notebook_02_lhc_optics_match.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3aa2467b-425b-4b68-8aa7-844eed6b6cf6",
   "metadata": {},
   "source": [
    "# Optics calculation and matching for a large ring (LHC) - part 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "70b7e0e3-b7e0-436a-bcd3-4b55548e6166",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib widget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d6de4eb3-7830-4527-91ee-15d26b640006",
   "metadata": {},
   "outputs": [],
   "source": [
    "import xtrack as xt\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e92dbde7-6c0c-43ff-bd66-e501c36f0935",
   "metadata": {},
   "source": [
    "### Load LHC model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7b8399d3-714e-4cf5-a277-1206c8597bba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4f85aa0d17db449aaa75bd718f7eaf5e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading line from dict:   0%|          | 0/29009 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done loading line from dict.           \n"
     ]
    }
   ],
   "source": [
    "collider = xt.Multiline.from_json(\"hllhc15_collider_thick.json\")\n",
    "collider.vars.load_madx(\"opt_round_150_1500.madx\")\n",
    "\n",
    "collider.build_trackers()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b9246f9-0efb-4d03-b8e9-a6301e030ff9",
   "metadata": {},
   "source": [
    "### Initial twiss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9bfdce19-8be5-4486-a154-8c60c19d6674",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw0 = collider.lhcb1.twiss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bd049a84-21c9-47c0-be41-1d62a6d27985",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TwissTable: 9 rows, 7 cols\n",
       "name            betx          bety           mux           muy             x             y\n",
       "ip1             0.15          0.15             0             0             0             0\n",
       "ip2               10            10       8.23376        7.6927   -1.8097e-17  -1.75964e-35\n",
       "ip3          121.567       218.584       15.9494       15.4503   4.41365e-16   4.75465e-35\n",
       "ip4           236.18       306.197        23.507       22.3832  -1.52091e-17   1.30816e-35\n",
       "ip5             0.15          0.15       30.9305       29.9889   6.20481e-18  -1.70714e-36\n",
       "ip6          273.434        183.74       38.7487       37.3936   6.75034e-16   1.55795e-35\n",
       "ip7          120.813       149.431       46.3524       44.5934  -4.78578e-16    7.5643e-35\n",
       "ip8              1.5           1.5       54.3432       52.2729  -5.55207e-17  -8.26294e-36\n",
       "ip1.l1          0.15          0.15         62.31         60.32  -1.70479e-17  -6.89158e-35"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect IPS\n",
    "tw0.rows['ip.*'].cols['betx bety mux muy x y']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f144e5e3-1ac0-43e4-9615-74682bb06408",
   "metadata": {},
   "source": [
    "### Prepare for optics matching: set limits and steps for all circuits"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "35858be9-dfac-4ecb-a112-315a9c0c671a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import lhc_match as lm\n",
    "lm.set_var_limits_and_steps(collider)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "494f98c7-eee7-4485-a1e0-4c07c02e1b70",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'step': 1e-06, 'limits': (0.00020557714282348692, 0.0068525714274495645)}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Inspect for one circuit\n",
    "collider.vars.vary_default['kq4.l2b2']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "889aabc1-094f-4f35-95d0-6b2bc74b3e75",
   "metadata": {},
   "source": [
    "### Twiss on a part of the machine (bidirectional)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f85d5a19-538c-40b4-9a40-c5d69c75024f",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw_81_12 = collider.lhcb1.twiss(start='ip8', end='ip2', init_at='ip1',\n",
    "                                betx=0.15, bety=0.15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3a16afbc-ec50-44be-9c1d-008e98e79c78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x331895550>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ceabc7214b9f490d87b689608d5a4e0b",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(tw_81_12.s, tw_81_12.betx)\n",
    "plt.plot(tw_81_12.s, tw_81_12.bety)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b102928b-a8e1-4e06-b179-dae25bfa9ff5",
   "metadata": {},
   "source": [
    "### Telescopic rematch of IP1 using IP2 and IP8"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02a3e65d-f1a6-4fca-84ee-2d91e1853516",
   "metadata": {},
   "source": [
    "#### Match left side"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3a9de07e-8698-4119-a3b4-bfba840d6862",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt = collider.lhcb1.match(\n",
    "    solve=False,\n",
    "    default_tol={None: 1e-8, 'betx': 1e-6, 'bety': 1e-6, 'alfx': 1e-6, 'alfy': 1e-6},\n",
    "    start='s.ds.l8.b1', end='ip1',\n",
    "    init=tw0, init_at=xt.START,\n",
    "    vary=[\n",
    "        # Only IR8 quadrupoles including DS\n",
    "        xt.VaryList(['kq6.l8b1', 'kq7.l8b1', 'kq8.l8b1', 'kq9.l8b1', 'kq10.l8b1', \n",
    "            'kqtl11.l8b1', 'kqt12.l8b1', 'kqt13.l8b1',\n",
    "            'kq4.l8b1', 'kq5.l8b1', 'kq4.r8b1', 'kq5.r8b1', \n",
    "            'kq6.r8b1', 'kq7.r8b1', 'kq8.r8b1', 'kq9.r8b1', \n",
    "            'kq10.r8b1', 'kqtl11.r8b1', 'kqt12.r8b1', 'kqt13.r8b1'])],\n",
    "    targets=[\n",
    "        xt.TargetSet(at='ip8', tars=('betx', 'bety', 'alfx', 'alfy', 'dx', 'dpx'), value=tw0),\n",
    "        xt.TargetSet(at='ip1', betx=0.15, bety=0.10, alfx=0, alfy=0, dx=0, dpx=0),\n",
    "        xt.TargetRelPhaseAdvance('mux', value = tw0['mux', 'ip1.l1'] - tw0['mux', 's.ds.l8.b1']),\n",
    "        xt.TargetRelPhaseAdvance('muy', value = tw0['muy', 'ip1.l1'] - tw0['muy', 's.ds.l8.b1']), \n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ae1bc9c8-822f-491e-b2fc-3870966b6009",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target status:               alty = 5.0000e-02              \n",
      "id state tag      tol_met       residue   current_val    target_val description                                 \n",
      "0  ON    ip8_betx    True  -3.97872e-10           1.5           1.5 ('betx', 'ip8'), val=1.5, tol=1e-06, wei ...\n",
      "1  ON    ip8_bety    True  -5.73914e-11           1.5           1.5 ('bety', 'ip8'), val=1.5, tol=1e-06, wei ...\n",
      "2  ON    ip8_alfx    True  -1.43987e-10   2.21743e-07   2.21887e-07 ('alfx', 'ip8'), val=2.21887e-07, tol=1e ...\n",
      "3  ON    ip8_alfy    True   1.85598e-12   2.15516e-07   2.15514e-07 ('alfy', 'ip8'), val=2.15514e-07, tol=1e ...\n",
      "4  ON    ip8_dx      True   9.97406e-10   1.71316e-09   7.15756e-10 ('dx', 'ip8'), val=7.15756e-10, tol=1e-0 ...\n",
      "5  ON    ip8_dpx     True   7.09237e-10   8.33401e-10   1.24164e-10 ('dpx', 'ip8'), val=1.24164e-10, tol=1e- ...\n",
      "6  ON    ip1_betx    True  -5.33938e-08          0.15          0.15 ('betx', 'ip1'), val=0.15, tol=1e-06, we ...\n",
      "7  ON    ip1_bety   False          0.05          0.15           0.1 ('bety', 'ip1'), val=0.1, tol=1e-06, wei ...\n",
      "8  ON    ip1_alfx    True    4.0091e-07    4.0091e-07             0 ('alfx', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "9  ON    ip1_alfy    True   1.73104e-07   1.73104e-07             0 ('alfy', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "10 ON    ip1_dx      True  -3.37519e-10  -3.37519e-10             0 ('dx', 'ip1'), val=0, tol=1e-08, weight= ...\n",
      "11 ON    ip1_dpx     True    5.0477e-09    5.0477e-09             0 ('dpx', 'ip1'), val=0, tol=1e-08, weight ...\n",
      "12 ON                True  -2.67079e-10       9.39479       9.39479 mux(__ele_stop__ - __ele_start__), val=9 ...\n",
      "13 ON                True   7.33422e-11       9.53049       9.53049 muy(__ele_stop__ - __ele_start__), val=9 ...\n"
     ]
    }
   ],
   "source": [
    "opt.target_status()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e07245a6-44cc-45dd-86d9-8954bbcf8e02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                             \n",
      "Optimize - start penalty: 0.05                              \n",
      "Matching: model call n. 445 penalty = 1.8373e-07              \n",
      "Optimize - end penalty:  1.83728e-07                            \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<xtrack.match.OptimizeLine at 0x33afbfe50>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt.step(40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "40b33b64-4540-44b5-9903-1c0385b82e00",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target status:               enalty = 1.8373e-07              \n",
      "id state tag      tol_met       residue   current_val    target_val description                                 \n",
      "0  ON    ip8_betx    True  -5.60544e-10           1.5           1.5 ('betx', 'ip8'), val=1.5, tol=1e-06, wei ...\n",
      "1  ON    ip8_bety    True   1.96854e-09           1.5           1.5 ('bety', 'ip8'), val=1.5, tol=1e-06, wei ...\n",
      "2  ON    ip8_alfx    True   1.60677e-10   2.22048e-07   2.21887e-07 ('alfx', 'ip8'), val=2.21887e-07, tol=1e ...\n",
      "3  ON    ip8_alfy    True    1.3808e-11   2.15528e-07   2.15514e-07 ('alfy', 'ip8'), val=2.15514e-07, tol=1e ...\n",
      "4  ON    ip8_dx      True  -1.03333e-10   6.12423e-10   7.15756e-10 ('dx', 'ip8'), val=7.15756e-10, tol=1e-0 ...\n",
      "5  ON    ip8_dpx     True  -1.46131e-10  -2.19672e-11   1.24164e-10 ('dpx', 'ip8'), val=1.24164e-10, tol=1e- ...\n",
      "6  ON    ip1_betx    True   2.80427e-10          0.15          0.15 ('betx', 'ip1'), val=0.15, tol=1e-06, we ...\n",
      "7  ON    ip1_bety    True  -6.16205e-11           0.1           0.1 ('bety', 'ip1'), val=0.1, tol=1e-06, wei ...\n",
      "8  ON    ip1_alfx    True  -2.95671e-10  -2.95671e-10             0 ('alfx', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "9  ON    ip1_alfy    True   2.52301e-09   2.52301e-09             0 ('alfy', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "10 ON    ip1_dx      True   8.12377e-10   8.12377e-10             0 ('dx', 'ip1'), val=0, tol=1e-08, weight= ...\n",
      "11 ON    ip1_dpx     True  -1.81171e-09  -1.81171e-09             0 ('dpx', 'ip1'), val=0, tol=1e-08, weight ...\n",
      "12 ON                True   1.04727e-10       9.39479       9.39479 mux(__ele_stop__ - __ele_start__), val=9 ...\n",
      "13 ON                True  -3.53289e-10       9.53049       9.53049 muy(__ele_stop__ - __ele_start__), val=9 ...\n"
     ]
    }
   ],
   "source": [
    "opt.target_status()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6463980c-7b68-49ae-ae15-08b3395bdbed",
   "metadata": {},
   "source": [
    "#### Match right side"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f36931b6-1fac-44df-a8d3-10e11f8f0cfa",
   "metadata": {},
   "outputs": [],
   "source": [
    "opt = collider.lhcb1.match(\n",
    "    solve=False,\n",
    "    default_tol={None: 1e-8, 'betx': 1e-6, 'bety': 1e-6, 'alfx': 1e-6, 'alfy': 1e-6},\n",
    "    start='ip1', end='e.ds.r2.b1',\n",
    "    init=tw0, init_at=xt.END, # <-- We match going backward in the line\n",
    "    vary=[\n",
    "        xt.VaryList([\n",
    "            'kq9.l2b1', 'kq10.l2b1', 'kqtl11.l2b1', 'kqt12.l2b1', 'kqt13.l2b1',\n",
    "            'kq9.r2b1', 'kq10.r2b1', 'kqtl11.r2b1', 'kqt12.r2b1', 'kqt13.r2b1',\n",
    "            'kq4.l2b1', 'kq5.l2b1',  'kq6.l2b1', 'kq7.l2b1', 'kq8.l2b1',\n",
    "            'kq6.r2b1',  'kq7.r2b1', 'kq8.r2b1', 'kq4.r2b1', 'kq5.r2b1'])],\n",
    "    targets=[\n",
    "        # Only IR2 quadrupoles including DS\n",
    "        xt.TargetSet(at='ip1', betx=0.15, bety=0.10, alfx=0, alfy=0, dx=0, dpx=0),\n",
    "        xt.TargetSet(at='ip2', tars=('betx', 'bety', 'alfx', 'alfy', 'dx', 'dpx'), value=tw0),\n",
    "        xt.TargetRelPhaseAdvance('mux', value = tw0['mux', 'e.ds.r2.b1'] - tw0['mux', 'ip1']),\n",
    "        xt.TargetRelPhaseAdvance('muy', value = tw0['muy', 'e.ds.r2.b1'] - tw0['muy', 'ip1']),\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2f5c81fd-07c5-4ac4-8159-4eaed702ccbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                             \n",
      "Optimize - start penalty: 0.05                              \n",
      "Matching: model call n. 112 penalty = 2.3723e-08              \n",
      "Optimize - end penalty:  2.37226e-08                            \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<xtrack.match.OptimizeLine at 0x33f440a50>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt.step(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3a89022c-9c6e-4751-a4fa-bce8da0b558f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Target status:               enalty = 2.3723e-08              \n",
      "id state tag      tol_met       residue   current_val    target_val description                                 \n",
      "0  ON    ip1_betx    True   8.25279e-11          0.15          0.15 ('betx', 'ip1'), val=0.15, tol=1e-06, we ...\n",
      "1  ON    ip1_bety    True  -1.02261e-10           0.1           0.1 ('bety', 'ip1'), val=0.1, tol=1e-06, wei ...\n",
      "2  ON    ip1_alfx    True  -8.97165e-10  -8.97165e-10             0 ('alfx', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "3  ON    ip1_alfy    True   6.43083e-11   6.43083e-11             0 ('alfy', 'ip1'), val=0, tol=1e-06, weigh ...\n",
      "4  ON    ip1_dx      True  -1.14725e-11  -1.14725e-11             0 ('dx', 'ip1'), val=0, tol=1e-08, weight= ...\n",
      "5  ON    ip1_dpx     True  -2.18901e-10  -2.18901e-10             0 ('dpx', 'ip1'), val=0, tol=1e-08, weight ...\n",
      "6  ON    ip2_betx    True  -2.89081e-10            10            10 ('betx', 'ip2'), val=10, tol=1e-06, weig ...\n",
      "7  ON    ip2_bety    True   1.69772e-10            10            10 ('bety', 'ip2'), val=10, tol=1e-06, weig ...\n",
      "8  ON    ip2_alfx    True  -4.80648e-11   5.17085e-07   5.17133e-07 ('alfx', 'ip2'), val=5.17133e-07, tol=1e ...\n",
      "9  ON    ip2_alfy    True   9.80618e-12   1.20213e-07   1.20203e-07 ('alfy', 'ip2'), val=1.20203e-07, tol=1e ...\n",
      "10 ON    ip2_dx      True  -1.46219e-10    1.3727e-09   1.51891e-09 ('dx', 'ip2'), val=1.51891e-09, tol=1e-0 ...\n",
      "11 ON    ip2_dpx     True   3.62529e-12   9.80611e-10   9.76986e-10 ('dpx', 'ip2'), val=9.76986e-10, tol=1e- ...\n",
      "12 ON                True  -1.60416e-10       9.67996       9.67996 mux(__ele_stop__ - __ele_start__), val=9 ...\n",
      "13 ON                True   5.96678e-12       9.07357       9.07357 muy(__ele_stop__ - __ele_start__), val=9 ...\n"
     ]
    }
   ],
   "source": [
    "opt.target_status()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbdb9823-33f5-436c-811d-40dcd4b98414",
   "metadata": {},
   "source": [
    "#### Inspect results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cb48fec0-0073-4a40-bd40-4a1817cd8398",
   "metadata": {},
   "outputs": [],
   "source": [
    "tw_new = collider.lhcb1.twiss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8b76c08f-9b44-427c-9a4c-8f723eb90ac8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x35b5bce50>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "376308a44f284723a907643a85ade2b7",
       "version_major": 2,
       "version_minor": 0
      },
      "image/png": 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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=640.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(tw_new.s, tw_new.bety, label='rematched')\n",
    "plt.plot(tw0.s, tw0.bety, '--', label='original')\n",
    "plt.xlabel('s [m]')\n",
    "plt.ylabel(r'$\\beta_y$ [m]')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab01d748-3f4c-41de-85e7-1c1f2cbd9f8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inspect table\n",
    "tw_new.rows['ip.*'].cols['betx bety mux muy x y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "85d37c81-093a-4296-9dcd-841ccd1699e8",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}