{
 "cells": [
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "# Logging\n",
   "id": "b81523b202f5194e"
  },
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2026-03-27T10:35:42.305708512Z",
     "start_time": "2026-03-27T10:35:40.307786598Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from smt_optim.benchmarks.registry import get_problem\n",
    "\n",
    "from smt_optim.core import Driver, ObjectiveConfig, ConstraintConfig, DriverConfig, Problem\n",
    "\n",
    "from smt_optim.surrogate_models.smt import SmtAutoModel\n",
    "\n",
    "from smt_optim.acquisition_strategies import MFSEGO"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-27T10:35:42.358013714Z",
     "start_time": "2026-03-27T10:35:42.306749472Z"
    }
   },
   "cell_type": "code",
   "source": [
    "problem = get_problem(\"Branin1\")\n",
    "\n",
    "obj_config = ObjectiveConfig(\n",
    "    objective=[problem.objective[-1]],\n",
    "    type=\"minimize\",\n",
    "    surrogate=SmtAutoModel,           # set which GP to model the objective\n",
    ")\n",
    "\n",
    "prob_definition = Problem(\n",
    "    obj_configs=[obj_config],\n",
    "    design_space=problem.bounds\n",
    ")"
   ],
   "id": "2b5de38864a2503b",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## Verbose",
   "id": "637423d1c47fbcea"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-27T10:35:48.912206027Z",
     "start_time": "2026-03-27T10:35:42.359143260Z"
    }
   },
   "cell_type": "code",
   "source": [
    "driver_config = DriverConfig(\n",
    "    max_iter = 10,              # stopping criterion\n",
    "    nt_init = 5,                # number of sample in the initial DoE\n",
    "    scaling = True,             # standardize every QoI\n",
    "    seed=42,\n",
    "    verbose = True,\n",
    ")\n",
    "\n",
    "# configure the optimizer\n",
    "driver = Driver(prob_definition, driver_config, MFSEGO)\n",
    "\n",
    "# start optimization\n",
    "state = driver.optimize()"
   ],
   "id": "ba75a6956ab46033",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          iter         budget           fmin       fidelity        gp_time       acq_time\n",
      "             1              6    7.30174e+00              1          0.204          0.296\n",
      "             2              7    7.30174e+00              1          0.315          0.253\n",
      "             3              8    7.30174e+00              1          0.301          0.207\n",
      "             4              9    6.62931e+00              1          0.317          0.348\n",
      "             5             10    4.83559e+00              1          0.332          0.318\n",
      "             6             11    4.83559e+00              1          0.301          0.335\n",
      "             7             12    1.73269e+00              1          0.303          0.453\n",
      "             8             13    1.34048e+00              1          0.326          0.428\n",
      "             9             14    1.07063e+00              1          0.314          0.389\n",
      "            10             15    1.07063e+00              1          0.331          0.411\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## Logging the DoE",
   "id": "fe2417c45eb54daa"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-27T10:35:52.106599789Z",
     "start_time": "2026-03-27T10:35:48.972237536Z"
    }
   },
   "cell_type": "code",
   "source": [
    "driver_config = DriverConfig(\n",
    "    max_iter = 5,              # stopping criterion\n",
    "    nt_init = 5,                # number of sample in the initial DoE\n",
    "    scaling = True,             # standardize every QoI\n",
    "    seed=42,\n",
    "    verbose = True,\n",
    "    log_doe = True,\n",
    ")\n",
    "\n",
    "# configure the optimizer\n",
    "driver = Driver(prob_definition, driver_config, MFSEGO)\n",
    "\n",
    "# start optimization\n",
    "state = driver.optimize()"
   ],
   "id": "866ee1ae3ee7cff3",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          iter         budget           fmin       fidelity        gp_time       acq_time\n",
      "             1              6    7.30174e+00              1          0.207          0.327\n",
      "             2              7    7.30174e+00              1          0.355          0.257\n",
      "             3              8    7.30174e+00              1          0.323          0.229\n",
      "             4              9    6.62931e+00              1          0.322          0.390\n",
      "             5             10    4.83559e+00              1          0.348          0.304\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "## Logging statistics",
   "id": "aad88a8afbcf869e"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2026-03-27T10:35:55.100594886Z",
     "start_time": "2026-03-27T10:35:52.159804656Z"
    }
   },
   "cell_type": "code",
   "source": [
    "driver_config = DriverConfig(\n",
    "    max_iter = 5,              # stopping criterion\n",
    "    nt_init = 5,                # number of sample in the initial DoE\n",
    "    scaling = True,             # standardize every QoI\n",
    "    seed=42,\n",
    "    verbose = True,\n",
    "    log_doe = True,\n",
    "    log_stats = True,\n",
    ")\n",
    "\n",
    "# configure the optimizer\n",
    "driver = Driver(prob_definition, driver_config, MFSEGO)\n",
    "\n",
    "# start optimization\n",
    "state = driver.optimize()"
   ],
   "id": "3950ee37d329616d",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          iter         budget           fmin       fidelity        gp_time       acq_time\n",
      "             1              6    7.30174e+00              1          0.207          0.293\n",
      "             2              7    7.30174e+00              1          0.319          0.260\n",
      "             3              8    7.30174e+00              1          0.308          0.208\n",
      "             4              9    6.62931e+00              1          0.316          0.282\n",
      "             5             10    4.83559e+00              1          0.321          0.353\n"
     ]
    }
   ],
   "execution_count": 5
  }
 ],
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