sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
0fff7e03bd1dfa22bb344df2b749be1c2080be9c2a9ea75529d15b5747a08a74 | Shell | 2,668 | 48 | #!/bin/bash -x
SMC=$(which smc++)
TMP=$(mktemp -d)
set -e
$SMC vcf2smc -v example/example.vcf.gz $TMP/example.1.smc.gz 1 msp1:msp_0
$SMC vcf2smc -v example/example.vcf.gz $TMP/example.11.smc.gz 1 msp1:msp_1
$SMC vcf2smc -v example/example.vcf.gz $TMP/example.22.smc.gz 1 msp2:msp_3
$SMC vcf2smc -d msp_0 msp_0 example/ex... |
cd5b67cf69969309aa80e270a704e6bf0d087fb23dc3a08ae9676168b58616fc | Shell | 2,732 | 94 | DATA=/shared/sheng/coop_data/
mkdir -p $DATA
# DATA=/work/tianjun/few-shot-learning/prompt-moe/CoOp/data/
cd $DATA
# pip install gdown
mkdir -p caltech-101
cd caltech-101
# wget http://www.vision.caltech.edu/Image_Datasets/Caltech101/101_ObjectCategories.tar.gz
wget https://data.caltech.edu/records/mzrjq-6wc02/files... |
ada7e34513008d3d642a09df5d17b9995c32ef2449272ae3de8cb9fe47afd9a6 | Shell | 2,734 | 67 | #!/usr/bin/env bash
set -e
[[ -z ${HCPDIR} ]] && export HCPDIR=$OGREDIR/lib/HCP
[[ -z ${FSLDIR} ]] && export FSLDIR=/usr/local/fsl
if [[ -z ${FREESURFER_HOME} ]];then
echo " FREESURFER_HOME not set. Abort!"
exit
fi
#echo "This script must be SOURCED to correctly setup the environment prior to running any... |
1af0b158e706f23b1ab1a4d9c77188a6d9a526ca2ae57bb5a92fcb18eb19ace9 | Shell | 2,744 | 164 |
# Command to download dataset:
# bash script_download_all_datasets.sh
############
# ZINC
############
DIR=molecules/
cd $DIR
FILE=ZINC.pkl
if test -f "$FILE"; then
echo -e "$FILE already downloaded."
else
echo -e "\ndownloading $FILE..."
curl https://data.dgl.ai/dataset/benchmarking-gnns/ZINC.pkl -o ZINC.p... |
3b0594599c691c051de04dec9b26fdd877f67baf9c2efc032b209e88361ca2e1 | Shell | 2,749 | 117 | #! /bin/bash
## Run MALF with MCCV ##
# Directories
LIB_DIR="${MALF_HVR_DIR:?path of the MALF working directory}/lib_dorothee2"
TMP_DIR="${MALF_HVR_DIR:?path of the MALF working directory}/tmp/mccv8"
#QC_DIR="${MALF_HVR_DIR}/qc_mccv6"
OUT_DIR="${MALF_HVR_DIR:?path of the MALF working directory}/proc/mccv8/original"
... |
e51cc9e45f16aa2888ca8304738711dae8787f13f0af9d7b1c6f5a200ad073fe | Shell | 2,791 | 78 | #!/bin/bash
# Compile all REACHER firmware paradigms for every supported board.
# Requires: arduino-cli with arduino:avr board package installed.
#
# Usage: bash compile.sh
# Output: ../src/reacher/hex/<board>/<paradigm>.hex for each (paradigm, board)
# pair — the reacher package-data directory shipped in the ... |
7fd9deee402946c48b376c9c615bf3cb850c4e2b4d840fec7badf1e3fccf5d69 | Shell | 2,795 | 67 | #!/bin/bash
############
# Usage
############
# bash script_main_xxx.sh
############
# GNNs
############
# GatedGCN
##########################
# GraphTheoryProp - 4 RUNS
##########################
seed0=41
seed1=95
seed2=12
seed3=35
code=main_GraphTheoryProp_multitask.py
dataset=GraphTheoryProp
tmux new -s ... |
29752f7aa8c07a28f9f8dbdf624e780ff38cc62937e8f301ce156fe3672216be | Shell | 2,838 | 119 | #!/usr/bin/env bash
## Compare overlap similarity between segmentations:
## CNN and manual labels :: Validation datasets — ADNI & ICBM
## XCorrelation
set -ux
## HOME
HERE="${HVR_VALIDATION_DIR:-$(git -C "$(dirname "$0")" rev-parse --show-toplevel)}"
## FUNCTIONS
# Recode labels to L-HC: 1 & R-HC 2
recode() {
loca... |
3bb5c144fcd8b26c7effda0734ff3cd510ecadde3364fa1110c68b46d80c6aa2 | Shell | 2,860 | 102 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-ebb87293" #extract
#INSTANCE_TYPE="p2.xlarge"
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"
... |
67acbebca31dd1d72025b21bd6a9554d2f32ce08a410f94bf6f3a1139a035887 | Shell | 2,860 | 56 | DATETIME=$(date +%Y%m%d_%H%M%S)
OUTPUT_FOLDER=outputs/experiment/pert/dentategyrus/pert_subset_sampling_ode_model_$DATETIME
export WANDB_API_KEY=YOUR_WANDB_KEY
python perturb.py --trainer_ckpt_path outputs/experiment/train/dentategyrus/ode_model_all_20240122_154741/model-3.pt \
--model.dim 64 \
--model.input-d... |
882f2c158f834da667934c010d3909e6d05c8e0a3f69edf86034f941735a3aac | Shell | 2,861 | 97 | #!/bin/bash
#
# # Compile_MATLAB_code.sh
#
# Compile the MATLAB code necessary for running the ReApplyFix Pipeline
#
# ## Copyright Notice
#
# Copyright (C) 2017 The Human Connectome Project
#
# * Washington University in St. Louis
# * University of Minnesota
# * Oxford University
#
# ## Author(s)
#
# * Timothy B. Bro... |
8087ede2117459d3d9e9e0d75c5fddd38ea453d64ae3477fa329cae5b41bd66e | Shell | 2,864 | 48 | set -e
# 1. mapping to reference genome
Mapit mapping -v GRCh38 --fq /home/gangx/data/MAPIT/clean/G3_1_val_1.fq.gz --fq2 /home/gangx/data/MAPIT/clean/G3_1_val_2.fq.gz --rna-strandness FR -n G3 -r 1 -o /home/gangx/data/MAPIT/Mapit_result -t 40
Mapit mapping -v GRCh38 --fq /home/gangx/data/MAPIT/clean/G3_2_val_1.fq.gz -... |
3941ff298787a1d9e906857b7f8ba34926cd83dfd9c95304649b6edc813c578a | Shell | 2,871 | 65 | #!/bin/bash
############
# Usage
############
# bash script_main_superpixels_graph_classification_MNIST_500k.sh
############
# GNNs
############
#3WLGNN
#RingGNN
############
# MNIST - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_superpixels_graph_classification.py
tmux new -s benchma... |
e34db63a2915b1be19c5a4f4502bde131f4c1b1ef9daec2e5bea21a9a24fd283 | Shell | 2,926 | 66 | #!/bin/bash
############
# Usage
############
# bash script_main_superpixels_graph_classification_CIFAR10_500k.sh
############
# GNNs
############
#3WLGNN
#RingGNN
############
# CIFAR10 - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_superpixels_graph_classification.py
tmux new -s be... |
e201498c8f6ec618d9157c7ba66d724467dfea638df6e75d5f5871530eeca7c7 | Shell | 2,940 | 70 | #!/bin/bash
############
# Usage
############
# bash script_main_CYCLES_graph_classification_CYCLES_100k.sh
############
# GNNs
############
# GatedGCN
############
# CYCLES - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_CYCLES_graph_classification.py
dataset=CYCLES
tmux new -s benchmar... |
afc5fe8b51f1a7ba5097a0b6675f81d273a0efd6332ae6fc09f0224b894b12ad | Shell | 2,960 | 104 | #!/bin/bash
#SBATCH --partition=gpu4_dev
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem=20G
#SBATCH --job-name=TCGA_08
#SBATCH --output=log_TCGA_08_%A_%a.out
#SBATCH --error=log_TCGA_08_%A_%a.err
unset PYTHONPATH
module load condaenvs/gpu/pathgan_SSL37
#### comb 005
all_ind=os_event_ind
all_data=o... |
7a09919a1f2053866906c3f2c4c2dbd9e50ce63e1159f252dfaa7a91ef4feae0 | Shell | 2,963 | 84 | #!/bin/bash
# custom config
# DATA=/path/to/datasets
#TRAINER=UPT
#TRAINER=VPT
# TRAINER=CoOp
TRAINER=$1
output_dir=~/opensource/ckpt/
#root=/shared/sheng/coop_data
# root=/tmp/ic/
root=//tmp/coop_data
# DATASET=$1 # ['hateful-memes', 'cifar-10', 'mnist', 'oxford-flower-102', 'oxford-iiit-pets', 'resisc45_clip', 'co... |
811bd840d7ebba6a5371f0cd47f81ce2d4562399557c070669e943c145272667 | Shell | 2,988 | 70 | #!/bin/bash
############
# Usage
############
# bash script_main_CYCLES_graph_classification_CYCLES_100k.sh
############
# GNNs
############
# GatedGCN
############
# CYCLES - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_CYCLES_graph_classification.py
dataset=CYCLES
tmux new -s benchmar... |
7debefa67c3d5a6b8355a8da48f334c1ffcc748541900270e3e4ba449c750ac0 | Shell | 2,992 | 81 | # This script will be run in the root directory.
### 1. For SAN, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/SAN/vocsuperpixels-SAN.yaml
# 1.1.1 SAN VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED seed $SEED wandb.project lrgb-voc name_tag S... |
6eccffe51ee2b125a06153660289a004e16306a230c4e80a96fd318065a7f81d | Shell | 3,008 | 87 | #!/bin/bash
# SPDX-FileCopyrightText: Copyright (c) 2023-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
set -euo pipefail
source rapids-init-pip
LIBCUML_WHEELHOUSE=$(rapids-download-from-github "$(rapids-artifact-name wheel_cpp libcuml cuml --cuda "$RAPIDS_CUDA_VERS... |
4678c687c4a0c02234283e1ad6ed24a5c9d21e8c097a006dd6dd5a9a9b5f9a00 | Shell | 3,013 | 81 | # This script will be run in the root directory.
### 1. For GINE, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/GINE/vocsuperpixels-GINE.yaml
# 1.1.1 GINE VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED seed $SEED wandb.project lrgb-voc name_t... |
710491ff496b84ca0eb51d59f65dcd141a16075594ec8cbcfba1ebdc7583e145 | Shell | 3,020 | 70 | #!/bin/bash
############
# Usage
############
# bash script_main_CYCLES_graph_classification_CYCLES_100k.sh
############
# GNNs
############
# GatedGCN
############
# CYCLES - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_CYCLES_graph_classification.py
dataset=CYCLES
tmux new -s benchmar... |
006bf8bc27ab0fb204282344efdca7e2f1b40d58961245a56a0b9da95cc7c78d | Shell | 3,036 | 61 | #!/bin/bash
# SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
# SPDX-License-Identifier: Apache-2.0
##########################################
# cuML black listed function call Tester #
##########################################
# PR_TARGET_BRANCH is set by the CI environment
git checkout --quiet... |
b9cf0239a1ef4f602c9bf4a1e84c85cb2df7cd4b54387881634a492de0bfa332 | Shell | 3,062 | 77 | #!/bin/bash -e
# Copyright (C) 2004-2011 University of Oxford
#
# SHCOPYRIGHT
Usage() {
echo ""
echo "Usage: mcflirt_acc <4dinput> <4doutput> [ref_image]"
echo ""
exit
}
[ "$2" = "" ] && Usage
input=`${FSLDIR}/bin/remove_ext ${1}`
output=`${FSLDIR}/bin/remove_ext ${2}`
TR=`fslval $input pixdim4`... |
e4b3690588d36541141c800be6ad484c601e56a20a3b2050fc03b8601cd6e5ec | Shell | 3,068 | 70 | #!/bin/bash
############
# Usage
############
# bash script_main_CYCLES_graph_classification_CYCLES_100k.sh
############
# GNNs
############
# GatedGCN
############
# CYCLES - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_CYCLES_graph_classification.py
dataset=CYCLES
tmux new -s benchmar... |
ceef068ef7a432fbb5d0111ee6cf266f4548dcdab61c424176b20fc97c9c045f | Shell | 3,087 | 81 | # This script will be run in the root directory.
### 1. For SAN-RWSE, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/SAN/vocsuperpixels-SAN+RWSE.yaml
# 1.1.1 SAN-RWSE VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED seed $SEED wandb.project lrgb... |
81dec9b9a3d57fb908231ff43de67ba0e4c30dd0b7c2927f846294a0ed4e63e9 | Shell | 3,097 | 81 | # This script will be run in the root directory.
### 1. For GatedGCN, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/GatedGCN/vocsuperpixels-GatedGCN.yaml
# 1.1.1 GatedGCN VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED seed $SEED wandb.project... |
0fbb54fc272447f6576d119cb851a7e29604e21bfa99e6dcd0119af8c252f4da | Shell | 3,103 | 63 | #!/bin/bash -e
#SBATCH # slurm/HPC commands here
#SBATCH --mem=498G
module add SPAdes/3.15.5
module add python/anaconda/2020.11/3.8
cd /path/to/folder
line=$(sed "${SLURM_ARRAY_TASK_ID}q;d" /path/to/metadata/files/contig_assemble_md.txt) # if running as an array job, contains full filenames
sample_id=$(echo $line)
sa... |
22b578b9817bd111c0a67a47f5fcc974fac29383cd2e361359eefdb162e1f115 | Shell | 3,108 | 87 | #!/bin/bash
# custom config
# DATA=/path/to/datasets
#TRAINER=UPT
#TRAINER=VPT
# TRAINER=CoOp
TRAINER=$1
output_dir=~/opensource/ckpt/
#root=/shared/sheng/coop_data
# root=/tmp/ic/
root=//tmp/coop_data
# DATASET=$1 # ['hateful-memes', 'cifar-10', 'mnist', 'oxford-flower-102', 'oxford-iiit-pets', 'resisc45_clip', 'co... |
72e23950cfd3034a0cd516de13d3d3174a7793325806480106ab7cdfd3b77909 | Shell | 3,139 | 86 | #!/bin/env bash
# This script runs Multilayer Meta-Matching (Chen et al. 2024) using functional coupling and clinical outcome data from STAGES.
# A total of 4 models are run in the main analysis, which differ in terms of the:
#
# 1. Clinical scale predicted:
# - Brief Psychiatric Rating Scale (BPRS)
# ... |
62417fef84d11e85a2f78f0c9c063a8ac25e61668b6ddf59d7765fa5c1153165 | Shell | 3,152 | 109 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-26429b5e" #extract
#AMI="ami-7428ff0c" #extract
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="p2.xlarge"... |
b86dd4a4a16c90dbd797700aa38b8a2b0412ae471262df707518f21d1eee18e8 | Shell | 3,170 | 165 | #!/bin/sh
#
# Downloads sequence for the hg19 version of H. spiens (human) from
# UCSC.
#
# Note that UCSC's hg19 build has three categories of compressed fasta
# files:
#
# 1. The base files, named chr??.fa.gz
# 2. The unplaced-sequence files, named chr??_gl??????_random.fa.gz
# 3. The alternative-haplotype files, na... |
489796af8c3f34a67393a730824fc14d3668c0c652d43d6deecf7cd6c64b6954 | Shell | 3,183 | 79 | #!/bin/bash
#22/06/2024
#Zeinab Eftekhari and Dr. Thomsa Shaw
# register the second time point scout to first time point T1W, then move the mask to the same space for calculating dice overlap
# Load required modules (ensure your environment uses 'ml' for loading modules)
ml fsl/6.0.6.4
ml freesurfer
ml ants
# Define ... |
85fa2233f706e7dafb52eb911bcc52f68a9cc3b65a8202ee4017359270d00ecb | Shell | 3,207 | 109 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-d21ab9aa" #extract
#AMI="ami-7428ff0c" #extract
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="p2.xlarge"... |
fffd04586dc0cd72f0769f9b17acdafe39c34380c782ae67d9691a90c61c16bd | Shell | 3,211 | 81 | # This script will be run in the root directory.
### 1. For GatedGCN-LapPE, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/GatedGCN/vocsuperpixels-GatedGCN+LapPE.yaml
# 1.1.1 GatedGCN-LapPE VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED seed $... |
b60f103d0e955ba1d46350da08d4ad555deaf3001ec5f7669c945f0ea2934a6b | Shell | 3,238 | 110 | #!/bin/bash
# Fine-tuning script for RCM Layer Classification on 4th Generation Images
# Usage:
# bash scripts/run_layer_finetune.sh --pretrained_model PATH_TO_MODEL
# bash scripts/run_layer_finetune.sh --pretrained_model PATH_TO_MODEL --test
echo "Starting RCM Layer Classification Fine-tuning on 4th Generation D... |
ef7a081dfacc55bf38a04075694d13cc697ad5e60ddbbf5ee6aaef81fd840e5d | Shell | 3,258 | 81 | # This script will be run in the root directory.
### 1. For Transformer-LapPE, 4 seeds ######################
## 1.1 VOCSuperpixels
config=configs/GPS/vocsuperpixels-Transformer+LapPE.yaml
# 1.1.1 Transformer-LapPE VOCSuperpixels slic 10
for SEED in {0..3}; do
python main.py --cfg $config device cuda:$SEED se... |
ce9a3e05606c921db9a9ec45176778fc58a69e42ce8ab568445e4f498afbe378 | Shell | 3,259 | 118 | #!/bin/bash
#~ND~FORMAT~MARKDOWN~
#~ND~START~
#
# # Compile_MATLAB_code.sh
#
# Compile the MATLAB code necessary for running the MSMAll Pipeline
#
# ## Copyright Notice
#
# Copyright (C) 2017 The Human Connectome Project
#
# * Washington University in St. Louis
# * University of Minnesota
# * Oxford University
#
# ## ... |
d338f49db587b104761b0932e18d008ecf4c353497dd84551f470aa84735f7f2 | Shell | 3,277 | 103 | #!/usr/bin/env bash
# Use python's argparse module in shell scripts
#
# The function `argparse` parses its arguments using
# argparse.ArgumentParser; the parser is defined in the function's
# stdin.
#
# Executing ``argparse.bash`` (as opposed to sourcing it) prints a
# script template.
#
# https://github.com/nhoffman/... |
1d65403d6bab87c7e707f68c787a8edd2a5d5c1e42cb03b140cdf69a5a23858a | Shell | 3,340 | 87 | #!/bin/bash
# SPDX-FileCopyrightText: Copyright (c) 2020-2026, NVIDIA CORPORATION.
# SPDX-License-Identifier: Apache-2.0
set -euo pipefail
. /opt/conda/etc/profile.d/conda.sh
rapids-logger "Configuring conda strict channel priority"
conda config --set channel_priority strict
rapids-logger "Downloading artifacts from... |
d85c92539b881b235811e58a331af259c11b71e65a96bc0d66cd5cb6935c8205 | Shell | 3,374 | 85 | #!/bin/bash
# SPDX-FileCopyrightText: Copyright (c) 2022-2025, NVIDIA CORPORATION.
# SPDX-License-Identifier: Apache-2.0
# This script is a wrapper for cmakelang that may be used with pre-commit. The
# wrapping is necessary because RAPIDS libraries split configuration for
# cmakelang linters between a local config fi... |
45039137a0ba81bc6affe6574437f2b98b2523412ab30459e4e71903ac01d1c3 | Shell | 3,407 | 117 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argum... |
12640dff3271a9f457684f914fbdeac161c0e4d01eed3c3a1db1f697750d9c56 | Shell | 3,456 | 116 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-6819d110" #extract
INSTANCE_TYPE="p2.xlarge"
# INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"... |
98924026b9a02039a58c9484703ab035148e87ab5ebad3d482e4db5c540177b6 | Shell | 3,486 | 150 | #!/bin/bash
## C. Vriend - Amsterdam UMC - Aug '24
# slurm settings
#SBATCH --job-name=RBA
#SBATCH --mem=4G
#SBATCH --partition=luna-cpu-long
#SBATCH --qos=anw-cpu
#SBATCH --cpus-per-task=24
#SBATCH --time=01-0:00:00
#SBATCH --nice=2000
#SBATCH --mail-type=END,FAIL
#SBATCH --output=RBA_%A.out
# running containerized... |
b807039a7c079bb54715618efb32a838ae93bcec63efcf87cf471af97e56a0db | Shell | 3,497 | 114 | #!/bin/bash
#!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
... |
7f56fefa37f8ea53e4fa2dda381b6c1fb5458ad1deb2021c367a2006c533f5fd | Shell | 3,504 | 116 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-55c2792d" #extract
#INSTANCE_TYPE="p2.xlarge"
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"
... |
7d8f56b33899ae0ccc7e61d982f833395a26c43c47f9fc8ac1138640d0b28791 | Shell | 3,509 | 105 | #!/bin/env bash
# This script runs Kernel Ridge Regression (Li et al. 2019) using functional coupling and clinical outcome data from STAGES.
# A total of 8 models are run in the main analysis, which differ in terms of the:
#
# 1. Clinical scale predicted:
# - Brief Psychiatric Rating Scale (BPRS)
# -... |
438586d54e5ea70a0fb5151e8572e9238565d7bb277421ce3ebc9bc99fb01113 | Shell | 3,516 | 116 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-a7fa31df" #extract
INSTANCE_TYPE="g3.4xlarge"
# INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge... |
f88cb41b7e84a3fdf1796088f3b7f20894d83fa5ea26d7b589ac5d7ae328ffc4 | Shell | 3,520 | 114 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-55c2792d" #extract
#INSTANCE_TYPE="p2.xlarge"
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"
... |
334c36b199beb7f28351ddfbbf98d8c5e1c0f5a29aab8d41f818399c5fa86b2e | Shell | 3,655 | 97 | #!/bin/bash
# custom config
# DATA=/path/to/datasets
#TRAINER=UPT
#TRAINER=VPT
# TRAINER=CoOp
TRAINER=$1
output_dir=./CoCoOp_mt_20
#root=/shared/sheng/coop_data
# root=/tmp/ic/
# root=/tmp//coop_data
root=/rscratch/shijiayang/Prompt/new0/prompt-moe/CoOp/outputs/datasets
# DATASET=$1 # ['hateful-memes', 'cifar-10', '... |
12d520e3b0850c2d66a8f4c7f31787a55faa8f977a50fc80902aa71a36ca0628 | Shell | 3,679 | 118 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argum... |
a505119909c42c703039c57fa536317b2775513d524668a5e57eb5b357005f5d | Shell | 3,788 | 98 | #!/bin/bash
# custom config
# DATA=/path/to/datasets
#TRAINER=UPT
#TRAINER=VPT
# TRAINER=CoOp
TRAINER=$1
# output_dir=./CoCoOp_single_task_20
#root=/shared/sheng/coop_data
# root=/tmp/ic/
# root=//tmp/coop_data
root=/rscratch/shijiayang/Prompt/new0/prompt-moe/CoOp/outputs/datasets
output_dir=./CoCoOp_single_task_20
... |
7cec23298367eb835585e22f8d458efaf8e2af4397c04bf68fc77994427b5129 | Shell | 3,813 | 66 | #### get all statistics ####
for i in `ls align/C*.md.filter.meth.sta.txt.gz`
do
smp=`basename $i |sed 's/.md.filter.meth.sta.txt.gz//g'`
echo -e "$smp,"\
`cat fastq/${smp}_1_fastqc.html|sed 's/<[^>]*>/\n/g'|grep -i total -A2|sed -n 3p`","\
`cat fastq/${smp}_fastp_1_fastqc.html|sed 's/<[^>]*>/\n/g'|grep -i total -A2|se... |
9403f945daf6314c4cb885073f16c3411987094d5fb8ca207b77cf009f3e3bef | Shell | 3,831 | 132 | #!/bin/bash
#SBATCH --partition=gpu4_dev
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=1
#SBATCH --mem=20G
#SBATCH --job-name=TCGA_09
#SBATCH --output=log_TCGA_09_%A_%a.out
#SBATCH --error=log_TCGA_09_%A_%a.err
unset PYTHONPATH
module load condaenvs/gpu/pathgan_SSL37
all_ind=os_event_ind
all_data=os_event_data
remov... |
5c9b5f4d8f860aa9a2d2b18f30a6a3a8417fd9da13debf357095d9013640271c | Shell | 3,882 | 85 | #!/bin/bash
mkdir -p 4D_data
mkdir -p 4D_data_only_ligand
mkdir -p 4D_data_only_ligand_tracking
mkdir -p 4D_data_only_protein
mkdir -p no_MD
mkdir -p MD_DA/complex
mkdir -p MD_DA/only_ligand
mkdir -p MD_DA/only_protein
mkdir -p reduced
wget https://zenodo.org/record/10390550/files/4D_complex_training_set.zip?download... |
da24525952ca74cca0e2bc3bcc94b91b4da181f95accba703c3002a4704214a6 | Shell | 3,895 | 103 | #!/usr/bin/env bash
# Run this script from the project root dir.
function run_repeats {
dataset=$1
cfg_suffix=$2
# The cmd line cfg overrides that will be passed to the main.py,
# e.g. 'name_tag test01 gnn.layer_type gcnconv'
cfg_overrides=$3
cfg_file="${cfg_dir}/${dataset}-${cfg_suffix}.yaml... |
0e50c8809e374093f313bc98407751908200d2b303858018f54c909540d4cc55 | Shell | 3,933 | 32 | #!/bin/bash
set -e
echo -e "\n START: RibbonVolumeToSurfaceMapping_1res"
WorkingDirectory="$1"
VolumefMRI="$2"
Subject="$3"
DownsampleFolder="$4"
LowResMesh="$5"
AtlasSpaceNativeFolder="$6"
RegName="$7"
if [ ${RegName} = "FS" ]; then
RegName="reg.reg_LR"
fi
for Hemisphere in L R ; do
for Map in mean cov ; do
... |
ce09b6a5594b24ea5eafac6aeb901d6e8c49a9f97a5209fc1404ddeaaf6b1740 | Shell | 3,961 | 146 | #!/usr/bin/env bash
root0=${0##*/}
helpmsg(){
echo "Copy scripts and lib directories from local OGRE-pipeline repository for testing."
echo "Required: ${root0} -r <repository directory> -v <version number>"
echo " -r --repo -repo --repository -repository"
echo " Repository directory. All cod... |
86cc3ae83efc57cae2c2a04a7c52a7b5538b0d28cbe637c9d618ade1901d0585 | Shell | 3,983 | 106 | #!/bin/env bash
# This script runs Connectome-based Predictive Modelling (Shen et al. 2017) using functional coupling and clinical outcome data from STAGES.
# A total of 16 models are run in the main analysis, which differ in terms of the:
#
# 1. Clinical scale predicted:
# - Brief Psychiatric Rating Scale ... |
8b052b1b8899ee19f0420ead0f2f79958238e50d43063cfcb0c8c878232c86ff | Shell | 3,985 | 118 | #!/bin/sh
# usage:
# sh superresolution_batch.sh /path/to/batch_list.txt
#
# Author: Sebastien Tourbier
#
###################################################################
# Use the latest stable release version of the docker image
VERSION_TAG="v1.1.0"
# Get the directory where the script is stored,
# which is su... |
ab2b6a3e1a605ac3e2df7747f808742fab8c1655f4dbca110cb17a89c4aa8212 | Shell | 4,009 | 102 | #!/bin/bash -e
#SBATCH slurm/HPC commands here
#SBATCH --mem=498G
module add BBMAP/38.86
cd /gpfs/home/hwe21ndu/scratch/sra_files
line=$(sed "${SLURM_ARRAY_TASK_ID}q;d" /path/to/metadata/files/trim_zip_md.txt) # if running as an array
# md should be a file containing ids and file paths
sample_name=$(echo $line)
samp... |
243602b7a53c8db57ab226f5e3e85607d04e70f0153decf84719489551bba162 | Shell | 4,030 | 88 | #!/bin/bash
############
# Usage
############
# bash script_main_WikiCS_node_classification_100k.sh
############
# GNNs
############
#MLP
#GCN
#GraphSage
#GAT
#MoNet
#GIN
############
# WikiCS - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_WikiCS_node_classification.py
tmux new -s ben... |
80bb8489cde7cb49a4d9de380f58df3b94b5f2a39ebc65cd138a078665a8377e | Shell | 4,165 | 82 | #!/bin/bash
# bash script_main_TUs_graph_classification_100k_seed1.sh
############
# GNNs
############
#GatedGCN
#GCN
#GraphSage
#MLP
#GIN
#MoNet
#GAT
#DiffPool
############
# ENZYMES & DD & PROTEINS_full
############
seed=41
code=main_TUs_graph_classification.py
tmux new -s benchmark_TUs_graph_classificati... |
c441704b4e4251b8537dfc8f235befe1c086cbc33d8b8fb134d9297bdaa14e67 | Shell | 4,166 | 83 | #!/bin/bash
# bash script_main_TUs_graph_classification_100k_seed2.sh
############
# GNNs
############
#GatedGCN
#GCN
#GraphSage
#MLP
#GIN
#MoNet
#GAT
#DiffPool
############
# ENZYMES & DD & PROTEINS_full
############
seed=95
code=main_TUs_graph_classification.py
tmux new -s benchmark_TUs_graph_classificati... |
6fd7dff3f227d1b3dd67fc4841aec08c626a3f6d8711ae32e2ee6b2630978d87 | Shell | 4,183 | 108 | #!/bin/bash
set -e
# Requirements for this script
# installed versions of: FSL (version 5.0.6) (including python with numpy, needed to run aff2rigid - part of FSL)
# environment: FSLDIR
################################################ SUPPORT FUNCTIONS ##################################################
Usage() {
... |
a2cda064f50e336fa2efd6cc8fe1959fa58373ed57a58ce77a392bf92dfcb659 | Shell | 4,215 | 133 | #!/bin/bash
# this script was used to process Sm-RIP-Seq libraries from Takara SMARTer Stranded Total RNA-Seq Kit v3 (product # 634451)
# Set paths to the indexed genome and annotation file (GTF)
index='/filepath to indexed genome'
gtf='/filepath to GTF/filename.gtf'
# Define output directories for the pipeline
outd... |
e57070dfa5f9f871e8354e18817573c6a16502e9cfebe755299cb4ef6ceb44f8 | Shell | 4,250 | 126 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-0460b47c" #extract
#INSTANCE_TYPE="p2.xlarge"
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"
... |
918a8695c7db78a750dfd6f6f817445993b61a4eedfcbada38b58c207c126f09 | Shell | 4,251 | 126 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-0460b47c" #extract
#INSTANCE_TYPE="p2.xlarge"
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="c3.2xlarge"
... |
46b14304a0395dbc2380d74fe5f2925a7d0e26c0352317b96aa418bb87295415 | Shell | 4,258 | 183 | #!/bin/bash
# Global default values
DEFAULT_STUDY_FOLDER="${HOME}/data/Pipelines_ExampleData"
DEFAULT_SUBJECT_LIST="100307"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/Pipelines/Examples/Scripts/SetUpHCPPipeline.sh"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_FIX_DIR="${HOME}/tools/fix1.06"
#
# Function Description
# Get the ... |
d1c2d3c1c0b8854e8ad9a15d480de4330c6963ba17454d674f2ccfbe6dbdd2d5 | Shell | 4,299 | 123 | #!/usr/bin/env bash
shebang="#!/usr/bin/env bash"
root0=${0##*/}
helpmsg(){
echo "Required: ${root0} PIPEDIR"
echo " -p PIPEDIR: pipeline directory of OGRE working outputs. "
echo " An optionless argument is assumed to be the pipeline directory."
echo " e.g. /Users/Shared/10_C... |
34f3d7209c198ef3dfa132a87340bd8666c9d90d68d10cc28d93032ea1a29d04 | Shell | 4,302 | 73 | #!/bin/bash
#SBATCH --account=def-lpenacas
#SBATCH --time=00:50:00
#SBATCH --mem=64G
module load python
source ../5_train/env/bin/activate
# python test.py dir model_weights_path model_name test_data test_labels
# # ------------------Train organisms, individually------------------ To test the performance of the mode... |
ab0f8a6a0850ac4f34d57758780205164c3d8f7b98d8576b50d3018347d1a592 | Shell | 4,307 | 145 | #!/bin/sh
# Copyright (C) 2015, 2018 Genome Research Ltd.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, m... |
bdb4f9e8e154ec700dac75b1e27afdb8dfdbaa3cee70bc31db418f0ef79daf39 | Shell | 4,406 | 127 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argum... |
fe0fc5f49d8f0e8af8431b94a26cb1d7fc8f85d8c736e39fda7f5933ce9fb1b7 | Shell | 4,412 | 188 | #!/bin/bash
# Global default values
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJECT_LIST="100307"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/Pipelines/Examples/Scripts/SetUpHCPPipeline.sh"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_FIX_DIR="${HOME}/tools/fix1.06"
#
# Function Description
# Get the command lin... |
c381fa79c2d79fe13b277d92bde7ef8daee5626115acfa35ebe8adb01ee9324a | Shell | 4,439 | 160 | #!/usr/bin/env bash
## Shell script to generate a single LaTeX file compiling all tables
## and compile it
# HERE
HERE="${HVR_VALIDATION_DIR:-$(git -C "$(dirname "$0")" rev-parse --show-toplevel)}"
TABLESDIR=${HERE}/tables
FIGSDIR=${HERE}/plots
TMETADATA=${TABLESDIR}/metadata.json
FMETADATA=${FIGSDIR}/metadata.json
O... |
ed7fe9bd28336b2102b479d3a69b28548e9d39ff2fd25e612d3932433de3e6d2 | Shell | 4,466 | 82 | #!/bin/bash
set -e
script_name="SubcorticalProcessing.sh"
echo "${script_name}: START"
AtlasSpaceFolder="$1"
echo "${script_name}: AtlasSpaceFolder: ${AtlasSpaceFolder}"
ROIFolder="$2"
echo "${script_name}: ROIFolder: ${ROIFolder}"
FinalfMRIResolution="$3"
echo "${script_name}: FinalfMRIResolution: ${FinalfMRIResol... |
06404d05fe498798667903e072bc455b072a563e4cd7a334770ee086ead91f62 | Shell | 4,477 | 175 | #! /usr/bin/env bash
## Apply CNN ensemble models to ADNI subjects from list
## Longitudinal list
## Need to load hvr_validation environment
TMPDIR=$(mktemp -d --tmpdir)
trap "rm -rf $TMPDIR" 0 1 2 15
set -ux
BASE_DIR="${HVR_VALIDATION_DIR:-$(git -C "$(dirname "$0")" rev-parse --show-toplevel)}"
MRI_DIR=${BASE_DIR... |
fccf30cf3401b4bc66f98766640797c8781e04751fbc0d884f6d16f3579ccbad | Shell | 4,482 | 77 | #!/bin/bash
set -e
# function for parsing options
getopt1() {
sopt="$1"
shift 1
for fn in "$@" ; do
if [ `echo "$fn" | grep -- "^${sopt}=" | wc -w` -gt 0 ] ; then
echo "$fn" | sed "s/^${sopt}=//"
return 0
fi
done
}
WD=`getopt1 "--workingdir" "$@"`
SubjectFolder=`getopt1 "--subjectfolder" ... |
ce34c2f7491dffa86a090ba084e77a28e1ee51dca0eb178551859ba143103a36 | Shell | 4,500 | 113 | #!/bin/bash
set -e
# Requirements for this script
# installed versions of: FSL (version 5.0.6), FreeSurfer (version 5.3.0-HCP) , gradunwarp (HCP version 1.0.2)
# environment: use SetUpHCPPipeline.sh (or individually set FSLDIR, FREESURFER_HOME, HCPPIPEDIR, PATH - for gradient_unwarp.py)
#########################... |
8a57bc01c740d5315a56f36a054776e0ae20daa15cc7498fe24e44beec713827 | Shell | 4,527 | 115 | #!/bin/bash
set -e
# Requirements for this script
# installed versions of: FSL (version 5.0.6), FreeSurfer (version 5.3.0-HCP) , gradunwarp (HCP version 1.0.2)
# environment: use SetUpHCPPipeline.sh (or individually set FSLDIR, FREESURFER_HOME, HCPPIPEDIR, PATH - for gradient_unwarp.py)
#########################... |
5784a8fe2eb19092825695166bf4718c50d31a56760ff0b0aaf5cd2f2ff76bee | Shell | 4,555 | 165 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-b663a9ce" #extract
#INSTANCE_TYPE="g3.4xlarge"
INSTANCE_TYPE="p2.xlarge"
# INSTANCE_TYPE="p3.2xlarge"... |
a1885162232aec11b65f526bfae22c64fc935f452e0688e5fb0de44937fafd7e | Shell | 4,604 | 135 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argum... |
1192c0fe291a66bef77f95dbf66c668fb8963a6d8d2fd8068606cb52917f10a2 | Shell | 4,623 | 135 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
argum... |
fa3ef345bc6ed4d05d009a04c9e9fd77924e603bd03d60a09af8f4a6ce2aeb44 | Shell | 4,690 | 167 | #!/bin/bash
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJ_LIST="102311"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/Pipelines/Examples/Scripts/SetUpHCPPipeline.sh"
#
# Function: get_batch_options
# Description:
# Retrieve the --StudyFolder=, --Subjlist=, --EnvironmentScript=... |
1c10507165b3b703fdb2ab18fe4ba05028e1a42af9d667d2767dc229f4be1632 | Shell | 4,704 | 90 | #!/bin/bash
# check :
# bash script.sh
# tmux attach -t script_tsp
# tmux detach
# pkill python
# bash script_main_COLLAB_edge_classification_40k.sh
############
# GNNs
############
#GatedGCN
#GCN
#GraphSage
#MLP
#GIN
#MoNet
#GAT
############
# OGBL-COLLAB - 4 RUNS
############
seed0=41
seed1=42
seed2=9... |
713ee5d84870afe1174031672b385b5217d2eb5ccb5cb7200b450c2f47339c51 | Shell | 4,733 | 183 | #! /usr/bin/env bash
## Apply CNN ensemble models to ADNI subjects from list
## Longitudinal list
## Need to load hvr_validation environment
TMPDIR=$(mktemp -d --tmpdir)
trap "rm -rf $TMPDIR" 0 1 2 15
set -ux
BASE_DIR="${HVR_VALIDATION_DIR:-$(git -C "$(dirname "$0")" rev-parse --show-toplevel)}"
QC_DIR=${BASE_DIR}... |
6a6f234f5f5a0c8821256cf1ccd052d8e4c0a6363b874e07ab48f604b6a72734 | Shell | 4,749 | 167 | #!/bin/bash
DEFAULT_STUDY_FOLDER="${HOME}/data/7T_Testing"
DEFAULT_SUBJ_LIST="102311"
DEFAULT_RUN_LOCAL="FALSE"
DEFAULT_ENVIRONMENT_SCRIPT="${HOME}/projects/Pipelines/Examples/Scripts/SetUpHCPPipeline.sh"
#
# Function: get_batch_options
# Description:
# Retrieve the --StudyFolder=, --Subjlist=, --EnvironmentScript=... |
40d4ed58c700bacb8b5b10c69f90b57145c00561c7747191a1b5906bb847419b | Shell | 4,795 | 171 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-b663a9ce" #extract
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="p2.xlarge"
# INSTANCE_TYPE="p3.2xlarge"... |
92970a089f14e7307edc7a2c8296cb5f61a86f2539b88a06c5a9c59e142419be | Shell | 4,824 | 132 | #!/usr/bin/env bash
# Run this script from the project root dir.
function run_repeats {
dataset=$1
cfg_suffix=$2
# The cmd line cfg overrides that will be passed to the main.py,
# e.g. 'name_tag test01 gnn.layer_type gcnconv'
cfg_overrides=$3
cfg_file="${cfg_dir}/${dataset}-${cfg_suffix}.yaml... |
e22ac74d81ba1de671bb901d8e6de16ea7e86a34a28959c4cb1b43b0fa8fde50 | Shell | 4,862 | 113 | #!/bin/bash
set -e
# Requirements for this script
# installed versions of: FSL (version 5.0.6) and HCP-gradunwarp (version 1.0.2)
# environment: FSLDIR, PATH to be able to find gradient_unwarp.py
################################################ SUPPORT FUNCTIONS ##################################################
... |
8ab98b320030445158fdb9c801d8ac648aaf8229d9e7fd013ba1cd1be3a23b69 | Shell | 4,873 | 143 | #!/bin/bash
set -e
# Intensity normalisation, and bias field correction, and optional Jacobian modulation, applied to fMRI images (all inputs must be in fMRI space)
# This code is released to the public domain.
#
# Matt Glasser, Washington University in St Louis
# Mark Jenkinson, FMRIB Centre, University of Oxfor... |
698f471030cb337d330c6d52817cc3df04a9ed866b429a1c80a28c7cde3606d9 | Shell | 4,874 | 85 | #!/bin/bash
# check :
# bash script.sh
# tmux attach -t script_tsp
# tmux detach
# pkill python
# bash script_main_TSP_edge_classification_edge_feature_analysis.sh
############
# GNNs
############
#GatedGCN
#GAT
############
# TSP - 4 RUNS
############
seed0=41
seed1=42
seed2=9
seed3=23
code=main_TSP_ed... |
947ef5eaf28daa6902ebb4f7232dee4f1fdd323a816a0660ca960bc777312060 | Shell | 4,913 | 120 | #!/bin/bash -e
# Copyright (C) 2004-2011 University of Oxford
#
# SHCOPYRIGHT
Usage() {
echo ""
echo "Usage: mcflirt.sh <4dinput> <4doutput> [<scout_image> [<mcref_image>]]"
echo ""
echo " If neither <scout_image> nor <mcref_image> is specified, a reference image"
echo " will be generated a... |
9f7bd4080ccd905ad2291eaaf204df6aca3a8c7e9df04c6dc338adf2950cf487 | Shell | 4,919 | 143 | #!/bin/bash
get_batch_options() {
local arguments=("$@")
unset command_line_specified_study_folder
unset command_line_specified_subj_list
unset command_line_specified_run_local
local index=0
local numArgs=${#arguments[@]}
local argument
while [ ${index} -lt ${numArgs} ]; do
... |
8f7df5d9a7db1d11ddde4038d98243fe504a8745d7ee259c42ccffc3bbf3a7d9 | Shell | 4,946 | 151 | platform='unknown'
unamestr=`uname`
if [[ "$unamestr" == 'Linux' ]]; then
platform='linux'
elif [[ "$unamestr" == 'Darwin' ]]; then
platform='darwin'
fi
# 1-100: g3.4
# 101-200: p2
# AMI="ami-660ae31e"
AMI="ami-d21ab9aa" #extract
#AMI="ami-7428ff0c" #extract
INSTANCE_TYPE="g3.4xlarge"
#INSTANCE_TYPE="p2.xlarge"... |
65937f4163c6a79d73efd841b55bb6901fd07f0db6b2a894fef8fcb22f785807 | Shell | 4,982 | 124 | #!/usr/bin/env bash
set -e
# Copyright (C) 2004-2011 University of Oxford
#
# SHCOPYRIGHT
Usage() {
echo ""
echo "Usage: mcflirt.sh <4dinput> <4doutput> [<scout_image> [<mcref_image>]]"
echo ""
echo " If neither <scout_image> nor <mcref_image> is specified, a reference image"
echo " will b... |
16b2712417c515f62ec577f006cf29786d06fb22cf16a259921fab1f2fe8a59a | Shell | 5,002 | 85 | #!/bin/bash
# check :
# bash script.sh
# tmux attach -t script_tsp
# tmux detach
# pkill python
# bash script_main_COLLAB_edge_classification_edge_feature_analysis.sh
############
# GNNs
############
#GatedGCN
#GAT
############
# OGBL-COLLAB - 4 RUNS
############
seed0=411
seed1=421
seed2=91
seed3=231
c... |
a891b149b9d62e99d195a876158df9ca5955b5e99f1e3893dbfb73d03b9bcef5 | Shell | 5,131 | 135 | # This script will be run in the root directory.
### 1. GCN ######################
for SEED in {0..3}; do
python main.py --cfg configs/expts_l2/GCN/peptides-func-GCN.yaml device cuda:$SEED seed $SEED wandb.project lrgb-2l name_tag GCN-peptides-func &
done
wait
for SEED in {0..3}; do
python main.py --cfg conf... |
4eddcda22861afd79f18feb3fff55f1d3123333b7a9f959d37e353313cf7ebc8 | Shell | 5,176 | 103 | #!/bin/bash
############
# Usage
############
# bash script_main_SBMs_node_classification_PATTERN_100k.sh
############
# GNNs
############
#MLP
#GCN
#GraphSage
#GatedGCN
#GAT
#MoNet
#GIN
#3WLGNN
#RingGNN
############
# SBM_PATTERN - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_SBMs_node... |
5ddab3786870afb5a9e1d25f1a7817e1dacb905f3f01e8b51251a9070b7fe34d | Shell | 5,177 | 103 | #!/bin/bash
############
# Usage
############
# bash script_main_SBMs_node_classification_CLUSTER_100k.sh
############
# GNNs
############
#MLP
#GCN
#GraphSage
#GatedGCN
#GAT
#MoNet
#GIN
#3WLGNN
#RingGNN
############
# SBM_CLUSTER - 4 RUNS
############
seed0=41
seed1=95
seed2=12
seed3=35
code=main_SBMs_nod... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.