{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to Migrate minto.v0 Experiment to minto.v1\n",
    "\n",
    "This notebook is a guide to help you migrate your minto.v0 experiment to minto.v1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import minto\n",
    "import numpy as np\n",
    "import jijmodeling as jm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "tsp = minto.problems.tsp.QuadTSP()\n",
    "tsp_problem = tsp.problem()\n",
    "tsp_data = tsp.data(n=8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## minto.v0 experiment\n",
    "\n",
    "You can use the `v0.x.x` version of the minto in `v1.x.x` with `minto.v1`.\n",
    "In the following, we create a simple experiment using `minto.v0` and then migrate it to `minto.v1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jijmodeling_transpiler as jmt\n",
    "\n",
    "compiled_instance = jmt.core.compile_model(tsp_problem, tsp_data)\n",
    "qubo_builder = jmt.core.pubo.transpile_to_pubo(compiled_instance)\n",
    "qubo, _ = qubo_builder.get_qubo_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import minto.v0\n",
    "import openjij as oj\n",
    "\n",
    "sampler = oj.SASampler()\n",
    "sweeps_list = np.arange(100, 1000, 100)\n",
    "\n",
    "exp_v0 = minto.v0.Experiment(\"v0_exp\")\n",
    "for sweeps in sweeps_list:\n",
    "    with exp_v0.run():\n",
    "        response = sampler.sample_qubo(qubo, num_reads=10, num_sweeps=sweeps)\n",
    "        sampleset = jmt.core.pubo.openjij_decode.decode_from_openjij(\n",
    "            response,\n",
    "            qubo_builder,\n",
    "            compiled_instance\n",
    "        )\n",
    "        sampleset = jm.experimental.from_old_sampleset(sampleset)\n",
    "        exp_v0.log_result(\"result\", sampleset)\n",
    "        exp_v0.log_parameter(\"sweeps\", sweeps)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>experiment_name</th>\n",
       "      <th>run_id</th>\n",
       "      <th>sweeps</th>\n",
       "      <th>result</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>(Sample(run_id=\"b62a278d-91eb-4413-aa4d-1f6df4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>1</td>\n",
       "      <td>200</td>\n",
       "      <td>(Sample(run_id=\"80153cc8-a3ec-42de-9199-13f121...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>2</td>\n",
       "      <td>300</td>\n",
       "      <td>(Sample(run_id=\"fa4d1964-8a02-40d8-acd4-a01eb9...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>3</td>\n",
       "      <td>400</td>\n",
       "      <td>(Sample(run_id=\"cc854ff9-fb96-424c-ae5b-10ed4e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>4</td>\n",
       "      <td>500</td>\n",
       "      <td>(Sample(run_id=\"421e6577-b98f-4a21-a0a3-4ca75b...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>5</td>\n",
       "      <td>600</td>\n",
       "      <td>(Sample(run_id=\"7a9526ee-46cb-4791-b994-cb376c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>6</td>\n",
       "      <td>700</td>\n",
       "      <td>(Sample(run_id=\"37557e74-9854-490d-a8c0-92062c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>7</td>\n",
       "      <td>800</td>\n",
       "      <td>(Sample(run_id=\"64a6df02-c64e-46ec-9c05-4dc2a4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>v0_exp</td>\n",
       "      <td>8</td>\n",
       "      <td>900</td>\n",
       "      <td>(Sample(run_id=\"ace33c00-8ac4-43b0-81b9-4a3d4a...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  experiment_name  run_id  sweeps  \\\n",
       "0          v0_exp       0     100   \n",
       "1          v0_exp       1     200   \n",
       "2          v0_exp       2     300   \n",
       "3          v0_exp       3     400   \n",
       "4          v0_exp       4     500   \n",
       "5          v0_exp       5     600   \n",
       "6          v0_exp       6     700   \n",
       "7          v0_exp       7     800   \n",
       "8          v0_exp       8     900   \n",
       "\n",
       "                                              result  \n",
       "0  (Sample(run_id=\"b62a278d-91eb-4413-aa4d-1f6df4...  \n",
       "1  (Sample(run_id=\"80153cc8-a3ec-42de-9199-13f121...  \n",
       "2  (Sample(run_id=\"fa4d1964-8a02-40d8-acd4-a01eb9...  \n",
       "3  (Sample(run_id=\"cc854ff9-fb96-424c-ae5b-10ed4e...  \n",
       "4  (Sample(run_id=\"421e6577-b98f-4a21-a0a3-4ca75b...  \n",
       "5  (Sample(run_id=\"7a9526ee-46cb-4791-b994-cb376c...  \n",
       "6  (Sample(run_id=\"37557e74-9854-490d-a8c0-92062c...  \n",
       "7  (Sample(run_id=\"64a6df02-c64e-46ec-9c05-4dc2a4...  \n",
       "8  (Sample(run_id=\"ace33c00-8ac4-43b0-81b9-4a3d4a...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_v0.table(enable_sampleset_expansion=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Migrate from minto.v0 to minto.v1\n",
    "\n",
    "To migrate from `minto.v0` to `minto.v1`, you need to use `migrate_to_v1_from_v0` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from minto.migrator.v0tov1 import migrate_to_v1_from_v0\n",
    "\n",
    "exp_v1 = migrate_to_v1_from_v0(exp_v0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">sampleset_result</th>\n",
       "      <th>parameter</th>\n",
       "      <th colspan=\"2\" halign=\"left\">metadata</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>num_samples</th>\n",
       "      <th>obj_mean</th>\n",
       "      <th>obj_std</th>\n",
       "      <th>obj_min</th>\n",
       "      <th>obj_max</th>\n",
       "      <th>feasible</th>\n",
       "      <th>feasible_unrelaxed</th>\n",
       "      <th>name</th>\n",
       "      <th>sweeps</th>\n",
       "      <th>run_id</th>\n",
       "      <th>elapsed_time</th>\n",
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       "      <th>run_id</th>\n",
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       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "      <td>3.522054</td>\n",
       "      <td>0.390917</td>\n",
       "      <td>2.883244</td>\n",
       "      <td>4.207748</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>0.001561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10</td>\n",
       "      <td>3.421715</td>\n",
       "      <td>0.495696</td>\n",
       "      <td>2.869669</td>\n",
       "      <td>4.380822</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>200</td>\n",
       "      <td>1</td>\n",
       "      <td>0.001403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10</td>\n",
       "      <td>3.105068</td>\n",
       "      <td>0.494227</td>\n",
       "      <td>2.661808</td>\n",
       "      <td>4.098958</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>300</td>\n",
       "      <td>2</td>\n",
       "      <td>0.001363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>3.198603</td>\n",
       "      <td>0.354913</td>\n",
       "      <td>2.831967</td>\n",
       "      <td>3.925243</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>400</td>\n",
       "      <td>3</td>\n",
       "      <td>0.001273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10</td>\n",
       "      <td>3.037024</td>\n",
       "      <td>0.241666</td>\n",
       "      <td>2.700304</td>\n",
       "      <td>3.529449</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>500</td>\n",
       "      <td>4</td>\n",
       "      <td>0.001263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10</td>\n",
       "      <td>3.153340</td>\n",
       "      <td>0.350452</td>\n",
       "      <td>2.661808</td>\n",
       "      <td>3.869771</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>600</td>\n",
       "      <td>5</td>\n",
       "      <td>0.001405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10</td>\n",
       "      <td>3.276451</td>\n",
       "      <td>0.363259</td>\n",
       "      <td>2.709548</td>\n",
       "      <td>3.735491</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>700</td>\n",
       "      <td>6</td>\n",
       "      <td>0.001281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>3.223950</td>\n",
       "      <td>0.388657</td>\n",
       "      <td>2.700304</td>\n",
       "      <td>3.665643</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>800</td>\n",
       "      <td>7</td>\n",
       "      <td>0.001315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10</td>\n",
       "      <td>3.274044</td>\n",
       "      <td>0.326622</td>\n",
       "      <td>2.987036</td>\n",
       "      <td>3.910863</td>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>result</td>\n",
       "      <td>900</td>\n",
       "      <td>8</td>\n",
       "      <td>0.001294</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sampleset_result                                                   \\\n",
       "            num_samples  obj_mean   obj_std   obj_min   obj_max feasible   \n",
       "run_id                                                                     \n",
       "0                    10  3.522054  0.390917  2.883244  4.207748       10   \n",
       "1                    10  3.421715  0.495696  2.869669  4.380822       10   \n",
       "2                    10  3.105068  0.494227  2.661808  4.098958       10   \n",
       "3                    10  3.198603  0.354913  2.831967  3.925243       10   \n",
       "4                    10  3.037024  0.241666  2.700304  3.529449       10   \n",
       "5                    10  3.153340  0.350452  2.661808  3.869771       10   \n",
       "6                    10  3.276451  0.363259  2.709548  3.735491       10   \n",
       "7                    10  3.223950  0.388657  2.700304  3.665643       10   \n",
       "8                    10  3.274044  0.326622  2.987036  3.910863       10   \n",
       "\n",
       "                                  parameter metadata               \n",
       "       feasible_unrelaxed    name    sweeps   run_id elapsed_time  \n",
       "run_id                                                             \n",
       "0                      10  result       100        0     0.001561  \n",
       "1                      10  result       200        1     0.001403  \n",
       "2                      10  result       300        2     0.001363  \n",
       "3                      10  result       400        3     0.001273  \n",
       "4                      10  result       500        4     0.001263  \n",
       "5                      10  result       600        5     0.001405  \n",
       "6                      10  result       700        6     0.001281  \n",
       "7                      10  result       800        7     0.001315  \n",
       "8                      10  result       900        8     0.001294  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exp_v1.get_run_table()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then you can save the migrated experiment using `.save()` or `.save_as_ommx_archive` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# exp_v1.save()  # save the experiment at disk\n",
    "# exp_v1.save_as_ommx_archive(\"v1_exp.ommx\")  # save the experiment as an ommx archive"
   ]
  }
 ],
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