{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Customization\n",
    "\n",
    "If you do not want to run the standard simulation you can easily modify the initial conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dustpy import Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim = Simulation()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation object has an attribute to set the initial conditions `Simulation.ini`. The attribute is structured in initial conditions for dust, gas, the grid, and the central star. If you call `Simulatio.initialize()`, the simulation object will be filled according the parameters set here. We'll go through all options one by one.\n",
    "\n",
    "**All quantities are in cgs units!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(dust=namespace(aIniMax=0.0001,\n",
       "                         allowDriftingParticles=False,\n",
       "                         crateringMassRatio=10.0,\n",
       "                         d2gRatio=0.01,\n",
       "                         distExp=-3.5,\n",
       "                         excavatedMass=1.0,\n",
       "                         fragmentDistribution=-1.8333333333333333,\n",
       "                         rhoMonomer=1.67,\n",
       "                         vfrag=100.0),\n",
       "          gas=namespace(alpha=0.001,\n",
       "                        gamma=1.4,\n",
       "                        Mdisk=9.942049353490256e+31,\n",
       "                        mu=3.847030424486999e-24,\n",
       "                        SigmaExp=-1.0,\n",
       "                        SigmaRc=897587224200000.0),\n",
       "          grid=namespace(Nmbpd=7,\n",
       "                         mmin=1e-12,\n",
       "                         mmax=100000.0,\n",
       "                         Nr=100,\n",
       "                         rmin=14959787070000.0,\n",
       "                         rmax=1.495978707e+16),\n",
       "          star=namespace(M=1.988409870698051e+33, R=139140000000.0, T=5772.0))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Stellar parameters\n",
    "\n",
    "The stellar parameters mainly influence the dynamical time scales and the temperature profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(M=1.988409870698051e+33, R=139140000000.0, T=5772.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.star"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* M\n",
    "\n",
    "Stellar mass, default: $1\\ M_\\odot$  \n",
    "Has influence on the dynamical timescales in the disk.\n",
    "\n",
    "* R\n",
    "\n",
    "Stellar radius, default: $2\\ M_\\odot$  \n",
    "Has influence on the temperature profile in the disk. The default temperature profile is a passively irradiated disk with a constant irradtion angle of 0.05.\n",
    "\n",
    "* T\n",
    "\n",
    "Effective temperature, default: 5772 K  \n",
    "Has influence on the temperature profile in the disk. The default temperature profile is a passively irradiated disk with a constant irradtion angle of 0.05."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grid parameters\n",
    "\n",
    "The grid parameters determine the shape of the grids. While you can set your own non-standard radial grid (see later), you should under no circumstances meddle with the mass grid, unless you know exactöy what you are doing. Please always use the `Simulation.ini.grid` namespace to customize your mass grid. The mass grid has to be strickly logarithmic. Otherwise, the coagulation algorithm will produce wrong results. Note: If you changed the mass grid for some reason during the simulation, you have to re-calculate the coagulation parameters in `Simulation.dust.coagulation`.\n",
    "\n",
    "**Note:** The performance of `DustPy` is very sensitive to the mass grid. A finer mass grid slows down the simulation drastically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(Nmbpd=7,\n",
       "          mmin=1e-12,\n",
       "          mmax=100000.0,\n",
       "          Nr=100,\n",
       "          rmin=14959787070000.0,\n",
       "          rmax=1.495978707e+16)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Nmbpd\n",
    "\n",
    "Number of mass bins per mass decade, default: 7  \n",
    "Should be at least 7, see [Drążkowska et al. (2014)](https://doi.org/10.1051/0004-6361/201423708)\n",
    "\n",
    "* mmin\n",
    "\n",
    "Minimum particle mass, default: $10^{-12}$ g\n",
    "\n",
    "* mmax\n",
    "\n",
    "Maximum particle mass, default: $10^{5}$ g\n",
    "\n",
    "* Nr\n",
    "\n",
    "Number of radial grid cells, default: 100\n",
    "\n",
    "* rmin\n",
    "\n",
    "Location of inner radial grid boundary, default 1 AU\n",
    "\n",
    "* rmax\n",
    "\n",
    "Location of outer radial grid boundary, default 1000 AU"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gas Parameters\n",
    "\n",
    "The gas parameters define the initial conditions of the gas disk. The standard surface density profile is the self-similar solution of [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(alpha=0.001,\n",
       "          gamma=1.4,\n",
       "          Mdisk=9.942049353490256e+31,\n",
       "          mu=3.847030424486999e-24,\n",
       "          SigmaExp=-1.0,\n",
       "          SigmaRc=897587224200000.0)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.gas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* alpha\n",
    "\n",
    "alpha viscosity parameter, default: $10^{-3}$  \n",
    "see [Shakura & Sunyaev (1973)](http://adsabs.harvard.edu/abs/1973A%26A....24..337S) for details\n",
    "\n",
    "* gamma\n",
    "\n",
    "heat capacity ratio, default: 7/5\n",
    "\n",
    "* Mdisk\n",
    "\n",
    "Inital gas disk mass, default: $0.05\\ M_\\odot$\n",
    "\n",
    "* mu\n",
    "\n",
    "Mean molecular weight of the gas, default: $2.3\\ m_\\mathrm{proton}$\n",
    "\n",
    "* SigmaExp\n",
    "\n",
    "Power law exponent of surface density profile, default: -1  \n",
    "see [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)\n",
    "\n",
    "* SigmaRc\n",
    "\n",
    "Critical cut-off radius of surface density, default: 30 AU  \n",
    "see [Lynden-Bell & Pringle (1974)](https://doi.org/10.1093/mnras/168.3.603)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dust Parameters\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "namespace(aIniMax=0.0001,\n",
       "          allowDriftingParticles=False,\n",
       "          crateringMassRatio=10.0,\n",
       "          d2gRatio=0.01,\n",
       "          distExp=-3.5,\n",
       "          excavatedMass=1.0,\n",
       "          fragmentDistribution=-1.8333333333333333,\n",
       "          rhoMonomer=1.67,\n",
       "          vfrag=100.0)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.ini.dust"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* aIniMax\n",
    "\n",
    "Maximum particle size that will be filled initially, default: 1 µm\n",
    "\n",
    "* allowDriftingParticles\n",
    "\n",
    "If `True` initially drifting particles will not be removed, default: `False`  \n",
    "Dust particles in the disk drift inwards more rapidly with increasing Stokes number. In the outer disk the gas surface density is low and therefore even the small initial particles can have large Stokes numbers causing them to drift already from the beginning on. This causes a visible particle wave in the simulation. By setting this parameter to `False`, these drifting particles will be removed.\n",
    "\n",
    "* crateringMassRatio\n",
    "\n",
    "If the mass ratio of colliding particles is below this ratio, both particles fully fragment, default: 10  \n",
    "In the standard model three things can happen when particles collide: they can stick together forming a larger particle, they can both fully fragment, or the smaller collision partner can fully fragment, chipping off some mass of the larger collision partner. The latter is called cratering. This parameter defines the threshold between full fragmentation and cratering.\n",
    "\n",
    "* d2gRatio\n",
    "\n",
    "Initial dust-to-gas ratio, default: $10^{-2}$\n",
    "\n",
    "* distExp\n",
    "\n",
    "Inital size distribution of particles, default: -7/2  \n",
    "The particles will initially have a size distribution of $n\\left(a\\right) \\propto a^\\mathrm{distExp}$ up to a maximum particle size of `Simulation.ini.dust.aIniMax`. The standard model uses the so-called MRN distribution of interstellar grains as initial condition. See [Mathis et al. (1977)](https://doi.org/10.1086/155591).\n",
    "\n",
    "* excavatedMass\n",
    "\n",
    "Excavated mass from larger particle in units of smaller particle mass, default: 1  \n",
    "In a cratering collision event the smaller particle will chip off mass from the larger particle. This parameter determines how much mass will be chipped off.\n",
    "\n",
    "* fragmentDistribution\n",
    "\n",
    "mass distribution of fragments, default: -11/6  \n",
    "Whenever a particle collision produces fragments the fragments will have a mass distribution of $n \\left(m\\right) \\mathrm{d}m \\propto m^\\mathrm{fragmentDistribution} \\mathrm{d}m$. The value used by the standard model is taken from [Dohnanyi (1969)](https://doi.org/10.1029/JB074i010p02531).\n",
    "\n",
    "* rhoMonomer\n",
    "\n",
    "Monomer bulk mass density, default: 1.67 g/cm³  \n",
    "In the standard model all particles will have a filling factor of unity and share therefore this bulk mass density.\n",
    "\n",
    "* vFrag\n",
    "\n",
    "Fragmentation velocity, default 1 m/s.  \n",
    "Particle collisions with a collision velocity that exceeds the fragmentation velocity will result in a fragmenting collision. Either full fragmentation or cratering depending on the mass ratio of the collision partners. Collisions below the fragmentation velocity lead to sticking."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Initial Conditions\n",
    "\n",
    "In this example we want to run a simulation with a larger disk mass. We can use the constants module of `DustPy`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dustpy import constants as c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim.ini.gas.Mdisk = 0.1 * c.M_sun"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now initialize the simulation as described in the previous section."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim.initialize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Snapshots\n",
    "\n",
    "The standard model runs for 100,000 years and starts writin data files at 1,000 with 10 files per time decade. In this example we only want to run the simulation for 10,000 years with only 5 snapshots per decade. This can easily be set by modifying `Simulation.t.snapshots`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim.t.snapshots = np.logspace(3, 4, num=6, base=10) * c.year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing the Output Directory\n",
    "\n",
    "By default `DustPy` will protect already existing data files. If we ran the simulation now, an error would be raised, because we have already existing data files in the output directory from the previous chapter.\n",
    "\n",
    "We could either set `Simulation.writer.overwrite` to `True` to overwrite our existing data files or we could change the name of the output directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sim.writer.datadir = \"2_data\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation is now ready to go."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DustPy v0.5.1\n",
      "\n",
      "Documentation: https://stammler.github.io/dustpy/\n",
      "PyPI:          https://pypi.org/project/dustpy/\n",
      "GitHub:        https://github.com/stammler/dustpy/\n",
      "\u001b[91m\n",
      "Please read README.md on the GitHub repository for\n",
      "information about the Terms of Usage.\u001b[0m\n",
      "\n",
      "\u001b[93mChecking for mass conservation...\n",
      "\u001b[0m\n",
      "\u001b[93m    - Sticking:\u001b[0m\n",
      "\u001b[98m        max. rel. error: \u001b[92m 2.81e-14\u001b[0m\n",
      "        for particle collision\n",
      "            m[114] =  1.93e+04 g    with\n",
      "            m[116] =  3.73e+04 g\u001b[0m\n",
      "\u001b[93m    - Full fragmentation:\u001b[0m\n",
      "\u001b[98m        max. rel. error: \u001b[92m 3.33e-16\u001b[0m\n",
      "        for particle collision\n",
      "            m[4] =  3.73e-12 g    with\n",
      "            m[6] =  7.20e-12 g\u001b[0m\n",
      "\u001b[93m    - Cratering:\u001b[0m\n",
      "\u001b[98m        max. rel. error: \u001b[92m 1.78e-15\u001b[0m\n",
      "        for particle collision\n",
      "            m[110] =  5.18e+03 g    with\n",
      "            m[118] =  7.20e+04 g\n",
      "\u001b[0m\n",
      "Creating data directory '2_data'.\n",
      "Writing file \u001b[94m2_data/data0000.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0001.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0002.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0003.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0004.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0005.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Writing file \u001b[94m2_data/data0006.hdf5\u001b[0m\n",
      "Writing dump file \u001b[94m2_data/frame.dmp\u001b[0m\n",
      "Execution time: \u001b[94m0:04:39\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "sim.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The simulation has now run for 10,000 years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10000.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sim.t / c.year"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we can have a look at the current state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from dustpy import plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1575x648.949 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.panel(sim)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When calling `Simulation.run()`, `DustPy` will perform a small mass conservation check, by going through all possible collisions and calculating their relative mass error. The limitation here is machine precision. Everything smaller than $10^{-13}$ is still acceptable. If you created your own collision model, that is not compatible with the default sticking-cratering-fragmentation model, you can either ignore the output, or you can overwrite the `Simulation.checkmassconservation()` function that is called by default when calling `Simulation.run()`.\n",
    "\n",
    "See a later chapter for details on coagulation."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}