#!/bin/bash

#SBATCH -p public            # targeting the public partition
#SBATCH --ntasks-per-core=1  # disabling multithreading
#SBATCH -n 40                # reserving 40 compute cores
#SBATCH -J g40               # naming the job
#SBATCH --array=0-12         # creating a SLURM job array of 13 sub-jobs

# Array of temperatures
TEMPERATURES=(1000 1100 1200 1300 1350 1400 1425 1450 1500 1550 1650 1750 1900)

# If the number of SLURM tasks exceeds the size of TEMPERATURES, we exit
if [ $SLURM_ARRAY_TASK_COUNT -gt ${#TEMPERATURES[@]} ]
then
    echo "number of tasks > number of temperatures"
    echo "($SLURM_ARRAY_TASK_COUNT > ${#TEMPERATURES[@]})"
    exit 1
fi

# JOB TASK ID with 3 zero padding
id=$(printf %03d $SLURM_ARRAY_TASK_ID)
MAIN_JOB_PATH="job_${SLURM_ARRAY_JOB_ID}"  # main job path
JOB_PATH="${MAIN_JOB_PATH}/${id}"  # sub-job path

# Run temperature
let "temperature = ${TEMPERATURES[$SLURM_ARRAY_TASK_ID]}"

# Activating the Python virtual environment
source ../../.venv/bin/activate

# Creating a directory dedicated to the run and moving into it
mkdir -p $JOB_PATH
cd $JOB_PATH

# Launching the MPI computation and redirecting standard output to the output.log file
mpiexec -n 40 llg3d -solver mpi -N 4000 -Jx 6000 -dx 1e-9 -T $temperature

wait

cd ..
llg3d.post --job_dir .