{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Distributed Model Representations in Dmipy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The typical diameter of a white matter axon ranges between [0.1 - 2$\\mu m$] *(Aboitiz et al. 1992)*, while the dMRI imaging resolution is typically around [1-2] $mm^3$. This means that for every voxel we are not measuring the signal of a single axon, but the average signal for large ensembles of axons and other neurites whose properties can vary within that same voxel. To estimate meaningful tissue microstructure parameters from the dMRI signal many approaches to represent these parameter *distributions* have been proposed. In Microstructure Imaging, the most intensely studied parameter distributions have been the *axon orientation dispersion distribution* and the *axon diameter distribution*.\n",
    "\n",
    "The axon orientation dispersion distribution refers to the phenomenon that axons are not all pointed in exactly the same directions within one axon bundle. Instead, their orientations are spread around the main bundle axis with some distribution. In Microstructure Imaging, these distributions are often model as Watson, Bingham or Spherical Harmonics distributions.\n",
    "\n",
    "The axon diameter distribution refers to the fact that the axon diameter varies within the same axon bundle. This distribution is often modelled as a Gamma distribution.\n",
    "\n",
    "Dmipy allows you to create orientation-dispersed, diameter-distributed (or both at the same time) representations for e.g. axon bundles. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating an axon-dispersed bundle representation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In Microstructure Imaging, the brain's axon bundles are typically represented as having both an intra- and an extra-axonal compartment. Intra-axonal compartments are typically represented using cylinder models, while extra-axonal compartments are typically Gaussian. To simulate the phenomenon of axon dispersion, it is possible to see a dispersed bundle as an ensemble of a single parallel \"micro-environments\", which exist with some probability for different orientations.\n",
    "\n",
    "Dmipy allows to create such a \"bundle representation\" using distribute_models module. A distributed model can be seen as a type of sub-multi-compartment model that can contain multiple single models representations (e.g. Sticks, Cylinders, Zeppelin) - **as long as they have an orientation**. The contained single models all experience the same distribution parameters. Currently, is possible to choose between the parametric Watson or Bingham distributions.\n",
    "\n",
    "### Watson-Dispersed Zeppelin and Stick representation\n",
    "We will start by creating a Watson-dispersed Stick and Zeppelin representation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from dmipy.signal_models import gaussian_models, cylinder_models\n",
    "from dmipy.distributions import distribute_models\n",
    "\n",
    "stick = cylinder_models.C1Stick()\n",
    "zeppelin = gaussian_models.G2Zeppelin()\n",
    "watson_bundle = distribute_models.SD1WatsonDistributed(models=[stick, zeppelin])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can list the parameters of this representation as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['G2Zeppelin_1_lambda_perp',\n",
       " 'SD1Watson_1_odi',\n",
       " 'G2Zeppelin_1_lambda_par',\n",
       " 'SD1Watson_1_mu',\n",
       " 'C1Stick_1_lambda_par',\n",
       " 'partial_volume_0']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "watson_bundle.parameter_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The parameters 'SD1Watson_1_odi' and 'SD1Watson_1_mu' represent the Orientation Dispersion Index (ODI) and orientation of the Watson distribution. The others are parameters of the Stick and Zeppelin models.\n",
    "\n",
    "Notice is that there is only one \"mu\" parameter, as the orientation of the Stick and Zeppelin are now tied to that of the Watson distribution, i.e. the Stick and Zeppelin are now always aligned.\n",
    "\n",
    "Lastly, the 'partial_volume_0' parameter represents the volume fraction of the first input model - in our case the stick - where the second volume fraction is defined as partial_volume_1 = 1-partial_volume_0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bingham-dispersed Zeppelin and Stick representation\n",
    "A Bingham-dispersed representation is made in the same way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SD2Bingham_1_odi',\n",
       " 'SD2Bingham_1_beta_fraction',\n",
       " 'G2Zeppelin_1_lambda_perp',\n",
       " 'SD2Bingham_1_psi',\n",
       " 'SD2Bingham_1_mu',\n",
       " 'G2Zeppelin_1_lambda_par',\n",
       " 'C1Stick_1_lambda_par',\n",
       " 'partial_volume_0']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stick = cylinder_models.C1Stick()\n",
    "zeppelin = gaussian_models.G2Zeppelin()\n",
    "bingham_bundle = distribute_models.SD2BinghamDistributed(models=[stick, zeppelin])\n",
    "bingham_bundle.parameter_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the additional parameters 'psi' and 'beta_fraction' have been introduced, which can represent dispersion anisotropy."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating an axon diameter distributed bundle representation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the same way, it is also possible to create an axon diameter distributed bundle representation. For this example, we model an diameter-distributed Gaussian-Phase cylinder:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['C4CylinderGaussianPhaseApproximation_1_mu',\n",
       " 'C4CylinderGaussianPhaseApproximation_1_lambda_par',\n",
       " 'DD1Gamma_1_beta',\n",
       " 'DD1Gamma_1_alpha']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cylinder = cylinder_models.C4CylinderGaussianPhaseApproximation()\n",
    "gamma_bundle = distribute_models.DD1GammaDistributed(models=[cylinder])\n",
    "gamma_bundle.parameter_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the distributed model has no 'diameter' parameter, but instead has the shape 'alpha' and scale 'beta' parameters of the Gamma distribution."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating an orientation dispersed AND diameter distributed bundle representation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dmipy is constructed in such a modular way that Watson/Bingham-dispersed bundle representation can be used as input for Gamma-distributed models, and the other way around. (It is noteworthy that dispersing a distributed model and distributing a dispersed model is mathematically the same).\n",
    "\n",
    "For this example, let us make a close-to-complete white matter representation (for single bundles) that can be made in PGSE-dMRI, combining Bingam-dispersed axon orientations *(Sotiropoulos et al. 2012)*, distributed axon diameters *(Assaf et al. 2008)*, and restricted extra-axonal diffusion *(Burcaw et al. 2015)*:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['SD2Bingham_1_odi',\n",
       " 'SD2Bingham_1_beta_fraction',\n",
       " 'SD2Bingham_1_psi',\n",
       " 'G3TemporalZeppelin_1_lambda_inf',\n",
       " 'SD2Bingham_1_mu',\n",
       " 'C4CylinderGaussianPhaseApproximation_1_lambda_par',\n",
       " 'C4CylinderGaussianPhaseApproximation_1_diameter',\n",
       " 'G3TemporalZeppelin_1_A',\n",
       " 'G3TemporalZeppelin_1_lambda_par',\n",
       " 'partial_volume_0']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import the base model components\n",
    "cylinder = cylinder_models.C4CylinderGaussianPhaseApproximation()\n",
    "restricted_zeppelin = gaussian_models.G3TemporalZeppelin()\n",
    "\n",
    "bingham_bundle = distribute_models.SD2BinghamDistributed(models=[cylinder, restricted_zeppelin])\n",
    "bingham_bundle.parameter_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To also distribute the diameter of the cylinder model, we must now set the 'target_parameter' variable to the correct name in the dispersed model:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gamma_bingham_bundle = distribute_models.DD1GammaDistributed(\n",
    "    models=[bingham_bundle],\n",
    "    target_parameter='C4CylinderGaussianPhaseApproximation_1_diameter')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating the multi-compartment model that can (technically) be fitted is then as in the previous examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['DD1GammaDistributed_1_SD2BinghamDistributed_1_C4CylinderGaussianPhaseApproximation_1_lambda_par',\n",
       " 'DD1GammaDistributed_1_DD1Gamma_1_beta',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_SD2Bingham_1_odi',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_partial_volume_0',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_SD2Bingham_1_psi',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_SD2Bingham_1_mu',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_G3TemporalZeppelin_1_lambda_par',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_G3TemporalZeppelin_1_A',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_SD2Bingham_1_beta_fraction',\n",
       " 'DD1GammaDistributed_1_DD1Gamma_1_alpha',\n",
       " 'DD1GammaDistributed_1_SD2BinghamDistributed_1_G3TemporalZeppelin_1_lambda_inf']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dmipy.core.modeling_framework import MultiCompartmentModel\n",
    "white_matter_mc_model = MultiCompartmentModel(models=[gamma_bingham_bundle])\n",
    "white_matter_mc_model.parameter_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can even visualize the flow of models (and their raw parameters) as a graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABVYAAAG7CAYAAAAorM5dAAAABmJLR0QA/wD/AP+gvaeTAAAgAElE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\nRK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "white_matter_mc_model.visualize_model_setup(view=False, cleanup=False, with_parameters=True)\n",
    "Image('Model Setup.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It can be seen that including all these tissue properties means that the model will have many parameters. Nonetheless, this model is fittable to any data set as all previous ones.\n",
    "\n",
    "However, It is important to realize the the more complicated the model (the more parameters), the more local minima there are, the more parameter combinations will produce the same fitting error, and the longer the optimization time. In fact, *(Jelescu et al. 2016)* already showed that estimating the diffusivity and dispersion in the NODDI model at the same time results in multiple parameter solutions with the same fitting error. \n",
    "\n",
    "To have meaningful results, it is therefore always important to make sure the model you are fitting is not more complex than the data you have!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "- Aboitiz, Francisco, et al. \"Fiber composition of the human corpus callosum.\" Brain research 598.1 (1992): 143-153.\n",
    "- Sotiropoulos, Stamatios N., Timothy EJ Behrens, and Saad Jbabdi. \"Ball and rackets: inferring fiber fanning from diffusion-weighted MRI.\" Neuroimage 60.2 (2012): 1412-1425.\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",
    "- Jelescu, Ileana O., et al. \"Degeneracy in model parameter estimation for multi‐compartmental diffusion in neuronal tissue.\" NMR in Biomedicine 29.1 (2016): 33-47."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}