sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
abbe6c0386dd8fb98aee14d00fb8f6150a9950bef0b02c55b86b3a02e0e7084e | Shell | 790 | 23 | #!/bin/bash
#$ -q iblm.q
#$ -V
#$ -cwd
#$ -o /iblm/netapp/data1/jezhou/out
#$ -e /iblm/netapp/data1/jezhou/err
atac=$HOME/rat_snatacseq_analysis/get_combined_peak_mtx/data/rds/full_cocaine_dataset_with_naive_rn6/harmony_with_predicted_id.rds
rna=$HOME/rat_snrnaseq_pipeline/rpca/out/subset/integrated_relabeled_inhneuro... |
b0a162bb5bff6a4ff1e0d74521cb86b1115dfdd4703ad2c45b510cc5746fda96 | Shell | 790 | 26 | #!/bin/sh
# This script analyzes subject data in ~/MATLAB/DATA/Avgusta for each task
# The SGE_TASK variable specifies the data sets, as in $HOME/test.qsub
cd /home/knight/hoycw/PRJ_Error/scripts/
# define where the datasets are located
#PRCSDATADIR="/home/knight/hoycw/PRJ_Error/data/"
# don't change this variable
#... |
d91503b18052ad17804923e9e5b5c4c7480612cc514dafb3f7dd757e6a801533 | Shell | 790 | 10 | #PBS -l walltime=23:59:00
#PBS -l select=1:ncpus=1:mem=16gb
#PBS -J 1-1000
module load anaconda3/personal
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY_INDEX 4 0 21
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY... |
f6b2cdfc783bc31b0a4f7fd7e2e855275db662a08d57992e54fa043a40c4f9f6 | Shell | 790 | 10 | #PBS -l walltime=23:59:00
#PBS -l select=1:ncpus=1:mem=16gb
#PBS -J 1-1000
module load anaconda3/personal
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY_INDEX 2 0 21
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY... |
ff59046cf9f3dbba98a5025d578de1376a5ccd051451f673ad8352ae2241bfc6 | Shell | 790 | 10 | #PBS -l walltime=23:59:00
#PBS -l select=1:ncpus=1:mem=16gb
#PBS -J 1-1000
module load anaconda3/personal
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY_INDEX 1 0 21
python run_AutX_pulses_false_fully_connected_scale10E3_rfmix_gnomix_maxanc_onlyfemales.py $PBS_ARRAY... |
6cca214d5e96fc8f86c53c787fcb7b136f3f199c0932f7542b248c3e1d1d31c8 | Shell | 791 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_20%_fall' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint/$... |
8b3427ee8a10d998995beed35e280398d29dc3708b4981a50f1d3aa20befaa85 | Shell | 791 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_fall' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint/$... |
91c842ab6197f95a67faf15e3eddeb8c15cf4b6cd0f23b788ea2b95287f11af2 | Shell | 792 | 23 | #! /usr/bin/bash
#SBATCH -o /cellar/users/dlaub/projects/ML4GLand/EUGENe_paper/scripts/out/%A_%a_%x.out
#SBATCH -e /cellar/users/dlaub/projects/ML4GLand/EUGENe_paper/scripts/err/%A_%a_%x.err
#SBATCH -p carter-compute
#SBATCH -c 2
#SBATCH --mem 32G
wdir=/cellar/users/dlaub/projects/ML4GLand/EUGENe_paper/scripts/train... |
9d9c48482604ff3684fa33ac959bb170094dcd92c395eb3c010c80e9f6d7ff96 | Shell | 792 | 19 | #!/bin/bash
#SBATCH --job-name=natsound_regressions_l21
#SBATCH --output=output/%x_%A_%a.out
#SBATCH --error=output/%x_%A_%a.err
#SBATCH --mem=16000
#SBATCH --array=0-11
#SBATCH --cpus-per-task=8
#SBATCH --time=24:00:00
#SBATCH --partition=mcdermott
module add openmind/miniconda/2020-01-29-py3.7
module add openmind/cu... |
a2b056697f95265e1ef6d5da5eb876d166ec7b59a00bd45295ecf9bcb791b30a | Shell | 792 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=9:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094
#SBATCH --partition=mcde... |
aba62244cc36aab5581ea5cab375dd569d333f8146f8c98931ea132ec3ccadb8 | Shell | 792 | 19 | #!/bin/bash
#SBATCH --job-name=natsound_regressions_l21
#SBATCH --output=output/%x_%A_%a.out
#SBATCH --error=output/%x_%A_%a.err
#SBATCH --mem=16000
#SBATCH --array=0-12
#SBATCH --cpus-per-task=8
#SBATCH --time=24:00:00
#SBATCH --partition=mcdermott
module add openmind/miniconda/2020-01-29-py3.7
module add openmind/cu... |
ac0bac2f389bb905ad0bf517ad889f92b8624d434e852d2825b55908f2e7f3f5 | Shell | 792 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=9:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=1-5
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094
#SBATCH --partition=normal... |
33f2225aef539844cca6bd8b75d3ab55759a02976ce1331e9e2e273c97f39d0b | Shell | 793 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
c12ecc655e631fea956c706593dc9991d39e609bec22ea8e9723fe03fef2b468 | Shell | 794 | 20 | #!/bin/bash
#SBATCH --job-name=met_vgg19
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=4:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
module add ope... |
c1c13fc7eede13aa92aba4ec6166801fb44b5bb4248b9f319a6c8b9717e105f8 | Shell | 794 | 42 | #!/bin/bash
# Post-process UKB diffusion data using our pipeline
#
# Author: Ivan I. Maximov
# version 1.0
# 30.01.2019
#SBATCH --account=p33_norment
#SBATCH --time=1:00:00
#SBATCH --job-name=BAYES
#SBATCH --cpus-per-task=1
#SBATCH --mem-per-cpu=16G
module load FSL/6.0.7.2
source ${FSLDIR}/etc/fslconf/fsl.sh
module ... |
63f7f5815101a7e054aaa4c31c8d2f0b853f24568457d15d97ddbcc2feaac49e | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_summer' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
6d8a47fe38fd17fc6ae56c22d278d72b17cd451e9f7d8bc2e1ff00b922905fbf | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_20%_spring' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
9240dad28e0ff64ea2c3a43de68b21e8ab529a100e83d09bf6c33eeb6f70c126 | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_winter' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
a0b5585cd2d32f2fb9aabc48107301d91d653f35306de4fd05a40ddc67c710f0 | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_spring' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=50
NITER_DECAY=50
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
a3de7ba83ef077e6f0ca7771c040ad3f2bfba758c5facabd2e16a9f9d10b45dc | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_20%_winter' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
c8153c89cf7eb41e251ea8f268bdd0419c0b72b9050a3eeb99521f8f6cc1af7b | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_spring' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=1
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
d12995bfa84d69e7da568843244247e323621fd25638f4dda84230686a9faee8 | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_20%_summer' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=40
NITER_DECAY=40
# training
GPU_ID=0
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
eb6f6f212940ea6cd4a52a33d86f0dd1c604d60ef7012ba1bd48a815a51b6186 | Shell | 795 | 34 | set -ex
MODEL='bicycle_gan'
# dataset details
CLASS='combined_SEN1_2_10%_spring' # facades, day2night, edges2shoes, edges2handbags, maps
NZ=8
NO_FLIP='--no_flip'
DIRECTION='AtoB'
LOAD_SIZE=256
CROP_SIZE=256
INPUT_NC=3
NITER=50
NITER_DECAY=50
# training
GPU_ID=1
DISPLAY_ID=$((GPU_ID*10+1))
CHECKPOINTS_DIR=./checkpoint... |
9ed99e43e6277fbbb858225d356e6838ac171be474ab319671be663d4e162249 | Shell | 796 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 6
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#set paths
data_dir=/gladstone/bioinformatics/adnetworksppg/Project... |
7ab158955d4c6a867fadeb516daf2c9d99a5c001b4ac123255ede7d90fbb2a02 | Shell | 797 | 36 | IPIPATH=<Complete with i-pi path>
lmp=<Complete with lammps path>
HOST=$(hostname)
NTIME=36000
echo {"init",$( date -u)} >>LIST
grep '<step>' RESTART >> LIST
######### CHECK RESTART FILE ###############
if [ ! -f "RESTART" ]
then
cp input.xml RESTART
fi
######### CHECK RESTART FILE ###############
# Run the ... |
5159663e005002e05e3a046f64c3bf81523dc9da2eec0cf656172ae42b753a76 | Shell | 798 | 20 | #!/bin/bash
#SBATCH --job-name=met_alexnet
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --dependency=after:19718639
#SBATCH --constraint=high-capacity
#SBATCH --partition=normal
module add... |
b7743cdffa7033c285d1d75c0e0cf3e60e8f2ce0af7a70acaf31ac5dc39c765a | Shell | 799 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
31115528fb35b10259ccc8d2d7ce1bfbde9ba30ba1e892bea6a2e4607f0b9413 | Shell | 800 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50l23
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=4:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
module a... |
38397d4282edf4f17871b49b1a6f8bd97dc3ce5a6def41b4528ac491e4ddae2d | Shell | 800 | 21 | # install dependencies
apt-get update
apt-get install -y --no-install-recommends unzip
# clone the PNET git repository and change `pipeline/one_split.py` and
# `train/run_me.py` to allow selection of random seeds
git clone https://github.com/marakeby/pnet_prostate_paper.git
git -C pnet_prostate_paper checkout -b pnet-... |
46aafc483bfec6d2a0ada399e441232824ec90b5d3517f86a773e879e7dbf9f1 | Shell | 800 | 17 | #!/bin/sh
set -e
TEST=$(mktemp)
TEST_EXTRA_CLASSES=$(mktemp)
pytest --collect-only --ignore=test/functional lib/galaxy_test/ $(find test/ -mindepth 1 -maxdepth 1 -type d) > "$TEST"
pytest -o python_classes='Test* *Test *TestCase' --collect-only --ignore=test/functional lib/galaxy_test/ $(find test/ -mindepth 1 -maxde... |
e7322573cd1232b5780f8d87890be3e0ae4733198d67e0eb421349f01eb7ab91 | Shell | 800 | 31 | #!/bin/bash
cd $(dirname $0)
cd ..
source ~/.bashrc
source ./scripts/utils.sh
root_path="../../../.."
export PYTHONPATH="$(pwd)/$root_path/":$PYTHONPATH
export CUDA_VISIBLE_DEVICES=0
### download demo data
wget https://baidu-nlp.bj.bcebos.com/PaddleHelix/datasets/compound_datasets/demo_zinc_smiles.tgz
tar xzf demo_z... |
a97bd29cd754435b380b1ca132a3f6282a83ef8a754b88f1c00ff74a892f801d | Shell | 801 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=80G
#$ -l scratch=50G
#$ -l h_rt=08:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
4283ae8d943affd5defd3c5248f274064da486462bbe709544b953a02fceff79 | Shell | 802 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50linf4
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
module... |
6f86576b80375d87b58e3d0be82cfc5b92c5ad56e2600a561f14a4b7f7c569bd | Shell | 802 | 29 | #!/bin/sh
set -xe
ldc93s1_dir="./data/smoke_test"
ldc93s1_csv="${ldc93s1_dir}/ldc93s1.csv"
if [ ! -f "${ldc93s1_dir}/ldc93s1.csv" ]; then
echo "Downloading and preprocessing LDC93S1 example data, saving in ${ldc93s1_dir}."
python -u bin/import_ldc93s1.py ${ldc93s1_dir}
fi;
# Force only one visible device be... |
998bb0ebe942981b265229108f9a2cec0d53dc2435f248171169c7ec7fd683d8 | Shell | 802 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50linf8
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=4:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
module... |
cfbef106e1f1cbb6a011580a56cc38b28da17eb88e1d0bbb008e8d3bb8dc2f32 | Shell | 802 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50linf8
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
module... |
f3120179b3ed71d57cc08f8514b9883dce3427749878135e897950b43c7dedb9 | Shell | 802 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node097,node098
#SBATCH ... |
0735a2d4fde0f411b41795b8051e5863bbc141725e6d3f7012b8575ddc33ad73 | Shell | 803 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50l2rand
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=4:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node040
#SBATCH --partition=normal
modul... |
24ff74079bc725d98e16ff714b55cbdc5e56756d9d01d01e113a8e7cd563bf90 | Shell | 803 | 21 | sbatch --wait << EOF
#!/bin/bash
#SBATCH -o logs/%j.job
#SBATCH -e logs/%j.job
#SBATCH -J BERT-RBP-snakemake
# #SBATCH --exclude=supergpu02pxe,supergpu03pxe,supergpu05,supergpu07,supergpu08
#SBATCH -p gpu_p
#SBATCH --gres=gpu:1
#SBATCH --qos=gpu
#SBATCH -c 4
#SBATCH --mem=15G
#SBATCH -t 16:00:00
#SBATCH --nice=10000
... |
0c1e8733b4d3a9556b7cc876874aeea64154d073ad56467ff2a180a74f20544a | Shell | 804 | 21 | sbatch --wait << EOF
#!/bin/bash
#SBATCH -o logs/%j.job
#SBATCH -e logs/%j.job
#SBATCH -J BERT-RBP-snakemake
# #SBATCH --exclude=supergpu02pxe,supergpu03pxe,supergpu05,supergpu07,supergpu08
#SBATCH -p gpu_p
#SBATCH --gres=gpu:1
#SBATCH --qos=gpu
#SBATCH -c 4
#SBATCH --mem=32G
#SBATCH -t 32:00:00
#SBATCH --nice=10000
... |
e41d4e78b140eab40155d94243d0838180304582e879de01df491c891fef4a2a | Shell | 804 | 20 | #!/bin/bash
#SBATCH --job-name=met_alexnet
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --partition=normal
#SBATCH --exclude=node093,node040,node094
modu... |
29fd45e2b55361326ac1f3350c5bd16b14c8e9118e7fe1b9f08d98df6b4c315b | Shell | 806 | 9 | #PBS -l walltime=71:59:00
#PBS -l select=1:ncpus=32:mem=124gb
#$ python3 gnomix.py <query_file> <output_folder> <chr_nr> <phase> <genetic_map_file> <reference_file> <sample_map_file>
module load anaconda3/personal
path_genetic_map="/rds/general/project/human-popgen-datasets/live/HGDP_1000g/gnomix"
path_gnomix="/rds/gen... |
24a15ca3f544eea38f2930c5e5d60e6d633ef3420adeff2267a5137a3a5750b5 | Shell | 807 | 35 | #!/bin/bash
set -xe
arm_flavor=$1
source $(dirname "$0")/tc-tests-utils.sh
source $(dirname "$0")/tf_tc-vars.sh
BAZEL_TARGETS="
//native_client:libdeepspeech.so
"
if [ "${arm_flavor}" = "armeabi-v7a" ]; then
LOCAL_ANDROID_FLAGS="${BAZEL_ANDROID_ARM_FLAGS}"
fi
if [ "${arm_flavor}" = "arm64-v8a" ]; then
LO... |
b238b6cf5bfa9eed2a7d2ca219fb590e5531d7955efdd1f67d72c6d5c2c30263 | Shell | 807 | 35 | #!/bin/bash
set -xe
arm_flavor=$1
source $(dirname "$0")/tc-tests-utils.sh
source $(dirname "$0")/tf_tc-vars.sh
BAZEL_TARGETS="
//native_client:libdeepspeech.so
//native_client:generate_scorer_package
"
if [ "${arm_flavor}" = "armeabi-v7a" ]; then
LOCAL_ANDROID_FLAGS="${BAZEL_ANDROID_ARM_FLAGS}"
fi
if [ "${a... |
58dadbc47589005dad943094794eb8ec276d67cfed601aa45b44c9b436ea9a12 | Shell | 808 | 24 | #!/bin/bash
BAM_DIRECTORY=$1
OUT_DIRECTORY=$2
MITOCALC_DIRECTORY=$3
## 1. Telomere length (assuming conda is already installed)
### install telseq
conda install -c bioconda telseq
### create bam file list
ls $BAM_DIRECTORY/*.bam > $BAM_DIRECTORY/telseq_bamlist.txt
### run telseq (one file for all samples)
telseq -f $... |
c3c952da8c63feb7c0d6cdffc210e83aa48881e147b9dd901c6cc33b99e7fb75 | Shell | 808 | 25 | #!/bin/sh
set -e
# Linux wheels are built inside manylinux2014 containers managed by cibuildwheel.
python -m pip install --upgrade pip cibuildwheel twine build
export CIBW_BUILD="cp310-* cp311-* cp312-* cp313-* cp314-*"
export CIBW_SKIP="*-musllinux_*"
export CIBW_MANYLINUX_X86_64_IMAGE="manylinux2014"
export CIBW_MA... |
f8f3138029554b10cec67439bb8812b329bd0e3155bcd3f3b33aa74316f2af63 | Shell | 809 | 21 | #!/bin/bash
#SBATCH --mail-user=alanxu@usc.edu
#SBATCH --mail-type=ALL
#SBATCH --ntasks=1
#SBATCH --nodes=1
#SBATCH --cpus-per-task=10
#SBATCH --time=48:00:00
#SBATCH --mem=60GB
#SBATCH --account=bbenayou_34
#SBATCH --partition=oneweek
# Author: Alan Xu
# This script uses TEtranscripts 2.2.1 to generate the count matr... |
fa34963a0a72ce7643458d9a2aa74546e638c40a1be85956eb1e6b8ab0259906 | Shell | 809 | 21 | #!/bin/bash
#SBATCH --mail-user=alanxu@usc.edu
#SBATCH --mail-type=ALL
#SBATCH --ntasks=1
#SBATCH --nodes=1
#SBATCH --cpus-per-task=10
#SBATCH --time=48:00:00
#SBATCH --mem=60GB
#SBATCH --account=bbenayou_34
#SBATCH --partition=oneweek
# Author: Alan Xu
# This script uses TEtranscripts 2.2.1 to generate the count matr... |
5ae3aeefa0b943e98fcfac445402c29ef1bb8aa7e8546f08cae33f980a95a973 | Shell | 810 | 21 | #!/bin/bash
###########################################
######## transfer from Lane to SCI ########
LANEDIR=/projects/pfenninggroup/singleCell/Logan_BU_Striatum_snRNA-seq
SCI_DIR=badoi.phan3-umw@hpc.umassmed.edu:/pi/ryan.logan-umw/badoi
LANEDIR1=bnphan@lanec1.compbio.cs.cmu.edu:/projects/pfenninggroup/singleCell/Log... |
76e22b59b07016a686a31ca36e48b06d976cc8a83654f5cfb255aff4ae8a9c63 | Shell | 810 | 46 | #!/bin/bash
#SBATCH --time=0-10:00:00
#SBATCH --mem-per-cpu=8000 # 8000MB of memory
#SBATCH --array=0-47
#SBATCH --output=./slurm_logs/slurm-%A_%a.out
if [ -z "$MRI_DIR" ]
then
echo "MRI_DIR not set, exiting"
exit 1
fi
if [ -z "$SUBJECTS_DIR" ]
then
echo "SUBJECTS_DIR not set, exiting"
exit 1
fi
echo "M... |
a40405de5f52d64d45f1f84a05d0c72cdcfb1827bc5ebacfa589fc423da7e862 | Shell | 810 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node097,node098,node037
... |
1a45d0cad42fe09dcee13819bff06664ba688d0f711bf04341c9e87e275da1ea | Shell | 811 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
adf1f770ce0ce98b1d63ec5edee0f1f45d8f171c5d4995a607823dfcc09738bf | Shell | 812 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node098,node097,dgx001
#... |
c534300631846d464929a777b77c6bbf23f515a06e58e7a11cc18d733c84ffc6 | Shell | 813 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=4:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --exclude=node093,node097,node094,node098
#SBATCH --partition=nor... |
030db3d429632b3cdcdd40969bbb869251eb1f5cf30e14e41357ba5554fb4ac8 | Shell | 816 | 21 | #!/bin/bash
#SBATCH --mail-user=alanxu@usc.edu
#SBATCH --mail-type=ALL
#SBATCH --ntasks=1
#SBATCH --nodes=1
#SBATCH --cpus-per-task=10
#SBATCH --time=48:00:00
#SBATCH --mem=60GB
#SBATCH --account=bbenayou_34
#SBATCH --partition=oneweek
# Author: Alan Xu
# This script uses TEtranscripts 2.2.1 to generate the count matr... |
f25e18115256e8f0e02d408e3cdfe1f785abf5878eba8c8bcc4e87ce257f1f58 | Shell | 816 | 21 | #!/bin/bash
#SBATCH --mail-user=alanxu@usc.edu
#SBATCH --mail-type=ALL
#SBATCH --ntasks=1
#SBATCH --nodes=1
#SBATCH --cpus-per-task=10
#SBATCH --time=48:00:00
#SBATCH --mem=60GB
#SBATCH --account=bbenayou_34
#SBATCH --partition=oneweek
# Author: Alan Xu
# This script uses TEtranscripts 2.2.1 to generate the count matr... |
8e49463c79eaf7199bbac3031b50ccd650eba5bde5f74c7960bc80882e92bfeb | Shell | 818 | 26 | #!/bin/sh
# This script analyzes subject data in ~/MATLAB/DATA/Avgusta for each task
# The SGE_TASK variable specifies the data sets, as in $HOME/test.qsub
cd /home/knight/hoycw/PRJ_Error/scripts/
# define where the datasets are located
#PRCSDATADIR="/home/knight/hoycw/PRJ_Error/data/"
# don't change this variable
#... |
8ed0aa594b72e2df91e6f7edce94e3bb10f239e4a1917a7241f884ba497326ba | Shell | 818 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node097,node098,node038,... |
9c30f11abff4c7d3f04fd42206de4774919f17b3d0f1b79e461b4ae9afda9477 | Shell | 819 | 21 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node097,node098,node038,... |
29427581cce14009722aa2025e3ff4afeeb5be04b483bb54b7d8346231075718 | Shell | 820 | 20 | #!/bin/bash
#SBATCH --job-name=met_alexnet
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --partition=normal
#SBATCH --exclude=node093,node040,node094,node0... |
69bd67ec8aa87b1b682e87b447f857dc5f2eb74810fa1cceecc3bc8983293ad6 | Shell | 820 | 20 | #!/bin/bash
#SBATCH --job-name=met_alexnet
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity
#SBATCH --partition=normal
#SBATCH --exclude=node093,node040,node094,node0... |
cdfe6e2c425e420cbae76dfae82789c87bbf108a9bbf965b3e3ac53803c3fffb | Shell | 820 | 9 | #PBS -l walltime=71:59:00
#PBS -l select=1:ncpus=64:mem=300gb
#$ python3 gnomix.py <query_file> <output_folder> <chr_nr> <phase> <genetic_map_file> <reference_file> <sample_map_file>
module load anaconda3/personal
path_genetic_map="/rds/general/project/human-popgen-datasets/live/HGDP_1000g/gnomix"
path_gnomix="/rds/gen... |
ac936b01711df464c1f1a414c721d257e091d40552e50681329b10eb0d17e3a8 | Shell | 821 | 48 | #!/bin/bash
set -xe
source $(dirname "$0")/all-vars.sh
source $(dirname "$0")/all-utils.sh
source $(dirname "$0")/asserts.sh
bitrate=$1
set_ldc_sample_filename "${bitrate}"
model_source=${DEEPSPEECH_PROD_MODEL}
model_name=$(basename "${model_source}")
model_source_mmap=${DEEPSPEECH_PROD_MODEL_MMAP}
model_name_mmap=... |
9fa6b6b4e28faa9b60950e52c46ed95d13bfc459ad8472dcf6fbe1e89e3e95b4 | Shell | 823 | 18 | #!/bin/bash
# https://slurm.schedmd.com/sbatch.html
#SBATCH --partition=priority # Partition (queue)
#SBATCH --time=5:00:00 # Runtime in D-HH:MM format
#SBATCH --job-name=seurat # Job name
#SBATCH -c 1 # cores
#SBATCH --mem=50G # Memory needed per CPU or --mem
#SB... |
3160e0dc6b2101b132518411c48e2d0c9ffc161fbc1419a150188ed6f75c4f6e | Shell | 824 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
7540d20185f7180338cf1ba453782b7aa401b59b2ad25776524362a3f7fac3dd | Shell | 824 | 28 | #! /bin/sh
#
# Run this script in the top source directory of HDF4 to regenerate
# all of the necessary files.
#
# This is a helper script to regenerate the aclocal.m4, h4config.h.in,
# Makefile.in, and configure files all in one go. The versions for the
# tools need to be according to this table or better:
#
# N... |
f170ff9a2ed3cb4a8bb47579465326a71075ae3b62ae4284eabe70e73be9e634 | Shell | 824 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=50G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
05db8501a6b8671af1387acc61b6b7b2618e111b68aab0f4cdb45bfe25907ac0 | Shell | 826 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=80G
#$ -l scratch=50G
#$ -l h_rt=02:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
2be6710e5244fc15579387b487b4ebaca5c3c34283fc2540dd21658c79ee872a | Shell | 827 | 41 | #!/bin/bash
#SBATCH --time=0-00:60:00
#SBATCH --mem-per-cpu=8000 # 8000MB of memory
#SBATCH --array=0-4
#SBATCH --output=./slurm_logs/slurm-%A_%a.out
if [ -z "$SUBJECTS_DIR" ]
then
echo "SUBJECTS_DIR not set, exiting"
exit 1
fi
echo "SUBJECTS_DIR set as $SUBJECTS_DIR"
temp=$SUBJECTS_DIR
module load teflon
mo... |
4b004cd241066ad183a5cd5bec964448bf82c8fd203339ff9ff82499a16cbf97 | Shell | 828 | 22 | #!/bin/bash
#$ -cwd
#$ -o /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -e /gladstone/bioinformatics/adnetworksppg/Project_1_Huang/NK01/tmp/log/
#$ -pe smp 1
#$ -l mem_free=80G
#$ -l scratch=50G
#$ -l h_rt=03:00:00
#$ -j yes
#$ -P neuroppg
#set paths
data_dir=/gladstone/bioinformatics/adnetw... |
a12ce0e99f47d5068dd1250335da164e10d8e61aede7025cfe04682b99301b64 | Shell | 828 | 20 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=5:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint="high-capacity&11GB"
#SBATCH --exclude=node093,node040,node094,node097,node098,node038,... |
d48aa5c8debe09c18bc106d6fa3b7249ec4316eb151a271a5c6d019fe0b82792 | Shell | 830 | 12 | #!/bin/bash
docker run \
--rm -it \
-v $PWD:/pnet_robustness \
-v $PWD/pnet_data/mounted/mutations.csv:/app/pnet_prostate_paper/_database/prostate/processed/P1000_final_analysis_set_cross_important_only.csv \
-v $PWD/pnet_data/mounted/cnvs.csv:/app/pnet_prostate_paper/_database/prostate/processed/P1000_data_CN... |
25e2014e5b4dc1914deef80c2b15850d134cd69bf33d8fb4c5f6df17ce6da52e | Shell | 831 | 28 | #!/bin/bash -ve
#######################################################
## Run Trinity to Generate Transcriptome Assemblies ##
#######################################################
if [ -z ${TRINITY_HOME} ]; then
echo "Must set env var TRINITY_HOME"
exit 1
fi
${TRINITY_HOME}/Trinity --seqType fq --max_me... |
c4b2b033550cee190415a6cbc724d5a68a0058955a264bb6dadf17054d4a7416 | Shell | 831 | 31 | set -ex
# models
RESULTS_DIR='results/combined_sar2opt'
# dataset
CLASS='combined_sar2opt'
DIRECTION='AtoB' # from domain A to domain B
LOAD_SIZE=286 # scale images to this size
CROP_SIZE=256 # then crop to this size
INPUT_NC=3 # number of channels in the input image
# misc
GPU_ID=0 # gpu id
NUM_TEST=587 # number ... |
c7ca2b0252413144fce087023f16309dbbb3b0feeb625497d38338af27c7c421 | Shell | 831 | 26 | #!/bin/sh
# This script analyzes subject data in ~/MATLAB/DATA/Avgusta for each task
# The SGE_TASK variable specifies the data sets, as in $HOME/test.qsub
cd /home/knight/hoycw/PRJ_Error/scripts/
# define where the datasets are located
#PRCSDATADIR="/home/knight/hoycw/PRJ_Error/data/"
# don't change this variable
#... |
e04e843aed2f587b72c0e7846b3a15f6fe6da7839abb7377fea01162d4819d63 | Shell | 831 | 33 | #!/bin/bash
set -xe
source $(dirname "$0")/tc-tests-utils.sh
unset PYTHON_BIN_PATH
unset PYTHONPATH
export PATH="${PYENV_ROOT}/bin:$PATH"
install_pyenv "${PYENV_ROOT}"
install_pyenv_virtualenv "$(pyenv root)/plugins/pyenv-virtualenv"
for pyver_conf in ${SUPPORTED_PYTHON_VERSIONS}; do
pyver=$(echo "${pyver_conf}... |
7882520083198883950b23d38ae7feb2dbbf9302e20e981a68607097942c2f9e | Shell | 832 | 27 | #!/bin/bash
#$ -q iblm.q
#$ -V
#$ -cwd
#$ -t 1-10
#$ -o /iblm/netapp/data1/jezhou/out
#$ -e /iblm/netapp/data1/jezhou/err
wd=$HOME/rat_snatacseq_analysis/coembed
celltype=`awk -v line=$SGE_TASK_ID 'NR==line' $wd/fimo_celltypes.txt`
bfile=${wd}/fimo/${celltype}_peak_seqs/all_peak_seqs_markov_bg.txt
motifs=${wd}/fimo/${... |
01e1b2e678d444cd3c379637ba1344b2fcf750a882646f83e26d1c2616f29497 | Shell | 835 | 21 | #!/bin/bash
#SBATCH --job-name=met_resnet50
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --constraint=high-capacity&11GB
#SBATCH --exclude=node093,node037,node098,node097,node075,node094
#S... |
03148f9e09535e6b8abcb3fbd4cdad7131df79ad17c02da2863286cb92c3882b | Shell | 835 | 42 | #!/bin/bash
TMPDIR=`mktemp -d`
mkdir -p $TMPDIR
OUTDIR=~/data/lpl/stdp
mkdir -p $OUTDIR
echo "Tempdir $TMPDIR"
trap 'rm -rf -- "$TMPDIR"' EXIT
# ln -s $TMPDIR/ out/
make
SIMTIME=200
LAMBDA=1
if [ "$1" != "" ]; then
MEAN=$1
else
MEAN=20
fi
if [ "$2" != "" ]; then
SIGMA2=$2
else
SIGMA2=0.1
fi
if [ "$3" != "" ... |
4864c1790389613013272d92800e622a174d196dfaf8302cf9c05e47656b53de | Shell | 836 | 27 | #!/bin/bash
#$ -q iblm.q
#$ -V
#$ -cwd
#$ -t 1-13
#$ -o /iblm/netapp/data1/jezhou/out
#$ -e /iblm/netapp/data1/jezhou/err
wd=$HOME/rat_snatacseq_analysis/coembed
celltype=`awk -v line=$SGE_TASK_ID 'NR==line' $wd/data/rds/full_cocaine_dataset_with_naive_rn6/celltypes_list.txt`
rds=$wd/data/rds/full_cocaine_dataset_with... |
80404885cf3439bcf4af4eae82e49130b51c234c61b2c7092341f483d5e8ef0a | Shell | 837 | 20 | #!/bin/bash
#SBATCH --job-name=met_alexnet_reduced_aliasing
#SBATCH --output=output/standard%A_%a.out
#SBATCH --error=output/standard%A_%a.err
#SBATCH --mem=4000
#SBATCH --time=3:00:00
#SBATCH --gres=gpu:1
#SBATCH --array=0-399
#SBATCH --exclude=node037,node093,node094,node098,node097
#SBATCH --constraint=high-capacity... |
caa28d4a97fcd44455b214501fb2c83945241585bf7ae0a022ca99054ea28ce9 | Shell | 837 | 41 | #!/bin/bash
test_hla_i=1
for hla_i in {2..85}
do
python sample_neg_tcrs_leave1out_match_train_valid.py \
--hla_class HLA_I \
--test_hla_i ${test_hla_i} \
--hla_i ${hla_i} \
--label leave1out_match \
--n_fold 5
done
test_hla_i=11
for hla_i in {1..10} {... |
11e846182167200ea4dc1bffabf9c06f59f61b203e72a2c4d7fbbd010f14a9d5 | Shell | 838 | 23 | #!/bin/bash
#SBATCH --job-name=null_cnet
#SBATCH --output=output/null_cnet.out
#SBATCH --error=output/null_cnet.err
#SBATCH --mem=16000
#SBATCH --cpus-per-task=4
#SBATCH --time=50:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=high-capacity
#SBATCH --array=0-4
#SBATCH --partition=normal
module add openmind/miniconda/... |
d9f82c5dfc8a4060a8e65b83aa13e42d895ee6bffb2363e29b3188b9fc5c7e68 | Shell | 839 | 26 | #!/bin/bash
echo "Updating bisweb source setup"
echo "---------------------------------------"
echo "1. update npm dependencies"
NV=`node -v | grep v10`
echo $NV
#if [ -n "$NV" ]; then
# echo "___ Not using node.js v12, no need for shrinkwrap file"
#else
# echo "___ Using node.js v12 or v14 -- adding shrinkwrap... |
5de7b32aeeba104089417d7fa5cdaa7109adb867823364ffd9a53ad583f2cc9f | Shell | 840 | 13 | #!/bin/sh
wget http://jmlr.csail.mit.edu/papers/volume5/lewis04a/a12-token-files/lyrl2004_tokens_test_pt0.dat.gz
gunzip lyrl2004_tokens_test_pt0.dat.gz
wget http://jmlr.csail.mit.edu/papers/volume5/lewis04a/a12-token-files/lyrl2004_tokens_test_pt1.dat.gz
gunzip lyrl2004_tokens_test_pt1.dat.gz
wget http://jmlr.csail.mit... |
fd3a19ca816756aa68ef9696e2b26fcf4874e0a209bafe5db85f5dae3d59f2a1 | Shell | 841 | 17 | #!/bin/bash
# path to the cell ranger script
cellranger_script=/gladstone/bioinformatics/projects/mn-1318-maxine-nelson-yadong-huang-snrnaseq-mm10-aug-2022/scripts/GB-MN-1318/03_cellranger_count/cellranger_count.sh
#make the results output directory
mkdir /gladstone/bioinformatics/projects/mn-1318-maxine-nelson-yadon... |
6ec7380a166c10f2af49d483df5cd0791c7559417cca3148d51bb34ca56cda92 | Shell | 842 | 30 | #!/bin/bash -ve
#######################################################
## Run Trinity to Generate Transcriptome Assemblies ##
#######################################################
if [ -z ${TRINITY_HOME} ]; then
echo "Must set env var TRINITY_HOME"
exit 1
fi
${TRINITY_HOME}/Trinity --seqType fq --max_me... |
ccc703d4b28c7a71d234871ef83da3c399eb248e068b00bd62218045cf42065c | Shell | 842 | 23 | #!/bin/bash
#SBATCH -n 1
#SBATCH -p fasse
#SBATCH --signal=USR2
#SBATCH --time=4-00:00:00
#SBATCH --account=somerville_lab
#SBATCH --job-name=hcp_adversity_normative_modeling
#SBATCH --cpus-per-task=10
#SBATCH --mem=40G
# Outputs ----------------------------------
#SBATCH -o /ncf/hcp/data/analyses/myelin/containers/log... |
46ccdb75ae774cada0d41c623224722a7418ed6992fed7ab57953b3a3f2602fc | Shell | 845 | 26 | #!/bin/sh
# This script analyzes subject data in ~/MATLAB/DATA/Avgusta for each task
# The SGE_TASK variable specifies the data sets, as in $HOME/test.qsub
cd /home/knight/hoycw/PRJ_Error/scripts/
# define where the datasets are located
#PRCSDATADIR="/home/knight/hoycw/PRJ_Error/data/"
# don't change this variable
#... |
d887a6d1eb2c229dbc620c4a95a6e2ed35506566c60c0fb14b50174532c8b37a | Shell | 845 | 23 | #!/bin/bash
#SBATCH --job-name=null_resnet50
#SBATCH --output=output/null_%A_%a.out
#SBATCH --error=output/null_%A_%a.err
#SBATCH --mem=16000
#SBATCH --cpus-per-task=4
#SBATCH --time=150:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=high-capacity
#SBATCH --array=0-4
#SBATCH --partition=normal
module add openmind/min... |
792fe23ceb7aea62f0b97d141b3b07f5e1c464f4e2cc8cc96d5f3b7e71f9c58e | Shell | 846 | 28 | #!/bin/bash -ve
#######################################################
## Run Trinity to Generate Transcriptome Assemblies ##
#######################################################
if [ -z ${TRINITY_HOME} ]; then
echo "Must set env var TRINITY_HOME"
exit 1
fi
${TRINITY_HOME}/Trinity --seqType fq --max_me... |
87e5b5f6a7a17aab4f12889de7c4290908aa8afc58347bdbe18d67d6837cd69d | Shell | 846 | 23 | #!/bin/bash
#SBATCH --job-name=null_resnet101
#SBATCH --output=output/null_%A_%a.out
#SBATCH --error=output/null_%A_%a.err
#SBATCH --mem=16000
#SBATCH --cpus-per-task=4
#SBATCH --time=150:00:00
#SBATCH --gres=gpu:1
#SBATCH --constraint=high-capacity
#SBATCH --array=0-4
#SBATCH --partition=normal
module add openmind/mi... |
aef64c3110d256fe8eb5d5cfc3e06c95fd3b0be2f16b21662ecb05e5e575131a | Shell | 846 | 26 | #!/bin/bash
# Usage: bash download_uniclust30.sh /path/to/download/directory
set -e
if [[ $# -eq 0 ]]; then
echo "Error: download directory must be provided as an input argument."
exit 1
fi
if ! command -v aria2c &> /dev/null ; then
echo "Error: aria2c could not be found. Please install aria2c (sudo apt i... |
1e046bf19ab456ba9c8acc2fcc3604d9b210473647887f620e6ec9a0b15862da | Shell | 848 | 50 | #!/bin/bash
if [ "$1" != "" ]; then
LAMBDA=$1
else
LAMBDA=1
fi
if [ "$2" != "" ]; then
PHI=$2
else
PHI=1
fi
if [ "$3" != "" ]; then
TAU=$3
else
TAU=600
fi
if [ "$4" != "" ]; then
SEED=$4
else
SEED=123
fi
make
EXPNAME='spiking'
SIMTIME=100000
ETA=1e-2
ZETA=1e-3
KAPPA=10
WEE=0.0
WEI=0.5
WIE=0.5
WII=0.4
TA... |
42339d52fbbd1c93d1fad11ef9db2a0351c043cdb57f9411dba4db0fedc094d2 | Shell | 850 | 48 | #!/bin/bash
set -xe
source $(dirname "$0")/all-vars.sh
source $(dirname "$0")/all-utils.sh
source $(dirname "$0")/asserts.sh
bitrate=$1
set_ldc_sample_filename "${bitrate}"
model_source=${DEEPSPEECH_PROD_MODEL//.pb/.tflite}
model_name=$(basename "${model_source}")
model_source_mmap=${DEEPSPEECH_PROD_MODEL_MMAP//.pb... |
f523e96e9df4b4a2c2acd2a54167d376b7126a34221d97a13dc97d4b7b930f64 | Shell | 850 | 26 | #!/bin/sh
# This script analyzes subject data in ~/MATLAB/DATA/Avgusta for each task
# The SGE_TASK variable specifies the data sets, as in $HOME/test.qsub
cd /home/knight/hoycw/PRJ_Error/scripts/
# define where the datasets are located
#PRCSDATADIR="/home/knight/hoycw/PRJ_Error/data/"
# don't change this variable
#... |
efa08d6451255319dc25037cce73950a48fb323c0359237fae9fddbc16ab4816 | Shell | 851 | 33 | #!/bin/bash
set -xe
source $(dirname "$0")/tc-tests-utils.sh
extract_python_versions "$1" "pyver" "pyver_pkg" "py_unicode_type" "pyconf" "pyalias"
bitrate=$2
set_ldc_sample_filename "${bitrate}"
model_source=${DEEPSPEECH_TEST_MODEL//.pb/.tflite}
model_name=$(basename "${model_source}")
model_name_mmap=$(basename "... |
19e1055ad94b52b32f1ca7d0a8169ffcb1a2e35a6f19078380388ab06447f744 | Shell | 852 | 49 | #!/bin/bash
if [ "$1" != "" ]; then
LAMBDA=$1
else
LAMBDA=1
fi
if [ "$2" != "" ]; then
PHI=$2
else
PHI=1
fi
if [ "$3" != "" ]; then
TAU=$3
else
TAU=600
fi
if [ "$4" != "" ]; then
SEED=$4
else
SEED=123
fi
make
EXPNAME='spiking_no_ei_plasticity'
SIMTIME=100000
ETA=1e-2
ZETA=1e-3
KAPPA=10
WEE=0.0
WEI=0.5
WI... |
31c72904ee12cc2d86f79b2c4ae4783f7b384f9dc572c0f482aca387f4b83d6c | Shell | 855 | 17 | ### aligned RNA-Seq data to genome. list: sample name list
#!/bin/bash
mkdir -p 02-read-align qc
cat list | while read i; do
path="/home/zhuby/RNA/no_reference/01-clean-data/ptep"
hisat2 -p 10 -x ./reference/Ptep/Ptep -1 ${path}/${i}_1.fastq.gz -2 ${path}/${i}_2.fastq.gz --new-summary --summary-fil... |
311385e2447156613eb87c6806a1bcb0a50950560042c7beb4df94751900483d | Shell | 859 | 49 | #!/bin/bash
if [ "$1" != "" ]; then
LAMBDA=$1
else
LAMBDA=1
fi
if [ "$2" != "" ]; then
PHI=$2
else
PHI=1
fi
if [ "$3" != "" ]; then
TAU=$3
else
TAU=600
fi
if [ "$4" != "" ]; then
SEED=$4
else
SEED=123
fi
make
EXPNAME='spiking'
SIMTIME=100000
ETA=1e-2
ZETA=1e-3
KAPPA=10
WEE=0.0
WEI=0.5
WIE=0.5
WII=0.4
TAU... |
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