | 12 | #!/bin/bash
#SBATCH --job-name=SC
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=120G
#SBATCH --cpus-per-task=28
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss02/charpier/analyses/vn_pet/slurm_output/output-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss02/charpier/analyses/vn_pet/slur... |
74c7e0f920cf70cc45a8da5e1b564680d06afa1603ea4b8a57b56578e857655d | Shell | 504 | 12 | #!/bin/bash
#SBATCH --job-name=SC
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=60G
#SBATCH --cpus-per-task=14
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss01/charpier/analyses/lgi1/Git-Paul/slurm-output/output-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/lgi1/... |
ff6b625af63932975923c7bcf7dae5b9a8e6be1311748a6a7ff3e7acbd33b157 | Shell | 504 | 13 | #!/usr/bin/env bash
# Run this command from the PyTorch directory after cloning the source code using the “Get the PyTorch Source“ section below
pip install -r requirements.txt
git submodule sync
git submodule update --init --recursive
# This takes some time
make setup-lint
# Add CMAKE_PREFIX_PATH to bashrc
echo 'exp... |
e874a8e8331e071dcfef66c9bd659c90a4c909c3f9a7541c7ebe54cf02c8ba3e | Shell | 505 | 26 | #!/bin/bash
#SBATCH --job-name=wod
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=32G
#SBATCH --cpus-per-task=2
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss01/charpier/analyses/wod/slurm-output/output-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/wod/slu... |
316d009500ece44acea7127f4806cdd5d81cb8fdfacdd5175a38e10c41dc3fb6 | Shell | 508 | 15 | #!/bin/bash
#SBATCH --job-name=pet
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=32G
#SBATCH --cpus-per-task=2
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss02/charpier/analyses/vn_pet/slurm_output/output-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss02/charpier/analyses/vn_pet/slurm... |
0a89dd4e292e64c8589b9ffcab8a7cd9ac4d5960108bf4611b7f69ce7ae0be72 | Shell | 510 | 26 | #!/bin/bash
#SBATCH --job-name=concat_lfp
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=12G
#SBATCH --cpus-per-task=2
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss01/charpier/analyses/wod/slurm-output/-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss01/charpier/analyses/wod/sl... |
48abbd8bb4333b2334583aadac7c4e9a3fcc602523dcda04620e2f216b5801f5 | Shell | 510 | 13 | for isimu in '_d_1_r_4_noise_0.1' '_d_1_r_4_noise_0.2' '_d_1_r_4_noise_0.3'
do
Rscript simu_nb_data.R ${isimu}
cp simu_nb_data.R data/simu_100${isimu}/
cp simu_nb_fit.R data/simu_100${isimu}/
for seed in $(seq 0 49);
do
Rscript --no-save --no-restore --verbose simu_nb_fit.R ${isimu} ${seed} ... |
52603cee37730d2524f528cea183e351362479a0516b3f4adf0ed1bc15af38fb | Shell | 511 | 23 | #! /bin/sh
CURDIR=`pwd`
UPSTREAM_BRANCH="${UPSTREAM_BRANCH:-master}"
cd ~/macports/dports
git pull origin "$UPSTREAM_BRANCH"
cd $CURDIR
declare -a arr=("python/py-stfio" "science/stimfit")
for TARGET in "${arr[@]}"
do
mkdir -p tmp/a
mkdir -p tmp/b
cp ~/macports/dports/$TARGET/Portfile ./tmp/a/
gsed -... |
7923e7d8f80a8d52632cf8f9ea50331a0c49551c83def5dac24c7087fb63711a | Shell | 512 | 12 | #!/bin/bash
#PBS -l nodes=1:ppn=4
#PBS -l walltime=11:59:59
#PBS -l mem=32gb
#PBS -l vmem=32gb
#PBS -m a
echo ${subid}
/usr/usc/matlab/default/bin/matlab -nodisplay -nosplash -r "addpath(genpath('/home/rcf-proj2/aaj/git_sandbox/bfp/src')); bfp /home/rcf-proj2/aaj/git_sandbox/bfp/supp_data/hpcconfig.ini /home/rcf-proj2... |
1eea61e0de9510f9c92ea542ee482b31b4dee505234fa99550efe7ac4fa6aa1d | Shell | 513 | 17 | #!/bin/bash
#SBATCH -J MACEH
#SBATCH --time=02:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=12
#SBATCH --mem-per-cpu=3850
#SBATCH --cpus-per-task=1
#SBATCH --output=%j.out
#SBATCH --partition=compute
#SBATCH --account=su007-rjm
module purge
module load GCC/13.2.0 CUDA/11.8.0
python_path="/home/c/chenqian3/.conda... |
01babba530833d86195c687c1e367fdda6a361ad16d403fc2c33b0abf97ab852 | Shell | 516 | 12 | #!/bin/bash
#SBATCH --job-name=SC
#SBATCH --partition=normal,bigmem
#SBATCH --time=99:99:99
#SBATCH --mem=120G
#SBATCH --cpus-per-task=28
#SBATCH --chdir=.
#SBATCH --output=/network/lustre/iss02/charpier/analyses/vn_preictal/scripts/slurm_output/output-%j_%a-%x.txt
#SBATCH --error=/network/lustre/iss02/charpier/analyse... |
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