C++/examples/PySESync.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "republican-saudi",
   "metadata": {},
   "source": [
    "# PySESync: SE-Sync Python bindings 🐍"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "configured-creature",
   "metadata": {},
   "source": [
    "This notebook demonstrates the use of SE-Sync's Python bindings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "coated-machinery",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import collections as mc\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from mpl_toolkits.mplot3d.art3d import Line3DCollection\n",
    "import matplotlib.animation as animation\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "toxic-determination",
   "metadata": {},
   "source": [
    "Import the SE-Sync Python library built using pybind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "moderate-inside",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "import PySESync"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fatal-delay",
   "metadata": {},
   "source": [
    "Load in some data from a .g2o file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "acknowledged-albany",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 2512 measurements between 1728 2-dimensional poses from file ../../data/intel.g2o\n"
     ]
    }
   ],
   "source": [
    "filename = \"../../data/intel.g2o\"\n",
    "#filename = \"../../data/parking-garage.g2o\"\n",
    "\n",
    "\n",
    "measurements, num_poses = PySESync.read_g2o_file(filename)\n",
    "\n",
    "d = measurements[0].R.shape[0]\n",
    "\n",
    "print(\"Loaded %d measurements between %d %d-dimensional poses from file %s\" % (len(measurements), num_poses, d, filename))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "special-windsor",
   "metadata": {},
   "source": [
    "### Run SE-Sync!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "lightweight-consent",
   "metadata": {},
   "source": [
    "Set SE-Sync options"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "buried-cuisine",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "opts = PySESync.SESyncOpts()\n",
    "opts.num_threads = 4\n",
    "opts.verbose=True\n",
    "\n",
    "opts.r0 = d\n",
    "opts.formulation = PySESync.Formulation.Explicit    # Options are Simplified or Explicit\n",
    "opts.initialization = PySESync.Initialization.Random   # Options are Chordal or Random\n",
    "\n",
    "# Termination criteria\n",
    "opts.rel_func_decrease_tol = 1e-6\n",
    "opts.min_eig_num_tol = 1e-3\n",
    "opts.max_time = 900\n",
    "\n",
    "# We will record the sequence of iterates generated by the SE-Sync algorithm as it runs,\n",
    "# in order to generate an animation of the solution process\n",
    "opts.log_iterates = True\n",
    "\n",
    "\n",
    "# Save the solution animation to a video file?\n",
    "save_animation = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "40f1577e",
   "metadata": {},
   "source": [
    "Run SE-Sync!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ce473161",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Constructing SE-Sync problem instance ... elapsed computation time: 0.031 seconds\n",
      "\n",
      "========= SE-Sync ==========\n",
      "\n",
      "ALGORITHM SETTINGS:\n",
      "\n",
      "SE-Sync settings:\n",
      " SE-Sync problem formulation: Explicit\n",
      " Initial level of Riemannian staircase: 2\n",
      " Maximum level of Riemannian staircase: 10\n",
      " Tolerance for accepting an eigenvalue as numerically nonnegative in optimality verification: 0.001\n",
      " LOBPCG block size: 4\n",
      " LOBPCG preconditioner maximum fill factor: 3\n",
      " LOBPCG preconditioner drop tolerance: 0.001\n",
      " Maximum number of LOBPCG iterations for escape direction computation: 100\n",
      " Initialization method: random\n",
      " Logging entire sequence of Riemannian Staircase iterates\n",
      " Running SE-Sync with 4 threads\n",
      "\n",
      "Riemannian trust-region settings:\n",
      " Stopping tolerance for norm of Riemannian gradient: 0.01\n",
      " Stopping tolerance for norm of preconditioned Riemannian gradient: 0.0001\n",
      " Stopping tolerance for relative function decrease: 1e-06\n",
      " Stopping tolerance for the norm of an accepted update step: 0.001\n",
      " Maximum number of trust-region iterations: 1000\n",
      " Maximum number of truncated conjugate gradient iterations per outer iteration: 10000\n",
      " STPCG fractional gradient tolerance (kappa): 0.1\n",
      " STPCG target q-superlinear convergence rate (1 + theta): 1.5\n",
      " Preconditioning the truncated conjugate gradient method using regularized Cholesky preconditioner with maximum condition number 1e+06\n",
      "\n",
      "INITIALIZATION:\n",
      " Sampling a random initialization ... \n",
      " SE-Sync initialization finished; elapsed time: 0.002 seconds\n",
      "\n",
      "Initial objective value: 3.01012e+06\n",
      "\n",
      "\n",
      "====== RIEMANNIAN STAIRCASE (level r = 2) ======\n",
      "\n",
      "Truncated-Newton trust-region optimization: \n",
      "\n",
      "Iter:    0, time: 0.000e+00, f:  3.010e+06, |g|: 6.116e+04, |M^{-1}g|: 2.023e+04, Delta: 1.000e+00, inner iters:     0, |h|: 4.540e+00, |h|_M: 1.000e+00, df:  4.522e+03, rho:  9.997e-01. Step accepted\n",
      "Iter:    1, time: 5.000e-03, f:  3.006e+06, |g|: 6.113e+04, |M^{-1}g|: 2.157e+04, Delta: 2.500e+00, inner iters:     0, |h|: 1.174e+01, |h|_M: 2.500e+00, df:  1.195e+04, rho:  9.977e-01. Step accepted\n",
      "Iter:    2, time: 1.400e-02, f:  2.994e+06, |g|: 6.107e+04, |M^{-1}g|: 2.517e+04, Delta: 6.250e+00, inner iters:     0, |h|: 3.151e+01, |h|_M: 6.250e+00, df:  3.434e+04, rho:  9.781e-01. Step accepted\n",
      "Iter:    3, time: 1.800e-02, f:  2.959e+06, |g|: 6.106e+04, |M^{-1}g|: 3.399e+04, Delta: 1.562e+01, inner iters:     0, |h|: 8.774e+01, |h|_M: 1.562e+01, df:  9.911e+04, rho:  8.094e-01. Step accepted\n",
      "Iter:    4, time: 2.300e-02, f:  2.860e+06, |g|: 6.147e+04, |M^{-1}g|: 3.726e+04, Delta: 1.562e+01, inner iters:     0, |h|: 9.062e+01, |h|_M: 1.562e+01, df:  8.713e+04, rho:  8.078e-01. Step accepted\n",
      "Iter:    5, time: 3.100e-02, f:  2.773e+06, |g|: 6.191e+04, |M^{-1}g|: 2.198e+04, Delta: 1.562e+01, inner iters:     0, |h|: 7.154e+01, |h|_M: 1.562e+01, df:  6.836e+04, rho:  9.185e-01. Step accepted\n",
      "Iter:    6, time: 3.400e-02, f:  2.705e+06, |g|: 6.156e+04, |M^{-1}g|: 1.556e+04, Delta: 3.906e+01, inner iters:     0, |h|: 1.480e+02, |h|_M: 3.906e+01, df:  1.327e+05, rho:  8.360e-01. Step accepted\n",
      "Iter:    7, time: 3.900e-02, f:  2.572e+06, |g|: 5.976e+04, |M^{-1}g|: 1.043e+04, Delta: 3.906e+01, inner iters:     0, |h|: 1.110e+02, |h|_M: 3.906e+01, df:  1.081e+05, rho:  8.591e-01. Step accepted\n",
      "Iter:    8, time: 4.500e-02, f:  2.464e+06, |g|: 5.853e+04, |M^{-1}g|: 1.968e+04, Delta: 3.906e+01, inner iters:     1, |h|: 1.470e+02, |h|_M: 3.906e+01, df:  9.140e+04, rho:  8.392e-01. Step accepted\n",
      "Iter:    9, time: 5.000e-02, f:  2.372e+06, |g|: 5.725e+04, |M^{-1}g|: 2.222e+04, Delta: 3.906e+01, inner iters:     1, |h|: 1.445e+02, |h|_M: 3.906e+01, df:  8.852e+04, rho:  8.289e-01. Step accepted\n",
      "Iter:   10, time: 5.500e-02, f:  2.284e+06, |g|: 5.591e+04, |M^{-1}g|: 2.479e+04, Delta: 3.906e+01, inner iters:     1, |h|: 1.512e+02, |h|_M: 3.906e+01, df:  1.040e+05, rho:  1.000e+00. Step accepted\n",
      "Iter:   11, time: 5.900e-02, f:  2.180e+06, |g|: 5.423e+04, |M^{-1}g|: 2.431e+04, Delta: 9.766e+01, inner iters:     2, |h|: 3.354e+02, |h|_M: 9.766e+01, df:  7.269e+04, rho:  3.076e-01. Step accepted\n",
      "Iter:   12, time: 6.400e-02, f:  2.107e+06, |g|: 5.173e+04, |M^{-1}g|: 5.402e+04, Delta: 9.766e+01, inner iters:     2, |h|: 3.514e+02, |h|_M: 9.766e+01, df:  2.633e+04, rho:  5.970e-02. Step accepted\n",
      "Iter:   13, time: 7.000e-02, f:  2.081e+06, |g|: 5.099e+04, |M^{-1}g|: 4.896e+04, Delta: 9.766e+01, inner iters:     2, |h|: 4.099e+02, |h|_M: 9.766e+01, df:  1.817e+05, rho:  5.152e-01. Step accepted\n",
      "Iter:   14, time: 7.800e-02, f:  1.899e+06, |g|: 4.786e+04, |M^{-1}g|: 5.394e+04, Delta: 9.766e+01, inner iters:     2, |h|: 4.692e+02, |h|_M: 9.766e+01, df:  2.842e+04, rho:  7.439e-02. Step accepted\n",
      "Iter:   15, time: 8.300e-02, f:  1.871e+06, |g|: 4.504e+04, |M^{-1}g|: 4.017e+04, Delta: 9.766e+01, inner iters:     2, |h|: 4.533e+02, |h|_M: 9.766e+01, df:  3.960e+04, rho:  1.438e-01. Step accepted\n",
      "Iter:   16, time: 8.800e-02, f:  1.831e+06, |g|: 4.404e+04, |M^{-1}g|: 5.062e+04, Delta: 9.766e+01, inner iters:     2, |h|: 4.589e+02, |h|_M: 9.766e+01, df:  9.451e+04, rho:  3.338e-01. Step accepted\n",
      "Iter:   17, time: 9.300e-02, f:  1.737e+06, |g|: 4.066e+04, |M^{-1}g|: 4.055e+04, Delta: 9.766e+01, inner iters:     2, |h|: 4.465e+02, |h|_M: 9.766e+01, df:  2.503e+04, rho:  5.923e-02. Step accepted\n",
      "Iter:   18, time: 9.800e-02, f:  1.712e+06, |g|: 3.985e+04, |M^{-1}g|: 4.547e+04, Delta: 9.766e+01, inner iters:     1, |h|: 6.068e+02, |h|_M: 9.766e+01, df: -8.170e+04, rho: -1.247e-01. Step REJECTED!\n",
      "Iter:   19, time: 1.010e-01, f:  1.712e+06, |g|: 3.985e+04, |M^{-1}g|: 4.547e+04, Delta: 2.441e+01, inner iters:     0, |h|: 1.494e+02, |h|_M: 2.441e+01, df:  1.230e+05, rho:  1.034e+00. Step accepted\n",
      "Iter:   20, time: 1.040e-01, f:  1.589e+06, |g|: 3.816e+04, |M^{-1}g|: 2.111e+04, Delta: 6.104e+01, inner iters:     1, |h|: 1.844e+02, |h|_M: 6.104e+01, df:  6.462e+04, rho:  5.745e-01. Step accepted\n",
      "Iter:   21, time: 1.080e-01, f:  1.524e+06, |g|: 3.627e+04, |M^{-1}g|: 2.561e+04, Delta: 6.104e+01, inner iters:     1, |h|: 3.222e+02, |h|_M: 6.104e+01, df:  6.977e+03, rho:  4.267e-02. Step REJECTED!\n",
      "Iter:   22, time: 1.130e-01, f:  1.524e+06, |g|: 3.627e+04, |M^{-1}g|: 2.561e+04, Delta: 1.526e+01, inner iters:     0, |h|: 8.491e+01, |h|_M: 1.526e+01, df:  5.331e+04, rho:  9.277e-01. Step accepted\n",
      "Iter:   23, time: 1.170e-01, f:  1.471e+06, |g|: 3.555e+04, |M^{-1}g|: 1.059e+04, Delta: 3.815e+01, inner iters:     1, |h|: 1.295e+02, |h|_M: 3.815e+01, df:  5.123e+04, rho:  8.585e-01. Step accepted\n",
      "Iter:   24, time: 1.210e-01, f:  1.419e+06, |g|: 3.485e+04, |M^{-1}g|: 1.492e+04, Delta: 3.815e+01, inner iters:     2, |h|: 1.286e+02, |h|_M: 3.815e+01, df:  5.624e+04, rho:  8.904e-01. Step accepted\n",
      "Iter:   25, time: 1.280e-01, f:  1.363e+06, |g|: 3.279e+04, |M^{-1}g|: 1.823e+04, Delta: 3.815e+01, inner iters:     2, |h|: 1.637e+02, |h|_M: 3.815e+01, df:  6.270e+04, rho:  9.674e-01. Step accepted\n",
      "Iter:   26, time: 1.330e-01, f:  1.301e+06, |g|: 3.176e+04, |M^{-1}g|: 1.228e+04, Delta: 9.537e+01, inner iters:     2, |h|: 1.810e+02, |h|_M: 9.537e+01, df:  9.756e+04, rho:  8.940e-01. Step accepted\n",
      "Iter:   27, time: 1.380e-01, f:  1.203e+06, |g|: 2.811e+04, |M^{-1}g|: 1.577e+04, Delta: 9.537e+01, inner iters:     3, |h|: 1.837e+02, |h|_M: 9.537e+01, df:  1.152e+05, rho:  9.797e-01. Step accepted\n",
      "Iter:   28, time: 1.430e-01, f:  1.088e+06, |g|: 2.447e+04, |M^{-1}g|: 1.335e+04, Delta: 2.384e+02, inner iters:     4, |h|: 2.751e+02, |h|_M: 2.384e+02, df:  1.290e+05, rho:  7.236e-01. Step accepted\n",
      "Iter:   29, time: 1.480e-01, f:  9.587e+05, |g|: 1.714e+04, |M^{-1}g|: 1.113e+04, Delta: 2.384e+02, inner iters:     8, |h|: 3.096e+02, |h|_M: 2.384e+02, df:  1.135e+05, rho:  7.771e-01. Step accepted\n",
      "Iter:   30, time: 1.600e-01, f:  8.453e+05, |g|: 9.826e+03, |M^{-1}g|: 1.140e+04, Delta: 2.384e+02, inner iters:    10, |h|: 2.684e+02, |h|_M: 2.384e+02, df:  9.176e+03, rho:  1.158e-01. Step accepted\n",
      "Iter:   31, time: 1.760e-01, f:  8.361e+05, |g|: 8.863e+03, |M^{-1}g|: 1.287e+04, Delta: 2.384e+02, inner iters:    16, |h|: 1.823e+02, |h|_M: 2.384e+02, df:  2.574e+04, rho:  3.818e-01. Step accepted\n",
      "Iter:   32, time: 1.920e-01, f:  8.104e+05, |g|: 6.757e+03, |M^{-1}g|: 7.718e+03, Delta: 2.384e+02, inner iters:    13, |h|: 2.187e+02, |h|_M: 2.384e+02, df: -5.049e+04, rho: -1.007e+00. Step REJECTED!\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter:   33, time: 2.070e-01, f:  8.104e+05, |g|: 6.757e+03, |M^{-1}g|: 7.718e+03, Delta: 5.960e+01, inner iters:     8, |h|: 7.714e+01, |h|_M: 5.960e+01, df:  2.965e+04, rho:  9.939e-01. Step accepted\n",
      "Iter:   34, time: 2.180e-01, f:  7.807e+05, |g|: 2.046e+03, |M^{-1}g|: 2.034e+03, Delta: 1.490e+02, inner iters:    23, |h|: 5.251e+01, |h|_M: 1.490e+02, df:  7.903e+02, rho:  1.329e-01. Step accepted\n",
      "Iter:   35, time: 2.490e-01, f:  7.799e+05, |g|: 2.429e+03, |M^{-1}g|: 2.030e+03, Delta: 1.490e+02, inner iters:    15, |h|: 3.089e+01, |h|_M: 4.691e+01, df:  4.344e+03, rho:  9.865e-01. Step accepted\n",
      "Iter:   36, time: 2.660e-01, f:  7.756e+05, |g|: 5.110e+02, |M^{-1}g|: 3.667e+02, Delta: 1.490e+02, inner iters:    28, |h|: 5.306e+01, |h|_M: 1.490e+02, df: -1.106e+03, rho: -9.410e-01. Step REJECTED!\n",
      "Iter:   37, time: 2.900e-01, f:  7.756e+05, |g|: 5.110e+02, |M^{-1}g|: 3.667e+02, Delta: 3.725e+01, inner iters:    17, |h|: 1.427e+01, |h|_M: 3.725e+01, df:  4.448e+02, rho:  9.760e-01. Step accepted\n",
      "Iter:   38, time: 3.060e-01, f:  7.751e+05, |g|: 3.925e+02, |M^{-1}g|: 5.072e+02, Delta: 9.313e+01, inner iters:    22, |h|: 3.092e+01, |h|_M: 9.313e+01, df:  3.454e+02, rho:  5.501e-01. Step accepted\n",
      "Iter:   39, time: 3.260e-01, f:  7.748e+05, |g|: 6.552e+02, |M^{-1}g|: 6.828e+02, Delta: 9.313e+01, inner iters:    33, |h|: 2.677e+01, |h|_M: 9.313e+01, df:  7.048e+02, rho:  9.295e-01. Step accepted\n",
      "Iter:   40, time: 3.530e-01, f:  7.741e+05, |g|: 4.587e+02, |M^{-1}g|: 3.781e+02, Delta: 2.328e+02, inner iters:    48, |h|: 5.165e+01, |h|_M: 2.328e+02, df: -2.134e+03, rho: -2.632e+00. Step REJECTED!\n",
      "Iter:   41, time: 3.920e-01, f:  7.741e+05, |g|: 4.587e+02, |M^{-1}g|: 3.781e+02, Delta: 5.821e+01, inner iters:    31, |h|: 1.880e+01, |h|_M: 5.821e+01, df:  3.556e+02, rho:  9.701e-01. Step accepted\n",
      "Iter:   42, time: 4.180e-01, f:  7.737e+05, |g|: 2.875e+02, |M^{-1}g|: 2.629e+02, Delta: 1.455e+02, inner iters:    47, |h|: 3.715e+01, |h|_M: 1.455e+02, df:  1.766e+02, rho:  4.305e-01. Step accepted\n",
      "Iter:   43, time: 4.550e-01, f:  7.735e+05, |g|: 5.561e+02, |M^{-1}g|: 6.613e+02, Delta: 1.455e+02, inner iters:    19, |h|: 7.929e+00, |h|_M: 1.329e+01, df:  2.700e+02, rho:  1.002e+00. Step accepted\n",
      "Iter:   44, time: 4.740e-01, f:  7.733e+05, |g|: 7.402e+01, |M^{-1}g|: 5.684e+01, Delta: 1.455e+02, inner iters:    44, |h|: 3.885e+01, |h|_M: 1.455e+02, df: -1.767e+02, rho: -8.352e-01. Step REJECTED!\n",
      "Iter:   45, time: 5.330e-01, f:  7.733e+05, |g|: 7.402e+01, |M^{-1}g|: 5.684e+01, Delta: 3.638e+01, inner iters:    26, |h|: 1.068e+01, |h|_M: 3.638e+01, df:  6.213e+01, rho:  9.386e-01. Step accepted\n",
      "Iter:   46, time: 5.720e-01, f:  7.732e+05, |g|: 1.036e+02, |M^{-1}g|: 6.594e+01, Delta: 9.095e+01, inner iters:    44, |h|: 3.041e+01, |h|_M: 9.095e+01, df:  5.957e+01, rho:  4.550e-01. Step accepted\n",
      "Iter:   47, time: 6.330e-01, f:  7.732e+05, |g|: 3.261e+02, |M^{-1}g|: 2.608e+02, Delta: 9.095e+01, inner iters:    30, |h|: 7.911e+00, |h|_M: 1.737e+01, df:  1.125e+02, rho:  1.014e+00. Step accepted\n",
      "Iter:   48, time: 6.730e-01, f:  7.730e+05, |g|: 5.093e+01, |M^{-1}g|: 2.421e+01, Delta: 9.095e+01, inner iters:    37, |h|: 2.395e+01, |h|_M: 9.095e+01, df: -2.198e+01, rho: -2.715e-01. Step REJECTED!\n",
      "Iter:   49, time: 7.230e-01, f:  7.730e+05, |g|: 5.093e+01, |M^{-1}g|: 2.421e+01, Delta: 2.274e+01, inner iters:    26, |h|: 5.858e+00, |h|_M: 2.274e+01, df:  2.282e+01, rho:  9.293e-01. Step accepted\n",
      "Iter:   50, time: 7.600e-01, f:  7.730e+05, |g|: 1.133e+02, |M^{-1}g|: 5.934e+01, Delta: 5.684e+01, inner iters:    36, |h|: 1.556e+01, |h|_M: 5.684e+01, df:  4.366e+01, rho:  7.746e-01. Step accepted\n",
      "Iter:   51, time: 7.980e-01, f:  7.730e+05, |g|: 2.011e+02, |M^{-1}g|: 1.550e+02, Delta: 5.684e+01, inner iters:    55, |h|: 1.523e+01, |h|_M: 5.684e+01, df:  6.670e+01, rho:  8.603e-01. Step accepted\n",
      "Iter:   52, time: 8.540e-01, f:  7.729e+05, |g|: 1.441e+02, |M^{-1}g|: 1.111e+02, Delta: 5.684e+01, inner iters:    62, |h|: 1.489e+01, |h|_M: 5.684e+01, df:  5.326e+01, rho:  9.699e-01. Step accepted\n",
      "Iter:   53, time: 9.120e-01, f:  7.729e+05, |g|: 1.256e+02, |M^{-1}g|: 1.235e+02, Delta: 1.421e+02, inner iters:   102, |h|: 1.718e+01, |h|_M: 7.651e+01, df:  3.521e+01, rho:  8.980e-01. Step accepted\n",
      "Iter:   54, time: 1.007e+00, f:  7.728e+05, |g|: 1.136e+02, |M^{-1}g|: 8.273e+01, Delta: 1.421e+02, inner iters:    76, |h|: 8.600e+00, |h|_M: 2.371e+01, df:  1.986e+01, rho:  1.088e+00. Step accepted\n",
      "Iter:   55, time: 1.074e+00, f:  7.728e+05, |g|: 3.933e+01, |M^{-1}g|: 5.495e+01, Delta: 1.421e+02, inner iters:   149, |h|: 6.002e+01, |h|_M: 1.421e+02, df: -3.420e+02, rho: -1.365e+01. Step REJECTED!\n",
      "Iter:   56, time: 1.205e+00, f:  7.728e+05, |g|: 3.933e+01, |M^{-1}g|: 5.495e+01, Delta: 3.553e+01, inner iters:    71, |h|: 1.442e+01, |h|_M: 3.553e+01, df:  7.496e+00, rho:  8.846e-01. Step accepted\n",
      "Iter:   57, time: 1.272e+00, f:  7.728e+05, |g|: 6.771e+01, |M^{-1}g|: 1.039e+02, Delta: 3.553e+01, inner iters:    44, |h|: 3.444e+00, |h|_M: 9.521e+00, df:  6.615e+00, rho:  1.060e+00. Step accepted\n",
      "Iter:   58, time: 1.312e+00, f:  7.728e+05, |g|: 2.166e+01, |M^{-1}g|: 2.261e+01, Delta: 3.553e+01, inner iters:    52, |h|: 1.605e+01, |h|_M: 3.553e+01, df:  1.015e+00, rho:  1.511e-01. Step accepted\n",
      "Iter:   59, time: 1.371e+00, f:  7.728e+05, |g|: 1.292e+02, |M^{-1}g|: 1.852e+02, Delta: 3.553e+01, inner iters:    17, |h|: 1.280e+00, |h|_M: 2.050e+00, df:  7.492e+00, rho:  1.004e+00. Step accepted\n",
      "Iter:   60, time: 1.395e+00, f:  7.728e+05, |g|: 1.932e+01, |M^{-1}g|: 1.164e+01, Delta: 3.553e+01, inner iters:    68, |h|: 1.277e+01, |h|_M: 3.553e+01, df:  1.724e+00, rho:  2.281e-01. Step accepted\n",
      "Iter:   61, time: 1.467e+00, f:  7.728e+05, |g|: 9.111e+01, |M^{-1}g|: 3.162e+01, Delta: 3.553e+01, inner iters:   110, |h|: 1.057e+01, |h|_M: 3.553e+01, df:  1.381e+01, rho:  1.081e+00. Step accepted\n",
      "Iter:   62, time: 1.564e+00, f:  7.728e+05, |g|: 3.706e+01, |M^{-1}g|: 3.263e+01, Delta: 8.882e+01, inner iters:   130, |h|: 2.363e+01, |h|_M: 8.882e+01, df: -1.983e+01, rho: -1.708e+00. Step REJECTED!\n",
      "Iter:   63, time: 1.664e+00, f:  7.728e+05, |g|: 3.706e+01, |M^{-1}g|: 3.263e+01, Delta: 2.220e+01, inner iters:    82, |h|: 6.139e+00, |h|_M: 2.220e+01, df:  4.613e+00, rho:  9.941e-01. Step accepted\n",
      "Iter:   64, time: 1.728e+00, f:  7.728e+05, |g|: 3.164e+01, |M^{-1}g|: 1.179e+01, Delta: 5.551e+01, inner iters:    93, |h|: 1.587e+01, |h|_M: 5.551e+01, df:  1.798e+00, rho:  2.340e-01. Step accepted\n",
      "Iter:   65, time: 1.800e+00, f:  7.728e+05, |g|: 9.323e+01, |M^{-1}g|: 1.065e+02, Delta: 5.551e+01, inner iters:    32, |h|: 2.445e+00, |h|_M: 4.888e+00, df:  8.063e+00, rho:  1.006e+00. Step accepted\n",
      "Iter:   66, time: 1.832e+00, f:  7.727e+05, |g|: 1.378e+01, |M^{-1}g|: 5.469e+00, Delta: 5.551e+01, inner iters:   120, |h|: 2.149e+01, |h|_M: 5.551e+01, df: -1.372e+00, rho: -2.240e-01. Step REJECTED!\n",
      "Iter:   67, time: 1.922e+00, f:  7.727e+05, |g|: 1.378e+01, |M^{-1}g|: 5.469e+00, Delta: 1.388e+01, inner iters:    68, |h|: 4.479e+00, |h|_M: 1.388e+01, df:  2.400e+00, rho:  9.861e-01. Step accepted\n",
      "Iter:   68, time: 1.977e+00, f:  7.727e+05, |g|: 1.079e+01, |M^{-1}g|: 5.332e+00, Delta: 3.469e+01, inner iters:    88, |h|: 1.384e+01, |h|_M: 3.469e+01, df:  2.140e+00, rho:  6.884e-01. Step accepted\n",
      "Iter:   69, time: 2.047e+00, f:  7.727e+05, |g|: 3.723e+01, |M^{-1}g|: 4.298e+01, Delta: 3.469e+01, inner iters:    53, |h|: 1.501e+00, |h|_M: 5.361e+00, df:  2.276e+00, rho:  1.007e+00. Step accepted\n",
      "Iter:   70, time: 2.098e+00, f:  7.727e+05, |g|: 6.971e+00, |M^{-1}g|: 2.503e+00, Delta: 3.469e+01, inner iters:   102, |h|: 1.581e+01, |h|_M: 3.469e+01, df:  7.763e-01, rho:  3.871e-01. Step accepted\n",
      "Iter:   71, time: 2.177e+00, f:  7.727e+05, |g|: 3.742e+01, |M^{-1}g|: 3.825e+01, Delta: 3.469e+01, inner iters:    36, |h|: 9.146e-01, |h|_M: 2.818e+00, df:  1.742e+00, rho:  1.003e+00. Step accepted\n",
      "Iter:   72, time: 2.207e+00, f:  7.727e+05, |g|: 7.639e+00, |M^{-1}g|: 2.392e+00, Delta: 3.469e+01, inner iters:   124, |h|: 1.415e+01, |h|_M: 3.469e+01, df:  2.410e-01, rho:  1.443e-01. Step accepted\n",
      "\n",
      "Optimization finished!\n",
      "Algorithm terminated due to insufficient relative decrease: 3.119e-07 < 1.000e-06\n",
      "Final objective value: 7.727e+05\n",
      "Norm of Riemannian gradient: 7.639e+00\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Norm of preconditioned Riemannian gradient: 2.392e+00\n",
      "Total elapsed computation time: 2.304e+00 seconds\n",
      "\n",
      "\n",
      "Found first-order critical point with value F(Y) = 772736!  Elapsed computation time: 2.304 seconds\n",
      "\n",
      "Checking second order optimality ... \n",
      "Saddle point detected! Curvature along escape direction: -41.8658.  Elapsed computation time: 0.042 seconds (1 LOBPCG iterations).\n",
      "\n",
      "\n",
      "====== RIEMANNIAN STAIRCASE (level r = 3) ======\n",
      "\n",
      "Truncated-Newton trust-region optimization: \n",
      "\n",
      "Iter:    0, time: 0.000e+00, f:  7.727e+05, |g|: 4.334e+01, |M^{-1}g|: 5.936e+01, Delta: 1.000e+00, inner iters:     1, |h|: 4.908e+00, |h|_M: 1.000e+00, df:  3.441e+02, rho:  9.941e-01. Step accepted\n",
      "Iter:    1, time: 8.000e-03, f:  7.724e+05, |g|: 1.086e+03, |M^{-1}g|: 1.346e+04, Delta: 2.500e+00, inner iters:     0, |h|: 1.719e+01, |h|_M: 2.500e+00, df:  1.875e+04, rho:  9.315e-01. Step accepted\n",
      "Iter:    2, time: 1.100e-02, f:  7.536e+05, |g|: 6.687e+03, |M^{-1}g|: 8.712e+04, Delta: 6.250e+00, inner iters:     0, |h|: 4.259e+01, |h|_M: 6.250e+00, df:  1.170e+05, rho:  7.328e-01. Step accepted\n",
      "Iter:    3, time: 1.500e-02, f:  6.366e+05, |g|: 1.379e+04, |M^{-1}g|: 1.218e+05, Delta: 6.250e+00, inner iters:     0, |h|: 3.887e+01, |h|_M: 6.250e+00, df:  1.191e+05, rho:  8.375e-01. Step accepted\n",
      "Iter:    4, time: 2.000e-02, f:  5.176e+05, |g|: 1.572e+04, |M^{-1}g|: 7.570e+04, Delta: 6.250e+00, inner iters:     0, |h|: 3.483e+01, |h|_M: 6.250e+00, df:  7.495e+04, rho:  8.686e-01. Step accepted\n",
      "Iter:    5, time: 2.300e-02, f:  4.426e+05, |g|: 1.683e+04, |M^{-1}g|: 4.282e+04, Delta: 6.250e+00, inner iters:     0, |h|: 3.127e+01, |h|_M: 6.250e+00, df:  4.714e+04, rho:  8.381e-01. Step accepted\n",
      "Iter:    6, time: 2.700e-02, f:  3.955e+05, |g|: 1.736e+04, |M^{-1}g|: 2.806e+04, Delta: 6.250e+00, inner iters:     0, |h|: 3.434e+01, |h|_M: 6.250e+00, df:  2.980e+04, rho:  9.652e-01. Step accepted\n",
      "Iter:    7, time: 3.000e-02, f:  3.657e+05, |g|: 1.745e+04, |M^{-1}g|: 2.379e+04, Delta: 1.562e+01, inner iters:     0, |h|: 8.806e+01, |h|_M: 1.562e+01, df:  5.515e+04, rho:  8.468e-01. Step accepted\n",
      "Iter:    8, time: 3.400e-02, f:  3.105e+05, |g|: 1.744e+04, |M^{-1}g|: 1.949e+04, Delta: 1.562e+01, inner iters:     0, |h|: 8.769e+01, |h|_M: 1.562e+01, df:  3.929e+04, rho:  7.994e-01. Step accepted\n",
      "Iter:    9, time: 3.900e-02, f:  2.712e+05, |g|: 1.728e+04, |M^{-1}g|: 2.631e+04, Delta: 1.562e+01, inner iters:     1, |h|: 9.063e+01, |h|_M: 1.562e+01, df:  3.771e+04, rho:  8.617e-01. Step accepted\n",
      "Iter:   10, time: 4.400e-02, f:  2.335e+05, |g|: 1.684e+04, |M^{-1}g|: 2.610e+04, Delta: 1.562e+01, inner iters:     1, |h|: 9.769e+01, |h|_M: 1.562e+01, df:  3.525e+04, rho:  8.751e-01. Step accepted\n",
      "Iter:   11, time: 4.900e-02, f:  1.983e+05, |g|: 1.658e+04, |M^{-1}g|: 1.686e+04, Delta: 1.562e+01, inner iters:     1, |h|: 8.021e+01, |h|_M: 1.562e+01, df:  2.612e+04, rho:  9.301e-01. Step accepted\n",
      "Iter:   12, time: 5.700e-02, f:  1.721e+05, |g|: 1.594e+04, |M^{-1}g|: 1.540e+04, Delta: 3.906e+01, inner iters:     2, |h|: 1.530e+02, |h|_M: 3.906e+01, df:  2.127e+04, rho:  4.480e-01. Step accepted\n",
      "Iter:   13, time: 6.400e-02, f:  1.509e+05, |g|: 1.473e+04, |M^{-1}g|: 2.785e+04, Delta: 3.906e+01, inner iters:     3, |h|: 2.080e+02, |h|_M: 3.906e+01, df:  4.478e+04, rho:  8.313e-01. Step accepted\n",
      "Iter:   14, time: 7.300e-02, f:  1.061e+05, |g|: 1.278e+04, |M^{-1}g|: 1.356e+04, Delta: 3.906e+01, inner iters:     2, |h|: 1.618e+02, |h|_M: 3.906e+01, df:  1.231e+04, rho:  3.803e-01. Step accepted\n",
      "Iter:   15, time: 8.000e-02, f:  9.379e+04, |g|: 1.220e+04, |M^{-1}g|: 1.420e+04, Delta: 3.906e+01, inner iters:     3, |h|: 1.436e+02, |h|_M: 3.906e+01, df:  2.952e+04, rho:  1.007e+00. Step accepted\n",
      "Iter:   16, time: 8.900e-02, f:  6.427e+04, |g|: 1.031e+04, |M^{-1}g|: 7.657e+03, Delta: 9.766e+01, inner iters:     4, |h|: 2.563e+02, |h|_M: 9.766e+01, df:  2.186e+04, rho:  5.651e-01. Step accepted\n",
      "Iter:   17, time: 1.000e-01, f:  4.241e+04, |g|: 8.116e+03, |M^{-1}g|: 8.061e+03, Delta: 9.766e+01, inner iters:     5, |h|: 2.767e+02, |h|_M: 9.766e+01, df: -1.089e+04, rho: -2.948e-01. Step REJECTED!\n",
      "Iter:   18, time: 1.100e-01, f:  4.241e+04, |g|: 8.116e+03, |M^{-1}g|: 8.061e+03, Delta: 2.441e+01, inner iters:     2, |h|: 1.301e+02, |h|_M: 2.441e+01, df:  1.469e+04, rho:  9.689e-01. Step accepted\n",
      "Iter:   19, time: 1.160e-01, f:  2.772e+04, |g|: 6.833e+03, |M^{-1}g|: 3.641e+03, Delta: 6.104e+01, inner iters:     4, |h|: 1.124e+02, |h|_M: 6.104e+01, df:  1.229e+04, rho:  8.876e-01. Step accepted\n",
      "Iter:   20, time: 1.280e-01, f:  1.543e+04, |g|: 4.741e+03, |M^{-1}g|: 6.000e+03, Delta: 6.104e+01, inner iters:     6, |h|: 1.471e+02, |h|_M: 6.104e+01, df:  5.600e+03, rho:  5.202e-01. Step accepted\n",
      "Iter:   21, time: 1.400e-01, f:  9.829e+03, |g|: 3.508e+03, |M^{-1}g|: 5.615e+03, Delta: 6.104e+01, inner iters:    10, |h|: 1.232e+02, |h|_M: 6.104e+01, df:  7.057e+03, rho:  7.920e-01. Step accepted\n",
      "Iter:   22, time: 1.580e-01, f:  2.772e+03, |g|: 1.328e+03, |M^{-1}g|: 3.960e+03, Delta: 6.104e+01, inner iters:    11, |h|: 6.473e+01, |h|_M: 1.857e+01, df:  1.863e+03, rho:  9.662e-01. Step accepted\n",
      "Iter:   23, time: 1.770e-01, f:  9.090e+02, |g|: 4.395e+02, |M^{-1}g|: 9.670e+02, Delta: 6.104e+01, inner iters:    19, |h|: 4.271e+02, |h|_M: 6.104e+01, df: -8.297e+04, rho: -1.332e+02. Step REJECTED!\n",
      "Iter:   24, time: 2.080e-01, f:  9.090e+02, |g|: 4.395e+02, |M^{-1}g|: 9.670e+02, Delta: 1.526e+01, inner iters:    13, |h|: 8.818e+01, |h|_M: 1.526e+01, df:  1.516e+02, rho:  5.171e-01. Step accepted\n",
      "Iter:   25, time: 2.310e-01, f:  7.574e+02, |g|: 4.812e+02, |M^{-1}g|: 2.048e+03, Delta: 1.526e+01, inner iters:     7, |h|: 2.018e+01, |h|_M: 3.569e+00, df:  2.210e+02, rho:  1.018e+00. Step accepted\n",
      "Iter:   26, time: 2.460e-01, f:  5.364e+02, |g|: 1.021e+02, |M^{-1}g|: 1.866e+02, Delta: 1.526e+01, inner iters:     6, |h|: 1.208e+02, |h|_M: 1.526e+01, df: -5.627e+02, rho: -3.869e+00. Step REJECTED!\n",
      "Iter:   27, time: 2.600e-01, f:  5.364e+02, |g|: 1.021e+02, |M^{-1}g|: 1.866e+02, Delta: 3.815e+00, inner iters:     5, |h|: 2.952e+01, |h|_M: 3.815e+00, df:  3.376e+01, rho:  8.201e-01. Step accepted\n",
      "Iter:   28, time: 2.720e-01, f:  5.027e+02, |g|: 1.775e+02, |M^{-1}g|: 5.081e+02, Delta: 3.815e+00, inner iters:     6, |h|: 2.841e+01, |h|_M: 3.815e+00, df:  6.608e+01, rho:  1.126e+00. Step accepted\n",
      "Iter:   29, time: 2.820e-01, f:  4.366e+02, |g|: 1.045e+02, |M^{-1}g|: 2.103e+02, Delta: 9.537e+00, inner iters:     7, |h|: 7.426e+01, |h|_M: 9.537e+00, df: -3.856e+01, rho: -4.435e-01. Step REJECTED!\n",
      "Iter:   30, time: 2.930e-01, f:  4.366e+02, |g|: 1.045e+02, |M^{-1}g|: 2.103e+02, Delta: 2.384e+00, inner iters:     4, |h|: 1.811e+01, |h|_M: 2.384e+00, df:  2.861e+01, rho:  9.383e-01. Step accepted\n",
      "Iter:   31, time: 3.020e-01, f:  4.080e+02, |g|: 1.008e+02, |M^{-1}g|: 2.520e+02, Delta: 5.960e+00, inner iters:     6, |h|: 4.699e+01, |h|_M: 5.960e+00, df:  5.591e+01, rho:  1.011e+00. Step accepted\n",
      "Iter:   32, time: 3.130e-01, f:  3.521e+02, |g|: 1.922e+02, |M^{-1}g|: 5.473e+02, Delta: 1.490e+01, inner iters:    14, |h|: 1.049e+02, |h|_M: 1.490e+01, df: -1.536e+02, rho: -1.249e+00. Step REJECTED!\n",
      "Iter:   33, time: 3.360e-01, f:  3.521e+02, |g|: 1.922e+02, |M^{-1}g|: 5.473e+02, Delta: 3.725e+00, inner iters:     7, |h|: 2.475e+01, |h|_M: 3.725e+00, df:  6.088e+01, rho:  1.076e+00. Step accepted\n",
      "Iter:   34, time: 3.490e-01, f:  2.912e+02, |g|: 1.250e+02, |M^{-1}g|: 2.545e+02, Delta: 9.313e+00, inner iters:     8, |h|: 7.055e+01, |h|_M: 9.313e+00, df: -5.963e+01, rho: -7.747e-01. Step REJECTED!\n",
      "Iter:   35, time: 3.640e-01, f:  2.912e+02, |g|: 1.250e+02, |M^{-1}g|: 2.545e+02, Delta: 2.328e+00, inner iters:     6, |h|: 1.569e+01, |h|_M: 2.328e+00, df:  2.912e+01, rho:  1.049e+00. Step accepted\n",
      "Iter:   36, time: 3.770e-01, f:  2.621e+02, |g|: 7.849e+01, |M^{-1}g|: 1.950e+02, Delta: 5.821e+00, inner iters:     6, |h|: 4.178e+01, |h|_M: 5.821e+00, df:  2.876e+01, rho:  5.412e-01. Step accepted\n",
      "Iter:   37, time: 3.910e-01, f:  2.333e+02, |g|: 1.950e+02, |M^{-1}g|: 6.419e+02, Delta: 5.821e+00, inner iters:    14, |h|: 4.036e+01, |h|_M: 5.821e+00, df:  6.493e+01, rho:  1.075e+00. Step accepted\n",
      "Iter:   38, time: 4.130e-01, f:  1.684e+02, |g|: 8.062e+01, |M^{-1}g|: 2.501e+02, Delta: 1.455e+01, inner iters:    21, |h|: 4.489e+01, |h|_M: 5.377e+00, df:  1.447e+01, rho:  5.949e-01. Step accepted\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iter:   39, time: 4.400e-01, f:  1.539e+02, |g|: 1.400e+02, |M^{-1}g|: 5.325e+02, Delta: 1.455e+01, inner iters:    10, |h|: 8.757e+00, |h|_M: 1.644e+00, df:  2.348e+01, rho:  1.070e+00. Step accepted\n",
      "Iter:   40, time: 4.570e-01, f:  1.304e+02, |g|: 3.003e+01, |M^{-1}g|: 7.243e+01, Delta: 1.455e+01, inner iters:    58, |h|: 1.647e+02, |h|_M: 1.455e+01, df: -4.813e+02, rho: -3.295e+01. Step REJECTED!\n",
      "Iter:   41, time: 5.280e-01, f:  1.304e+02, |g|: 3.003e+01, |M^{-1}g|: 7.243e+01, Delta: 3.638e+00, inner iters:    12, |h|: 2.768e+01, |h|_M: 3.638e+00, df: -1.853e-01, rho: -2.295e-02. Step REJECTED!\n",
      "Iter:   42, time: 5.460e-01, f:  1.304e+02, |g|: 3.003e+01, |M^{-1}g|: 7.243e+01, Delta: 9.095e-01, inner iters:     5, |h|: 6.033e+00, |h|_M: 9.095e-01, df:  3.233e+00, rho:  1.075e+00. Step accepted\n",
      "Iter:   43, time: 5.570e-01, f:  1.272e+02, |g|: 3.112e+01, |M^{-1}g|: 5.682e+01, Delta: 2.274e+00, inner iters:     7, |h|: 1.608e+01, |h|_M: 2.274e+00, df:  3.638e+00, rho:  7.471e-01. Step accepted\n",
      "Iter:   44, time: 5.680e-01, f:  1.236e+02, |g|: 5.962e+01, |M^{-1}g|: 1.477e+02, Delta: 2.274e+00, inner iters:    15, |h|: 1.591e+01, |h|_M: 2.060e+00, df:  5.554e+00, rho:  1.091e+00. Step accepted\n",
      "Iter:   45, time: 5.900e-01, f:  1.180e+02, |g|: 1.823e+01, |M^{-1}g|: 4.020e+01, Delta: 5.149e+00, inner iters:    19, |h|: 6.555e+00, |h|_M: 9.326e-01, df:  9.513e-01, rho:  1.174e+00. Step accepted\n",
      "Iter:   46, time: 6.230e-01, f:  1.171e+02, |g|: 9.026e+00, |M^{-1}g|: 1.700e+01, Delta: 5.149e+00, inner iters:    18, |h|: 3.300e+00, |h|_M: 5.419e-01, df:  2.234e-01, rho:  1.158e+00. Step accepted\n",
      "Iter:   47, time: 6.490e-01, f:  1.168e+02, |g|: 3.680e+00, |M^{-1}g|: 7.290e+00, Delta: 5.149e+00, inner iters:    18, |h|: 1.409e+00, |h|_M: 2.412e-01, df:  3.569e-02, rho:  1.093e+00. Step accepted\n",
      "Iter:   48, time: 6.740e-01, f:  1.168e+02, |g|: 1.130e+00, |M^{-1}g|: 1.602e+00, Delta: 5.149e+00, inner iters:    22, |h|: 5.075e-01, |h|_M: 9.222e-02, df:  3.441e-03, rho:  1.020e+00. Step accepted\n",
      "Iter:   49, time: 7.040e-01, f:  1.168e+02, |g|: 2.177e-01, |M^{-1}g|: 2.489e-01, Delta: 5.149e+00, inner iters:    26, |h|: 8.054e-02, |h|_M: 1.337e-02, df:  1.011e-04, rho:  1.001e+00. Step accepted\n",
      "\n",
      "Optimization finished!\n",
      "Algorithm terminated due to insufficient relative decrease: 8.658e-07 < 1.000e-06\n",
      "Final objective value: 1.168e+02\n",
      "Norm of Riemannian gradient: 2.177e-01\n",
      "Norm of preconditioned Riemannian gradient: 2.489e-01\n",
      "Total elapsed computation time: 7.410e-01 seconds\n",
      "\n",
      "\n",
      "Found first-order critical point with value F(Y) = 116.802!  Elapsed computation time: 0.741 seconds\n",
      "\n",
      "Checking second order optimality ... \n",
      "Saddle point detected! Curvature along escape direction: -0.0114243.  Elapsed computation time: 0.049 seconds (2 LOBPCG iterations).\n",
      "\n",
      "\n",
      "====== RIEMANNIAN STAIRCASE (level r = 4) ======\n",
      "\n",
      "Truncated-Newton trust-region optimization: \n",
      "\n",
      "Iter:    0, time: 0.000e+00, f:  1.168e+02, |g|: 3.482e+00, |M^{-1}g|: 7.857e+00, Delta: 1.000e+00, inner iters:     3, |h|: 6.291e+00, |h|_M: 1.000e+00, df: -2.841e-01, rho: -3.770e-01. Step REJECTED!\n",
      "Iter:    1, time: 1.000e-02, f:  1.168e+02, |g|: 3.482e+00, |M^{-1}g|: 7.857e+00, Delta: 2.500e-01, inner iters:     2, |h|: 1.494e+00, |h|_M: 2.500e-01, df:  1.766e-01, rho:  1.052e+00. Step accepted\n",
      "Iter:    2, time: 1.700e-02, f:  1.166e+02, |g|: 9.965e+00, |M^{-1}g|: 2.948e+01, Delta: 6.250e-01, inner iters:     5, |h|: 3.774e+00, |h|_M: 6.250e-01, df:  6.772e-01, rho:  6.089e-01. Step accepted\n",
      "Iter:    3, time: 2.900e-02, f:  1.159e+02, |g|: 2.718e+01, |M^{-1}g|: 5.767e+01, Delta: 6.250e-01, inner iters:     5, |h|: 3.274e+00, |h|_M: 6.250e-01, df:  2.854e+00, rho:  1.182e+00. Step accepted\n",
      "Iter:    4, time: 4.000e-02, f:  1.131e+02, |g|: 1.756e+01, |M^{-1}g|: 5.089e+01, Delta: 1.562e+00, inner iters:     4, |h|: 8.949e+00, |h|_M: 1.562e+00, df: -5.546e+00, rho: -8.511e-01. Step REJECTED!\n",
      "Iter:    5, time: 4.800e-02, f:  1.131e+02, |g|: 1.756e+01, |M^{-1}g|: 5.089e+01, Delta: 3.906e-01, inner iters:     2, |h|: 2.150e+00, |h|_M: 3.906e-01, df:  1.630e+00, rho:  9.671e-01. Step accepted\n",
      "Iter:    6, time: 5.500e-02, f:  1.115e+02, |g|: 2.813e+01, |M^{-1}g|: 8.038e+01, Delta: 9.766e-01, inner iters:     4, |h|: 5.485e+00, |h|_M: 9.766e-01, df:  4.180e+00, rho:  8.913e-01. Step accepted\n",
      "Iter:    7, time: 6.600e-02, f:  1.073e+02, |g|: 6.859e+01, |M^{-1}g|: 1.598e+02, Delta: 9.766e-01, inner iters:     4, |h|: 5.270e+00, |h|_M: 9.766e-01, df:  6.228e+00, rho:  8.985e-01. Step accepted\n",
      "Iter:    8, time: 7.600e-02, f:  1.011e+02, |g|: 6.713e+01, |M^{-1}g|: 1.665e+02, Delta: 9.766e-01, inner iters:     5, |h|: 5.059e+00, |h|_M: 9.766e-01, df:  9.421e+00, rho:  1.180e+00. Step accepted\n",
      "Iter:    9, time: 8.600e-02, f:  9.163e+01, |g|: 4.516e+01, |M^{-1}g|: 1.292e+02, Delta: 2.441e+00, inner iters:     5, |h|: 1.280e+01, |h|_M: 2.441e+00, df: -3.167e+00, rho: -2.465e-01. Step REJECTED!\n",
      "Iter:   10, time: 9.700e-02, f:  9.163e+01, |g|: 4.516e+01, |M^{-1}g|: 1.292e+02, Delta: 6.104e-01, inner iters:     3, |h|: 2.999e+00, |h|_M: 6.104e-01, df:  5.179e+00, rho:  1.077e+00. Step accepted\n",
      "Iter:   11, time: 1.070e-01, f:  8.645e+01, |g|: 3.150e+01, |M^{-1}g|: 1.007e+02, Delta: 1.526e+00, inner iters:     4, |h|: 7.893e+00, |h|_M: 1.526e+00, df:  6.756e+00, rho:  7.792e-01. Step accepted\n",
      "Iter:   12, time: 1.190e-01, f:  7.970e+01, |g|: 7.902e+01, |M^{-1}g|: 1.688e+02, Delta: 1.526e+00, inner iters:     7, |h|: 8.040e+00, |h|_M: 1.526e+00, df:  1.104e+01, rho:  1.070e+00. Step accepted\n",
      "Iter:   13, time: 1.340e-01, f:  6.866e+01, |g|: 5.332e+01, |M^{-1}g|: 1.314e+02, Delta: 3.815e+00, inner iters:    15, |h|: 2.014e+01, |h|_M: 2.467e+00, df:  8.820e+00, rho:  1.103e+00. Step accepted\n",
      "Iter:   14, time: 1.590e-01, f:  5.984e+01, |g|: 3.192e+01, |M^{-1}g|: 1.273e+02, Delta: 6.167e+00, inner iters:    11, |h|: 6.003e+00, |h|_M: 1.014e+00, df:  3.808e+00, rho:  1.160e+00. Step accepted\n",
      "Iter:   15, time: 1.800e-01, f:  5.603e+01, |g|: 3.052e+01, |M^{-1}g|: 6.802e+01, Delta: 6.167e+00, inner iters:    15, |h|: 1.347e+01, |h|_M: 1.409e+00, df:  2.194e+00, rho:  1.109e+00. Step accepted\n",
      "Iter:   16, time: 2.070e-01, f:  5.383e+01, |g|: 1.728e+01, |M^{-1}g|: 8.146e+01, Delta: 6.167e+00, inner iters:    10, |h|: 3.105e+00, |h|_M: 6.492e-01, df:  8.461e-01, rho:  9.439e-01. Step accepted\n",
      "Iter:   17, time: 2.280e-01, f:  5.299e+01, |g|: 2.084e+01, |M^{-1}g|: 4.291e+01, Delta: 6.167e+00, inner iters:     9, |h|: 1.113e+00, |h|_M: 2.064e-01, df:  4.629e-01, rho:  1.124e+00. Step accepted\n",
      "Iter:   18, time: 2.470e-01, f:  5.252e+01, |g|: 3.440e+00, |M^{-1}g|: 7.780e+00, Delta: 6.167e+00, inner iters:    22, |h|: 3.809e+00, |h|_M: 4.818e-01, df:  1.335e-01, rho:  8.622e-01. Step accepted\n",
      "Iter:   19, time: 2.830e-01, f:  5.239e+01, |g|: 7.187e+00, |M^{-1}g|: 1.676e+01, Delta: 6.167e+00, inner iters:     3, |h|: 7.008e-02, |h|_M: 1.930e-02, df:  3.764e-02, rho:  1.000e+00. Step accepted\n",
      "Iter:   20, time: 2.890e-01, f:  5.235e+01, |g|: 8.699e-01, |M^{-1}g|: 1.638e+00, Delta: 6.167e+00, inner iters:    23, |h|: 4.770e-01, |h|_M: 7.949e-02, df:  5.432e-03, rho:  9.857e-01. Step accepted\n",
      "Iter:   21, time: 3.220e-01, f:  5.235e+01, |g|: 2.910e-01, |M^{-1}g|: 5.211e-01, Delta: 6.167e+00, inner iters:     9, |h|: 1.172e-02, |h|_M: 2.622e-03, df:  7.359e-05, rho:  1.000e+00. Step accepted\n",
      "Iter:   22, time: 3.380e-01, f:  5.235e+01, |g|: 5.317e-02, |M^{-1}g|: 8.254e-02, Delta: 6.167e+00, inner iters:    26, |h|: 6.288e-02, |h|_M: 6.301e-03, df:  1.569e-05, rho:  9.999e-01. Step accepted\n",
      "\n",
      "Optimization finished!\n",
      "Algorithm terminated due to insufficient relative decrease: 2.996e-07 < 1.000e-06\n",
      "Final objective value: 5.235e+01\n",
      "Norm of Riemannian gradient: 5.317e-02\n",
      "Norm of preconditioned Riemannian gradient: 8.254e-02\n",
      "Total elapsed computation time: 3.690e-01 seconds\n",
      "\n",
      "\n",
      "Found first-order critical point with value F(Y) = 52.3482!  Elapsed computation time: 0.369 seconds\n",
      "\n",
      "Checking second order optimality ... \n",
      "Found second-order critical point! Elapsed computation time: 0.009 seconds.\n",
      "\n",
      "\n",
      "===== END RIEMANNIAN STAIRCASE =====\n",
      "\n",
      "Found global optimum!\n",
      "\n",
      "Rounding solution ... elapsed computation time: 0.001 seconds\n",
      "\n",
      "SDP RESULTS:\n",
      "Value of dual SDP solution F(Y): 52.3482\n",
      "Norm of Riemannian gradient grad F(Y): 0.00629562\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Value of primal SDP solution tr(Lambda): 52.3455\n",
      "SDP duality gap: 0.00273647\n",
      "\n",
      "SE-SYNCHRONIZATION RESULTS:\n",
      "Value of rounded pose estimates F(x): 52.3482\n",
      "Suboptimality bound F(x) - tr(Lambda) of recovered pose estimate: 0.00273644\n",
      "\n",
      "Total elapsed computation time: 3.574 seconds\n",
      "\n",
      "===== END SE-SYNC =====\n",
      "\n"
     ]
    }
   ],
   "source": [
    "result = PySESync.SESync(measurements, opts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "female-nature",
   "metadata": {},
   "source": [
    "## Plot some interesting data about the solution process"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b66c958b",
   "metadata": {},
   "source": [
    "Plot the sequence of gradient norms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "committed-sheep",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot sequence of Riemannian gradient norms\n",
    "fig, ax = plt.subplots()\n",
    "# Extract sequences of gradient and preconditioned gradient norms\n",
    "grad_norms = np.concatenate(result.gradient_norms)\n",
    "precon_grad_norms = np.concatenate(result.preconditioned_gradient_norms)\n",
    "\n",
    "# Plot these sequences\n",
    "plt.semilogy(grad_norms, '-b')\n",
    "plt.semilogy(precon_grad_norms, '--c')\n",
    "plt.legend(['Gradient', 'Preconditioned gradient'])\n",
    "\n",
    "# Set the following flag to \"True\" in order to draw red vertical \n",
    "# lines indicating iterations at which the relaxation rank \n",
    "# increased in the Riemannian Staircase\n",
    "show_rank_increases = True\n",
    "\n",
    "if show_rank_increases and len(result.gradient_norms) > 1:\n",
    "    steps = np.cumsum([len(l) for l in result.gradient_norms[:-1]])\n",
    "    for i in steps:\n",
    "        plt.axvline(x=i, ymin=0, ymax=np.log10(grad_norms.max()), color='red', linestyle='--')\n",
    "\n",
    "plt.title(\"Gradient norms\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ed92ddd",
   "metadata": {},
   "source": [
    "Plot the sequence of update step sizes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "146b8762",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot sequence of update step norms\n",
    "fig, ax = plt.subplots()\n",
    "# Extract sequences of gradient and preconditioned gradient norms\n",
    "update_step_norms = np.concatenate(result.update_step_norms)\n",
    "update_step_M_norms = np.concatenate(result.update_step_M_norms)\n",
    "\n",
    "# Plot these sequences\n",
    "plt.semilogy(update_step_norms, '-b')\n",
    "plt.semilogy(update_step_M_norms, '--c')\n",
    "plt.legend(['Frobenius norm', 'M norm'])\n",
    "\n",
    "# Set the following flag to \"True\" in order to draw red vertical \n",
    "# lines indicating iterations at which the relaxation rank \n",
    "# increased in the Riemannian Staircase\n",
    "show_rank_increases = True\n",
    "\n",
    "if show_rank_increases and len(result.gradient_norms) > 1:\n",
    "    steps = np.cumsum([len(l) for l in result.gradient_norms[:-1]])\n",
    "    for i in steps:\n",
    "        plt.axvline(x=i, ymin=0, ymax=np.log10(grad_norms.max()), color='red', linestyle='--')\n",
    "\n",
    "plt.title(\"Update step norms\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebb3ff1f",
   "metadata": {},
   "source": [
    "Plot the sequence of gain ratios for the computed update steps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0ff93d64",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot sequence of gain ratio values: this measures how well the second-order local model\n",
    "# of the objective used to calculate the update steps h agrees with the *actual* objective F.\n",
    "#\n",
    "# This value should be close to 1 if the local model is accurately capturing the shape of the objective F over\n",
    "# a region of the same size as the length of the update steps h\n",
    "#\n",
    "# Blue markers indicate iterations for which the gain ratio is positive (corresponding to accepted steps),\n",
    "# while red markers indicate iterations for which the gain ratio is negative (corresponding to rejected steps)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "gain_ratios = np.concatenate(result.gain_ratios)\n",
    "\n",
    "# Plot sequence of nonnegative gain ratios with blue markers\n",
    "nonnegative_rho_indicators = (gain_ratios >= 0)\n",
    "nonnegative_rho_indxs = np.nonzero(nonnegative_rho_indicators)[0]\n",
    "plt.plot(nonnegative_rho_indxs, gain_ratios[nonnegative_rho_indicators], \\\n",
    "         color='blue', marker=\".\", linestyle='None')\n",
    "\n",
    "# Extract the set of iterations in which the gain ratio is less than 0;\n",
    "# these correspond to iterations in which the proposed update was rejected\n",
    "neg_rho_idxs = np.nonzero(gain_ratios < 0)[0]\n",
    "num_neg_rhos = len(neg_rho_idxs)\n",
    "\n",
    "# Plot these rejected steps\n",
    "plt.plot(neg_rho_idxs, np.zeros(len(neg_rho_idxs)), color='red', marker='.', linestyle=\"None\")\n",
    "\n",
    "# Set reasonable range for viewing gain ratios\n",
    "ax.set_ylim(-.1, 1.1)\n",
    "\n",
    "# Set the following flag to \"True\" in order to draw red vertical \n",
    "# lines indicating iterations at which the relaxation rank \n",
    "# increased in the Riemannian Staircase\n",
    "show_rank_increases = True\n",
    "\n",
    "if show_rank_increases and len(result.function_values) > 1:\n",
    "    steps = np.cumsum([len(l) for l in result.function_values[:-1]])\n",
    "    for i in steps:\n",
    "        plt.axvline(x=i, ymin=-2, ymax=2, color='red', linestyle='--')\n",
    "\n",
    "\n",
    "plt.title(\"Gain ratios\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "female-privilege",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot sequence of objective values\n",
    "fig, ax = plt.subplots()\n",
    "fvals = np.concatenate(result.function_values)\n",
    "plt.semilogy(fvals)\n",
    "\n",
    "# Set the following flag to \"True\" in order to draw red vertical \n",
    "# lines indicating iterations at which the relaxation rank \n",
    "# increased in the Riemannian Staircase\n",
    "show_rank_increases = True\n",
    "\n",
    "if show_rank_increases and len(result.function_values) > 1:\n",
    "    steps = np.cumsum([len(l) for l in result.function_values[:-1]])\n",
    "    for i in steps:\n",
    "        plt.axvline(x=i, ymin=0, ymax=np.log10(fvals.max()), color='red', linestyle='--')\n",
    "\n",
    "\n",
    "plt.title(\"Objective value\")\n",
    "plt.xlabel(\"Iteration\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "diverse-cycle",
   "metadata": {},
   "source": [
    "### Plot estimated SLAM solution"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e436355c",
   "metadata": {},
   "source": [
    "Define some useful functions for visualizing SLAM solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "732bad46",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Given a list of position estimates and a collection of measurements, this function constructs a list of\n",
    "# pairs of the form (ti, tj), where ti and tj are the endpoints of a relative pose measurement\n",
    "def construct_line_segments(t, measurements):\n",
    "    lines = []\n",
    "    \n",
    "    for m in measurements:\n",
    "        lines.append((t[:,m.i], t[:,m.j]))\n",
    "    \n",
    "    return lines\n",
    "\n",
    "# Given an SESyncProblem instance, a low-rank factor Y for an estimated SDP solution X = YY', this function\n",
    "# returns the rounded (projected) position estimates t\n",
    "def get_rounded_position_estimates(prob, Y):\n",
    "    # Get problem dimensions\n",
    "    d = prob.dimension()\n",
    "    n = prob.num_states()\n",
    "    \n",
    "    # Get relaxtion rank for the passed estimate Y\n",
    "    r = Y.shape[0]\n",
    "    \n",
    "    # Compute rounded pose estimates\n",
    "    xhat = prob.round_solution(Y)\n",
    "    \n",
    "    # Extract rotational and translational parts\n",
    "    R0 = xhat[:, n : n + d]\n",
    "    R0inv = R0.transpose()\n",
    "    return np.matmul(R0inv, xhat[:, 0:n])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "245c451f",
   "metadata": {},
   "source": [
    "Plot the final SLAM estimate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8bea0ac1",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
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       "    this.context = undefined;\n",
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       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
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       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract translational states from solution xhat\n",
    "xhat = result.xhat\n",
    "R0inv = np.linalg.inv(xhat[:, num_poses : num_poses + d])\n",
    "t = np.matmul(R0inv, xhat[:, 0:num_poses])\n",
    "\n",
    "# Construct set of inter-pose measurements at the estimated robot positions\n",
    "lines = construct_line_segments(t, measurements)\n",
    "\n",
    "# Determine dimension of problem\n",
    "\n",
    "# Plot the estimated solution\n",
    "fig = plt.figure()\n",
    "\n",
    "if d == 2:\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim(t[0, :].min(), t[0, :].max())\n",
    "    ax.set_ylim(t[1, :].min(), t[1, :].max())\n",
    "    ax.set_xlabel(\"x [m]\")\n",
    "    ax.set_ylabel(\"y [m]\")\n",
    "    \n",
    "    lc = mc.LineCollection(lines)\n",
    "    ax.add_collection(lc)\n",
    "    ax.set_aspect('equal')\n",
    "\n",
    "else:\n",
    "    # d == 3\n",
    "    ax = fig.add_subplot(projection='3d')\n",
    "    ax.set_xlim(t[0, :].min(), t[0, :].max())\n",
    "    ax.set_ylim(t[1, :].min(), t[1, :].max())\n",
    "    ax.set_zlim(t[2, :].min(), t[2, :].max())\n",
    "    ax.set_xlabel(\"x [m]\")\n",
    "    ax.set_ylabel(\"y [m]\")\n",
    "    ax.set_zlabel(\"z [m]\")\n",
    "    \n",
    "    lc = Line3DCollection(lines)\n",
    "    ax.add_collection3d(lc)\n",
    "    ax.set_box_aspect((1,1,1))\n",
    "\n",
    "plt.title(\"Estimated SLAM solution\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11195091",
   "metadata": {},
   "source": [
    "### Generate a video of the solution process"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18de64b6",
   "metadata": {},
   "source": [
    "Compute rounded position estimates for each iterate generated during the entire optimization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2fe702f7",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Construct SE-Sync problem instance\n",
    "prob = PySESync.SESyncProblem(measurements, opts.formulation, opts.projection_factorization, \\\n",
    "                              opts.preconditioner, opts.reg_Chol_precon_max_cond)\n",
    "\n",
    "# Record maximum and minimum x- and y- values of each estimated position; we will use these later\n",
    "# to set the figure axis ranges\n",
    "xmax = -float('inf')\n",
    "xmin = float('inf')\n",
    "ymax = -float('inf')\n",
    "ymin = float('inf')\n",
    "zmax = -float('inf')\n",
    "zmin = float('inf')\n",
    "\n",
    "\n",
    "# Construct a list of line collections, one for each estimated (rounded) solution\n",
    "solns = []\n",
    "for Ys in result.iterates:\n",
    "    for Y in Ys:\n",
    "        # Get rounded position estimates\n",
    "        t = get_rounded_position_estimates(prob, Y)\n",
    "        \n",
    "        # Update maximum and minimum x- and y- values\n",
    "        xmax = max(xmax, t[0, :].max())\n",
    "        xmin = min(xmin, t[0, :].min())\n",
    "        ymax = max(ymax, t[1, :].max())\n",
    "        ymin = min(ymin, t[1, :].min())\n",
    "        \n",
    "        if d == 3:\n",
    "            # Also record zmax and zmin values\n",
    "            zmax = max(zmax, t[2, :].max())\n",
    "            zmin = min(zmin, t[2, :].min())\n",
    "\n",
    "        # Calculate the set of segments for this solution\n",
    "        solns.append(construct_line_segments(t, measurements))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e8b5912",
   "metadata": {},
   "source": [
    "Render visualization!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "145e05bb",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\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(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "    fig.rubberband_canvas.style.cursor = msg['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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\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",
       "                img.type = 'image/png';\n",
       "            }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       " * https://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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\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",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First set up the figure, the axis, and the plot element we want to animate\n",
    "fig = plt.figure()\n",
    "\n",
    "if d == 2:\n",
    "    # Construct set of 2D axes\n",
    "    ax = plt.axes(xlim=(xmin, xmax), ylim=(ymin, ymax))\n",
    "    ax.set_xlabel(\"x [m]\")\n",
    "    ax.set_ylabel(\"y [m]\")\n",
    "    ax.set_aspect('equal')\n",
    "\n",
    "    # Initialize line collection and add it to the figure\n",
    "    lc = mc.LineCollection([])\n",
    "    ax.add_collection(lc)\n",
    "    \n",
    "else:\n",
    "    # Construct set of 3D axes\n",
    "    ax = fig.add_subplot(projection='3d')\n",
    "    ax.set_xlim(xmin, xmax)\n",
    "    ax.set_ylim(ymin, ymax)\n",
    "    ax.set_zlim(zmin, zmax)\n",
    "    ax.set_xlabel(\"x [m]\")\n",
    "    ax.set_ylabel(\"y [m]\")\n",
    "    ax.set_zlabel(\"z [m]\")\n",
    "    ax.set_box_aspect((1,1,1))\n",
    "    \n",
    "    # Initialize line collection and add it to the figure\n",
    "    lc = Line3DCollection([])\n",
    "    ax.add_collection3d(lc)\n",
    "    \n",
    "\n",
    "\n",
    "# Initialization function: plot the background of each frame\n",
    "def init():\n",
    "    lc.set_segments([])\n",
    "    return lc\n",
    "\n",
    "# Animation function.  This is called sequentially\n",
    "def update(i):\n",
    "    lc.set_segments(solns[i])\n",
    "    ax.set_title(\"Iteration %d\" % i)\n",
    "    return lc\n",
    "\n",
    "# Call the animator.  blit=True means only re-draw the parts that have changed.\n",
    "anim = animation.FuncAnimation(fig, update, init_func=init, frames=len(solns), interval=67)\n",
    "\n",
    "if save_animation:\n",
    "    # Save this animation to disk\n",
    "    writer = animation.FFMpegWriter(fps = 15, codec='ffv1')\n",
    "    anim.save('SESync.avi', writer=writer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "926daf0c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}