entrypoint_cuda.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.dataquest.io/blog/jupyter-notebook-tips-tricks-shortcuts/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Development for photon source"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "NUMBER_OF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Potential Plot\n",
    "Minimization of the following:\n",
    "\n",
    "$$\\bar{u}_\\text{pot} = \\frac{U}{E_J} = -\\big[ \\alpha\\cos(\\varphi_{02}) + \\cos(\\varphi_{03}) + \\cos(\\varphi_{01}) + \\\\\n",
    "+ \\cos(\\varphi_{02} - \\varphi_{01} - L) + \\cos(\\varphi_{02} - \\varphi_{03} + R)\\big]\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils.array_stacker import ArrayStacker\n",
    "from kernels.potential_minimum_searcher import PotentialMinimumSearcher\n",
    "from kernels.potential_evaluator import PotentialEvaluator\n",
    "from functions.potential import potential_function_cuda\n",
    "from common import plotter\n",
    "from matplotlib import cm\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "from numba.cuda.cudadrv.devicearray import DeviceNDArray\n",
    "from numba import cuda\n",
    "import numpy as np\n",
    "import math\n",
    "import itertools\n",
    "from collections import defaultdict\n",
    "from typing import Tuple, List, Dict\n",
    "from utils.info import allocate_max_threads, verify_blocks_per_grid\n",
    "\n",
    "\n",
    "pi = math.pi\n",
    "sin = np.sin\n",
    "cos = np.cos\n",
    "\n",
    "plt.style.use('my_official')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameters of the simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "NUMBER_OF_PHI_POINTS = 80\n",
    "NUMBER_OF_FIELD_POINTS = 600\n",
    "NUMBER_OF_FIELD_POINTS_PER_RUN = 50\n",
    "NUMBER_OF_FIELD_RUNS = (\n",
    "    NUMBER_OF_FIELD_POINTS - 1\n",
    ") // NUMBER_OF_FIELD_POINTS_PER_RUN + 1\n",
    "ALPHA = 1\n",
    "LOWER = -0.5\n",
    "UPPER = 1.5\n",
    "\n",
    "lr_array = np.linspace(LOWER * 2 * pi, UPPER * 2 * pi, NUMBER_OF_FIELD_POINTS)\n",
    "phixx_array = np.linspace(-pi, pi, NUMBER_OF_PHI_POINTS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create kernels to cuda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🐳 Allocating           THREADS_PER_BLOCK = (8, 8, 8)\n",
      "🐳 Allocating           THREADS_PER_BLOCK = (10, 10, 10)\n"
     ]
    }
   ],
   "source": [
    "BLOCKS_PER_GRID = (NUMBER_OF_FIELD_POINTS_PER_RUN, NUMBER_OF_FIELD_POINTS_PER_RUN)\n",
    "\n",
    "potential_evaluator = PotentialEvaluator(NUMBER_OF_PHI_POINTS, potential_function_cuda)\n",
    "THREADS_PER_BLOCK_potential_evaluation = allocate_max_threads(8)\n",
    "\n",
    "potential_minimum_searcher = PotentialMinimumSearcher(NUMBER_OF_PHI_POINTS)\n",
    "THREADS_PER_BLOCK_potential_search = allocate_max_threads()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Execution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Allocate arrays on GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "DEVICE_lr_array = cuda.to_device(lr_array)\n",
    "DEVICE_phixx_array = cuda.to_device(phixx_array)\n",
    "DEVICE_potential_array = cuda.device_array(\n",
    "    shape=(\n",
    "        NUMBER_OF_FIELD_POINTS_PER_RUN,\n",
    "        NUMBER_OF_FIELD_POINTS_PER_RUN,\n",
    "        NUMBER_OF_PHI_POINTS,\n",
    "        NUMBER_OF_PHI_POINTS,\n",
    "        NUMBER_OF_PHI_POINTS,\n",
    "    ),\n",
    "    dtype=np.float64,\n",
    ")\n",
    "DEVICE_grid_search_result_array = cuda.device_array(\n",
    "    shape=(NUMBER_OF_FIELD_POINTS_PER_RUN, NUMBER_OF_FIELD_POINTS_PER_RUN, 4),\n",
    "    dtype=np.float32,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run kernels on each quadrant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🦑 Running (L=11/11, L_offset=550), (R=10/11, R_offset=500)\n",
      "🦑 Running (L=11/11, L_offset=550), (R=11/11, R_offset=550)\n"
     ]
    }
   ],
   "source": [
    "# Go through teach of the field section and evaluate ##########################\n",
    "quadrants = defaultdict(lambda: [[None] * NUMBER_OF_FIELD_RUNS for i in range(0, NUMBER_OF_FIELD_RUNS)])\n",
    "for (L_RUN, R_RUN) in itertools.product(\n",
    "    range(0, NUMBER_OF_FIELD_RUNS), range(0, NUMBER_OF_FIELD_RUNS)\n",
    "):\n",
    "    L_OFFSET = int(L_RUN * NUMBER_OF_FIELD_POINTS_PER_RUN)\n",
    "    R_OFFSET = int(R_RUN * NUMBER_OF_FIELD_POINTS_PER_RUN)\n",
    "    print(\n",
    "        f\"🦑 Running (L={L_RUN}/{NUMBER_OF_FIELD_RUNS - 1}, L_offset={L_OFFSET}), (R={R_RUN}/{NUMBER_OF_FIELD_RUNS - 1}, R_offset={R_OFFSET})\"\n",
    "    )\n",
    "    potential_evaluator.kernel[BLOCKS_PER_GRID, THREADS_PER_BLOCK_potential_evaluation](\n",
    "        DEVICE_phixx_array,\n",
    "        DEVICE_lr_array,\n",
    "        L_OFFSET,\n",
    "        R_OFFSET,\n",
    "        ALPHA,\n",
    "        DEVICE_potential_array,\n",
    "    )\n",
    "    \n",
    "    potential_minimum_searcher.kernel[\n",
    "        BLOCKS_PER_GRID, THREADS_PER_BLOCK_potential_search\n",
    "    ](DEVICE_potential_array, DEVICE_grid_search_result_array)\n",
    "        \n",
    "    grid_search_result_array = DEVICE_grid_search_result_array.copy_to_host()\n",
    "    \n",
    "    quadrants[\"potential\"][L_RUN][R_RUN] = grid_search_result_array[:,:,0]\n",
    "    quadrants[\"phi01\"][L_RUN][R_RUN] = phixx_array[grid_search_result_array[:,:,1].astype(int)]\n",
    "    quadrants[\"phi02\"][L_RUN][R_RUN] = phixx_array[grid_search_result_array[:,:,2].astype(int)]\n",
    "    quadrants[\"phi03\"][L_RUN][R_RUN] = phixx_array[grid_search_result_array[:,:,3].astype(int)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Collect up results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "result = {key: ArrayStacker.stack_into_square(value)\n",
    "          for key, value in quadrants.items()}\n",
    "\n",
    "for key in [\"phi01\", \"phi02\", \"phi03\"]:\n",
    "    result[key] = result[key] / (2 * pi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis\n",
    "For cells {0,0} {0,1} and {1,0}, the degeneracy point it is located at\n",
    "\\begin{equation}\n",
    "    \\varphi_T = 2\\arccos \\left( \\sqrt{\\alpha^2 + 1} - \\alpha \\right)\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot minimal values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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StU5gFHcpyzmvB24CbkopfQn4KbAPcFlK6fic882jNZdoFjeSJEnqOUWjQaNR4XVuHn3uZQFrakYk53xnSuldwKW0Nhp4N/DiKuYSwbelSZIkSb3tex3Hp1c1iQh2brqwZfJCNk9Z2HXO5VevDZhNy3Ofc0RY1uJNS8OyANbvfWZYVuPhDWFZyxq7351kT+w1eXJY1rSHfhWWBbD5prgNUB468cNhWasfiPv6P+3UA8OyJk/uC8sC6O8fCMuaM3tqWNbqv7ojLOsVqy8PywJ4+TNuDMu65LXfD8va8rKvh2Xdcf/qsKypG9eHZQE8vPbwsKy0z5qwrOLw54Rl0dwWFvVwc3FYFsC6DVvCsvaevanrjIH+uH/fxorta18qO//A2LjOTVvnP8Z7VzaLAHZuJEmSpN52aMfxg5XNIoCdG0mSJPWcRqNBo6+63/M3+sdUj+G8juOfVTaLABY3kiRJUs2klM4DlgDX5Jybg4zpA/4ceFPHw58ehemVxuJGkiRJPafyNTfln/sk4DPAvSmlK4CbgRXAFmA2kIDnAwd0vOZDOecflz2xMlncSJIkSfW1GHjNEGNWA3+Zc/7MKMynVBY3kiRJ6jmtzk2F17kpv3Pzp8C/A6cBxwIHA/OAicA6YDnwa+AHwNdzznHbN1ao1OImpTQTeCZwBnAcrZ0YZgMbgQeA64AvAz8Y7L2A7ZxXARfvwakvyDmfP7JZS5IkSeNbznkN8K32rWeUVtyklN4GfACYsounZwKHt28vB65NKZ2Tc76nrPlIkiRJ2zWKgkajujU3jWJMXeemNsrs3BzGjsLmfuBK4AZaC5mm0FrkdA4wAzgVuCaldFLOecUQuZ8Arh5izG9GOmlJkiRJ41OZxU0T+CHwMeCqnPPOl+e+JKX0YVrv8zscOBD4MEMveLox5/zt6MlKkiSph/Q1Kl1zQ5XnrrEyP6vvzjk/K+d8xS4KGwByzncDZ3c8dHZKaVqJc5IkSZJUU6UVNznnh4c57iZaFxgCmAYcUtacJEmSJNhxnZsqb4o3VvphazqOp1Y2C0mSJEnjVuXXuUkpTaK1+cB2dw/xkjellN5J64JEDeAh4FfA94BLcs4bSpmoJEmSaqPRKGhU2D2pcqe2Oqu8uAFeCsxqH9+Yc142xPgTdrq/uH07C7ggpfSanPN/jHQyKaV9hxiyaKTZkiRJkspTaXGTUpoPfKTjoQt3M7wf+E/gWuC3tK6sOht4IvAnwBxgPvCdlNLLcs7/OsJp3TvC10mSJEmqUGXFTfvtaN8EFrQf+nbOebArqP4UOCDnfN8unvu/KaW/AC6itfNaAXwhpfQzLwoqSZKkXSkaDYpGdcvPqzx3nVVS3KSUGsAXaF28E+AOdnN9m5zz73aXl3Nem1J6GbAQOJ3WRULfCbx5BNNbPMTzi4DrAdat28K0qZtHcIpH2++AvbvO2O7an8fVc6dP/m5YFsDUBYeHZe2/4OiwrIEbLgnLWrLotWFZR8zYEpYFsORFV4VlHb30K2FZj33s8WFZ9E8Mi/rd8seGZQEcvP7ysKyJXz4/LOuOl/88LKtx0NPCsgAuvXx9WNZqXhGWNXNiX1jWIfM3hmVt6JsZlgWwYePWsKzm7T8My2LS9LCoxoGnh2XNbQxrk9hhazbjfjZYvOmnXWcsm7I6YCZS+Ua9uEkpFcA/Ay9rP3QP8PSc86pucnPO/Smlv6bV5QF4LiMobgbpDv1BSmkEs5MkSdJY0uireEMBt4Iuxaj2w9qFzaeB17Ufug94as75rqBT/CewqX28nxcElSRJknrHqHVu2oXNp4Dz2g/dD5yRc74j6hw554GU0sPAPu2HZgNuDS1JkqRHaV1Is8I1N3ZuSjEqf6Idhc0b2w89QKuw2e1amhGcpwF0vkn1kch8SZIkSWNX6Z2bXRQ2S2kVNreXcLqTgKnt4/u8oKckSZJ2pWgUlXZPCi/iWYrR6Nx8kh2FzTJahc1vo0/S7tq8r+OhEV/IU5IkSdL4U2rnJqX0CeBN7bvLgNNzzkv2MOPJwNHApTnnTYOMmQ58Fti+D+lmHn1xUEmSJOkPikaDhte5qZ3SipuU0oXAW9p3m8A/AkemlI4c4qU37nTxzYW0CpePp5SuAG4A7gXWA7OA44AXA3M7zvXawB3YJEmSJI0DZXZuTuk4LoAPDfN1rwa+uIvHZwAvaN8Gs4xWYXPZMM8lSZKkHtTaLa3CNTfullaKUb+I5whcCTwfOBF4ErCYVpdm+zbPK4AbgcuArw321jVJkiRJ9VZacZNzPj0oZx3wnfZNkiRJ6lqjUdCosHvScLe0UriSSZIkSVItjIe3pUmSJEmhGo2i0u6JnZty2LmRJEmSVAt2biRJktRziqKgKCrcLa3Cc9eZnRtJkiRJtWDnpgtzpm5k3vQNXefM3W9twGxabrxnZlgW0w+KywKeeujPw7K+dM9JYVn7LF0SlnXEEfeHZS0nhWUBHN3/zbCs4pBnhGU1778+LOvOaXHzOnSf/rAsgC19Lw3L+ukznhyWdeq/nDL0oGFqvvnSsCyAYu5hYVl73fW9sKz3vH9yWNa7zn96WNbMYnVYFsDUKZPiwh64LSyqeMr/CcvaOm1xWNbmzdvCsgDmrr02LOvWbU/qOmPltgcDZjK2NBrVrntp2GIohZ9WSZIkSbVg50aSJEk9p6h4t7TC3dJKYedGkiRJUi3YuZEkSVLPaRQVX+fG3dJKYedGkiRJUi3YuZEkSVLPaVS85qbKc9eZnRtJkiRJtWDnRpIkST2nURSVrntxzU057NxIkiRJqgU7N5IkSeo5RQMaFf6av7DFUAo/rZIkSZJqwc6NJEmSeo67pdWTnRtJkiRJtWDnRpIkST2nUVTcuXG3tFLYuZEkSZJUC3ZuJEmS1HOKRkFRYedmNM6dUpoJPBM4AzgOOBSYDWwEHgCuA74M/CDn3Cx9QqPAzo0kSZJUMymltwErgG8AbwaeDMyj1dyYCRwOvBz4HvDjlNJ+FU01lJ2bbjT7YaC/+5iVtwdMpmXSxBPCsrbs9+ywLIAfLT8wLOtfvve7sKxznnd+WNZty6aHZS1fsTIsC6D/4BeGZU3YEvd7kb6Fzw3LWrzXlLCsn1x/b1gWwGlP6P57xXbPOOiusKyBM34blsXSX8RlAUvujfsl4oKFcd/PLnzLz8OyeDgua+Cu2M//6gXnhmVNOeUjYVmf/qf/DMt6x58vDsua0bcmLAugOSnu35MH79vQdcaqVRsDZjK29MBuaYcB2/9hvB+4EriBVsEzBTgJOAeYAZwKXJNSOinnvKLsiZXJ4kaSJEmqnybwQ+BjwFU554Gdnr8kpfRh4Ae0ujgHAh8GXjOqswxmcSNJkqSeUxTV7lg2Cqd+d8754d0NyDnfnVI6G/hV+6GzU0pvyTl33+6riGtuJEmSpJoZqrDpGHcTsKR9dxpwSGmTGgV2biRJktRzemDNzZ7oXDQ2tbJZBLBzI0mSJPWolNIkWpsPbHd3VXOJYOdGkiRJPadRVNy5efSim0Uppd2OzznfV9JUXgrMah/fmHNeVtJ5RoXFjSRJklSt64cxJrwSSynNBzr3ar8w+hyjzbelSZIkST2m/Xa0bwIL2g99O+f8rQqnFMLOjSRJknrOGNtQ4ARg1N4OllJqAF+gdfFOgDsY59e32c7iRpIkSarWshLX1DxKSqkA/hl4Wfuhe4Cn55xXjcb5y2ZxI0mSpJ4zxjo3o6Jd2HwaeF37ofuAp+ac7xr1yZTENTeSJElSzbULm08B57Ufuh84I+d8R3WzimfnRpIkST2n6Cto9FXXuSlG8dwdhc0b2w89QKuw+d2oTWKU2LmRJEmSamoXhc1SWoXN7dXNqjx2biRJktRzxthFPMv0SXYUNstoFTa/Ha2TjzY7N5IkSVINpZQ+AbypfXcZcHrOeUmFUyqdnZsubCz2ZkNjbtc5P7r9kIDZtJy54NthWY0tzwnLAhh45J6wrHNeeGxY1sDSX4ZlHf7Lr8ZlrYrd7r447MNhWWunHhGWNeO2z4dlLV/8irCsU9Z8OiwLYEPjA2FZU/c+KCxr2bK1YVlz5h4flgVw6G/iPmfFrBeGZTVXxq29bRz5/LAsps2LywKOzJ8Ly1q/75+HZf3Z204Jy1r58MawrEmP6f7ngU5rp00Py3p86j5jxYpm9yFjTKPRoNGo7vf8ZZ87pXQh8Jb23Sbwj8CRKaUjh3jpjTnnuB/aRpnFjSRJklQ/nb8JKIAPDfN1rwa+GD6bUWJxI0mSpJ5TNKCocM1N4eKQUljcSJIkSTWTcz696jlUweJGkiRJPafRqHi3tArPXWc2xCRJkiTVgp0bSZIk9ZyiUdDoq3LNjZ2bMti5kSRJklQLdm4kSZLUc+p+nZte5WdVkiRJUi3YuZEkSVLPcbe0erJzI0mSJKkW7NxIkiSp59i5qSc7N5IkSZJqwc6NJEmSek5RcefG69yUw86NJEmSpFqwcyNJkqSe02g0aPR5nZu68bMqSZIkqRbs3HQh37qc+5f2d52zetWGgNm0NJ/9+risVb8JywL46fIjw7JOnX5/WNbSaSeHZT32uY8Py6LRF5cF3LF8YljWgb96X1jW8mP+Mixr85ZtYVkPPvFvwrIArvnOrWFZf/SCx4Vl7bPhxrCsh9ensCyAyfsdH5bV/N2VYVnFwU8Ny3po48ywrKKxV1gWwN6PPTosa/2GLWFZ8+fPCMvaq7kiLGvg99eGZQE8MjHu36b91/xH1xkbV64NmMnY0mhUu2OZjZty+GmVJEmSVAt2biRJktRzikZR6Y5l7pZWDjs3kiRJkmrBzo0kSZJ6TqPRqHTHMndLK4efVUmSJEm1UGrnJqU0E3gmcAZwHHAoMBvYCDwAXAd8GfhBzrk5zMxDgDcAZwKLgT7gfuBK4KKc86+CPwxJkiTVTFEUle6WVhSuuSlDaZ2blNLbgBXAN4A3A08G5tEqqGYChwMvB74H/DiltN8wMl8P/Bp4B/A4YC9gOnAY8Cbgv1JKsfu3SpIkSRoXyuzcHAZMaR9v76zcQKvgmQKcBJwDzABOBa5JKZ2Uc97lpvMppXOAz7bvDgBfAa4CtgEnA68EJgMXpJQ255w/UsYHJUmSpPGv0ai2c1PlueuszOKmCfwQ+BhwVc55YKfnL0kpfRj4Aa0uzoHAh4HX7ByUUpoPfKp9dwB4Qc75Ox1DLk0pXUyr2JkGXJhS+nbOeUnkByRJkiRp7CpzQ4F355yflXO+YheFDQA557uBszseOjulNG0XQ99B6y1oAJ/aqbDZnvUL4D3tuxOA94586pIkSaqzRqP6m+KV9mnNOT88zHE3Ads7LNOAQ3YxrLMA+vvdxF0ErG8fPy+lNHU4c5AkSZI0/o2VmnFNx/GjCpKU0lHA/u27t+Wc7xwsJOe8Fri2fXc68JTISUqSJKketq+5qfKmeJUXNymlSbQ2H9ju7p2GHN1xfP0wIjvHHD3oKEmSJEm1Uup1bobppcCs9vGNOedlOz1/eMfxoF2bQcYcPugoSZIk9axGUdCo8FozVZ67ziotbtq7oHVu2XzhLobN7jh+aBixKwd57XDntO8QQxbtaaYkSZKk8lVW3LTfjvZNYEH7oW/nnL+1i6EzOo43DSN6Y8fxzBFM7d4RvEaSJEnjSFFUu+6lsHNTikqKm5RSA/gCrYt3AtzBLq5vM9Ydf/AWFi3Y0nXOyfusDphNS/O6T4RlXdv/vLAsgNOeMGXoQcN03yO72lRvZB5YumboQcOUb9k49KBh+tF3bwvLAnj3B54VllXw1LCsRVMfDMuiEfdnuX7akWFZAGefFdf0XbW+++872/3DpRvCsv48vWfoQXug/1kfDctaNvXUoQcN02MfvCwsa07f78KyinnB78See9jQY4Zp0aTAf+dW3hWWxdS5YVHFvNjvGfsvuyos63M/6/7fzHXrVgXMRCrfqBc3KaUC+GfgZe2H7gGennMe7G/Nuo7j4fx03Lnb2to9nyGLh3h+EcPb2ECSJEljVOtaMxWuual8W696GtXipl3YfBp4Xfuh+4Cn5pzv2s3LHuk4njeM03T+GuaRQUcNIud83+6eTyntaaQkSZKkUTBqNWO7sPkUcF77ofuBM3LOdwzx0iUdxwcO41SdYz17NUIAACAASURBVJYMOkqSJElSrYxK56ajsHlj+6EHaBU2w3mz8c0dxycMY3znmDy8GUqSJKmXFI2CosoNBbyIZylK79zsorBZSquwuX04r88530prXQ7AkSmlA3Zzrhns2KRgA/DjkcxZkiRJ0vgzGm9L+yQ7CptltAqb3+5hxlc7jt+2m3GvB6a3j7+Tc47bBkiSJEm10WgUld8Ur9TiJqX0CeBN7bvLgNNzziNZB/Mxdux89uaU0n/bozildCLw/vbdbcAFIziPJEmSpHGqtDU3KaULgbe07zaBf6T1trKhNoK/Med8T+cDOecVKaW3Al+kVZB9K6X0FeAKoB84GXglO7aKfm/O+TchH4gkSZJqp1HxRTwbXsSzFGVuKHBKx3EBfGiYr3s1rSLmUXLOl6SUpgF/R6uIeWn71qkf+EDO+YN7PFtJkiRJ49qoX8SzGznnz6SUrqS1nfSzaV1ws0Fr97WrgM/lnH9Z4RQlSZI0DhRFUWn3pLBzU4rSipuc8+kl5d4OvL19kyRJkrQLKaU+4EjgeOCJ7f8/HpjaHnJJzvlV1cyuHOOqcyNJkiRFqHrHslE699eAF47GicaK0dgKWpIkSdLo69vp/sPAsK41OV7ZuZEkSVLP6ZHOzXXAbcANwA055ztTSq8CLh6Nk1fB4kaSJEmqoV7cQdjiRpIkST2nRzo3Pcc1N5IkSZJqwc5NF/L903hg4/Sucw496MkBs2n5r7sOCMt66hPCogBoblkflnXf/VvDsubNmxaWNX9e918P2z39H84KywJoPHxrXNjeB4VF/ct3V4VlveyUuKyBqc2wLIDNk+aGZc26/m/Dst7y1rhd9ZeuPi4sC2B+4B/BvtMfCsu6Y8uzwrL2njV16EHDdM/9q8OyAI46Yn5Y1tYt/XFZE+aEZc269/KwrKWznhmWBTB5/plhWee9elPXGcuWr+CL/1/AZMYQOzf1ZHEjSZIkVWtRSmm3A3LO943SXMY1ixtJkiT1nKKotntSPPrU1w/nJeXMpF5ccyNJkiSpFuzcSJIkqecUxX/rnoz6+TucACyrZib1YnEjSZIkVWuZa2piWNxIkiSp5xRFQVFh66bKc9eZa24kSZIk1YKdG0mSJPWcRlHQqLB7UuW568zOjSRJkqRasHMjSZKknjPGdktTEDs3kiRJkmrBzo0kSZJ6TtEoKBoV7pY2CudOKR0InLvTw8d0HB+bUrpwp+evzjlfXe7MymNxI0mSJNXT/sC7d/P8MTy62AHYBljcSJIkSeNFUfFuaV7nphwWN5IkSVIN5ZyvAXqqirK4kSRJUs8pqHi3tOpOXWsWN12YP3c68+fP6Dpn8pS4P4Yz0qawrCUr5odlAey/3+ywrCft9Z2wrK37Pi8sqwj8VvXja+8KywI47JB9w7L2+f2XwrKee9ZrwrKKyevCsmbcfXlYFsDvJz0lLOvgg04Ly+r76LFhWZc95vNhWQDPe8HjwrJWr5kVlnX/A2vCsn74vSVhWW969cFhWQBrNm8Ly5o4sS8s66tndP/v7nav/uh7w7L2mXNIWBbA2klHhGU9smla1xlrNk8NmIlUPosbSZIk9ZyiKCpd9+Kam3J4nRtJkiRJtWDnRpIkST2nUfFuaVWeu87s3EiSJEmqBTs3kiRJ6jlFo3Wr8vyK56dVkiRJUi3YuZEkSVLPcbe0erJzI0mSJKkW7NxIkiSp5zSK1q3K8yuenRtJkiRJtWDnRpIkSb2n4jU3uOamFHZuJEmSJNWCxY0kSZKkWvBtaZIkSeo5RVHtdsy+K60cdm4kSZIk1YKdG0mSJPWcRgGNCn/N71bQ5bC46cJtv3mQpcsGus55dloZMJuWtTOPDctatKAZlgUw6e7LwrK2HfT8sKxJG+4Oy/rXyx4Jy3rx0beEZQH8/J7TwrLmHfeGsKzbb1kelnX8vnF/l4r5R4ZlARy87tdhWQ9POzEsa+a74+b1uvV3hWUBLNsUl/XYx8yMCwu0/36zwrLWbJsWlgVw7U/vCst60gn7hmW9+oPvCsu6Y783hmXtMyP2a2zrpm1hWZs2d5+1YWPcfKQyWdxIkiSp5xQVbwVd6TbUNeaaG0mSJEm1YOdGkiRJPae1W1q151c8OzeSJEmSasHOjSRJknqOa27qyc6NJEmSpFqwcyNJkqTeU7RvVZ5f4ezcSJIkSaoFOzeSJEnqOUX7vyrPr3h2biRJkiTVgp0bSZIk9Ryvc1NPdm4kSZIk1YKdG0mSJPWeiq9zY+umHHZuJEmSJNWCnRtJkiT1HNfc1JOdG0mSJEm1YOdGkiRJPaji1o3XuSmFxU0XznjSDBYt2KvrnFVb9g2YTcuMqRPDsiYs+0VYFkBzy/qwrG3b+sOyJlx/cVjWqU95R1gWD98SlwVs2LA1LGvjhi1hWcfP/W1Y1u/XPz4sa96cqWFZAHsVD4Zlzdnwy7Csb187Oyzr+Y3PhWUBzHr634ZlTbnhH8OyDksvDMtiy9qwqOayu8OyAJ71rLPCsi69+L/Csl70J+8Oy5q9eVtY1vd/sCQsC+CFJ64Ly3qgeFxYljTWWdxIkiSp57jmpp5ccyNJkiSpFuzcSJIkqecUFV/nptJr7NSYnRtJkiRJtWDnRpIkST3HNTf1ZOdGkiRJUi2U2rlJKfUBRwLHA09s///xwPY9Vi/JOb9qGDmvAvZkv94Lcs7n78lcJUmS1DuK9n9Vnn+0pJSeB7wcOAFYBKwBfgd8C/hsznnNqE2mZGW/Le1rQOAFASRJkiQNR0ppBvAvwPN2emp++/Zk4K0ppT/JOcde4LAiZRc3fTvdfxhYCRzaReYngKuHGPObLvIlSZJUc3Vfc9N+B9XXgWe3H1oOXATcCswBXgKcDCwGLk8pnZxzvq3cWZWv7OLmOuA24AbghpzznSN4i9nObsw5fzticpIkSVJNvZYdhc2twFNzzss7nv9USuljwNuBvYHPAqeN7hTjlVrc5Jw/WGa+JEmSNCI1bt20uzbv7Xjo5TsVNtu9E3ga8ATg1JTSM3POPyxtYqPA3dIkSZKkejkNeEz7+Mc55xt3NSjn3A/8U8dDLyl7YmXzOjeSJEnqOTVu3ACc2XF8+RBjvzfI68al8VjcvCml9E5ai58awEPAr2j9wVySc95Q5eQkSZKkih3dcXz97gbmnJellO6l9bP1wpTS/Jzzg6XOrkTjsbg5Yaf7i9u3s4ALUkqvyTn/x0jDU0r7DjFk0UizJUmSNDa0OjcVXufm0adelFLa7fic8317EH94x/Gdwxh/J62fp7e/1uJmFPQD/wlcC/wWWAfMpnVx0D+htaXdfOA7KaWX5Zz/dYTnuTdgrpIkSdJw7ba70rYnldjsjuOHhjF+5SCvHXfGS3HzU+CAQSrW/5tS+gta+3afTesP/gsppZ/lnO8pc1IDd1zJwKqZXed84DNzAmbT8tE/2xqWxZxD4rKAL//y8KEHDdOZj9kWljXtxNeFZe276e6wrK1HvDQsC+DE/beEZc0q4n6h05y5T1jWgT98W1hW8Yx3hmUBXL/ioLCs446N+5w9f+lnwrKY/dS4LGDKxc8Jy9r2uu+HZW3aFPd9dubALWFZ37zpwLAsgP+1z7KwrFfNuzQsi2/cHxY182l/Gpb1x8/o5hJ+/91Pft39zxfbHfypxww9aChb+4D9u88ZQxpbHqFvy6RKz1+iGR3Hm4YxfmPHcdwXXwXGRXGTc/7dEM+vTSm9DFgInA5MobW13ZtHcLrFQzy/iOFV15IkSdJwnADE/Uahh42L4mY4cs79KaW/ptXlAXguIyhuhno/41Dvh5QkSdI40GxCc6Da8++wbA/X1AxlHa0Lc0Lrl/7rhhg/teN4beA8Rl3drnPzn+xove2XUppW5WQkSZKkCnS+523eMMbPHeS1406tipuc8wDwcMdD43pBlCRJksoy0OrcVHWj1K7Rko7j4SzI6xyzZNBR40CtipuUUoMdLTgY55WnJEmSNAI3dxzvfBmVR0kpLWTHmvMV4/kaN1Cz4gY4iR3vGbzPC3pKkiRpl5rN6m/l6dwi8swhxv7PjuPLS5jLqKpNcdPu2ryv46ERX8hTkiRJGsd+zI7d105PKR23q0EppT6gc0/0r5Q9sbKN+eImpfTklNLrU0pTdjNmOnAp8LT2Q5uBj4zG/CRJkqSxJOfcz6N/6X9pSmnBLoZ+GHhC+/hnOecflD65kpW6FXRK6UDg3J0ePqbj+NiU0oU7PX91zvnqjvsLgc8CH08pXQHcANwLrAdmAccBL2bHLg9N4LU557tCPghJkiTVzx8W9ld4/nJdBLwAeAbwOOCmlNJFwK3AHOAlwCntsY8Abyh7QqOh7Ovc7A+8ezfPH8Ojix2AbcDVuxg7g9Yf0At2k7eMVmFz2Z5MUpIkSaqTnPO2lNIfA1+mdf3HRcB7djH0PuDsnPMtozm/soyHi3heCTwfOBF4Eq3dHObS2uZ5A7ACuBG4DPhaznnTIDmSJElSS/07N+Sc1wJnpZSeD7yC1s5pC2hdqPMO4N+Az+acV5c+mVFSanGTc74GKLrMWAd8p32TJEmStAdyzv8O/HvV8xgN46FzI0mSJMVqNivu3JS6FXTPGvO7pUmSJEnScNi5kSRJUu/pgTU3vcjOjSRJkqRasHMjSZKkntNsDtCssHtS5bnrzOKmC42Dnkpjwfyuc/7PBTMCZtN25evCoppPeG5YFsAL//jssKxVj8Tt+P2lyx8My3rJy44Ly5q0cXlYFsCElTeFZW1d/PSwrN/ftSos68AXfj4s67YlcV8XAOmoOWFZjRs+E5eVXhSW1dy8LiwLoHnmO8KyJm2J+/s0ce3dYVn9i04My/rjAy8KywK4b/WLw7JmP/3jYVmbN/eHZa1avTEs66Dl14VlATzhmDPCsqZeurbrjOby5XDmMwNmI5XL4kaSJEm9p9msdscyd0srhWtuJEmSJNWCnRtJkiT1oIH2rcrzK5qdG0mSJEm1YOdGkiRJvafZrPg6N665KYOdG0mSJEm1YOdGkiRJPWig2s6Na25KYedGkiRJUi3YuZEkSVLvaVbcuam0a1Rfdm4kSZIk1YKdG0mSJPUeOze1ZOdGkiRJUi3YuZEkSVLvaTarvdaM17kphZ0bSZIkSbVg50aSJEm9p9mseM2NnZsy2LmRJEmSVAt2broRtMvGtv643xo0/uhvw7JuvndyWBZAWn1zWNa0mQvDss550X5hWc2lvwjLYu+D4rKA/v2eEZa1ft3msKy773kkLOuwSXFfY48/+KiwLIB/v/J3YVlnHbl/WNbAPT8Ly+o/5I/CsgAmbFkblnX+R28Jy3rvn8V9z9iypT8s6+6ZLwzLAjiiWBKW9avfLw7LenzfT8Ky9r7tqrCs5Sd/PCwLYOH9l8eF3XpF1xGN1XHf98eMgf7WrcrzK5ydG0mSJEm1YOdGkiRJvafZ37pVeX6Fs3MjSZIkqRbs3EiSJKn3NAcq7txUuFNbjdm5kSRJklQLdm4kSZLUe5oDMFDldW7s3JTBzo0kSZKkWrBzI0mSpN7jbmm1ZOdGkiRJUi3YuZEkSVLvsXNTS3ZuJEmSJNWCnRtJkiT1noEBGKiwe1LlTm01ZudGkiRJUi3YuZEkSVLPaTb7aVa47qXKc9eZnRtJkiRJtWDnRpIkSb1nYKDadS+uuSmFnRtJkiRJtWDnpgv/77Z+9l62reucU/f9ZcBs2vqODIs6ev/Y94LetfKgsKzJ6+K+dBf+2wvDsjj2zLCotXsdG5YFMOOKd4Vl3bvf28OyFu87KyyrufX2sKyf3bQpLAvgrENvDctav+issKxPfuLnYVnvPOpPw7IAmtP3Dst6x1/8dVhWc8U1YVkDkw4Iy5r1/gPDsgBWf/LBsKxpU9eHZd3O08KyDjvjmLCsRn8RlgWw9aDnhWUtnXpG1xkPPbQCeFH3k5FKZnEjSZKkHjRQ8YU0fVtaGSxuJEmSJI1ISmku8ETg+I7/79cx5MCc812jNR+LG0mSJPWeZn+1nZsabAWdUjoa+HXV8+jkhgKSJEmSRqJvp/v9wC3AxgrmAti5kSRJUi8a6G/dqjz/+LcWuBS4Afgv4Fc55w0ppbuA/auYkMWNJEmSpD2Wc74DeGXV8+hkcSNJkqTe02xCs8Idy5rN6s5dY665kSRJklQLdm4kSZLUe1xzU0sWN5IkSVK1FqWUdjsg53zfKM1lXLO4kSRJUu8ZW9e5uX4YryhKmkmtuOZGkiRJUi3YuZEkSVLvGRioeM3No3ZqOwFYFn2KlNI1wFOC4l6Sc/5KUFZpLG4kSZKkai1zTU0MixtJkiT1nmbFu6WNznqfbwC/CspaEpRTKosbSZIkqYZyzp+seg6jzeKmC8ekRSxcuLDrnKI5NWA228Pi9ojY9MHTw7IA9jvxOWFZxYmviss6N+7towN3/igsa+mydWFZAIufcmFY1uN+++WwrMa+p4dl3fXISWFZ/+PB88OyAIpDXhuW9dOf3x2W9c7nBr4Lou/UuCxg+Zz/GZb1X9f8PizrOff+fVjWpHOfHpY17wurw7IAli5fG5Y1e9aUsKxZgVlsiPucPXB/3OcLYMGkFWFZq1Z3/3PG6jWbA2Yyxgxsa92qPL/CuVuaJEmSpFqwcyNJkqTeM7Z2S1MQOzeSJEmSasHOjSRJknqPa25CpJTOBQ7c6eHZHcdvTyk9aoFbzvmvy5qPxY0kSZKkkXo5u79Q6Ft28ZjFjSRJkhSmN65z03NKLW5SSn3AkcDxwBPb/388sH1Pwktyzq/aw8xDgDcAZwKLgT7gfuBK4KKcc9SFiiRJkiTtRs759Krn0Knszs3XgBdGhaWUXg/8AzuKo+0Oa9/ekFJ6X875fVHnlCRJUg0N9Fe85sbOTRnK3i2tb6f7DwO3jyQopXQO8Flahc0A8GXgXOCVwOeAze3zXZBSeudIJyxJkiRpfCq7c3MdcBtwA3BDzvnOlNKrgIv3JCSlNB/4VPvuAPCCnPN3OoZcmlK6GLgKmAZcmFL6ds55SbcfgCRJkmqov791q/L8CldqcZNz/mBQ1DuAvdrHn9qpsNl+rl+klN4DfJzWx/Ve4KVB55ckSZI0xo2Xi3ie3XH897sZdxGwvn38vJTSzmtzJEmSpB1rbiq72bkpw5gvblJKRwH7t+/elnO+c7CxOee1wLXtu9PZ/Z7bkiRJkmpkPFzn5uiO4+uHMf564Nkdr/1++IwkSZI0vnmdm1oaD8XN4R3Hg3ZtBhlz+KCjBpFS2neIIYv2NFOSJElS+cZDcTO74/ihYYxfOchrh+veEbxGkiRJ48n2tS9Vnl/hxvyaG2BGx/GmYYzf2HE8M3gukiRJksao8dC5GW2Lh3h+Ee21PwP9A/RvG+j+jAMbhx4zTEs3zA3LWnDBbWFZAF//+q/Dsv7XVR8Py9r2x58Py5q470lhWQu2TQvLAtjWH/C1ut2MhWFRA7/617CsCYe8KSyLfY6KywKaq34flnX6U/5nWNaW4qCwrAkTYn9ftmjtXWFZzz1ubVhW/5mXh2VNDPwY2Rb3bwnAXjMODMvq72+GZU1eG3cJu8uv2/la4yOXjo7doHX1iN58smvpqMldZyxfHjCRsWZgoNo1NwOB/y7rD8ZDcbOu43jKMMZ3fnfZ43/Ncs737e75lNKeRkqSJEkaBeOhuHmk43jeMMZ3ti4eGXSUJEmSetdAxbuleZ2bUoyHNTed/efh9Mg7x8T1riVJkiSNaeOhc3Nzx/EJwxjfOSYHz0WSJEl14G5ptTTmOzc551uBe9p3j0wpHTDY2JTSDODU9t0NwI/LnZ0kSZKksWLMFzdtX+04fttuxr0emN4+/k7OeUN5U5IkSdK4NTAA/f3V3dwtrRTjpbj5GDt2PntzSul5Ow9IKZ0IvL99dxtwwSjNTZIkSdIYUOqam5TSgcC5Oz18TMfxsSmlC3d6/uqc89WdD+ScV6SU3gp8kVZB9q2U0leAK4B+4GTglezYKvq9OeffxHwUkiRJqh3X3NRS2RsK7A+8ezfPH8Ojix1odV2u3nlgzvmSlNI04O9oFTEvbd869QMfyDl/cMQzliRJkjQujYfd0v4g5/yZlNKVwHnAs4HFtDo5DwBXAZ/LOf+ywilKkiRpPBgYqPg6N665KUOpxU3O+RqgCM68HXh7+yZJkiRJwPjZUECSJEmSdmtcvS1NkiRJCjHQX/Hb0io8d43ZuZEkSZJUC3ZuJEmS1HuaFXdumnZuymDnRpIkSVIt2LnpwtLl69iybWrXOYff9bmA2bTsffr7wrK2vX/nSxB158RX/SQs68s/eWtY1kn3PhKWte9jF4Vlzd5ye1gWQPPBe8KyirmHhGUNHPTssKzpqzeGZf1k47PCsgAmbYv7XdKT5/4uLKuYPCss6/pbmmFZAEcc+tiwrOk//3BY1rqnHx2Wtdf1F4dl/XL+G8OyAI5tfDMsa/NhLw7LKrbtHZZ15pKzw7IuG4j7txzgqMctDMsaeGf3f5fWbW4Aj+l+MmOJW0HXkp0bSZIkSbVg50aSJEm9x93SasnOjSRJkqRasHMjSZKk3mPnppbs3EiSJEmqBTs3kiRJ6j3NindLa7pbWhns3EiSJEmqBTs3kiRJ6j0D/TBQ4e/5XXNTCjs3kiRJkmrBzo0kSZJ6j52bWrJzI0mSJKkW7NxIkiSp9wxUvFvagLullcHOjSRJkqRasHMjSZKk3jPQD/1FtedXODs3kiRJkmrBzo0kSZJ6z0A/DNi56VZK6RjgmcDJQAL2ASYCq4BbgSuBL+Scl47GfCxuunDwXstYNHtL1znFKX8aMJt2VuDf0Umv+ee4MOCAud1/rra7Ze70sKzpUyeFZW3dEveNqjHzsLAsgObMQ8OyJm9bGZbVuPuqsKzfrz4qLOuIw+aGZQEsuPPisKy1E18fljVz/W/Csg4/5IiwLIBHVm8Ky/qXB18dlvXisCT459+eGZb1xqPuDssC+Pxlcd+DXnvYmrCs716zOizroGd/MyzrqCmxP1IdNOP+uLALf9x1xOYHV8KL3xowGdVFSmk2cB0w2A8YC9q304G/Sin9Rc75U2XPy+JGkiRJvcfd0ro1hR2FTT9wbfv2e2A9sD/wv4AnAdOAT6aUpuacP1bmpCxuJEmSJI3ESuDvGfxtZx9LKb0L+FD7/gdSSt/OOf+urAlZ3EiSJKn3DPRDlc2T8b/mZiVwQM553e4G5Zw/nFI6EfgjYBJwDnB+WZOyuJEkSZK0R3LOW4Gtwxz+VVrFDcAx5cyoxeJGkiRJvcfOzWjq3FVkapkn8jo3kiRJksp0dMdx7NaOO7FzI0mSpN7THKi2c9N81MkXpZR2OzznfF+p8ylJSmkicG7HQ5eVeT6LG0mSJKla1w9jTIVXHO3KX7Jjy+hfYXEjSZIkBRuouHMz/q9zM6SU0nOA97bvbgVen3Mu9QO3uJEkSZKqdQKwLDo0pXQN8JSguJfknL+yB+c+HvhXdqzxf3vOeTgdqq5Y3EiSJKn3DPTTHGhWeP5HNTCWjdc1NbuSUjoG+AEws/3Q+3POnxiNc1vcSJIkSfX0DVrrXCIsGc6glNLRwFXAnPZDH8o5/03QHIZkcSNJkqSe0+wfoFnhpWaa/eWvuck5f7L0k3ToKGzmtR/6SM75r0ZzDl7nRpIkSVJXOgqb+e2HPpZzftdoz8POjSRJknpOszlQ6ZqbZrPC9T7BdlHY/F3O+c+rmIudG0mSJEkjklJ6HI8ubP4+5/z2quZj50aSJEm9Z6AfBiq8LmaVO7UFSSkdBVzNowubt1U4JYubbhQzH0Mxa0HXOf2T5gw9aJgm3hF30dfm5jVhWQCbF5wYlnXmhveEZfXP/+ewrG3b4lYm3rbkwbAsgPS4hWFZA7/6RlhWsfCosKxjV30hLAv2DcyCex/7irCsxb/5fFjW2iPPDctavmJ9WBbAI2+M+5p9w5duDMv6/v+7NyzrZeccG5a16SPHhGUBnPt//i0sa+De/wzLeu4pcd8zYF1Y0rbp+4dlAbBuZVhU8/Yfdp/xcNznSvWQUtqXVmGz/YfhXwI/SSn90RAv3ZBz7v6LchAWN5IkSeo5zYEBmhV2biq9xk6MQ4DO30IdC3xrGK+7GzigjAmBa24kSZIk1YSdG0mSJPWc6q9zU925I+ScrwEqXLS0a3ZuJEmSJNWCxY0kSZKkWvBtaZIkSeo5rYt4Vnl+sM8Qz8+oJEmSpFqwcyNJkqTeM9APFXZuWue2zxDNz6gkSZKkWrBzI0mSpJ7T7O8fA1tBT6xuAjVl50aSJElSLdi5kSRJUs9pDjRpDjQrPP+Yu/5lLdi5kSRJklQLdm4kSZLUc5rN/mo7N007N2WwcyNJkiSpFuzcSJIkqfcMDECFnRtcc1MKi5subJswm60T9u46Z8LKHDCbttn7x2VtWReXBaxdsyksa+7K+8Oyli1bG5a1Zu3msKwD958dlgWwefO2sKwp1387LGvL694QlvVA8wlhWQc0bg7LAth/3tawrGbjuLCsmVvvDssamLtfWBbAvK+uCcsamDU1LOvMU5aHZS1bF/f38oZn/TAsC+CgDXHfg265PW6722cddEBYVuOrrwzLmnDm+WFZAMWEuK/ZPP1FXWes3PQg8KXuJyOVzOJGkiRJvae/n2Z/hZ2bfjs3ZXDNjaT/v707D7OkKg8//u0ZGIZlAgRmGFQQooLAq0YUwQ1ENIIKakwkENFocIvR3/PEPDFE/Rl3TYxJXH6GYHBJNBoX1CAGN0CDGAQUeQFBEJRtWIYZRhhGnL7390dVpy9t731uV9+638/z3GfqVp1663TNud313lN1jiRJUivYcyNJkqShU81z02nw+PYx9INnVZIkSVIr2HMjSZKkoVPNc9Ngz023wed9WsyeG0mSJEmtMFA9NxFxLnDEHHbZNzOv709tJEmSNKi6nU7Dz9w0duhWs+dGkiRJUisMVM/NBM+bRZnb+l4LSZIkDZxqtLTmnntp8thtQV0t3gAAHK9JREFUNrDJTWaWmyJdkiRJ0sAb2ORGkiRJmq9Op0unwd6TJo/dZj5zI0mSJKkV7LmRJEnS0Ol2oDva5DM3jR261QY2uYmIM4FHA6uBe4Cbge8Cn8rMc5qsmyRJkqTFN7DJDfCsnuVd6teBwMkR8S3ghZl5y1yDRsSDZiiydq4xJUmStLR0G37mxtHS+mMQk5sNwNeBi4CbgFHggcBRwDHACPBU4IKIOCwz180x/g0F6ypJkiRpkQxacnMKcHFm3jfJtvdFxGOBzwN7Aw8GTgeeuYj1kyRJ0gBwtLR2GqjkJjMvmGH7RRFxNPADYDvgmIg4JDO/P4fD7DXD9rXA9wHOPfdadt554xxCT+5xj9t3wTHG7LHTPcVidb75d8ViAXDUB8vFOvwlxULtusvKYrHW7rFTsVg33rSpWCyA3Xbbvlis237vC8VirR3dUCzWLjvvWCzWyPYHFYsF0PnOPxSLNfLYFxWLde97ji4Wa+OrLioWC+DBI5cVi9W9slzdOqOjxWKt2WO/YrFGDjiqWCyAZSPlYj3ykXsWizU6Wu4p7EsPfE+xWI++6dxisQC6K3ctFuuKfMCCY2zatL5ATaT+G6jkZjYy88qI+Ffg5HrVs6mTkVnuf+N02yNiAbWTJEnSUtDtdOh2mhuyrNsp+A2C/ldb57npHS3tgMZqIUmSJGnRtK7npnZ7z/IujdVCkiRJS5LP3LRTW3tudu9ZXvhDMZIkSZKWvLb23BzZs3xVY7WQJEnSktTtdhuda6bbteemH1rXcxMR+wEn9aw6s6m6SJIkSVo8A9NzExGvBS7KzO9OU+bRwBeAsbF9v5aZ/7MY9ZMkSdLg8JmbdhqY5AZ4KvCPEXEt8A0ggfXAKPAA4CiqCTvHeqN+BpSbDEWSJEnSkjZIyc2Yh9Sv6ZwNvDQzb16E+kiSJGnQdJp95gZ7bvpikJKb1wH/CRwKPApYQzUq2nbAXcD1wAXAJ70VTZIkSRo+A5PcZOa1wLXAvzRdF0mSJA22TqfZ5146ncYOXUxE7AYcDhwCPAbYi6rzYVfgXuBm4GLgs8CXM7PvP/XAJDeSJEmSlpSXAH87xbZVwP7160Tgkog4PjOv6WeFTG4kSZI0dJznpphR4FLgIuBq4BbgPqrem8cAxwO7AAcD34mIR2Xmbf2qjMmNJEmSpPn4DPCRzNw4xfbTIuINwFnA44C1wJuBV/erQiY3kiRJGjrOc7NwmXnDLMqsj4hXUT17A3AsfUxuls1cRJIkSZLm7fKe5bX9PJA9Nwtw1EGbWLt6+YLjdHZ/eIHaVLq3XFYs1q1HfKBYLIAdtyvX3G5a9fRisdau3LZYrNG3HFgu1kvOLxYLYKdL/r5crC2/KBbrviPfVizWTqtGisX6yc/uLRYL4KH7l2uzbL6jWKgd/uqcYrEefM9Pi8UCOOsHa4rFetYRJxaL1fn2+4rF+vneJxeLtc8Om4rFAujeV+5z3nnAfsViLd9S7lb9HbYv9/t/0x7PKxYL4Jxzy32eXnD4lgXHWHf7KP9Y9rJAw+WhPcvr+nkgkxtJkiQNnW6nQ7fB8ZibPPZiioidgN7U+HP9PJ7JjSRJktSstRExbYHMvHGR6jIvEbEGeEL9dhmwM/BI4A8YvxXtYuCv+1kPkxtJkiQNnSU2oMD3Z7FLuXuv++Ng4Iwptt0OfBR4c2Yu/D7JaTiggCRJkqR++jbw7X4nNmDPjSRJkoZQtwNNPvbSvf+xD6EPD9pHxLnAEYXCnZCZn55qY2b+F3XvUkQsB1YDhwKvAZ4PPD8i/h04OTM3F6rTrzG5kSRJkpq1bqk/UzMXmTlKlax9CfhSRLwTOAU4oS5SbgjLCUxuJEmSNHS2AlsbnEdz6+Ic5nPADwvFumoB+74J+D3gYcAJEfHWzPxxmWrdn8mNJEmS1EKZ+cGm6wBVT05EfI0quQF4CmByI0mSJJUw2q1eTR5/yPTODLxrvw7iaGmSJEmS+u1hPcu39+sg9txIkiRp6HQa7rlpcIqdRRcRewPH9Kw6v1/HMrmRJEmSNCcRsRZ4BfCBzLxzmnL7AV8AdqhXnZOZV/arXiY3kiRJGjqj3RFGuyONHn/ArQT+GnhjPZ/OhcC1wCZgBfAg4MnAM4Bt631uAk7uZ6VMbiRJkiTN1zbA0+rXdL4GvDwzf9bvykiSJElDZbQDow12nox2mjt2CZl5fUQ8iiqpORQ4kKq3ZhXwK+Au4CdUPTqfycwLF6NeJjeSJEmS5iwzfwT8qOl69DK5kSRJ0tAZ7cJW57lpHZObJeBrX/9JsVhHH7pHsVh7nHtKsVgAy57+xmKxuqt2LhZrm5vOKxZry19cWizWb131sWKxALjhsmKhRp799nKxlpW7J2D5j04vFmufR7ykWCyA7tW3FIvVefjvF4u1fH0Wi/U/N6wpFgvgSU/cvVis7m0FRx1dscPMZWZp9e47FovV/dWGYrEA7hh9YLFYu13yz8VibT7opcViPfQhy4vFWn7hPxSLBfCch+9TLNbILk9eeIxfbl+gJlL/mdxIkiRp6Iw2PM+NPTf9sazpCkiSJElSCfbcSJIkaejYc9NO9txIkiRJagV7biRJkjR0OjTbezLg09wsWfbcSJIkSWoFe24kSZI0dLY2PM9Nk8duM3tuJEmSJLWCPTeSJEkaOp2GR0vr2HPTF/bcSJIkSWoFe24kSZI0dEa7I4x2Rxo9vsqz50aSJElSK9hzI0mSpKEz2oHRho+v8uy5kSRJktQK9txIkiRp6DhaWjvZcyNJkiSpFey5WYCRXfdlZLc1C47zhMN2KFCbys33/KpYrD1vuaZYLAC65W4u/Y0tVxWLtW7FY4vFuu7yW4vFOmD/k4rFAtj1Yc8oFuvWX+5eLNaa239QLBYPelyxUPfdV/ZO7Kv+7MRisX77z7NYrJHHv6pYrMMevrVYLAC2vbtYqM9cuLpYrGc965RisZYvLzda0jkXlR15aevWdcViPW3nYqFYv35zsVgrViwvFqv7kJcViwWw5up/Khbrn87Zc8Ex7r57Q4GaLC1bu9WryeOrPHtuJEmSJLWCPTeSJEkaOp1us8+9+MxNf9hzI0mSJKkV7LmRJEnS0OnQ8GhpzR261ey5kSRJktQK9txIkiRp6HS6zfae+MxNf9hzI0mSJKkV7LmRJEnS0BntQtkZzeZ+fJVnz40kSZKkVjC5kSRJktQK3pYmSZKkoeOAAu1kz40kSZKkVrDnRpIkSUOn23DPTdeem76w50aSJElSK9hzI0mSpKEzSsNDQTd47Daz50aSJElSK9hzI0mSpKHjaGntZHKzAD+9Be66b+Etc+XKXxaoTeU3dlpRLNaX9vy7YrEAnrvhunLBtltVLNTGTVuKxVqzZsdisXZef16xWACdW7JYrHNufHqxWMcfvUuxWDdt3r1YrD2337ZYLIAHfGJjsVjf/emdxWI94YozisX66h1HFYsFsPOu5f7yP+e5BxWLteKazxeL9ZMV5c7ZkQdtLhYLgE65m2ZGVv1usVgPvPzTxWJx76Zyse6+vVws4KLVry0W6xW/e8eCY6y7/V4+9q8FKiP1mcmNJEmShs5od4RRRho9vsrzmRtJkiRJrWDPjSRJkoaO89y0kz03kiRJklrBnhtJkiQNndFuw/Pc2HPTFwOb3ETEccBJwCHAWmATcA1wBnBqZhYcAkWSJEnSbEXEw4EfACvH1mVm30dRGLjkJiJ2Aj4JHDdh0+r69XjgNRHxgsz83mLXT5IkSUtfh2bnmmnyeZ9+i4hlwOn0JDaLZaCeuYmI5cBnGU9sbgXeDpwI/Clwfr1+L+CsiDhg0SspSZIkDbf/Q9XhcM9iH3jQem5OBo6ul68AnpqZt/Zs/1BEvBd4HbArcCpw+OJWUZIkSUtdp+FnbjpAg9Ps9E1EPISq8wHgjcDfL+bxB6bnpu61eXPPqpMmJDZjXg/8sF5+ckT8Tt8rJ0mSJA25iBgBPgLsAFwIvH+x6zAwyQ1VD8ye9fJ5mXnJZIUyc5T7n8gT+l0xSZIkDZZOt/lXC70SeArwK+DkzFz0R4sGKbk5pmf5rBnKfnWK/SRJkiQVFhF7A++p3/5tZl7WRD0GKbl5RM/y96crmJnrgBvqt3tExOq+1UqSJEkDZ7Tb/Ktl/hlYBVwNvLWpSgxScrN/z/J1syjfW2b/KUtJkiRJmreIeAnwDKALvCwzf9lUXQZptLRdepbvmEX59VPsO62IeNAMRR44trBhw/rpys3adtstLxIHYMvmbYvFuuuuMj/fmHV3FJxXdcV9xUKtv6vcx2CbbcoNe7JDZ2OxWABsKDca46ZNdxaLte62cr//br+33K29y5ZtLhYLYP36cvE2bCjXNtYtu7tYrI2Ff2d0Ck6PcOut5T7n264v97ts/Yrbi8Vat7Xs+adTbhypkc3lzn/nznJtli0FR6m9595ysYA7lxdsGys3LDjG7evv93un3IVLgzZ3t2l0rpkt978MXxsR05bPzBv7WqF5iogHAO+r356Wmd9usj6DlNzs1LO8ZRble3/LrJrDcW6YuUjl9a9/1RzC6r1NV0AFfb5YpPd/qFgoNe7fmq7AAFr0gYQ0MM5tugLTWQ38rOlKLNS3tnlw01XoNe0jF7WlOnD0h6k6Em4G/qLhugxUciNJkqTmrWm6ApqdiDgXOKJQuBMy89MT4p8IHFe//dPMvKvQseZtkJKbu6km5gRYWb+fzvY9y7+Yw3H2mmH73sD59fJhwE1ziK2FW8v4txuHAOsarMsw8vw3y/PfLM9/szz/zXog8L16+cdNVmSB1jHztd5iWwvcTrNzis5ZRKwB/rF+e0ZmntFkfcYMUnKzkfHkZndmTm52m7DvrMx0P+OE+yFvWqr3P7bVhPO/zvO/uDz/zfL8N8vz3yzPf7MmnP9yD74usszcCiy1ttPP+nyO8cntF+qqCe8/SHVNfhfw6kLHWLBBSm6uAvatl/cFrp+h/L49yxP/MyRJkqRWy8wP9iNuROwM/H799nLgj2caEKHe7409b0/LzFtL122QkpvLgKPr5UOAc6YqGBF7MN7leFtmlhtyRJIkSRpuvYMbPKF+zcbbepbPBIonN4M0z81/9SwfM0PZZ/Ysn9WHukiSJElaYgap5+Y8qofA1gJPiYiDM/OSiYUiYjnw2p5Vn55YRpIkSdL8ZOZGZjk0dUR0e/br+3DWA9Nzk5mjwFt7Vn2iHqVhoncDv10vn5+ZZ/e9cpIkSZIaN0g9NwCnAc8Dng4cBFwaEacBVwC/CZwAPKkuuxF4RROVlCRJkrT4Biq5ycytEfF84FPAs6luUXvTJEVvBI7PzMsXs36SJEmSmjPS7XZnLrUERcRzgBdRjZy2hmqizmuBLwCnLoUZUiVJkqRhttjP3AxsciNJkiRJvQZmQAFJkiRJmo7JjSRJkqRWMLmRJEmS1AomN5IkSZJaweRGkiRJUiuY3EiSJElqBZMbSZIkSa1gciNJkiSpFbZpugKDJCKOA04CDgHWApuAa4AzgFMzc1OD1WuliDgXOGIOu+ybmdf3pzbtERHLgQOAxwKPqf99FLB9XeTjmflHc4z5UOAVwDHAXsBy4CbgG8BpmfnDIpVvgVLnPyL+CPjoHA79lsz867nUtY0iYhXwO8CRwMHAw4BdgHuBm4ELgU8BZ2fmrGa6tv3PXqnzb/ufn4g4BHgc1bXMQcBqYHdgW2AjcCVwDvCxzPzZLGPuSdX+jwX2ofpddgvwHeD0zPx22Z9CmprJzSxExE7AJ4HjJmxaXb8eD7wmIl6Qmd9b7PpJ8/AfwO+WChYRLwf+gfGL8zH71a9XRMRbM/OtpY454Iqef81eRPwZ8A5g5SSbVwH716+TgO9ExAsz8+czxLT9z1I/zr/m7Bxgxym2ralfRwCnRMRbMvNd0wWLiOdQJZm7Ttj0W/XrxRFxKvDqzBxdUM2lWTC5mUH9DetngaPrVbcCpwFXAL8JnAA8keqburMi4omZeWUTdR0Cz5tFmdv6Xot2WD7h/Z3AeqpvUOckIl4InFq/7QCfBr4JbKX6bLwY2A54S0T8MjPfM99Kt0ix89/jA8C3Zijz4wXEb4v9GL+wHutZuZjqd8dK4DDghcBOwJOBcyPisMyc9HeL7X/Oip7/Hrb/ubmNqofsUuA64C6qnpt9gGdRtd3tgHdGxLZTJeYRcSTVlzUr6lVfAb4M3EPVK/fHwM5UvTpd4FX9+XGkcSY3MzuZ8cTmCuCpmXlrz/YPRcR7gddRfWtxKnD44lZxOGTmF5uuQ4tcSHXrwcXAxZl53Txu8SAiVgMfqt92gOdl5pd7inwiIj5KdbG3A/D2iPhiZl610B9gwBU5/xNc4mdkVrrA14D3At/MzM6E7R+PiHcDZ1P1IOwLvBt46cRAtv95KXb+J7D9z95hwOXT3PL3roh4EfAxYAR4U0R8JDNv7i0UEdsBpzOe2LwmMz/YU+STdY/NeVS38r8yIj6bmTMlodKCOKDANOpemzf3rDppQmIz5vXA2P3UT46I3+l75aQFyMx3ZuYpmfm5zLxuAaH+HPiNevlDEy7sxo71PeBN9dttuP9naigVPP+auzdk5jMy8+uTXFgDUD9ncHzPquMjYodJitr+567k+dc8ZGXaZ8ky8xPAmfXbbRj/krfXS6l6egD+c0JiMxbnauDVPavePucKS3NkcjO9w4E96+XzMvOSyQrV95C+v2fVCf2umLRE9F6A/P005U6juk0B4LiImPhsgrQoMvPOWZa7FBjrYdkBeOgkxWz/c1T4/Ku/Lu9ZXjvJ9j/oWX7fNHG+CFxfLz8+Ih68wHpJ0zK5md4xPctnzVD2q1PsJ7VSRBwIjP2RunK6HojM/AXVqDlQPcg6lxHwpKb0joB5v4TE9r8opjz/WhS9CeW63g31iHdPqt/2tu9fU/fQ/VfPKq+R1Fc+czO9R/Qsf3+6gpm5LiJuoBpYYI+IWJ2Zt/e1dkMmIs4EHk01Qt09VEOGfhf4VGae02TdhtSsPx89ZcZubXgE9/9jp4X7k4h4PdXvoGXAHVS3y36VamjpzU1WbtBExAqqh9/HTBwS1/bfR7M4/xPZ/guKiGMZH8RnC9VAAb0OZPwL8h/MYhS07wOvrJcfMV1BaaFMbqa3f8/ybO6Lv47qF+vYviY3ZT2rZ3mX+nUgcHJEfAt4YWbe0kjNhtN8Ph+T7asyDpnwfq/6dSzVSF0vzcwzf303TeFEqlGeoHpYfd2E7bb//prp/E9k+5+HiDicauRXqAYG2ItqDqKxZ4e3Aq+c5Hlj27+WLJOb6e3Ss3zHLMqvn2JfLcwG4OvARVRDh44CDwSOoureHgGeClxQDxk60x9BleHnY2kYBS6gui3kauBuqvP7GOAFVBcuq4EvR8QfZua/N1XRQVGPgtY7ZPNkD0Hb/vtklud/jO1/Yf4GOHSS9V2qUc7ePMUEnLZ/LVkmN9PbqWd5yyzK39uzvKpwXYbVKVRD5d43ybb3RcRjgc8De1Pd/3468MxFrN8w8/PRvP8G9snMGyfZ9pGI+Auqh9mPp/oS4PSION9JEadW3w71eaqJDAG+mJlnTFLU9t8Hczj/YPvvp5uovlT8yRTbbf9ashxQQEtaZl4wRWIztv0iqvvYf1mvOiYiJt6eILVSZl4zxYXd2PZfAH8InFuvWkk1dL0mERHLqL4geXK96lpmnl9Fhcz1/Nv+Fy4zD8vMkcwcoUpYfhv4v1QJyDuAyyLiaU3WUZork5vp3d2zvHLKUuN6R3P5ReG6aAqZeSXwrz2rnt1UXYaMn48BUD/o+8aeVX4+JhERI8A/UV0MA/wceFpmbphiF9t/QfM4/7Ni+5+9zLwnMy/NzLdRDd5zM7Ab8JWImDgIgO1fS5bJzfQ29izvPovyu02xr/qvd7S0AxqrxXDx8zE4LmD81pG9nRDx/uoL6/8HvKxedSPw1My8fprdbP+FzPP8z4Xtf47qoc3/sn67AnjDhCK2fy1ZJjfTu6pned9ZlO8tc9WUpdQPvSPT+bDi4vDzMSDqeSZ6J0/0M1KrL6w/xPgwtTcBR2bmtTPsavsvYAHnf9Zs//PWO3/fUyZss/1ryTK5md5lPcvTPscREXswPgz0bc5xs+h6vznyW6HFMevPxyRlsnBdNI36WYZde1b5GeF+F9avqlfdTHVhfc0sdrf9L9ACz/9cjmP7n5/e28d2nbDtCqBTLz86IpbPEMv2r0VjcjO9ucyo2ztC11l9qIumd2TPst8KLYLMvILqvniAAyJin6nKRsROjD8kvJlqiFEtnsMYv+f9Ric0nPTC+haqC+upRoe6H9v/wiz0/M+R7X9+HtazfL8vbOvBGs6v364CnjRVkDq5fEbPqq9OVVYqweRmeucBY3OmPCUiDp6sUP2NxWt7Vn263xXTuIjYDzipZ5UTtS2ez/Qs/9k05V4O7Fgvf9mLi8VTX1i8tWeVn4/KBxm/sF5HdWF99Rxj2P7nr8T5n5Htf0Fe2bN8/iTbe691XjdNnOcyflva9wo+SyVNyuRmGvUoK72/FD8REWsmKfpuquETAc7PzLP7XrkhEBGvjYgnzFDm0cDZjI/W8rXM/J++V05j3sv4rQuvjojjJhaIiEOBt9VvtwJvWaS6tVpEPD4iXh4RU45UFBE7Ap+gmvAWqiHT3zNV+WERER8A/qR+uw54SmbOp8fX9j8PJc6/7X9+IuKVEXFk3XM2VZnlEfGXjP8fQTXgw0SnM957eWxEvHqSWA+j6qEb86Z5VFuak5Fut9t0HZa0iNiG6jazp9er1lFNCnYF1czHJzDeHbsReFJmXr7Y9WyjiPgi8ByquQ6+QXWf7nqqGakfQPUH65mMJ+k/A56QmTcvfm0HS0TsC/zxhNWPBI6tl38E/OeE7d/KzG9NEuvFwMfqtx2qb/O+TvX/9ETgxYwnn2/IzHcutP6DrsT5j4jnAmdQDcn6deBi4AbgHmBn4GDgDxgfpagLvCgz/63cTzJ4IuLtjI/81AX+CvjxLHa9ZLLJH23/c1Pq/Nv+5yciPkbVJm+gOm+XAbcB91ENtBBUf3f36dntXZn5V1PEexrVNdK29aozgS9T/T8cDJxM9f8BcFpmvrzcTyNNbpumK7DUZebWiHg+8Cmq8fHXMvk3DzcCx5vY9MVD6td0zgZeamIzaw/m14f27PXI+tVrK/BryU1mfrweWvV9VBdxJ9avXqPAO4b9wq5HsfNPNfHe8+rXVNYBJ2fmV+ZSyZbqfTZgBHjXLPd7CeNJzP+y/c9Z0fOP7X++9mLmCWrvAk7JzA9PVSAzvxERx1P14uxCdZ002VxCpzF+G6LUVyY3s1A/OHdsRDwHeBHVqB9rqG5HuBb4AnBqZt7VXC1b6XVU314fCjyK6pzvDmxH9Uv3eqr5Cz7prWjNyswPR8Q3qO7RPprqD+cyqtGPvgn8c2b+oMEqttE3qL5hPRR4HNU5343qAmMz1bexlwBfAf4jM7dMEUcLZPtvhO1/fl4LfAk4nGqizodQ/V3dlqoX7FaqnuOzgc/O5romM8+IiO9RJS/HUvX6rKQaJOK/gX/JzKEfREOLx9vSJEmSJLWCAwpIkiRJagWTG0mSJEmtYHIjSZIkqRVMbiRJkiS1gsmNJEmSpFYwuZEkSZLUCiY3kiRJklrB5EaSJElSK5jcSJIkSWoFkxtJkiRJrWByI0mSJKkVTG4kSZIktYLJjSRJkqRWMLmRJEmS1AomN5IkSZJaweRGkiRJUiuY3EiSJElqBZMbSZIkSa1gciNJkiSpFUxuJEmSJLWCyY0kSZKkVjC5kSRJktQKJjeSJEmSWsHkRpIkSVIrmNxIkiRJaoX/DzKjsU+fj7W1AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "from matplotlib.colors import ListedColormap, LinearSegmentedColormap\n",
    "def plot_examples(colormaps):\n",
    "    \"\"\"\n",
    "    Helper function to plot data with associated colormap.\n",
    "    \"\"\"\n",
    "    np.random.seed(19680801)\n",
    "    data = np.random.randn(30, 30)\n",
    "    n = len(colormaps)\n",
    "    fig, axs = plt.subplots(1, n, figsize=(n * 2 + 2, 3),\n",
    "                            constrained_layout=True, squeeze=False)\n",
    "    for [ax, cmap] in zip(axs.flat, colormaps):\n",
    "        psm = ax.pcolormesh(data, cmap=cmap, rasterized=True, vmin=-4, vmax=4)\n",
    "        fig.colorbar(psm, ax=ax)\n",
    "    plt.show()    \n",
    "\n",
    "top = cm.get_cmap('Oranges_r', 128)\n",
    "bottom = cm.get_cmap('Purples', 128)\n",
    "\n",
    "newcolors = np.vstack((top(np.linspace(0, 1, 128)),\n",
    "                       bottom(np.linspace(0, 1, 128))))\n",
    "orange_cm = ListedColormap(newcolors, name='OrangeBlue')\n",
    "plot_examples([orange_cm])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"599.9999910593034\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, '$\\\\varphi_l/2\\\\pi$')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig, ax = plt.subplots(2, 2, sharex=True, sharey=True, figsize=(6, 5))\n",
    "plt.subplots_adjust(\n",
    "    left=0.12,\n",
    "    bottom=None, \n",
    "    right=0.9,\n",
    "    top=None, \n",
    "    wspace=None, \n",
    "    hspace=None)\n",
    "cb = defaultdict(lambda: defaultdict(int))\n",
    "im = defaultdict(lambda: defaultdict(int))\n",
    "\n",
    "im[0][0] = ax[0][0].imshow(result[\"potential\"],\n",
    "                           extent=[LOWER, UPPER, LOWER, UPPER],\n",
    "                           origin='lower',\n",
    "                           #cmap='viridis',\n",
    "                           interpolation='bessel',\n",
    "                           vmin=0, vmax=2.2)\n",
    "ax[0][0].set_title(r\"$U_{min}/E_J$\", fontsize=14, loc=\"left\")\n",
    "\n",
    "im[0][1] = ax[0][1].imshow(result[\"phi02\"],\n",
    "                           extent=[LOWER, UPPER, LOWER, UPPER],\n",
    "                           origin='lower',\n",
    "                           cmap=orange_cm,\n",
    "                           interpolation='bessel',\n",
    "                           vmin=-0.5, vmax=0.5)\n",
    "ax[0][1].set_title(r\"$\\varphi_{02}$\", fontsize=14)\n",
    "\n",
    "im[1][0] = ax[1][0].imshow(result[\"phi01\"] + result[\"phi01\"],\n",
    "                           extent=[LOWER, UPPER, LOWER, UPPER],\n",
    "                           origin='lower',\n",
    "                           cmap=orange_cm,\n",
    "                           interpolation='bessel',\n",
    "                           vmin=-0.5, vmax=0.5)\n",
    "ax[1][0].set_title(r\"$\\varphi_{01} + \\varphi_{12}$\", fontsize=14)\n",
    "\n",
    "im[1][1] = ax[1][1].imshow(result[\"phi03\"] + result[\"phi03\"],\n",
    "                           extent=[LOWER, UPPER, LOWER, UPPER],\n",
    "                           origin='lower',\n",
    "                           cmap=orange_cm,\n",
    "                           interpolation='bessel',\n",
    "                           vmin=-0.5, vmax=0.5)\n",
    "ax[1][1].set_title(r\"$\\varphi_{03} + \\varphi_{32}$\", fontsize=14)\n",
    "\n",
    "# Colorbars\n",
    "for (i, j) in list(itertools.product([0, 1], [0, 1])):\n",
    "    if i == 0 and j == 0:\n",
    "        cb[i][j] = fig.colorbar(im[i][j], ax=ax[i][j],\n",
    "                                fraction=0.046, pad=0.04)\n",
    "        cb[i][j].ax.set_ylabel(\n",
    "            r\"$\\frac{U_{min}}{E_J}$\", fontsize=14, rotation=0, ha=\"left\", labelpad=-20, y=1.15)\n",
    "        cb[i][j].set_ticks([0, 0.5, 1, 1.5, 2])\n",
    "    else:\n",
    "        cb[i][j] = fig.colorbar(im[i][j], ax=ax[i][j],\n",
    "                                fraction=0.046, pad=0.04)\n",
    "        cb[i][j].ax.set_ylabel(\n",
    "            r\"$\\frac{\\varphi}{2\\pi}$\", fontsize=12, rotation=0, ha=\"left\", labelpad=-40, y=1.15)\n",
    "        cb[i][j].set_ticks([-0.5, 0, 0.5])\n",
    "    cb[i][j].ax.tick_params(labelsize=12)\n",
    "\n",
    "# X ticks\n",
    "ax[0][0].set_xticks([-0.5, 0, 0.5, 1, 1.5])\n",
    "# Axes Labels\n",
    "ax[0][0].set_ylabel(r\"$\\varphi_r/2\\pi$\", fontsize=14)\n",
    "ax[1][0].set_xlabel(r\"$\\varphi_l/2\\pi$\", fontsize=14)\n",
    "ax[1][0].set_ylabel(r\"$\\varphi_r/2\\pi$\", fontsize=14)\n",
    "ax[1][1].set_xlabel(r\"$\\varphi_l/2\\pi$\", fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Supplementary points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fc70be8b5f8>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Degeneracy\n",
    "phiT0 = 2 * math.acos(math.sqrt(float(ALPHA ** 2 + 1)) - ALPHA) / (2 * math.pi)\n",
    "phiT1 = (2 * pi - 2 *\n",
    "         math.acos(math.sqrt(float(ALPHA ** 2 + 1)) - ALPHA)) / (2 * math.pi)\n",
    "ax[0][0].scatter(float(phiT0), float(phiT0), marker='D', color='red', s=15)\n",
    "ax[0][0].scatter(float(phiT1), float(phiT1), marker='D', color='red', s=15)\n",
    "ax[0][0].scatter(float(0.5), float(0.5), marker='D', color='C9', s=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Supplementary lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.patches.FancyArrow at 0x7fc70bea1f98>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax[0][0].arrow(0.25, 0.25,\n",
    "            0.5, 0.5,\n",
    "            color='red', head_width=0.1, head_starts_at_zero=False, linewidth=0.8)\n",
    "ax[0][0].arrow(0.25, 0.75,\n",
    "            0.5, -0.5,\n",
    "            color='yellow', head_width=0.12, head_starts_at_zero=False, \n",
    "               linestyle=(0, (2,5)),\n",
    "               linewidth=1)\n",
    "\n",
    "# curve2_coords = evaluate_endpoints_for_2d_phi_plus_slice(0.6, 0.2)\n",
    "# ax_2d.plot([curve2_coords[\"x0\"], curve2_coords[\"x1\"]],\n",
    "#            [curve2_coords[\"y0\"], curve2_coords[\"y1\"]])\n",
    "# curve3_coords = evaluate_endpoints_for_2d_phi_plus_slice(0.55, 0.2)\n",
    "# ax_2d.plot([curve3_coords[\"x0\"], curve3_coords[\"x1\"]],\n",
    "#            [curve3_coords[\"y0\"], curve3_coords[\"y1\"]])\n",
    "# curve4_coords = evaluate_endpoints_for_2d_phi_plus_slice(0.5, 0.2)\n",
    "# ax_2d.plot([curve4_coords[\"x0\"], curve4_coords[\"x1\"]],\n",
    "#            [curve4_coords[\"y0\"], curve4_coords[\"y1\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotter.save_onto_white_background(ax, \"./output/potential_minimum_diamonds\", \"svg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Individual plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"399.99999403953564\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig, ax = plt.subplots(1, 1, sharex=True, sharey=True, figsize=(4, 3))\n",
    "# plt.subplots_adjust(\n",
    "#     left=0.12,\n",
    "#     bottom=None, \n",
    "#     right=0.9,\n",
    "#     top=None, \n",
    "#     wspace=None, \n",
    "#     hspace=None)\n",
    "# cb = defaultdict(lambda: defaultdict(int))\n",
    "# im = defaultdict(lambda: defaultdict(int))\n",
    "\n",
    "im= ax.imshow(result[\"potential\"],\n",
    "                           extent=[LOWER, UPPER, LOWER, UPPER],\n",
    "                           origin='lower',\n",
    "                           #cmap='viridis',\n",
    "                           interpolation='bessel',\n",
    "                           vmin=0, vmax=2.2)\n",
    "\n",
    "# Colorbars\n",
    "cb = fig.colorbar(im, ax=ax, fraction=0.046, pad=0.04)\n",
    "cb.ax.set_ylabel(\n",
    "    r\"$\\frac{U_{min}}{E_J}$\", fontsize=14, rotation=0, ha=\"left\", labelpad=-20, y=1.15)\n",
    "cb.set_ticks([0, 0.5, 1, 1.5, 2])\n",
    "# cb.ax.tick_params(labelsize=12)\n",
    "\n",
    "# X ticks\n",
    "ax.set_xticks([-0.5, 0, 0.5, 1, 1.5])\n",
    "ax.set_yticks([-0.5, 0, 0.5, 1, 1.5])\n",
    "\n",
    "# Axes Labels\n",
    "ax.set_ylabel(r\"$\\varphi_r/2\\pi$\", fontsize=14)\n",
    "ax.set_xlabel(r\"$\\varphi_l/2\\pi$\", fontsize=14)\n",
    "\n",
    "# Degeneracy\n",
    "phiT0 = 2 * math.acos(math.sqrt(float(ALPHA ** 2 + 1)) - ALPHA) / (2 * math.pi)\n",
    "phiT1 = (2 * pi - 2 *\n",
    "         math.acos(math.sqrt(float(ALPHA ** 2 + 1)) - ALPHA)) / (2 * math.pi)\n",
    "ax.scatter(float(phiT0), float(phiT0), marker='D', color='red', s=15)\n",
    "ax.scatter(float(phiT1), float(phiT1), marker='D', color='red', s=15)\n",
    "ax.scatter(float(0.5), float(0.5), marker='D', color='C9', s=15)\n",
    "\n",
    "ax.arrow(0.25, 0.25,\n",
    "            0.5, 0.5,\n",
    "            color='red', head_width=0.1, head_starts_at_zero=False, linewidth=0.8)\n",
    "ax.arrow(0.25, 0.75,\n",
    "            0.5, -0.5,\n",
    "            color='yellow', head_width=0.12, head_starts_at_zero=False, \n",
    "               linestyle=(0, (2,5)),\n",
    "               linewidth=1)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotter.save_onto_white_background(ax, \"./output/potential_minimum_energy\", \"svg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## 3D Plot of potential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"499.9999925494195\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7fc709d597f0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "fig = plt.figure(figsize=(5,5))\n",
    "ax = fig.gca(projection='3d')\n",
    "\n",
    "grid_x, grid_y = np.meshgrid(lr_array, lr_array)\n",
    "surf = ax.plot_surface(grid_x, grid_y, \n",
    "                       result[\"potential\"],\n",
    "                       #result[\"phi02\"], \n",
    "                       #quadrants[\"potential\"][0][0],\n",
    "                       cmap=cm.viridis,\n",
    "                       linewidth=0, antialiased=True)\n",
    "ax.plot\n",
    "fig.colorbar(surf, shrink=0.5, aspect=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Parabollic approximation comparisson\n",
    "- Along $\\varphi_l == \\varphi_r$\n",
    "- Along $\\frac{\\varphi_l + \\varphi_r}{2} = \\pi \\equiv \\varphi_+$ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "### Naive approximation\n",
    "Just immediately expand the cosines, no thinking about if it is valid\n",
    "$$\\varphi_{02} \\approx \\frac{\\varphi_l-\\varphi_r - 2\\pi(L-R)}{2(1+\\alpha)}$$\n",
    "$$\\frac{U_\\text{min}}{E_J}   \\approx \\left(\\frac{\\varphi_{02}   - \\varphi_l + 2\\pi L}{2}\\right)^2 + \\left(\\frac{\\varphi_{02} +  \\varphi_r - 2\\pi R}{2}\\right)^2 + \\frac{\\alpha}{2}\\varphi_{02}^2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "cell_style": "split",
    "hidden": true
   },
   "outputs": [],
   "source": [
    "def phi02_naive_approximation(phi_l: float, phi_r: float, L: int, R: int, alpha: float):\n",
    "    return (phi_l - phi_r - 2 * pi * (L - R)) / (2 * (1 + alpha))\n",
    "\n",
    "\n",
    "def potential_naive_approximation(phi02: float, phi_l: float, phi_r: float, L: int, R: int, alpha: float):\n",
    "    \n",
    "    #return ((phi02 - phi_l + 2 * pi * L)**2) / 4 + ((phi02 + phi_r - 2 * pi * R) ** 2 / 4) + alpha * phi02 # (alpha * phi02 ** 2) / 2\n",
    "    \n",
    "    return (phi02 - phi_l + 2 * pi * L) ** 2 / 4 + (phi02 + phi_r - 2 * pi * R) ** 2 / 4 + alpha * phi02 ** 2 / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "cell_style": "split",
    "hidden": true
   },
   "outputs": [],
   "source": [
    "potential_slice_naive = defaultdict(list)\n",
    "alpha = 1\n",
    "\n",
    "for phi_l_idx, phi_l in enumerate(lr_array):\n",
    "    phi_r_idx = len(lr_array) - phi_l_idx - 1\n",
    "    phi_r = lr_array[phi_r_idx]\n",
    "\n",
    "    potential_slice_naive[\"potential_phi_plus\"].append(\n",
    "        result[\"potential\"][phi_l_idx][phi_r_idx]\n",
    "    )\n",
    "\n",
    "    min_potential = None\n",
    "    for (L, R) in itertools.permutations([-1, 0, 1], r=2):\n",
    "        phi02 = phi02_naive_approximation(phi_l, phi_r, L, R, alpha)\n",
    "        potential = potential_naive_approximation(\n",
    "            phi02, phi_l, phi_r, L, R, alpha)\n",
    "\n",
    "        if min_potential is None or potential < min_potential:\n",
    "            min_potential = potential\n",
    "        if L == 0 and R == 1:\n",
    "            potential_slice_naive[\"potential_phi_approximation_01\"].append(potential)\n",
    "        if L == 1 and R == 0:\n",
    "            potential_slice_naive[\"potential_phi_approximation_10\"].append(potential)\n",
    "\n",
    "    potential_slice_naive[\"potential_phi_approximation\"].append(min_potential)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"399.99999403953564\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig, ax = plt.subplots(1, 1, figsize=(4, 1.5))\n",
    "plt.subplots_adjust(left=None, bottom=0.2, right=None, top=None, wspace=1, hspace=None)\n",
    "\n",
    "ax.plot(potential_slice_naive[\"potential_phi_plus\"])\n",
    "ax.plot(potential_slice_naive[\"potential_phi_approximation_01\"], color='red')\n",
    "ax.plot(potential_slice_naive[\"potential_phi_approximation_10\"], color='red')\n",
    "ax.plot(potential_slice_naive[\"potential_phi_approximation\"], color='yellow')\n",
    "\n",
    "\n",
    "# X ticks\n",
    "ax.set_xticks(list(np.linspace(0, NUMBER_OF_FIELD_POINTS, 5)))\n",
    "ax.set_ylim([0, 3])\n",
    "ax.set_xticklabels([-0.5, 0, 0.5, 1, 1.5])\n",
    "None"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Thorough approximation with $\\delta$ from the center\n",
    "$$\\frac{U_\\text{min}}{E_J}   \\approx\\left(\\frac{\\varphi_{02} - \\delta_l}{2}\\right)^2 +  \\left(\\frac{\\varphi_{02}+ \\delta_r}{2}\\right)^2 +\n",
    "        \\frac{\\alpha}{2}\\varphi_{02}^2$$\n",
    "        \n",
    "where we have deviations \n",
    "- $\\delta_l=\\varphi_l-2\\pi    L$\n",
    "- $\\delta_r=\\varphi_r-2\\pi R$ \n",
    "- $\\varphi_{02}   \\approx  \\frac{\\delta_{l}   -  \\delta_r}{2(1+\\alpha)}$\n",
    "\n",
    "from the center of cell $\\{L,R\\}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "cell_style": "split"
   },
   "outputs": [],
   "source": [
    "def potential_approximation(phi_l: float, phi_r: float, L: int, R: int, alpha: float):\n",
    "    delta_l = phi_l - 2 * pi * L\n",
    "    delta_r = phi_r - 2 * pi * R\n",
    "    phi02 = (delta_l - delta_r) / (2 * (1 + alpha))\n",
    "\n",
    "    #return ((phi_02 - delta_l) ** 2) / 4 + ((phi_02 + delta_r) ** 2) / 4 + alpha * phi02 #(alpha * phi02 ** 2) / 2\n",
    "    \n",
    "    return (phi02 - delta_l) ** 2 / 4 + (phi02 + delta_r) ** 2 / 4 + alpha * phi02 ** 2 / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "cell_style": "split"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "done\n"
     ]
    }
   ],
   "source": [
    "potential_slice = defaultdict(list)\n",
    "alpha = 1\n",
    "\n",
    "for phi_l_idx, phi_l in enumerate(lr_array):\n",
    "    phi_r_idx = len(lr_array) - phi_l_idx - 1\n",
    "    phi_r = lr_array[phi_r_idx]\n",
    "\n",
    "    potential_slice[\"potential_phi_plus\"].append(\n",
    "        result[\"potential\"][phi_l_idx][phi_r_idx]\n",
    "    )\n",
    "\n",
    "    min_potential = None\n",
    "    for (L, R) in itertools.permutations([-1, 0, 1], r=2):\n",
    "        potential = potential_approximation(phi_l, phi_r, L, R, alpha)\n",
    "        phi02 = phi02_naive_approximation(phi_l, phi_r, L, R, alpha)\n",
    "        potential_naive = potential_naive_approximation(phi02, phi_l, phi_r, L, R, alpha)\n",
    "        assert abs(potential - potential_naive) < 0.00000001, f\"{potential}--{potential_naive}\"\n",
    "\n",
    "        if min_potential is None or potential < min_potential:\n",
    "            min_potential = potential\n",
    "        if L == 0 and R == 1:\n",
    "            potential_slice[\"potential_phi_approximation_01\"].append(potential)\n",
    "        if L == 1 and R == 0:\n",
    "            potential_slice[\"potential_phi_approximation_10\"].append(potential)\n",
    "\n",
    "    potential_slice[\"potential_phi_approximation\"].append(min_potential)\n",
    "print(\"done\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"399.99999403953564\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "fig, ax = plt.subplots(1, 1, figsize=(4, 3))\n",
    "plt.subplots_adjust(left=None, bottom=0.2, right=None, top=None, wspace=1, hspace=None)\n",
    "\n",
    "ax.plot(potential_slice[\"potential_phi_approximation_01\"], color='red', linestyle=\"--\")\n",
    "ax.plot(potential_slice[\"potential_phi_approximation_10\"], color='red', linestyle=\"--\")\n",
    "# ax.plot(potential_slice[\"potential_phi_approximation\"], color='red')\n",
    "y1 = potential_slice[\"potential_phi_plus\"]\n",
    "\n",
    "# For some reason, raw point cannot be plotted\n",
    "y = np.ones(len(y))\n",
    "for i in range(0, len(y)):\n",
    "    y[i] = y1[i]\n",
    "x = np.arange(0, len(y))\n",
    "\n",
    "# Create a set of line segments so that we can color them individually\n",
    "# This creates the points as a N x 1 x 2 array so that we can stack points\n",
    "# together easily to get the segments. The segments array for line collection\n",
    "# needs to be numlines x points per line x 2 (x and y)\n",
    "points = np.array([x, y]).T.reshape(-1, 1, 2)\n",
    "segments = np.concatenate([points[:-1], points[1:]], axis=1)\n",
    "lc = LineCollection(segments, \n",
    "                    cmap=plt.get_cmap('viridis'),\n",
    "                    norm=plt.Normalize(0, 1)\n",
    "                   )\n",
    "\n",
    "# Set the data that the cmap will be applied according to\n",
    "lc.set_array(y)\n",
    "lc.set_linewidth(5)\n",
    "# Add to axes - need to set limits as well\n",
    "ax.add_collection(lc)\n",
    "ax.set_xlim([0, len(x)])\n",
    "\n",
    "ax.set_xlabel(r\"$\\varphi_-=(\\varphi_l - \\varphi_r)/2$\",              fontsize=14)\n",
    "ax.set_ylabel(r\"${U_{min}}/{E_J}$\",\n",
    "              fontsize=14\n",
    "#               , fontsize=14, rotation=0, ha=\"left\", labelpad=-20, y=1.15\n",
    "             )\n",
    "\n",
    "# X ticks\n",
    "ax.set_xticks(np.linspace(0, NUMBER_OF_FIELD_POINTS, 5))\n",
    "ax.set_ylim([0, 3])\n",
    "ax.set_xticklabels([-0.5, 0, 0.5, 1, 1.5])\n",
    "# ax.set_yticklabels([])\n",
    "ax.tick_params(labelsize=14)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotter.save_onto_white_background(ax, \"./output/potential_minimum_cross_section\", \"svg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# 2D Plot of potential\n",
    "Investigate region around the degenreacy point"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "from kernels.potential_evaluated_in_phi02_phi01_plane import PotentialEvaluatedInPhi02Phi02Plane\n",
    "\n",
    "NUMBER_OF_PHI_POINTS_FOR_2D = 1000\n",
    "ALPHA_2D_plot = [0.8, 1, 1.2]\n",
    "phi01_bounds = (-0.5, 0.5)\n",
    "phi02_bounds = (0, 1)\n",
    "\n",
    "phi01_array = np.linspace(2 * pi * phi01_bounds[0],\n",
    "                          2 * pi * phi01_bounds[1], NUMBER_OF_PHI_POINTS_FOR_2D)\n",
    "phi02_array = np.linspace(2 * pi * phi02_bounds[0],\n",
    "                          2 * pi * phi02_bounds[1], NUMBER_OF_PHI_POINTS_FOR_2D)\n",
    "phi03_array = np.linspace(2 * pi * phi01_bounds[0],\n",
    "                          2 * pi * phi01_bounds[1], NUMBER_OF_PHI_POINTS_FOR_2D)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Kernel creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🐳 Verified             BLOCKS_PER_GRID=(1000, 1000)\n",
      "🐳 Allocating           THREADS_PER_BLOCK = (10, 10, 10)\n"
     ]
    }
   ],
   "source": [
    "BLOCKS_PER_GRID_FOR_2D = (NUMBER_OF_PHI_POINTS_FOR_2D, NUMBER_OF_PHI_POINTS_FOR_2D)\n",
    "verify_blocks_per_grid(BLOCKS_PER_GRID_FOR_2D)\n",
    "THREADS_PER_BLOCK_FOR_2D = allocate_max_threads()\n",
    "\n",
    "potential_evaluated_in_phi02_phi01_plane = PotentialEvaluatedInPhi02Phi02Plane(NUMBER_OF_PHI_POINTS_FOR_2D, potential_function_cuda)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Array allocation on GPU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "DEVICE_phi01_array = cuda.to_device(phi01_array)\n",
    "DEVICE_phi02_array = cuda.to_device(phi02_array)\n",
    "DEVICE_phi03_array = cuda.to_device(phi03_array)\n",
    "\n",
    "DEVICE_output_2d_plot = cuda.device_array(\n",
    "    shape=(NUMBER_OF_PHI_POINTS_FOR_2D, NUMBER_OF_PHI_POINTS_FOR_2D),\n",
    "    dtype=np.float64,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Running"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "output_2d_plot = {}\n",
    "for alpha in ALPHA_2D_plot:\n",
    "    potential_evaluated_in_phi02_phi01_plane.kernel[BLOCKS_PER_GRID_FOR_2D, THREADS_PER_BLOCK_FOR_2D](\n",
    "        DEVICE_phi01_array,\n",
    "        DEVICE_phi02_array,\n",
    "        DEVICE_phi03_array,\n",
    "        pi,\n",
    "        pi,\n",
    "        alpha,\n",
    "        DEVICE_output_2d_plot,\n",
    "    )\n",
    "    output_2d_plot[f\"{alpha}\"] = (DEVICE_output_2d_plot.copy_to_host())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Post processing\n",
    "Now minimise $U(\\varphi_{01}, \\varphi_{02})$ with respect to $\\varphi_{01}$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Warning\n",
    "Remember! Matplotlib is retarded!\n",
    "If you give it an array (100,20), it will plot:\n",
    "- 100 points along the y axis  **(idx0=100 is for the y axis)** 100 rows\n",
    "- 20 points along the x axis   **(idx1=20 is for the x axis)** 20 columns\n",
    "\n",
    "\n",
    "Therefore for searching the minimal value at each x value, you need to search the top-level axis=1\n",
    "### Because of this, a reflection will be needed for further x-y things plotted onto it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "def reflect_in_line(x_array: List[float], y_array: List[float],\n",
    "                        m: float, c: float) -> Tuple[List[float], List[float]]:\n",
    "    \"\"\"Takes arrays of x-y pairs and reflects them about\n",
    "            y = mx + c\n",
    "    shift -> reflection in line -> -shift\n",
    "    \"\"\"\n",
    "    reflection_matrix = np.matrix([[1 - m**2, 2 * m],\n",
    "                                   [2 * m, m**2 - 1]]) / (1 + m**2)\n",
    "\n",
    "    x_list, y_list = [], []\n",
    "    for (x, y) in zip(x_array, y_array):\n",
    "        vec = np.array([x, y]) - np.array([0, c])\n",
    "        vec = reflection_matrix.dot(vec)\n",
    "        vec = vec.tolist()[0]\n",
    "        vec = vec + np.array([0, c])\n",
    "        x_list.append(vec[0])\n",
    "        y_list.append(vec[1])\n",
    "    return (np.array(x_list), np.array(y_list))\n",
    "\n",
    "def reflect_in_line_points(x, y, m, c) -> Tuple[float, float]:\n",
    "        (reflected_x, reflected_y) = reflect_in_line([x], [y], m, c)\n",
    "        return (reflected_y[0], reflected_x[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "plt.contourf(\n",
    "    phi02_array / (2 * pi),\n",
    "    phi01_array / (2 * pi),\n",
    "    output_2d_plot[\"1\"],\n",
    "    levels=25,\n",
    "    origin=None,\n",
    "    vmin=2, vmax=6)\n",
    "\n",
    "phi02_plot, phi01_plot = reflect_in_line(\n",
    "    phi02_array / (2 * pi),\n",
    "    phi01_array[np.argmin(\n",
    "        output_2d_plot[\"1\"], axis=1)] / (2 * pi),\n",
    "    m=1,\n",
    "    c=-0.5)\n",
    "\n",
    "plt.scatter(phi02_plot, phi01_plot)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Run the search"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "potential_minimised_wrt_phi01_phi03 = defaultdict(lambda: defaultdict(int))\n",
    "\n",
    "for (key, potential_array) in output_2d_plot.items():\n",
    "    min_indexes = np.argmin(potential_array, axis=1)    \n",
    "\n",
    "    potential_minimised_wrt_phi01_phi03[key][\"potential\"] = np.min(potential_array, axis=0)\n",
    "    \n",
    "    (phi02_plot, phi01_plot) = reflect_in_line(\n",
    "        phi02_array, phi01_array[min_indexes], m=1, c=-0.5 * (2 * pi))\n",
    "    potential_minimised_wrt_phi01_phi03[key][\"phi01_plot\"] = phi01_plot\n",
    "    potential_minimised_wrt_phi01_phi03[key][\"phi02_plot\"] = phi02_plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Plotting\n",
    "**Note that in the array**\n",
    "- phi02 runs along index=1\n",
    "- phi01 runs along index=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"pdf\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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     "data": {
      "text/plain": [
       "Text(0, 0.5, '$U_{min}/E_J$')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "FONTSIZE = 17\n",
    "\n",
    "fig = plt.figure(figsize=(9,5))\n",
    "ax = defaultdict(lambda: defaultdict(int))\n",
    "ax[0][0] = fig.add_subplot(2,3,1)\n",
    "ax[0][1] = fig.add_subplot(2,3,2, sharey=ax[0][0])\n",
    "ax[0][2] = fig.add_subplot(2,3,3, sharey=ax[0][1])\n",
    "ax[0][0].tick_params(labelbottom=False)\n",
    "ax[0][1].tick_params(labelleft=False)\n",
    "ax[0][1].tick_params(labelbottom=False)\n",
    "ax[0][2].tick_params(labelleft=False)\n",
    "ax[0][2].tick_params(labelbottom=False)\n",
    "ax[1][0] = fig.add_subplot(2,3,4, sharex=ax[0][0])\n",
    "ax[1][1] = fig.add_subplot(2,3,5, sharex=ax[0][1], sharey=ax[1][0])\n",
    "ax[1][2] = fig.add_subplot(2,3,6, sharex=ax[0][2], sharey=ax[1][0])\n",
    "ax[1][1].tick_params(labelleft=False)\n",
    "ax[1][2].tick_params(labelleft=False)\n",
    "\n",
    "plt.subplots_adjust(left=0.1, bottom=None, right=0.85,\n",
    "                    top=None, wspace=None, hspace=None)\n",
    "cb = defaultdict(lambda: defaultdict(int))\n",
    "im = defaultdict(lambda: defaultdict(int))\n",
    "\n",
    "im[0][0] = ax[0][0].contourf(phi02_array / (2 * pi), phi01_array /\n",
    "                       (2 * pi), output_2d_plot[\"0.8\"], levels=20,\n",
    "                       origin='lower',\n",
    "                       vmin=2, vmax=6)\n",
    "ax[0][0].plot(\n",
    "    potential_minimised_wrt_phi01_phi03[\"0.8\"][\"phi02_plot\"][1:-1] / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"0.8\"][\"phi01_plot\"][1:-1] / (2 * pi),\n",
    "    color='C2', marker='.', alpha=0.05\n",
    ")\n",
    "ax[1][0].set_title(r\"$\\alpha=0.8$\", fontsize=FONTSIZE)\n",
    "ax[1][0].plot(\n",
    "    phi02_array / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"0.8\"][\"potential\"],\n",
    "    color='C2', marker='.', alpha=0.2\n",
    ")\n",
    "\n",
    "im[0][1] = ax[0][1].contourf(phi02_array / (2 * pi), phi01_array /\n",
    "                       (2 * pi), output_2d_plot[\"1\"], levels=20,\n",
    "                       origin='lower',\n",
    "                       vmin=2, vmax=6)\n",
    "ax[0][1].plot(\n",
    "    potential_minimised_wrt_phi01_phi03[\"1\"][\"phi02_plot\"][1:-1] / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"1\"][\"phi01_plot\"][1:-1] / (2 * pi),\n",
    "    color='C2', marker='.', alpha=0.05\n",
    ")\n",
    "ax[1][1].set_title(r\"$\\alpha=1.0$\", fontsize=FONTSIZE)\n",
    "ax[1][1].plot(\n",
    "    phi02_array / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"1\"][\"potential\"],\n",
    "    color='C2', marker='.', alpha=0.2\n",
    ")\n",
    "\n",
    "im[0][2] = ax[0][2].contourf(phi02_array / (2 * pi), phi01_array /\n",
    "                       (2 * pi), output_2d_plot[\"1.2\"], levels=20,\n",
    "                       origin='lower',\n",
    "                       vmin=2, vmax=6)\n",
    "ax[0][2].plot(\n",
    "    potential_minimised_wrt_phi01_phi03[\"1.2\"][\"phi02_plot\"][1:-1] / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"1.2\"][\"phi01_plot\"][1:-1] / (2 * pi),\n",
    "    color='C2', marker='.', alpha=0.05\n",
    ")\n",
    "ax[1][2].set_title(r\"$\\alpha=1.2$\", fontsize=FONTSIZE)\n",
    "ax[1][2].plot(\n",
    "    phi02_array / (2 * pi), \n",
    "    potential_minimised_wrt_phi01_phi03[\"1.2\"][\"potential\"],\n",
    "    color='C2', marker='.', alpha=0.2\n",
    ")\n",
    "\n",
    "#Magic for extra axes to put colorbar\n",
    "(x0, y0, width, height) = ax[0][2].get_position().bounds\n",
    "(w_pad, h_pad, wspace, hspace) = fig.get_constrained_layout_pads()\n",
    "cb_axes = fig.add_axes([x0 + width + wspace / 2, y0, wspace, height])\n",
    "cb_axes.set_visible(False)\n",
    "cb = fig.colorbar(im[0][2], ax=cb_axes,\n",
    "                 fraction=1\n",
    "                 )\n",
    "cb.ax.set_ylabel(\n",
    "    r\"$\\frac{U_{min}}{E_J}$\", fontsize=FONTSIZE, rotation=0, ha=\"left\", labelpad=-30, y=1.25)\n",
    "cb.ax.tick_params(labelsize=FONTSIZE)\n",
    "cb.set_ticks([3, 4, 5, 6])\n",
    "\n",
    "# Axes labels\n",
    "for i in range(0, 3):\n",
    "    ax[1][i].set_xticks([0, 0.5, 1.0])\n",
    "    ax[1][i].set_xlabel(r\"$\\varphi_{02}/2\\pi$\", fontsize=FONTSIZE)\n",
    "    ax[1][i].tick_params(axis='both', which='major', labelsize=FONTSIZE)\n",
    "    ax[0][i].tick_params(axis='both', which='major', labelsize=FONTSIZE)\n",
    "\n",
    "ax[0][0].set_ylabel(r\"$\\varphi_{01}/2\\pi$\", fontsize=FONTSIZE)\n",
    "ax[1][0].set_ylabel(r\"$U_{min}/E_J$\", fontsize=FONTSIZE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "### Add the potential dips in double well\n",
    "\\begin{equation}\n",
    "\\varphi_{02}=\\pi\\pm2\\arccos\\frac{1}{\\alpha}, \\alpha > 1.\n",
    "\\end{equation}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "def dip_evaluator() -> List[Dict]:\n",
    "    \"TODO: alpha=1.2 is hardcoded\"\n",
    "    dip_list = []\n",
    "    for dip_phi02 in [np.pi - 2 * np.arccos(1/1.2),\n",
    "                      np.pi + 2 * np.arccos(1/1.2)]:\n",
    "\n",
    "        # Find the index to extract from other lists\n",
    "        dip_idx = next(idx for (idx, phi02) in enumerate(\n",
    "            phi02_array) if phi02 > dip_phi02)\n",
    "        # Remember - because imshow plots a transpose, we need to take indexes from the reflected arrays\n",
    "        dip_idx_reflected = next(idx for (idx, phi02) in enumerate(\n",
    "            potential_minimised_wrt_phi01_phi03[\"1.2\"][\"phi02_plot\"]) if phi02 > dip_phi02)\n",
    "        \n",
    "        dip_list.append({\n",
    "            \"phi02\": dip_phi02,\n",
    "            \"phi02_reflected\": potential_minimised_wrt_phi01_phi03[\"1.2\"][\"phi02_plot\"][dip_idx_reflected],\n",
    "            \"phi01_reflected\": potential_minimised_wrt_phi01_phi03[\"1.2\"][\"phi01_plot\"][dip_idx_reflected],\n",
    "            \"potential\": potential_minimised_wrt_phi01_phi03[\"1.2\"][\"potential\"][dip_idx]\n",
    "        })\n",
    "    return dip_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7f630c7a0668>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dip_list = dip_evaluator()\n",
    "\n",
    "ax[0][2].scatter(dip_list[0][\"phi02_reflected\"] / (2*pi), dip_list[0][\"phi01_reflected\"] / (2 * pi),\n",
    "                 marker='o', color='C2', s=40)\n",
    "ax[1][2].scatter(dip_list[0][\"phi02\"] / (2*pi), dip_list[0][\"potential\"],\n",
    "                 marker='o', color='C2', s=80)\n",
    "\n",
    "ax[0][2].scatter(dip_list[1][\"phi02_reflected\"] / (2*pi), dip_list[1][\"phi01_reflected\"] / (2 * pi),\n",
    "                 marker='o', color='C2', s=40)\n",
    "ax[1][2].scatter(dip_list[1][\"phi02\"] / (2*pi), dip_list[1][\"potential\"],\n",
    "                 marker='o', color='C2', s=80)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "## Save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "hidden": true
   },
   "outputs": [],
   "source": [
    "plotter.save_onto_white_background(ax, \"./output/potential_inspection\", \"svg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rabi oscillations"
   ]
  }
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