{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# AxCaliber"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To estimate the axon diameter distribution itself, *(Assaf et al. 2008)* proposed a method called AxCaliber.\n",
    "In AxCaliber, a distribution of cylinders with different diameters are fitted to the diffusion signal. In particular, a Gamma distribution is used. A requirement of this technique is that the signal is measured perpendicular to the axon bundle direction for different gradient strengths and diffusion times.\n",
    "The signal representation in AxCaliber is given as\n",
    "\n",
    "\\begin{equation}\n",
    "E_{\\textrm{AxCaliber}}= \\underbrace{(1-f_r)\\overbrace{E_h(\\lambda_{\\textrm{h}})}^{\\textrm{Ball}}}_{\\textrm{Extra-Axonal}} + \\underbrace{f_r \\overbrace{\\Gamma(\\alpha,\\beta)}^{\\textrm{Gamma Distribution}}*_{\\mathbb{R}}\\overbrace{E_r(\\cdot|D_\\perp)}^{\\textrm{Cylinder}}}_{\\textrm{Intra-Axonal}}\n",
    "\\end{equation}\n",
    "\n",
    "where the cylinder was initially represented using the Callaghan model, but was later replaced with the more general Van Gelderen model *(Assaf et al. 2008, Huang et al. 2015, De Santis et al. 2016)*.\n",
    "\n",
    "Advantages:\n",
    "- Estimates the axon diameter distribution.\n",
    "\n",
    "Limitations:\n",
    "- Tissue orientation must be known for the signal to be measured perpendicular,\n",
    "- Does not take axon dispersion into account,\n",
    "- Does not include the effects of extra axonal restriction *(Burcaw et al. 2015)*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## AxCaliber model with Gaussian Phase Approximation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The process of setting up the AxCaliber model with Gamma-distributed cylinder diameters is the same as setting up an axon dispersed model. We import the needed Ball and Cylinder models, and then distribute the cylinder using the DD1GammaDistributed function from distribute_models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from dmipy.distributions import distribute_models\n",
    "from dmipy.signal_models import gaussian_models, cylinder_models\n",
    "\n",
    "ball = gaussian_models.G1Ball()\n",
    "cylinder = cylinder_models.C4CylinderGaussianPhaseApproximation()\n",
    "gamma_cylinder = distribute_models.DD1GammaDistributed(models=[cylinder])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then put the models together in a MultiCompartmentModel and display the parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('DD1GammaDistributed_1_DD1Gamma_1_alpha', 1),\n",
       "             ('G1Ball_1_lambda_iso', 1),\n",
       "             ('DD1GammaDistributed_1_C4CylinderGaussianPhaseApproximation_1_mu',\n",
       "              2),\n",
       "             ('DD1GammaDistributed_1_DD1Gamma_1_beta', 1),\n",
       "             ('DD1GammaDistributed_1_C4CylinderGaussianPhaseApproximation_1_lambda_par',\n",
       "              1),\n",
       "             ('partial_volume_0', 1),\n",
       "             ('partial_volume_1', 1)])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dmipy.core import modeling_framework\n",
    "axcaliber_gamma = modeling_framework.MultiCompartmentModel(models=[ball, gamma_cylinder])\n",
    "axcaliber_gamma.parameter_cardinality"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Visualize the model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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U2alTp8jZ2ZmUlZVp5cqV1NDQwHWkVmlqaqItW7aQsbExKSsrU0BAAN2+fZvrWMwrePjw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\n/gegA+SX/RzGTwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "axcaliber_gamma.visualize_model_setup(view=False, cleanup=False, with_parameters=True)\n",
    "Image('Model Setup.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data we will fit is measured only along 2 gradient orientations that are perpendicular to the axon axis (along x and y axis). This means there is no data that provides information to fit parallel diffusivity \"lambda_par\" or the axon orientation \"mu\". To not fit these superfluous parameters we fix mu along the z-axis and give lambda_par an arbitrary value (it will not affect the results)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "axcaliber_gamma.set_fixed_parameter(\n",
    "    'DD1GammaDistributed_1_C4CylinderGaussianPhaseApproximation_1_lambda_par', 1.7e-9)\n",
    "axcaliber_gamma.set_fixed_parameter(\n",
    "    'DD1GammaDistributed_1_C4CylinderGaussianPhaseApproximation_1_mu', [0, 0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load AxCaliber-compatible data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the example data, we kindly make use of a cat spinal cord dataset hosted at the White Matter Microscopy Database (https://osf.io/yp4qg/). The data includes 2D Axcaliber data, 3D multi-shell data and the corresponding histology values for axon diameter, intra-axonal volume fraction (and others)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This data was used by Duval et al. 'Validation of quantitative MRI metrics using full slice histology with automatic axon segmentation', ISMRM 2016. Reference at Cohen-Adad et al. White Matter Microscopy Database. http://doi.org/10.17605/OSF.IO/YP4QG\n"
     ]
    }
   ],
   "source": [
    "from dmipy.data import saved_data\n",
    "scheme_spinal_cord, data_spinal_cord = saved_data.duval_cat_spinal_cord_2d()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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V+aayu3LOFTOhVP37aztN3TOPbM7K5/+vO3GmwBmfkASh4BOSIBR8QhIkSRtf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\nBKHgE5IgFHxCEuT/AybUeH1r0Zp4AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56366abe50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.imshow(data_spinal_cord.signal[:,:,0,0])\n",
    "plt.title('b0 of spinal cord data')\n",
    "plt.axis('off');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Printing the acquisition scheme information we can see the Delta-shells of the acquisition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acquisition scheme summary\n",
      "\n",
      "total number of measurements: 1791\n",
      "number of b0 measurements: 72\n",
      "number of DWI shells: 418\n",
      "\n",
      "shell_index |# of DWIs |bvalue [s/mm^2] |gradient strength [mT/m] |delta [ms] |Delta[ms] |TE[ms]\n",
      "0           |96        |191             |0                        |3.0        |7.0       |36.152\n",
      "1           |4         |627             |402                      |3.0        |7.0       |36.152\n",
      "2           |4         |681             |419                      |3.0        |7.0       |36.152\n",
      "3           |4         |738             |437                      |3.0        |7.0       |36.152\n",
      "4           |4         |797             |454                      |3.0        |7.0       |36.152\n",
      "5           |4         |858             |471                      |3.0        |7.0       |36.152\n",
      "6           |4         |922             |488                      |3.0        |7.0       |36.152\n",
      "7           |4         |988             |505                      |3.0        |7.0       |36.152\n",
      "8           |4         |1056            |522                      |3.0        |7.0       |36.152\n",
      "9           |4         |1126            |539                      |3.0        |7.0       |36.152\n",
      "10          |4         |1199            |557                      |3.0        |7.0       |36.152\n",
      "11          |4         |1274            |574                      |3.0        |7.0       |36.152\n",
      "12          |4         |1351            |591                      |3.0        |7.0       |36.152\n",
      "13          |4         |1431            |608                      |3.0        |7.0       |36.152\n",
      "14          |4         |1512            |625                      |3.0        |7.0       |36.152\n",
      "15          |4         |1596            |642                      |3.0        |7.0       |36.152\n",
      "16          |4         |1683            |659                      |3.0        |7.0       |36.152\n",
      "17          |4         |1771            |677                      |3.0        |7.0       |36.152\n",
      "18          |4         |1862            |694                      |3.0        |7.0       |36.152\n",
      "19          |4         |1955            |711                      |3.0        |7.0       |36.152\n",
      "20          |4         |2051            |728                      |3.0        |7.0       |36.152\n",
      "21          |4         |2148            |745                      |3.0        |7.0       |36.152\n",
      "22          |4         |2248            |762                      |3.0        |7.0       |36.152\n",
      "23          |3         |2350            |779                      |3.0        |7.0       |36.152\n",
      "24          |3         |2455            |797                      |3.0        |7.0       |36.152\n",
      "25          |3         |2562            |814                      |3.0        |7.0       |36.152\n",
      "26          |3         |2671            |831                      |3.0        |7.0       |36.152\n",
      "27          |3         |2782            |848                      |3.0        |7.0       |36.152\n",
      "28          |20        |31              |0                        |3.0        |40.0      |57.288\n",
      "29          |4         |149             |77                       |3.0        |40.0      |57.288\n",
      "30          |4         |223             |94                       |3.0        |40.0      |57.288\n",
      "31          |4         |311             |111                      |3.0        |40.0      |57.288\n",
      "32          |4         |415             |128                      |3.0        |40.0      |57.288\n",
      "33          |4         |533             |145                      |3.0        |40.0      |57.288\n",
      "34          |4         |666             |162                      |3.0        |40.0      |57.288\n",
      "35          |4         |813             |179                      |3.0        |40.0      |57.288\n",
      "36          |4         |976             |197                      |3.0        |40.0      |57.288\n",
      "37          |4         |1153            |214                      |3.0        |40.0      |57.288\n",
      "38          |4         |1345            |231                      |3.0        |40.0      |57.288\n",
      "39          |4         |1551            |248                      |3.0        |40.0      |57.288\n",
      "40          |4         |1773            |265                      |3.0        |40.0      |57.288\n",
      "41          |4         |2009            |282                      |3.0        |40.0      |57.288\n",
      "42          |4         |2260            |299                      |3.0        |40.0      |57.288\n",
      "43          |4         |2526            |317                      |3.0        |40.0      |57.288\n",
      "44          |4         |2806            |334                      |3.0        |40.0      |57.288\n",
      "45          |4         |3101            |351                      |3.0        |40.0      |57.288\n",
      "46          |4         |3411            |368                      |3.0        |40.0      |57.288\n",
      "47          |4         |3736            |385                      |3.0        |40.0      |57.288\n",
      "48          |4         |4076            |402                      |3.0        |40.0      |57.288\n",
      "49          |4         |4430            |419                      |3.0        |40.0      |57.288\n",
      "50          |4         |4799            |437                      |3.0        |40.0      |57.288\n",
      "51          |4         |5183            |454                      |3.0        |40.0      |57.288\n",
      "52          |4         |5582            |471                      |3.0        |40.0      |57.288\n",
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      "297         |4         |23920           |437                      |8.0        |30.0      |52.288\n",
      "298         |4         |25832           |454                      |8.0        |30.0      |52.288\n",
      "299         |4         |27820           |471                      |8.0        |30.0      |52.288\n",
      "300         |4         |29879           |488                      |8.0        |30.0      |52.288\n",
      "301         |4         |32013           |505                      |8.0        |30.0      |52.288\n",
      "302         |4         |34220           |522                      |8.0        |30.0      |52.288\n",
      "303         |4         |36500           |539                      |8.0        |30.0      |52.288\n",
      "304         |4         |38856           |557                      |8.0        |30.0      |52.288\n",
      "305         |4         |41283           |574                      |8.0        |30.0      |52.288\n",
      "306         |4         |43784           |591                      |8.0        |30.0      |52.288\n",
      "307         |4         |46359           |608                      |8.0        |30.0      |52.288\n",
      "308         |4         |49007           |625                      |8.0        |30.0      |52.288\n",
      "309         |4         |51731           |642                      |8.0        |30.0      |52.288\n",
      "310         |4         |54526           |659                      |8.0        |30.0      |52.288\n",
      "311         |4         |57395           |677                      |8.0        |30.0      |52.288\n",
      "312         |4         |60338           |694                      |8.0        |30.0      |52.288\n",
      "313         |4         |63354           |711                      |8.0        |30.0      |52.288\n",
      "314         |4         |66446           |728                      |8.0        |30.0      |52.288\n",
      "315         |4         |69609           |745                      |8.0        |30.0      |52.288\n",
      "316         |4         |72846           |762                      |8.0        |30.0      |52.288\n",
      "317         |3         |76156           |779                      |8.0        |30.0      |52.288\n",
      "318         |3         |79540           |797                      |8.0        |30.0      |52.288\n",
      "319         |3         |82999           |814                      |8.0        |30.0      |52.288\n",
      "320         |3         |86531           |831                      |8.0        |30.0      |52.288\n",
      "321         |3         |90135           |848                      |8.0        |30.0      |52.288\n",
      "322         |8         |5               |0                        |8.0        |35.0      |57.288\n",
      "323         |4         |97              |25                       |8.0        |35.0      |57.288\n",
      "324         |4         |271             |42                       |8.0        |35.0      |57.288\n",
      "325         |4         |533             |59                       |8.0        |35.0      |57.288\n",
      "326         |4         |881             |77                       |8.0        |35.0      |57.288\n",
      "327         |4         |1316            |94                       |8.0        |35.0      |57.288\n",
      "328         |4         |1838            |111                      |8.0        |35.0      |57.288\n",
      "329         |4         |2447            |128                      |8.0        |35.0      |57.288\n",
      "330         |4         |3144            |145                      |8.0        |35.0      |57.288\n",
      "331         |4         |3927            |162                      |8.0        |35.0      |57.288\n",
      "332         |4         |4797            |179                      |8.0        |35.0      |57.288\n",
      "333         |4         |5754            |197                      |8.0        |35.0      |57.288\n",
      "334         |4         |6799            |214                      |8.0        |35.0      |57.288\n",
      "335         |4         |7930            |231                      |8.0        |35.0      |57.288\n",
      "336         |4         |9149            |248                      |8.0        |35.0      |57.288\n",
      "337         |4         |10454           |265                      |8.0        |35.0      |57.288\n",
      "338         |4         |11846           |282                      |8.0        |35.0      |57.288\n",
      "339         |4         |13327           |299                      |8.0        |35.0      |57.288\n",
      "340         |4         |14893           |317                      |8.0        |35.0      |57.288\n",
      "341         |4         |16546           |334                      |8.0        |35.0      |57.288\n",
      "342         |4         |18287           |351                      |8.0        |35.0      |57.288\n",
      "343         |4         |20114           |368                      |8.0        |35.0      |57.288\n",
      "344         |4         |22030           |385                      |8.0        |35.0      |57.288\n",
      "345         |4         |24031           |402                      |8.0        |35.0      |57.288\n",
      "346         |4         |26120           |419                      |8.0        |35.0      |57.288\n",
      "347         |4         |28295           |437                      |8.0        |35.0      |57.288\n",
      "348         |4         |30558           |454                      |8.0        |35.0      |57.288\n",
      "349         |4         |32909           |471                      |8.0        |35.0      |57.288\n",
      "350         |4         |35345           |488                      |8.0        |35.0      |57.288\n",
      "351         |4         |37869           |505                      |8.0        |35.0      |57.288\n",
      "352         |4         |40480           |522                      |8.0        |35.0      |57.288\n",
      "353         |4         |43177           |539                      |8.0        |35.0      |57.288\n",
      "354         |4         |45963           |557                      |8.0        |35.0      |57.288\n",
      "355         |4         |48835           |574                      |8.0        |35.0      |57.288\n",
      "356         |4         |51794           |591                      |8.0        |35.0      |57.288\n",
      "357         |4         |54840           |608                      |8.0        |35.0      |57.288\n",
      "358         |4         |57972           |625                      |8.0        |35.0      |57.288\n",
      "359         |4         |61194           |642                      |8.0        |35.0      |57.288\n",
      "360         |4         |64501           |659                      |8.0        |35.0      |57.288\n",
      "361         |4         |67895           |677                      |8.0        |35.0      |57.288\n",
      "362         |4         |71375           |694                      |8.0        |35.0      |57.288\n",
      "363         |4         |74943           |711                      |8.0        |35.0      |57.288\n",
      "364         |4         |78600           |728                      |8.0        |35.0      |57.288\n",
      "365         |4         |82342           |745                      |8.0        |35.0      |57.288\n",
      "366         |4         |86171           |762                      |8.0        |35.0      |57.288\n",
      "367         |3         |90087           |779                      |8.0        |35.0      |57.288\n",
      "368         |3         |94090           |797                      |8.0        |35.0      |57.288\n",
      "369         |3         |98182           |814                      |8.0        |35.0      |57.288\n",
      "370         |3         |102359          |831                      |8.0        |35.0      |57.288\n",
      "371         |3         |106623          |848                      |8.0        |35.0      |57.288\n",
      "372         |8         |6               |0                        |8.0        |40.0      |62.288\n",
      "373         |4         |113             |25                       |8.0        |40.0      |62.288\n",
      "374         |4         |314             |42                       |8.0        |40.0      |62.288\n",
      "375         |4         |615             |59                       |8.0        |40.0      |62.288\n",
      "376         |4         |1017            |77                       |8.0        |40.0      |62.288\n",
      "377         |4         |1519            |94                       |8.0        |40.0      |62.288\n",
      "378         |4         |2122            |111                      |8.0        |40.0      |62.288\n",
      "379         |4         |2826            |128                      |8.0        |40.0      |62.288\n",
      "380         |4         |3630            |145                      |8.0        |40.0      |62.288\n",
      "381         |4         |4534            |162                      |8.0        |40.0      |62.288\n",
      "382         |4         |5539            |179                      |8.0        |40.0      |62.288\n",
      "383         |4         |6644            |197                      |8.0        |40.0      |62.288\n",
      "384         |4         |7851            |214                      |8.0        |40.0      |62.288\n",
      "385         |4         |9157            |231                      |8.0        |40.0      |62.288\n",
      "386         |4         |10564           |248                      |8.0        |40.0      |62.288\n",
      "387         |4         |12071           |265                      |8.0        |40.0      |62.288\n",
      "388         |4         |13678           |282                      |8.0        |40.0      |62.288\n",
      "389         |4         |15387           |299                      |8.0        |40.0      |62.288\n",
      "390         |4         |17196           |317                      |8.0        |40.0      |62.288\n",
      "391         |4         |19105           |334                      |8.0        |40.0      |62.288\n",
      "392         |4         |21115           |351                      |8.0        |40.0      |62.288\n",
      "393         |4         |23225           |368                      |8.0        |40.0      |62.288\n",
      "394         |4         |25436           |385                      |8.0        |40.0      |62.288\n",
      "395         |4         |27748           |402                      |8.0        |40.0      |62.288\n",
      "396         |4         |30159           |419                      |8.0        |40.0      |62.288\n",
      "397         |4         |32671           |437                      |8.0        |40.0      |62.288\n",
      "398         |4         |35283           |454                      |8.0        |40.0      |62.288\n",
      "399         |4         |37998           |471                      |8.0        |40.0      |62.288\n",
      "400         |4         |40811           |488                      |8.0        |40.0      |62.288\n",
      "401         |4         |43725           |505                      |8.0        |40.0      |62.288\n",
      "402         |4         |46739           |522                      |8.0        |40.0      |62.288\n",
      "403         |4         |49854           |539                      |8.0        |40.0      |62.288\n",
      "404         |4         |53071           |557                      |8.0        |40.0      |62.288\n",
      "405         |4         |56387           |574                      |8.0        |40.0      |62.288\n",
      "406         |4         |59803           |591                      |8.0        |40.0      |62.288\n",
      "407         |4         |63320           |608                      |8.0        |40.0      |62.288\n",
      "408         |4         |66937           |625                      |8.0        |40.0      |62.288\n",
      "409         |4         |70657           |642                      |8.0        |40.0      |62.288\n",
      "410         |4         |74475           |659                      |8.0        |40.0      |62.288\n",
      "411         |4         |78394           |677                      |8.0        |40.0      |62.288\n",
      "412         |4         |82413           |694                      |8.0        |40.0      |62.288\n",
      "413         |4         |86533           |711                      |8.0        |40.0      |62.288\n",
      "414         |4         |90755           |728                      |8.0        |40.0      |62.288\n",
      "415         |4         |95076           |745                      |8.0        |40.0      |62.288\n",
      "416         |4         |99497           |762                      |8.0        |40.0      |62.288\n",
      "417         |3         |104018          |779                      |8.0        |40.0      |62.288\n",
      "418         |3         |108640          |797                      |8.0        |40.0      |62.288\n",
      "419         |3         |113365          |814                      |8.0        |40.0      |62.288\n",
      "420         |3         |118188          |831                      |8.0        |40.0      |62.288\n",
      "421         |3         |123112          |848                      |8.0        |40.0      |62.288\n"
     ]
    }
   ],
   "source": [
    "scheme_spinal_cord.print_acquisition_info"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The 2D data only has data measured in the xy-plane, where we only use the [1, 0, 0] dummy direction for b0 measurements. We can see the unique gradient directions as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.70711 , -0.70711 ,  0.      ],\n",
       "       [-0.70711 ,  0.70711 ,  0.      ],\n",
       "       [-0.707107, -0.707107,  0.      ],\n",
       "       [-0.707107,  0.707107,  0.      ],\n",
       "       [ 0.707107, -0.707107,  0.      ],\n",
       "       [ 0.707107,  0.707107,  0.      ],\n",
       "       [ 0.70711 , -0.70711 ,  0.      ],\n",
       "       [ 0.70711 ,  0.70711 ,  0.      ],\n",
       "       [ 1.      ,  0.      ,  0.      ]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "unique_directions = np.unique(scheme_spinal_cord.gradient_directions, axis=0)\n",
    "unique_directions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is valuable to check if actually the signal between the two orthogonal directions is the same:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sxIAzPM4SA2fPniXUGrF6/vx5jh8/TokSJbh//37E/O7fv8+6deuMxEB6o2xZ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\n3c7/B+979UaaTrgyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56365cb750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dir1mask = np.all(scheme_spinal_cord.gradient_directions == unique_directions[0], axis=1)\n",
    "dir2mask = np.all(scheme_spinal_cord.gradient_directions == unique_directions[1], axis=1)\n",
    "\n",
    "test_voxel = data_spinal_cord.signal[20, 20, 0]\n",
    "data_dir1 = test_voxel[dir1mask]\n",
    "data_dir2 = test_voxel[dir2mask]\n",
    "\n",
    "Delta_dir1 = scheme_spinal_cord.Delta[dir1mask]\n",
    "Delta_dir2 = scheme_spinal_cord.Delta[dir2mask]\n",
    "\n",
    "G = scheme_spinal_cord.gradient_strengths\n",
    "colors = ['r', 'g', 'b', 'orange']\n",
    "\n",
    "unique_Deltas = np.unique(scheme_spinal_cord.shell_Delta)[2:-1:2]\n",
    "for i, Delta_ in enumerate(unique_Deltas):\n",
    "    mask_Delta1 = Delta_dir1 == Delta_\n",
    "    mask_Delta2 = Delta_dir2 == Delta_\n",
    "\n",
    "    plt.plot(G[dir1mask][mask_Delta1], data_dir1[mask_Delta1], c=colors[i], label='dir1 Delta='+str(Delta_))\n",
    "    plt.plot(G[dir2mask][mask_Delta2], data_dir2[mask_Delta2], c=colors[i], ls='--', label='dir2 Delta='+str(Delta_))\n",
    "plt.legend()\n",
    "plt.xlabel('Gradient Strength [T/m]')\n",
    "plt.ylabel('Signal [-]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be seen that the two measured perpendicular directions experience slightly different levels of diffusion restriction; the dir2 signal profiles attenuate faster than the dir1 ones. This could implies that that some kind of anisotropic axon dispersion could be happening, or that the axon bundle is slightly tilted towards dir2.\n",
    "\n",
    "Dmipy allows us to add axon dispersion into the AxCaliber model to compensate for this, but we'll ignore that for this example and fit the signal as-is."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit AxCaliber to spinal cord data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is known that a Gamma distribution is tricky to fit since there are several parameter combinations that produce similar distributions. We will use the stochastic MIX optimization *(Farooq et al. 2016)*, which is slow but is likely to robustly give the global minimum.\n",
    "\n",
    "#### NOTE: Fitting AxCaliber to this dataset with MIX takes over 7 hours!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using parallel processing with 8 workers.\n",
      "Setup MIX optimizer in 4.57763671875e-05 seconds\n",
      "Fitting of 968 voxels complete in 30356.3031921 seconds.\n",
      "Average of 31.3598173473 seconds per voxel.\n"
     ]
    }
   ],
   "source": [
    "axcaliber_gamma_fit = axcaliber_gamma.fit(\n",
    "    scheme_spinal_cord, data_spinal_cord.signal,\n",
    "    mask=data_spinal_cord.mask, solver='mix', maxiter=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize fitted parameter maps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize the fitted parameters as before:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dx5VGfO7wuCVRUh9Nt2kOpShuNURSawfTn3J1PMWuKlPlsTJrLK5bYj/qJgbh\n7lcqOyE6XvaWMHZJr2v94CiJHUf/Zk/qBbR3OnXvix1AY+RzVVgQOcY2K6EoxcXn20020n1Gwu1i\nDDOOh6zzY403UxwqLt4cz+moKd23HgrJWK0YT93fSNG0Q41UV+J2RA0ri66GToiNtH07a2nh7eOH\nUvRqUy2N11VTJ1JJKjYwXNblqFacLppgSTTCWhEedG36/H3llhTHbkyHyGjYNWmGrp+VobBofKhZ\nsQtn+w56/GhZyekzPhlPVQn7cKH7qMcF7sOC9c3R8NxxW8PlNss/tVNTYdc8bODoqlTD6iFOGytW\nfG/GD6T90EPjqTbtWpXe4/3r020mV6fHPBT2tSTpfsMpDj9S6dz5eVD1U3yUSSEASdk/lE4zBwA9\nZpbaNNfi0DTCArBs+m2/iUkhgJzz5SmAHtRlbaIRFoBl1U/7TUwKF8lG0lfvvn5NPp5aH6IHoQNo\njEVWp+PlMbcQniDGNtviRM2SZGR83OpEilbE2GaMmMYIZzMsGu2VkqMfJYvMty9277Nse8fLw1fw\nxW2Nj5nGMZbbDAvE1kJUtba/GHOoNsODhXGM/vpEinQ1dg7SqW8rNwePzr5453fz8VcPrc/Ht46n\n7sjrhtLfe+ywWRYZna/4WLGDaHzcjXGx5BBJivHRRkmP4wONkY6XN0ORiB1Qx6rF+Oh8OpZG1cJr\nSN33qqFmNsJp+vvrKZ5aD0eSY2z15OH7Cs9RCY81HGKw/+fWb+fjY8JrevGpg9KVtOvalDfCknSn\nskZY7Z1FvyDpEklX0AjryHnlzf+dj/9hV+pUPrErxdmr69JnNi44HztsNkI30Opw6O45Pb9vb2In\n0maIjFZip/OJzp3YC11GY5Q0pt9Hwj5SSQt5O6y7c4zBhodthH2eMC50Uw3K3oNDB1Pt3B5iqPcd\nTLHSBxyzs3CfwmkDIQb7xOtSl9ITh3fn40+dnbrI9rf+2m9iUggg44efewEAR12Xtcnd62Y20wir\nKuljM42wJF3r7lta1/1MqxFWQzTCAjBffbbfxKQQQLJC2ygD6HNd1iYaYQFYVl3WprnWUDWzUyX9\nlaQNrdu8oVXPlg2TwkWqhPhoY3VYZHQoLEw61fmr/RivjApJgnl2H40Ry9qBlF2I8dEYGbVv/SA9\n7OMfHh4oLMwaHrMQDQ1jC+PKVDEaUV8VOofFOEV8SbHbXnifyrq0Fn/p3B21viouLlvsoBXFFEjh\nvWmUd1Hsa17slIaV70AzxRzvrqdF6idCN9B14SMS11aqhw9ntWTx+ma4vNJWoOJjxRjnCWGB9/Uh\nPhojo59/8P3y8S/ceG96zBCBlH2vAAAgAElEQVRpn/TQ0VSdu5jGSOpYpRgfva++uuNzx6hrjJiu\nDgs2x+eIr7MQSQ3JrXh5XOx+NtVQ1CthPNRPJ7DMF7Wp70yHz+/+etqPsvD/uVoNcdDCYvTpcQpd\nPGOdCmOrttWveuyyHjcqRFHHQ4Qz7BJsflOKct/6B49N2+QxSppuH+cLsVbE/Y/27pWxs2gtLGwf\nb1fYTQyvx8c7dy6Np96olt7AeujQftDTPuzNu4qL0k9sCJ3fw+MeF7qS3jO9XgOny9oU1lB9urLz\nmq8xsy3ufmO42ZuVLfP1wdb6qldK2rz4jS7HpBBA0kcxCAB9hNoEoBd1V5vyNVQlycxm1lCNk0KX\ntK41Xq/Dm2QtOSaFADJe/MYZAHoCtQlAL5q9Ns22jup81lC9VNKXzezVklZLetqit3cOTAoX6aPX\np3jvr77g1fm4NhG6eMZunTE6OY+DCyVrOGfXhT/E6mR64NqhEBmNC7RffV3Hx7n3f6fug5v+JHX+\nsqHO0dUY7SzEU9sSGjYSV5sNw9ApNEZGK9MxrxpiEpWSN1All8duXauK3bfMh8I4xmDTc8f/LdVN\nqUujH0rvU/PgQfUf42h8n3nBU16Yjy/+QupEun5ootPNCzHPKC5kH6NDZQu9S9JINV23OnTrPKZ2\nIB/HeGdZt7r3/9Wz8/ErXvSP+XgoLGRfCdGyGAWN8dTYJVSS9lvqAjpdSRGq2GVvTdju0ZIFm2M0\ntBG6jFZDxq0ZwmIxQrZrOkVY28X46JA6/3/56O3fzMcbKmm7f/HkC0sfd2WiNvWbjz3lp/Lx1F+F\nf6fXps9ZocNmLbYh7/yYseGHFeKmbX87JddVwiL11cl0+alv+1bH5zvzg7fl462vOC09dyyL9c5/\nt9PTqSYMDbV9vkONaIQoaexSWogs7o/7NeFh4h5+PBUpxGQ9vBexjk5OFacHd+6dOxq6IdTbl9yU\n3pvjaumUgXc/4KFzPs7KMmttmm0d1fmsoXqJpCvc/T1m9lhJH2+tobpsh8iYFAJIOBoPoBdRmwD0\nouVbQ/Wlki6SJHf/tpmNStokaUdXzzgP81vIBUD/c8madtgPABxV1CYAvaikNs2jPuVrqJrZsLI1\nVLe03eZ2SU+VJDN7sKRRSfdqGfFNIYBklg63AHDUUJsA9KIuatM811D9bUkfNrPXtp7lxa0ldJYN\nk8JFetnjnpuPmw9MX7zWJtL/t8Zw59bGsUVw2bmGJZ3gD7sunttXmUrj+Zy3eL9n/yjdPi5PEZ8r\nnEcYz2WMl3u17cms8+uuhXMHq+H8x/i9dbMafontneNzFM5zjLdRx9tIUmM4nKOwOuTww+uIX5/b\nVDrvSPXy86f6BUff+8t7vvKJfPzFA+lcjg1D6dyPA43UDn4ofLinQ4GKlzfDqRCV2bp/hPtvDOea\nrK2m8xkb8yhQJ70rnc9TfVHn5yucfxeXpLB0ftKEF5eniecCxvMF4/atrx7q+HwT8WSdsEkTSs8R\nl7aI5wQ2ZgnojIfzJGN793ieZHyt+8PrW93nnVioTf3loquuz8d/c9uj8/HoWFo6ZmI8nDcczils\nhnPiLCxb4fWSnar2P524vxXOW6xNLuxvrH5nSvtZM51TWFiZZizVo3j+Ylxuo1IpfnbjGWPV4fRL\nPL+weTDUmqm40xgeKD5s7NMQHrNw7uUs9fjQZHq+u/at63ibfcNpf2l9LdXODdXxTjfvG93Wpnms\noXqjpMcvauMWiEkhgIyL83YA9B5qE4Be1Ge1iUkhgFyff9kAYIWiNgHoRf1Um5gULtJbv/GFfPy7\nv/GKfFyIMEbzWYaiZNWFw24XWgxXJ5fmr9JrnZ+wEuOj9biMRIo11UeHVSYu+VAN8dHxN+3Nx6sv\nW9vx+ZoW3sywfXFJicKyFfF5Z3lbGnHJjLVp22PIrDqRoiyqpY/LVXf9Zz5+xomdI7crjbEWWN95\n7S+8PB8/9orv5+MYnYxLTMRoaNnllZC9anp5FDJGS2MkczHaI6AzRkL8czT0g19dSUtK7J0eK9wn\nxjBHwn3GwjIUH/nwz+bjV/7PVOsrId81HZawiMtexKT7dFiSohFj/22HmONyFXvrq8I1x6iTtZX0\nvq71tN21E47Px/W77+l435WE2tR//vmpZ+fjQx9Kn+tChDF8VpoxGlqIOYYbVUrOt5llSQpNpseN\nq87MUtrm1BxL+0VDIfbaCFHVNavTZ3ff/mJtivt9MXLaOJhqzTmXpiUf/vu1Z6TbV8O+WngRHpYY\n83TGQOlzNduipLVaek2HJtP+UlyqYt9oio+uqqY38+Th+9LjUJt6GpNCAAnn7QDoRdQmAL2oj2oT\nS1IAyFnz8J8572N2kZndZGZbzewNs9zuOWbmZla2mCsAdNRNbQKA5dapNq3U+sQ3hYt06c+k7qNK\n3+DLrfsjB6XdR9uSEZXpEBNohA5cMbd09XULeu7GSOfca3w91ckUC/BaOq7Qft8YGS3ET6fS5Qcm\nUo7h0BtSnGLTH4aun7GJWPigFbu3hhvVSzpxtf0eI6cxSmrN0JV0KkW4KlPpdT/znCeGB92rvtBF\nDMLMqpI+IOnpyhZjvcbMtrS6ZsXbrZX0GknfWZqNxXz8/uc/no//Zf9D8nGMfcYOoDEyWnZ5WZS0\nXYwPxXhnjK5+6uwTZ38BbQ40RjteHl/P+trBfBzjpnsbqwr3iR09Y8fSGMmMT/d///Ln8/FvveTv\n8vF4uO9Q6Eo63Uyvs6wTaXtEK4rv0/6wIbEr6dpK6vC31nbm409c8/f5+HmnPK70OVaMPotoQXrM\nVXfk49u3HZuPp6fDfkTJxyPGHC12Jw//9sdupe0fMwufR5vs/N3IaW/9VsfLy4TGwbKREC8fTzVo\n7bGhNk2lyxv7i7H46rp02sp07DJ6IJ5Kk174A/8sRUlvflXoghr3d+LuWXz9lc5jNYpvWtylje9f\nvZnevwMxVjqe6tQtq47Lxy//xr/n4w+edaZWvD6rTXxTCCDXxdGux0ja6u7b3H1K0qclPbvD7d4u\n6d2SlubkMgADpV+OxAPoL/30TSGTQgAZ76qwnSTpjvD79tZlOTN7hKRT3P2LS7q9AAZDd7UJAJZX\nSW1aqfWJ+OhihdhijHNGZRHQsoXpC1/az7J4feG68N1+jI/OJ8Raf8oj031jF88YyQxdPwuR0dH0\nJ9Rs61xaCcccbDpFrGLU9f7vSPf3a/6r4/ZVnpC6exa6o8YFaAuv2TvepuPvaWNzMUpaGUtxCBsP\nLbsOpsVYbSRd7pOpA+CK1LmQbTKza8Pvl7v75a1xpz+x/F02s4qk90p68RJtIRagGv7gY1dNKXX6\nHSr516tSUqCa86oqxc6aMSZZ1kG0zNOu35+P99ZTl74Y/4wmPH1md9dX5+PxRrE78lg1RbTWWPoC\neyh0In3jS/42H//1g07Jx5959wn5+Fk37srHkyF6XjjkGt9iC/Wl7T1u70Y6oyxKem89LSJ9bPVA\nGKdY6Rfv/G4+/rmTUq1fcbrcyTKziyS9T1JV0kfc/Y9KbvccSZ+V9Gh3v7bTbbB0RmPH4KH0mTuw\nO33GraSbqJUtZF/YfSmvU4X46Wz7WHO49Q8em4/ra8KC8GFh+rho/LrRVIPv2rEh3WaobfH6EN20\nifTZt3D51lecmo83v+nb+fj0N96Vj7e9K21fsR513keshPe7VgutWFV8b5uxI2roqFqrpNexbzLV\nqR8dSPXy1OEUc3/btlSb3noGtalTbTKzX5Z0qbL9qh+4+/O73s55YFIIQFL2j0PJ/GCnu5c1h9ku\n6ZTw+8mS7gq/r5X0EElfs+xflRMkbTGzZ7HjBWA+ZqlNs9+Pc54BLKPlrE1mdpakN0p6vLvvNrP7\nLclGz4L4KIBMdxGtaySdZWanm9mwpOdJ2pI/pPted9/k7pvdfbOkqyUxIQQwf93HRznnGcDy6T4+\nOp/a9HJJH3D33ZLk7juWevPb8U3hIsVYZG08fd1eX52+8m8OlXTDLERJw8KiNvft26+LnT/jY8WG\nUz/+ZIphnvbRdE19LI0LHarCExSSWmGx5sZoeacwa8ZOVmm8+63p392NP3uzOrFHpU6Je9+YOnat\n+5MUeyvrlFr4Kr/9sMc8km/NoXSn+uqwMPXBECUdDjGxlCRd8RZ6xMvd62b2KklXKftz+5i732Bm\nl0m61t23zP4IWE5jIaJ1XC3FMO+upM5wMfJY1lk0LkQ/31WdG+HDt7+ZokTVkgz3rW9PUacXPftf\n07ZOpm2d9s6f+RgljdsdO462d/qMt4v3/5MP/3I+vv97OncgfMlNqdvfOy+/JB//ykuuStvamHtb\n219PYx7HaQ80Ulw9diI9rrYvH59S66Oi1FJSm2aLtkudz3m+oPC44ZxnM/udJdpczCF+Du6/Nv3t\n3rc7Rb4LC9bHca3zH4OXxCIPu12IYVanQ82b7HyvuOD61lemNvP1NaGWrUn7gjG6OjqWYuqFbQix\n1+qqeuG6GImNHvR/bknP/ZO7O97m1nekOvrA927Lxze9/vR0oxATHRouPveM2RroW0nmNnZUjfX2\nvpEUCf7J9Ma0fcMrf/F6adb9ptnq05y1SdIDJcnM/l3Z/tWl7v7Pi97gWTApBJBxdZWNd/crJV3Z\ndtlbSm77pC62DMAgK69Ns0XbJc55BrCcZt9vmq0+zVqbWmqSzpL0JGWn5nzDzB7i7nsWvqHzQ3wU\nQK5fOmgB6C9d1qaFnPN8q6QLlZ3zPNtEEwByXcZH56pNM7f5B3efdvdbJN2kbJK4bPimcLHqIbY0\nnmIC1bCIp1cqYdw5GurzyDW2J6dizDR2zKxOdv5rbEymB5heE8arw7GBQkfPsKnhIavDnbc1LlCf\nbV8Yh46lG965WgsRoxjx/YuxXIvPPb/miMXnKMlKxHisj4RFZGv9+dFhEthfRkNEK8YLNw6leOHO\n6TX5uN7sHHmMi8OXRUyn22KlMT4Uu4aurXY+bSs27twxnWLiOybSOHbrnArbWgt/uIfCKtKNsA2r\nqsVuevF1xBjnq172hXz8+ffMfV5/fNnxfTpQTzHPkbDA/WwL1pcpu8/u8L7ub6ao7MGwoLRKUvYr\nTZe1KT/nWdKdys55zrv3ufteSZvy5zD7mqTf4ZznI+v+q/bm41vXpnjhwf0pdl76uYmR0WrnWGOM\nlUoqLMwey1Glc0PjgukN6Q/RV6c7DK9K9SV25Ix27kv7PpXhdN/27fNw//h3/9//K0VAz3hD5/ho\nWVf6+D4NrU7bOlRL21EPz1upFD9wcQur4bqpejjFJnRdjY812Ui32TEVTgFa3cXOWg9ajtrU8gVJ\nl0i6wsw2KYuTbtMy4ptCAJKy1tydfgDgaOq2Nrl7XdLMOc8/lPSZmXOezexZy7vVAPpdWW2aqz7N\nszZdJWmXmd0o6auSXu/uuzo/4tLoz687AHSFbwoB9KJuaxPnPANYTstVm9zdJb2u9XNEMClcpPqd\nKQJcHUtRh9qB9PV8cyjEmUY6L75eiJLGNGe4vD3aUNYp1Gudv5I/eUv63z09FqKnIYZZqaeNasYF\n4eP2pZdZUGtbt70S7h8Xl49xULvwvHSHq69L4/CEG9+ZYlGTx6QX3Qgx1tpE5+6thQ6os7GScdAc\nTs9drRQyY2lcCf9TmvPIovQaJoV95dWnPT4fv2Xb9/Lx/YZSlDQuhj4VOgvHaGiMWsZIZoxdxohk\n+3Xx72q00jnPePHTUmIvRkbH66l+joYFladCJKkZiuN9UylSGTXb4q1jlRT3jx1YY3fUS36U6vun\nzj4xH8cuoa/+tRQ3vflQ6lIYY6xxUecYgxuy+dWIZsiAlsXo4v/HYsQ3ja+66z/z8TNOTN2oVwRq\nU1+56iHr8vEjv586jJ+4LtWmWybT53JqMp7P0nk/KnYVLWlynN19Miy4Pj73fW5+Teo4ahtD3jQ8\nXyEyGj6j9dA1tTGdXsPQSIiUt8dNQ5TeY/473Cx2GY2L18f9l62vSnHT5mj6AK1elWpfjHkOhyhp\ne3y0TLWktsUNOTiVamHsnhx99PZv5uOXnvqEeT13z+ij2sSkEEDG+aYQQA+iNgHoRX1Wm5gUAsj1\nU3ED0D+oTQB6UT/VJiaFS6hxc2oKVF11dj6uhUXWmyHaGTtplkVGZxVud8fT0wOc8i/p8vrPPyZt\nX4iulsVYCzHPmFoIsdKy7W5rPiqLHbTClTFl5tV0m7u/8OB8fP8/Cl1Gw/vXGC2JutZiZDRuRHGb\nCq+1pBNsWYSkEMv18H40SiJgKy1K6tI802xYgS474/x8/Mqb/zsfHxhKscPJEB+NnUhjZLQ9hplf\n3vZhi1Giz33n0fn4ORdek48fdG16vj3TKSYeO3fGGOtUWBC+HrZjtJJipfXQeTO+hkrbB3uksiqM\n62GcHmsixEq3v/Fx+XjaP5eP9zbS4+yZTtHVVdUYTw0d+kLWqGHF9zJeF+O38b2slC0c7aE7cnit\nVev8/2tFRUmpTX3tu49If6MPunZHPj4wlerAT6bX5+PmVPi3NX4cYhfPsEC72rp71van5zvtih/n\n41tf8oB8fMebw+f9mFQfquFxY9fQQnCymv5Ym6EeVUJ31JiArVTLZxX1uBsxlO5fGw8R2BNSbL3Q\n9T189G1DqkfNQrw1dHGO29Es1o143WS4T6E7fGGc7nswdOOPNTlG9U+upS7YHw5R0pf3epS0z2oT\nk0IAkrJ/1PrpiBeA/kBtAtCL+q02MSkEkPEFNOYBgCOF2gSgF/VZbWJSuEwq+w/l4+pY6EIX4pn1\n1eEr+GpJZjRkDLwtNrT94vT7SV9O49F//I98vP+5F+bjkGAqRAziM4eGfoV1VuJ4vvHW+HzF15HG\nt706fe9+2ntC97xaiIytSw9UiK7GmESMuoaoavv7WvY1fyERF2Mdk51js4VsRB/ppyNeKHdSbU8+\n3tNIkccYl4wLyE+HKHiMHsXI6JCKH64rv/7IfPwzP/WDfHzd+emzc+LV6TM/0UjP3SwpUBOhE2mM\nURY6pc6zQMVIZ3wdMR77vs8+Ox//5gv/KW1HeJ/unEyLbTdLYraTIYoVo6qNZnl8NIrdTmNMf001\ntXyOz1ftwwVGqU2D4YxV9+bj7WMb8vGh9enzunt3ihr6dDhNpRYWlp/o3OVYks76s3Sqz/ZLUmT0\n5D/8Vj7e9q7U3bMSFntvhuerDIXni08QPtfN0H20NpRqZCN0Lq1W2z6v4fPro+k+1f2p7pzxoRR7\n3fYb6TVY2DdpjIYaGZ5jaiq9lxaeK3YitbYyWlZX4/1jfDQuZF9WkY+vpv3k8dCt+fhq5w6lvaqf\nahOL1wPIWfPwHwA42qhNAHpRp9o0n/pkZheZ2U1mttXM3jDL7Z5jZm5mj1rK7e6EbwoBZPqstTKA\nPkFtAtCLuqxNZlaV9AFJT5e0XdI1ZrbF3W9su91aSa+R9J3Fb+zcmBQuk/ott6VfjntoPowdM4cO\npFjA9JoQJQ0xxZBSUnWqLWLQjLdL47LIaFyMPn6fX0gwhXElLkYfG3mVpDLamxIWOpmG57vt19Mn\n6NQPh8hYeK3N4RCXGomtWUNMLLzmmOkuLF7fFvOMMVNvz0e0xP9H8X2Kt/f9Bzret2AldBwNshOm\n+y92hsP93umpK/ELfrQ9H4+FOOL9w790O6ZSlHTS0gf1UIh8rgqLwUvFz9rB0E30xKtTUYr3j4vR\nR7GbaIwnjdbS88Uoab2ka2e9rUBNFrqrpusu//xF+fglv/iVfDzhaft21lN8bf90isBG8bXF7Ysx\nz0pbnr3YcTTeLv2/iAvex9fXCMXquMrcEdqe7zgaUJsGx5fOTZHR47+d6tHakVBfNqZ/f2OUtCBG\nMuvln4d6+PhufW/YdwqxTdXjPkiMz6vj5QWhW2mjfZH6mcvrxd8rJZ1TH/inKfZ6y0sfoE4K+zjt\nsdSZy8PFtRC5jc9rbRH0QpPXZqXj7eI4vtaxkRS/PWb4YD5eXVKnnnXSozte3osWUZseI2mru2+T\nJDP7tKRnS7qx7XZvl/RuSb+ziM2cN+KjADJORAtAD6I2AehFJbWpVZ82mdm14efXwz1PknRH+H17\n67KcmT1C0inu/sXlfhkz+KYQQK6f1tsB0D+oTQB60Sy1aae7l50H2Olr0vwrRzOrSHqvpBcvZtsW\niknhEVA9GGJOUyH6M5y+57eQnayPxShp6Cg3WTw0evKX0+2mV4crwjfZjeHOkdGybpsxD1GIZMZI\nQuxQGj4Mh8Ux4wLvsevqROj6FyKg8TnqoyEyFiOtIWYRY6xxO+JjVtpiGfE+1ekQ6QoL03t4D+J2\nr7pzPB83DqQIRPEJVvCeS5+1Vsb8nFDbm4/XVSfy8b5GylXF+OLO0JU0du3cOJQ+H5J08eO/n493\nTKaIV4xxHphOsdJCFLLZOcQS40m1StqmqfDBnqyHheLDbWbrSho7kcaOfbEjXuw4umc6LVgf77uq\nOh0uT9u0qpIuP9hIj7lK6XJJmo73qaZ/N+JzxC6CBxrp/btwzdZ8vLGaOspGKykyWkBtGkjnrvlJ\nPj5mONWXuyfW5eM7htI/8nsOps/lIaXPhqt4zsu2X0/Ry+l1oUasCv/4F+KnoR7FDqdx8fqS5uSx\n6njoOGqVkhu1scmSQF/ZflsoKR66uFuohfXQfTTGRycOpRo3PNJWm6bTezgykt7z2Mk0aob46IOO\n25GPz1p1Tz7eFd6PX9mcTmlYUbqvTdslnRJ+P1nSXeH3tZIeIulrlv1xnSBpi5k9y92v7XJr58Sk\nEECOSBaAXkRtAtCLuqxN10g6y8xOl3SnpOdJev7Mle6+V9Km/DnMvibpd5ZzQihxTiGAFnOXNQ//\nmfN+c7RVNrPXmdmNZnadmf0/MzttWV4AgL7UbW0CgOVUVpvmqk/uXpf0KklXSfqhpM+4+w1mdpmZ\nPesIbHpHfFN4BDRuuCkf187YnK4YS/Esa4SFPkNkqXYwxBrbOjXVR0MXrJLOol6yYH0x05CG1ZB+\njEc/CvHKcCjBQjzTy9eKLV4X45nhsRqh42h8vqiwHYXF60sunyWW0RiK71nnN6R6KPx/uf3uzg+0\nkiOjbRZ6xGuebZW/L+lR7j5uZq9Q1knruUuzxVis95x5bj5++y3X5ONRS5HP4ZDPjt0vjx9Kn9np\ntgIQI5axs2iMnE43qh0vj1HP2LlzVTUVnFr4Y50Ijx/jqXFb621tk6uFjqCd61uMcxY6pcY4Z9iO\nGBmN3UPj7aPGLAUqdmyN702MqB47lGLsF46mRb+ldD7Bio2Mtun2m0Izu0jS+yRVJX3E3f+o7frX\nSXqZpLqkeyX9mrvfdtgD4Yj714emv+OfuyH9fY+FTscxVvrjofyLFR1cnfajfrJzfeFx66tDXHx9\n7DI6d9fegmasGyWTgHibmBiN8dS2uzZCXNWmS7Yp7reFxqxxn6+yNtWK+kRo7x5q39Rk6JIcdgCb\n7RH+UKsOHUrvbTNsa2041edVY6lz7PkbUj+Vc0dSt+vf2vw49YNua5O7XynpyrbL3lJy2yd19ywL\nwzeFADIuWcMP+5lD3lbZ3ackzbRVTg/r/lV3n/mX+2pl2XkAmJ/ualM8aHWxpHMkXWJm57TdbOag\n1XmSPqfsoBUAzK2kNs2nPvUiJoUAciWFbVFtldu8VNKXln7LAfSzLne6OGgFYFn106SQ+OgRVt92\na8fLqw8+Kx9bPbaSSl/ZTx2zKt5FhbVF42L0cRH42Ck0PmxJTLTsa/BmScfRwva0X14SVz3li6Gz\naOxqGteHLSwyX7KtMX1R6TyuDxWjF2WvrzqVHiwuXr9q2335uLl/f7pDH0VGc176/nTdVrlwQ7MX\nSnqUpCd2tX1Ydr9/eudFg//3j/8rH49VUiyoGY4r3jx5fOE+MVYZ44+H6qlAxfho7BQao6HFyzt/\n7mI8s1byR1yrFO8bo5sx+vrMJ6fz+GPXz3q4zWRJHLbsuacLsdJ0+4P14cLtyu6/dih1hR0JLZWf\ntvb6fHxsJf370C+R0Vx5bZpLp4NWF8xyew5a9agvnrux4+WP+8G+fFwLUdAdk6lL8n0Hit14D22I\nOzRxRyL8cxajpKGLZ4yDFsZRfMjQYTN2NHWL5+G0LRQfu52GYVywPnZWr6aSrEMnhOeI0dXweiy8\n/Lgr04wx/LbX5iWv1UL30qGh9GBPOOmWfPyYsR/n48vOOL/j46xY3demnsSkEICkbHbXxdGtudoq\nZ49t9jRJb5L0RHefbL8eAMrMUps2mVnsxne5u1/edtd2HLQCsCS63G/qWUwKAWS6W29n1rbKkmRm\nj5D0F5Iucvcdhz8EAMyivDbNlmKQOGgFYDn12RqqTAoBtCy8zbu7181spq1yVdLHZtoqS7rW3bdI\n+mNJayR9trUI6+3uftRaLgNYabpegoKDVgCWUX8tj8OksEc0fnhzx8vjuYbVyeL5J0MH03kqjaFw\nEl7sPByzzgv8u43LXMTz9MqWvGiPVceYfHysQnw+9GgunBdYcj5i4TbxYSqd8+7x/MD2547nEVYn\n0tavuj2dO+h33dPxcfuSdxeDmKutsrs/bfEbh6Pp3Q94aMfL47mG66uHCtcdN3wgH4+Hc+cOhQIV\nzxeMS0+Yzf13OBXO0ytb2iKe+1dpe8xK+FufDMs8xKUq4n3KziOM5wjWS3q3xdvE8WhYYqPdunAe\n4YZaarv/02vTEkcPG0696KuWljjqO93XJg5a9blvPSzuF6XP8eb/SPVo87H3Kbqzlpao2Lc7nG84\nHPZi4nl9ceemEZaLCOfpea3k77OwDxZuH6+ot63nFc7Ti+chNkfSuHYo1JTwFjTXp/dAhzqvE1Y4\nzzGWrPgSqm37TuF3q6btGx5NNexxJ9+ajy9cuzUfnzO8u+N29IUua1OvYlIIIOmjI14A+kiXtYmD\nVgCWVR/tN7EkBYCcNZuH/QDA0UZtAtCLOtWm+dQnM7vIzG4ys61m9oYO17/OzG40s+vM7P+Z2WnL\n8gICvinscTaeIkSVNVG1StwAACAASURBVMV40PCeFBOImeaptSFWtaokAlomRj7DX0fpfeNyEW0J\nzkZYDsLDlbXJEM8Kt2/W4oOFy2P0tLB8RudlJApx0/ZUxni63ch96f0bvvdgutFd6bSS5mTqOeD1\n8qhXPzBfuWvr4Og4rpo+N3dXiv05No/uyse1EBP9ycS6fLxnKkW3pkIEtD3q2enyiUaKoZbFOaN6\ns1jEJkKMddfk6ny8PsQ2K6EgxuUp4nNMhVhpXPYivubhcHnhvs1igdo0kt7PB47dnY/PGbkzHz98\nZE8+XlNJ2913y1AE1CYs1CmjKbLYbNuBOWYkxbFvX5WWurjvYKpH4/vS/pZPpM9pjIyq5PQcm+5c\ng3w43ChGONvrXb3zeTJl+2QTx3R+XKvH5b/iBpZ8luKyFW3RUx9LNez441MNOu/Y1LfpkWtvy8eP\nHr09H7/01Cd0fr4+0G1tMrOqpA9IerqyhljXmNkWd78x3Oz7kh7l7uNm9gpJ75b03CXY7FJ8Uwgg\naTYP/wGAo43aBKAXdapNc9enx0ja6u7b3H1K0qclPTvewN2/6u4zRzCuVtY9eVnxTSGATJ+dMA2g\nT1CbAPSi2WvTbOuoniTpjnDddkkXzPJML5X0pa63c56YFPa4+m3pb6Y6OlK80kO8IUQsK9OhQ9VY\n+jJ4OoxLO4sGzaGyy2M+MwwP6+4XrovJhfABihFQa3aOj1bCneNTxNcZt8nC847sCb9IGtmZomHV\n3Smq1bh5W7p/LX0svI9OIJ6bc/QdC/L6zRfm4zdt+8/CddWQrZoOOe6xSuqYuWsoxR93TK7NxzHq\nWW927qBX6AYaIpmT9c4dR9tjpTHeGf8lHAkdQSshrz5UEgGt1FIMPcZNV4WOpodC1DVGTGPEVpLO\nXpWiWA8YTjH2y844Px9feef3NHioTViYb5yX9o9+7obthev2Nlbl4/g53T2WLr99JMVK9x1MjzW5\nP+yHxX2WGL1sdI6PaiqMqyUx1Lb7eyXVlMZYiLPHp94YTm0pi4zGXZmwz1cJXeybISI6dOy4onPv\n/5N8fP6GtF8a3+fX3PrjfHxireQ96Duz1qbZ1lHt9AZ13OE0sxdKepSkJy58+xaGSSGAjEviaDyA\nXkNtAtCLuq9N2yWdEn4/WdJd7Tcys6dJepOkJ7r7ZPv1S41JIYAcHf0A9CJqE4Be1GVtukbSWWZ2\nuqQ7JT1P0vMLj2v2CEl/Iekid99x+EMsPSaFK0jjpq2l1w2dd3Y+9rCQfe1gii0ND6XMQGMkRgys\n4+UxzhkXh/ew6HvZIvOSVKnHcVgoPi4aPxk+TLGB1nDJYvQhDVobT/eNMdTqoXSjymSxY2htx958\nXL/1dnXS711GS7lL9cbctwM6eMcZ5d0vX7P1R/l4f4hu7RlK3f42h3j8/kaIa4WWe/vq6b4x/hnj\nplNDnf9Za+8+OhpiY3ER+VUh3rpxKEWoYhT1oKVtjVHSGD09ZijF00cr6bnWVw+Fceh6LOm80GX0\nd0/vfHrJM086v+PlfY3ahEX44rkbS697yn+lfe37hlOcPX7e946murNjZE0+boTP/oF96TZNTzWo\nsB8VFrgvLHxfLf+myYfCdWFd+un7pVpTHQ3R9hhjDdHTuMj82Gj6wml0KF2+ZijVvuPH9hW24wkb\n0v7n5x98v47b+rrNj+14eV/rsja5e93MXiXpKklVSR9z9xvM7DJJ17r7Fkl/LGmNpM9a1sH/dnd/\n1tJt/OGYFALIuKQGR+MB9BhqE4BetIja5O5XSrqy7bK3hPHTFrVtXWBSCKDFpSZH4wH0GmoTgF7U\nX7WJSWGfaF6X4lnVM0/Px5WJ4XxciJWGcYyANofT5cNhXB8Ltw/NAOOC8+2Rz7hIfew4OrIzRRcq\nUyECsSZta7PWefHW6kS6vdXT0ZnqwdDWK7Y6nQp5C0nNXbuFEhyNxzL5szNTvP1t276bj/dVU0x0\n3FMk82AzjWNEa38zRbQOjKb77pxOka7Y6TR2/TxYL3ZvXhcWqR8OWfdzxtK5/msLUc8NaTtCvHUo\n3DdGQ0ct1aQTaim2XtiGykTh99OH+Px1RG3CMvnXh6bI6FP+K8W5x9amz++BsVQ79qxJkfcYHb93\nY6pBuw6l2xyYSPetVdPkYXI61SZvS496eNxaLd0nRuZXDad9m+HwuNONVP9Whzjo6qG037UmjO8/\nWoyJzjh1pNgZ+cJVqUP759U5PjqQ+qw2MSkE0ELbdwC9iNoEoBf1V21iUggg45Ia/RODANAnqE0A\nelGf1SYmhX2osfWWjpfXzticj70WMqChW19lKsZEQ4RhPF6eop3Noc5dTLPH6twdtLbrQLpROMJS\nGU9RBx8Of5pxsfvw4bPxFL3y8WIMK7/rvfd2vBydeF/FINCb3nrGIzte/vZbrsnHE56iVRPNNF7d\nTDWiUUuxp+OH9na8/XiIocZYqSStqaaaMWSprpw1cnc+Hla6/Nhqqlsx3loNC9yvDpHRDZUUJT2m\nGhe4T1566hOE+aA2YfnFKGn0CzemDqX7h2Nn5FRrNo2k+jC5Ju2/xAh7tHsqRUyHK8VJxVQzREBr\nqaZUwrk0zdDuff1QqjVToVvz2lqqcbED8v2GUu18wHB6bRWlz9h7zjy3sE1bdGzH14H+qk1MCgFk\nXPI+OuIFoE9QmwD0oj6rTUwKAWTc+yoGAaBPUJsA9KI+q01MCgdIfdut+bh67DHpilqIj4YFpD0u\nAl0JoacQPY0dTWPMU5Isnnwbu4Du2pPGnm7T2NO5Qx+OnG6OeJnZRZLep2wB1o+4+x+1XT8i6a8l\nPVLSLknPdfdbF72x6Cu/f/qj8/HH7/j3fDwRWvPtae7Px+MhujWlVIdifDTGUGPMU5JGLdWkGPs8\nI3QljVHPF5zSOfaKI6Pbo/HUJyzW359zXD5+zdbU6f3e+rp8fM/0+ny8t566JI+E7sTRuhDtbL9N\nrFUba6kj6nG1VP9iV+a/OfvkcO/OzyfFGOuxJWN0o59qU2XumwAYCN7Kxrf/zMLMqpI+IOliSedI\nusTMzmm72Usl7Xb3MyW9V9K7lmHrAfSrLmqTRH0CsMzKatMK3XdiUghAUtZEyxuNw37m8BhJW919\nm7tPSfq0pGe33ebZkv6qNf6cpKeamQkA5qHL2iRRnwAso7LatFL3nYiPDqjGrvuO9iag17h3E4M4\nSdId4fftki4ou427181sr7LMys4utxR97ldOefzR3gT0ku5qk0R9whL7szPPXqJHiqfbVNuui79v\nKBmjJ/RZbWJSCECStF+7r/qX5mc2dbhq1MyuDb9f7u6Xt8adjlp52+/zuQ0AdNRlbZKoTwCW0Sy1\nSVqB+05MCgFIktz9oi7utl3SKeH3kyXdVXKb7WZWk7ReEl9VA5iXLmuTRH0CsIz6rTZxTiGAxbhG\n0llmdrqZDUt6nqQtbbfZIulFrfFzJP2ru3MkHsByoz4B6EU9WZv4phBA11o591dJukrZiRAfc/cb\nzOwySde6+xZJH5X0cTPbquwo1/OO3hYDGBTUJwC9qFdrk/XDAbGnV35p5b8IYAl9pflZuuf1COoT\nUER96g3UJqBo0GsT8VEAAAAAGGBMCgEAAABggDEpBAAAAIABxqQQAAAAAAYYk0IAAAAAGGBMCgEA\nAABggDEpBAAAAIABxqQQAAAAAAYYk0IAAAAAGGBMCgEAAABggDEpBAAAAIABxqQQAAAAAAYYk0IA\nAAAAGGBMCgEAAABggDEpBAAAAIABxqQQAAAAAAYYk0IAAAAAGGBMCgEAAABggDEpBAAAAIABxqQQ\nAAAAAAYYk0IAAAAAGGBMCgEAAABggDEpBAAAAIABxqQQAAAAAAYYk0IAAAAAGGBMCgEAAABggDEp\nBAAAAIABxqQQAAAAAAYYk0IAAAAAGGBMCgEAAABggDEpBAAAAIABZu5+tLcBAAAAAHCU8E0hAAAA\nAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAA\nAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIA\nAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUA\nAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkh\nAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNS\nCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCY\nFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAww\nJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAAD\njEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADA\nAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAAMMCYFAIAAADAAGNSCAAAAAADjEkhAAAAAAwwJoUAAAAA\nMMCYFAIAAADAAGNSCAAA0KPM7GNmtsPMri+53szsz8xsq5ldZ2bnH+ltBPD/s3fncXZUdf7/X5/u\nzkISsgfIBgQSkOBolAjMoH4ZUAmiBEdAUFkUxYUMOqMj4AyoCL+Bma+ifgE1CrIohIgLUaOILArK\nFlZNEAhJIBuB7AkhS3d/fn/U6apzb6pu377dnfTyfj4e95Fzq06dU7e67kmdW586p/tTp1BERESk\n67oBmFZh/fHApPA6F/juLtgnEelh1CkUERER6aLc/U/A2gpZpgM3eeIhYKiZjd41eyciPUXD7t4B\nEREREanZWGBp9H5ZWLayPKOZnUtyN5GBAwce9oY3vGGX7KCI7BqPPfbYancfVcu26hSKiIiIdF+W\ns8zzMrr7TGAmwNSpU33evHmduV8isouZ2Yu1bqvwUREREZHuaxkwPno/Dlixm/ZFRLopdQpFRERE\nuq85wJlhFNIjgQ3uvlPoqIhIJQofFREREemizOxW4GhgpJktA74C9AFw9+8Bc4H3AguBLcDHds+e\nikh3pk6hiIiISBfl7qe3st6B83bR7ohID6XwURERERERkV5MnUIREREREZFeTJ1CERERERGRXkyd\nQhERERERkV5MnUIRkV7IzH5rZmd1UFnvMLNno/dLzOxdHVF2DftydBihUXqBtvy9dW6IiBRTp3AX\n0QWYdBdmdp+ZfWJ370eRcL6/bmabzGy9mf3FzD5tZnVh/Q1mtj2s32RmfzOz/zazIVEZo81sjpmt\nMDM3s/1z6nm3md0bylhjZk+a2QVm1n/XfdrahM/0mpltDvt+t5l9KM7j7se7+41VljWxUh53v9/d\nD27vfof6bjCzyzqirFbqmWFm88xsm5ndUOU2R5tZczium81smZnNNrO3leVr9fib2anh3N1iZvfl\n1NXXzC4xs2dDWcvD/yPvac/n3p2q+d6JiMju0WqnUBdgrdMFWFX16AJsF9sdF2C26zqU73f3PYH9\ngCuAC4DrovX/E9aPIpmz60jgz2Y2MKxvBn4HfDCvcDM7BbgduAXYz91HAB8CxgHjO/7jdIo3u/sg\n4GDgBuBqM/tKR1diZt11aqMVwGXA9W3dLhzXPUnOq78D95vZsWX5Wjv+a4FvkZy/eW4HpgNnAsOA\nCcC3gRPauL9dScXvnYiI7D7V3inUBVjrdAFWmS7Adr0efwHm7hvcfQ5Je3GWmb2xbP1Wd38UOBEY\nQZjU2d1Xufu1wKPlZZqZAd8ELnX3H7j72rDNs+7+r+7+fMh3uJk9GH4sW2lmV5tZ36gcN7PPmtnz\n4ceur5vZgWGbjeEHjr4h79HhR48vmdkrobyTzOy9Zvacma01sy9HZVesu+wYrHb3m4HPABeZ2YhQ\nRtqBN7OJZvZHM9tgZqvN7Law/E+hmKfCjy4fivb1AjN7GfiR5UcMvM3MFpjZOjP7UcsPfGZ2tpk9\nUHbMPezDucBHgC+F+n4V1o8xs5+Z2atmttjMzo+23SP8uLXOzBYAJT8aFXH3n7v7L4E11eTP2d7d\nfZm7XwL8ELiyIF/u8Xf3P7j7bJK2sYQlkR/vBqa7+8Puvj28fufun4vyXWhmL4Tza4GZfSBad7aZ\n/dnMrgrnySIz+6ewfGk4z86K8t9gZteGH8M2h233MbNvhWP7dzN7SzV1Vzhmhd+7SszsY2b2TKhr\nkZl9qkLeJWZ2Ud65F+X5QvQ9+1i0/AQzeyJ8P5ea2Vfbsp8iIt2au1d8AUuAd5UtO5zkgvONJBfg\nl5Wt3xNYCcwoW94AOLB/tMyApcAXWtmPw4EHgfWh7KuBvtF6Bz4LPA9sAr4OHBi22QjMbskPHA0s\nA74EvBLKOwl4L/AcSQfiy22se2LZ/p4MbAVGhPf3AZ8I6YnAH4ENwGrgtrD8T6Gs14DNJBe6Lft6\nAfAycHPLsrK/0UXAAmAd8COgf1h3NvBA2b552IdzgR3A9lDfr8L6McDPgFeBxcD50bZ7hL/5ulDf\nf8T7UsX5dBlwQ5V5j84rOxz/eW05/tHyTwD3lS17F/A6MK6V/bkQeCGcXwuAD0Trzgb+DFwVzpNF\nwD+F5UvDeXZWlP8G4Frgt+HY/xnYh6Tjuo6k8/uWauqu4jju9L1rJf99wH8Dj4Rz9A5geLT+SOAv\n4XM+BRwdll8ONIXjvhm4Oiz/djgGG4HHgHdUu+/Vtklh+UskF943UNYmhfU3Eb5rrbRJb6jmeAGH\nhWPRAOwPPAN8vuy8nAMMBg4FtgF3AwcAQ8Lf8azoXG8ELgH6AJ8k+f7dQtKeHhqO6wFtqLv8O9En\n1HF8Tpt0K/CfJD8U9gfeXlRWtK9XAv1I2oSj2blN+hvJj3rDSc7vy6LvSm6bFH03LovW1YXz5hKg\nbzh+i4DjwvorgPtDPeNDvbu6TTqG5P/EgdUe/2h5Xpt0Rfmygv05haS9riP5/+I1YHR0nBtJfgip\nD5/zJeCa8Hd7D0l7Mig67qvDudUfuIek/T8z2v7eauquYr/b2iadQPL/uQH/B9gCvDXvb9LKuXd0\nOCaXhr/He0NZw6L1/xA+05uAVcBJtbRT3eF12GGHuYj0LETXx2191fRMobs/QtJReUfB+k3AXUXr\nyxxMckfwZ63kawL+DRgJ/CNwLEknMDaN7GLpS8BMkl+dx5N0YE+P8u5D8h/fWJKLjR8AHw3bvwO4\nxMwOaEPd5e4g+Y/v8Jx1Xwd+T3JHahzw/wDc/Z1h/ZvdfZC73xbt63CSO7XnFtT3EeA4kv84DwL+\nq5X9w91nAj8hudM7yN3fb0lY8K9ILvbHknzWz5vZcWGzr4Q6Dgz1dchzkm30c+Ctlt2JzlPp+Jd7\nF/Cwu7f2bOQLJOfGEOBrwI/NbHS0/gjgaZI7UrcAs0juWkwkObeuNrNBUf5TSf5OI0k6DA8Cj4f3\nt5Pcraq27o52JvBxkou+RuA7AGY2FvgNyQXicOCLwM/MbJS7/yfJxfmMcD7NCGU9CkwJ+W8Bflr+\ny30HWRHqqHV9i5Hh35dbFpjZrHC3ZYuZnQHg7o+5+0Pu3ujuS4Dvk1ywxq50943uPp/kQvX37r7I\n3TeQ/CDwlijvDuByd99Bcu6MBL7t7pvC9vNJLlSrrbtEKHd1wTHYQdK+jPHk7uoDOXlizcBX3H2b\nu79ekOdqd1/qyZ3Wyyltf9vibcAod7/Uk7tli0ja69PC+lNJjttad19KOFd3sRUkHZahRRlaOf7l\nRlJ6/g0P598GM9salflTd1/h7s3h/4vnKW3zFrv7j9y9CbiN5P/CS8Pf7fckPwjGjyv8IpxbW4Ff\nAFvd/aZo+/R8raLuDuPuv3H3F8I1zx9J/v+sdH1R6dzbQXIMdrj7XJIfsA4O9dzn7n8Nn+lpkh9L\nKn6vRER6ivYMNKMLsAp0AdapdAHWiRdgwc3u/jd3fw24GDjVzOpJOrdz3X1u2Je7gHkkv7jncvcf\nu/ua8P35Bsldig55JrbMWJK7/LWub9ESTph2ut39NHcfStJprwcws4PM7Ndm9rKZbQT+P7L2rMWq\nKP16zvv4R4I14W/fsi5v+0FtqLuEmfUhCfHPOwZfIvlOPWJm883s45XKAl4N520lS6P0iyQ/MNRi\nP2BM+E6uN7P1wJeBvcP6MTl17WpjSe58rS/K0MrxL7eG0vNvbTj/DiP5/rSUeaYlz9+3HJc3Unoe\nlJ8/uHulc7Dq87WKujuMmR1vZg9ZEka9nqS9qVRXpXNvjbs3Ru+3kH2vjrBkbINXzWwD8OlW6hER\n6THa0ynUBVgFugDrVLoA68QLsKD8b9wn1LcfcErZ+fF2ouNXLjy/80zoZK8nudvZoftuyeBDY4Hc\nH1jCHdp3kdzJbM3fgeXAv7SS77sh7yR3H0zyPbFq97mdaql7Osld30fKV7j7y+7+SXcfA3wKuNYq\nD3jlVexj/Dz4vmTPzr0GDGhZYWb7tFL2UpIfXIZGrz3dveWHiJU5de1qHwAeDz+iFCk8/jnuJnkm\nc1xRBjPbj+QHuxkkYfJDSX4M7fRzcFfWbWb9SCKJ/i+wd6hrbit1FZ17rbmFJOR7vLsPAb7XSj0i\nIj1GTZ1CXYDpAqysrl1NF2CdX3f537jlzutSkruI8fkx0N1bBvApOZ/M7B0kz8OeSvLczlCS5xQ7\nZN/NbLCZvY/kbv+P3f2vZev7mdlhwC/JnrdtWdefrNPfryWk1d0d+ALwFTP7pJkNs8Qksh9HIHnW\nbyOw2czeQPI8465Sdd3hzvdHSJ4lu9LddxpYxcxOic7/dSR/x5YfzVaRPMfXVueZ2TgzG07SZraE\nwz8FHGpmU8Ix/2rZduX1PQJstGRgmz3MrN7M3mjZKMSzSQZwGRY+w79Ws3Nm1hDqrwfqzay/tWEg\nr3BOjLVkQKtPhM+Yly/3+IfP0Z8kzL0u1N8HIEQW3Av8Mty96hvWHRkVPZDk7/RqKO9jJD8W7Qo1\n1130vaugb8j/KtBoZseTPA9ZSdG515o9gbXuvtXMDgc+XOV2IiLdXps6hboA0wUYugDr6RdgLT5q\nZpPNbADJoAy3hzvrPwbeb2bHtRxTS0aebDmfy8+nPUk6568CDWZ2CcnAK+31KzPbRNJJ/U+S5y8/\nFq3/Uli/lmSAmceAfyr7IeF1kueJIPnRJw3NDiG6p5KEyy4l6RDPJnlO+ach2xdJLho3kXTaq73w\n7AjV1P2UmW0GFpJ8Z/7Nk5Ey87wNeDjknwN8zt0Xh3VfBW605M7wqW3Yx1tInv1aFF6XAbj7cyTn\n1B9IwqDLf1y8Dpgc6vtlOO/eT/Jc6mKSv8UPSe44Q/KM7Yth3e9JBuOqxn+R/M0vJPk7v04Vz2KT\nRFJsJjl3HiUZmOTo0I7EWjv+Z4Q6v0vyfNzrJH/LFv8C/JrkO7c+fL6PkDw7j7svAL5B8izyqrAf\nf67mg7dXO+su/N4V1LUJOJ/k+7eO5Lyf00oduedeFT4LXBrajktCnSIivYO3PurXEpJGexPJL/wP\nAucB9Z6NWLY9rH+N5Fm8K4GhZeV4+ats/TSSETk3k4TzPUEysmXLaG7vJPkPZDPJHchLiUawY+cR\n8h4Azo7eXwb80PNHK8sbgfAB4KNtqLtlxNC1JB2MD5d9vvvIRvr7H5K7o5tJBhA5N8r3aZK7cetJ\nLkpL9rVg/5eQjT66HrgRGBCt/0+yuzwfjY8VMAl4Mmz3y7BsDMkD9i+T/Cf8EGG0R5K7jjeF/FWP\nPkpyYVl+Dny1lW2OJnmecnM4vitIBmA5Mufcau34n51T/w3R+n5hH58necZkGclzqMdFeS4P5a8m\n6YT8Mfqbnl12Tkxk53N8GWFUR3YeYbFkBMKwfWM1dbdyDCt+7wq2uY9s9NGNJAMPjYzWHxHqX0vS\n2fsNsG9Y948kI/iuI3netJ7kIn8jyXn9JQpGD9VLL730au9L7Uv1L40+KtLz0I7RRy3ZXkRERKR7\nM7MlJD+Y/WF370tXN3XqVJ83b97u3g0R6UBm9pi7T61l2/YMNCMiItIlmdm+lkzCnvcqfBbazL5c\nsM1vd+X+d1dm9r2C4/e9VrYr+ltVM7WViIi0k+4USocIF1kLClZPdveXCrb7MvnPB97v7sd31P71\nVOFC66M5q37s7p+usN3mglXHu3s1A0SJiEg3pjuFIj1Pe+4UqlMoIiIi0suoUyjS87SnU1j16I9d\n2bvrTlHPViRyV/NPNbdWF6H2SaSU2icRka5HzxSKiIiIiIj0YuoUioiIiIiI9GLqFIqIiIiIiPRi\n6hSKiIiIiIj0YuoUioiIiIiI9GLqFIqIiIiIiPRi6hSKiIiIiIj0YuoUioiIiIiI9GLqFIqIiIiI\niPRi6hSKiIiIiIj0YuoUioiIiIiI9GLqFIqIiIiIiPRi6hSKiIiIiIj0YuoUioiIiIiI9GLqFIqI\niIiIiPRi6hSKiIiIiIj0YuoUioiIiIiI9GLqFIqIiIiIiPRi6hSKiIiIiIj0YuoUioiIiIiI9GLq\nFIqIiIh0YWY2zcyeNbOFZnZhzvp9zexeM3vCzJ42s/fujv0Uke5LnUIRERGRLsrM6oFrgOOBycDp\nZja5LNt/AbPd/S3AacC1u3YvRaS7U6dQREREpOs6HFjo7ovcfTswC5helseBwSE9BFixC/dPRHoA\ndQpFREREuq6xwNLo/bKwLPZV4KNmtgyYC/xrXkFmdq6ZzTOzea+++mpn7KuIdFPqFIqIiIh0XZaz\nzMvenw7c4O7jgPcCN5vZTtd47j7T3ae6+9RRo0Z1wq6KSHelTqGIiIhI17UMGB+9H8fO4aHnALMB\n3P1BoD8wcpfsTLccggAAIABJREFUnYj0COoUioiIiHRdjwKTzGyCmfUlGUhmTlmel4BjAczsEJJO\noeJDRaRq6hSKiIiIdFHu3gjMAO4EniEZZXS+mV1qZieGbF8APmlmTwG3Ame7e3mIqYhIoYbdvQMi\nIiIiUszd55IMIBMvuyRKLwCO2tX7JSI9h+4UioiIiIiI9GLqFIqIiIiIiPRi6hSKiIiIiIj0YuoU\niki7mNk0M3vWzBaa2YU56/uZ2W1h/cNmtn+07qKw/FkzO661MsPoew+b2fOhzL6V6jCzd5vZY2b2\n1/DvMVFZh4XlC83sO2ZmYflwM7sr1HGXmQ3r+KMmIp3NzPqb2SNm9pSZzTezr4Xlue2IiEhvpk6h\niNTMzOqBa4DjgcnA6WY2uSzbOcA6d58IXAVcGbadTDK0+qHANOBaM6tvpcwrgavcfRKwLpRdWAew\nGni/u/8DcBZwc7Rf3wXOBSaF17Sw/ELg7lDH3eG9iHQ/24Bj3P3NwBRgmpkdSXE7IiLSa6lTKCLt\ncTiw0N0Xuft2YBYwvSzPdODGkL4dODbclZsOzHL3be6+GFgYysstM2xzTCiDUOZJlepw9yfcvWWS\n5/lA/3BXcTQw2N0fDMO231RQVlyHiHQjntgc3vYJL6e4HRER6bU0JYWIAHDcPw/0NWubdlr+2NPb\n5gNbo0Uz3X1mSI8FlkbrlgFHlBWR5nH3RjPbAIwIyx8q23ZsSOeVOQJYH+bsKs9fVMfqqJwPAk+4\n+zYzGxu2z6t7b3dfGcpaaWZ7ISK7TY1tE5BGMzwGTCSJQHiB4nZERKTXUqdQRABYvbaJh+8ct9Py\nPqNf2OruUws2s5xl5RMmF+UpWp4XwVApf6v7YWaHkoSMvaea/CLSddTYNgHg7k3AFDMbCvwCOCQv\nW4fsqIhIN6bwUREBwHF2eNNOr1YsA8ZH78cBK4rymFkDMARYW2HbouWrgaGhjPK6iurAzMaRXAye\n6e4vRPnjq8y4rFUhvJTw7yutHAMR6UQ1tk2lZbivB+4DjqS4HRER6bXUKRQRoOYLr0eBSWE0v74k\nA8fMKcszh2SQF4CTgXvCc3xzgNPCM34TSAZ7eaSozLDNvaEMQpl3VKoj3B34DXCRu/85/axJeOgm\nMzsyPKt4ZkFZcR0ishvU2ik0s1GhDcDM9gDeBTxDcTsiItJrKXxURIAkfmoHzW3bJnl+bwZwJ1AP\nXO/u883sUmCeu88BrgNuNrOFJHfvTgvbzjez2cACoBE4L4R6kVdmqPICYJaZXQY8EcqmqA5gBsmz\nRBeb2cVh2Xvc/RXgM8ANwB7Ab8ML4ApgtpmdA7wEnNKmgyIiHaqWtikYDdwYniusA2a7+6/NbAH5\n7YiISK+lTqGIAOHCy9t+4eXuc4G5ZcsuidJbKehYufvlwOXVlBmWLyIZnbR8eW4d7n4ZcFlB3fOA\nN+YsXwMcm7eNiOx67WibngbekrM8tx0REenN1CkUESCEaGm8BRHpYtQ2iYh0PnUKRQQAd9ih6y4R\n6WLUNomIdD51CkUEAMfY4XkzNYiI7D5qm0REOp86hSICJM/tbNeAxCLSxahtEhHpfOoUigjQMpiD\nLrxEpGtR2yQi0vnUKRQRoCVEq35374aISAm1TSIinU+dQhEBkguv7brwEpEuRm2TiEjnUzyGiAAt\nE0TX7/RqjZlNM7NnzWyhmV2Ys76fmd0W1j9sZvtH6y4Ky581s+NaK9PMJoQyng9l9q1Uh5mNMLN7\nzWyzmV0dlbOnmT0ZvVab2bfCurPN7NVo3SfafjRFpKPU2jaJiEj11CkUEQCa3djqfXZ6VWJm9cA1\nwPHAZOB0M5tclu0cYJ27TwSuAq4M204GTgMOBaYB15pZfStlXglc5e6TgHWh7MI6gK3AxcAX4x1y\n903uPqXlBbwI/DzKclu0/ocVD4KIdKpa2iYREWkbdQpFBGh5bqdhp1crDgcWuvsid98OzAKml+WZ\nDtwY0rcDx5qZheWz3H2buy8GFobycssM2xwTyiCUeVKlOtz9NXd/gKRzmMvMJgF7Afe39mFFZNer\nsW0SEZE2UKdQRIDsuZ3yFzDSzOZFr3OjzcYCS6P3y8Iy8vK4eyOwARhRYdui5SOA9aGM8rqK6qjG\n6SR3BuPpsT9oZk+b2e1mNr7KckSkE1Rom0REpIPopzYRAVqGfc9tEla7+9SCzfJmlPYq8xQtz/ux\nqlL+avejyGnAGdH7XwG3uvs2M/s0yR3IY6osS0Q6WIW2SUREOojuFIoIkA37Xv5qxTIgvpM2DlhR\nlMfMGoAhwNoK2xYtXw0MDWWU11VUR0Vm9magwd0fa1nm7mvcfVt4+wPgsNbKEZHOU2PbhJmNDwNN\nPWNm883sc2H5V81seTSY1Hs7/UOIiHRx6hSKCADuNV14PQpMCqOC9iW56zanLM8c4KyQPhm4J4Rq\nzgFOCyOHTgAmAY8UlRm2uTeUQSjzjlbqaM3pwK3xAjMbHb09EXiminJEpJPU2DYBNAJfcPdDgCOB\n86JBq66KBpOa21n7LiLSXSgeQ0SAJERrextDtNy90cxmAHcC9cD17j7fzC4F5rn7HOA64GYzW0hy\n9+60sO18M5sNLCC5eDvP3ZsA8soMVV4AzDKzy4AnQtkU1RHKWgIMBvqa2UnAe9x9QVh9KlB+l+B8\nMzsx7NNa4Ow2HRQR6VC1tE0A7r4SWBnSm8zsGXZ+5llERFCnUESClhCtNm+X/Mo+t2zZJVF6K3BK\nwbaXA5dXU2ZYvohkdNLy5ZXq2L/Cvh+Qs+wi4KKibURk16rQNo00s3nR+5nuPjMvY5i79C3Aw8BR\nwAwzOxOYR3I3cV2H7rSISDejTqGIALV3CkVEOlOFtqnSIFgpMxsE/Az4vLtvNLPvAl8nuQn5deAb\nwMc7cJdFRLoddQpFBGgZ4U+dQhHpWtrTNplZH5IO4U/c/ecA7r4qWv8D4NcdsJsiIt2aOoUiAoTB\nHJrVJIhI11Jr22RmRvK88TPu/s1o+ejwvCHAB4C/dciOioh0Y7oCFBFA4aMi0jW1o206imQO0r+a\n2ZNh2ZeB081sCslNyCXApzpiP0VEujN1CkUEUPioiHRNtbZN7v4AYDmrNAWFiEgZdQpFBEh+jW9U\np1BEuhi1TSIinU+T14sIAM1ubGtq2OnVGjObZmbPmtlCM7swZ30/M7strH84DA3fsu6isPxZMzuu\ntTLDhPYPm9nzocy+leowsxFmdq+ZbTazq8v2675Qx5PhtVdr+ysiu16tbZOIiFRPnUIRAVpCtOp2\nelViZvXANcDxwGSSZ3Uml2U7B1jn7hOBq4Arw7aTSSaZPxSYBlxrZvWtlHklcJW7TwLWhbIL6wC2\nAhcDXyz4CB9x9ynh9UorZYnIblBL2yQiIm2jVlVEgiREq/zVisOBhe6+yN23A7OA6WV5pgM3hvTt\nwLFhVMDpwCx33+bui4GFobzcMsM2x4QyCGWeVKkOd38tPFe0tQ0Homh/RWS3qKltEhGRNlCnUEQA\ncIcdzfU7vYCRZjYvep0bbTYWWBq9XxaWkZfH3RuBDcCICtsWLR8BrA9llNdVVEdrfhRCRy+OOn61\nliUinaBC2yQiIh1EQfk9UP3I6PrVon5/Xes3O0puiETpxpUvd8SuSReWDOaQ+zvRanefWrBZ3knl\nVeYpWp63E5XyV7sf5T7i7svNbE+Sya3PAG6qsSyp0pFP7UjTf90wJk1v2L5Hmt7WmP3X1FDXnKZX\nbx6Yprdvy/JMOP2pDt9P6ToqtE0iItJB1MqKCJD0ehqb63d6tWIZMD56Pw5YUZTHzBqAIcDaCtsW\nLV8NDA1llNdVVEfx53VfHv7dBNxCErZaU1ki0nlqbJtERKQN1CkUEQDck1/jy1+teBSYFEYF7Usy\ncMycsjxzgLNC+mTgHnf3sPy0MNrnBGAS8EhRmWGbe0MZhDLvaKWOXGbWYGYjQ7oP8D7gb7WUJSKd\nq8a2qUdpbZTnkOdUM1tgZvPN7JZdvY8i0r0pfLSLqx82LHvjzaUrrYr/FONtmgryROXE/89affZL\nbMN+0Y2bOKx0yUut74N0C8mv8W270HL3RjObAdwJ1APXu/t8M7sUmOfuc4DrgJvNbCHJHbfTwrbz\nzWw2sABoBM5z9yaAvDJDlRcAs8zsMuCJUDZFdYSylgCDgb5mdhLwHuBF4M7QIawH/gD8oLWypNRn\nnl+Ypk8auLlk3WPbtqfpJTtGpum/bJqYpt86NHt09OVtQ3LrWL8jCytt9qztWbYpaxsXfuvING2N\naZIDv/hQxf2X7qGWtqkniUZkfjdJJMOjZjbH3RdEeSYBFwFHufu6lil2RESqpU6hiADhuZ0aLrzc\nfS4wt2zZJVF6K3BKwbaXA5dXU2ZYvogszDNeXqmO/Qt2/bCC/IVliciuV2vb1IOkIzIDmFnLKM8L\nojyfBK5x93UA0RQ7IiJV6dWtrIhEnF4foiUiXZDapmpGeT4IOMjM/mxmD5nZtF22dyLSI+hOYRdR\nPzQ/dGqnkNFq1jUWLI/DTeNtC8JQvTGKw6rLQkmtPstfv3cWodK0Sj9Mdme9PURLit254slW8zyz\nfUvJ+8P6DYjSG9P0Bwc9nrv909uzqSTf1Ld/7vL6aBDYe8a9IU3fvy4LSX1+zag0vfpXB6Xpke9/\nrvIHkC5LbVNVIyI3kDyXfTTJIFz3m9kb3X19SUHJlELnAuy7774dv6ci0m316lZWRDKO0dRct9NL\nRGR3qrVtMrPxZnavmT0TBl/5XFg+3MzuMrPnw7/DWitrN6t2lOc73H2Huy8GniXpJJZw95nuPtXd\np44aNap8tYj0YrriExEgmSC6l4doiUgX1I62qRH4grsfAhwJnGdmk4ELgbvdfRJwd3jflVUzyvMv\ngX8GCCMrHwQs2qV7KSLdmsJHd4GKI4i2KArtbK4wEn4Vk9GXKAoZrSKUtKSYHdnk0zS0/RRqGJtN\nWE1TNCRqNKopfftEeZpz8zeufLnNdUslpjuDvdDPlmUjdA6q65+b56Gt2ffuyP7588Md0ndAyfvN\nzVnYZ1zu4h3ZKKUT+gxK0wdETckj23ZEy7O6/7BlXJpuiiLq6ixrJz9z0J/S9I+W/GPuvlay/OeH\npumhA15P09ubss+9evHwbINBWZh9Q78sPeH0p9pctxSprW1y95XAypDeZGbPkDyLN50kzBLgRuA+\nkpGNu6QqR3m+E3iPmS0gGWv8P9x9ze7baxHpbtQpFBEg/BrfpE6hiHQtFdqmkWY2L3o/091n5mU0\ns/2BtwAPA3uHDiPuvrI7TN9QxSjPDvx7eImItJk6hSICJKMWNClcVES6mApt02p3n9ra9mY2CPgZ\n8Hl332jWxigbEZFeQJ3CTlJVyGis2pDRWJyvraGkcf6iSe1L9qMgU5SnYfQ+JauKwjt9exR+2lxQ\nbhyiGovCW+tHjsiW10ejo1YIaW1cXv5svmSMpua2XyyFoc+/TRLW9EN3v6JsfT/gJpJ5AdcAH3L3\nJWHdRcA5JCfY+e5+Z6UyzWwCMAsYDjwOnOHu24vqMLMRwO3A24Ab3H1GKGcA8FPgwFD3r9z9wrDu\nbOB/geXhI1zt7j9s84HpwkpHE80PGY2NaXg9ejeoMF+sKBQ1DhmN1UWPuC/Ylo22P74+eyxqVEM2\nimmdZW3mUUNfyC1zv8Hr0vRTP/2HknX7nvLX3G1OnJAtf9OAbBaArZ6FtK8Yn7Xva3YMTNOrtg1O\n08PnZfn/ui4LmX9x+cg07VtLQ3EP+vQjufsktbVNAGbWh6RD+BN3/3lYvMrMRoe7hKMBDZ0tIr2e\nbguICJCEaDU31+30qsTM6oFrgOOBycDpYSCH2DnAOnefCFwFXBm2nUwyYMKhwDTgWjOrb6XMK4Gr\nwgAR60LZhXUAW4GLgS/m7P7/dfc3kISUHWVmx0frbnP3KeHVozqEIt1NLW0TgCW3BK8DnnH3b0ar\n5gBnhfRZwB0dvtMiIt2MOoUikmpqtp1erTgcWOjui9x9O8ldvOlleaaTDOYAyV2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ho7E/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\nonEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56364f3c10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitted_parameters = axcaliber_gamma_fit.fitted_parameters\n",
    "\n",
    "fig, axs = plt.subplots(2, 3, figsize=[15, 10])\n",
    "axs = axs.ravel()\n",
    "\n",
    "counter = 0\n",
    "for name, values in fitted_parameters.items():\n",
    "    cf = axs[counter].imshow(values.squeeze().T, origin=True, interpolation='nearest')\n",
    "    axs[counter].set_title(name)\n",
    "    axs[counter].set_axis_off()\n",
    "    fig.colorbar(cf, ax=axs[counter], shrink=0.5)\n",
    "    counter += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that the maps for alpha and beta are not super smooth. This could be because we're actually fitting two signals experiencing different restriction levels at the same time, but hard to say without fitting each signal separately. We can visualize the distributions themselves as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Fb/o0Z2iXRP4xYx3pe464HceYE+bPw2hDgQxVzVLVAuAjYCAQ7xxWA2gB7HDubwNaAjjP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\ni60FmqnxkpMa8OCF3fhhfRb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zuqr2wTOK7HgROcvtQC6KAPoAL6lqbyAHsCHcAeeQ4oXA\n+25nqSpWbPzAORQwGxjuchQ3nQ5cKCKZeEZKHSwib7kbyX2qusO53YPnWHx/dxO5ahuwzesIwAd4\nio/x/BhZoqq73Q5SVazYVBERSRCReOd+LDAUWOtuKveo6n2q2kJVk/AcDpipqte4HMtVIlJbROJK\n7gPnAavcTeUeVd0FbBWRTs6sIcAaFyMFkqsIoUNoYK3RqlJTYJrTgiQMeE9Vrbmv8dYY+FhEwPN/\n721V/drdSK67FfiPc9hoEzDW5TyuE5FawLnATW5nqUrWXY0xxhi/s8Noxhhj/M6KjTHGGL+zYmOM\nMcbvrNgYY4zxOys2xhhj/M6KjTHGGL+zYmOMMcbvrNiYGkVEjnjdn1/J1z4oIn+uwiw/r6+yWU5g\nW/EicvNJriNJRI46nc1WRaZYZ8yWfBFpVBXrNIHLio2psVR1oL/WLR4+///yZxZHPFCpYlPGe9jo\ndDZ70lT1qLOuHVWxPhPYrNiYoCciY0RkhTNK6psi8oiITPB6/jERua2U1x1xfq2nichrzgir3zh9\n25Usc7+IrBOR74BOXvOvcUZmXSYirzjDS5Ss60VgCdCylG2WtT7vPa5PnCEIVpcMQ+Cse63TDf8q\nEfmPiAwVkXkiskFE+nu9/lfZgCeAds68J0/mPRz3fmaX9G0mIg2dbD5nNTWIqtpkU9BOQDdgHdDI\nedwASMLTYy54flBtBBo6j494vfaIs2whcIoz7z3gGud+X2AlntEj6wLpwJ+BLsBnQKSz3IvAGGdd\nxcBpZWQtdX2l5Grg3Mbi6aizoVfOHs57SgUmAwKMBj5xXlNetlVe26j0ezh+Hc68bUCYc38Qns4j\nfcrqtY7Mku/PptCdrCNOE+wGAx+oM8yyqu4H9ovIPhHpjafzy6Wquq+cdWSoasl5iFQ8fywBzgQ+\nVtVcABGZ7swfgqdwLHY61YzFM2Dej8BmLXso8LLWd7zbRORi535LoAOwy8m50nntauB7VVURWemV\nubxs3k70PfxMRFoD21W1ZHC8nsAK574vWU0NYsXGBDuh9OG3XweuB5rg+VVdnjyv+0V4/vCWKG3d\nAkxT1ft+MVMkCc8AYOUpt+dbETkHz/AUA1Q1V0RmAzGl5Cz2elzM//4vl5etqt5DiVP4X3EBT/F6\ntxJZTQ1i52xMsPseuFxEGgKISANn/sd4Bq/rB8w4wXX/CFzstJqKA0Z5bfNSEUks2abzK/9E1+et\nHnDAKTSdgdMqmbmsbNlAnA/LVUYvnEIoIh3wHCJbWcl1mBrCfmGYoKaqq0XkMeAHESkClgLXq2q+\niMwCDqpq0Qmue4mIvAssAzYDc5z5a0TkAeAbp7VWATAez6GuSq/vOF8DfxCRFXjORVV4OOu4bZSa\nTVV/ck7QrwK+UtW7TuQ9HOcU4KiILMezh5MGXAe8WZnMpmaw8WxMSHL+gC4BLlPVDW7nCQXOIbbP\nVbW78zgd6K2q2Se53kwgueS8mwlNdhjNhBwR6Yqnpdf3VmiqVBFQz2kqHQcUn0yhcQ4nLgMi8ZzL\nMSHM9myMMcb4ne3ZGGOM8TsrNsYYY/zOio0xxhi/s2JjjDHG76zYGGOM8TsrNsYYY/zOio0xxhi/\n+38NaIvHJRX6NQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5634a443d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "axcaliber_alpha = axcaliber_gamma_fit.fitted_parameters['DD1GammaDistributed_1_DD1Gamma_1_alpha']\n",
    "axcaliber_beta = axcaliber_gamma_fit.fitted_parameters['DD1GammaDistributed_1_DD1Gamma_1_beta']\n",
    "\n",
    "from dmipy.distributions.distributions import DD1Gamma\n",
    "gamma = DD1Gamma()\n",
    "\n",
    "x = 15 # some x-pos in the data\n",
    "y = 25 # some y-pos in the data\n",
    "\n",
    "alpha = axcaliber_alpha[x, y, 0]\n",
    "beta = axcaliber_beta[x, y, 0]\n",
    "\n",
    "radii, Pgamma = gamma(alpha=alpha, beta=beta)\n",
    "plt.plot(2 * radii * 1e6, Pgamma)\n",
    "plt.xlabel('cylinder diameter [$\\mu$m]')\n",
    "plt.ylabel('Gamma probability density')\n",
    "plt.title('Estimated Gamma distribution');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison between estimated and histology axon diameter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean axon diameter can be estimated from the axon diameter distribution as diameter = 2$\\alpha\\beta$. We compare the histological axon diameter with the estimated ones:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean_diameter = 2 * axcaliber_alpha * axcaliber_beta * 1e6  # in microns\n",
    "mean_diameter_histology = data_spinal_cord.histology.h1_axonEquivDiameter  # was already in microns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f56346bea10>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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D6/uLAN6oqkOqOoCgA+9vw2vrDARf7lchSBetQ9ChP+nH1UUIPsObANyAYADIzeFjnwSw\nMTzGLQhiyHBs/+8i+JzVEreeDq//Sj6M4LNwd/g5ugVB6w8Q9NnrRBBD70aQKqtZWKF7OYJ+MTZu\nPRAe860A/gZBK/s/hT8y3w7g7SJylqqOAHgtgs/3DgQdyy9R1cfrOZ9Qj4j0I+h/dAGAC1X12wnb\nfgjBD7Y+BJWYH9T7pFXEocsBfDS8tj4UVpz/FMEPy+0IWob+HjOrjjAtxjuEERFRExKRv0RQ+Xqp\nue9gBKmZA1S1N7WTI5pmua/lERGRIyIHisiLwnT6UQhabG8wjxcA/B2C4d+sAFGusRJERB4RmSci\nPxKRxyWYTO+FaZ8TNVQbglGlfQjmy/kJgtQPwk7ZvQjmiZlK3xyi1NQSw5gOIyKPiHwXwB2q+k0J\nZqCdFU6HQEQ049USw1gJIqKIBMugPARgVXx0IhHRTFdrDOO6RUQ5cN7LunTnrtLkGwJ44OHhRxGM\nLBp3hapeEZZXIRgd8h0ROQnBrLTvT5iPiYioIaqNYZPEL6DGGLZfK0HnFi7kL0uiKtxc/mFNk6Tt\n3FXCvTdVNx9n8cAnh1T1tISHWxBMs/DXqnqPiHwRwD8A+KdaziePGL+IqlNr/AKqj2GTxC+gxhjG\njtFEOaAAylX+N4mNCOZ/uie8/SMEAYWIaNpUG8OqUFMMYzqMKAcUilGtLh024XFUt4jIBhE5SlXX\nIJh87rEpH5iIaAJpxTBWgohyospfSdX4awBXh6Mq1iKYVZeIaFqlEcNYCSLKAYWi1KDBXKr6IICJ\ncu5ERA2VVgxjJYgoBxTAaON+RRER7VdpxTBWgohyogwOXiKi7EojhrESRJQDCjSsKZmIaH9LK4ax\nEkSUE0yGEVGWpRHDWAkiygFVxQhbgogoo9KKYawEEeVAMNEYEVE2pRXDWAkiygVBCTXPVE9ENEOk\nE8NYCSLKAQVQZjaMiDIqrRjGShBRDiiAES4FSEQZlVYMYyWIKCfKynQYEWVXGjGMlSCiHFCAfYKI\nKLPSimGsBBHlgEJQYjqMiDIqrRjGShBRDiiAUWUliIiyKa0YxkoQUS4ISqwEEVFmpRPDWAkiyoFg\nojFWgogom9KKYawEEeUEO0YTUZaxYzQR1UVVMKrFtE+DiKguacUwVoKIciAYXsp0GBFlU1oxjJUg\nolxgx2giyjJ2jCaiOrFjNBFlGTtGE1HdFIIR9gkiooxKK4axEkSUE2Wmw4gow9KIYawEEeUAO0YT\nUZaxYzQR1U0hKHEVeSLKqLRiGCtBRDmgCowqP85ElE1pxTBGTaJcEJQbNNuqiKwH0AegBGBMVU9r\nyIGJiBKlE8NYCSLKAQUaPcfGy1R1RyMPSESUJK0YxkoQUU6wYzQRZRk7RhNRXRQ1rbuzSETuN7ev\nUNUrvMMBvxIRBfD12GNERA1XQwybLH4Fh6syhrESRJQDiprm2NgxST+fF6nqJhFZAuBmEXlcVW+f\n8kkSESWoIYZNFr+AGmIY28+JckFQqvLfZFR1U/j/bQBuAPD8aT55Imp6jYlfQG0xjJUgohwY/xVV\nzb+JiEiXiHSPlwH8CYBHpv8VEFEzqzaGTabWGMZ0GFEOqNbUJ2giSwHcICJAEB/+S1V/2YgDExEl\nSSuGsRJElBONGF6qqmsBnDT1syEiqk0aMYyVIKIcUKBhE40REe1vacUwVoKIckEaPdEYEdF+lE4M\nYyWIKAcUaFQ+nYhov0srhrESRJQDCkGZq8gTUUalFcNYCSLKiTJnvCCiDEsjhrESRJQDqkCJLUFE\nlFFpxTBWgohyQCEYK7NPEBFlU1oxjJUgopyodkp5IqKZKI0YxkoQUQ4EU86zEkRE2ZRWDGMliCgX\nBGMcIk9EmZVODGMliCgH2DGaiLKMHaOJaEqqWWGZiGimSiOGsRJElAOcLJGIsoyTJRJR3RTAGFuC\niCij0ophrAQR5QTTYUSUZUyHEVF9lOkwIsqwlGIYK0FEOaAAypwskYgyKq0YxkoQUQ4ogLEy02FE\nlE1pxTBWgohygukwIsoypsOIqC4cIk9EWcYh8kQ0JewTRERZxj5BRFQXVfYJIqLsSiuGsRJElBNM\nhxFRljEdRkR1YZ8gIsoy9gkioilRVoKIKMPSiGGsBBHlgGpj190RkSKA+wE8p6qvbtiBiYgqaGQM\nqyV+sRJElBMN/hX1fgCrAcxp5EGJiJI0MIZVHb84nIQoF4J8ejX/Jj2SyAoArwLwzWk/bSIiANXG\nsEmPUmP8YksQUU7U8CtqkYjcb25foapXmNtfAHApgO5GnRsR0WSqjGENjV+sBBHlgCpQKlddCdqh\nqqdVekBEXg1gm6o+ICJnN+r8iIgmUkMMa2j8YiWIKCcaNNvqiwC8VkQuANABYI6IfF9V39KIgxMR\nJWlADKs5frESNAP81ZNPROWilF0ZGpVbZSxx/1F1f8aSuYi+dPjRjTpFmuEUjelUqKqXAbgMAMJf\nUh9iBYgmUjzysKhc7uqIyoURE7OGR6KiDA57++vQUFQu7dptHlBQ82hEDKsnfrESRJQLnCyRiLKM\nkyUS0RSUq+8TVBVVvQ3AbQ09KBFRgkbGsGrjFytBDfa3T62OyiNajMo2zQUAJTMpVFIKzLIprzib\nArPHtWm2NilF5X8//JjEY1E2qXLGaJq64vz5UXn3+UdF5fgcdmLC1K5j3HU3dsiQ2arN7V/ucuVS\n7GAmNB78E/fY7Ee2un12ujRZqbc38fwpu9KKYawEEeUE02FElGVMhxFR3diPlIiyLI0YxkpQnS57\n+uGo3Ft2IyJ6SrMqbl+IpcOsLnGjJZJSWxMpm4m/k/YZ0tao/PrVW6LydcccUNVz0MymEJTLnACe\nqiOnHheVN547NyqPznbfQiNL3OguaXfp9H0PVrHopzZMWVpisdB88W240Dx24cKo2P7U8qh86A+2\nReXSmqeSz4syJa0YxkoQUU6wIYiIsiyNGMZKEFEesGM0EWUZO0bPDNdu+F1UfmhktveYTXs9O7og\nKhfNUIn+cnvF47bFJjvskNFJ90naPj5SzKbQ7CiwpNTYRBMvJvnWs3dG5WFTXR+JPcf2sksHjprR\ncTYdx0kcpwmbgppecZ5LbaHsXxCDZ7rRXhte7mJIucPFDC2afUouruhg7KtCK5e97zCbJrPHao2l\nw8xzild225WO3RuVV/+dG8F25F+gKtLuYqy0uVFr0jLBqNs9ZhSamnNm57vpwz5BRFSvRs8TRES0\nP6URw1gJIsqBRi2bQUSUhrRiGCtBAG7a9GBUfmDYvSVbxuZW2hwAMKSuSbUDbl0cmwJqleQRFfYx\nu49VMqO+/PRZm7edTccNlVsxmY6CO5Yd5QYAlx924qT795t03GgsHVY0M5/1mNSYHcFmJ3G0abKB\nWFpwxDzP9ccsmfS8mpoilougZlE89sio/Nx5i6Ly3oP8tJOd4FALJu006q6bwnDCUK/4L3Szvw1f\n2qIVyxgzo8NiI4C8fUyqTMy3U4sZUSbz3GhaO7kjAJR270YlcvSqqLzjefOi8sAB/usaXuDOZdFD\nrlxqddt19Lhz6X5sp9vmyXX+k5YnGFFH+0ophrESRJQT7KpARFnGeYKIqE4CZZ8gIsqsdGIYK0FE\necGWICLKMrYEpWOg7Pr0rB91OfXtY3O87bqLgxX3t/1dyraPjOn3E+8f5M0Mbfa3w+W7Ci73bfvO\n2OcLntMcN2FYvF2k1R53QXHA2+5f198dlRcX3FD6HpPHt/2A+sy0AQDQr35/pUrnVUp4v+LnbvtK\nXfT4pqi8faw7Kt9yfDcInCeoiT13rukHtNL0nYl3STFxwk5gXzbfApIw9H2fCe/NtaZSuX+R7Xdk\nD+wNwwf8vkcmBLS0uhewqLs/Kre3mCk+Frr+PQCw+7Vu+o0WM5fH8Fz3JLvPNH2KYsP11Qzl37bU\nznhtiqa1onCWe+/nP7bYO9aS293M1vrsc1G5PDQEqoDzBBHRlLAliIiyjC1BRFQ3tgQRUZaxJWj/\nscPiHx5xTaI7S26W6Piip32lzqjcboaZ22HpQ2ZYdzvcNnboeHwfOwO03c6WJ0obWTbtZVNw9lgL\nC65puTV2Xna4/ai5f8Cco02B2TRd/NziM1u7+yvPJB1n03b2uBNNPdDU2BLUNHovOiMqDx6QMCw9\n1snUGyIvlR9QsUPZq/tCssctt7obhRH3mS0OmvR/p3+hltvtbMyuWDDptHkdrivCEbNdmumPS/0p\nPfoONUPZT3HD5fsHXZp+bqfr/tDb52I6AJTHTGxN+EIWOz3AInesXS/xt9t5qlsAdtlvXKps7q1P\nRuXSjp0ggy1BRFQXzhNERFnGeYKIaCo03nmViChD0ohhTVUJuvG5+6KyXQR0w5iZQdTMxlyOpZ1m\nmfSMlTTayaag7CzNANA/5kaB2ZmSk0agWfFj2eex6SV7/zwzCmxBcchs789W3WUWVy2Z96in7JqN\n+0x5ohFd8XTiZEqxUW+2adQ+ZtNhr3y0JyrvGXMzVP/upMqj1HKNLUG5tv5TL4zKoytdLFKTwpF+\n83mOXQ5JMzvbj516A7qSU2s2iy7eE7l9uja4A6/4mUth9ZyyCNaWs8z+ZuRYa6uLRcNjdpZ690Lk\nkzu8Y7X1udGi82a5WLpynkuNbeg1KwHE0y82HVZKGB1mX65d8LXNT9MX57g4vf1k14WgvefQqNzx\ngJmVepeZ7bpZZz5lSxAR1UuaNG4SUT6kEcNYCSLKAwU7RhNRdqUUw5qqEtQuLlW0o+RGSNlJEYvm\nrzBRMmc4YaFSO2rMpq3iaaOkUVHdBZeqsgulXn30iqj89jXPePvYVFEBlUeHLS72mXNJbnLsMKND\n1o65Jlw7iWN/bKFTy0uHmQRvfILHcXaUXDzNl7SdTfPtKbkUWHOPGpN9UxaUK2NdLja1dbjPysiQ\n+2xom03hxNPLZiLDVi/v5Yo2tW/XUo0dyma6xaSNFt3vNlz8q7Xu3DdvicrFY92oKQBQszhqwZRL\nJXeso+ZujcqdRffaV3S5dHj8dtmk6db1uufsH3TxqzwaW7y6XLlsX6OXPrSvo9//Oi21mfi3wqUv\nnznfxfVFBxzlyndujspja9ej+aQTw5qqEkSUa2wJIqIsY0sQEdWNlSAiyjJWgvafvnLld3ui0U02\nhVVNOsymnfrUX2PLjmRa0LK34vPbFJj1xu7d3u3r9prRDuZP2lEYQSXD5jkWFf0UVJ95yUnrlbWa\nEWRtsRSUTZX5o9aSJ3hMkjQppE3/zSq6Zmb7NznjoeTU2t0nJU/QmFkNmmNDRDoA3A6gHcHF9CNV\n/diUD0xT1jLg/r7FolkjLGldrlimBwkxDyZt4y19aCY71HiP1bHKa4ctvnWj28SkwKzuR/0RXXMO\nXhqV+0518aStxZXtaFqb9p7X6q99aO0a7YrKA6PuMz82Zt6YMf8zI97osMRDm+3N/qXY58/ctiP4\ndI6LnztOdvFaCwdG5UV7ev1D7dw1+clkXUoxrGkrQUR5U+OMBEmGAZyjqntFpBXAnSLyC1W9e7Id\niYimIo0YxkoQEUVUVQGMN022hv+YaCOiTKg1htWeoyCiGUm0un8AFonI/ebfu73jiBRF5EEA2wDc\nrKr3pPByiKjJNCJ+AbXFsKZtCdpj+o+MaOXZSAuxKVdHy5W3s2w/IjsTdHxI/LB5Tr9P0OR/kvOW\nnezd/qsnn4jKbd6iqWY2UvNaOrxtfP3m+e052/45HTJacZtgO7NQojl60ntsZ9guxGZJLZtj2X4A\n1bz37abfEuC/37lVfT59h6qelngY1RKAk0VkHoAbROR4VX2kEadI9WvrcX9fmzUomH5A9jPj9Q8C\nALNQabGzcoeXkhmirGahUInFwn2OPX7/nK6K93vP8cTT3u3l5nO/5nTXv7FQMAtbD7vjdrW4foDt\nBf9zvmvEbbd5wE190tvv+mTaRVJlyG8HWPCwecy8Rb2rXHl0jnlf7B8i9pbIqHkvbbnVlNvdTruP\ncfcXxo70jjX/hj+68+/vR25VF8MmjF9AbTGMLUFEeaAIvhmr+VftIVV7ANwG4PyGnisRUVy1MayW\nQ1YRw1gJIsqJGtJhyccQWRz+eoKIdAJ4BYDHp//siajZTTV+AbXHsCbIEVTWqy5VZYdW2yHuSWmX\n+GNeqsakzPrgmmDtkPj4PlNlh6/bmZXt8HGbtrKLpPaU/Xrw9pJrTh4xr9Gm0/68yw1L9Yfn++k4\nO5R9r5l92r52+34XY9X8oh2svJunAAAZHElEQVR9ao5V9FdvjNg03bOj/qy0BfPpuWnTg1E5nlrM\ntMZ0Xz4QwHdFpIjgR9J1qvqzhhyZpmTWVvcH3ra7s/JGSbMcA5AhF5tKJiVUmG0+gx3m82sXDY2n\nKcyxj/mim7Kj/OS6yuc1kV7XHaBQcCmsgnnKTXvd/Y/e43JT8bTcYSe7Ifrb+10sG+518b5tq4uF\n3ev9U1l8/56oXG5z8a9/mVuY1abD7Gdun/c7IVVm77dTEpRtauwo/1jzDzvI7b/Gvcc6XHlR78xK\nIYY1bSWIKHcaEEBU9WEAp0z9SERENUohhrESRJQDooBw7TAiyqi0YlhTVYL8RVPd7Jx2BmSYUUTl\nWLV0wBvVZEZqmEVHd5u012yTjuod82eMXtjqzsWOCPveUQehVkPeSDd3jqNmdFbZpL3miDkv9RdD\nTVoc1aaarNfP3uPdvrHfvf4es7ipTXt56UdUXnAW8EeaDZUrN/97I81Mymx+qz+Cwo5C+9ddh1U8\nVuZxNp9ca+91qSoZNql6m52Z5bbR2GjLwpD7PLX0uv21zxzLpI1b7BdSlR1SdWxs8o1iSlu3ReUj\nLzWLwZqRZuV2t+jonLkufu08PjYT/zHu9uCw22feg668+AEXG1qf3e7tXzYzMxfnuhTcgjUulm1e\naEZxjUzwpZ30UNL99u8Ym9R+ZLF7L9qfda+xxHTYlDVVJYgoz6rpNEhENFOlEcNYCSLKC1aCiCjL\nWAmaXmvHXJNo0XTRn1VwTYoD3gKi/tuzt1Q5VTRaqpwms9vbBQABYElbn9t/glFolbx9zTOJj8VT\nSuPs6K5+09Y6lLAQbFyXeY9+PuCaY790+NGJ+7zzCTeKwZsE0oyIaDOpyPjosKEqRvDZNJ23sKr4\ni8faY28ddSPaTvy9e18efl6GaxHasHV3aIZq6TeproKLGd6oJLugZ8G/nsut7rYdE2r3txP8iTfy\nyT8XGwpL3X5KalLi54MKs0yq6Suzo/LpBzwble1kiQ886kaHLfu1f2KtX54flYdXuZhx4M0u5VZe\nvyEqj02QTip2uhR8S7/7cBVGzKKnLTaHNUFqzPwtksK9fY/LLf7fbv2r3GuZf8ixUXnprZui8ti6\n5O+FTEgphjVVJYgo1zJchyMiYksQEdWNfYKIKMvYJ2ia2bRTd2EwKnsjquwaV2X/7bGT/A2bx+xE\nfDZtY9eyKsT+utVMlmgn9bu2zzXzTrSvTfPZ9b7syCk7AmwgNjrM7mNHzb3crDV03rITEp/fpsDs\nyLFv7XFNy/G0V/TcsQnM7d/Lpu1mF4cqHsumxkZiqcw9JfP85j2yaw25hYeJZp6WfjPyqmBn2TMp\nrGF3v8ZSKl66xo78SvjiEZtai8UvM/AV5XYTC+35HnhAVB46drnbZsT//I/8sxuR9ZIFbl0xG+fs\nSNsVp/dE5R0nuvQZANx1t0vPH/0fz0Xl0gZXnmgEm03N6Uo3gnjr6WbUWkvZlO3e/nvkZccKld9k\nL5VpN5kgszY6x6zPuNBN4og65qmkJqsEEeUW+wQRUZaxTxARTQnTYUSUZUyHTa+ieYdtU6u936Zk\nWgt+s2mrafu029kRYUkpsPbYsQ5sdevtDGkbalGKtZXaVJEdHTZUdqM2bDpsxIwsKcauOnvskhlF\n9uN+v9m5VjYFtcdMomj/DvE0n01N2r+FlwJLWOutHBupYSdLtNt1teRosjFWgnKtOOiu9VmL3Odh\nYJtL6doZdyday8rLbmnl+72PoyQfq9xm1iEz24wdtDgqt390c1QuxdYrnN/qPoObBt3IzbFy5fW9\n57e5rgxzWoe8x4oHuse006X6q53EsTzkzqVltxvBi2A9zuBY5lvTSznGUljeumb2jU1KRdrF0uLH\nstlP+61dytmHnpUgIqqHgB2jiSi70ophrAQR5QH7BBFRlrFPEBFNCVuCiCjL2BI0vT626tSo/I9r\n3fBzOxS8w8w0vBf+TKi2z0pJXJJ2WCsPl7cWmxmiq2WHxXvDx2NPUTTP2WbOsUe7UEmh7KrbbbF+\nOF6fKPO+2H5Hb358Y1S++ugV3v4DZvj9dXtdft8OWU+aIbuv5L/fdjvvvTfnaM/Lbj8QWwjW298k\n2Nf3L4zKN236ZVQ+b9nJFc9xRmMlKNfKDz4WlVdc6K71pz/3/Khc6raLrPp9arwh7wm/uO1H084w\nHV/d2/ZRGe12O9kvlJZtboqMJzYvcfvG+uuJiV+2bLdrbXOxaMkcN5XFitluuDwAHL/czaD83GmH\nR+WF213/pNKOHeaF+B8aaTX9Phe5BVRLnW67ckfCmxcfBu/NJm3uH63c98cLi7HvEdv3qNRh+mAN\nue+rySddyQBWgoioXuwTRERZxj5BRFQfReKveyKiGS+lGNa0laDPrHLpjkuf/mNU7iu7mYXbExYj\nBfz0Slk7K95v0zYHtvnNtpfMcU2yV+xZFpX/5qnHo7Kd2XmWuKGbQ+ovemofK6PysFKb5vOHlfuX\nQMk2QSfMWrqwxTVH21mtAf+12LTbtlHXtFwwbZ59Zhj/8ASLudpH9pq0mX2/bTosPo3ArIJ7/XNb\nBqLy6rsOjcrnnX1KVL5p0x/c/RlJjbElqImUTdrLfnG0m0VW4xNG2xyWza6bj0pxJCFVE0v1LH3A\nzOZ82xq3y6Ero/K6N7lZosvb3Enuk05KunDNiY3BTSOyYdBFg10Dnd4u8zrdkPm+17ouCGOdLjW2\n9MfuuOWdbrZqACgucF0QNpzt0vlihqIXBs30KF1mqpUufxh+Umqv5C1y68p2JmoUY2k683cdPMRt\nt/kcl+Y7YOMWd159tXe/mAnYEkRE9WMliIiyjJUgIqoXW4KIKMvYEpQSO1poXrE/KtsFOQGgx8x0\nnLS45yyz0J9dgPXdc92oBQC4us+NSrr+GDdy4oNPbY/KduRWV8GuWOifv91u21jlc+wwLbCjVYzU\nAvwRVjbt9KpZrsnZpr8AfzbnXSU3y7Qd+dVtFkDdY843rpgwaYQ3K7ed4dqU5xYHvX3mmAVzH+0/\nKiqv+oe7onI8tZcp7BPUtA642/3hN73ELPS5cMTbrlx0n3UZsVMQu6KadJidJPqgW/yZ1Yu3PxSV\nSyY119Lp0lNDS8yBExYQDQ5mHitVnvHapuPKgy5+9Q37I2D7280s+f0mLtuhU2V3rOLiRd7+2//E\npcdHzdqktoWiOGjP0cxSP+J3RdA2+8aiIm9WaZMOk1b/w9zSZrpZmH3a+szIupaMf52zTxAR1Usw\n4cLTREQzWloxjJUgorxgOoyIsozpsHR8/vDjovLn1t0TlXuks9LmAID+shutsLR1T8VtCsXkv6hN\nD12yZkNUHtDKI8JsCis+AqzfpN32lLrMPq6pdl7RjYiyI8AKsfZHe2z72Ju7d0ZlO4ljMba/Hblm\nU12DpdbEfca1Fvzpvsp2tJdJWdp0ml0Y1absFhbdCDbA/3v9cvWxUfl9j9xW8VyyMiLMYp+g5jTr\nBhezFs1+YVTe9crYZ3uWSSmZ1BjMaKWSzZKZ+/sO9icf7Tz/eVF5wytMSqjTrtKakA6Lx0VvMdeE\ntgBJKI/FUlCDJuY97spL7nLxC8Murg4870hv//7lJgVnB8rZt9IO7jLvkQzEJpQctKPxzHvfbkaN\ntdh0llngu8MfaVY2f5jWte67Y+EvnorKpR5/BHIWsU8QEdWPfYKIKMtSiGGVJ5UhomzR4FdUNf8m\nIiIHichvRGS1iDwqIu/fPy+AiJpaA+IXUHsMY0tQTKtp94xPuGfX0uoy1Uc7+WBfyaXQFrf0RuWf\nD/jrYll2FJp9Djs6yo5AG4mN6OoxKbCtZlLCpa3u+b3jmrrvrII/6sOOCLMpNMtLeZX80V125NbO\nUXdeY+acbZqunNT8Hdtubstgxftnm9SYP1Glf9wnhg6Mymqa0L9243lR+aaP3IVMa0xT8hiAD6rq\n70WkG8ADInKzqj422Y6UvkW3udR6qeMg77E9L3OfIbWjj8xMpIVuF4tKA+7rYccp/ldFYdjctmt/\nmfSQtpvRTmayv3jvVzWjwFCyF7GdxdHcb1NrpdjBzM0x05thbI6Lvy1L3MjcHSe4NDngr99ll1XU\non0erVCKjfSCn07TtsopMPveqXnvRgdjE8f2uvf7iKvdCOJyj+mKEZ8dM4tSiGGsBBHlRMKMAjVR\n1c0ANoflPhFZDWA5AFaCiGhapRHDWAkiyokaOhUuEpH7ze0rVPWKfY4ncgiAUwDcE3+MiKjRqoxh\nVcUvoLoYxkpQzN8d4kZX/ONaf/K8A1pc0+P2UjcqsWkrO8HhTjNxIOCnoTrMulatMCkdM/LJjtqy\nKTcA2GNu2xRaIaFabZ/bTrQIAKPmdjxVFh3X9F6z6SgAeG7EjRzrGXXntaDNpdYGS64JurPoXvtA\n2W+aXtTqRnjZddwWmAktLft+PzPiT4L2X3eeGZXf89Jbo/KtJ/iTrWWWopam5B2qetpEG4jIbADX\nA/iAqvZOtC3NHGMbNkblxVf762LNf8JNEvrUxWa00WwzqaJd48qmc1r8i6vkpafMdjZVZfcxx9XR\nWArLjvBKuobN84l5DlU/xomZSLFzu1nv6/7Vbp9Wt01b3wHe/gOzzLpirQmv0fZGqJwlC24mjALz\n0nllO7rMPUn7Lr/Lw4pfu1Rmeb1LeeqoPyFmplUfwyaNX0D1MYyVIKK8aFCXABFpRRA8rlbV/27M\nUYmIJpFCDGMliCgHBI3Jp4uIAPgWgNWq+m9TPyIR0eTSimEcIk+UE6Ja1b9JvAjAxQDOEZEHw38X\nTP/ZE1Gza0D8AmqMYWwJmsBnViXPGmz7C9mFVZe37q64vZ3ZGAAWtrj+LrYf0Cjswqyuj8z2MdcH\nyQ5RB4BtI25Y/CzTx8Y+py2Pmj97vE+QHUpv9/n5gN9fZ1x89uc9Zlzq4ra98c0BAO0tdri+27+9\n4M+SWjBto7NsvylzjnYmbft3uGe3WwgRAP7l3Oui8neOWlnxvDKttj5ByYdRvRNchiwXygP+FBeF\n//lDVD72Kbfwsc51/RW3nuWGj+85wvRpif1c9vq7JMwG7ffdsSfmX152oVQxC7iWO0xssR2U7PPF\nrlQ7Y/XOk9xJj8x1XUiWX78+Ks9f4/d7HO1yQ+mHbLfCKrot7fOpsadphr/blWnV9ARu6XdPsvCP\nflwu/PZht0/Zfyw3UophrAQR5QSXzSCiLOOyGURUt0bk04mI0pJGDGMlqE5JqbKvPXNnVH5y1A0X\njw83t7NE26HwNgVm0zt2Zub4UPL+kll01aTD7MzKdpZpO7NyfAHVommqtfsUTTtll0lN7Sz55zK7\n6F6nXejULhhrZ9i2Ka/WWDrMf87Ki8mWTDv1YwOuif/BDSu8Y73lgLuRe2wJoiqNPbfJ3XjOFbsP\nOT0q7znCff5jk9T715pNPJhUlw7Fdwo3H/MzFQWz0Kj9EizbNVslIbUWv+ZtODMprMElbsOxg1ye\na/eR/sKwZsJ9LwXoz/Jsn2+CrEvCe2TTh/a1d69z28y57UnvUCVtkl84bAkiorpUua4OEdGMlFIM\nYyWIKC9YCSKiLGMlKPs6TLOnHXlVjCU7bTqsX12TbL9Jde0yC6PaUVfD5dhihglXTnwR0XF2dFVc\nl7hUV2/ZpLDM+Y56aTL/dR3a7hb3s4uxtkrlEQ32HIux12Fnibb7j5h02DbTfv3wruVR+SdnftU7\nlp0JPI+COTZYC6Kpae0zsUFMOqvgX1s2pRNPb0VMaCia2ZBbBmOjw+wgMLPQqB01pjbtNNHELjbt\nZEaq2Un2n3q961qgbROkmRJSa36YqjyrdPz5C/b1D7ty5zZ3wgf84tmoPLYrNso4D4ujTiKtGMZK\nEFFOMB1GRFnGdBgR1adBc2wQEaUipRjGSlCDve3gF0flT627LyoPlNsrbQ7AnyCxnNDWWzBV5EKs\nutzVUnmh01GTNhvSNlN2aab4ZIm9ZgFYOworaUSWnfQR8EeU2bSZTW3Z0W2lhFFr8dt2dJkdKXfH\nie7+Fz/4dFQ+rs1fZLYZcIg8TVXhDjeh4lFr3WjLp999iLfdyLzKF1vBTHZo11YumEVTvYVJARRM\n2stu17LXxZkxO+qs3Tx3vOnAZtpMKLXPqTbl1hnrGmDTaUkLu9pUoN1+NBa7zbl1r3fxc/lP3AKo\nY8+YMohD5ImobqwEEVGWsRJERPVRNEXnSSLKqZRiGCtB0+ifDj098bHLnnZrwfSYUWDeBIljrjxY\n8tcLs8rq2mT3lF0ayE5cuGPUrT3WZkaHxdNhlh1FZtN5duLCA4p7vH3siLI5ba49fJtZ+6xYcNV9\nmzLbJ81nnseunXbrCV2o5L6T3bHOQ/K6b3nFjtHUSHZCxZUf2+Q91nOxG23Zu8qui+WKZk5Vfx0t\n9UeH2YkYbdlLrZn7S0WpuP0+TGjz0nF2m1jWvKXNxbxSwUwWmTAJpL1/7mP+1+ns59wJzF7v4qRN\ngZGPHaOJqH6sBBFRlrESRET1EFXOE0REmZVWDGMlKCWXH3ZiVL7ocdfUvNeMgopPijiupeD3HrOj\nqGzazN4/y6TG7MSH8YkTk9Y026Wzo/IJrX7TuGUnP7QjyuaYoSI93jpoLs22stVNtAgA84oDUXn1\n4DLQxJgOo/1l3lV3ReU5Z50SlXuOcPFrtMvFguGFycey2TEziNTfxoTCskmTIdZLwE5QmDBXLOY+\n7tJZs7f4j43MdvFocJE7QMdOd9xZO1zMlJK5f41ZhA3A2Lpn3HlVPhWKYTqMiOrHSEtEWcZKEBHV\niy1BRJRlbAkiovoogBJrQUSUUSnFMFaCZoBrjq7c3+XUP5gxnjZvHqsue32CYGd8NjNRa+WZqIfM\n7M0A0N3i+u4MqTuW7cdj+/0Mxcao2tmk7ezRs8T1SeqBO5btk7Sk2Ocd62OrTq14zlQZW4IoDXaW\n6QV3uPuLixdH5Z5zDovKY51+Zx3b98byQoudmtkuuNoRH27vPgR2odb2Xa686GHX17B4z2Pe/rOL\nLn7JbDcVhw66uFg2ZWtMOVvpVLEliIjqx8kSiSjLOFkiEdWLLUFElGVsCSLPA6e4ptkTf++ac2d5\nU7H62gsuvTSasJipTXPZMgB0lN2xt4zOi8q7x1zT8NrRRVH5q0ccnvwCanQDFk++EVUkCs4TRDNK\nabub8qL7B65cnDPH205XrXBlk/Yqd7ivp+FFbui6HZYusT4kHVtdqkvWuyHrSSksHR2J3TY3hirv\nQ9MjrRjGShBRXrBLAhFlGRdQJaJ6CfsEEVGGpRHDWAnKiIefZy+O5MVUk3UllOMmn5n5bjQuBUYN\nouBkiZQJpd5e/44HH6u4nR331VFxi32xMTTDUophlcdNE1HGBOvuVPNvMiLybRHZJiKP7IcTJyJC\ntTFsMrXGL1aCiPJCtbp/k7sSwPnTe7JERDEpxC+mw4jyQAFpUC5AVW8XkUMaczQioio0KIbVGr9Y\nCSLKi+o7FS4SkfvN7StU9YppOCMioupVF8MaGr9YCSLKiRrm2NihqqdN57kQEdWqyhjW0PjFShBR\nXnCIPBFlGYfIE1FdFBwfTETZlVIM4+gwohwQKESr+zfpsUSuAXAXgKNEZKOIvHPaXwARNbVqY9ik\nx6kxfrEliCgvyo35GaWqFzXkQEREtWhADKs1frESRJQHTIcRUZalFMNYCSLKCa4dRkRZxrXDiKhO\n2rB0GBHR/pdODGMliCgPFBwiT0TZlVIMYyWIKC/YEEREWcY+QURUL/YJIqIsY58gIqqPAiixKYiI\nMiqlGMZKEFEuKPsEEVGGpRPDWAkiygtWgogoy1gJIqK6sRJERFnGShAR1UUVKJXSPgsiovqkFMNY\nCSLKC7YEEVGWsSWIiOqiAMqsBBFRRqUUw1gJIsoLtgQRUZaxJYiI6sO1w4goy7h2GBHVS8FKEBFl\nV0oxjJUgorxgOoyIsozpMCKqGytBRJRlrAQRUV1UoZwniIiyKqUYxkoQUV5wiDwRZRmHyBNR3ZgO\nI6IsYzqMiOqiHCJPRBmWUgxjJYgoJ9gniIiyjH2CiKhOynQYEWVYOjGMlSCiPODaYUSUZSnFsMJ+\nf0Yimh5aru7fJETkfBFZIyJPicg/7IczJyJqSPwCaothbAkiygFt0BwbIlIE8J8AzgWwEcB9InKj\nqj425YMTESVIK4axJYgoJ7SsVf2bxPMBPKWqa1V1BMC1AP502k+eiJpeA+IXUGMM268tQTeXfyj7\n8/mImkUfdt90S/m6RVVu3iEi95vbV6jqFWF5OYAN5rGNAF7QiHPMOsYvoulTQwybKH4BNcYwpsOI\nckBVz2/QoSp90bPHNRFNq7RiGNNhRGRtBHCQub0CwKaUzoWIqFY1xTBWgojIug/AESJyqIi0AXgj\ngBtTPiciomrVFMOYDiOiiKqOicj7ANwEoAjg26r6aMqnRURUlVpjmChnmSUiIqImxHQYERERNSVW\ngoiIiKgpsRJERERETYmVICIiImpKrAQRERFRU2IliIiIiJoSK0FERETUlFgJIiIioqbEShARERE1\nJVaCiIiIqCmxEkRERERNiZUgIiIiakqsBBEREVFTYiWIiIiImhIrQURERNSUWAkiIiKipsRKEBER\nETUlVoKIiIioKf1/gSCWpYuQNLIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f563487d250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, [ax1, ax2] = plt.subplots(1, 2, figsize=[10, 5])\n",
    "\n",
    "ax1plot = ax1.imshow(mean_diameter.squeeze().T,\n",
    "           origin=True, vmax=6, interpolation='nearest')\n",
    "ax1.set_title('Estimated Mean Axon Diameter')\n",
    "ax1.set_axis_off()\n",
    "plt.colorbar(ax1plot, ax=ax1, shrink=0.75)\n",
    "\n",
    "ax2plot = ax2.imshow(mean_diameter_histology.T, \n",
    "           origin=True, vmax=6, interpolation='nearest')\n",
    "ax2.set_title('Histology Mean Axon Diameter')\n",
    "ax2.set_axis_off()\n",
    "plt.colorbar(ax2plot, ax=ax2, shrink=0.75)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that our estimated mean axon diameter map is completely smooth, aside from a few outliers in areas which actually lie outside of the white matter area (see right histology image). The estimated diameters are overestimated in general. We find between 4-6 $\\mu$m, while the histological values are between 0-5 $\\mu$m. \n",
    "\n",
    "Using the Seaborn package, we can nicely visualize the correlation between our estimated and the histology diameters. We separate visualize this correlation of axon diameters between 1-2$\\mu$m, 2-3$\\mu$m and 3+$\\mu$m, and remove the exceptional outliers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean_diameter_mask12 = np.all([mean_diameter_histology > 1,\n",
    "                               mean_diameter_histology < 2,\n",
    "                               mean_diameter.squeeze() < 10], axis=0)\n",
    "mean_diameter_mask23 = np.all([mean_diameter_histology > 2,\n",
    "                               mean_diameter_histology < 3,\n",
    "                               mean_diameter.squeeze() < 10], axis=0)\n",
    "mean_diameter_mask3p = np.all([mean_diameter_histology > 3,\n",
    "                               mean_diameter.squeeze() < 10], axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axon diameter correlation 1-2 $\\mu$m - not significant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7f56139c7550>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IRRSwYMSgpTsg3VeEyAGrVdHpDeU6jJwadRpTKfVJ4JMDbvp7pVT7kMtcwMnA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\nrmtXGICSyxu27hlBBFwRNu0cHDfqUs/h1I3l8vziz1uZk45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n+o/9jv9aXOg/5vqiYwqv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\nslNKKRV5muyUUkpF3n8CwmXK8GZx0xsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f56139c7590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "mask = mean_diameter_mask12\n",
    "im = sns.jointplot(mean_diameter[mask].squeeze(),\n",
    "                   mean_diameter_histology[mask].squeeze(), kind=\"reg\")\n",
    "im.set_axis_labels(\"Estimated Axon Diameter\", \"Histology Axon Diameter\", fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axon diameter correlation 2-3 $\\mu$m - not significant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7f5634a06a10>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UbiGU+HUC2pwj+/U7cdeuXcG3oLYWmDwZWLMG+PBD4Iwzgv8aHWPKGQq72LW+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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5634a57110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = mean_diameter_mask23\n",
    "im = sns.jointplot(mean_diameter[mask].squeeze(),\n",
    "                   mean_diameter_histology[mask].squeeze(), kind=\"reg\", color='r')\n",
    "im.set_axis_labels(\"Estimated Axon Diameter\", \"Histology Axon Diameter\", fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axon diameter correlation 3+ $\\mu$m - Significant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x7f56138db490>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Twk82lw2FwmAwgII4YxxGZUQp1W6Lp6lgzWz0dxJJMMbhOjuRpWUs6fHp9Erp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\ns2RnjDEm8f4fRhaLlnjfPYkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5634a06a90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = mean_diameter_mask3p\n",
    "im = sns.jointplot(mean_diameter[mask].squeeze(),\n",
    "                   mean_diameter_histology[mask].squeeze(), kind=\"reg\", color='g')\n",
    "im.set_axis_labels(\"Estimated Axon Diameter\", \"Histology Axon Diameter\", fontsize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results show that for our current approach to the data set we can only estimate axon diameters that correlate with the histology values for axon diameters of 3+$\\mu$m."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison between estimated and histology volume fraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, we can also visualize the estimated intra-axonal volume fraction between our model and the histology values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "axcaliber_fraction = axcaliber_gamma_fit.fitted_parameters['partial_volume_1'].squeeze()\n",
    "histology_fraction = data_spinal_cord.histology.h4_fr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f561330e450>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IMsABTcn3i0gewI0ALgUwAGCtiKx2zj2YWPXrzrnrjnqHRETwP4axskSUAQ6CcnMais8H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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5613620890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, [ax1, ax2] = plt.subplots(1, 2, figsize=[10, 5])\n",
    "\n",
    "ax1plot = ax1.imshow(axcaliber_fraction.T,\n",
    "           origin=True,interpolation='nearest', vmax=0.55)\n",
    "ax1.set_title('Estimated Volume Fraction')\n",
    "ax1.set_axis_off()\n",
    "plt.colorbar(ax1plot, ax=ax1, shrink=0.75)\n",
    "\n",
    "ax2plot = ax2.imshow(histology_fraction.T, \n",
    "           origin=True, interpolation='nearest', vmax=0.55)\n",
    "ax2.set_title('Histology Volume Fraction')\n",
    "ax2.set_axis_off()\n",
    "plt.colorbar(ax2plot, ax=ax2, shrink=0.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CQKkglZUXUFX1aXy+IncDnMWSrcbMY/wG9CByvU4IMYJhdGIYLW6HMWv09PyT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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f561350a890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im = sns.jointplot(axcaliber_fraction[mean_diameter_histology > 1],\n",
    "              histology_fraction[mean_diameter_histology > 1], kind=\"reg\", color='y')\n",
    "im.set_axis_labels(\"Estimated Volume Fraction\", \"Histology Volume Fraction\", fontsize=15);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results show that estimating intra-axonal volume fractions that correlate with histology is easier than doing the same for axon diameter. However, the model does systematically underestimate the value compared to histology."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "- Assaf, Yaniv, et al. \"AxCaliber: a method for measuring axon diameter distribution from diffusion MRI.\" Magnetic resonance in medicine 59.6 (2008): 1347-1354.\n",
    "- Burcaw, Lauren M., Els Fieremans, and Dmitry S. Novikov. \"Mesoscopic structure of neuronal tracts from time-dependent diffusion.\" NeuroImage 114 (2015): 18-37.\n",
    "- De Santis, Silvia, Derek K. Jones, and Alard Roebroeck. \"Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter.\" NeuroImage 130 (2016): 91-103.\n",
    "- Farooq, Hamza, et al. \"Microstructure imaging of crossing (MIX) white matter fibers from diffusion MRI.\" Scientific reports 6 (2016): 38927.\n",
    "- Huang, Susie Y., et al. \"The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter.\" NeuroImage 106 (2015): 464-472."
   ]
  }
 ],
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     "DOI": "10.1016/j.neuroimage.2015.03.061",
     "URL": "http://linkinghub.elsevier.com/retrieve/pii/S1053811915002578",
     "accessed": {
      "day": 8,
      "month": 8,
      "year": 2016
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     "author": [
      {
       "family": "Burcaw",
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      },
      {
       "family": "Fieremans",
       "given": "Els"
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     "page": "18-37",
     "page-first": "18",
     "title": "Mesoscopic structure of neuronal tracts from time-dependent diffusion",
     "type": "article-journal",
     "volume": "114"
    },
    "1647435/THCKBHVE": {
     "DOI": "10.1038/srep38927",
     "URL": "http://www.nature.com/articles/srep38927",
     "accessed": {
      "day": 26,
      "month": 12,
      "year": 2016
     },
     "author": [
      {
       "family": "Farooq",
       "given": "Hamza"
      },
      {
       "family": "Xu",
       "given": "Junqian"
      },
      {
       "family": "Nam",
       "given": "Jung Who"
      },
      {
       "family": "Keefe",
       "given": "Daniel F."
      },
      {
       "family": "Yacoub",
       "given": "Essa"
      },
      {
       "family": "Georgiou",
       "given": "Tryphon"
      },
      {
       "family": "Lenglet",
       "given": "Christophe"
      }
     ],
     "container-title": "Scientific Reports",
     "id": "1647435/THCKBHVE",
     "issued": {
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     },
     "page": "38927",
     "page-first": "38927",
     "title": "Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI",
     "type": "article-journal",
     "volume": "6"
    },
    "1647435/TKDYMRGX": {
     "author": [
      {
       "family": "De Santis",
       "given": "Silvia"
      },
      {
       "family": "Jones",
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     },
     "page": "91–103",
     "page-first": "91",
     "title": "Including diffusion time dependence in the extra-axonal space improves in vivo estimates of axonal diameter and density in human white matter",
     "type": "article-journal",
     "volume": "130"
    },
    "1647435/WIBPFNDJ": {
     "author": [
      {
       "family": "Assaf",
       "given": "Yaniv"
      },
      {
       "family": "Blumenfeld-Katzir",
       "given": "Tamar"
      },
      {
       "family": "Yovel",
       "given": "Yossi"
      },
      {
       "family": "Basser",
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      }
     ],
     "container-title": "Magnetic Resonance in Medicine",
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     "issue": "6",
     "issued": {
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     "page": "1347–1354",
     "page-first": "1347",
     "title": "AxCaliber: a method for measuring axon diameter distribution from diffusion MRI",
     "type": "article-journal",
     "volume": "59"
    },
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     "author": [
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       "family": "Huang",
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      },
      {
       "family": "Nummenmaa",
       "given": "Aapo"
      },
      {
       "family": "Witzel",
       "given": "Thomas"
      },
      {
       "family": "Duval",
       "given": "Tanguy"
      },
      {
       "family": "Cohen-Adad",
       "given": "Julien"
      },
      {
       "family": "Wald",
       "given": "Lawrence L"
      },
      {
       "family": "McNab",
       "given": "Jennifer A"
      }
     ],
     "container-title": "NeuroImage",
     "id": "1647435/X4YR23CQ",
     "issued": {
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     },
     "page": "464–472",
     "page-first": "464",
     "title": "The impact of gradient strength on in vivo diffusion MRI estimates of axon diameter",
     "type": "article-journal",
     "volume": "106"
    }
   }
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