{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Heat\n",
    "\n",
    "In this example the laser-excitation of a sample `Structure` is shown.\n",
    "It includes the actual absorption of the laser light as well as the transient temperature profile calculation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "Do all necessary imports and settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import udkm1Dsim as ud\n",
    "u = ud.u #  import the pint unit registry from udkm1Dsim\n",
    "import scipy.constants as constants\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "u.setup_matplotlib() #  use matplotlib with pint units"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Structure\n",
    "\n",
    "Refere to the [structure-example](structure.ipynb) for more details."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "O = ud.Atom('O')\n",
    "Ti = ud.Atom('Ti')\n",
    "Sr = ud.Atom('Sr')\n",
    "Ru = ud.Atom('Ru')\n",
    "Pb = ud.Atom('Pb')\n",
    "Zr = ud.Atom('Zr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# c-axis lattice constants of the two layers\n",
    "c_STO_sub = 3.905*u.angstrom\n",
    "c_SRO = 3.94897*u.angstrom\n",
    "# sound velocities [nm/ps] of the two layers\n",
    "sv_SRO = 6.312*u.nm/u.ps\n",
    "sv_STO = 7.800*u.nm/u.ps\n",
    "\n",
    "# SRO layer\n",
    "prop_SRO = {}\n",
    "prop_SRO['a_axis'] = c_STO_sub # aAxis\n",
    "prop_SRO['b_axis'] = c_STO_sub # bAxis\n",
    "prop_SRO['deb_Wal_Fac'] = 0 # Debye-Waller factor\n",
    "prop_SRO['sound_vel'] = sv_SRO # sound velocity\n",
    "prop_SRO['opt_ref_index'] = 2.44+4.32j\n",
    "prop_SRO['therm_cond'] = 5.72*u.W/(u.m *u.K) # heat conductivity\n",
    "prop_SRO['lin_therm_exp'] = 1.03e-5 # linear thermal expansion\n",
    "prop_SRO['heat_capacity'] = 'lambda T: 455.2 + 0.112*T - 2.1935e6/T**2' # heat capacity [J/kg K]\n",
    "\n",
    "SRO = ud.UnitCell('SRO', 'Strontium Ruthenate', c_SRO, **prop_SRO)\n",
    "SRO.add_atom(O, 0)\n",
    "SRO.add_atom(Sr, 0)\n",
    "SRO.add_atom(O, 0.5)\n",
    "SRO.add_atom(O, 0.5)\n",
    "SRO.add_atom(Ru, 0.5)\n",
    "\n",
    "# STO substrate\n",
    "prop_STO_sub = {}\n",
    "prop_STO_sub['a_axis'] = c_STO_sub # aAxis\n",
    "prop_STO_sub['b_axis'] = c_STO_sub # bAxis\n",
    "prop_STO_sub['deb_Wal_Fac'] = 0 # Debye-Waller factor\n",
    "prop_STO_sub['sound_vel'] = sv_STO # sound velocity\n",
    "prop_STO_sub['opt_ref_index'] = 2.1+0j\n",
    "prop_STO_sub['therm_cond'] = 12*u.W/(u.m *u.K) # heat conductivity\n",
    "prop_STO_sub['lin_therm_exp'] = 1e-5 # linear thermal expansion\n",
    "prop_STO_sub['heat_capacity'] = 'lambda T: 733.73 + 0.0248*T - 6.531e6/T**2' # heat capacity [J/kg K]\n",
    "    \n",
    "STO_sub = ud.UnitCell('STOsub', 'Strontium Titanate Substrate', c_STO_sub, **prop_STO_sub)\n",
    "STO_sub.add_atom(O, 0)\n",
    "STO_sub.add_atom(Sr, 0)\n",
    "STO_sub.add_atom(O, 0.5)\n",
    "STO_sub.add_atom(O, 0.5)\n",
    "STO_sub.add_atom(Ti, 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "S = ud.Structure('Single Layer')\n",
    "S.add_sub_structure(SRO, 100) # add 100 layers of SRO to sample\n",
    "S.add_sub_structure(STO_sub, 200) # add 200 layers of STO substrate"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize Heat\n",
    "\n",
    "The `Heat` class requires a `Structure` object and a boolean `force_recalc` in order overwrite previous simulation results.\n",
    "\n",
    "These results are saved in the `cache_dir` when `save_data` is enabled.\n",
    "Printing simulation messages can be en-/disabled using `disp_messages` and progress bars can using the boolean switch `progress_bar`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Heat simulation properties:\n",
      "\n",
      "This is the current structure for the simulations:\n",
      "\n",
      "Structure properties:\n",
      "\n",
      "Name   : Single Layer\n",
      "Thickness : 117.59 nanometer\n",
      "Roughness : 0.00 nanometer\n",
      "----\n",
      "100 times Strontium Ruthenate: 39.49 nanometer\n",
      "200 times Strontium Titanate Substrate: 78.10 nanometer\n",
      "----\n",
      "no substrate\n",
      "\n",
      "\n",
      "Display properties:\n",
      "\n",
      "================================  =======================================================\n",
      "                       parameter  value\n",
      "================================  =======================================================\n",
      "                    force recalc  True\n",
      "                 cache directory  ./\n",
      "                display messages  True\n",
      "                       save data  False\n",
      "                    progress bar  True\n",
      "              excitation fluence  [] mJ/cm²\n",
      "                excitation delay  [0.0] ps\n",
      "         excitation pulse length  [0.0] ps\n",
      "           excitation wavelength  799.9999999999999 nm\n",
      "                excitation theta  90.0 deg\n",
      "excitation multilayer absorption  True\n",
      "                  heat diffusion  False\n",
      "       interpolate at interfaces  11\n",
      "                         backend  scipy\n",
      "                       distances  no distance mesh is set for heat diffusion calculations\n",
      "               top boundary type  isolator\n",
      "            bottom boundary type  isolator\n",
      "================================  =======================================================\n"
     ]
    }
   ],
   "source": [
    "h = ud.Heat(S, True)\n",
    "\n",
    "h.save_data = False\n",
    "h.disp_messages = True\n",
    "\n",
    "print(h)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Excitation\n",
    "\n",
    "In order to calculate the temperature of the sample after quasi-instantanious (delta) photoexcitation the `excitation` must be set with the following parameters:\n",
    "* `fluence`\n",
    "* `delay_pump`\n",
    "* `pulse_width`\n",
    "* `multilayer_absorption`\n",
    "* `wavelength`\n",
    "* `theta`\n",
    "\n",
    "The `wavelength` and `theta` angle of the excitation are only relevant if `multilayer_absorption = True`.\n",
    "Otherwise the _Lambert_Beer_-law is used.  \n",
    "__Note:__ the `fluence`, `delay_pump`, and `pulse_width` must be given as `array` or `list`.\n",
    "\n",
    "The simulation requires also a `delay` array as temporal grid as well as an initial temperature `init_temp`.\n",
    "The later can be either a scalar which is then the constant temperature of the whole sample structure, or the initial temperature can be an array of temperatures for each single layer in the structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\schick\\general\\python\\wpy64-3770\\python-3.7.7.amd64\\lib\\site-packages\\pint\\quantity.py:1138: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  magnitude = magnitude_op(self._magnitude, other_magnitude)\n"
     ]
    }
   ],
   "source": [
    "h.excitation = {'fluence': [5]*u.mJ/u.cm**2,\n",
    "                'delay_pump':  [0]*u.ps,\n",
    "                'pulse_width':  [0]*u.ps,\n",
    "                'multilayer_absorption': True,\n",
    "                'wavelength': 800*u.nm,\n",
    "                'theta': 45*u.deg}\n",
    "\n",
    "# when calculating the laser absorption profile using Lamber-Beer-law\n",
    "# the opt_pen_depth must be set manually or calculated from the refractive index\n",
    "SRO.set_opt_pen_depth_from_ref_index(800*u.nm)\n",
    "STO_sub.set_opt_pen_depth_from_ref_index(800*u.nm)\n",
    "\n",
    "# temporal and spatial grid\n",
    "delays = np.r_[-10:200:0.1]*u.ps\n",
    "_, _, distances = S.get_distances_of_layers()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Laser Absorption Profile\n",
    "\n",
    "Here the difference in the spatial laser absorption profile is shown between the multilayer absorption algorithm and the Lamber-Beer law.  \n",
    "Note that Lambert-Beer does not include reflection of the incident light from the surface of the sample structure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "dAdz, _, _, _ = h.get_multilayers_absorption_profile()\n",
    "plt.plot(distances.to('nm'), dAdz, label='multilayer')\n",
    "dAdz = h.get_Lambert_Beer_absorption_profile()\n",
    "plt.plot(distances.to('nm'), dAdz, label='Lamber-Beer')\n",
    "plt.legend()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Differnetial Absorption')\n",
    "plt.title('Laser Absorption Profile')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Temperature Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time for _temperature_after_delta_excitation_: 0.015956 s\n",
      "Elapsed time for _temp_map_: 0.087948 s\n"
     ]
    }
   ],
   "source": [
    "temp_map, delta_temp = h.get_temp_map(delays, 300*u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[101, :])\n",
    "plt.xlim([0, distances.to('nm').magnitude[-1]])\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.title('Temperature Profile')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heat Diffusion\n",
    "\n",
    "In order to enable heat diffusion the boolean switch `heat_diffusion` must be `True`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time for _temperature_after_delta_excitation_: 0.014962 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c4c8de98d8fa4703a1ffab934aedc700",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 6.501284 s\n",
      "Elapsed time for _temp_map_: 6.611260 s\n"
     ]
    }
   ],
   "source": [
    "# enable heat diffusion\n",
    "h.heat_diffusion = True\n",
    "# set the boundary conditions\n",
    "h.boundary_conditions = {'top_type': 'isolator', 'bottom_type': 'isolator'}\n",
    "# The resulting temperature profile is calculated in one line:\n",
    "temp_map, delta_temp = h.get_temp_map(delays, 300*u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[101, :], label=np.round(delays[101]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[501, :], label=np.round(delays[501]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[-1, :], label=np.round(delays[-1]))\n",
    "plt.xlim([0, distances.to('nm').magnitude[-1]])\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.legend()\n",
    "plt.title('Temperature Profile with Heat Diffusion')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map with Heat Diffusion')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Heat Diffusion Paramters\n",
    "\n",
    "For heat diffusion simulations various parameters for the underlying pdepe solver can be altered.\n",
    "\n",
    "By default, the `backend` is set to `scipy` but can be switched to `matlab`.\n",
    "Currently, the is no obvious reason to choose _MATLAB_ above _SciPy_.\n",
    "\n",
    "Depending on the `backend` either the `ode_options` or `ode_options_matlab` can be configured and are directly handed to the actual solver.\n",
    "Please refere to the documentation of the actual backend and solver and the __API documentation__ for more details.\n",
    "\n",
    "The speed but also the result of the heat diffusion simulation strongly depends on the spatial grid handed to the solver.\n",
    "By default, one spatial grid point is used for every `Layer` (`AmorphousLayer` or `UnitCell`) in the `Structure`.\n",
    "The resulting `temp_map` will also always be interpolated in this spatial grid which is equivalent to the distance vector returned by `S.get_distances_of_layers()`.\n",
    "\n",
    "As the solver for the heat diffusion usually suffers from large gradients, e.g. of thermal properties or initial temperatures, additional spatial grid points are added by default only for internal calculations.\n",
    "The number of additional points (should be an odd number, default is 11) is set by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "h.intp_at_interface = 11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The internally used spatial grid can be returned by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "dist_interp, original_indicies = S.interp_distance_at_interfaces(h.intp_at_interface)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The internal spatial grid can also be given by hand, e.g. to realize logarithmic steps for rather large `Structure`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "h.distances = np.linspace(0, distances.magnitude[-1], 100)*u.m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As already shown above, the heat diffusion simulation supports also an top and bottom  boundary condition. The can have the types:\n",
    "* `isolator`\n",
    "* `temperature`\n",
    "* `flux`\n",
    "\n",
    "For the later types also a value must be provides:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Heat simulation properties:\n",
      "\n",
      "This is the current structure for the simulations:\n",
      "\n",
      "Structure properties:\n",
      "\n",
      "Name   : Single Layer\n",
      "Thickness : 117.59 nanometer\n",
      "Roughness : 0.00 nanometer\n",
      "----\n",
      "100 times Strontium Ruthenate: 39.49 nanometer\n",
      "200 times Strontium Titanate Substrate: 78.10 nanometer\n",
      "----\n",
      "no substrate\n",
      "\n",
      "\n",
      "Display properties:\n",
      "\n",
      "================================  =======================================================\n",
      "                       parameter  value\n",
      "================================  =======================================================\n",
      "                    force recalc  True\n",
      "                 cache directory  ./\n",
      "                display messages  True\n",
      "                       save data  False\n",
      "                    progress bar  True\n",
      "              excitation fluence  [5.0] mJ/cm²\n",
      "                excitation delay  [0.0] ps\n",
      "         excitation pulse length  [0.0] ps\n",
      "           excitation wavelength  800.0 nm\n",
      "                excitation theta  45.0 deg\n",
      "excitation multilayer absorption  True\n",
      "                  heat diffusion  True\n",
      "       interpolate at interfaces  11\n",
      "                         backend  scipy\n",
      "                       distances  a distance mesh is set for heat diffusion calculations.\n",
      "               top boundary type  temperature\n",
      "        top boundary temperature  500 K\n",
      "            bottom boundary type  flux\n",
      "            bottom boundary flux  500000000000.0 W/m²\n",
      "================================  =======================================================\n"
     ]
    }
   ],
   "source": [
    "h.boundary_conditions = {'top_type': 'temperature', 'top_value': 500*u.K,\n",
    "                         'bottom_type': 'flux', 'bottom_value': 5e11*u.W/u.m**2}\n",
    "\n",
    "print(h)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8d2688314b2641c187a05558bebd50f3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 0.791059 s\n",
      "Elapsed time for _temperature_after_delta_excitation_: 0.006981 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3e749e60e6d84b39a6dd416b2f68fb1d",
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       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 0.979264 s\n",
      "Elapsed time for _temp_map_: 1.830167 s\n"
     ]
    }
   ],
   "source": [
    "# The resulting temperature profile is calculated in one line:\n",
    "temp_map, delta_temp = h.get_temp_map(delays, 300*u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[101, :], label=np.round(delays[101]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[501, :], label=np.round(delays[501]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[-1, :], label=np.round(delays[-1]))\n",
    "plt.xlim([0, distances.to('nm').magnitude[-1]])\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.legend()\n",
    "plt.title('Temperature Profile with Heat Diffusion and BC')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map with Heat Diffusion and BC')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Multipulse Excitation\n",
    "\n",
    "As already stated above, also multiple pulses of variable fluence, pulse width and, delay are possible.\n",
    "\n",
    "The heat diffusion simulation automatically splits the calculation in parts with and without excitation and adjusts the initial temporal step width according to the pulse width.\n",
    "Hence the solver does not miss any excitation pulses when adjusting its temporal step size.\n",
    "\n",
    "The temporal laser pulse profile is always assumed to be gaussian and the pulse width must be given as FWHM:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "h.excitation = {'fluence': [5, 5, 5]*u.mJ/u.cm**2,\n",
    "                'delay_pump':  [0, 10, 20]*u.ps,\n",
    "                'pulse_width':  [0.1, 0.1, 0.1]*u.ps,\n",
    "                'multilayer_absorption': True,\n",
    "                'wavelength': 800*u.nm,\n",
    "                'theta': 45*u.deg}\n",
    "\n",
    "h.boundary_conditions = {'top_type': 'isolator', 'bottom_type': 'isolator'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating _heat_diffusion_ for excitation 1:1 ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c9b019601c2a4b1588ec43f62b57e7fb",
       "version_major": 2,
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      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 0.848871 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d41448c62c9a46f0b130266783e362f8",
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      },
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       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 0.648266 s\n",
      "Calculating _heat_diffusion_ for excitation 2:2 ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "41eb6b5a4ede4ae099bea181a84008ea",
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      },
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       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
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     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 0.613387 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cb72b8a7ea3b42b2813460ba12afce58",
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      },
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       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 0.519606 s\n",
      "Calculating _heat_diffusion_ for excitation 3:3 ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a8b1568159a64c7b8f6ab704b586387f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 0.543585 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4a4078517f8f4595b1c9b5fd77bff4c1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 0.692392 s\n",
      "Elapsed time for _temp_map_: 4.025329 s\n"
     ]
    }
   ],
   "source": [
    "# The resulting temperature profile is calculated in one line:\n",
    "temp_map, delta_temp = h.get_temp_map(delays, 300*u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[101, :], label=np.round(delays[101]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[201, :], label=np.round(delays[201]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[301, :], label=np.round(delays[301]))\n",
    "plt.plot(distances.to('nm').magnitude, temp_map[-1, :], label=np.round(delays[-1]))\n",
    "plt.xlim([0, distances.to('nm').magnitude[-1]])\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.legend()\n",
    "plt.title('Temperature Profile Multiplulse')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map)\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map Multiplulse')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## N-Temperature Model\n",
    "\n",
    "The heat diffusion is also capable of simulating an _N_-temperature model which is often applied to empirically simulate the energy flow between _electrons_, _phonons_, and _spins_.\n",
    "In order to run the _NTM_ all thermo-elastic properties must be given as a list of _N_ elements.\n",
    "In addition the `sub_system_coupling` must be provided in order to allow for energy-flow between the sub-systems.\n",
    "The actual external laser-excitation is always set to happen within the __first__ sub-system, which is usually the _electron_-system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# update the relevant thermo-elastic properties of the layers in the sample structure\n",
    "SRO.therm_cond = [0,\n",
    "                  5.72*u.W/(u.m *u.K)]\n",
    "SRO.lin_therm_exp = [1.03e-5,\n",
    "                     1.03e-5]\n",
    "SRO.heat_capacity = ['lambda T: 0.112*T',\n",
    "                     'lambda T: 455.2 - 2.1935e6/T**2']\n",
    "SRO.sub_system_coupling = ['lambda T: 5e17*(T[1]-T[0])',\n",
    "                           'lambda T: 5e17*(T[0]-T[1])']\n",
    "\n",
    "STO_sub.therm_cond = [0,\n",
    "                      12*u.W/(u.m *u.K)]\n",
    "STO_sub.lin_therm_exp = [1e-5,\n",
    "                         1e-5]\n",
    "STO_sub.heat_capacity = ['lambda T: 0.0248*T',\n",
    "                         'lambda T: 733.73 - 6.531e6/T**2']\n",
    "STO_sub.sub_system_coupling = ['lambda T: 5e17*(T[1]-T[0])',\n",
    "                               'lambda T: 5e17*(T[0]-T[1])']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As no new `Structure` is build, the `num_sub_systems` must be updated by hand.\n",
    "Otherwise this happens automatically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "S.num_sub_systems = 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set the exciation conditions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "h.excitation = {'fluence': [5]*u.mJ/u.cm**2,\n",
    "                'delay_pump':  [0]*u.ps,\n",
    "                'pulse_width':  [0.25]*u.ps,\n",
    "                'multilayer_absorption': True,\n",
    "                'wavelength': 800*u.nm,\n",
    "                'theta': 45*u.deg}\n",
    "\n",
    "h.boundary_conditions = {'top_type': 'isolator', 'bottom_type': 'isolator'}\n",
    "\n",
    "delays = np.r_[-5:15:0.01]*u.ps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating _heat_diffusion_ for excitation 1:1 ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2788d4306d334a7b88bc58e1a853e71e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_ with 1 excitation(s): 2.053165 s\n",
      "Calculating _heat_diffusion_ ...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d730ce3266674ee6998b3805fd234192",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Elapsed time for _heat_diffusion_: 2.248610 s\n",
      "Elapsed time for _temp_map_: 4.445906 s\n"
     ]
    }
   ],
   "source": [
    "# The resulting temperature profile is calculated in one line:\n",
    "temp_map, delta_temp = h.get_temp_map(delays, 300*u.K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[6, 8])\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 0])\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map Electrons')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.pcolormesh(distances.to('nm').magnitude, delays.to('ps').magnitude, temp_map[:, :, 1])\n",
    "plt.colorbar()\n",
    "plt.xlabel('Distance [nm]')\n",
    "plt.ylabel('Delay [ps]')\n",
    "plt.title('Temperature Map Phonons')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(delays.to('ps'), np.mean(temp_map[:, S.get_all_positions_per_unique_layer()['SRO'], 0], 1), label='SRO electrons')\n",
    "plt.plot(delays.to('ps'), np.mean(temp_map[:, S.get_all_positions_per_unique_layer()['SRO'], 1], 1), label='SRO phonons')\n",
    "plt.ylabel('Temperature [K]')\n",
    "plt.xlabel('Delay [ps]')\n",
    "plt.legend()\n",
    "plt.title('Temperature Electrons vs. Phonons')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.7.7"
  },
  "toc-autonumbering": true
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
