run_benchmarks.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# ==========================================\\\n",
        "# Author: Leonhard Felix Richter\n",
        "# Date:   25 Jan 2023\n",
        "# =========================================="
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "notebookRunGroups": {
          "groupValue": "1"
        }
      },
      "outputs": [],
      "source": [
        "import pickle\n",
        "from benchmark import bench_frame, bench_instance, load_instances, bench_looping, bench_series\n",
        "from qaoa_and_tdvp import tdvp_optimize_qaoa, QAOA\n",
        "from itertools import product\n",
        "import pandas as pd\n",
        "import networkx as nx"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>n</th>\n",
              "      <th>p</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"2\" valign=\"top\">3</th>\n",
              "      <th>1</th>\n",
              "      <td>59.0</td>\n",
              "      <td>4.242641</td>\n",
              "      <td>56.0</td>\n",
              "      <td>62.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>95.0</td>\n",
              "      <td>29.698485</td>\n",
              "      <td>74.0</td>\n",
              "      <td>116.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"5\" valign=\"top\">4</th>\n",
              "      <th>1</th>\n",
              "      <td>55.0</td>\n",
              "      <td>7.014271</td>\n",
              "      <td>44.0</td>\n",
              "      <td>62.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>194.0</td>\n",
              "      <td>203.399115</td>\n",
              "      <td>56.0</td>\n",
              "      <td>602.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>548.666667</td>\n",
              "      <td>1003.912081</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2588.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>83.333333</td>\n",
              "      <td>71.079298</td>\n",
              "      <td>0.0</td>\n",
              "      <td>182.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>370.0</td>\n",
              "      <td>621.564478</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1574.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">5</th>\n",
              "      <th>1</th>\n",
              "      <td>55.4</td>\n",
              "      <td>22.52998</td>\n",
              "      <td>20.0</td>\n",
              "      <td>92.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>184.2</td>\n",
              "      <td>152.561682</td>\n",
              "      <td>0.0</td>\n",
              "      <td>542.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>110.0</td>\n",
              "      <td>88.528715</td>\n",
              "      <td>0.0</td>\n",
              "      <td>224.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>314.0</td>\n",
              "      <td>650.809411</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2134.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           mean          std   min     max\n",
              "n p                                       \n",
              "3 1        59.0     4.242641  56.0    62.0\n",
              "  2        95.0    29.698485  74.0   116.0\n",
              "4 1        55.0     7.014271  44.0    62.0\n",
              "  2       194.0   203.399115  56.0   602.0\n",
              "  3  548.666667  1003.912081   0.0  2588.0\n",
              "  4   83.333333    71.079298   0.0   182.0\n",
              "  5       370.0   621.564478   0.0  1574.0\n",
              "5 1        55.4     22.52998  20.0    92.0\n",
              "  2       184.2   152.561682   0.0   542.0\n",
              "  3       110.0    88.528715   0.0   224.0\n",
              "  4       314.0   650.809411   0.0  2134.0"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "with open(\"tmp/tdvp_fun_calls.p\",'rb') as file:\n",
        "    tdvp_num_fun_calls = pickle.load(file)\n",
        "tdvp_num_fun_calls"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "optimizing with gradient descent\n",
            "done 58\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 58\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 94\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 94\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 193\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 547\n",
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            "optimizing with gradient descent\n",
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            "optimizing with gradient descent\n",
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            "optimizing with gradient descent\n",
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            "optimizing with gradient descent\n",
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            "optimizing with gradient descent\n",
            "done 82\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 369\n",
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            "optimizing with gradient descent\n",
            "done 369\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 369\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 369\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 369\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 369\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 54\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 183\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 109\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n",
            "optimizing with gradient descent\n",
            "done 313\n",
            "\n"
          ]
        }
      ],
      "source": [
        "for n in [3,4,5]:\n",
        "    instances = load_instances(n,p_max={3:2,4:5,5:4}[n])\n",
        "    path = f'results/tdvp_vs_gd_n{n}_new.p'\n",
        "    optimizers={\"tdvp\": False, \"scipy\": False, \"gradient_descent\": True}\n",
        "    \n",
        "    out = instances.apply(\n",
        "        lambda x: bench_series(\n",
        "            x,\n",
        "            optimizers=optimizers,\n",
        "            tollarance=0,\n",
        "            max_iter=10,\n",
        "            max_steps=int(tdvp_num_fun_calls['mean'].loc[n,x.name[0]]),\n",
        "            tdvp_range=10,\n",
        "            print_msg=False,\n",
        "        ),  # type: ignore\n",
        "        axis=1,\n",
        "    )\n",
        "    if path is not None:\n",
        "        with open(path, \"wb\") as f:\n",
        "            pickle.dump(out, f)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "notebookRunGroups": {
          "groupValue": "1"
        },
        "pycharm": {
          "is_executing": true
        }
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "n= 3\n",
            "Running benchmark on 6 instances with optimizers ('tdvp', 'scipy')\n",
            "optimizing with tdvp\n",
            "rhs step 197\r"
          ]
        },
        {
          "ename": "UnboundLocalError",
          "evalue": "local variable 'pool' referenced before assignment",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/qutip/parallel.py:213\u001b[0m, in \u001b[0;36mparallel_map\u001b[0;34m(task, values, task_args, task_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m    212\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 213\u001b[0m     pool \u001b[39m=\u001b[39m Pool(processes\u001b[39m=\u001b[39;49mkw[\u001b[39m'\u001b[39;49m\u001b[39mnum_cpus\u001b[39;49m\u001b[39m'\u001b[39;49m])\n\u001b[1;32m    215\u001b[0m     async_res \u001b[39m=\u001b[39m [pool\u001b[39m.\u001b[39mapply_async(task, (value,) \u001b[39m+\u001b[39m task_args, task_kwargs,\n\u001b[1;32m    216\u001b[0m                                   _update_progress_bar)\n\u001b[1;32m    217\u001b[0m                  \u001b[39mfor\u001b[39;00m value \u001b[39min\u001b[39;00m values]\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/context.py:119\u001b[0m, in \u001b[0;36mBaseContext.Pool\u001b[0;34m(self, processes, initializer, initargs, maxtasksperchild)\u001b[0m\n\u001b[1;32m    118\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39m.\u001b[39;00m\u001b[39mpool\u001b[39;00m \u001b[39mimport\u001b[39;00m Pool\n\u001b[0;32m--> 119\u001b[0m \u001b[39mreturn\u001b[39;00m Pool(processes, initializer, initargs, maxtasksperchild,\n\u001b[1;32m    120\u001b[0m             context\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mget_context())\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/pool.py:215\u001b[0m, in \u001b[0;36mPool.__init__\u001b[0;34m(self, processes, initializer, initargs, maxtasksperchild, context)\u001b[0m\n\u001b[1;32m    214\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 215\u001b[0m     \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_repopulate_pool()\n\u001b[1;32m    216\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m:\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/pool.py:306\u001b[0m, in \u001b[0;36mPool._repopulate_pool\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    305\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m_repopulate_pool\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 306\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_repopulate_pool_static(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_ctx, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mProcess,\n\u001b[1;32m    307\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_processes,\n\u001b[1;32m    308\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_pool, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_inqueue,\n\u001b[1;32m    309\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_outqueue, \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_initializer,\n\u001b[1;32m    310\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_initargs,\n\u001b[1;32m    311\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_maxtasksperchild,\n\u001b[1;32m    312\u001b[0m                                         \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_wrap_exception)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/pool.py:329\u001b[0m, in \u001b[0;36mPool._repopulate_pool_static\u001b[0;34m(ctx, Process, processes, pool, inqueue, outqueue, initializer, initargs, maxtasksperchild, wrap_exception)\u001b[0m\n\u001b[1;32m    328\u001b[0m w\u001b[39m.\u001b[39mdaemon \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m\n\u001b[0;32m--> 329\u001b[0m w\u001b[39m.\u001b[39;49mstart()\n\u001b[1;32m    330\u001b[0m pool\u001b[39m.\u001b[39mappend(w)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/process.py:121\u001b[0m, in \u001b[0;36mBaseProcess.start\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    120\u001b[0m _cleanup()\n\u001b[0;32m--> 121\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_popen \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_Popen(\u001b[39mself\u001b[39;49m)\n\u001b[1;32m    122\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_sentinel \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_popen\u001b[39m.\u001b[39msentinel\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/context.py:281\u001b[0m, in \u001b[0;36mForkProcess._Popen\u001b[0;34m(process_obj)\u001b[0m\n\u001b[1;32m    280\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39m.\u001b[39;00m\u001b[39mpopen_fork\u001b[39;00m \u001b[39mimport\u001b[39;00m Popen\n\u001b[0;32m--> 281\u001b[0m \u001b[39mreturn\u001b[39;00m Popen(process_obj)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/popen_fork.py:16\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[0;34m(self, process_obj)\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39m__init__\u001b[39m(\u001b[39mself\u001b[39m, process_obj):\n\u001b[0;32m---> 16\u001b[0m     util\u001b[39m.\u001b[39;49m_flush_std_streams()\n\u001b[1;32m     17\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mreturncode \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/multiprocessing/util.py:435\u001b[0m, in \u001b[0;36m_flush_std_streams\u001b[0;34m()\u001b[0m\n\u001b[1;32m    434\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 435\u001b[0m     sys\u001b[39m.\u001b[39;49mstdout\u001b[39m.\u001b[39;49mflush()\n\u001b[1;32m    436\u001b[0m \u001b[39mexcept\u001b[39;00m (\u001b[39mAttributeError\u001b[39;00m, \u001b[39mValueError\u001b[39;00m):\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/ipykernel/iostream.py:480\u001b[0m, in \u001b[0;36mOutStream.flush\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    479\u001b[0m \u001b[39m# and give a timeout to avoid\u001b[39;00m\n\u001b[0;32m--> 480\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m evt\u001b[39m.\u001b[39;49mwait(\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mflush_timeout):\n\u001b[1;32m    481\u001b[0m     \u001b[39m# write directly to __stderr__ instead of warning because\u001b[39;00m\n\u001b[1;32m    482\u001b[0m     \u001b[39m# if this is happening sys.stderr may be the problem.\u001b[39;00m\n\u001b[1;32m    483\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mIOStream.flush timed out\u001b[39m\u001b[39m\"\u001b[39m, file\u001b[39m=\u001b[39msys\u001b[39m.\u001b[39m__stderr__)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/threading.py:607\u001b[0m, in \u001b[0;36mEvent.wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    606\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m signaled:\n\u001b[0;32m--> 607\u001b[0m     signaled \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_cond\u001b[39m.\u001b[39;49mwait(timeout)\n\u001b[1;32m    608\u001b[0m \u001b[39mreturn\u001b[39;00m signaled\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/threading.py:324\u001b[0m, in \u001b[0;36mCondition.wait\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m    323\u001b[0m \u001b[39mif\u001b[39;00m timeout \u001b[39m>\u001b[39m \u001b[39m0\u001b[39m:\n\u001b[0;32m--> 324\u001b[0m     gotit \u001b[39m=\u001b[39m waiter\u001b[39m.\u001b[39;49macquire(\u001b[39mTrue\u001b[39;49;00m, timeout)\n\u001b[1;32m    325\u001b[0m \u001b[39melse\u001b[39;00m:\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: ",
            "\nDuring handling of the above exception, another exception occurred:\n",
            "\u001b[0;31mUnboundLocalError\u001b[0m                         Traceback (most recent call last)",
            "Cell \u001b[0;32mIn [7], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39mfor\u001b[39;00m n \u001b[39min\u001b[39;00m [\u001b[39m3\u001b[39m]:\n\u001b[1;32m      2\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39mn=\u001b[39m\u001b[39m\"\u001b[39m,n)\n\u001b[0;32m----> 3\u001b[0m     bench_frame(\n\u001b[1;32m      4\u001b[0m         load_instances(n,p_min\u001b[39m=\u001b[39;49m\u001b[39m3\u001b[39;49m,p_max\u001b[39m=\u001b[39;49m\u001b[39m5\u001b[39;49m),\n\u001b[1;32m      5\u001b[0m         optimizers\u001b[39m=\u001b[39;49m{\u001b[39m\"\u001b[39;49m\u001b[39mtdvp\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mTrue\u001b[39;49;00m, \u001b[39m\"\u001b[39;49m\u001b[39mscipy\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mTrue\u001b[39;49;00m, \u001b[39m\"\u001b[39;49m\u001b[39mgradient_descent\u001b[39;49m\u001b[39m\"\u001b[39;49m: \u001b[39mFalse\u001b[39;49;00m},\n\u001b[1;32m      6\u001b[0m         path\u001b[39m=\u001b[39;49m\u001b[39mf\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m./results/n\u001b[39;49m\u001b[39m{\u001b[39;49;00mn\u001b[39m}\u001b[39;49;00m\u001b[39mresults_p3_5.p\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m      7\u001b[0m         tollarance\u001b[39m=\u001b[39;49m\u001b[39m1e-2\u001b[39;49m,\n\u001b[1;32m      8\u001b[0m         max_iter\u001b[39m=\u001b[39;49m\u001b[39m10\u001b[39;49m,\n\u001b[1;32m      9\u001b[0m         max_steps\u001b[39m=\u001b[39;49m\u001b[39m3000\u001b[39;49m,\n\u001b[1;32m     10\u001b[0m         tdvp_range\u001b[39m=\u001b[39;49m\u001b[39m10\u001b[39;49m,\n\u001b[1;32m     11\u001b[0m     )\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/benchmark.py:496\u001b[0m, in \u001b[0;36mbench_frame\u001b[0;34m(input, p, optimizers, tollarance, max_iter, max_steps, tdvp_range, auto_save, path, print_msg)\u001b[0m\n\u001b[1;32m    492\u001b[0m \u001b[39mif\u001b[39;00m print_msg:\n\u001b[1;32m    493\u001b[0m     \u001b[39mprint\u001b[39m(\n\u001b[1;32m    494\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mRunning benchmark on \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mlen\u001b[39m(\u001b[39minput\u001b[39m)\u001b[39m}\u001b[39;00m\u001b[39m instances with optimizers \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mtuple\u001b[39m(key \u001b[39mfor\u001b[39;00m key,value \u001b[39min\u001b[39;00m optimizers\u001b[39m.\u001b[39mitems() \u001b[39mif\u001b[39;00m value)\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[1;32m    495\u001b[0m     )\n\u001b[0;32m--> 496\u001b[0m out \u001b[39m=\u001b[39m \u001b[39minput\u001b[39;49m\u001b[39m.\u001b[39;49mapply(\n\u001b[1;32m    497\u001b[0m     \u001b[39mlambda\u001b[39;49;00m x: bench_series(\n\u001b[1;32m    498\u001b[0m         x,\n\u001b[1;32m    499\u001b[0m         optimizers\u001b[39m=\u001b[39;49moptimizers,\n\u001b[1;32m    500\u001b[0m         tollarance\u001b[39m=\u001b[39;49mtollarance,\n\u001b[1;32m    501\u001b[0m         max_iter\u001b[39m=\u001b[39;49mmax_iter,\n\u001b[1;32m    502\u001b[0m         max_steps\u001b[39m=\u001b[39;49mmax_steps,\n\u001b[1;32m    503\u001b[0m         tdvp_range\u001b[39m=\u001b[39;49mtdvp_range,\n\u001b[1;32m    504\u001b[0m         auto_save\u001b[39m=\u001b[39;49mauto_save,\n\u001b[1;32m    505\u001b[0m         path\u001b[39m=\u001b[39;49mpath,\n\u001b[1;32m    506\u001b[0m         print_msg\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[1;32m    507\u001b[0m     ),  \u001b[39m# type: ignore\u001b[39;49;00m\n\u001b[1;32m    508\u001b[0m     axis\u001b[39m=\u001b[39;49m\u001b[39m1\u001b[39;49m,\n\u001b[1;32m    509\u001b[0m )\n\u001b[1;32m    510\u001b[0m \u001b[39m# type: ignore\u001b[39;00m\n\u001b[1;32m    511\u001b[0m \u001b[39mif\u001b[39;00m path \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/pandas/core/frame.py:9555\u001b[0m, in \u001b[0;36mDataFrame.apply\u001b[0;34m(self, func, axis, raw, result_type, args, **kwargs)\u001b[0m\n\u001b[1;32m   9544\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mpandas\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mcore\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mapply\u001b[39;00m \u001b[39mimport\u001b[39;00m frame_apply\n\u001b[1;32m   9546\u001b[0m op \u001b[39m=\u001b[39m frame_apply(\n\u001b[1;32m   9547\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m   9548\u001b[0m     func\u001b[39m=\u001b[39mfunc,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   9553\u001b[0m     kwargs\u001b[39m=\u001b[39mkwargs,\n\u001b[1;32m   9554\u001b[0m )\n\u001b[0;32m-> 9555\u001b[0m \u001b[39mreturn\u001b[39;00m op\u001b[39m.\u001b[39;49mapply()\u001b[39m.\u001b[39m__finalize__(\u001b[39mself\u001b[39m, method\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mapply\u001b[39m\u001b[39m\"\u001b[39m)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/pandas/core/apply.py:746\u001b[0m, in \u001b[0;36mFrameApply.apply\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    743\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mraw:\n\u001b[1;32m    744\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mapply_raw()\n\u001b[0;32m--> 746\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mapply_standard()\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/pandas/core/apply.py:873\u001b[0m, in \u001b[0;36mFrameApply.apply_standard\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    872\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mapply_standard\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 873\u001b[0m     results, res_index \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mapply_series_generator()\n\u001b[1;32m    875\u001b[0m     \u001b[39m# wrap results\u001b[39;00m\n\u001b[1;32m    876\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mwrap_results(results, res_index)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/pandas/core/apply.py:889\u001b[0m, in \u001b[0;36mFrameApply.apply_series_generator\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    886\u001b[0m \u001b[39mwith\u001b[39;00m option_context(\u001b[39m\"\u001b[39m\u001b[39mmode.chained_assignment\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mNone\u001b[39;00m):\n\u001b[1;32m    887\u001b[0m     \u001b[39mfor\u001b[39;00m i, v \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(series_gen):\n\u001b[1;32m    888\u001b[0m         \u001b[39m# ignore SettingWithCopy here in case the user mutates\u001b[39;00m\n\u001b[0;32m--> 889\u001b[0m         results[i] \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mf(v)\n\u001b[1;32m    890\u001b[0m         \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(results[i], ABCSeries):\n\u001b[1;32m    891\u001b[0m             \u001b[39m# If we have a view on v, we need to make a copy because\u001b[39;00m\n\u001b[1;32m    892\u001b[0m             \u001b[39m#  series_generator will swap out the underlying data\u001b[39;00m\n\u001b[1;32m    893\u001b[0m             results[i] \u001b[39m=\u001b[39m results[i]\u001b[39m.\u001b[39mcopy(deep\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m)\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/benchmark.py:497\u001b[0m, in \u001b[0;36mbench_frame.<locals>.<lambda>\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m    492\u001b[0m \u001b[39mif\u001b[39;00m print_msg:\n\u001b[1;32m    493\u001b[0m     \u001b[39mprint\u001b[39m(\n\u001b[1;32m    494\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mRunning benchmark on \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mlen\u001b[39m(\u001b[39minput\u001b[39m)\u001b[39m}\u001b[39;00m\u001b[39m instances with optimizers \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39mtuple\u001b[39m(key \u001b[39mfor\u001b[39;00m key,value \u001b[39min\u001b[39;00m optimizers\u001b[39m.\u001b[39mitems() \u001b[39mif\u001b[39;00m value)\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m\n\u001b[1;32m    495\u001b[0m     )\n\u001b[1;32m    496\u001b[0m out \u001b[39m=\u001b[39m \u001b[39minput\u001b[39m\u001b[39m.\u001b[39mapply(\n\u001b[0;32m--> 497\u001b[0m     \u001b[39mlambda\u001b[39;00m x: bench_series(\n\u001b[1;32m    498\u001b[0m         x,\n\u001b[1;32m    499\u001b[0m         optimizers\u001b[39m=\u001b[39;49moptimizers,\n\u001b[1;32m    500\u001b[0m         tollarance\u001b[39m=\u001b[39;49mtollarance,\n\u001b[1;32m    501\u001b[0m         max_iter\u001b[39m=\u001b[39;49mmax_iter,\n\u001b[1;32m    502\u001b[0m         max_steps\u001b[39m=\u001b[39;49mmax_steps,\n\u001b[1;32m    503\u001b[0m         tdvp_range\u001b[39m=\u001b[39;49mtdvp_range,\n\u001b[1;32m    504\u001b[0m         auto_save\u001b[39m=\u001b[39;49mauto_save,\n\u001b[1;32m    505\u001b[0m         path\u001b[39m=\u001b[39;49mpath,\n\u001b[1;32m    506\u001b[0m         print_msg\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[1;32m    507\u001b[0m     ),  \u001b[39m# type: ignore\u001b[39;00m\n\u001b[1;32m    508\u001b[0m     axis\u001b[39m=\u001b[39m\u001b[39m1\u001b[39m,\n\u001b[1;32m    509\u001b[0m )\n\u001b[1;32m    510\u001b[0m \u001b[39m# type: ignore\u001b[39;00m\n\u001b[1;32m    511\u001b[0m \u001b[39mif\u001b[39;00m path \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/benchmark.py:453\u001b[0m, in \u001b[0;36mbench_series\u001b[0;34m(input, p, optimizers, tollarance, max_iter, max_steps, tdvp_range, auto_save, path, print_msg)\u001b[0m\n\u001b[1;32m    440\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mbench_series\u001b[39m(\n\u001b[1;32m    441\u001b[0m     \u001b[39minput\u001b[39m: pd\u001b[39m.\u001b[39mSeries,\n\u001b[1;32m    442\u001b[0m     p: \u001b[39mint\u001b[39m \u001b[39m|\u001b[39m \u001b[39mNone\u001b[39;00m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    450\u001b[0m     print_msg: \u001b[39mbool\u001b[39m \u001b[39m=\u001b[39m \u001b[39mTrue\u001b[39;00m,\n\u001b[1;32m    451\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m pd\u001b[39m.\u001b[39mDataFrame \u001b[39m|\u001b[39m pd\u001b[39m.\u001b[39mSeries:\n\u001b[1;32m    452\u001b[0m     \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 453\u001b[0m         out \u001b[39m=\u001b[39m bench_instance(\n\u001b[1;32m    454\u001b[0m             \u001b[39minput\u001b[39;49m[\u001b[39m\"\u001b[39;49m\u001b[39minstance\u001b[39;49m\u001b[39m\"\u001b[39;49m],\n\u001b[1;32m    455\u001b[0m             p\u001b[39m=\u001b[39;49m\u001b[39minput\u001b[39;49m\u001b[39m.\u001b[39;49mname[\u001b[39m0\u001b[39;49m],  \u001b[39m# type: ignore\u001b[39;49;00m\n\u001b[1;32m    456\u001b[0m             optimizers\u001b[39m=\u001b[39;49moptimizers,\n\u001b[1;32m    457\u001b[0m             tollarance\u001b[39m=\u001b[39;49mtollarance,\n\u001b[1;32m    458\u001b[0m             max_iter\u001b[39m=\u001b[39;49mmax_iter,\n\u001b[1;32m    459\u001b[0m             max_steps\u001b[39m=\u001b[39;49mmax_steps,\n\u001b[1;32m    460\u001b[0m             tdvp_range\u001b[39m=\u001b[39;49mtdvp_range,\n\u001b[1;32m    461\u001b[0m             auto_save\u001b[39m=\u001b[39;49mauto_save,\n\u001b[1;32m    462\u001b[0m             path\u001b[39m=\u001b[39;49mpath,\n\u001b[1;32m    463\u001b[0m             print_msg\u001b[39m=\u001b[39;49m\u001b[39mFalse\u001b[39;49;00m,\n\u001b[1;32m    464\u001b[0m         )\n\u001b[1;32m    465\u001b[0m     \u001b[39mexcept\u001b[39;00m LinAlgError:\n\u001b[1;32m    466\u001b[0m         out \u001b[39m=\u001b[39m \u001b[39minput\u001b[39m\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/benchmark.py:350\u001b[0m, in \u001b[0;36mbench_instance\u001b[0;34m(input, p, optimizers, tollarance, max_iter, max_steps, tdvp_range, auto_save, path, print_msg)\u001b[0m\n\u001b[1;32m    348\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m    349\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39m\"\u001b[39m\u001b[39moptimizing with tdvp\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m--> 350\u001b[0m     tdvp_res \u001b[39m=\u001b[39m tdvp_optimize_qaoa(\n\u001b[1;32m    351\u001b[0m         qaoa\u001b[39m=\u001b[39;49mqaoa,\n\u001b[1;32m    352\u001b[0m         delta_0\u001b[39m=\u001b[39;49mdelta_0,\n\u001b[1;32m    353\u001b[0m         Delta\u001b[39m=\u001b[39;49m\u001b[39m100\u001b[39;49m,\n\u001b[1;32m    354\u001b[0m         grad_tol\u001b[39m=\u001b[39;49mtollarance,\n\u001b[1;32m    355\u001b[0m         int_mode\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39mRK45\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m    356\u001b[0m         max_iter\u001b[39m=\u001b[39;49mmax_iter,\n\u001b[1;32m    357\u001b[0m         max_steps\u001b[39m=\u001b[39;49mmax_steps,\n\u001b[1;32m    358\u001b[0m     )\n\u001b[1;32m    359\u001b[0m \u001b[39mexcept\u001b[39;00m LinAlgError:\n\u001b[1;32m    360\u001b[0m     \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mLinAlgError at p=\u001b[39m\u001b[39m{\u001b[39;00mp\u001b[39m}\u001b[39;00m\u001b[39m and instance \u001b[39m\u001b[39m{\u001b[39;00m\u001b[39minput\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/qaoa_and_tdvp.py:1193\u001b[0m, in \u001b[0;36mtdvp_optimize_qaoa\u001b[0;34m(qaoa, delta_0, Delta, rhs_mode, int_mode, grad_tol, max_iter, max_steps)\u001b[0m\n\u001b[1;32m   1191\u001b[0m \u001b[39mwhile\u001b[39;00m go_on \u001b[39mand\u001b[39;00m \u001b[39miter\u001b[39m \u001b[39m<\u001b[39m max_iter:\n\u001b[1;32m   1192\u001b[0m     \u001b[39miter\u001b[39m \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[0;32m-> 1193\u001b[0m     int_result \u001b[39m=\u001b[39m integrate\u001b[39m.\u001b[39;49msolve_ivp(\n\u001b[1;32m   1194\u001b[0m         fun\u001b[39m=\u001b[39;49mtdvp_rhs,\n\u001b[1;32m   1195\u001b[0m         t_span\u001b[39m=\u001b[39;49m(t_0, t_1),\n\u001b[1;32m   1196\u001b[0m         y0\u001b[39m=\u001b[39;49mdelta,\n\u001b[1;32m   1197\u001b[0m         method\u001b[39m=\u001b[39;49mint_mode,\n\u001b[1;32m   1198\u001b[0m         \u001b[39m# t_eval=eval_points,\u001b[39;49;00m\n\u001b[1;32m   1199\u001b[0m         events\u001b[39m=\u001b[39;49m[\n\u001b[1;32m   1200\u001b[0m             tdvp_terminal, tdvp_max_steps\n\u001b[1;32m   1201\u001b[0m         ],\n\u001b[1;32m   1202\u001b[0m     )\n\u001b[1;32m   1203\u001b[0m     nfev \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m int_result\u001b[39m.\u001b[39mnfev\n\u001b[1;32m   1204\u001b[0m     times\u001b[39m.\u001b[39mextend(int_result\u001b[39m.\u001b[39mt)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/integrate/_ivp/ivp.py:614\u001b[0m, in \u001b[0;36msolve_ivp\u001b[0;34m(fun, t_span, y0, method, t_eval, dense_output, events, vectorized, args, **options)\u001b[0m\n\u001b[1;32m    611\u001b[0m \u001b[39mif\u001b[39;00m sol \u001b[39mis\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n\u001b[1;32m    612\u001b[0m     sol \u001b[39m=\u001b[39m solver\u001b[39m.\u001b[39mdense_output()\n\u001b[0;32m--> 614\u001b[0m root_indices, roots, terminate \u001b[39m=\u001b[39m handle_events(\n\u001b[1;32m    615\u001b[0m     sol, events, active_events, is_terminal, t_old, t)\n\u001b[1;32m    617\u001b[0m \u001b[39mfor\u001b[39;00m e, te \u001b[39min\u001b[39;00m \u001b[39mzip\u001b[39m(root_indices, roots):\n\u001b[1;32m    618\u001b[0m     t_events[e]\u001b[39m.\u001b[39mappend(te)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/integrate/_ivp/ivp.py:108\u001b[0m, in \u001b[0;36mhandle_events\u001b[0;34m(sol, events, active_events, is_terminal, t_old, t)\u001b[0m\n\u001b[1;32m     81\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mhandle_events\u001b[39m(sol, events, active_events, is_terminal, t_old, t):\n\u001b[1;32m     82\u001b[0m     \u001b[39m\"\"\"Helper function to handle events.\u001b[39;00m\n\u001b[1;32m     83\u001b[0m \n\u001b[1;32m     84\u001b[0m \u001b[39m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    106\u001b[0m \u001b[39m        Whether a terminal event occurred.\u001b[39;00m\n\u001b[1;32m    107\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 108\u001b[0m     roots \u001b[39m=\u001b[39m [solve_event_equation(events[event_index], sol, t_old, t)\n\u001b[1;32m    109\u001b[0m              \u001b[39mfor\u001b[39;00m event_index \u001b[39min\u001b[39;00m active_events]\n\u001b[1;32m    111\u001b[0m     roots \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(roots)\n\u001b[1;32m    113\u001b[0m     \u001b[39mif\u001b[39;00m np\u001b[39m.\u001b[39many(is_terminal[active_events]):\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/integrate/_ivp/ivp.py:108\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m     81\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mhandle_events\u001b[39m(sol, events, active_events, is_terminal, t_old, t):\n\u001b[1;32m     82\u001b[0m     \u001b[39m\"\"\"Helper function to handle events.\u001b[39;00m\n\u001b[1;32m     83\u001b[0m \n\u001b[1;32m     84\u001b[0m \u001b[39m    Parameters\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    106\u001b[0m \u001b[39m        Whether a terminal event occurred.\u001b[39;00m\n\u001b[1;32m    107\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 108\u001b[0m     roots \u001b[39m=\u001b[39m [solve_event_equation(events[event_index], sol, t_old, t)\n\u001b[1;32m    109\u001b[0m              \u001b[39mfor\u001b[39;00m event_index \u001b[39min\u001b[39;00m active_events]\n\u001b[1;32m    111\u001b[0m     roots \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39masarray(roots)\n\u001b[1;32m    113\u001b[0m     \u001b[39mif\u001b[39;00m np\u001b[39m.\u001b[39many(is_terminal[active_events]):\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/integrate/_ivp/ivp.py:77\u001b[0m, in \u001b[0;36msolve_event_equation\u001b[0;34m(event, sol, t_old, t)\u001b[0m\n\u001b[1;32m     54\u001b[0m \u001b[39m\"\"\"Solve an equation corresponding to an ODE event.\u001b[39;00m\n\u001b[1;32m     55\u001b[0m \n\u001b[1;32m     56\u001b[0m \u001b[39mThe equation is ``event(t, y(t)) = 0``, here ``y(t)`` is known from an\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     74\u001b[0m \u001b[39m    Found solution.\u001b[39;00m\n\u001b[1;32m     75\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m     76\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mscipy\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39moptimize\u001b[39;00m \u001b[39mimport\u001b[39;00m brentq\n\u001b[0;32m---> 77\u001b[0m \u001b[39mreturn\u001b[39;00m brentq(\u001b[39mlambda\u001b[39;49;00m t: event(t, sol(t)), t_old, t,\n\u001b[1;32m     78\u001b[0m               xtol\u001b[39m=\u001b[39;49m\u001b[39m4\u001b[39;49m \u001b[39m*\u001b[39;49m EPS, rtol\u001b[39m=\u001b[39;49m\u001b[39m4\u001b[39;49m \u001b[39m*\u001b[39;49m EPS)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/optimize/_zeros_py.py:783\u001b[0m, in \u001b[0;36mbrentq\u001b[0;34m(f, a, b, args, xtol, rtol, maxiter, full_output, disp)\u001b[0m\n\u001b[1;32m    781\u001b[0m \u001b[39mif\u001b[39;00m rtol \u001b[39m<\u001b[39m _rtol:\n\u001b[1;32m    782\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mrtol too small (\u001b[39m\u001b[39m%g\u001b[39;00m\u001b[39m < \u001b[39m\u001b[39m%g\u001b[39;00m\u001b[39m)\u001b[39m\u001b[39m\"\u001b[39m \u001b[39m%\u001b[39m (rtol, _rtol))\n\u001b[0;32m--> 783\u001b[0m r \u001b[39m=\u001b[39m _zeros\u001b[39m.\u001b[39;49m_brentq(f, a, b, xtol, rtol, maxiter, args, full_output, disp)\n\u001b[1;32m    784\u001b[0m \u001b[39mreturn\u001b[39;00m results_c(full_output, r)\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/scipy/integrate/_ivp/ivp.py:77\u001b[0m, in \u001b[0;36msolve_event_equation.<locals>.<lambda>\u001b[0;34m(t)\u001b[0m\n\u001b[1;32m     54\u001b[0m \u001b[39m\"\"\"Solve an equation corresponding to an ODE event.\u001b[39;00m\n\u001b[1;32m     55\u001b[0m \n\u001b[1;32m     56\u001b[0m \u001b[39mThe equation is ``event(t, y(t)) = 0``, here ``y(t)`` is known from an\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     74\u001b[0m \u001b[39m    Found solution.\u001b[39;00m\n\u001b[1;32m     75\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m     76\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mscipy\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39moptimize\u001b[39;00m \u001b[39mimport\u001b[39;00m brentq\n\u001b[0;32m---> 77\u001b[0m \u001b[39mreturn\u001b[39;00m brentq(\u001b[39mlambda\u001b[39;00m t: event(t, sol(t)), t_old, t,\n\u001b[1;32m     78\u001b[0m               xtol\u001b[39m=\u001b[39m\u001b[39m4\u001b[39m \u001b[39m*\u001b[39m EPS, rtol\u001b[39m=\u001b[39m\u001b[39m4\u001b[39m \u001b[39m*\u001b[39m EPS)\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/qaoa_and_tdvp.py:1140\u001b[0m, in \u001b[0;36mtdvp_optimize_qaoa.<locals>.tdvp_terminal\u001b[0;34m(t, x)\u001b[0m\n\u001b[1;32m   1138\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mtdvp_terminal\u001b[39m(t, x) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mfloat\u001b[39m:\n\u001b[1;32m   1139\u001b[0m     \u001b[39mreturn\u001b[39;00m (\n\u001b[0;32m-> 1140\u001b[0m         linalg\u001b[39m.\u001b[39mnorm(tdvp_rhs(t, x)) \u001b[39m-\u001b[39m grad_tol\n\u001b[1;32m   1141\u001b[0m     )\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/qaoa_and_tdvp.py:1120\u001b[0m, in \u001b[0;36mtdvp_optimize_qaoa.<locals>.tdvp_rhs\u001b[0;34m(t, x)\u001b[0m\n\u001b[1;32m   1118\u001b[0m rhs_step \u001b[39m+\u001b[39m\u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m   1119\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mrhs step \u001b[39m\u001b[39m{\u001b[39;00mrhs_step\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m, end\u001b[39m=\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m\\r\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[0;32m-> 1120\u001b[0m \u001b[39mreturn\u001b[39;00m qaoa_tdvp_rhs(t, x, qaoa)\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/qaoa_and_tdvp.py:999\u001b[0m, in \u001b[0;36mqaoa_tdvp_rhs\u001b[0;34m(t, x, qaoa)\u001b[0m\n\u001b[1;32m    987\u001b[0m \u001b[39m\"\"\"right hand side of linear equation system of tdvp. In the right format for the scipy solvers.\u001b[39;00m\n\u001b[1;32m    988\u001b[0m \u001b[39mUses the qaoa class to calculate the gradient and gram matrix.\u001b[39;00m\n\u001b[1;32m    989\u001b[0m \u001b[39mInverts the gram matrix using the scipy linalg.inv.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    996\u001b[0m \u001b[39m    NDArray: the matrix defining the RHS of the equation\u001b[39;00m\n\u001b[1;32m    997\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m    998\u001b[0m _ \u001b[39m=\u001b[39m t\n\u001b[0;32m--> 999\u001b[0m inv_real_gram \u001b[39m=\u001b[39m linalg\u001b[39m.\u001b[39minv(\u001b[39m2\u001b[39m \u001b[39m*\u001b[39m np\u001b[39m.\u001b[39mreal(qaoa\u001b[39m.\u001b[39;49mgram(x)))\n\u001b[1;32m   1000\u001b[0m real_grad \u001b[39m=\u001b[39m \u001b[39m2\u001b[39m \u001b[39m*\u001b[39m np\u001b[39m.\u001b[39mreal(qaoa\u001b[39m.\u001b[39mgrad(x))\n\u001b[1;32m   1001\u001b[0m \u001b[39mreturn\u001b[39;00m np\u001b[39m.\u001b[39marray(\u001b[39m-\u001b[39minv_real_gram \u001b[39m*\u001b[39m real_grad\u001b[39m.\u001b[39mT)\u001b[39m.\u001b[39mflatten()\n",
            "File \u001b[0;32m~/Documents/Uni/Bachelorarbeit /TDVP_and_QAOA/qaoa_and_tdvp.py:552\u001b[0m, in \u001b[0;36mQAOA.gram\u001b[0;34m(self, delta)\u001b[0m\n\u001b[1;32m    549\u001b[0m gram \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39mzeros((\u001b[39m2\u001b[39m \u001b[39m*\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mp, \u001b[39m2\u001b[39m \u001b[39m*\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mp), dtype\u001b[39m=\u001b[39mnp\u001b[39m.\u001b[39mcomplex128)\n\u001b[1;32m    550\u001b[0m \u001b[39m# populate the upper triangular part and diagonal of the gram matrix using self._Gij\u001b[39;00m\n\u001b[1;32m    551\u001b[0m \u001b[39m# np.triu_indices returns the indices of the upper triangular part of a matrix\u001b[39;00m\n\u001b[0;32m--> 552\u001b[0m gram[np\u001b[39m.\u001b[39mtriu_indices(\u001b[39m2\u001b[39m \u001b[39m*\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mp)] \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mmapping(\n\u001b[1;32m    553\u001b[0m     task\u001b[39m=\u001b[39;49m\u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49m_Gij,\n\u001b[1;32m    554\u001b[0m     values\u001b[39m=\u001b[39;49m\u001b[39mlist\u001b[39;49m(\n\u001b[1;32m    555\u001b[0m         combinations_with_replacement(\u001b[39mrange\u001b[39;49m(\u001b[39m2\u001b[39;49m \u001b[39m*\u001b[39;49m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mp), r\u001b[39m=\u001b[39;49m\u001b[39m2\u001b[39;49m)\n\u001b[1;32m    556\u001b[0m     ),  \u001b[39m# all combinations of indices, including the diagonal\u001b[39;49;00m\n\u001b[1;32m    557\u001b[0m     task_args\u001b[39m=\u001b[39;49m(delta,),\n\u001b[1;32m    558\u001b[0m )\n\u001b[1;32m    559\u001b[0m \u001b[39m# use that the gram matrix is hermetian\u001b[39;00m\n\u001b[1;32m    560\u001b[0m \u001b[39m# np.tril_indices returns the indices of the lower triangular part of a matrix, -1 to exclude the diagonal\u001b[39;00m\n\u001b[1;32m    561\u001b[0m gram \u001b[39m=\u001b[39m gram \u001b[39m+\u001b[39m np\u001b[39m.\u001b[39mconj(gram\u001b[39m.\u001b[39mT) \u001b[39m-\u001b[39m np\u001b[39m.\u001b[39mdiag(gram\u001b[39m.\u001b[39mdiagonal())\n",
            "File \u001b[0;32m~/anaconda3/envs/qutip-env/lib/python3.10/site-packages/qutip/parallel.py:228\u001b[0m, in \u001b[0;36mparallel_map\u001b[0;34m(task, values, task_args, task_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m    226\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mKeyboardInterrupt\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n\u001b[1;32m    227\u001b[0m     os\u001b[39m.\u001b[39menviron[\u001b[39m'\u001b[39m\u001b[39mQUTIP_IN_PARALLEL\u001b[39m\u001b[39m'\u001b[39m] \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mFALSE\u001b[39m\u001b[39m'\u001b[39m\n\u001b[0;32m--> 228\u001b[0m     pool\u001b[39m.\u001b[39mterminate()\n\u001b[1;32m    229\u001b[0m     pool\u001b[39m.\u001b[39mjoin()\n\u001b[1;32m    230\u001b[0m     \u001b[39mraise\u001b[39;00m e\n",
            "\u001b[0;31mUnboundLocalError\u001b[0m: local variable 'pool' referenced before assignment"
          ]
        }
      ],
      "source": [
        "for n in [4,5]:\n",
        "    print(\"n=\",n)\n",
        "    bench_frame(\n",
        "        load_instances(n,p_min=1,p_max=5),\n",
        "        optimizers={\"tdvp\": True, \"scipy\": True, \"gradient_descent\": False},\n",
        "        path=f\"./results/n{n}results_p3_5.p\",\n",
        "        tollarance=1e-2,\n",
        "        max_iter=10,\n",
        "        max_steps=3000,\n",
        "        tdvp_range=10,\n",
        "    )\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": []
    }
  ],
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      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
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