{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7d9d2849",
   "metadata": {},
   "source": [
    "# **Pyramidal Morphology described as Probability Clouds**\n"
   ]
  },
  {
   "attachments": {
    "hippo_cells.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "id": "ed7d5228",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"attachment:hippo_cells.png\" width=\"350\"/>\n",
    "</div>\n",
    "\n",
    "**Fig 1.** Excitatory and inhibitory cell placements according to \n",
    "the CA1 region layer subdivision provided by the Blue Brain cell Atlas."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c34a3a6",
   "metadata": {},
   "source": [
    "###  Morphological descriptions of axons and dendrites\n",
    "\n",
    "In our approach, the rule to generate a connection between any two neurons was implemented assuming that neuronal classes are characterized by specific morphological properties.\n",
    "\n",
    "These properties have been modeled as combinations of **ellipsoids** and **cones** mimicking the cross-section volume of pre-synaptic **axons** and post-synaptic **dendrites** .\n",
    "\n",
    "In general, the probability cloud <u> eigenvalue </u>  parametrization depended on the relative <u> distances </u> between each cell soma location and its CA1 targeting subregion while the probability cloud <u> eigenvectors </u> parametrization depended on the relative <u> orientations </u> between each soma location and its CA1 targeting subregion.\n",
    "\n",
    "All cells were associated with their relative distances from CA3 and from Subiculum, in order to consider the experimentally observed preferential orientation of PC axons along the direction of the minimum distance between CA3 and Subiculum. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6314cb23",
   "metadata": {},
   "source": [
    "<img src=\"ellips_eigenv.png\" width=\"600\" >\n",
    "\n",
    "**Fig 2. “Positional-Morpho-Anatomical”  modelling**. CA1 PC cells are indicated by orange circle."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "404cb8c6",
   "metadata": {},
   "source": [
    "## Ellipsoids \n",
    "\n",
    "Assuming that any quadratic function $f (x_1, . . . , x_n)$ can be written in the form $  X ^\\mathsf{T}  Q  X $, where $ Q$ is a symmetric matrix ( $ Q =  Q^\\mathsf{T} $ ), given a system of eigenvectors that diagonalize the symmetric matrix, any ellipsoid can be described as a volume oriented in the direction set by the eigenvectors and elongated along the semi-axis as set by the eigenvalues.\n",
    "\n",
    "\n",
    "Considering an orthonormal system of eigenvectors $ \\mathbf{v_1, v_2, v_3}$  associated, respectively, with the eigenvalues $ \\lambda_1, \\lambda_2, \\lambda_3$ of a $3 \\times 3$ symmetric positive matrix $M$. If \n",
    "$$\n",
    "V = [ \\mathbf{v_1, v_2, v_3} ] ,\n",
    "$$  \n",
    "Then\n",
    "$$\n",
    "V^\\mathsf{T} M  V = \\Bigg[ \\begin{matrix}\n",
    " \\lambda_1 & 0          & 0           \\\\\n",
    "0         &  \\lambda_2 & 0           \\\\\n",
    "0          & 0          &  \\lambda_3  \\\\\n",
    "\\end{matrix} \\Bigg] = D \\,[\\lambda_1, \\lambda_2, \\lambda_3 ]\n",
    "$$\n",
    "\n",
    "<br>\n",
    "\n",
    "So we built the symmetric matrix ($Q$) starting from an arbitrary base of orthonormal vectors $ \\mathbf{u_1, u_2, u_3}$ (ellipsoid orientation vectors) forming the matrix $U$ and diagonal matrix $D$ of arbitrary eigenvalues (semiaxis lengths) $    Q = U  D U^\\mathsf{T} $.\n",
    "1. Transversal orientation vector ($\\mathbf{u_1}$) was taken along the direction of the PC-Subiculum minimum distance vector and constituted the ellipsoid major axis orientation. \n",
    "2. The orientation vector along the longitudinal direction ($\\mathbf{u_2}$) was taken from the cross product between PC-Subiculum and PC-CA3 minimum distance vectors. \n",
    "3. The orientation along the vertical direction ($\\mathbf{u_3}$) was taken as the cross product between $\\mathbf{u_1}$ and $\\mathbf{u_2}$.\n",
    "\n",
    "<br>\n",
    "\n",
    "The probability cloud associated with the ellipsoid was then modelled as scattered tridimensional points following the canonical parametric equations: \n",
    "\n",
    "$$\n",
    "\\begin{align}\n",
    "x &= \\lambda_1 \\cos \\theta \\sin \\phi,  \\\\\n",
    "y &= \\lambda_2 \\cos \\theta \\sin \\phi,  \\\\\n",
    "z &= \\lambda_3 \\cos \\phi  \\\\\n",
    "\\end{align}\n",
    "$$\n",
    "\n",
    "where $ \\; \\; 0 \\leq \\theta \\leq 2 \\pi  \\; \\; and \\; \\; −\\pi \\leq \\phi \\leq 0 $.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "boxed-wyoming",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6cd96b60",
   "metadata": {},
   "source": [
    "## Cones\n",
    "\n",
    "Pyramidal dendrites are modeled as conic probability clouds.\n",
    "**u** and **v** are two orthogonal vectors that lie in the plane of the circle forming the basis of the cone. \n",
    "To build a cone between point $ O $ (apex) and base center point ($ P $) with a given radius $ R $ we determined the norm of the cone base plane, which is given by $ d = P - O $. \n",
    "\n",
    "The probability cloud associated with the cone was then modelled as scattered tridimensional points following the general parametric equation:\n",
    "\n",
    "$$\n",
    "\\begin{bmatrix}\n",
    "x \\\\\n",
    "y \\\\ \n",
    "z \n",
    "\\end{bmatrix}  =\n",
    "\\begin{pmatrix}\n",
    "O_x + \\frac{h}{H} dx \\\\ \n",
    "O_y + \\frac{h}{H} dy \\\\ \n",
    "O_z + \\frac{h}{H} dz  \n",
    "\\end{pmatrix} \n",
    "+ \\begin{pmatrix}\n",
    "R \\cdot \\frac{h}{H} \\cdot \\cos \\theta \\cdot u_x \\\\ \n",
    "R \\cdot \\frac{h}{H} \\cdot \\cos \\theta \\cdot u_y \\\\\n",
    "R \\cdot \\frac{h}{H} \\cdot \\cos \\theta \\cdot u_z \n",
    "\\end{pmatrix}\n",
    "+ \\begin{pmatrix}\n",
    "R \\cdot \\frac{h}{H} \\cdot \\sin \\theta \\cdot v_x \\\\ \n",
    "R \\cdot \\frac{h}{H} \\cdot \\sin \\theta \\cdot v_y \\\\ \n",
    "R \\cdot \\frac{h}{H} \\cdot \\sin \\theta \\cdot v_z  \n",
    "\\end{pmatrix}\n",
    "$$\n",
    "\n",
    "with $\\quad 0 \\leq  h \\leq H, \\quad 0 \\leq  \\theta \\leq  2 \\pi $\n",
    "\n",
    "where $ H = |P - O| = d $. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1beb59d9",
   "metadata": {},
   "source": [
    "# **Create Superficial Pyramidal Morphology**\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a30dec93",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.io\n",
    "from scipy.spatial import ConvexHull\n",
    "from itertools import product\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "PyrS_features = scipy.io.loadmat('PyrS_features.mat')\n",
    "PyrS_features_df = pd.DataFrame( PyrS_features['PyrS_features'])\n",
    "\n",
    "ColumnNames = ['PlacementPyr_x', 'PlacementPyr_y', 'PlacementPyr_z', \n",
    "               'MinDistCA3', 'MinDistCA3_x', 'MinDistCA3_y', 'MinDistCA3_z',\n",
    "               'MinDistSub', 'MinDistSub_x', 'MinDistSub_y', 'MinDistSub_z',\n",
    "               'eigenv_ellips_l1', 'eigenv_ellips_l2', 'eigenv_ellips_l3',\n",
    "               'H_BasalDend', 'r_BasalDend','H_ApicalDend', 'r_ApicalDend', 'nn',\n",
    "               'MinDistOriens','MinDistOriens_x','MinDistOriens_y','MinDistOriens_z',\n",
    "               'MinDistLacun','MinDistLacun_x','MinDistLacun_y','MinDistLacun_z']\n",
    "PyrS_features_df.columns = ColumnNames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "92b1411d",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PlacementPyr_x</th>\n",
       "      <th>PlacementPyr_y</th>\n",
       "      <th>PlacementPyr_z</th>\n",
       "      <th>MinDistCA3</th>\n",
       "      <th>MinDistCA3_x</th>\n",
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       "      <th>MinDistCA3_z</th>\n",
       "      <th>MinDistSub</th>\n",
       "      <th>MinDistSub_x</th>\n",
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       "      <th>r_ApicalDend</th>\n",
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       "      <th>MinDistOriens_y</th>\n",
       "      <th>MinDistOriens_z</th>\n",
       "      <th>MinDistLacun</th>\n",
       "      <th>MinDistLacun_x</th>\n",
       "      <th>MinDistLacun_y</th>\n",
       "      <th>MinDistLacun_z</th>\n",
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       "      <td>2366.489990</td>\n",
       "      <td>...</td>\n",
       "      <td>75.562119</td>\n",
       "      <td>1.0</td>\n",
       "      <td>44.070309</td>\n",
       "      <td>8102.819824</td>\n",
       "      <td>2440.929932</td>\n",
       "      <td>9110.271484</td>\n",
       "      <td>268.089783</td>\n",
       "      <td>8122.830078</td>\n",
       "      <td>2677.699951</td>\n",
       "      <td>8916.571289</td>\n",
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       "      <td>8176.560059</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>3671.210938</td>\n",
       "      <td>9361.021484</td>\n",
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       "      <td>5826.859863</td>\n",
       "      <td>8160.361328</td>\n",
       "      <td>37.691891</td>\n",
       "      <td>7916.029785</td>\n",
       "      <td>5796.759766</td>\n",
       "      <td>8149.270020</td>\n",
       "      <td>1309.069458</td>\n",
       "      <td>9080.230469</td>\n",
       "      <td>5367.250000</td>\n",
       "      <td>...</td>\n",
       "      <td>90.401756</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.279541</td>\n",
       "      <td>7905.229980</td>\n",
       "      <td>5898.060059</td>\n",
       "      <td>8225.571289</td>\n",
       "      <td>51.631149</td>\n",
       "      <td>7980.679688</td>\n",
       "      <td>5810.830078</td>\n",
       "      <td>8140.451172</td>\n",
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       "      <th>3</th>\n",
       "      <td>8230.169922</td>\n",
       "      <td>2692.069824</td>\n",
       "      <td>9283.851562</td>\n",
       "      <td>608.663940</td>\n",
       "      <td>7816.259766</td>\n",
       "      <td>3013.169922</td>\n",
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       "      <td>937.358215</td>\n",
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       "      <td>2683.639893</td>\n",
       "      <td>...</td>\n",
       "      <td>58.591160</td>\n",
       "      <td>4.0</td>\n",
       "      <td>72.143684</td>\n",
       "      <td>8245.179688</td>\n",
       "      <td>2652.079834</td>\n",
       "      <td>9341.991211</td>\n",
       "      <td>211.220276</td>\n",
       "      <td>8314.849609</td>\n",
       "      <td>2787.929932</td>\n",
       "      <td>9115.761719</td>\n",
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       "      <td>5.0</td>\n",
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       "      <td>8942.380859</td>\n",
       "      <td>609.587769</td>\n",
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       "      <td>8861.049805</td>\n",
       "      <td>2161.629883</td>\n",
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       "      <td>54.149960</td>\n",
       "      <td>216431.0</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>216435 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        PlacementPyr_x  PlacementPyr_y  PlacementPyr_z  MinDistCA3  \\\n",
       "0          8125.370117     2469.269775     9085.161133  600.477478   \n",
       "1          8176.560059     3510.365967     9620.210938  376.325958   \n",
       "2          7935.819824     5826.859863     8160.361328   37.691891   \n",
       "3          8230.169922     2692.069824     9283.851562  608.663940   \n",
       "4          8718.200195     4007.935791     9805.201172  800.595398   \n",
       "...                ...             ...             ...         ...   \n",
       "216430     8022.179688     2303.029785     8942.380859  609.587769   \n",
       "216431     8197.729492     5001.349609     9580.071289  540.179443   \n",
       "216432     8316.330078     3736.258789     9763.931641  524.106201   \n",
       "216433     8199.200195     2605.719971     9225.611328  613.186035   \n",
       "216434     6990.308105     1737.569824     7572.471191  470.250702   \n",
       "\n",
       "        MinDistCA3_x  MinDistCA3_y  MinDistCA3_z   MinDistSub  MinDistSub_x  \\\n",
       "0        7744.009766   2885.100098   8879.679688   959.296570   8988.040039   \n",
       "1        7882.220215   3629.330078   9418.139648  1015.934021   9184.879883   \n",
       "2        7916.029785   5796.759766   8149.270020  1309.069458   9080.230469   \n",
       "3        7816.259766   3013.169922   8973.940430   937.358215   9137.700195   \n",
       "4        8240.089844   3964.889893   9164.490234   489.271667   9188.759766   \n",
       "...              ...           ...           ...          ...           ...   \n",
       "216430   7711.689941   2799.010010   8771.509766   978.513672   8861.049805   \n",
       "216431   7890.080078   4773.049805   9199.250000   937.382385   9113.049805   \n",
       "216432   7952.270020   3733.139893   9386.919922   884.767029   9190.419922   \n",
       "216433   7816.259766   3013.169922   8973.940430   949.058411   9106.450195   \n",
       "216434   6677.490234   2086.320068   7613.140137  1175.725464   7978.209961   \n",
       "\n",
       "        MinDistSub_y  ...  r_ApicalDend        nn  MinDistOriens  \\\n",
       "0        2366.489990  ...     75.562119       1.0      44.070309   \n",
       "1        3528.199951  ...     72.826775       2.0     108.608330   \n",
       "2        5367.250000  ...     90.401756       3.0     101.279541   \n",
       "3        2683.639893  ...     58.591160       4.0      72.143684   \n",
       "4        4043.209961  ...     65.722137       5.0      78.015656   \n",
       "...              ...  ...           ...       ...            ...   \n",
       "216430   2161.629883  ...     54.149960  216431.0      49.564491   \n",
       "216431   5022.910156  ...     73.821106  216432.0      63.861050   \n",
       "216432   3823.790039  ...     73.559975  216433.0     107.298393   \n",
       "216433   2624.780029  ...     63.066402  216434.0      80.917030   \n",
       "216434   1884.729980  ...     52.314598  216435.0      52.514091   \n",
       "\n",
       "        MinDistOriens_x  MinDistOriens_y  MinDistOriens_z  MinDistLacun  \\\n",
       "0           8102.819824      2440.929932      9110.271484    268.089783   \n",
       "1           8128.389648      3473.450928      9710.281250    308.827515   \n",
       "2           7905.229980      5898.060059      8225.571289     51.631149   \n",
       "3           8245.179688      2652.079834      9341.991211    211.220276   \n",
       "4           8762.959961      3949.673828      9831.441406    308.917267   \n",
       "...                 ...              ...              ...           ...   \n",
       "216430      8041.060059      2308.499756      8987.880859    272.917908   \n",
       "216431      8155.500000      4957.020020      9561.911133    401.460388   \n",
       "216432      8282.729492      3687.611816      9853.471680    258.790009   \n",
       "216433      8231.530273      2564.829834      9287.500977    234.244354   \n",
       "216434      7010.776855      1691.729858      7557.061523    241.867889   \n",
       "\n",
       "        MinDistLacun_x  MinDistLacun_y  MinDistLacun_z  \n",
       "0          8122.830078     2677.699951     8916.571289  \n",
       "1          8224.769531     3671.210938     9361.021484  \n",
       "2          7980.679688     5810.830078     8140.451172  \n",
       "3          8314.849609     2787.929932     9115.761719  \n",
       "4          8701.339844     4021.460938     9497.041016  \n",
       "...                ...             ...             ...  \n",
       "216430     8151.359863     2368.969971     8711.191406  \n",
       "216431     8352.639648     4764.562988     9295.281250  \n",
       "216432     8321.149414     3801.478271     9513.541016  \n",
       "216433     8334.459961     2703.499756     9061.250977  \n",
       "216434     7150.609863     1907.689819     7510.321289  \n",
       "\n",
       "[216435 rows x 27 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PyrS_features_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5687b99e",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "'''\n",
    "This script creates morphologies of superficial pyramidal cells.\n",
    "Axons are modelled as ellipsoids and dendrites as probability clouds distributed in a conic volume.\n",
    "They are created by the DataFrame containing all the necessary features.\n",
    "\n",
    "It returns a dictionary with axonal and dendritic probability clouds for each pyramidal cell.\n",
    "'''\n",
    "\n",
    "rP = np.size(PyrS_features_df,0) # number of pyramidal cells\n",
    "rP = 100 # number of simulated cells\n",
    "\n",
    "PyrS_M = {} ; Pyrtemp = {}\n",
    "\n",
    "for w in range(rP):\n",
    "    print('pyramidal cell n: ',w+1)\n",
    "    PyrS_M[w] = {}\n",
    "    \n",
    "    #### CREATION OF FIRST ELLIPSOID ####\n",
    "    \n",
    "    #creation of the eigenvectors for ellipsoid projecting towards stratum oriens\n",
    "    Dx = 10\n",
    "    Dy = 10\n",
    "    Dz = ( 0.5 * PyrS_features_df['MinDistOriens'][w] ) + 20\n",
    "    N = 8 # number of concentric ellipes defining ellipsoid\n",
    "    D = np.zeros((3,3))\n",
    "    D[0,0] = Dx**2; D[1,1] = Dy**2; D[2,2] = Dz**2;\n",
    "    \n",
    "    p1 = PyrS_features_df.loc[w, ['PlacementPyr_x','PlacementPyr_y','PlacementPyr_z'] ].values\n",
    "    por = PyrS_features_df.loc[w, ['MinDistOriens_x','MinDistOriens_y','MinDistOriens_z'] ].values\n",
    "    plm = PyrS_features_df.loc[w, ['MinDistLacun_x','MinDistLacun_y','MinDistLacun_z'] ].values\n",
    "\n",
    "    # create eigenvectors: semi-axes of the first ellipsoid (vx, vy, vz)\n",
    "    vz = por - plm # eigenvector vz\n",
    "    vz = vz / np.linalg.norm(vz,2)\n",
    "    vor = por - p1 # vector connecting pyramidal to oriens\n",
    "    vor = vor / np.linalg.norm(vor,2)\n",
    "    vnorm = np.cross(vz,vor) # create vector orthogonal to plane defined by vz e vor\n",
    "    vnorm = vnorm / np.linalg.norm(vnorm,2)\n",
    "    vy = vnorm # eigenvector  vy\n",
    "    vx = np.cross(vz,vy) # eigenvector vx orthogonal to plane z,y\n",
    "\n",
    "    V = np.stack((vx, vy, vz), axis=1)\n",
    "    Q = np.dot(V,np.dot(D,V.T))\n",
    "    (d,V) = np.linalg.eig(Q)\n",
    "    \n",
    "    s = np.argsort(d)\n",
    "    D = np.sort(d)\n",
    "    V = V[:,s]; D = np.real(D)\n",
    "    uv = np.arange(-1,1+2/(N-1),2/(N-1))\n",
    "    u,v = np.meshgrid( uv *np.pi/2, uv *np.pi )\n",
    "    \n",
    "\n",
    "    # x,y,z for definition of concentric ellipses\n",
    "    x = D[0]**.5 * np.cos(u) * np.cos(v)\n",
    "    y = D[1]**.5 * np.cos(u) * np.sin(v)\n",
    "    z = D[2]**.5 * np.sin(u)\n",
    "    \n",
    "    # shift vector to move ellipsoid center in a different point than pyramidal cell placement\n",
    "    Vshift = ( PyrS_features_df['MinDistOriens'][w] + 20 ) * vz;\n",
    "    \n",
    "    # temporary coordinates of ellipsoid center\n",
    "    qtemp = np.zeros(3)\n",
    "    qtemp[0] = p1[0] + Vshift[0]\n",
    "    qtemp[1] = p1[1] + Vshift[1]\n",
    "    qtemp[2] = p1[2] + Vshift[2]\n",
    "    xx = np.zeros((N,N)); yy = np.zeros((N,N)); zz = np.zeros((N,N));\n",
    "    for k,j in product( range(len(x)), range(len(x)) ): \n",
    "            point = - np.dot( V, np.vstack([x[k,j], y[k,j], z[k,j]]) )\n",
    "            xx[k,j] = point[0] + qtemp[0]\n",
    "            yy[k,j] = point[1] + qtemp[1]\n",
    "            zz[k,j] = point[2] + qtemp[2]\n",
    "\n",
    "  \n",
    "    # allocate in (axon1) the coordinates of first axonal cloud \n",
    "    P = np.hstack([ np.reshape(xx,(-1,1)) , np.reshape(yy,(-1,1)) , np.reshape(zz,(-1,1)) ])\n",
    "    P = np.hstack([ P , np.ones((np.size(P,0),1)) * w ])  \n",
    "    PyrS_M[w]['axon1'] = P\n",
    "\n",
    "    \n",
    "    #### CREATION OF SECOND ELLIPSOID ####\n",
    "    \n",
    "    # axon2 is created with the same procedure as axon1 with different eigenvalues and eigenvectors\n",
    "    Dx = PyrS_features_df['eigenv_ellips_l1'][w]\n",
    "    Dy = PyrS_features_df['eigenv_ellips_l2'][w]\n",
    "    Dz = PyrS_features_df['eigenv_ellips_l3'][w]\n",
    "    N = 8  # number of concentric ellipes defining second ellipsoid\n",
    "    D = np.zeros((3,3))\n",
    "    D[0,0] = Dx**2; D[1,1] = Dy**2; D[2,2] = Dz**2;\n",
    "   \n",
    "    Vshift2 = 2*Dz*vz  # second shift from pyramidal cell placement\n",
    "    p1 = PyrS_features_df.loc[w, ['PlacementPyr_x','PlacementPyr_y','PlacementPyr_z']].values + Vshift2\n",
    "    pCA3 = PyrS_features_df.loc[w, ['MinDistCA3_x', 'MinDistCA3_y', 'MinDistCA3_z']].values\n",
    "    psub = PyrS_features_df.loc[w, ['MinDistSub_x', 'MinDistSub_y', 'MinDistSub_z']].values\n",
    "\n",
    "    vx = psub - p1\n",
    "    vz = vz / np.linalg.norm(vz,2)\n",
    "    vx = vx / np.linalg.norm(vx,2)\n",
    "    vsub = p1 - pCA3 \n",
    "    vsub = vsub / np.linalg.norm(vsub,2)\n",
    "\n",
    "    vnorm = np.cross(vx,vsub)\n",
    "    vnorm = vnorm / np.linalg.norm(vnorm,2)\n",
    "    vy = vnorm\n",
    "    vz = np.cross(vx,vy)\n",
    "    V[:,0] = vx; V[:,1] = vy; V[:,2] = vz\n",
    "\n",
    "    Q = np.dot(V,np.dot(D,V.T))\n",
    "    (d,V) = np.linalg.eig(Q)\n",
    "    s = np.argsort(d)\n",
    "    D = np.sort(d)\n",
    "    V = V[:,s]\n",
    "    uv = np.arange(-1,1+2/(N-1),2/(N-1))\n",
    "    u,v = np.meshgrid( uv *np.pi/2, uv *np.pi )\n",
    "\n",
    "    x = D[0]**.5 * np.cos(u) * np.cos(v)\n",
    "    y = D[1]**.5 * np.cos(u) * np.sin(v)\n",
    "    z = D[2]**.5 * np.sin(u)\n",
    "\n",
    "    Vshift3 = 0.75 * Dx * vx # third shift\n",
    "    \n",
    "    qtemp = np.zeros(3)\n",
    "    qtemp[0] = p1[0] + Vshift3[0];\n",
    "    qtemp[1] = p1[1] + Vshift3[1];\n",
    "    qtemp[2] = p1[2] + Vshift3[2];\n",
    "    xx = np.zeros((N,N)); yy = np.zeros((N,N)); zz = np.zeros((N,N));\n",
    "    for k,j in product( range(len(x)),range(len(x)) ): \n",
    "            point = - np.dot( V, np.vstack([x[k,j], y[k,j], z[k,j]]) )\n",
    "            xx[k,j] = point[0] + qtemp[0]\n",
    "            yy[k,j] = point[1] + qtemp[1]\n",
    "            zz[k,j] = point[2] + qtemp[2]\n",
    "        \n",
    "    # allocate in (axon2) the coordinates of second axonal cloud \n",
    "    P = np.hstack([ np.reshape(xx,(-1,1)), np.reshape(yy,(-1,1)), np.reshape(zz,(-1,1)) ])\n",
    "    P = np.hstack([ P , np.ones((np.size(P,0),1))*w ])  \n",
    "    PyrS_M[w]['axon2'] = P\n",
    "\n",
    "    #### CREATE COORDINATES OF BASAL AND APICAL DENDRITES ####\n",
    "    '''\n",
    "    While ellipsoid is build through (empty) concentric ellipses, dendrites \n",
    "    are made of a collection of points randomly distributed to form a cone\n",
    "    '''\n",
    "    \n",
    "    # u and v are parallel to the axon travelling towards subiculum \n",
    "    u = vx\n",
    "    v = vy\n",
    "    vlm = plm - p1\n",
    "    vlm = vlm / np.linalg.norm(vlm,2)\n",
    "    Dlm = PyrS_features_df['MinDistLacun'][w]\n",
    "\n",
    "    # cone1 is the BASAL one (the upper, shorter and larger, inserted in stratum oriens)\n",
    "    # cone2 is the APICAL one (the lower, longer and narrowe, inserted in stratum radiatum)\n",
    "    H1 = PyrS_features_df['H_BasalDend'][w]\n",
    "    H2 = PyrS_features_df['H_ApicalDend'][w]\n",
    "    Vcone1 = H1 * vlm\n",
    "    Vcone2 = H2 * vlm\n",
    "    \n",
    "    O = PyrS_features_df.loc[w, ['PlacementPyr_x','PlacementPyr_y','PlacementPyr_z']].values #cone origin\n",
    "    \n",
    "    P1 = np.zeros(3); P2 = np.zeros(3);\n",
    "    P1[0] = O[0] + Vcone1[0] # origin of cone1 circular base\n",
    "    P1[1] = O[1] + Vcone1[1]\n",
    "    P1[2] = O[2] + Vcone1[2]\n",
    "    P2[0] = O[0] - Vcone2[0] # origin of cone2 circular base\n",
    "    P2[1] = O[1] - Vcone2[1]\n",
    "    P2[2] = O[2] - Vcone2[2]\n",
    "\n",
    "    d1 = np.hstack([O[0] - P1[0] , O[1] - P1[1] , O[2] - P1[2] ])\n",
    "    d2 = np.hstack([O[0] - P2[0] , O[1] - P2[1] , O[2] - P2[2] ])\n",
    "    N = 100 # number of points for the description of cross section (volume)\n",
    "    theta = np.random.rand(N,1) * 2 * np.pi\n",
    "    h1 = np.random.rand(N,1) * H1\n",
    "    h2 = np.random.rand(N,1) * H2\n",
    "    R1 = np.random.rand(N,1) * PyrS_features_df['r_BasalDend'][w] \n",
    "    R2 = np.random.rand(N,1) * PyrS_features_df['r_ApicalDend'][w]    \n",
    "\n",
    "    x1 = O[0] + (h1/H1)*d1[0] + R1*(h1/H1)*np.cos(theta)*u[0] + R1*(h1/H1)*np.sin(theta)*v[0]\n",
    "    y1 = O[1] + (h1/H1)*d1[1] + R1*(h1/H1)*np.cos(theta)*u[1] + R1*(h1/H1)*np.sin(theta)*v[1]\n",
    "    z1 = O[2] + (h1/H1)*d1[2] + R1*(h1/H1)*np.cos(theta)*u[2] + R1*(h1/H1)*np.sin(theta)*v[2]\n",
    "    x2 = O[0] + (h2/H2)*d2[0] + R2*(h2/H2)*np.cos(theta)*u[0] + R2*(h2/H2)*np.sin(theta)*v[0]\n",
    "    y2 = O[1] + (h2/H2)*d2[1] + R2*(h2/H2)*np.cos(theta)*u[1] + R2*(h2/H2)*np.sin(theta)*v[1]\n",
    "    z2 = O[2] + (h2/H2)*d2[2] + R2*(h2/H2)*np.cos(theta)*u[2] + R2*(h2/H2)*np.sin(theta)*v[2]\n",
    "\n",
    "    \n",
    "    # allocate in (dendrite1) and (dendrite2) the coordinates of basal and apical dendrites. \n",
    "    # allocate in (DENDRITES) all the dendrites\n",
    "    Pyrtemp[w] = {}\n",
    "    Pyrtemp[w]['dendrite1'] = np.hstack([ x1 , y1 , z1, np.ones((len(x1),1))*w ])\n",
    "    Pyrtemp[w]['dendrite2'] = np.hstack([ x2 , y2 , z2, np.ones((len(x2),1))*w ])\n",
    "    PyrS_M[w]['DENDRITES'] = np.vstack([ Pyrtemp[w]['dendrite1'] , Pyrtemp[w]['dendrite2'] ])\n",
    "    PyrS_M[w]['dendrite1'] = Pyrtemp[w]['dendrite1']                                    \n",
    "    PyrS_M[w]['dendrite2'] = Pyrtemp[w]['dendrite2']  \n",
    "    \n",
    "    # convex hull or convex envelope of a shape is the smallest convex set that contains it\n",
    "    PyrS_M[w]['AXONShull1'] = ConvexHull( PyrS_M[w]['axon1'][:,0:3] )\n",
    "    PyrS_M[w]['AXONShull2'] = ConvexHull( PyrS_M[w]['axon2'][:,0:3] )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c82de481",
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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",
       "    // 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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## PLOT SUPERFICIAL PYRAMIDAL MORPHOLOGY ##\n",
    "%matplotlib notebook\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(6,6)) \n",
    "ax = Axes3D(fig)\n",
    "\n",
    "col = np.round(np.linspace(0,255,rP))\n",
    "cmap = cm.jet \n",
    "for w in range(rP):\n",
    "    ptsd = PyrS_M[w]['dendrite1']\n",
    "    ax.scatter(ptsd[:,0], ptsd[:,1], ptsd[:,2], '.', color=[0, .8, 0], s=1.8  )\n",
    "    ptsd2 = PyrS_M[w]['dendrite2']\n",
    "    ax.scatter(ptsd2[:,0], ptsd2[:,1], ptsd2[:,2], '.', color=[0, .2, 1], s=1.8  )\n",
    "        \n",
    "    pts = PyrS_M[w]['axon1']\n",
    "    ax.plot(pts[:,0], pts[:,1], pts[:,2], '.', c=[.9, 0, .8] , markersize=2 )\n",
    "    \n",
    "    pts2 = PyrS_M[w]['axon2']\n",
    "    ax.plot(pts2[:,0], pts2[:,1], pts2[:,2], '.', c=[.9, 0, .8], markersize=2 )\n",
    "\n",
    "fig.suptitle('Hippocampus (superficial) pyramidal cells morphology')\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "ax.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9f1607b",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfff178d",
   "metadata": {},
   "source": [
    "# **Create Deep Pyramidal Morphology**\n",
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "bebfcd77",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.io\n",
    "from scipy.spatial import ConvexHull\n",
    "from itertools import product\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "\n",
    "PyrD_features = scipy.io.loadmat('PyrD_features.mat')\n",
    "PyrD_features_df = pd.DataFrame( PyrD_features['PyrD_features'])\n",
    "\n",
    "ColumnNames = ['PlacementPyr_x', 'PlacementPyr_y', 'PlacementPyr_z', \n",
    "               'MinDistCA3', 'MinDistCA3_x', 'MinDistCA3_y', 'MinDistCA3_z',\n",
    "               'MinDistSub', 'MinDistSub_x', 'MinDistSub_y', 'MinDistSub_z',\n",
    "               'eigenv_ellips_l1', 'eigenv_ellips_l2', 'eigenv_ellips_l3',\n",
    "               'H_BasalDend', 'r_BasalDend','H_ApicalDend', 'r_ApicalDend', 'nn',\n",
    "               'MinDistOriens','MinDistOriens_x','MinDistOriens_y','MinDistOriens_z',\n",
    "               'MinDistLacun','MinDistLacun_x','MinDistLacun_y','MinDistLacun_z']\n",
    "PyrD_features_df.columns = ColumnNames"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a8e907c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PlacementPyr_x</th>\n",
       "      <th>PlacementPyr_y</th>\n",
       "      <th>PlacementPyr_z</th>\n",
       "      <th>MinDistCA3</th>\n",
       "      <th>MinDistCA3_x</th>\n",
       "      <th>MinDistCA3_y</th>\n",
       "      <th>MinDistCA3_z</th>\n",
       "      <th>MinDistSub</th>\n",
       "      <th>MinDistSub_x</th>\n",
       "      <th>MinDistSub_y</th>\n",
       "      <th>...</th>\n",
       "      <th>r_ApicalDend</th>\n",
       "      <th>nn</th>\n",
       "      <th>MinDistOriens</th>\n",
       "      <th>MinDistOriens_x</th>\n",
       "      <th>MinDistOriens_y</th>\n",
       "      <th>MinDistOriens_z</th>\n",
       "      <th>MinDistLacun</th>\n",
       "      <th>MinDistLacun_x</th>\n",
       "      <th>MinDistLacun_y</th>\n",
       "      <th>MinDistLacun_z</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7392.106934</td>\n",
       "      <td>1747.999878</td>\n",
       "      <td>6732.710449</td>\n",
       "      <td>890.852295</td>\n",
       "      <td>7059.520020</td>\n",
       "      <td>2480.439941</td>\n",
       "      <td>7115.509766</td>\n",
       "      <td>481.840271</td>\n",
       "      <td>7805.290039</td>\n",
       "      <td>1948.609985</td>\n",
       "      <td>...</td>\n",
       "      <td>75.934700</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>234.771942</td>\n",
       "      <td>7299.580078</td>\n",
       "      <td>1944.149902</td>\n",
       "      <td>6822.609375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7621.520020</td>\n",
       "      <td>1876.859863</td>\n",
       "      <td>8444.201172</td>\n",
       "      <td>628.380432</td>\n",
       "      <td>7357.609863</td>\n",
       "      <td>2436.050049</td>\n",
       "      <td>8332.309570</td>\n",
       "      <td>1056.485596</td>\n",
       "      <td>8534.780273</td>\n",
       "      <td>1838.369995</td>\n",
       "      <td>...</td>\n",
       "      <td>71.809219</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>327.164154</td>\n",
       "      <td>7824.839844</td>\n",
       "      <td>2055.999756</td>\n",
       "      <td>8260.880859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8242.309570</td>\n",
       "      <td>4284.031738</td>\n",
       "      <td>9922.581055</td>\n",
       "      <td>604.455139</td>\n",
       "      <td>7884.509766</td>\n",
       "      <td>4205.689941</td>\n",
       "      <td>9441.740234</td>\n",
       "      <td>976.706604</td>\n",
       "      <td>9181.580078</td>\n",
       "      <td>4373.419922</td>\n",
       "      <td>...</td>\n",
       "      <td>79.149597</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>449.711182</td>\n",
       "      <td>8482.290039</td>\n",
       "      <td>4196.378906</td>\n",
       "      <td>9552.491211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7902.299805</td>\n",
       "      <td>1866.799805</td>\n",
       "      <td>8285.681641</td>\n",
       "      <td>760.362732</td>\n",
       "      <td>7498.049805</td>\n",
       "      <td>2510.729980</td>\n",
       "      <td>8295.030273</td>\n",
       "      <td>733.929565</td>\n",
       "      <td>8534.780273</td>\n",
       "      <td>1838.369995</td>\n",
       "      <td>...</td>\n",
       "      <td>65.585480</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>158.995499</td>\n",
       "      <td>7922.120117</td>\n",
       "      <td>2017.859863</td>\n",
       "      <td>8240.210938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8585.219727</td>\n",
       "      <td>2023.969849</td>\n",
       "      <td>8492.821289</td>\n",
       "      <td>944.984985</td>\n",
       "      <td>8081.180176</td>\n",
       "      <td>2794.449951</td>\n",
       "      <td>8279.980469</td>\n",
       "      <td>253.315735</td>\n",
       "      <td>8810.830078</td>\n",
       "      <td>2034.680054</td>\n",
       "      <td>...</td>\n",
       "      <td>86.468346</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>252.800308</td>\n",
       "      <td>8631.629883</td>\n",
       "      <td>2248.109863</td>\n",
       "      <td>8385.511719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45403</th>\n",
       "      <td>8710.139648</td>\n",
       "      <td>3970.956787</td>\n",
       "      <td>9976.451172</td>\n",
       "      <td>927.806396</td>\n",
       "      <td>8133.100098</td>\n",
       "      <td>3930.250000</td>\n",
       "      <td>9251.059570</td>\n",
       "      <td>563.599426</td>\n",
       "      <td>9205.879883</td>\n",
       "      <td>3958.399902</td>\n",
       "      <td>...</td>\n",
       "      <td>67.252625</td>\n",
       "      <td>45404.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>479.555908</td>\n",
       "      <td>8534.519531</td>\n",
       "      <td>4050.527832</td>\n",
       "      <td>9537.361328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45404</th>\n",
       "      <td>8492.479492</td>\n",
       "      <td>1886.529907</td>\n",
       "      <td>8391.851562</td>\n",
       "      <td>993.687744</td>\n",
       "      <td>8043.640137</td>\n",
       "      <td>2757.699951</td>\n",
       "      <td>8227.469727</td>\n",
       "      <td>284.303741</td>\n",
       "      <td>8700.129883</td>\n",
       "      <td>1938.589966</td>\n",
       "      <td>...</td>\n",
       "      <td>69.881683</td>\n",
       "      <td>45405.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>329.694336</td>\n",
       "      <td>8392.959961</td>\n",
       "      <td>2137.069824</td>\n",
       "      <td>8202.051758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45405</th>\n",
       "      <td>7346.531738</td>\n",
       "      <td>1707.459839</td>\n",
       "      <td>6708.384277</td>\n",
       "      <td>919.362610</td>\n",
       "      <td>6983.200195</td>\n",
       "      <td>2498.370117</td>\n",
       "      <td>7004.490234</td>\n",
       "      <td>532.282715</td>\n",
       "      <td>7805.290039</td>\n",
       "      <td>1948.609985</td>\n",
       "      <td>...</td>\n",
       "      <td>73.362648</td>\n",
       "      <td>45406.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>266.971924</td>\n",
       "      <td>7299.580078</td>\n",
       "      <td>1944.149902</td>\n",
       "      <td>6822.609375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45406</th>\n",
       "      <td>6590.809570</td>\n",
       "      <td>1857.409912</td>\n",
       "      <td>6773.599121</td>\n",
       "      <td>324.349274</td>\n",
       "      <td>6431.700195</td>\n",
       "      <td>2124.780029</td>\n",
       "      <td>6865.250000</td>\n",
       "      <td>1213.702148</td>\n",
       "      <td>7727.000000</td>\n",
       "      <td>2113.169922</td>\n",
       "      <td>...</td>\n",
       "      <td>68.168320</td>\n",
       "      <td>45407.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>244.541473</td>\n",
       "      <td>6804.740723</td>\n",
       "      <td>1888.679810</td>\n",
       "      <td>6659.335449</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45407</th>\n",
       "      <td>8286.349609</td>\n",
       "      <td>1671.939819</td>\n",
       "      <td>8027.061523</td>\n",
       "      <td>1049.507446</td>\n",
       "      <td>7832.270020</td>\n",
       "      <td>2617.790039</td>\n",
       "      <td>8052.459961</td>\n",
       "      <td>305.399933</td>\n",
       "      <td>8509.259766</td>\n",
       "      <td>1774.050049</td>\n",
       "      <td>...</td>\n",
       "      <td>67.491074</td>\n",
       "      <td>45408.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>327.380371</td>\n",
       "      <td>8327.570312</td>\n",
       "      <td>1993.229858</td>\n",
       "      <td>8074.511230</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>45408 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       PlacementPyr_x  PlacementPyr_y  PlacementPyr_z   MinDistCA3  \\\n",
       "0         7392.106934     1747.999878     6732.710449   890.852295   \n",
       "1         7621.520020     1876.859863     8444.201172   628.380432   \n",
       "2         8242.309570     4284.031738     9922.581055   604.455139   \n",
       "3         7902.299805     1866.799805     8285.681641   760.362732   \n",
       "4         8585.219727     2023.969849     8492.821289   944.984985   \n",
       "...               ...             ...             ...          ...   \n",
       "45403     8710.139648     3970.956787     9976.451172   927.806396   \n",
       "45404     8492.479492     1886.529907     8391.851562   993.687744   \n",
       "45405     7346.531738     1707.459839     6708.384277   919.362610   \n",
       "45406     6590.809570     1857.409912     6773.599121   324.349274   \n",
       "45407     8286.349609     1671.939819     8027.061523  1049.507446   \n",
       "\n",
       "       MinDistCA3_x  MinDistCA3_y  MinDistCA3_z   MinDistSub  MinDistSub_x  \\\n",
       "0       7059.520020   2480.439941   7115.509766   481.840271   7805.290039   \n",
       "1       7357.609863   2436.050049   8332.309570  1056.485596   8534.780273   \n",
       "2       7884.509766   4205.689941   9441.740234   976.706604   9181.580078   \n",
       "3       7498.049805   2510.729980   8295.030273   733.929565   8534.780273   \n",
       "4       8081.180176   2794.449951   8279.980469   253.315735   8810.830078   \n",
       "...             ...           ...           ...          ...           ...   \n",
       "45403   8133.100098   3930.250000   9251.059570   563.599426   9205.879883   \n",
       "45404   8043.640137   2757.699951   8227.469727   284.303741   8700.129883   \n",
       "45405   6983.200195   2498.370117   7004.490234   532.282715   7805.290039   \n",
       "45406   6431.700195   2124.780029   6865.250000  1213.702148   7727.000000   \n",
       "45407   7832.270020   2617.790039   8052.459961   305.399933   8509.259766   \n",
       "\n",
       "       MinDistSub_y  ...  r_ApicalDend       nn  MinDistOriens  \\\n",
       "0       1948.609985  ...     75.934700      1.0            0.0   \n",
       "1       1838.369995  ...     71.809219      2.0            0.0   \n",
       "2       4373.419922  ...     79.149597      3.0            0.0   \n",
       "3       1838.369995  ...     65.585480      4.0            0.0   \n",
       "4       2034.680054  ...     86.468346      5.0            0.0   \n",
       "...             ...  ...           ...      ...            ...   \n",
       "45403   3958.399902  ...     67.252625  45404.0            0.0   \n",
       "45404   1938.589966  ...     69.881683  45405.0            0.0   \n",
       "45405   1948.609985  ...     73.362648  45406.0            0.0   \n",
       "45406   2113.169922  ...     68.168320  45407.0            0.0   \n",
       "45407   1774.050049  ...     67.491074  45408.0            0.0   \n",
       "\n",
       "       MinDistOriens_x  MinDistOriens_y  MinDistOriens_z  MinDistLacun  \\\n",
       "0                  0.0              0.0              0.0    234.771942   \n",
       "1                  0.0              0.0              0.0    327.164154   \n",
       "2                  0.0              0.0              0.0    449.711182   \n",
       "3                  0.0              0.0              0.0    158.995499   \n",
       "4                  0.0              0.0              0.0    252.800308   \n",
       "...                ...              ...              ...           ...   \n",
       "45403              0.0              0.0              0.0    479.555908   \n",
       "45404              0.0              0.0              0.0    329.694336   \n",
       "45405              0.0              0.0              0.0    266.971924   \n",
       "45406              0.0              0.0              0.0    244.541473   \n",
       "45407              0.0              0.0              0.0    327.380371   \n",
       "\n",
       "       MinDistLacun_x  MinDistLacun_y  MinDistLacun_z  \n",
       "0         7299.580078     1944.149902     6822.609375  \n",
       "1         7824.839844     2055.999756     8260.880859  \n",
       "2         8482.290039     4196.378906     9552.491211  \n",
       "3         7922.120117     2017.859863     8240.210938  \n",
       "4         8631.629883     2248.109863     8385.511719  \n",
       "...               ...             ...             ...  \n",
       "45403     8534.519531     4050.527832     9537.361328  \n",
       "45404     8392.959961     2137.069824     8202.051758  \n",
       "45405     7299.580078     1944.149902     6822.609375  \n",
       "45406     6804.740723     1888.679810     6659.335449  \n",
       "45407     8327.570312     1993.229858     8074.511230  \n",
       "\n",
       "[45408 rows x 27 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PyrD_features_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2a6460d3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pyramidal cell n:  1\n",
      "pyramidal cell n:  2\n",
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      "pyramidal cell n:  90\n",
      "pyramidal cell n:  91\n",
      "pyramidal cell n:  92\n",
      "pyramidal cell n:  93\n",
      "pyramidal cell n:  94\n",
      "pyramidal cell n:  95\n",
      "pyramidal cell n:  96\n",
      "pyramidal cell n:  97\n",
      "pyramidal cell n:  98\n",
      "pyramidal cell n:  99\n",
      "pyramidal cell n:  100\n"
     ]
    }
   ],
   "source": [
    "'''\n",
    "This function creates morphologies of deep pyramidal cells.\n",
    "Axons are modelled as ellipsoids and dendrites as probability clouds distributed in a conic volume.\n",
    "They are created by the DataFrame containing all the necessary features\n",
    "\n",
    "It returns a dictionary with axonal and dendritic probability clouds for each pyramidal cell\n",
    "'''\n",
    "\n",
    "rP = np.size(PyrD_features_df,0) # number of pyramidal cells\n",
    "rP = 100 # number of simulated cells\n",
    "\n",
    "PyrD_M = {} ; Pyrtemp = {}\n",
    "\n",
    "for w in range(rP):\n",
    "    print('pyramidal cell n: ',w+1)\n",
    "    PyrD_M[w] = {}\n",
    "    \n",
    "    \n",
    "    #### CREATION OF FIRST ELLIPSOID ####\n",
    "    \n",
    "    #creation of the eigenvectors for ellipsoid projecting towards stratum oriens\n",
    "    Dx = PyrD_features_df['eigenv_ellips_l1'][w]\n",
    "    Dy = PyrD_features_df['eigenv_ellips_l2'][w]\n",
    "    Dz = PyrD_features_df['eigenv_ellips_l3'][w]\n",
    "    N = 8 # number of concentric ellipes defining ellipsoid\n",
    "    D = np.zeros((3,3))\n",
    "    D[0,0] = Dx**2; D[1,1] = Dy**2; D[2,2] = Dz**2;\n",
    "    \n",
    "    p1 = PyrD_features_df.loc[w, ['PlacementPyr_x', 'PlacementPyr_y', 'PlacementPyr_z'] ].values\n",
    "    p2 = PyrD_features_df.loc[w, ['MinDistCA3_x', 'MinDistCA3_y', 'MinDistCA3_z'] ].values\n",
    "    p3 = PyrD_features_df.loc[w, ['MinDistSub_x', 'MinDistSub_y', 'MinDistSub_z'] ].values\n",
    "    por = PyrD_features_df.loc[w, ['MinDistOriens_x','MinDistOriens_y','MinDistOriens_z'] ].values\n",
    "    plm = PyrD_features_df.loc[w, ['MinDistLacun_x','MinDistLacun_y','MinDistLacun_z'] ].values\n",
    "\n",
    "    # create eigenvectors: semi-axes of the first ellipsoid (vx, vy, vz)\n",
    "    # eigenvector vx : orientation from pyramidal towards subiculum\n",
    "    vx = p3 - p1\n",
    "    vx = vx / np.linalg.norm(vx,2)\n",
    "    # vector vsub : from CA3 towards pyramidal\n",
    "    vsub = p1 - p2\n",
    "    vsub = vsub / np.linalg.norm(vsub,2)\n",
    "    \n",
    "    # vector vnorm : normal to (vx , vsub) plane \n",
    "    # vy : ellipses semi-axis\n",
    "    vnorm = np.cross(vx,vsub)\n",
    "    vnorm = vnorm / np.linalg.norm(vnorm,2)\n",
    "    vy = vnorm\n",
    "    # vz : normal to vx and vy\n",
    "    vz = np.cross(vx,vy)\n",
    "    V = np.stack((vx, vy, vz), axis=1)\n",
    "    Q = np.dot(V,np.dot(D,V.T))\n",
    "    (A,V) = np.linalg.eig(Q)\n",
    "    \n",
    "    s = np.argsort(A)\n",
    "    D = np.sort(A)\n",
    "    V = V[:,s]; D = np.real(D)\n",
    "    uv = np.arange(-1,1+2/(N-1),2/(N-1))\n",
    "    u,v = np.meshgrid( uv *np.pi/2, uv *np.pi )\n",
    "    \n",
    "    # x,y,z for definition of concentric ellipses\n",
    "    x = D[0]**.5 * np.cos(u) * np.cos(v)\n",
    "    y = D[1]**.5 * np.cos(u) * np.sin(v)\n",
    "    z = D[2]**.5 * np.sin(u)\n",
    "    \n",
    "    # shift vector to mode ellipsoid so that  pyramidal cell placement is inside the ellipsoid \n",
    "    Vshift = 0.85 * Dx * vx\n",
    "     \n",
    "    # temporary coordinates of ellipsoid center\n",
    "    qtemp = np.zeros(3)\n",
    "    qtemp[0] = p1[0] + Vshift[0]\n",
    "    qtemp[1] = p1[1] + Vshift[1]\n",
    "    qtemp[2] = p1[2] + Vshift[2]\n",
    "    xx = np.zeros((N,N)); yy = np.zeros((N,N)); zz = np.zeros((N,N));\n",
    "    for k,j in product( range(len(x)), range(len(x)) ): \n",
    "            point = - np.dot( V, np.vstack([x[k,j], y[k,j], z[k,j]]) )\n",
    "            xx[k,j] = point[0] + qtemp[0]\n",
    "            yy[k,j] = point[1] + qtemp[1]\n",
    "            zz[k,j] = point[2] + qtemp[2]\n",
    "\n",
    "  \n",
    "    # allocate in (axon1) the coordinates of first axonal cloud \n",
    "    P = np.hstack([ np.reshape(xx,(-1,1)) , np.reshape(yy,(-1,1)) , np.reshape(zz,(-1,1)) ])\n",
    "    P = np.hstack([ P , np.ones((np.size(P,0),1)) * w ])  \n",
    "    PyrD_M[w]['AXON'] = P\n",
    "    \n",
    "    #### CREATE COORDINATES OF BASAL AND APICAL DENDRITES ####\n",
    "    \n",
    "    # u and v are parallel to the axon travelling towards subiculum \n",
    "    u = vx\n",
    "    v = vy\n",
    "    vlm = plm - p1\n",
    "    vlm = vlm / np.linalg.norm(vlm,2)\n",
    "    Dlm = PyrD_features_df['MinDistLacun'][w]\n",
    "\n",
    "    # cone1 is the BASAL one (the upper, shorter and larger, inserted in stratum oriens)\n",
    "    # cone2 is the APICAL one (the lower, longer and narrowe, inserted in stratum radiatum)\n",
    "    H1 = PyrD_features_df['H_BasalDend'][w]\n",
    "    H2 = PyrD_features_df['H_ApicalDend'][w]\n",
    "    Vcone1 = H1 * vlm\n",
    "    Vcone2 = H2 * vlm\n",
    "    \n",
    "    O = PyrD_features_df.loc[w, ['PlacementPyr_x','PlacementPyr_y','PlacementPyr_z']].values #cone origin\n",
    "    \n",
    "    P1 = np.zeros(3); P2 = np.zeros(3);\n",
    "    P1[0] = O[0] + Vcone1[0] # origin of cone1 circular base\n",
    "    P1[1] = O[1] + Vcone1[1]\n",
    "    P1[2] = O[2] + Vcone1[2]\n",
    "    P2[0] = O[0] - Vcone2[0] # origin of cone2 circular base\n",
    "    P2[1] = O[1] - Vcone2[1]\n",
    "    P2[2] = O[2] - Vcone2[2]\n",
    "\n",
    "    d1 = np.hstack([O[0] - P1[0] , O[1] - P1[1] , O[2] - P1[2] ])\n",
    "    d2 = np.hstack([O[0] - P2[0] , O[1] - P2[1] , O[2] - P2[2] ])\n",
    "    N = 100 # number of points for the description of cross section (volume)\n",
    "    theta = np.random.rand(N,1) * 2 * np.pi\n",
    "    h1 = np.random.rand(N,1) * H1\n",
    "    h2 = np.random.rand(N,1) * H2\n",
    "    R1 = np.random.rand(N,1) * PyrD_features_df['r_BasalDend'][w] \n",
    "    R2 = np.random.rand(N,1) * PyrD_features_df['r_ApicalDend'][w]    \n",
    "\n",
    "    x1 = O[0] + (h1/H1)*d1[0] + R1*(h1/H1)*np.cos(theta)*u[0] + R1*(h1/H1)*np.sin(theta)*v[0]\n",
    "    y1 = O[1] + (h1/H1)*d1[1] + R1*(h1/H1)*np.cos(theta)*u[1] + R1*(h1/H1)*np.sin(theta)*v[1]\n",
    "    z1 = O[2] + (h1/H1)*d1[2] + R1*(h1/H1)*np.cos(theta)*u[2] + R1*(h1/H1)*np.sin(theta)*v[2]\n",
    "    x2 = O[0] + (h2/H2)*d2[0] + R2*(h2/H2)*np.cos(theta)*u[0] + R2*(h2/H2)*np.sin(theta)*v[0]\n",
    "    y2 = O[1] + (h2/H2)*d2[1] + R2*(h2/H2)*np.cos(theta)*u[1] + R2*(h2/H2)*np.sin(theta)*v[1]\n",
    "    z2 = O[2] + (h2/H2)*d2[2] + R2*(h2/H2)*np.cos(theta)*u[2] + R2*(h2/H2)*np.sin(theta)*v[2]\n",
    "\n",
    "    \n",
    "    # allocate in (dendrite1) and (dendrite2) the coordinates of basal and apical dendrites. \n",
    "    # allocate in (DENDRITES) all the dendrites\n",
    "    Pyrtemp[w] = {}\n",
    "    Pyrtemp[w]['dendrite1'] = np.hstack([ x1 , y1 , z1, np.ones((len(x1),1))*w ])\n",
    "    Pyrtemp[w]['dendrite2'] = np.hstack([ x2 , y2 , z2, np.ones((len(x2),1))*w ])\n",
    "    PyrD_M[w]['DENDRITES'] = np.vstack([ Pyrtemp[w]['dendrite1'] , Pyrtemp[w]['dendrite2'] ])\n",
    "    PyrD_M[w]['dendrite1'] = Pyrtemp[w]['dendrite1']                                    \n",
    "    PyrD_M[w]['dendrite2'] = Pyrtemp[w]['dendrite2']  \n",
    "    \n",
    "    # convex hull or convex envelope of a shape is the smallest convex set that contains it\n",
    "    PyrD_M[w]['AXONShull'] = ConvexHull( PyrD_M[w]['AXON'][:,0:3] )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "777d3f75",
   "metadata": {},
   "outputs": [
    {
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       "            }\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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(6,6)) \n",
    "ax = Axes3D(fig)\n",
    "\n",
    "col = np.round(np.linspace(0,255,rP))\n",
    "cmap = cm.jet \n",
    "for w in range(rP):\n",
    "    ptsd = PyrD_M[w]['dendrite1']\n",
    "    ax.scatter(ptsd[:,0], ptsd[:,1], ptsd[:,2], '.', color=[0, .8, 0], s=1.8  )\n",
    "    ptsd2 = PyrD_M[w]['dendrite2']\n",
    "    ax.scatter(ptsd2[:,0], ptsd2[:,1], ptsd2[:,2], '.', color=[0, .2, 1], s=1.8  )\n",
    "        \n",
    "    pts = PyrD_M[w]['AXON']\n",
    "    ax.plot(pts[:,0], pts[:,1], pts[:,2], '.', c=[.9, 0, .8] , markersize=2 )\n",
    "\n",
    "fig.suptitle('Hippocampus (deep) pyramidal cells morphology')\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "ax.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "09450b3f",
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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",
       "    // 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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# deep vs superficial pyramidal cells\n",
    "%matplotlib notebook\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(6,6)) \n",
    "ax = Axes3D(fig)\n",
    "\n",
    "col = np.round(np.linspace(0,255,rP))\n",
    "cmap = cm.jet \n",
    "for w in range(50):\n",
    "    \n",
    "    ### DEEP (yellow)\n",
    "    ptsd = PyrD_M[w]['DENDRITES']\n",
    "    ax.scatter(ptsd[:,0], ptsd[:,1], ptsd[:,2], '.', color=[.85, .85, 0], s=1.8  )\n",
    "        \n",
    "    pts = PyrD_M[w]['AXON']\n",
    "    ax.plot(pts[:,0], pts[:,1], pts[:,2], '.', c=[.85, .85, 0] , markersize=2 )\n",
    "    \n",
    "    ### SUPERFICIAL (red)\n",
    "    ptsd = PyrS_M[w]['DENDRITES']\n",
    "    ax.scatter(ptsd[:,0], ptsd[:,1], ptsd[:,2], '.', color=[.9, 0, .2], s=2  )\n",
    "        \n",
    "    pts = PyrS_M[w]['axon1']\n",
    "    ax.plot(pts[:,0], pts[:,1], pts[:,2], '.', c=[.9, 0, .2] , markersize=2 )\n",
    "    \n",
    "    pts2 = PyrS_M[w]['axon2']\n",
    "    ax.plot(pts2[:,0], pts2[:,1], pts2[:,2], '.', c=[.9, 0, .2], markersize=2 )\n",
    "\n",
    "fig.suptitle('Hippocampus pyramidal cells morphology')\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "ax.grid(False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c96fc79f",
   "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_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = 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",
       "    // 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",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.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",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\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 http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\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",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\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.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, 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, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"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.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = 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",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "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=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot single pyramidal cell\n",
    "%matplotlib notebook\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig = plt.figure(figsize=(6,6)) \n",
    "ax = Axes3D(fig)\n",
    "\n",
    "col = np.round(np.linspace(0,255,rP))\n",
    "cmap = cm.jet \n",
    "\n",
    "w=3\n",
    "\n",
    "ptsd = PyrD_M[w]['dendrite1']\n",
    "ax.scatter(ptsd[:,0], ptsd[:,1], ptsd[:,2], '.', color=[0, .8, 0], s=1.8  )\n",
    "ptsd2 = PyrD_M[w]['dendrite2']\n",
    "ax.scatter(ptsd2[:,0], ptsd2[:,1], ptsd2[:,2], '.', color=[0, .2, 1], s=1.8  )\n",
    "\n",
    "pts = PyrD_M[w]['AXON']\n",
    "ax.plot(pts[:,0], pts[:,1], pts[:,2], '.', c=[.9, 0, .8] , markersize=3 )\n",
    "#for simplex in PyrD_M[w]['AXONShull'].simplices:\n",
    "#        ax.plot(pts[simplex,0], pts[simplex,1], pts[simplex,2], '-k',  lw=.5)\n",
    "    \n",
    "ax.set_axis_off()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "474ea452",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df = pd.DataFrame(PyrS_M)\n",
    "#df"
   ]
  }
 ],
 "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": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
