sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
2a60b807942edd0a52464e1ff2e166439bb304680eb24569d90601debca44b5c | Shell | 309 | 21 | conda activate Compass
cat cells | while read filename
do
DIR="${filename%.*}"
meta=meta-${DIR}.csv
compass --data $filename \
--num-processes 32 \
--species homo_sapiens \
--calc-metabolites \
--num-threads 32 \
--output-dir $DIR \
--temp-dir $DIR \
--lambda 0.25 \
--microcluster-size 50
done
|
50c13b09428a5bd58347fb13f56459580418e0d2e4f10eb4a00d9d9dbf82af94 | Shell | 309 | 17 | #!/bin/bash
#PBS -l walltime=12:00:00
#PBS -N imageSimilarity
#PBS -q normal
#PBS -m ae
#PBS -M matt.mattoni@temple.edu
#PBS -l nodes=1:ppn=28
projectdir=/gpfs/scratch/tug87422/smithlab-shared/night-owls
scriptdir=$projectdir/code
cd $PBS_O_WORKDIR
umask 0000
module load python
python imageSimilarity.py
|
7cc5e00205d1ed04c341e61bcae3f735ec1b8505b1c256e1dd2a3a1dd92befb7 | Shell | 309 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KMCaLs_outw
#SBATCH --output=data/output/dI_KMCaLs_outw-%j.txt
#SBATCH --error=data/output/dI_KMCaLs_outw--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_outw_km.jl $i_batch_KM |
4d15347e12873237169df552ac29d1ba8d8c3bad41094739d3b87742ab235b26 | Shell | 310 | 18 | #!/usr/bin/env bash
LEVEL=$1
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )";
cd ${DIR};
npm version $LEVEL;
npm run-script doc;
# Gallery not working atm
# npm run-script gallery;
./deploy.sh $LEVEL;
cd ${DIR}/..;
if [ "$LEVEL" = "prerelease" ]; then
npm publish --tag next;
else
npm publish;
fi
|
78799c89d1de02af5693e99b76e838cb083289b317cfd60646675bd4a9b809f3 | Shell | 310 | 13 | #!/bin/bash -e
ver=$(fgrep '#define VERSION ' gffcompare.cpp)
ver=${ver#*\"}
ver=${ver%%\"*}
if [[ "$1" == "delete" || "$1" == "del" ]]; then
echo "Deleting tag v$ver .."
git tag -d v$ver
git push origin :refs/tags/v$ver
exit
fi
git checkout master
git tag -a "v$ver" -m "release $ver"
git push --tags
|
a5e23fc56acb7df89bc653fcbf8f444a9588ac84c49845d465c18a673b6de440 | Shell | 310 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KirCaLs_inw
#SBATCH --output=data/output/dI_KirCaLs_inw-%j.txt
#SBATCH --error=data/output/dI_KirCaLs_inw--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_inw_kir.jl $i_batch_Kir |
b10e2e82a3dc994b777ba4c426598e4d0db92a764567ad6a12e5bea4b4df84c7 | Shell | 310 | 17 | #!/bin/bash
echo "Running GangSTR test:"
ref=path/to/hg38/refgenome.fa
for bam in alignment/*.bam
do
name=$(basename $bam .sorted.bam)
echo Sample: $name
../src/GangSTR \
--bam $bam \
--ref $ref \
--regions HTT.bed \
--out results/$name \
--coverage 50 \
--output-readinfo \
--verbose
done
|
6126247a90f8c1f18c318f79a51926652e7b2fe3011734dbf3d3b138b486f5f1 | Shell | 311 | 11 | # please set the IP of the SpiNNaker2 here
export S2_IP=<your.s2.ip.here>
# set to default, change only if necessary
export S2_STM=/dev/ttyACM0
cd ../s2_lab_sw/host/units/s2_top/tc_s2app_qsar_19bill
# run inference, get log files and shut voltage logs
time ./measure_all.sh 0 510 5 1 0 1 $S2_IP $S2_STM
cd -
|
de6b4e9475b7b4e60a75129e879d800ead8f830be6a5f5ff873d33acd7388c6c | Shell | 311 | 10 | export PYTHONPATH=./:$PYTHONPATH
model_dir=~/models/feature_scatter_cifar10/
CUDA_VISIBLE_DEVICES=1 python fs_eval.py \
--model_dir=$model_dir \
--init_model_pass=latest \
--attack=True \
--attack_method_list=natural-fgsm-pgd-cw \
--dataset=cifar10 \
--batch_size_test=80 \
--resume
|
5774c3d1d799100a6c319505bdc4963fcc8e22fbbbc8b249cc5bb5a61f2c6aba | Shell | 312 | 10 | #!/bin/bash
cd /data/mat/zhi/BigNeuron/first2000/images/
for filename in `ls -d *`
do
mkdir "/data/mat/zhi/BigNeuron/first2000/reconstructions2/"$filename
mkdir "/data/mat/zhi/BigNeuron/first2000/images2/"$filename
mv $filename"/"$filename "/data/mat/zhi/BigNeuron/first2000/images2/"$filename"/"
done
|
5aceebc195575ff518d3758a3ddabdee85db120199cb3a45c01417ce3ffc920a | Shell | 312 | 16 | if grep -q xlc depcomp ; then
#echo "depcomp already extended to handle xlc. No change to file."
true;
else
sed '/^aix)/,/;;/ {
H
s/\.u/.d/
s/^aix)/xlc) #following fragment is just like AIX but the extension is .d instead of .u/
}
/^icc)/ {
x
G
}
' depcomp > temp
mv temp depcomp
fi
|
82d99edef919297e55017d6285e6234f44b10e1c877b1723e5455dcaeb680b88 | Shell | 312 | 10 | #!/usr/bin/env bash
. utils.sh
for exec_cores in 1 2 4; do
for total_cores in 4 8 16 32 64; do
num_exec=$((total_cores / exec_cores))
time_gatk "CountReadsSpark -I hdfs:///user/$USER/q4_spark_eval/WGS-G94982-NA12878.bam -L Broad.human.exome.b37.interval_list" $num_exec $exec_cores 1g 1g
done
done
|
97b06de0b3cbbb212589eb735ec05979fe23cf31473a854942ef8dc890569bce | Shell | 312 | 14 | #!/bin/bash
# This script deletes a Google Dataproc cluster used for running the GATK-SV pipeline.
set -eu
if [ "$#" -ne 2 ]; then
echo "Usage: delete_cluster.sh <CLUSTER_NAME> <PROJECT>"
exit 1
fi
CLUSTER_NAME=$1
PROJECT=$2
gcloud dataproc clusters delete --project $PROJECT "$CLUSTER_NAME" --async
|
bd238eaf29ddb0ddd0af62ee57c6f123db1169235fd3d3ab01313ad574687366 | Shell | 312 | 9 | #!/bin/bash
#SBATCH --account=rrg-pbellec
#SBATCH --time=12:00:00
#SBATCH --job-name=shinobi_regs_corrs
#SBATCH --mem=32G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /project/rrg-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/visualization/regressors_correlations.py
|
31c4c292cf5cd46005e651502d0bdec4cd44b1e4a4ce698f95c0231f1b3c07f4 | Shell | 313 | 15 | #!/bin/bash
# define project directory and working directory
pd=/your/project/directory/
wd=$pd/data/neural_differentiation_dataset/FASTQ
cutadapt \
-A A{41} \
-o $wd/all_i1r1_trimmed.fq.gz \
-p $wd/all_r2_trimmed.fq.gz \
$wd/all_i1r1.fq.gz \
$wd/all_r2.fq.gz \
--discard-casava \
--minimum-length 24:40 \
-j 20 |
da03e997b301a9d7311000241598eaa95a6d1b5bf7b27c1d9c16388e58b3264f | Shell | 313 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=24:00:00
#SBATCH --job-name=shi_seslevel
#SBATCH --mem=32G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/visualization/viz_session-level.py
|
eda4745becd90ccfebd71e7bef41afbad1d5f001d3e73eb4a8f41a07b2edc141 | Shell | 313 | 11 | cd c:/nrn
rm -f nrnfiles.zip
zip -r nrnfiles.zip lib/*.mak lib/hoc lib/nrn.def \
lib/prologue.id iv lib/*.sh lib/psfilt.sed \
lib/*.cm* lib/cleanup lib/nrnunits.lib \
bin/*.ico examples demo \
src/nrnoc/*.mod lib/helpdict \
src/oc/*.h src/nrnoc/*.h src/scopmath/*.h \
classes/*.jar
zip -d nrnfiles.zip \*.o \*.c
|
8fb5afb7ac63ebe3ea00e9c0ea83d97513ba6558bdc4dd70d00dda9f0d3d6cc3 | Shell | 314 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=12:00:00
#SBATCH --job-name=shinobi_corrmat
#SBATCH --mem=48G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=32
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/correlations/session_corrmat.py
|
a1ccc434c3df4ebe04ae354e8f1a399646b9978d316b8301410bd99a1a434d91 | Shell | 314 | 19 | #!/bin/bash
set -e
NO_CACHE=${NO_CACHE:-false}
# add --no-cache if NO_CACHE is false
if [ "$NO_CACHE" = true ] ; then
echo "Building without cache..."
CACHE_ARG="--no-cache"
else
CACHE_ARG=""
fi
docker buildx build \
$CACHE_ARG \
-t pisces2:"${1:-latest}" \
-f ./Dockerfile \
"$PWD" |
b59e4c0dfaa058e1c10aacec6472930ed904cdf4a4650a9d1bcb26103b15fefe | Shell | 314 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KirCaLs_outw
#SBATCH --output=data/output/dI_KirCaLs_outw-%j.txt
#SBATCH --error=data/output/dI_KirCaLs_outw--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_outw_kir.jl $i_batch_Kir |
0e10aeda7879e1cf3cdd4290d22ce90b94ce9609f466bc6f5053edbdc4458f04 | Shell | 315 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=12:00:00
#SBATCH --job-name=shi_subjlevel
#SBATCH --mem=12G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=16
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/visualization/viz_subject-level.py
|
2e774448c7b4507508c8005623295599ab1c2ad123a3cd52ffe66da43414081b | Shell | 315 | 1 | Rscript createSparseGRM.R --bimFile=input/plinkforGRM_1000samples_10kMarkers.bim --bedFile=input/plinkforGRM_1000samples_10kMarkers.bed --famFile=input/plinkforGRM_1000samples_10kMarkers.fam --nThreads=72 --outputPrefix=./test_sparseGRM --numRandomMarkerforSparseKin=5000 --relatednessCutoff=0.05 &> createGRM.log
|
3b7ad86bdc6fdec9c9ec1fca0b7df575029debc9bd2aba35eb1803bb466e9e5c | Shell | 315 | 19 | #!/bin/bash
# Run CellBender
module load python/3.8.x-anaconda
module load gcc/12.2.0
source activate cellbender
cd /home2/gkonop/project/03_MATRIX_FROM_CELLBENDER/HUMAN_OUR/CELLBENDER_RUN
for dir in `ls -d $PWD/*`
do
cellbender remove-background --input $dir --output $dir"/CellBender_out.h5" --cuda
done
|
768c8a9cb60c0d7d3656dc31348434ce961dd57945b6e2a00b1ad9c6f55047ec | Shell | 315 | 5 | #!/bin/bash
echo "Running the script to extract embeddings..."
. ./.venv/bin/activate
# Run the Python script extract_embd.py extracting embeddings
python3 extract_embd.py --path_data "../../test_data/fusionai_test_sim.txt" --output_folder "./output" --output_name "bert_test_mean" --batch_size 2 --embd_type "mean" |
42c7a9b5aec25b38f5a82a4b3240109b480b61e57437e94799cfc36f7335ce02 | Shell | 317 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=24:00:00
#SBATCH --job-name=shi_runlevel
#SBATCH --mem=96G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/glm/compute_run_level.py -s $1 -ses $2
|
de28b697da07d28ed913e8a1045dad9d052211aa606025cefed2dd37852df1bc | Shell | 317 | 11 | conda create -n NeNe -c conda-forge python=3.8 -y
conda activate NeNe
pip install biopython==1.81
pip install joblib==1.1.0
pip install numpy==1.22.3
pip install scikit_learn==1.1.0
pip install pandas==1.5.3
pip install tqdm==4.64.1
pip install tensorflow==2.8.0
pip install keras==2.8.0
pip install protobuf==3.20.1
|
7c0eda3038ede6de8982207aef60688c23bf7b89ffc26f956c527d64142f7a30 | Shell | 318 | 7 | #!/bin/bash
cd /media/Synology3/Robert/counting-3
PATH=/usr/local/bin:$PATH
source /home/robert/anaconda3/bin/activate torch-py37
python scripts/test_counting_page.py http://10.122.168.56:5000\
static/test_data/egg_ct_official_2021_10_30_img_0002.csv\
/media/Synology3/Rebecca/2021_10_30/IMG_0002.JPG rca30@duke.edu |
e992657f257cf3f7df4f9ca0491e7497ad6d8451e739ac25d888ea0451565440 | Shell | 319 | 22 | #!/bin/sh
N="`$1/bin/cygpath -u $1`"
export N
export PYTHONHOME=$N
shift
PATH=$N/bin:/usr/bin:$PATH
export PATH
SH_PATH=$N/bin/sh
export SH_PATH
ARG="`cygpath -u $1`"
DD=`dirname "$ARG"`
FF=`basename "$ARG"`
cd $DD
nrniv $FF
a=$?
if test $a -ne 0 ; then
echo exit status $a
echo Hit return key to exit.
read a
fi
|
703946c8152cb7a611c4e77bbc4b78d1dd3db83263467ae97d398d8552a66366 | Shell | 321 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=12:00:00
#SBATCH --job-name=shi_runlevel
#SBATCH --mem=16G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/visualization/viz_run-level.py -s $1 -c $2... |
4fd2cf000961641b1026703b4a4a602565978320724c20badb1bc70453027dbf | Shell | 322 | 19 | #!/bin/bash
set -e
NO_CACHE=${NO_CACHE:-false}
# add --no-cache if NO_CACHE is false
if [ "$NO_CACHE" = true ] ; then
echo "Building without cache..."
CACHE_ARG="--no-cache"
else
CACHE_ARG=""
fi
docker buildx build \
$CACHE_ARG \
-t pisces2-jax:"${1:-latest}" \
-f ./Dockerfile.jax \
"$PW... |
a51427e7b6bb7f849ab92997622e1bf209c9e8300594db32baa880a1da14797a | Shell | 323 | 5 | # command 1
humann_merge_abundance_tables --input-genes demo_genefamilies.tsv --input-pathways demo_pathabundance.tsv --output merge_output.tsv
# command 2
humann_merge_abundance_tables --input-genes demo_genefamilies.tsv --input-pathways demo_pathabundance.tsv --output merge_output_remove_taxonomy.tsv --remove-taxono... |
00b9448c9fdcaf42452a79cfdbd85d14626623ae1f6be594e267792cad16c3ea | Shell | 324 | 15 | #!/bin/bash
# Run CellBender
module load python/3.8.x-anaconda
module load gcc/12.2.0
source activate cellbender
cd /home2/gkonop/project/02_MATRIX_FOR_CELLBENDER/KRIENEN_MOUSE
for dir in `ls -d $PWD/SRR* | grep -v SRR11921005`
do
cellbender remove-background --input $dir --output $dir"/CellBender_out.h5" --cuda
d... |
04ef9c67bb5cfe75a252de4089cb282b3c62e9fc02307d9d68f46d278d481e38 | Shell | 324 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KMCaLs_m2
#SBATCH --output=data/output/dI_KMCaLs_m2-%j.txt
#SBATCH --error=data/output/dI_KMCaLs_m2--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_f_repl_by_s_km.jl $i_pCaLs $i_batc... |
43b034c68c033dde66ead052ec709bb151cfbd6b3edf8f377a154fc9fb9c166d | Shell | 325 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KirCaLs_m2
#SBATCH --output=data/output/dI_KirCaLs_m2-%j.txt
#SBATCH --error=data/output/dI_KirCaLs_m2--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_f_repl_by_s.jl $i_pCaLs $i_batc... |
703cdf7af388123d24e60257c560b2fbf9b038bf6873fd70a7560a75fd056408 | Shell | 325 | 12 | #!/bin/bash
[ $# -lt 1 ] && { echo 'Usage :
$1 = folder path
[Optional] $2 = roi1 suffix
[Optional] $3 = roi2 suffix';
exit 1; }
./mrstats_median.sh $1 median_ad.csv ad $2 $3
./mrstats_median.sh $1 median_rd.csv rd $2 $3
./mrstats_median.sh $1 median_fa.csv fa $2 $3
./mrstats_median.sh $1 median_adc.csv adc $... |
ec30d3dcaefad7ce7f0be989543f319ff5906ef0df20aa848f88056a7fd7be3b | Shell | 326 | 10 | #!/bin/bash
# Usage: bash run_example.sh {file_to_run.py} {num_gpus}
# where file_to_run = example to run. Default = 'main.py'
# num_gpus = num local gpus to use. Default = 16
# samples to run include:
# main.py
echo "Launching ${1:-main.py} with ${2:-16} gpus"
torchrun --standalone --nproc_per_node=${2:-16} ${1:-mai... |
edb9ed28a9643c9868de4ebbb1218fa3687c1f5d449e7e6867687938112f3e8e | Shell | 326 | 10 | #! /bin/bash
step=1
if [[ $step -eq 1 ]]
then
script_dir=/home/huyang/Projects/HuYang/HY_20250708/SCRIPTS/T1/MIND
sublist=/home/huyang/Projects/HuYang/HY_20250708/PROCDATA/LIST/t1_sublist.txt
parallel --jobs 8 --joblog ${script_dir}/zlog_parallel.txt python ${script_dir}/calc_MIND.py {1} ::: $(cat $sublist)... |
263ff2313437f7374eba072f17492b540720ef00cc273337dc06e8ad741683b6 | Shell | 327 | 15 | #!/bin/bash
# Filters electrode data
# Created on 20200804 by Max B Wang
Data_Dir=/media/mwang/easystore/Processed_Data/
# EP1165, EP1166, EP1188
subjID="EP1174"
numEDFs=`ls "${Data_Dir}/${subjID}/ElectrodesRaw/" | wc -l`
for (( i=0; i<${numEDFs}; i++)); do
python3 FilterElectrodes.py ${Data_Dir} ${subjID} ${i}
... |
71c1da4c837682f81e42cf9184e324bf5c87dc0101f110958bcbbe4a630fe173 | Shell | 328 | 12 | #!/bin/bash
subc=$1
outdir="bam"
merged_bam="Subtype_$subc.bam"
samtools merge $outdir/$merged_bam $outdir/${subc}/*filtered.bam
samtools sort -o "$outdir/${merged_bam%.bam}_sorted.bam" $outdir/$merged_bam
samtools index "$outdir/${merged_bam%.bam}_sorted.bam"
echo "Final merged BAM: $outdir/${merged_bam%.bam}_sort... |
b8540a61097bfb2fe64b577f7469350a9d7a000d5debb4b6dc356657b7ed6d9a | Shell | 329 | 17 | #!/bin/bash
# define project directory and working directory
pd=/your/project/directory/
mkdir -p $pd/data/validations/nanopore_FASTQ
cd $pd/data/validations/nanopore_FASTQ
# download files
HOST=ftp.ebi.ac.uk
USER=anonymous
DIR=biostudies/nfs/E-MTAB-/XXX/E-MTAB-XXXXX/Files
lftp -e "
cd $DIR
mget *.fq.gz
bye
" -u $US... |
1f42b771edcbc58a6dfb8df4ffaf8e1ac182843c333cad3c3c1425a168432051 | Shell | 330 | 11 | #!/usr/bin/env bash
# Centralized config to define the minimum and maximum tested Kubernetes versions.
# This is used in the CI workflow for e2e tests, the devcontainer, and to generate docs.
declare -A K8S_VERSIONS=(
[min]=v1.34.9
[max]=v1.36.2
)
# renovate: datasource=github-releases depName=k3d-io/k3d
K3D_VERS... |
2fd43dc9cbe243032a01a42d58043019aff228ad80cabbaa63a53abe7c2f174a | Shell | 330 | 8 |
# warp F99 coordinates to MNI space
echo "warping F99 coordinates to MNI"
MNIref=$MRCATDIR/data/macaque/MNI/MNI
F99ref=$MRCATDIR/data/macaque/F99/F99
warp=$MRCATDIR/data/macaque/transform/MNI_to_F99_warp # yes, this is the inverse warp
# coordinates
echo 24.8 -12.7 8.2 | std2imgcoord -std $F99ref -img $MNIref -warp $w... |
5a64a20dc179c21b9af72522ad39f0e31af5997aa02a76c1799468649b75a6f8 | Shell | 331 | 16 | #!/bin/bash
# Written by Jianzhong Chen and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
file=$1
num=$2
nfinished=`cat $file | wc -l`
while [ $nfinished -lt ${num} ]
do
nfinished=`cat $file | wc -l`
njob=`qstat | grep $(whoami) | wc -l`
if [ "$njob" -eq 0 ];then
break
fi
sle... |
b9f34910dc0c12d16bddd56b24329d0b62cbfe531209daf506ad78e76d6cb516 | Shell | 331 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KMCaLs_no_ghk
#SBATCH --output=data/output/dI_KMCaLs_no_ghk-%j.txt
#SBATCH --error=data/output/dI_KMCaLs_no_ghk--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_km_no_ghk.jl $i_pCaLs ... |
0e373bbc3d55a70905425961eef0c49b6615ec4e87cb4e4f4c2856067a3eab5b | Shell | 332 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KirCaLs_no_ghk
#SBATCH --output=data/output/dI_KirCaLs_no_ghk-%j.txt
#SBATCH --error=data/output/dI_KirCaLs_no_ghk--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_no_ghk.jl $i_pCaLs ... |
75753eb2340363a1154be3fd92bde7baab965be89e8e2d0825ed7bf4bf684e73 | Shell | 333 | 8 | #!/bin/bash
nohup python -u data/scripts/sample_qc.py \
--mt_input_path 'file:///home/ubuntu/data/hail_data/mts/chd_ukbb_split_v2_09092020.mt' \
--ht_output_path 'hdfs://spark-master:9820/dir/chd_ukbb_split_v2_09092020_raw' \
--write_to_file \
> nohup... |
8467f5838459293c7399f0dfc4df43dda87948db84c4fb0d1c1f9e6bbcf14e24 | Shell | 334 | 14 | #!/bin/bash
#SBATCH --job-name=pro_DTL
#SBATCH --error=%x-%j.error
#SBATCH --out=%x-%j.out
#SBATCH --mem=80G
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --time=1-0:0:0
#SBATCH --partition=theia,mtst,bigmem
#conda activate polyfun
python 5.Rank_Evaluate_Percentage.py $1 DTL prostate 2024 #$1 ... |
8ae182f627710debfe92957bdb12219013555bd59ce5ee4db455e60ef3d9cde1 | Shell | 334 | 5 | for lane in `cat /data/share/htp/perturb-seq/TF94_combined/download_from_tuebingen/ids.txt`
do
sbatch -J hg38_${lane}_cr --output=hg38_${lane}_%j.out --exclude=gorilla4 run_cellranger_array.sh hg38 ${lane}
sbatch -J macFas6_${lane}_cr --output=macFas6_${lane}_%j.out --exclude=gorilla4 run_cellranger_array.sh macFas... |
cf2b07fe4e546b9075bd7de192591459f9f67312830b7a26f1d58a017d7fdcd3 | Shell | 335 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=12:00:00
#SBATCH --job-name=shi_sesslevel
#SBATCH --mem=128G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/glm/compute_session_level.py --subject $... |
e07e12f5ddb5f919f755286132ada7cfe236257c47b5deac6b77c12992377596 | Shell | 335 | 11 | # export PYTHONPATH=./:$PYTHONPATH
python adversarial_defense/feature_scatter/fs_main.py --adv_mode 'feature_scatter' --lr 0.1 \
--init_model_pass latest \
--max_epoch 200 \
--save_epochs 100 \
--decay_epoch1 60 \
--decay_epoch2 90 \
--batch_size_train 60 \
--dataset CIFAR-100 \
--arch... |
fc3c0fc01787a9e1665026d77ab20fe00603987db39bcd3eba844c32829b7f66 | Shell | 335 | 10 | #!/bin/sh
set -e ${DEBUG:+-x}
if [ -n "${POSTGRE_HOST:-}" ] || [ -n "${MYSQL_HOST:-}" ] && [ "${SKIP_DB_MIGRATIONS:-}" != "true" ]; then
echo >&3 "=> Do database migrations..."
python3 /label-studio/label_studio/manage.py locked_migrate >&3
echo >&3 "=> Migrations completed."
else
echo >&3 "=> Skipping run db ... |
40869d1f64d35c42f5cf6bf749a227bac316d9f2139dd61bbc55ea450c4fdfeb | Shell | 336 | 10 | #!/bin/bash
# point to working directory
cd /Path/to/personal/working/directory
apptainer exec --env PATH=/work/CaPTk/bin/install/appdir/usr/bin:$PATH \
/Path/to/Wrappers/captk.sif \
/work/CaPTk/bin/install/appdir/usr/bin/captk "$@"
# To use CaPTk tools, use:
# /Path/to/Wrappers/captk_wrapper.sh <CaPTkComman... |
93c5d859d2f1ff803673fa6b2b5cbb7f49c0af7d362532f46d21616dc8fb9ed2 | Shell | 336 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=01:00:00
#SBATCH --job-name=shi_subjlevel
#SBATCH --mem=32G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=8
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/glm/compute_subject_level.py --subject $1... |
e93aed364520f280c9a92bb489bb7a1e2db0da190bf9f4e47261d176fca555ac | Shell | 336 | 13 | #!/usr/bin/env bash
set -ex
image_name="mlflow-r-dev"
if [ "${USE_R_DEVEL:-false}" = "true" ]
then
docker_file="Dockerfile.r-devel"
else
docker_file="Dockerfile.dev"
fi
docker build -f $docker_file -t $image_name .
docker run --rm -v $(pwd):/mlflow/mlflow/R/mlflow $image_name Rscript -e 'source(".build-package.R"... |
36154782bb98c6aa478872f66c3dbcd862c6bbb85d9fbc09ca5f8ecfb17edd62 | Shell | 338 | 10 | /data/home/Longh/.virtualenvs/ai4fuel/bin/python train_moleculeNet.py \
--csv ../data/molnet_desc/esol_desc.csv \
--dataset Esol \
--mapping ../descriptors_group/descriptorsMap/descriptorsMapping.json \
--exp_k 10 \
--seed 42 \
--device cuda:0 \
--trials 50 \
--epochs_embed 1000 \
--... |
3c4bc754ad157e00c35b29af54b4a5cba6d6e1e712be8c67fd6aa8aee1c4dcbb | Shell | 338 | 8 | #!/bin/bash
nohup python -u data/scripts/variant_qc.py \
--mt_input_path "file:///home/ubuntu/data/hail_data/mts/chd_ukbb_split_09092020.mt" \
--ht_output_path "file:///home/ubuntu/data/hail_data/hts/chd_ukbb_split_09092020_raw" \
--write_to_file \
> ... |
49916437f299dec77652c19d5502d3b9f5789880d2eecefe257e5f1d93364cd8 | Shell | 338 | 18 | #!/bin/bash
#SBATCH --time=01-00:00:00
#SBATCH --mem=30G
#SBATCH --cpus-per-task=1
module load gatk
# input the gvcf list
gvcfs=($(cat $1))
# input the reference genome
ref=$2
# input the output gvcf
out_gvcf=$3
gatk CombineGVCFs \
-R ${ref} \
$(for gvcf in ${gvcfs[@]}; do echo "--variant ${gvcf}"; done) \
... |
6db40cf03e58c76812382ef13037f00473ff9f06c79e0b81dd66a6a964faf57c | Shell | 338 | 8 | #!/bin/bash
# first arg is fs install directory, second arg is subject directory, third arg is subject # ID, fourth is the filename of the first dicom file
export FREESURFER_HOME=$1
source $FREESURFER_HOME/SetUpFreeSurfer.sh
export FS_LOAD_DWI=0
recon-all -sd "$2" -s "$3" -i "$4"
chmod -R +rwx "$2"
recon-all -cw256 -sd... |
c0e1d65149b8a960e803906c762ccf1d2e3e7275114c817d9bd9986bb1e13c26 | Shell | 339 | 10 | #!/bin/bash
# Extract the dicom files to the current folder
cd .../Raw_data_to_BIDS/fMRIprep_BUG/raw_data/UM0083/
for file in *.tgz; do
base=$(basename "$file" .tgz)
mkdir -p .../Raw_data_to_BIDS/fMRIprep_BUG/extracted_data/UM0083/$base
tar -xvzf "$file" -C .../Raw_data_to_BIDS/fMRIprep_BUG/extracted_data/... |
c47c92531eb415e83e1087e5b8e251685d35eb9976542bb23119c3debc1b2a35 | Shell | 339 | 10 | #!/usr/bin/env bash
# Copy genome data to HDFS on a GCS cluster.
${GATK_HOME:-../..}/gatk ParallelCopyGCSDirectoryIntoHDFSSpark \
--input-gcs-path gs://broad-spark-eval-test-data/genome/ \
--output-hdfs-directory hdfs://${GCS_CLUSTER}-m:8020/user/$USER/q4_spark_eval \
-- \
--spark-runner GCS \
--c... |
ca2657bf8e5093bcd02896e501afaaa97e148ae5fca45875543b88bcaa7ff243 | Shell | 339 | 18 | #!/usr/bin/env bash
which npm
which node
which yarn
if [[ ! -d "AlgoliaScripts" ]]; then
echo "The AlgoliaScripts directory isn't in this branch yet"
exit 1
fi
cd "AlgoliaScripts"
if [[ ! -d "node_modules" ]]; then
npm install || exit 1
fi
node ./upload_s3_expectation_to_algolia.js
node ./upload_s3_pack... |
36ceb9338d63ea4dca8d769dcbae99f414eef5819ac11d1bd9f2efab26515d40 | Shell | 340 | 8 | #!/bin/bash
# Delete any existing dist or egg dirs and run from the root of the repository
python -m build
read -p "Package built, check dist/*, press [ENTER] to continue"
python -m twine upload --repository testpypi dist/*
read -p "Uploaded to PyPi test, press [ENTER] to continue"
python -m twine upload dist/*
echo "... |
9f5b6b93b664356814582a33c47f2fd82eeccb081a8b25d8233712968ef353b9 | Shell | 340 | 10 | #!/usr/bin/env bash
# Copy exome data to HDFS on a GCS cluster.
${GATK_HOME:-../..}/gatk ParallelCopyGCSDirectoryIntoHDFSSpark \
--input-gcs-path gs://broad-spark-eval-test-data/exome/ \
--output-hdfs-directory hdfs://${GCS_CLUSTER}-m:8020/user/$USER/exome_spark_eval \
-- \
--spark-runner GCS \
--... |
eaea76d32bb734a66a8de066933e612eebf0d5997bf23e5e62e61e30fb841043 | Shell | 340 | 10 | #!/usr/bin/env bash
# Copy small data to HDFS on a GCS cluster.
${GATK_HOME:-../..}/gatk ParallelCopyGCSDirectoryIntoHDFSSpark \
--input-gcs-path gs://broad-spark-eval-test-data/small/ \
--output-hdfs-directory hdfs://${GCS_CLUSTER}-m:8020/user/$USER/small_spark_eval \
-- \
--spark-runner GCS \
--... |
77e4fb275d0349d5d0b83cc55dcdf9ea6197fdd39f644a3a008cf58668fe8cbe | Shell | 341 | 11 | #!/bin/bash
nohup python -m sample_qc.ancestry_inference \
--exome_cohort 'chd_ukbb' \
--skip_filter_step \
--n_pcs 20 \
--overwrite \
--write_to_file \
--default_reference 'GRCh38' \
> pca_ancestry_i... |
56258e8ffc751ca43f93848599a6525f4c22b27b30232a0c3aabe57f54a25a1d | Shell | 342 | 15 | #!/usr/bin/env bash
git clone https://github.com/bcamath-ds/compass
cd compass
sudo apt-get install libtool m4
sudo apt-get install libgsl0-dev libatlas-base-dev libbfd-dev libiberty-dev
sudo apt-get install libssl-dev
sudo apt-get install autoconf automake
autoheader
libtoolize
aclocal
automake --add-missing
autoconf
... |
823b5e5bb4808a8a893cbbe4a33ea39a99a6d83dfaed643127d19db3d6e9c64e | Shell | 342 | 3 | #!/bin/bash
cat gencode.v25.annotation.gtf |awk '$0 !~ /gene_type "rRNA"/'|awk '$0 !~ /transcript_type "rRNA"/'|awk '$0 !~ /gene_type "Mt_rRNA"/'|awk '$0 !~ /transcript_type "Mt_rRNA"/' | awk '$0 !~ /gene_type "Mt_tRNA"/' | awk '$0 !~ /gene_type "tRNA"/' | awk '$0 !~ /transcript_type "tRNA"/' > gencode.v25.annotation.w... |
46666e7a8e0dc75df9f4e7e1d02a3b5ce0d2b2c2ec6db6613947ad87c7662be7 | Shell | 343 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KMCaLs_no_ghk_m2
#SBATCH --output=data/output/dI_KMCaLs_no_ghk_m2-%j.txt
#SBATCH --error=data/output/dI_KMCaLs_no_ghk_m2--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_km_no_ghk_m2.... |
f5c73927fc76e89be2d1f2875599bdf2faf52e00430a807002485e002f0996db | Shell | 344 | 13 | #!/bin/sh
#
#SBATCH --job-name=dI_KirCaLs_no_ghk_m2
#SBATCH --output=data/output/dI_KirCaLs_no_ghk_m2-%j.txt
#SBATCH --error=data/output/dI_KirCaLs_no_ghk_m2--%j.err
#SBATCH --partition=batch
#
#SBATCH --time=2:30:00
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=8G
julia script_dI_grad_no_ghk_m2.... |
59adfc6372da8044ede09ed5452deb21d9ec78822a26c8dddbc2207dac9b529c | Shell | 345 | 12 | #!/usr/bin/env bash
set -e
SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
echo "SCRIPT_DIR: ${SCRIPT_DIR}"
MANAGE=${SCRIPT_DIR}/../label_studio/manage.py
echo "=> Collect static..."
python3 $MANAGE collectstatic --no-input
echo "=> Create version file..."
python3 ${SCRIPT_DIR}/../labe... |
11cc2d000daa386c8f66011be7c36004d4e32c85d1d4608706f622724b9f2885 | Shell | 347 | 18 | #!/usr/bin/env bash
set -euo pipefail
if [[ $# -ne 3 ]]; then
echo "USAGE: $0 X_NPY META_NPZ OUT_ROOT"
exit 2
fi
X_NPY="$1"
META_NPZ="$2"
OUT_ROOT="$3"
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
export SEEDS="0 1 2 3 4"
export FOLDS="0 1 2 3 4"
bash "${SCRIPT_DIR}/build_v13_pool_full.sh" "$X_NP... |
826cd5110791b72b050fe75ac98bc4f79a35e9f8e1407dd5fc3e05711efe8c0c | Shell | 347 | 16 | #!/bin/bash
# source run_all.sh
#
echo #############################################
echo Press Esc at anytime to skip example
echo #############################################
echo
echo
for f in *.py
do
if [[ "$f" == *"geological_model"* ]]; then continue; fi
echo "Processing $f script.."
... |
c1c99618cd2d7135412dd0ef428c1ddc73333aa6d377d43106908975e9b97e64 | Shell | 347 | 19 | #!/bin/bash
#SBATCH -A m2_jgu-funcpoll
#SBATCH -J run_quast
#SBATCH -C skylake
#SBATCH -p parallel
#SBATCH -n 1
#SBATCH -c 1
#SBATCH -t 01:00:00
#SBATCH -v
#SBATCH -o run_quast.%j.out
#SBATCH -e run_quast.%j.err
module purge
PROJECT_DIR=/lustre/project/m2_jgu-funcpoll
src/quast-5.3.0/quast.py -o quast_output -t 10... |
8990ca27f741e753229a29edc4e4d2af69a3220330e26ff024202982e533866e | Shell | 348 | 11 | # /bin/bash
# bash run_example.sh {file_to_run.py} {num_gpus}
# where file_to_run = example to run. Default = 'example.py'
# num_gpus = num local gpus to use (must be at least 2). Default = 4
# samples to run include:
# example.py
echo "Launching ${1:-example.py} with ${2:-4} gpus"
torchrun --nnodes=1 --nproc_per_nod... |
4bb5212a2c3c524ed1bbccf2333f2eb4b0ffd4291e327771440cf5f4f251ccd6 | Shell | 350 | 9 | #!/bin/bash
#SBATCH --account=def-pbellec
#SBATCH --time=24:00:00
#SBATCH --job-name=shi_mvpa_seslvl
#SBATCH --mem=256G
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=40
/home/hyruuk/python_envs/shinobi_env/bin/python /home/hyruuk/projects/def-pbellec/hyruuk/shinobi_fmri/shinobi_fmri/mvpa/compute_ses-level_with_hcp.py -s... |
eb962a9202399e7d198b465dc15944b6f279c752ff9d33a985117aa46202d887 | Shell | 350 | 24 | #!/bin/bash
path=/mnt/d/TN/MVD_noeffective
cd ${path}
for sbj in 1
#1 2 3 4 5 6 7 8 9 10 11
do
for run in ST0 ST1
do
dcm2bids -d sourcedata/${sbj}/DICOM/PA0/${run} -p ${sbj} -s ${run} -c code/dcm2bids_config.json -o ${path} --force_dcm2bids
done
done
#dcm2bids -d sourcedata/1/DICOM/PA0/ST0 -p ${sbj} -s ST0 -... |
fe6c2ae2da72d7904f94b9ef5f7eeb56a0d93f3f7892587b9cb6a3bc8e922b2c | Shell | 350 | 13 | #!/bin/bash
dt=$(date '+%d_%m_%Y_%H_%M');
# Load Neccessary modules
#module load python/3.11.11
. .venv/bin/activate # add correct path corresponding to your virtual environment as step above
python ../extract_embd.py --path_data "../../test_data/fusionai_test_sim.txt" --output_folder "./output" --output_name "evo_... |
b2f4cdd0e198b895244f112cf1c4353d7920a3cb4fbedc949a78c8ba5e84666b | Shell | 352 | 4 | # Preprocessing
/data/project/sleep_ENIGMA_insomnia/Tools/CAT12.8.1_r2040_R2017b_MCR_Linux/standalone/cat_standalone.sh -m /data/group/sysmed/TOOLS/MCR/v93 \
-b /data/project/sleep_ENIGMA_insomnia/Tools/CAT12.8.1_r2040_R2017b_MCR_Linux/standalone/cat_standalone_segment_enigma.m \
/data/project/sleep_ENIGMA_insomnia/... |
35d9f252dfa974ace7063d3df7824e1441d0e858ca915b5671347f0687ead0e6 | Shell | 353 | 9 | #!/bin/bash
cd /home/ab714/bancpipeline
source /home/ab714/bancpipeline/o2/o2_env.sh
# Connect to transfer node
# ssh $(whoami)@transfer.rc.hms.harvard.edu 'bash -s; exit' < o2_banc_results.sh
# ssh $(whoami)@transfer.rc.hms.harvard.edu 'Rscript -e "$HOME/bancpipeline/banc/meta/banc-sort-folders.R" && exit'
Rscript -... |
02954f6485c462e8c31b9f6725e9f24d047c99632a20f3fda78e6a1223b52402 | Shell | 354 | 11 | #!/usr/bin/env bash
nohup python -m sample_qc.relatedness_inference \
--mt_input_path 'file:///home/ubuntu/data/hail_data/mts/chd_ukbb_split_v2_09092020.mt' \
--skip_compute_pc_relate \
--write_to_file \
--overwrite \
> relatedness_in... |
5c963f534b30f47f8c88af76f600dd8519f0ee761c035823c6f72aee4ef391fd | Shell | 354 | 9 | cd /data/share/htp/perturb-seq/TF94_combined/individual_demultiplexing
for lane in `cat /data/share/htp/perturb-seq/TF94_combined/download_from_tuebingen/ids.txt`
do
for genome in hg38 macFas6
do
sbatch -J ${genome}_${lane}_indiv_demux --output=${genome}_${lane}_%j.out --exclude=gorilla4 run_cellsnp_supervised... |
78798d01d1f31abbbde07129a95c7eb4a030a97ac7cb55a3c2ce5a31f4695ac5 | Shell | 355 | 17 | #!/bin/bash
# Process UKBB SNPTEST allele frequency data
# TODO: Add traps etc
body() {
IFS= read -r header
printf '%s\n' "$header"
"$@"
}
dataset='ukbb.eur'
infiles=("$@")
data_id=$(get_dataset_bits "$dataset")
parse_snpstats -v "$data_id" "${infiles[@]}" |
body sort --compress-program='gzip' -t$'\t... |
9bd585290cbd6ce4f144b287976119abc0b81f4101da78c28da4a00734ec0420 | Shell | 355 | 10 | apptainer exec \
-B /path/to/input:/src/data \
-B /path/to/output/Hypomap_output:/src/outdir \
/path/to/hires_latest.sif \
/src/CIBERSORTxHiRes \
--username YOUR_EMAIL_HERE \
--token YOUR_TOKEN_HERE \
--mixture /src/data/CIBERSORTx_Mixtures_Adjusted.txt \
--sigmatrix /src/data/Hypomap_custom_sig... |
492cb13a5e0a4b229e7b6c72c5a52999e45441b946d38295fa431c198d8845e8 | Shell | 356 | 11 | SCRIPT_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"
if bash ${SCRIPT_DIR}/../deploy/prebuild.sh; then
docker build -t heartexlabs/label-studio ${SCRIPT_DIR}/..
fi
if [ $? -eq 0 ]; then
docker run -it -p 8080:8080 -v $(pwd)/mydata:/label-studio/data heartexlabs/label-studio:latest
else... |
6666746734aa8aa42c95a152b3735843d33fc2239abbafbc369ac3e5ac877b9f | Shell | 357 | 8 | #!/usr/bin/env bash
nohup python ../sample_qc/sex_imputation.py \
--mt_input_path 'file:///home/ubuntu/data/hail_data/mts/chd_ukbb_split_v2_09092020.mt' \
--ht_output_path 'hdfs://spark-master:9820/dir/chd_ukbb_samples_sex_annotation_24092020.ht' \
--write_to_file \
... |
db45e33178e6da484233a13bf723b74e5e7f7e8c59ab8a36a59386888e20eb93 | Shell | 357 | 13 | # the first argument to this script should be the path to the ffhq_images1024x1024 folder
# the same path should be provided as the `data_root` argument to train.py
cd $1
mkdir train
mkdir train/0
mkdir valid
mkdir valid/0
for i in $(seq -f "%05g" 0 64999); do
mv $i.png train/0
done
for i in $(seq -f "%05g" 65000 6... |
45d7fa3318b777480a6bb0096d92ca5ba31931148e3d82afbc243129da168bbf | Shell | 358 | 23 | ANTsPath=$1
DataPath=$2
OutputPath=$3
prefix=$4
Data=`ls ${DataPath}/*.nii.gz`
${ANTsPath}/antsMultivariateTemplateConstruction2.sh \
-d 3 \
-o ${OutputPath}/${prefix}_ \
-i 10 \
-g 0.25 \
-c 4 \
-k 1 \
-w 1 \
-f 8x4x2x1 \
-s 3x2x1x0 \
-q 100x70x50x10 \
-n 1 \
-r 1 \
-l 1 \
-m CC[2] \
-t ... |
ff57c51b5fa49cbba817c149ca1d0baa54f0b239dd4c7c3e31565b8a4a1eb266 | Shell | 358 | 5 | #!/bin/sh -f
# Written by CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
sh ${CBIG_CODE_DIR}/utilities/matlab/fslr_matlab/bash_scripts/CBIG_border_to_fs_lr.sh $1 $2 $3 #project from freesurfer to fslr 164k
sh ${CBIG_CODE_DIR}/utilities/matlab/fslr_matlab/bash_scripts/CBIG_resample_... |
faddf5fcbb93883454d10ff14c04fb157ca4f8a878596f896882af647fc41494 | Shell | 359 | 10 | #!/bin/bash
for i in {1..9}
do
for j in {1..27}
do
#sh /local3/human_cell_penglab_test/text_jobs/$i/$j.txt
/data/mat/zhi/human_cell_penglab_test/gen_bench_job_scripts.sh /data/mat/zhi/human_cell_penglab_test/text_jobs/$i/$j.txt /data/mat/zhi/VAA3D/Bin_Vaa3D_BigNeuron_version1 /data/mat/zhi/human_cell_penglab_tes... |
4f9f980f8c8f30a8982204dad6368982b9b50477e18c26bdb54068cbd6c97e7e | Shell | 360 | 7 | #!/bin/bash
export TOKENIZERS_PARALLELISM=false
echo "=== STEP 1: CSSI Experiment ==="
python3 /mnt/d/openclaw/biodyn-nmi-paper/cssi_real/cssi_experiment.py 2>&1
echo "=== STEP 2: Remaining 6 Perturbation Genes ==="
bash /mnt/d/openclaw/intelligence-augmentation/analysis/results/insilico_wsl/launch_final6.sh 2>&1
echo ... |
f96f7082e6c133741d1f56b2b682cc4d60d3e5e3e209d1d61b9b68b642ef197e | Shell | 360 | 14 | #! /bin/bash
#
# Script to generate the version info of GEMMA and its environment
# in ./src/version.h
DATE=$(date "+%Y-%m-%d")
YEAR=$(date "+%Y")
PROFILE=$1
echo // version.h generated by GEMMA $0
echo \#define GEMMA_VERSION \"$(cat ./VERSION)\"
echo \#define GEMMA_DATE \"$DATE\"
echo \#define GEMMA_YEAR \"$YEAR\"
e... |
9bafd467e1f43c0b56a97b27f9359f1aff7fcdbaad0d0be8a9569182f4d0ac23 | Shell | 361 | 1 | curl -X POST -H "Content-Type:application/json" --data '{"dataframe_split": {"columns":["Year", "Month", "DayofMonth", "DayofWeek", "CRSDepTime", "CRSArrTime", "UniqueCarrier", "FlightNum", "ActualElapsedTime", "Origin" , "Dest", "Distance", "Diverted"],"data":[[1987, 10, 1, 4, 1, 556, 0, 190, 247, 202, 162, 1846, 0... |
9ffa63e8e3bacd244634e94b78371caa16884bc589b8eb43f41c320036826bfd | Shell | 363 | 6 | #!/usr/bin/env bash
# Test for running a single experiment. --repeat means run how many different random seeds.
python main.py --cfg configs/pyg/example_node.yaml --repeat 3 # node classification
python main.py --cfg configs/pyg/example_link.yaml --repeat 3 # link prediction
python main.py --cfg configs/pyg/example_gr... |
299e1220ceccc140e759b5650918c88e372c76f71cc183487d33571fc44533df | Shell | 364 | 10 | # Convert to netcdf
for file in /media/rasp/Elements/weather-benchmark/IFS_T21/raw/*; do
cdo -f nc copy "$file" "${file%.grib}.nc"
done
## Regrid to 5.625 degrees
#python ../src/regrid.py \
#--input_fns /media/rasp/Elements/weather-benchmark/IFS_T42/raw/output_42_pl_2.8125*.nc \
#--output_dir /media/rasp/Elements/we... |
413616bb23914674eeb0c4b71d12997dff72bbc001b106f6820f56d16673c876 | Shell | 364 | 14 | #!/bin/bash
# Submits slurm batches to do HCP coherency calculations
# Created on 20200804 by Max B Wang
MEG_Dir=/media/mwang/easystore/Processed_Data/
subjID="EP1188"
numEDFs=`ls "${MEG_Dir}/${subjID}/Electrode_Trials/" | wc -l`
for (( i=0; i<${numEDFs}; i++)); do
python3 GenCohMats.py ${subjID} ${i} 3 0 0 >> "L... |
aab1f4a4ffae471447b78b4de58ff8c302bed95d92c230c30a6d8fe44272cb12 | Shell | 364 | 19 | #!/bin/bash
#
echo "Running all examples in the 'examples' folder. This may take a while..."
cd basic; ./run_all.sh; cd ..
cd advanced; ./run_all.sh; cd ..
cd animation; ./run_all.sh; cd ..
cd volumetric; ./run_all.sh; cd ..
cd pyplot; ./run_all.sh; cd ..
cd other; ./run_all.sh; cd ..
echo ... |
462190eab941fdcfc837e8b068fa89ef2dcd37b07b57ed1be1b3cc78ff158d2e | Shell | 366 | 15 | #!/bin/bash
. /opt/miniconda3/etc/profile.d/conda.sh
if ! conda env list | grep "GRNBoost2" >/dev/null 2>&1
then
conda create --name GRNBoost2 python=3.6
conda activate GRNBoost2
conda install -c conda-forge loompy
conda install numba
conda install pandas
conda install tqdm
conda install tornado
conda ... |
d30ca0c288b0222bf946c7fffb846c56791fef03131b86304749a31cbb2a09b2 | Shell | 366 | 7 | pathway=$1
input=$2
output=$3
mkdir -p $output
java -cp /Users/kunyang/Applications/gsea-3.0.jar -Xmx5000m xtools.gsea.GseaPreranked -gmx $pathway -norm meandiv -nperm 1000 -rnk $input -scoring_scheme classic -rpt_label myAnal -create_svgs false -make_sets true -plot_top_x 10 -rnd_seed timestamp -set_max 500 -set_min... |
0e3367805c0cd4778302b4d9a5a812384b87a5bbbe3cbf9aa3d2e88a02852829 | Shell | 367 | 28 | #!/bin/bash
# batch build all bigneuron related plugins for v2.940
# by Zhi Zhou
svn up
cd zhijiang_zn_bjut/fastmarching_spanningtree_vaa3d/
make clean
qmake
make
cd ../../
cd qul/anisodiffusion/general/
make clean
qmake
make
cd ../../../
cd qul/anisodiffusion/littlequick/
make clean
qmake
make
cd ../../../
cd zho... |
2f10e9e2becb544b506294675c2c21557e2461b5a0fdb21e3b6fa98124a3059f | Shell | 367 | 15 | #!/bin/bash
if [[ "$COVERALLS" = 'true' ]]
then
sed -i '/Devel::Cover/d' ensembl/cpanfile
sed -i '/Devel::Cover/d' cpanfile
fi
cpanm --quiet --installdeps --with-recommends --notest --cpanfile ensembl/cpanfile .
cpanm --quiet --installdeps --with-recommends --notest .
if [[ "$COVERALLS" = 'true' ]]
then
cpanm... |
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