sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
5f755c676cfb08f35eb109d503e90af7719bb4282a76094c2108aece5703f828 | Shell | 80 | 2 |
scp -r $1 tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/MARS/MARS
|
e73b79d581b983c87d575f7a8fe9a04cb922fb18ad32f1ba6d04d967c2a57b2d | Shell | 81 | 2 | # For use inside Docker image.
medpseg -i /workspace/inputs -o /workspace/outputs |
edf31289c9b7894ef74b8703721a4a4453742582fee6976d35419bfcfe37daa0 | Shell | 81 | 1 | scp -r tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/MARS/result* .
|
aaadbaf82247a29fc51ab7ade5ac3de60ff5cb5c1445aaffdf1291088d83eaf8 | Shell | 84 | 6 | #!/bin/bash
YELLOW="\033[1;33m"
RED="\033[1;31m"
BLUE='\033[0;34m'
RESET="\033[0m"
|
049b934fe88cc6e6f51436b3ccfd6ee401683640ad1c749e8d6b6d23df46cb2c | Shell | 85 | 4 | #!/usr/bin/env bash
export PYTHONPATH="$PWD:$PYTHONPATH"
python dev/proto_plugin.py
|
0a5ad21970a64a8d7b909d9c0c89f382202209b3853945f2ad1f57f3589d9754 | Shell | 85 | 6 | #/bin/bash
A=`grep -v \> $1 | wc -c`
B=`grep -v \> $1 | wc -l`
C=$(($A-$B))
echo $C |
6bd7e9b4404700fbb30ae505d6d196466394c14a772bef1944a299d894eb5066 | Shell | 85 | 2 | #!/bin/bash
ln -s ../../k_fold_mode/train_val/Fold1/Pytest_Fold1_200K_chunk27.h5ad .
|
0f8135449fa02c5b3b456dd0bff6c4e79c5eb99355e7faa7962472a39414c8db | Shell | 86 | 5 | #!/bin/bash
mkdir -p ../ants ../spm ../fsl
./fsl_to_fmriprep.sh
./fmriprep_to_fsl.sh
|
45025b1a1972d85fa022dc720a4df64c1a278f7488d287c0e09332d8be2d63b3 | Shell | 87 | 2 |
scp -r $1 tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/mol_dqn_docking/
|
aabbb6e2bcdcd420b0f229382cec4ce7773075dfcdb91200c48af825dbf49c68 | Shell | 87 | 8 | #!/bin/bash
mkdir data/conditons/
mkdir data/mask/
mkdir data/nsdata
mkdir projects
|
9fddb4c0853717491c713880e690b4b9268ef37ad3431fd1e31e8034a4db49d2 | Shell | 89 | 4 | #!/bin/bash
nohup python -u data/scripts/split_multi_allelic_hts.py > nohup.log 2>&1 &
|
e95937b178ca7be3eb89be438805e3b1a05921c063671ad94f14896f831032b3 | Shell | 89 | 2 | #!/bin/bash
ln -s ../Fold1/Pytest_Fold1_200K_chunk27.h5ad Pytest_Fold3_200K_chunk1.h5ad
|
af2075e9a68a9ce511402a2f8f258cd15c86a7e4a24219f9144da695d5617f2a | Shell | 90 | 3 | #!/bin/bash
CHECKER="pep8 --max-line-length 120"
find . -name "*.py" -exec $CHECKER {} \;
|
a1cc72a7b67bea0eeb63aa1b50e09579ec71ebc9b8fbdf1b33acfc8889fe94b9 | Shell | 92 | 2 |
scp -r $1 tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/guacamol_tdc/guacamol
|
ef0595b78d2b7de3f9df646f0dc80672a678bd11dc8493c370af38450ca29bc8 | Shell | 92 | 2 | wget https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
tar -xf cifar-10-python.tar.gz
|
f17d70105b00177087bc375634119a47cc088961ce8b8a70fa1062f21a347639 | Shell | 93 | 3 | META=./final_ids_lens.csv
OUTDIR=./
python3 ./align_for_sim.py --meta $META --outdir $OUTDIR
|
bbcd23580e682dd1033da6a8e6112646d79c160008963b23d1d6d41ddcc5e814 | Shell | 95 | 1 | coverage run -m unittest discover tests && coverage report && coverage-badge -f -o coverage.svg |
6a97018bfcd8e124fa070de775b0c1ba206e7e5a68e5a9d7cf899097818efee3 | Shell | 96 | 7 | dataset=$1;
cd utils
python extract_audios.py --$dataset
python extract_frames.py --$dataset
|
c02bc3d4c1ec3785b4dded40a8f19af98ea46aaf4b9bc9da68195394456b3fe7 | Shell | 96 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
pod5 convert fast5 "$input_dir" --output "$output_dir"
|
d467360a2331d86c69162c17e4e025fd1e862a42b58369f8cf27e5ece32f64a3 | Shell | 96 | 7 | #!/bin/bash
for file in *.mp4
do
fn=${file%.*}
ffmpeg -i "$file" -pix_fmt rgb24 "$fn".gif
done
|
b26896a37d51f8ee3c6e2b6373f2d3d11716f588f83535a97502389894544023 | Shell | 97 | 5 | #!/usr/bin/env bash
set -eu -o pipefail
echo "# This is an auto-generated file. DO NOT EDIT"
cat |
e54fdfca4658f34d6826ffd39c7c1c5e66040e58a74d04c18407ba9ce72e1f1c | Shell | 97 | 5 | mkdir src
catkin_make
source devel/setup.bash
echo $ROS_PACKAGE_PATH
chmod +x ./devel/setup.bash
|
02600e5ef1d41e4b0544ac545402446d5d0604162b6edecce317d08e7566bf05 | Shell | 99 | 3 | #! /bin/sh
python prep.py mol2d models/model_bitshift_int8_0.onnx --providers CPU --batch_size 67
|
1bbd282a43c4d39b6c6e96bd2606eec3487fc56c46ceba30e623c96b9af5f0a5 | Shell | 101 | 5 | #!/usr/bin/env bash
ROW=$SGE_TASK_ID
TASK_FILE=$1
`awk -v r=$ROW '{if(NR==r){print }}' ${TASK_FILE}` |
3eba865cf56d17aa8f524e9207cabb0a9fc4311c5c6df137cd0b6eaea68ba9e8 | Shell | 101 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
./tools/fast5_to_single_blow5.sh "$input_dir" "$output_dir"
|
1d7d0c48a6bac11bc4103e08e0eb3a4e9d7543532e709c9be8e78ce211f6163c | Shell | 102 | 2 |
scp -r $1 tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/guacamol_tdc/guacamol_baselines
|
744b2edaea0c0483746e79eb787d5316597d4c9c737cec76f3f2d5a3b0cf3926 | Shell | 102 | 2 | #./coseg_two ../data/two_img1.bin.tree ../data/two_img2.bin.tree
./coseg_more ../data/frame*.bin.tree
|
f9b18d5ea1672b90fb3e119786d34fc04a7f4b80e278f7d1e49f9042d6fa1230 | Shell | 102 | 6 | if ! $* ; then
echo '
NEURON exited abnormally. Press the return key to close this window
'
read a
fi
|
5793d6b9f6b008a9f2090ac628f4a25b36e1a13a97535e8009a53a166821cf67 | Shell | 103 | 2 | #!/bin/bash
gnome-terminal -e "bash -c \"source activate pyecog2PySide; python -m pyecog2; exec bash\"" |
718a7cff55ee6db2287feb4bddae2a37dda2992a5a77cc844ccfbae78ec15eec | Shell | 105 | 3 | conda activate BiaPy_env
docker build -t BiaPyX/biapy:latest-11.8 -f BiaPy/biapy/utils/env/Dockerfile .
|
2ec9ee090dcc562f8fe6a23fbdc62251b0fb3d2f05d9ceef68fd45cef012bd6a | Shell | 106 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
tools/find_and_get_fast5.py "${input_dir}/fast5" "${output_dir}"
|
695b78a54216daae032536a68b7c55e4ced5982733715be6eddb3e42fcbf94b1 | Shell | 106 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
./tools/find_and_get_pod5.py "${input_dir}/pod5" "${output_dir}"
|
74f64f54c028c4a7d4eb5e8a3c30c733cdbe508b0e3c8df846c495ac1c357e21 | Shell | 107 | 3 | #!/bin/bash
gsutil -m rsync -r -d . gs://encode-pipeline-test-samples/encode-atac-seq-pipeline/ref_output
|
9e3b1bee561f2557d0f90cb9440f4395a86701826c62bb163edbad1f4bda147c | Shell | 108 | 10 | dataset=$1;
cd utils
python gen_audio_features.py --$dataset
python gen_visual_features.py --$dataset
|
e1382f9c84d8f5c12f3ec5a15db326dfc7ac2f2c6e90de5e7dd586744d105513 | Shell | 108 | 3 | #!/usr/bin/env bash
echo "Building docker image..."
docker build -f Dockerfile -t transmorph_brain_mri_t1 .
|
25dbbada331698595b4b7daeca7e02a42fe606528b06bab7167610e821cedba8 | Shell | 111 | 1 | python -m coverage run -m pytest --ignore=.venv --ignore=datasets --ignore=tools --ignore=tflite --ignore=utils |
2e6c89de05bf854bad111600ab0bcc85568c2aadf84a7453ef9b45dbaa55feff | Shell | 111 | 2 | export PYTHONPATH=$PYTHONPATH:/mnt/d/CSU/QC/QuantumProteinStructurePredictProject/
python train.py --valkfold 4 |
6935337c015b054b84df1da02b0814106c725d8dc2c2a5059af3c7860caeaefa | Shell | 111 | 5 | #!/bin/sh -e
sudo systemctl stop mmseqs-server
rm -rf -- jobs
mkdir -p jobs
sudo systemctl start mmseqs-server
|
8ade5e70be0cdb623af0c95d213fb91685a5c92be04fcd09d72ec5d92e908cd3 | Shell | 111 | 2 | export PYTHONPATH=$PYTHONPATH:/mnt/d/CSU/QC/QuantumProteinStructurePredictProject/
python train.py --valkfold 2 |
9180a4bfe19778868b9e5183c24f46447bb0e6475f09948d4244f68dd73ca082 | Shell | 111 | 2 | export PYTHONPATH=$PYTHONPATH:/mnt/d/CSU/QC/QuantumProteinStructurePredictProject/
python train.py --valkfold 1 |
9b7b3b2fea608e70469872bd295fd129f6fd61f318f89adedcf4bf1560a96105 | Shell | 111 | 2 | export PYTHONPATH=$PYTHONPATH:/mnt/d/CSU/QC/QuantumProteinStructurePredictProject/
python train.py --valkfold 3 |
bf7c925d6b37f861f7da9839693791d6e9ed104ffe547c43c81ff472e973ab48 | Shell | 111 | 2 | export PYTHONPATH=$PYTHONPATH:/mnt/d/CSU/QC/QuantumProteinStructurePredictProject/
python train.py --valkfold 0 |
14506d8fca23a5787a534f00c9fe0366f0cceec37552353dd1d4fb73d0f1d28b | Shell | 113 | 5 | #!/bin/bash
echo 'hexamers <- c('
python hexamers.py | awk 'NR > 1 {printf(",\n")} {printf("%s", $1)}'
echo ')'
|
4684324d15858229a5dce1813d84141ef30361ac5a1612c821d64ab227342aa0 | Shell | 114 | 2 | #!/bin/bash
gnome-terminal -e "bash -c \"source activate pyecog2PySide; python -m pip install -e . ; exec bash\"" |
54ffa34cc31fdf9248d8171ab04c780373341f6b38d83d37a4a3bd6bdce42b3e | Shell | 114 | 7 | nrnivmodl ./mechanisms
# Use for python 2.6+
python ./run.py "$@"
# Use for python 3.4+
# python3 ./run.py "$@"
|
cbb05d785b182c40731dd17789861fb324aafb2d5e6e018f8a5462fd0051fdfc | Shell | 114 | 7 | #!/bin/bash
for (( i=$1; i<$2; i++ ))
do
echo "Starting $i..."
sbatch model_building_order2.sh 1000 $i
done
|
cf94fcef7784429d9d95ec2ce5a400a9a270db2aebf40dd84c52df7635086be5 | Shell | 115 | 6 | cd c:/nrn
rm -f mknrndll.zip
zip mknrndll.zip bin/nocmodl.exe bin/modlunit.exe \
bin/mos2nrn.exe \
lib/libscpmt.a
|
14b2dc64d6f85cf66ae33039d0527b2d2c6e0007e7fd7c31920b43bbe6639025 | Shell | 116 | 4 | #!/bin/bash
for filename in crash-*.pklz; do
nipypecli crash "$filename" > "$(basename "$filename" .txt).txt"
done |
683b74551e321fea7216f8294be6263f9bb20cdd3bdebd2176faafc3ae6e77f7 | Shell | 116 | 4 | # command
humann_infer_taxonomy -i genes.tsv -g uniref50_rxn -o genes_inferred.tsv
# output
# 1) genes_inferred.tsv
|
dc8b3cef5a4ee8c1cf79978057e22f43c7418943cefab037daf1376787a81e9a | Shell | 116 | 3 | #!/usr/bin/env bash
echo "Building docker image..."
docker build -f Dockerfile_GPU -t transmorph_brain_mri_t1_gpu .
|
9ea6cee6d5643271f24f57cf1de8089717fc872edcb2f57b46f37742019f44a3 | Shell | 117 | 5 | #!/usr/bin/env bash
bash ./build.sh
docker save transmorph_brain_mri_t1 | gzip -c > transmorph_brain_mri_t1.tar.gz
|
295464e9e567028bf4988db6d262730e8d9f9188042f16c0240275f9166cc3f1 | Shell | 118 | 2 | export PYTHONPATH=/root/workspace/QPSPP/QuantumProteinStructurePredictProject:$PYTHONPATH
python train.py --valkfold 4 |
2f51c076a2159fb77299d36a8b0903d931a22f703abf761d5587e36000bbea7a | Shell | 118 | 12 | #!/bin/sh
a=$1
if test "$a" = "" ; then
a=.
fi
b=0
d=""
if test -d $a/.svn ; then
b=`svnversion $a`
fi
echo "($b)"
|
5a3c72c2c3b0fc0a2926c832539d1b8b8d22b47c6a7d433b574e64fb52ce120c | Shell | 118 | 8 | #!/bin/bash
cd /local2/neuron_tracing_comparision/first2000/
for filename in `ls *zip`
do
unzip $filename
done
|
76833d7bf8aeae0052d97ec767bc661dabbd73b5a6edd7db5d5a6ad65a3c334a | Shell | 118 | 6 | #!/bin/bash
cd /global/homes/z/zhizhou/bigneuron/first2000/
for foldername in `ls *.zip`
do
unzip $foldername
done
|
80e0f0fb1df28f4053ba00cfb0bfe00cf7f2f0b46d0fffcb54d80dca43f33265 | Shell | 118 | 2 | export PYTHONPATH=/root/workspace/QPSPP/QuantumProteinStructurePredictProject:$PYTHONPATH
python train.py --valkfold 3 |
8952dbb6f34fff3dcbe21b3463183b090455602210398018f3babf55d199046c | Shell | 118 | 2 | export PYTHONPATH=/root/workspace/QPSPP/QuantumProteinStructurePredictProject:$PYTHONPATH
python train.py --valkfold 0 |
b30e0c68a832ac28e87eb5d2e3aeafd20316271f4995df77cac247d45f4358d5 | Shell | 118 | 2 | export PYTHONPATH=/root/workspace/QPSPP/QuantumProteinStructurePredictProject:$PYTHONPATH
python train.py --valkfold 1 |
ceeaf26035ea7e6ab3768b6906092a0302431fb3003b5bf0cc4ae1b8aa53ebef | Shell | 118 | 2 | export PYTHONPATH=/root/workspace/QPSPP/QuantumProteinStructurePredictProject:$PYTHONPATH
python train.py --valkfold 2 |
7759260399a038a82ff65191ea2c333a85e959616ab49c9c96fb9795968fcb08 | Shell | 120 | 2 |
scp -r tfu42@orcus1.cc.gatech.edu:/project/molecular_data/graphnn/mol_dqn_docking/chemgraph/docking_smilesvaluelst_* .
|
96e65396f92b32300ce80a731a1c013c75957ef9b8761e7f5000f6d03bf46ba5 | Shell | 122 | 6 | #!/bin/sh
conda activate pyscenic_dev
rm -rf dist/*
python setup.py sdist
python setup.py bdist_wheel
twine upload dist/*
|
0700d6197bcde90382a44d728a9602092549f700aa0a86bd393bf16e99617195 | Shell | 123 | 5 | #!/usr/bin/env bash
rm -rf dist
pip wheel --no-deps --wheel-dir dist ../..
DOCKERFILE=Dockerfile.dev docker compose build
|
4d674f52891c7060213d368120a90fad45288baa2909297b42a689f8b5956ec8 | Shell | 124 | 5 | echo "Installing required libraries"
conda env create -f env.yml
conda activate ecseg
echo "Successfully setup ecseg"
|
85f58039c9f8d2bb2bff2b756f65136379fb68a85376bfe6cd69bd8c0cb1c5d2 | Shell | 125 | 4 | #!/usr/bin/env bash
set -eu -o pipefail
CLUSTER_NAME="${K3D_CLUSTER_NAME:-k3s-default}"
k3d cluster delete "${CLUSTER_NAME}"
|
0e3e1a7c66a4c3465d81323a38ee10c0834598a31d5341a536addb6dd8e25f5e | Shell | 126 | 11 | #!/bin/bash
set -e
echo "Running black..."
black src
echo "Running isort..."
isort src
echo "Running flake8..."
flake8 src
|
65e57b1b903fc9f9127ebb3b754ee91f2e6441db8e4444a67f5f444323d88b38 | Shell | 126 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
tools/pyslow5_tests.py "${input_dir}"/blow5/*.blow5 "${output_dir}" get_all_read_ids
|
2f92310acec3ecc9fee6286afddd0d9dedc03d70a1eb24ecefc5410d76bb03fd | Shell | 127 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
tools/find_and_get_fast5.py "${input_dir}/fast5" "${output_dir}" --get-column samples
|
9b2a89ca743f23bdde55987bee2261918c7e4a51b38b0d80ed4770538ede2558 | Shell | 127 | 6 | #!/bin/bash
echo 'Swapping x voxel order'
for f in $(find ./* -name '*.nii.gz'); do
fslswapdim $f -x y z $f
done
echo 'Done'
|
c155fc9f1ba168eb700b851ec9c4060db4eaab10887a9bdf3e490a4ef12ac975 | Shell | 127 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
./tools/find_and_get_pod5.py "${input_dir}/pod5" "${output_dir}" --get-column samples
|
92a9cf030dcc1e14fc1d10fddb7e63987ae96a78202aba12322756d792309744 | Shell | 128 | 4 | #!/bin/bash
# Build the conda package from this directory
cd "$(dirname "$0")"
conda-build -c anaconda -c conda-forge -c cfin .
|
0726f2b2a07d28810a79b6c9cd4587008fcaf300bb0deaf22b878363c6354d2c | Shell | 129 | 5 | # command
humann_renorm_table -i renorm_table-input.txt -n cpm -o renorm_table-output.txt
# output
# 1) renorm_table-output.txt
|
11cc52305ad68ea22cd0533fad3905b4ad155b1e75e3461d96fe8d7abde4cc0e | Shell | 131 | 10 | #!/bin/bash
SPECIMEN_NAMES_TXT=$1
for p in $(<$SPECIMEN_NAMES_TXT)
do
echo ${p}
bash run_patchseq_specimen.sh ${p}
done
|
0a3fa637224f253231ea296c1f72c677653de8748f82214e081a5c304e764242 | Shell | 132 | 7 | # download lastest LDSC
cd /home
git clone https://github.com/bulik/ldsc.git
cd /
# put ldsc on path
export PATH=$PATH:/home/ldsc
|
92cd83c92929c5f73a09caa299b69e55e956da4116ffcba8871f58157356ad26 | Shell | 133 | 2 | #!/bin/bash
$PYTHON setup.py install --single-version-externally-managed --record=record.txt # Python command to install the script. |
d61e18c467f15e0f0ce492b7844009e5b3c31b2e30c11d8b5644d4a1d5bb48c2 | Shell | 134 | 6 | #!/bin/bash
source activate seqkit
zcat {input} | seqkit rmdup --by-name | seqkit grep -p "/{readnum}" -v > {output}
gzip {output}
|
9f3b4fd59f6a1882ee333a824e847e6bd2f6ffdb5cbf611b2e153f3f8a1861e8 | Shell | 135 | 5 | # command
humann_strain_profiler -i strain_profiler-input.txt -m 1 -n 2
# output
# 1) s1-strain_profile.tsv
# 2) s2-strain_profile.tsv
|
f540a62da3b1353ee84a6974f81c19a2a5b4e795a8a2b84a47c8c0ce8164124d | Shell | 136 | 7 | WEBADDR=https://www.uniprot.org/uniprot
for i in {1..947}
do
ID=$(sed -n $i'p' ./ids.txt)
echo $ID
wget $WEBADDR/$ID'.fasta'
done
|
afd104e88b7db8fcd4df958e3a151ba04b6ce3be05aa05d9c44313247afe5f23 | Shell | 137 | 7 | WEBADDR=https://www.uniprot.org/uniprot
for i in {1..1733}
do
ID=$(sed -n $i'p' ./ids.txt)
echo $ID
wget $WEBADDR/$ID'.fasta'
done
|
c7dc857f64d68c8ea3b4f266a4412d0b2511481d554c174da805cde245d9afe7 | Shell | 137 | 6 | #!/bin/sh
set -e ${DEBUG:+-x}
echo >&3 "=> Run label-studio init..."
label-studio init -q >&3
echo >&3 "=> label-studio init completed." |
d5140de1c3422c448b4732ce77ffc3b821b7caa1ae749787f2b059c168ace749 | Shell | 138 | 3 | #!/bin/bash
docker-compose run -T linkchecker https://docs.greatexpectations.io/en/latest/ -o csv/utf_8 2> /dev/null > ge_docs_links.csv
|
7a4e433d6ce082af7522d2488d8d276081df99d0c72a881f16efa2e768bb8e89 | Shell | 139 | 7 | #!/bin/bash
RANDOMSEED=0
export PATH="./localcolabfold/.pixi/envs/default/bin:${PATH}"
colabfold_batch inputs.fasta ./outputs --msa-only |
319cbbb82cf35694162f6aa8e26a2739cae02cc1a11e810ec0e336f8278bc88b | Shell | 141 | 9 | # cd docs
if [ "$1" == "autogen" ]
then
PYTHONPATH=../ sphinx-autogen source/*.rst
else
make clean
make html
cp -r build/html/* .
fi
|
3c7094291a39b0f6f3abeffea3c1ccfca56ceb6b230f6074ec2aca3718818b06 | Shell | 141 | 9 | FILE=test.txt
if test -f "$FILE"; then
echo "$FILE exists."
exit 0
else
touch $FILE
echo "$FILE don't exists."
exit 1
fi |
a96c87bb8f6363456bad3dd8b274c65531e36d17fd066215462589c7741dbdb5 | Shell | 141 | 3 | sed -i.bak '/torch/d' ./requirements.txt
gcloud app deploy --project=egg-counting-336514 --quiet
mv -f requirements.txt.bak requirements.txt
|
b29074a141abc88221f1a9d8b9edbb189a4f5a0c6fab81b409fed2885b8d7e2f | Shell | 141 | 6 | #!/bin/bash
input_dir=$1
output_dir=$2
tools/pyslow5_tests.py "${input_dir}"/blow5/*.blow5 "${output_dir}" all_values --get-column samples
|
489a499106aa62005c1284873dad28e2251a3a0c3112a9c5c5de41411e32f023 | Shell | 144 | 9 | #!/usr/bin/env bash
cd ./databases/
mkdir -p spice_dataset
cd spice_dataset
wget https://zenodo.org/records/10975225/files/SPICE-2.0.1.hdf5
|
ccc21c144646bc2473c9b84df4767602f89222823ca7096aa5515776b5c28bb1 | Shell | 144 | 3 | #!/bin/bash
python postprocess_and_classify_generated.py --input_dir models/finetune_model_ref --output results/finetune_unique_classified.csv
|
f92cda07756e363f7461e3180438676579b4bc6089f8b1ce94c95224fd16620b | Shell | 144 | 10 | #!/usr/bin/env bash
set -eu -o pipefail
port=$1
pids=$(lsof -t -s TCP:LISTEN -i ":$port" || true)
if [ "$pids" != "" ]; then
kill $pids
fi
|
7320c37a00c86f08b6fa7f0af70ab6374ea938fdfe4d2ba5be14b5843c040669 | Shell | 145 | 6 | # ulimit -s 10m
# OMP_NUM_THREADS=10
# export OMP_NUM_THREADS
OMP_STACKSIZE=500m
export OMP_STACKSIZE
nohup ./dmc_parallel.out > log.log 2>&1 &
|
eff3812f72f391498adbf46aeeb2553c1bc4058e199c440991f0d75b3e3ac46f | Shell | 146 | 12 | #!/bin/sh
set -e
INSTALL_DIR=$1
MOD_DIR=$2
cd ${INSTALL_DIR}
echo "Building mod files"
rm -rf x86_64
nrnivmodl ${MOD_DIR} >nrnivmodl.log 2>&1
|
2f9972bdb3b76d93a517e5b73ec3d8d5aadaac17c773a8bf46cde34e5cb6442b | Shell | 148 | 16 | #!/bin/sh
set -eu
arch=$(uname -m)
case $arch in
x86_64)
echo amd64
;;
aarch64)
echo arm64
;;
*)
echo $arch
;;
esac
|
826aa5e1902e32a08e9f16e2570302e35fdb1ba20f1deaebc5b7cc318067e36c | Shell | 149 | 4 | # command
humann_rename_table -i rename_table-input.txt -n uniref50 -o rename_table-builtin_output.txt
# output
# 1) rename_table-builtin_output.txt
|
e1a5e541724cc221770fed6913b44ca848eeb9194612ccb92ad2a4cb4b1b2ce4 | Shell | 149 | 7 | #!/bin/sh
for filename in *.tex; do
basename=$(basename $filename .tex)
pdflatex "$basename.tex"
pdf2svg "$basename.pdf" "$basename.svg"
done
|
54e795db6cab1e667d20e54cfbc29979d07c93d7023522b2fc223b682fee59f5 | Shell | 150 | 4 | sudo pip install --upgrade pip
sudo pip install -r requirements.txt
echo "bash shell/lint.sh" > .git/hooks/pre-commit
chmod a+x .git/hooks/pre-commit
|
d1cd84e426f9c9b0c5e91049aa47df81ab32f580b5174b9e05f5649a945ce820 | Shell | 150 | 4 | # command
humann_rename_table -i rename_table-input.txt -n rename_table-names.txt.gz -o rename_table-output.txt
# output
# 1) rename_table-output.txt
|
8b5038ebad4a98a7d6eae6b8d52366340f800d82572668aae8ceb15675ddb86b | Shell | 154 | 6 | #!/bin/bash
# Copy data from google bucket
# gsutil -m rsync -r ../data/ gs://gene_features/data/
gsutil -m rsync -r gs://gene_features/data/ ../data/
|
a2a21f9b9fb3c3f2fe11a054b8aa2b09668ee75811d1f962700ae61c55d04396 | Shell | 154 | 5 | mkdir ~/.ros
wget https://github.com/isl-org/MiDaS/releases/download/v2_1/model-small-traced.pt
cp ./model-small-traced.pt ~/.ros/model-small-traced.pt
|
48084caa6a1d8af4e5d4f40d9764a722faeff7fd8c8edc91738ac6d92d4ab82a | Shell | 155 | 7 |
THEANO_FLAGS="device=gpu0,floatX=float32" python train.py \
--emb ../preprocessed_data/restaurant/w2v_embedding \
--domain restaurant \
-o output_dir \
|
fb6bf0b9908e9ce397fc199a5bfbe8b3fe8c9a4884102763a3a052dec9a660f8 | Shell | 155 | 9 | #!/bin/sh
# Mac os x intermediate between applescript and idraw
echo -e "\033]0;idraw\007"
IDRAW="${NRNHOME}/../iv/x86_64/bin/idraw"
cd
"${IDRAW}" "$@"
|
d606aacfb1d6686fc5f0825893b07b8b6bc41a1ab68731dee4034d7ac0f165dd | Shell | 156 | 4 | #!/usr/bin/env bash
set -eu
. hack/k8s-versions.sh
printf 'This version is tested under Kubernetes %s and %s.' "${K8S_VERSIONS[min]}" "${K8S_VERSIONS[max]}" |
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