sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
0cc9fc5cc0bb6e2159ab530a67bc0196ac3a6bfdafd0a2e09b26f067b0f1cca7 | Shell | 237 | 4 | # rmf 5.4.2020, last modified 5.19.2020
# filter on pvalue and FPKM
SGE_Batch -c 'python ../../scripts/filterFimoSummaryFile1.py fimoResultsSummary.txt transcriptMedianExpression.txt 0.00005 1' -r filterFimoResultsSummary -q nucleotide
|
e423be0612337002654eedccc6815c7a2b1ad3af6bd51c8ebcc999269878d5d1 | Shell | 238 | 10 | #prepare human and mouse tables (Table S1)
Rscript master_comparison_human.R
Rscript master_comparison_mouse.R
gzip all_HLs_human.txt
gzip all_HLs_mouse.txt
#visualize Spearman correlations & bar plots
Rscript Fig1_S1.R
Rscript FigS2.R
|
cef1102a2a0e760a7047b9c61660605b2c9accc28188ba3ffd1d1ab8ce611153 | Shell | 239 | 10 | #!/bin/bash
clear
size=64
rm -rf "gridworld_${size}_policy_checkpoints" "gridworld_${size}_data.db"
time python solve_gridworld.py\
--size $size\
--num-workers 34\
--num-mcts-samples 32\
--log-level debug
|
0128d6c7c4c2c922766dd4265821b187c33d6fdd77f1a2e27cff42dc645aa686 | Shell | 243 | 7 | git config --global --add safe.directory $(pwd)/askcos-deploy
git config --global --add safe.directory $(pwd)/askcos-site
git config --global --add safe.directory $(pwd)/askcos-core
cd askcos-deploy/bkms-data
git lfs pull
cd ../
bash build.sh
|
02077b1cc55b88e14d3f92d1bdfd106bd70589fa6dca79fb6e991590ee363ef5 | Shell | 248 | 5 | sphx_glr_python_to_jupyter.py plot_using_trained_model.py
sphx_glr_python_to_jupyter.py minimal_example.py
sphx_glr_python_to_jupyter.py training_neuroquery.py
sphx_glr_python_to_jupyter.py reverse_search_from_brain_maps_to_terms.py
mv *.ipynb ../
|
c2e8c7d9a26e4895576cbeeb4b2ad623e01b460e10c43b6c578cf051457953b2 | Shell | 257 | 10 | #!/bin/bash
# Automatiza la realización del test sobre las distintas regiones:
mkdir ../../Datos/Test/Detections/
for file in ../../Datos/Test/*.png; do
python Test.py -i "$file"
done
mv ../../Datos/Test/*_detection.png ../../Datos/Test/Detections/
|
d1051ff694edadbaa0cf94aa03c179fbdbc56a4a6da2a64de463654ffdeba368 | Shell | 260 | 10 | #! /bin/zsh
#download friendly_clearmap docker image (if available, for testing purposes this is delivered with the script)
#wget -O ./friendly_clearmap_03.tar ___
#assuming it's already here, install it
sudo docker load -i ./friendly_clearmap_03.tar
|
55c8e0fd31658ec82fa06faa7fc02e3c5063205517064f9f78829a88c1c8c9cc | Shell | 273 | 10 | if [ ! -d /home/travis/nest-$NEST_VERSION/lib/python3.6 ] ; then
export HAS_NEST_CACHE=0
else
export HAS_NEST_CACHE=1
fi
if [ ! -f /home/travis/nest-$NEST_VERSION/lib/nest/libcerebmodule.so ] ; then
export HAS_CEREBNEST_CACHE=0
else
export HAS_CEREBNEST_CACHE=1
fi
|
827af55d528924cbeb7f0702b91148bcd9d1707160718ba6d13efa8ad863b821 | Shell | 273 | 12 | #!/usr/bin/env bash
set -e
echo "" > coverage.txt
for d in $(go list ./... | grep -v vendor); do
go test -race -coverprofile=profile.out -covermode=atomic "$d"
if [ -f profile.out ]; then
cat profile.out >> coverage.txt
rm profile.out
fi
done
|
dfad1663568646b6a92173745996841a3d8889766a8d5f6fc70e5fe742d485c7 | Shell | 279 | 10 | module load daint-mc Mesa/.18.3.3-CrayGNU-20.08
module load gcc/9.3.0
# Multicore stack
module load daint-mc
# Python 3 & mpi4py
module load cray-python/3.8.2.1
# Cython
module load PyExtensions/python3-CrayGNU-20.08
# h5py
module load h5py/2.10.0-CrayGNU-20.08-python3-parallel
|
3e72a0bd102ca04e9dfd5e18fbc6c408cfe9a5a21ae362c9a32708714f09d40f | Shell | 282 | 9 | hostname
date
PROJECT_DIR='/home/vauvelle/doctor_signature/'
export PYTHONPATH=$PYTHONPATH:$PROJECT_DIR
cd $PROJECT_DIR || exit
source /share/apps/source_files/python/python-3.7.0.source
source /share/apps/source_files/cuda/cuda-10.1.source
source .env
source ./.myenv/bin/activate
|
79fccb9401c6a7519f0ec72c62a8a2e25f321b9a745519da079da3c32ed12a95 | Shell | 285 | 12 | git clone https://github.com/nest/nest-simulator $GITHUB_WORKSPACE/_nest_repo
cd $GITHUB_WORKSPACE/_nest_repo
git checkout tags/v$1
mkdir build
cd build
sudo apt install libgsl-dev -y
pip install cython
mkdir -p $2
cmake .. \
-DCMAKE_INSTALL_PREFIX=$2 \
-Dwith-mpi=ON
make install
|
52ec18df5216b30863d1338c21b3a2d5f378ca37a1ffe6b83e7a86cb3978f5a6 | Shell | 287 | 12 | # install dependencies for local execution
python3 -m venv .venv
source .venv/bin/activate
sudo apt -y install python3-opencv
pip install --upgrade pip
pip install -r requirements.txt
# Kill Azure Function is already running
pkill func
# start Azure Function locally
func host start &
|
5cffd380d32deef59ba6151cb99e44fcce45ad3772202cf1bebf8257eb3abb49 | Shell | 287 | 18 | #!/bin/bash
# P300 data:
# Filters all subjects without graphical output
rm -rf p300
mkdir -p p300
n=1;
max=20;
while [ "$n" -le "$max" ]; do
rm -rf "p300/subject$n"
mkdir -p "p300/subject$n"
n=`expr "$n" + 1`;
done
echo "Successfully created the p300 folders"
./eeg_filter -b
|
6da82f5e8288818d78cd7248e214ecab677e50a83fd963981a2e3e0c31ce5224 | Shell | 288 | 10 | #!/bin/bash
FILE=../../../mil_deepsmile.sif
if test -f "$FILE"; then
echo "$FILE exists. This will be used for the rest of the scripts."
else
echo "$FILE does not exist. Please follow ~/dlup-lightning-mil/docker/README.md to set up a singularity image. Aborting."
exit 1
fi
|
fb8ef7d23dea73ef4c25187e771fa883d444d66af0e0b711fb3c899604792cd9 | Shell | 291 | 5 | CONDA_PATH="$HOME/.conda/envs/meld"
MELD_PATH="$HOME/software/meld_classifier"
source activate $CONDA_PATH
$CONDA_PATH/bin/python $MELD_PATH/scripts/classifier/ensemble.py --exp iteration_21-05-26 --ensemble-experiment-path iteration_21-05-26 --ensemble-exp-name iteration --ensemble-folds
|
930b988105ca28351a56f65c69f2b4d77f27e7478702c90318fa6ffc6ce03c86 | Shell | 301 | 8 | #!/bin/bash
set -e
# Setting NODE_PATH and config appropriately, using dependencies from
# client/node_modules, run eslint against args passed to this script.
# Primary use case here is for a pre-commit check.
NODE_PATH=src/ node client/node_modules/eslint/bin/eslint.js -c client/.eslintrc.js "$@"
|
feba45ad1f03d67c511df8b4cbc8dba9bec56430397fcb7e61d667e49b93de85 | Shell | 301 | 11 | #!/bin/bash
savepath=$1;
if [ ! -d "$savepath/train-midair" ]
then
mv "$savepath/train" "$savepath/train-midair";
mv "$savepath/best" "$savepath/train";
fi
python finetune-kitti.py --arch_depth=6 --ckpt_dir="$savepath" --log_dir="$savepath/summaries" --records=data --enable_validation $2
|
cd247b46227657d10a2e0517dd0579aeb286548e3b7d342f462a966919434cc8 | Shell | 303 | 4 | # rmf 4.9.2019, last modified 4.7.2020
# gets promoters and first introns of all transcripts in Drosophila genome
python ../scripts/getAllPromotersAndFirstIntrons.py transcriptPromoterAndFirstIntronLocs6000bp.txt /nfs0/BB/Hendrix_Lab/Drosophila/Genome/dm6.21/dmel-all-chromosome-r6.21.fasta transcript
|
0466388d875687ce0cf868b3f4ec549c5b87f1442f22b165b3b05a7115a0e40c | Shell | 306 | 15 | #!/bin/bash
#
#SBATCH --job-name=gk_detr
#SBATCH --time=01-10:00:00
#SBATCH --output=job_output_%j.out
#SBATCH --error=job_output_%j.err
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=1
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=grahamking@cusacklab.org
python K_detrend.py
|
3e5a9055a9cd4f36a91d934c83c458049de0d494ee0960696af5db151ae9071b | Shell | 306 | 7 | cellranger count --id=DP_OC3 \
--transcriptome=/d1/software/cellranger/refdata-gex-mm10-2020-A \
--fastqs=/d2/studies/scanPy/ACWS_DP/RawData/930_3GEX_DP_OC3_premrna/fastqs/930_3GEX_DP_DC3-mouse-nuclei-premrna_0_1_HVLLMDSXX/ \
--sample=930_3GEX_DP_OC3 \
--localcores=16 \
--localmem=128 \
--include-introns
|
2b4e3d1613a4a0b534d78d72818de849d1869dc41a1d651bbf5ec5a2e046430d | Shell | 312 | 3 | # rmf 3.2.2022
python scripts/plotMotifBindingSites_svg.py bindingSiteInfo_DAVID_LLCs_transcriptGroups0.05_Cluster6_calcium_ion_transmembrane_transport_FDR0.05.txt DAVID_LLCs_transcriptGroups0.05_Cluster6_calcium_ion_transmembrane_transport_transcriptList.txt transcriptPromoterAndFirstIntronLocs6000bp.txt 1 4
|
c7329a488c91d447e2b34aeba9f5af25686e2d4e47b6163c15f362445762c5ce | Shell | 315 | 16 | #!/bin/bash
# A simple script to build clpipe and generate the documentation
echo "Starting build"
echo "Clearing previous build"
rm -rf dist/*
# Build the .whl file
echo "Building wheel"
python -m build --wheel
# Build the documentation
echo "Building Documentation"
(cd docs; make html)
echo "Build complete"
|
e98d4f487d40b141940187d88b280af41c16174c727d35f08c0bedea846e8f14 | Shell | 333 | 10 | #/bin/bash
conda install -c anaconda jupyter
conda install pandas
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
conda install -c conda-forge nibabel
conda install -c conda-forge matplotlib
conda install -c conda-forge nilearn
conda install -c conda-forge tensorboard
conda install -c anaconda... |
e1c68ad34872aac04b2deecd0e9c2600ce36f9ae5a50d2d51088c89376f1d171 | Shell | 337 | 18 | #!/bin/bash
# Jaw clench experiment data:
# Filters all subjects without graphical output
rm -rf jawclench
mkdir -p jawclench
n=1;
max=20;
while [ "$n" -le "$max" ]; do
rm -rf "jawclench/subject$n"
mkdir -p "jawclench/subject$n"
n=`expr "$n" + 1`;
done
echo "Successfully created the results folders"
./eeg_fil... |
816b5d759e1560fc8aa488747276e746654c081c12011cdbabe07eb8e2dace32 | Shell | 342 | 7 | cellbender remove-background \
--input /d2/studies/scanPy/VM_NDB_Stress/D1_4_NDB_ctrl/outs/raw_feature_bc_matrix.h5 \
--output /d2/studies/scanPy/VM_NDB_Stress/CellBender/VM_D1_NDB_Ctrl_CellBender_Expect13k_Total50k/VM_NDB_Ctrl_CellBender_Matrix.h5 \
--cuda --expected-cells 13000 \
--total-droplets-included 50000 \
--f... |
3c3f58297b6a14ff5a12964597dfe7ac47e387efad4d4d84942676f2c0707061 | Shell | 343 | 13 | #!/bin/bash
declare config='../config/orthancDICOMWeb.json'
if [ $# -gt 0 ]; then
if [ "$1" = '--dimse' ]; then
config="${config%/*}/orthancDIMSE.json"
[ -f "$config" ] && echo "DIMSE config file selected: $config"
fi
fi
echo 'Starting Meteor server...'
METEOR_PACKAGE_DIRS="../Packages" meteo... |
bf6efb5c39d32a545f8761dbecf8827dbf5b3d50baed5d78c66b99b6362e2831 | Shell | 350 | 15 | #!/bin/bash
#SBATCH -n 2
#SBATCH --job-name=insideness
#SBATCH --mem=12GB
#SBATCH -t 10:00:00
#SBATCH --qos=cbmm
#SBATCH --workdir=./log
cd /om/user/xboix/src/insideness/
singularity exec -B /om:/om --nv /om/user/xboix/singularity/belledon-tensorflow-keras-master-latest.simg tensorboard \
--port=6058 \
--logdir=/om... |
cbef5668b0666a1b9edbfb07c7483927630d74aae20fa45d49cb82936dc88da7 | Shell | 350 | 5 | TRAIN_DIR=/home/zchayav/projects/syntheye/image_encoder/ae_trainset.csv
VAL_DIR=/home/zchayav/projects/syntheye/image_encoder/ae_testset.csv
SAVE_DIR=experiment_7/
DEVICE="0,1"
python train_ae.py --train-fpath=$TRAIN_DIR --val-fpath=$VAL_DIR --resize=512 --latent-size=2048 --loss=mae --epochs=100 --device=$DEVICE --sav... |
a18579d84d3f39b8567b39cef9353c0d1102e104091d7231707fe3865e5d45ab | Shell | 361 | 13 | #!/bin/bash
#SBATCH -n 6
#SBATCH --job-name=GZ_fastq
#SBATCH -t 1-0:0
#SBATCH -o slurm.GZ_fastq.out
#SBATCH -e slurm.GZ_fastq.err
#SBATCH --mail-type=END,FAIL
#SBATCH --mail-user=kcolney@asu.edu
#--------------------------
snakemake --snakefile Snakefile -j 30 --nolock --latency-wait 15 --rerun-incomplete --cluster "s... |
23ebaa07a1f0c88706f31b1388ad1ff63aa48627a2cf013a8c29af14fc145d2b | Shell | 366 | 12 | #!/bin/bash
# First change manually the version
version="$(python setup.py --version)"
echo "Current version $version"
read -p "Enter new version:" newVersion
sed -i ".backup" "s/$version/$newVersion/g" setup.py
git tag "$newVersion" -m "from $version to $newVersion"
git push --tags origin master
python2 setup.py sd... |
d4c8118374ad60db8b008db978ad3ab078038063a3028cd24df6eba073da0493 | Shell | 368 | 13 | PREVIOUS_DIR=$PWD
cd /home/travis
git clone https://github.com/dbbs-lab/cereb-nest/
cd cereb-nest
mkdir build
cd build
CEREBNEST_BUILD_DIR=$PWD
cmake -Dwith-nest=${NEST_INSTALL_DIR}/bin/nest-config ..
export NEST_MODULE_PATH=${NEST_INSTALL_DIR}/lib/nest:$NEST_MODULE_PATH
export SLI_PATH=${NEST_INSTALL_DIR}/share/nest/s... |
410f0faba013be6cf64ffc9fe05346e9f517156ed9fb80600dd4f10d04994172 | Shell | 369 | 17 | #!/bin/bash
#SBATCH -c 2
#SBATCH --job-name=rcnn
#SBATCH --mem=20GB
#SBATCH -t 10:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=any-gpu
#SBATCH --partition=cbmm
#SBATCH -D ./log/
cd /om/user/shobhita/src/symmetry/
hostname
singularity exec -B /om:/om --nv /om/user/xboix/singularity/xboix-tf_fujitsu3.simg \
python... |
0dc6af35e89d13b742bd568f165abd103b81114369e580c56956b7ab58a1fa6d | Shell | 370 | 18 | #!/bin/bash
#SBATCH --job-name=learnMSA
#SBATCH --output=slurm/learnMSA%j.out
#SBATCH --error=slurm/learnMSA%j.err
#SBATCH --nodes=1
#SBATCH --partition=vision
#SBATCH --gpus=1
#SBATCH --time=12:00:00
#SBATCH --mem=100gb
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
learnMSA \
-i ../test/data/egf.fasta \
-o ../test/eg... |
f9955666ea685dc69af41ab0b3ba6fbc27f8d647292144cb6f48fda20773a800 | Shell | 379 | 10 | #!/bin/bash
NEFF_CONC_VALUES=(2 2.25 2.5 2.75 3 3.25 3.5 3.75 4)
for conc in "${NEFF_CONC_VALUES[@]}"; do
python learnMSA/hmm/tf/fit_dirichlet.py ~/data/PFAM/seed_fasta/ \
--alphabet aa --name pfam_aa_neff_conc_${conc} --pattern *.fasta \
--num-runs 10 --clans ~/data/PFAM/Pfam-A.clans.tsv -c 1 \
--nef... |
f60f76d3d02de60a9b33d88550c0759b88e948f17c58f882d6bae152a3dcdbbc | Shell | 385 | 14 | #!/bin/bash
# To run GAM models in array, run `bash /PATH/TO/submit_gams.sh`
# Get current directory
filepath=`realpath $0`
cwd=`dirname $filepath`
# Get list of models in directory
models=($(ls $cwd/run_gam*.r))
# Get number of models
len=$(expr ${#models[@]} - 1) # len - 1
echo Spawning ${#models[@]} sub-jobs.
# Sp... |
4fa2f321ad574b6ef1639a2f464e573463f5a2a071ea1f57f1d0682f3adec84f | Shell | 387 | 12 | #!/bin/bash
if [ "${TRAVIS_OS_NAME}" = "linux" ]; then
sudo add-apt-repository ppa:ubuntu-toolchain-r/test --yes
sudo apt update
sudo apt install gcc-7 g++-7 --yes
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 60 \
--slave /usr/bin/g++ g++ /usr/bin/g++-7
sudo u... |
6313e665cef7d42d1a43e16e7313e0f61b2760c2af8d2c9b05d4636fb446aa63 | Shell | 393 | 20 | #!/bin/bash
#SBATCH --job-name=molecule_gym
#SBATCH --cpus-per-task=36
#SBATCH --mem-per-cpu=1GB
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --time=480
#SBATCH --account=rlmolecule
#SBATCH --cpu-freq=high-high:Performance
# MODIFY HERE according to your environment setup
source ~/arlmol
unset LD_PRELOAD
ech... |
6cfad5d4462c896bd34f04205fe420f748aa6f134451aef76de7d58b7a543c55 | Shell | 394 | 7 | #!/bin/bash
# rmf 7.2.2020, last modified 4.7.2020
# usage: <results file list> <median expression file> <p-value threshold> <fimoSummaryFile_FPKM1.0_p5e-05.txt> <FDR (True/False)> <TF expr thresh (FPKM)>
python ../../../../scripts/getSignificantBindingSites.py fileList.motifEnrichmentCorrectedResults.txt ../../gene... |
d3495ec39bba2ca069d23dd0623c205ab41b6706fadc450e7817e3e33c1ebeb3 | Shell | 397 | 5 | jupyter nbconvert --to python --template simplepython.tpl 02_load_and_concatenate.ipynb
jupyter nbconvert --to python --template simplepython.tpl 03_run_ica.ipynb
jupyter nbconvert --to python --template simplepython.tpl 04_epoching.ipynb
jupyter nbconvert --to python --template simplepython.tpl rsa_analysis_9x9.ipynb
... |
d2f2b041f0e77dd12659c45701ca2b6f39ed76d29f49ecfd3b4cffbc0efa7967 | Shell | 422 | 17 | #!/bin/bash
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
# Create virtualenv
ENV_DIR=${SCRIPT_DIR}/venv
python3 -m venv ${ENV_DIR}
source ${ENV_DIR}/bin/activate
# Install python dependencies
pip install -r "${SCRIPT_DIR}"/requirements.txt
# Install non-python dependencies
git clone https://github.com/ufoym/imbalance... |
6ad31f25d7c67069662f18901eac8f6d6d0f8dd5bac39e5b1b09e110dab04e0e | Shell | 423 | 8 | # rmf 5.11.2021
# get the input numbers for the venn diagram
sort -k11g motifEnrichmentSummary_LLCphases_addendum_eScoreNA_5FPKM_N10.txt | grep -v NO_TEST | head -n2 | awk 'NR > 1 {print $5, $6, $7}'
# then plot
# <group 1> <group 2> <intersect> <outbase> ### note that the calculations are done in the script, ent... |
05dd3e2f9620e48f282d57b12806f69db82651ba6baf00335bfba48d2fa90417 | Shell | 426 | 11 | #!/bin/sh
# instead of running rsa_analysis_script, clusterperm_script, and rsa_plotting_script
# one after another, you can call this script with "nohup" once.
# ---------------------------------------------------------------------------------
set -eu # subsequent commands which fail will cause the shell script to e... |
a1f0f8364940808cb1b08fbf755ca5942157d2aa7bf7d02e28548795521ae5f6 | Shell | 427 | 21 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name 'cnnlstm' \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 100 \
--task "detection" \... |
fec21a2b477bb2160eeaf967e1d21b4836b50a81d470055a7f044a3731115e80 | Shell | 427 | 19 | #!/bin/bash
#SBATCH -c 2
#SBATCH --job-name=activation_mean
#SBATCH --mem=50GB
#SBATCH -t 10:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=any-gpu
#SBATCH -D ./log/
cd /om/user/shobhita/src/symmetry/
hostname
singularity exec -B /om:/om /om/user/xboix/singularity/xboix-tensorflow1.14.simg \
python /om/user/shobh... |
c8310cb3ee94514e18c80e6b003bc6bbf692825fa4892e24c81fe4e8d27d6d55 | Shell | 428 | 21 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name 'cnnlstm' \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 60 \
--task "classificatio... |
2eb21521ce5d2bbbb2cb23a2f6242b0b74264b1cc29bad97dd2f12483d4f5c76 | Shell | 429 | 10 | #!/bin/bash
#$ -cwd # Current working directory
#$ -S /bin/bash # Shell
#$ -N ERR649813_cnc # Job name
#$ -j y # Merge stderr with stdout
#$ -o ERR649813_cnc.err # Stdout name
#$ -q nucleotide # Queue name
#$ -l mem_free=10G # Limit memory request
#$ -V ... |
36e82b1db176f827f681275c72eb0d783576b53a5d984b74a60f5afba37171ad | Shell | 429 | 10 | #!/bin/bash
#$ -cwd # Current working directory
#$ -S /bin/bash # Shell
#$ -N ERR649812_cnc # Job name
#$ -j y # Merge stderr with stdout
#$ -o ERR649812_cnc.err # Stdout name
#$ -q nucleotide # Queue name
#$ -l mem_free=10G # Limit memory request
#$ -V ... |
9984fcc8b8c3dfc9a8bc5b557ad9d2fe1fe2645106b543f6b6dfd8e4689fc929 | Shell | 429 | 10 | #!/bin/bash
#$ -cwd # Current working directory
#$ -S /bin/bash # Shell
#$ -N ERR649811_cnc # Job name
#$ -j y # Merge stderr with stdout
#$ -o ERR649811_cnc.err # Stdout name
#$ -q nucleotide # Queue name
#$ -l mem_free=10G # Limit memory request
#$ -V ... |
ec4d45c583b810b794008f16e7a48df94ccdc6561ff230807917681825ebf890 | Shell | 429 | 10 | #!/bin/bash
#$ -cwd # Current working directory
#$ -S /bin/bash # Shell
#$ -N ERR649814_cnc # Job name
#$ -j y # Merge stderr with stdout
#$ -o ERR649814_cnc.err # Stdout name
#$ -q nucleotide # Queue name
#$ -l mem_free=10G # Limit memory request
#$ -V ... |
21993eb9d659536448a9223faea304ce10dfa4814844710f6523812cbb44f21b | Shell | 433 | 14 | modelname="gpt2"
mode="history-profile"
modeldir=~/ivcds/simulator/clm-output/$modelname
dataset_dir=~/ivcds/data/data_for_clm_ablation/$mode
output_dir=~/ivcds/simulator/ablation/inference/inference-results
python inference_clm_bs.py \
--model_path $modeldir \
--model_name ori-$mode-$modelname-bs \
--batc... |
55578fcf777fe947279135f6bb80ed95974433370e133ae9399e041c7ad55bff | Shell | 434 | 33 | #!/bin/bash
HOMFAM="../../data/large/train/*.fasta"
mkdir -p alignments
mkdir -p times
run () {
mkdir tmp_files_large
for f in $1
do
filename=$(basename "$f")
cp $f tmp_files_large/$filename
perl replace_U.pl tmp_files_large/$filename
{ time mafft --parttree tmp_files_large/$filename > alignments/$fi... |
3a52a82f8994b0159945b4c69702e1c58f3f91d7a2d00a1d418cfbcd2ca159ce | Shell | 441 | 10 | # rmf 4.30.2021, last modified 5.17.2021
# cleaned up 3.1.2022
awk 'NR > 1 {print $2}' R2A_youngPhases20.0to24.0.txt > ELCs_youngPhase20to24_transcriptList.txt
awk 'NR > 1 {print $2}' R2R_youngPhases20.0to24.0.txt > RLCs_youngPhase20to24_transcriptList.txt
awk 'NR > 1 {print $2}' R2R_oldPhases21.0to1.0.txt > RLCs_ol... |
557dfa8d9e4710cf0f0373b3da6d319cc354d38196d0894bffd665246aaf1a14 | Shell | 441 | 11 | # Fix label mismatch: NUMEX that should be TIMEX:
sed -i '194s/NUMEX/TIMEX/' original_BBN_dataset/data/WSJtypes-subtypes/wsj00c.qa
# Fix ampersand issue: & -> %amp;
sed -i 's/&/TTEMP/g' original_BBN_dataset/data/WSJtypes-subtypes/*
sed -i 's/&/&/g' original_BBN_dataset/data/WSJtypes-subtypes/*
sed -i 's/TTEMP/... |
a6d89469121ef1336d110c61f163e41d7c08dfb46ee1dbe24da80657786bee03 | Shell | 443 | 19 | #!/bin/bash
#SBATCH -c 4
#SBATCH --job-name=clusters
#SBATCH --mem=50GB
#SBATCH --gres=gpu:1
#SBATCH --constraint=any-gpu
#SBATCH --partition=cbmm
#SBATCH -t 10:00:00
#SBATCH -D ./log/
cd /om/user/shobhita/src/symmetry/
hostname
singularity exec -B /om:/om /om/user/xboix/singularity/xboix-tf_fujitsu3.simg \
python ... |
15020549c5aa88a8e9271a88a7d3953b979376076b78e78747511b45a11d119b | Shell | 449 | 20 | #!/bin/bash
#SBATCH --time=7-00:00:00
#SBATCH --mem=50GB
#SBATCH --cpus-per-task=32
#SBATCH -J ModelArray
#module add openmind/singularity/3.9.5
config=/PATH/TO/config
source $config
set -eu # Stop on errors
# Get model from list of models
args=($@)
models=(${args[@]:0})
model=${models[${SLURM_ARRAY_TASK_ID}]}
IMG=/P... |
d1d371d6ae6219fde061e7aeda6cdc65d8cb7d407baf3d1b138373afb1915449 | Shell | 449 | 14 | modelname="gpt2"
mode="history-profile"
modeldir=~/ivcds/simulator/ablation/ablation-output/$mode-$modelname
dataset_dir=~/ivcds/data/data_for_clm_ablation/$mode
output_dir=~/ivcds/simulator/ablation/inference/inference-results
python inference_clm_bs.py \
--model_path $modeldir \
--model_name $mode-$modelname... |
bee955d6648eff3a984ac07f31cc7f362b6d16d0e575271881bf0773e4d30951 | Shell | 451 | 20 | #!/bin/bash
#Shelli Kesler 12/8/14
# Check mask files before moving on to dcon2
SUBJS=$(cat /Volumes/EHD/Study/paths.txt) #edit path to paths file
for subjdir in ${SUBJS}
do
cd ${subjdir}
#eddy current correction of raw DTI data
eddy_correct data.nii.gz dti_corr 0
#extract the first B0 volume
fslroi dti_co... |
39cc440d8945152b9bd8cbdad74a69c189b7f6742e0df5e61deff85997c927e2 | Shell | 453 | 22 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name 'densecnn' \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 100 \
--task "detection" ... |
5c2b6e7de8caa26712756c6844ba9bc1d1474157299cead284b232136559293a | Shell | 454 | 22 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name 'densecnn' \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 60 \
--task "classificati... |
561414a7344acb2fdbe297afa6e2d1921c87f9a19f759d212954501c7717b383 | Shell | 457 | 11 | #!/bin/bash
# rmf 4.6.2018; last modified 4.2.2019
# download and gunzip fastq files from ENA
wget ftp.sra.ebi.ac.uk/vol1/fastq/ERR649/ERR649811/ERR649811.fastq.gz
wget ftp.sra.ebi.ac.uk/vol1/fastq/ERR649/ERR649812/ERR649812.fastq.gz
wget ftp.sra.ebi.ac.uk/vol1/fastq/ERR649/ERR649813/ERR649813.fastq.gz
wget ftp.sra.e... |
227782d3fcefdb38598eb51e05bea69c80bc2dbd39894b23d9b2acc8bb838483 | Shell | 470 | 23 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name "lstm" \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 100 \
--task "detection" \
... |
8b7b7c192b6b2c36ad966180642bdda9a928a2c739cef5df9fb11c8ac3d0e828 | Shell | 471 | 12 | modeldir='/home/jitianbo/Workspace/driver_simulator_kvret/simulator/clm-output/gpt2/'
modelname="gpt2"
dataset_dir="/home/jitianbo/Workspace/driver_simulator_kvret/data/data_for_clm/"
output_dir="/home/jitianbo/Workspace/driver_simulator_kvret/simulator/inference/inference-results"
python inference_clm.py \
--mode... |
eb45a1b558c1abad4d1dde1c9ddfd82e741332ee26ddc5d15a27dfef0c36d3b6 | Shell | 471 | 23 | #!/bin/bash
INPUT_DIR=<resampled-dir>
RAW_DATA_DIR=<tusz-data-dir>
SAVE_DIR=<save-dir>
cd ..
python train.py \
--model_name 'lstm' \
--input_dir $INPUT_DIR \
--raw_data_dir $RAW_DATA_DIR \
--save_dir $SAVE_DIR \
--max_seq_len 60 \
--do_train \
--num_epochs 60 \
--task "classification" ... |
356f22239f38e49eaf9bf9f4d2a0441d8f397e380db2d6034355245aa04eab19 | Shell | 477 | 29 | #!/usr/bin/env bash
# check for template developer flag
JUPYTER_DIR='scripts'
update=0
while test $# -gt 0
do
case "$1" in
-u|--update)
update=1
shift
;;
*)
echo "$1 is not an accepted option..."
echo "-u, --update : Update default scripts"
exit
... |
16b3b54c4d7735ac275f914ff6b115eaab0a0b8977fdc1e175e09b132b387b45 | Shell | 481 | 29 | #!/bin/bash
markdown_files=(*_AMBA_legend.Rmd)
markdown_files+=(*_figure*.Rmd)
markdown_files+=(*_gene_enrichment.Rmd)
echo "Generating figures..."
for file in ${markdown_files[@]};
do
Rscript extract_code.R --infile $file
r_file="${file/".Rmd"/".R"}"
echo "Executing ${r_file} ..."
Rscript $r_file
rm $r_... |
1ce52a2efd27194eb70333113e0bb74554764f40d6aa89fb473a587acf3346a4 | Shell | 481 | 21 | #!/bin/bash
#SBATCH --account=rlmolecule
#SBATCH --time=2-00
#SBATCH --job-name=learning_curves
#SBATCH --nodes=1
#SBATCH --gres=gpu:2
#SBATCH --output=/scratch/jlaw/gpu_model_lc.%j.out
source ~/.bashrc
module load cudnn/8.1.1/cuda-11.2
module load gcc
conda activate /home/jlaw/.conda-envs/crystals_nfp0_3
run_id=1
f... |
af86b2699c7c5fd9af5792bb640b3a267b78e9d72a4ab8dc8380214f014a9650 | Shell | 482 | 20 | # Setup modules needed for the development environment
# Specific to UNC Longleaf system but can be adapted to your system's available
# modules.
# Clear any loaded modules
module purge
# Load all dependent modules
# Load system modules
module load fsl/6.0.3
module load freesurfer/6.0.0
module load afni/20.3.00
mo... |
34662673d9a5b988027a74d19f1768b4598b8a0312a45a09b374079937eda7db | Shell | 483 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o gen_gtex_ind-%A-%a.log --array=1-10 gen_gtex_ind.sh
module load MATLAB/2019a
module load GC... |
f11b99fc8bf2d5180c440b311706f8388a195b95022ebb81bd09b215b881a395 | Shell | 487 | 12 | #!/usr/bin/env bash
set -ex
SCRIPTDIR=$(dirname "${BASH_SOURCE[0]}")
kubectl apply -f "$SCRIPTDIR/deployment.yaml"
kubectl expose deployment testing --type=LoadBalancer --name=testing-service
CLUSTER_IP=$(kubectl get service testing-service -o jsonpath='{.spec.clusterIP}')
GALAXY_TEST_DBURI="postgresql+psycopg://post... |
8fa5ae6cfd487fef8ff316472576d999a48ea48a2f56f529c06381c5ddfab728 | Shell | 488 | 20 | # Setup modules needed for the development environment
# Specific to UNC Longleaf system but can be adapted to your system's available
# modules.
# Clear any loaded modules
module purge
# Load all dependent modules
# Load system modules
module load fsl/6.0.3
module load freesurfer/6.0.0
module load afni/20.3.00
mo... |
3608668a8a622394c3db3236b6e45cf6ba147489d4583873a14776de4f4ea038 | Shell | 491 | 18 | #!/bin/bash
subjs=($@) # You can run 'submit_job_array.sh sub-xx sub-xy' to only run specific subjects
base='' # PUT YOUR BIDS DIRECTORY HERE
# Get subject names from the directory
if [[ $# -eq 0 ]]; then
pushd $base
subjs=($(ls sub-* -d))
popd
fi
# take the length of the array
# this will be useful for i... |
dc7279b25dac7217b4b7350eca1afe32e85c6452c0a98a23a3b615b3a59b13e1 | Shell | 491 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o logs/gen_gtex_ind8-%A-%a.log --array=1-10 gen_gtex_ind8.sh
module load MATLAB/2019a
module ... |
f1e336f6127cba123f624b1bbc6eb657e139c6bdd728203f407ea8b620c26875 | Shell | 495 | 18 | #!/bin/bash
subjs=($@) # You can run 'submit_job_array.sh sub-xx sub-xy' to only run specific subjects
base='' # SET THIS TO BE YOUR BIDS DIRECTORY
# Get subject names from the directory
if [[ $# -eq 0 ]]; then
pushd $base
subjs=($(ls sub-* -d))
popd
fi
# take the length of the array
# this will be useful... |
40d7ec293b79ead0cb853ea1f9dd765be41e284799d9723169bdb39d4c179113 | Shell | 496 | 6 | # rmf 11.6.2019, last modified 3.6.2021
# rhythmic gene group files qval 0.05
ln -s /nfs0/BB/Hendrix_Lab/Drosophila/CircadianRhythms/RNASeq/RP24Analysis/Hisat2AlignmentTranscripts/newGeneGroups/R2A.txt ELCs_q0.05.txt
ln -s /nfs0/BB/Hendrix_Lab/Drosophila/CircadianRhythms/RNASeq/RP24Analysis/Hisat2AlignmentTranscripts/... |
53427a3aa480061570dec295d982684c2e76da24b70131f07304d5bf0b56189e | Shell | 498 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o run_lc3_tasks_run_5-%A-%a.log --array=1-16 run_lc3_tasks_run_5.sh
module load MATLAB/2019a
... |
d2b36a4983aed807ed3237d5e58d3de972f43023f1f4ba5f07e06ee62a913163 | Shell | 504 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o run_mcor3_tasks_run_5-%A-%a.log --array=1-17 run_mcor3_tasks_run_5.sh
module load MATLAB/20... |
bb8069fb10ddfa99ec7d538d0bcd1af0ee42d3e6ea320d24b0b0416b801067d7 | Shell | 507 | 12 | #!/bin/bash
# rmf 12.16.2020, last modified 3.6.2021
# ELCs
for f in ../DAVID_outputFiles/DAVID_ELC*_transcriptIDs.txt; do python ../../scripts/processDAVIDclusterGeneLists.py $f ../ELCs_q0.05.txt; done
# RLCs
for f in ../DAVID_outputFiles/DAVID_RLC*_transcriptIDs.txt; do python ../../scripts/processDAVIDclusterGene... |
35e4bf00be9f67c9919263d77a6e72b52f04c5b08a941f107e3435581f6abd7e | Shell | 509 | 17 | #!/bin/bash
wget https://zenodo.org/record/6524237/files/extHomFam-v2.zip
unzip extHomFam-v2.zip
X=("small" "medium" "large" "xlarge" "huge")
for folder in "${X[@]}"
do
mkdir ext_homfam_$folder
mkdir ext_homfam_$folder/refs
mkdir ext_homfam_$folder/train
mv extHomFam-v2/$folder/* ext_homfam_$folder/trai... |
93f51e9b0f155c44b8f0c17aed1806c30424bad4388c28c5941703e452f1abf8 | Shell | 513 | 19 | modelname="gpt2"
savename="gpt2"
dataset="~/ivcds/data/data_for_clm"
python run_clm.py \
--model_name_or_path $modelname \
--dataset_dir $dataset \
--per_device_train_batch_size 4 \
--per_device_eval_batch_size 4 \
--num_train_epochs 40 \
--do_train \
--do_eval \
--learning_rate=5e-5 \
... |
0cd96796ce8c3248a88f681a68a884e43039930d08df20840528089b31ece2d2 | Shell | 516 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o gen_mcor3_models_run_5-%A-%a.log --array=1-17 gen_mcor3_models_run_5.sh
module load MATLAB/... |
8eaa0b9669d0ccf5071a01fce37202c9436227f657733d01116719e4d5b3f3fe | Shell | 516 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o gen_lc3_models_run_5-%A-%a.log --array=1-16 gen_lc3_models_run_5.sh
module load MATLAB/2019... |
43a8fecfa8f2c923d3ab891fad0f06c4c85d63465ef22a6d29712a0d44259ce9 | Shell | 518 | 13 | #!/bin/bash
# must be run from a virtualenv with...
# https://github.com/koxudaxi/datamodel-code-generator
# Use the installed datamodel-codegen
CODEGEN="datamodel-codegen"
# Base URL for WES OpenAPI spec
WES_SPEC_URL="https://raw.githubusercontent.com/ga4gh/workflow-execution-service-schemas/develop/openapi/workflo... |
78468ce399ce8a13fdf5b2a6ece7d4111cc66b7a5802277064fd1a515a067ab1 | Shell | 519 | 28 | dataset=$1
device=$2
[ -z "${dataset}" ] && dataset="mutag"
[ -z "${device}" ] && device=-1
python main_graph.py \
--device $device \
--dataset $dataset \
--mask_rate 0.5 \
--encoder "gin" \
--decoder "gin" \
--in_drop 0.2 \
--attn_drop 0.1 \
--num_layers 2 \
--num_hidden 512 \
--num_heads 2 \
--max_epoch ... |
7f1e1d4ec92f1cdb6ce015705d0380dac6108b4af92178ddccb1e31f8819f944 | Shell | 520 | 20 | #!/bin/bash
#SBATCH -p gpu
#SBATCH -n 16
#SBATCH --gres=gpu:gtx1080ti:1
#SBATCH --mem 200G
#SBATCH -J orf
#SBATCH -o orf.%j.out
######################################################################
##### Script modified from one written by Han Yuan, Calico Labs
#######################################################... |
18b693892d651fd5041743547dc7d77d6944f36578083451d3ff4942d65448e0 | Shell | 521 | 15 | DATA_DIR=/home/TR2000
fmriprep-docker \
--image=poldracklab/fmriprep:1.2.6 \
--nthreads=16 \
--task-id=memory \
--output-space=template \
--template-resampling-grid=/data/derivatives/templates/mni_icbm152_nlin_asym_09c_3.5mm_T1_brain.nii.gz \
--skip-bids-validation \
--fs-license-file=licen... |
0a3adbea2d5a86719695f686ddaebd32a3a33b14a4b1646ec0bac6ef583e627a | Shell | 522 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o gen_PS_hcat-%A-%a.log --array=1-10 gen_PS_hcat.sh
module load MATLAB/2019a
module load GCCc... |
4218d705d94821fbaf39715dea61abe8913d26efde765872d81d0d23fc0c6195 | Shell | 522 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o gen_PS_t68k-%A-%a.log --array=1-10 gen_PS_t68k.sh
module load MATLAB/2019a
module load GCCc... |
681be8bbe96359d60ef087d0767e5c7b5753679184ef1c413c7e8859365e961e | Shell | 525 | 22 | #!/bin/bash
#SBATCH -c 2
#SBATCH --job-name=activation_mean
#SBATCH --mem=50GB
#SBATCH -t 10:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=any-gpu
#SBATCH -D ./log/
cd /om/user/shobhita/src/symmetry/
hostname
singularity exec -B /om:/om --nv /om/user/xboix/singularity/xboix-tensorflow1.14.simg \
python /om/user/... |
89ad5573431a42dcd33e0e5d96c218bea3ffb2fa780c416f646a869b19381b2f | Shell | 525 | 8 | #!/bin/bash
MODEL=inceptionv3
TRAIN_DIR=/home/zchayav/projects/syntheye/all_baf_valid_50deg_filtered_train_0_edited.csv
VAL_DIR=/home/zchayav/projects/syntheye/dataset/all_baf_valid_50deg_filtered_val_0.csv
SAVE_DIR=experiments/feature_extractor
DEVICE=2,3
python retrain.py --model=$MODEL --train=$TRAIN_DIR --val=$VAL... |
5be76da3edd1fdca2ee245f25a1b47b675fd33f9cada6de62128f3dad5413e8c | Shell | 526 | 21 | #!/bin/bash
#SBATCH -A C3SE2022-1-16 -p vera
#SBATCH -n 20
#SBATCH -t 5-00:00:00
#SBATCH --mail-user=gustajo@chalmers.se
#SBATCH --mail-type=end # send mail when job ends
# submit batch job using the line below:
# sbatch -o generate_GTEx_models_old_tINIT-%A-%a.log --array=1-20 generate_GTEx_models_old_tINIT.sh
mod... |
3d820599f37d9f4bbd9f2d6d9ebfe789f39ccb5968cea6c6bdd9e856f2e759f9 | Shell | 532 | 15 | DATA_DIR=/home/TR600
fmriprep-docker \
--image=poldracklab/fmriprep:1.2.6 \
--nthreads=16 \
--task-id=hrf \
--output-space=template \
--template-resampling-grid=/data/derivatives/templates/mni_icbm152_nlin_asym_09c_3.0mm_T1_brain.nii.gz \
--skip-bids-validation \
--fs-license-file=license.t... |
dc87d80336fcef04f69d5bd3b066025eda9470d2ce7d1c5d536f55ae58af4a24 | Shell | 532 | 8 | #!/bin/bash
TEST_DIR=/home/zchayav/projects/stylegan2-ada-pytorch/synthetic_datasets/stylegan2_synthetic_-2perclass/generated_examples2.csv
MODEL_DIR=/home/zchayav/projects/syntheye/classifier_training/experiments/R_r1/
SAVE_DIR=/home/zchayav/projects/syntheye/classifier_training/experiments/synthetic_data_evaluation
W... |
1e980b9e96d3a611d31c5ef149613757a7d1b68f433e46eb38f7c92b0f3ebc56 | Shell | 537 | 12 | TF_CFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_compile_flags()))') )
TF_LFLAGS=( $(python -c 'import tensorflow as tf; print(" ".join(tf.sysconfig.get_link_flags()))') )
CUDALIB=/usr/local/cuda/lib64/
nvcc -std=c++11 -c -o backproject_op_gpu.cu.o backproject_op_gpu.cu.cc \
${TF_C... |
1530cb862827dce1ab3bf5529ddee784ac4bf27dd8c85b6d6fc5740e0d84f885 | Shell | 540 | 11 | #!/bin/bash
export LC_NUMERIC=POSIX
sigma=0.15
for ieff in `seq -0.035 0.01 0.055`
do
i0=$(python -c "print($ieff + 2*$sigma**2)")
echo "Running ring_simulation.py with sigma =" $sigma "and i0 =" $i0 ", (i0eff =" $ieff")."
OMP_NUM_THREADS=8 python3 -W ignore ring_simulation.py -f conf/conf_paper.txt -ntri... |
af8d0444d848f0984aa7df4a03f3c110209d3eb3d8f19dffb941c3c57e186722 | Shell | 562 | 15 | DATA_DIR=/home/TR1000
fmriprep-docker \
--image=poldracklab/fmriprep:1.2.6 \
--nthreads=16 \
--task-id=MGT \
--output-space=template \
--template-resampling-grid=/data/derivatives/templates/mni_icbm152_nlin_asym_09c_2.0mm_T1_brain.nii.gz \
--skip-bids-validation \
--fs-license-file=license.... |
4944fda8e62e8a9c403deb7fb34d9060cd448fbec15cea244e77837ef78452d1 | Shell | 564 | 23 | #!/bin/bash
mkdir homfam
cd homfam
wget http://www.clustal.org/omega/homfam-20110613-25.tar.gz
tar -xvf homfam-20110613-25.tar.gz
rm homfam-20110613-25.tar.gz
mkdir refs
mkdir train
mv *_test-only.vie train
mv *_ref.vie refs
for file in refs/*.vie
do
mv $file ${file%_ref.vie}.ref
done
for file in train/*.vie
do
... |
b5bb208bfcc820abbacd10eaf899dadccc751771f4cce11cc699ad81784bf1ba | Shell | 564 | 8 | #!/bin/bash
# rmf 3.24.2020, last modified 6.18.2021
# cleaned up 3.1.2022
for f in significanceTestingResults/*.txt; do python ../../../scripts/performMultipleTestCorrection_BG.py $f ../../memeMapFile.txt ../geneMedianExpression.txt ../../secondaryIDsFile_fb_2020_05.txt ../../JASPARsecondaryIDsFile.txt; done
for f ... |
014bf8c2892b63d5152f1c84041d0333c0bdbcf1676ea8ac89a4eb154e4e6bd9 | Shell | 565 | 26 | #!/bin/bash
# ----------------------------------------------------------------------------
# pipeline_main
# Author: Antoine Beauchamp
#
# Pipeline to download and process all data necessary to generate the paper.
#On MICe machine
module purge
source activate_venv.sh
#Download and process AMBA data
source build_AMB... |
94c9f5ec18170176e05291eb3be27daa1e3359b85535735e271f5c74c6c43e35 | Shell | 565 | 11 | #!/bin/bash
## Run this script in the dircetory containing all the model structures.
## The standalone version of MolProbity can be downloaded from http://molprobity.biochem.duke.edu/
## Install MolProbity locally on your machine and edit the next line with the absolute path of installation.
MODULE=<Absolute Path t... |
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