#!/usr/bin/env bash
script_path="$(dirname "$(realpath "$0")")"
name=Constraint_dora
if [[ $# -gt 0 ]]; then
    if [[ "-clean" == "$1" ]]; then
        rm -rf ${name}_results_* 2>/dev/null
        exit 0
    fi
fi
results_dir=${name}_results_$(date +%s)
rm -rf $results_dir  2>/dev/null
mkdir -p $results_dir
echo "Working directory: $(realpath $results_dir)"
cd  $results_dir
log=${name}.log
dataset=${name}.csv.gz
name_lc="$(echo "$name" | tr '[:upper:]' '[:lower:]')"
"${script_path}/${name_lc}_dataset.py" #Create dataset and visualize the problem
results=${name}_poly_optimization_results.txt
rm -f "$results" 2>/dev/null
smlp_args=(
    -data ${name}.csv.gz   # input CSV dataset
    -spec ${script_path}/${name_lc}.json  # JSON spec file
    -pref ${name}          # output file prefix
    -mode optimize         # operation mode
    -model poly_sklearn    # model type
    -epsilon 0.0000005     # convergence threshold
)

smlp "${smlp_args[@]}" >"$log" 2>&1
for var in X1 X2 Y1; do
    echo "$var = $(jq ".${var}.value_in_config" ${name}_${name}_optimization_results.json)" 2>&1 | tee -a "$results"
done