{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating fusion source with AFSI\n",
    "\n",
    "This example shows how to create a fusion source with AFSI in various cases.\n",
    "\n",
    "AFSI (Ascot Fusion Source Integrator) calculates the 5D distributions of fusion reaction products based on the 5D distributions of the reactants.\n",
    "The algorithm iterates over all cells in cylindrical coordinates, and on each location creates fusion products via Monte Carlo sampling.\n",
    "First, a pair of markers is sampled from the reactant (velocity) distributions and the velocities of the fusion products for a given reaction are calculated using the initial velocities.\n",
    "The reaction probability, which depends on the relative velocity between the reactants, is used to weight the products which in turn are used to calculate the 5D distributions for the output.\n",
    "Several pairs are created before the algorithm proceeds to the next cylindrical cell.\n",
    "\n",
    "The Monte Carlo sampling makes AFSI capable of not only calculating reactions for thermal (Maxwellian) species but for arbitrary distributions.\n",
    "In practice this often means NBI slowing-down distributions and, hence, the arbitrary distribution is referred to as ``beam`` when working with AFSI.\n",
    "\n",
    "Note that AFSI calculates the distributions for both products, i.e., one can use AFSI to calculate the neutron source as well.\n",
    "\n",
    "AFSI has three modes of operation based on what the inputs are:\n",
    "\n",
    "- ``thermal`` calculates the fusion products for two Maxwellian species.\n",
    "  The population can also react itself as is the case with D-D fusion.\n",
    "- ``beam-thermal`` calculates the fusion products for a Maxwellian species that is interacting with an arbitrary distribution.\n",
    "- ``beam-beam`` calculates the fusion products for two arbitrary distributions.\n",
    "  A distribution can interact with itself, e.g. if there is a single deuterium beam.\n",
    " \n",
    "AFSI requires only the magnetic field and plasma data for it to work, but we also need to get the beam ion distribution somewhere for this tutorial.\n",
    "The following cell initializes the inputs and runs a short slowing-down simulation for a deuterium beam.\n",
    "Its contents are not relevant for this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:01.743146Z",
     "iopub.status.busy": "2025-04-14T13:13:01.742973Z",
     "iopub.status.idle": "2025-04-14T13:13:15.098613Z",
     "shell.execute_reply": "2025-04-14T13:13:15.098086Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ASCOT5_MAIN\n",
      "Tag 37c8483\n",
      "Branch docs\n",
      "\n",
      "Initialized MPI, rank 0, size 1.\n",
      "\n",
      "Reading and initializing input.\n",
      "\n",
      "Input file is ascot.h5.\n",
      "\n",
      "Reading options input.\n",
      "Active QID is 3374861502\n",
      "Options read and initialized.\n",
      "\n",
      "Reading magnetic field input.\n",
      "Active QID is 3441897426\n",
      "\n",
      "Analytical tokamak magnetic field (B_GS)\n",
      "Psi at magnetic axis (6.618 m, -0.000 m)\n",
      "-5.410 (evaluated)\n",
      "-5.410 (given)\n",
      "Magnetic field on axis:\n",
      "B_R = 0.000 B_phi = 4.965 B_z = -0.000\n",
      "Number of toroidal field coils 0\n",
      "Magnetic field read and initialized.\n",
      "\n",
      "Reading electric field input.\n",
      "Active QID is 3768711148\n",
      "\n",
      "Trivial Cartesian electric field (E_TC)\n",
      "E_x = 0.000000e+00, E_y = 0.000000e+00, E_z = 0.000000e+00\n",
      "Electric field read and initialized.\n",
      "\n",
      "Reading plasma input.\n",
      "Active QID is 2749263616\n",
      "\n",
      "1D plasma profiles (P_1D)\n",
      "Min rho = 0.00e+00, Max rho = 2.00e+00, Number of rho grid points = 101, Number of ion species = 2\n",
      "Species Z/A  charge [e]/mass [amu] Density [m^-3] at Min/Max rho    Temperature [eV] at Min/Max rho\n",
      "   1  /  2     1  /  2.014             1.00e+21/1.00e+00                1.00e+04/1.00e+04       \n",
      "   1  /  3     1  /  3.016             1.00e+21/1.00e+00                1.00e+04/1.00e+04       \n",
      "[electrons]   -1  /  0.001             2.00e+21/1.00e+00                1.00e+04/1.00e+04       \n",
      "Toroidal rotation [rad/s] at Min/Max rho: 0.00e+00/0.00e+00\n",
      "Quasi-neutrality is (electron / ion charge density) 2.00\n",
      "Toroidal rotation [rad/s] at Min/Max rho: 0.00e+00/0.00e+00\n",
      "Plasma data read and initialized.\n",
      "\n",
      "Reading neutral input.\n",
      "Active QID is 0286353851\n",
      "\n",
      "1D neutral density and temperature (N0_1D)\n",
      "Grid:  nrho =    3   rhomin = 0.000   rhomax = 2.000\n",
      " Number of neutral species = 1\n",
      "Species Z/A   (Maxwellian)\n",
      "        1/  1 (1)    \n",
      "Neutral data read and initialized.\n",
      "\n",
      "Reading wall input.\n",
      "Active QID is 1021600252\n",
      "\n",
      "2D wall model (wall_2D)\n",
      "Number of wall elements = 20, R extend = [4.10, 8.40], z extend = [-3.90, 3.90]\n",
      "Wall data read and initialized.\n",
      "\n",
      "Reading boozer input.\n",
      "Active QID is 4262271107\n",
      "\n",
      "Boozer input\n",
      "psi grid: n =    6 min = 0.000 max = 1.000\n",
      "thetageo grid: n =   18\n",
      "thetabzr grid: n =   10\n",
      "Boozer data read and initialized.\n",
      "\n",
      "Reading MHD input.\n",
      "Active QID is 3989567557\n",
      "\n",
      "MHD (stationary) input\n",
      "Grid: nrho =    6 rhomin = 0.000 rhomax = 1.000\n",
      "\n",
      "Modes:\n",
      "(n,m) = ( 1, 3) Amplitude = 0.1 Frequency =   1 Phase =   0\n",
      "(n,m) = ( 2, 4) Amplitude =   2 Frequency = 1.5 Phase = 0.785\n",
      "MHD data read and initialized.\n",
      "\n",
      "Reading atomic reaction input.\n",
      "Active QID is 1266838790\n",
      "\n",
      "Found data for 1 atomic reactions:\n",
      "Reaction number / Total number of reactions = 1 / 1\n",
      "  Reactant species Z_1 / A_1, Z_2 / A_2     = 0 / 0, 0 / 0\n",
      "  Min/Max energy                            = 1.00e+03 / 1.00e+04\n",
      "  Min/Max density                           = 1.00e+18 / 1.00e+20\n",
      "  Min/Max temperature                       = 1.00e+03 / 1.00e+04\n",
      "  Number of energy grid points              = 3\n",
      "  Number of density grid points             = 4\n",
      "  Number of temperature grid points         = 5\n",
      "Atomic reaction data read and initialized.\n",
      "\n",
      "Reading marker input.\n",
      "Active QID is 1747484544\n",
      "\n",
      "Loaded 100 guiding centers.\n",
      "Marker data read and initialized.\n",
      "\n",
      "All input read and initialized.\n",
      "\n",
      "Initializing marker states.\n",
      "Estimated memory usage 0.0 MB.\n",
      "Marker states initialized.\n",
      "\n",
      "Preparing output.\n",
      "Note: Output file ascot.h5 is already present.\n",
      "\n",
      "The qid of this run is 1690074440\n",
      "\n",
      "Inistate written.\n",
      "Simulation begins; 4 threads.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulation complete.\n",
      "Simulation finished in 11.316906 s\n",
      "Endstate written.\n",
      "\n",
      "Combining and writing diagnostics.\n",
      "\n",
      "Writing diagnostics output.\n",
      "\n",
      "Writing 5D distribution.\n",
      "\n",
      "Diagnostics output written.\n",
      "Diagnostics written.\n",
      "\n",
      "Summary of results:\n",
      "      100 markers had end condition Sim time limit\n",
      "\n",
      "          No markers were aborted.\n",
      "\n",
      "Done.\n",
      "Simulation complete"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from a5py import Ascot\n",
    "\n",
    "a5 = Ascot(\"ascot.h5\", create=True)\n",
    "\n",
    "a5.data.create_input(\"bfield analytical iter circular\", desc=\"ANALYTICAL\")\n",
    "\n",
    "# DT-plasma\n",
    "nrho  = 101\n",
    "rho   = np.linspace(0, 2, nrho).T\n",
    "prof  = (rho<=1)*(1.0 - rho**(3.0/2))**3 + 1e-6\n",
    "vtor  = np.zeros((nrho, 1))\n",
    "edens = 2e21 * prof\n",
    "etemp = 1e4  * np.ones((nrho, 1))\n",
    "idens = 1e21 * np.tile(prof,(2,1)).T\n",
    "itemp = 1e4  * np.ones((nrho, 1))\n",
    "\n",
    "edens[rho>=1]   = 1\n",
    "idens[rho>=1,:] = 1\n",
    "\n",
    "pls = {\n",
    "    \"nrho\" : nrho, \"nion\" : 2, \"rho\" : rho, \"vtor\": vtor,\n",
    "    \"anum\" : np.array([2, 3]), \"znum\" : np.array([1, 1]),\n",
    "    \"mass\" : np.array([2.014, 3.016]), \"charge\" : np.array([1, 1]),\n",
    "    \"edensity\" : edens, \"etemperature\" : etemp,\n",
    "    \"idensity\" : idens, \"itemperature\" : itemp}\n",
    "a5.data.create_input(\"plasma_1D\", **pls, desc=\"DT\")\n",
    "\n",
    "# These inputs are not relevant for AFSI\n",
    "a5.data.create_input(\"wall rectangular\")\n",
    "a5.data.create_input(\"E_TC\")\n",
    "a5.data.create_input(\"N0_1D\")\n",
    "a5.data.create_input(\"Boozer\")\n",
    "a5.data.create_input(\"MHD_STAT\")\n",
    "a5.data.create_input(\"asigma_loc\")\n",
    "\n",
    "# Generate deuterium markers with Ekin=1MeV and run a short slowing down simulation.\n",
    "from a5py.ascot5io.marker import Marker\n",
    "mrk = Marker.generate(\"gc\", n=100, species=\"deuterium\")\n",
    "mrk[\"energy\"][:] = 1.0e6\n",
    "mrk[\"pitch\"][:]  = 0.99 - 0.2 * np.random.rand(100,)\n",
    "mrk[\"r\"][:]      = np.linspace(6.2, 7.2, 100)\n",
    "a5.data.create_input(\"gc\", **mrk)\n",
    "\n",
    "from a5py.ascot5io.options import Opt\n",
    "opt = Opt.get_default()\n",
    "opt.update({\n",
    "    \"SIM_MODE\":2, \"ENABLE_ADAPTIVE\":1,\n",
    "    \"ENDCOND_SIMTIMELIM\":1, \"ENDCOND_MAX_MILEAGE\":0.05,\n",
    "    \"ENABLE_ORBIT_FOLLOWING\":1, \"ENABLE_COULOMB_COLLISIONS\":1,\n",
    "    \"ENABLE_DIST_5D\":1,\n",
    "    \"DIST_MIN_R\":4.3,        \"DIST_MAX_R\":8.3,       \"DIST_NBIN_R\":50,\n",
    "    \"DIST_MIN_PHI\":0,        \"DIST_MAX_PHI\":360,     \"DIST_NBIN_PHI\":1,\n",
    "    \"DIST_MIN_Z\":-2.0,       \"DIST_MAX_Z\":2.0,       \"DIST_NBIN_Z\":50,\n",
    "    \"DIST_MIN_PPA\":-1.3e-19, \"DIST_MAX_PPA\":1.3e-19, \"DIST_NBIN_PPA\":100,\n",
    "    \"DIST_MIN_PPE\":0,        \"DIST_MAX_PPE\":1.3e-19, \"DIST_NBIN_PPE\":50,\n",
    "    \"DIST_MIN_TIME\":0,       \"DIST_MAX_TIME\":1.0,    \"DIST_NBIN_TIME\":1,\n",
    "    \"DIST_MIN_CHARGE\":1,     \"DIST_MAX_CHARGE\":3,    \"DIST_NBIN_CHARGE\":1,\n",
    "})\n",
    "a5.data.create_input(\"opt\", **opt, desc=\"SLOWINGDOWN\")\n",
    "\n",
    "import subprocess\n",
    "subprocess.run([\"./../../build/ascot5_main\", \"--d=\\\"BEAMSD\\\"\"])\n",
    "print(\"Simulation complete\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "AFSI is used via the ``Ascot`` object using the attribute ``afsi`` which has all the relevant methods.\n",
    "To use AFSI, we need to specify what reaction is that we are considering.\n",
    "To list possible reactions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:15.100609Z",
     "iopub.status.busy": "2025-04-14T13:13:15.100278Z",
     "iopub.status.idle": "2025-04-14T13:13:15.106073Z",
     "shell.execute_reply": "2025-04-14T13:13:15.105590Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['DT_He4n', 'DHe3_He4p', 'DD_Tp', 'DD_He3n'])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a5.afsi.reactions()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run AFSI on ``thermal`` mode, we need to specify $(R,z)$, and optionally $\\phi$, grid on which the distributions are calculated.\n",
    "Since both reactant populations are Maxwellian, there is no need to define velocity grids for those as AFSI can use the analytical distribution.\n",
    "Specifying the velocity grid for the products is required however.\n",
    "\n",
    "Once inputs are set, we can call ``thermal`` function that computes the product distributions for us."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:15.107683Z",
     "iopub.status.busy": "2025-04-14T13:13:15.107518Z",
     "iopub.status.idle": "2025-04-14T13:13:16.023078Z",
     "shell.execute_reply": "2025-04-14T13:13:16.022532Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<a5py.ascotpy.ascot2py.struct_c__SA_histogram at 0x7f8ec62fb840>,\n",
       " <a5py.ascotpy.ascot2py.struct_c__SA_histogram at 0x7f8ec416c0c0>)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grid spanning the whole plasma\n",
    "r = np.linspace(4.2, 8.2, 51)\n",
    "z = np.linspace(-2.0, 2.0, 51)\n",
    "ppar = np.linspace(-1.3e-19, 1.3e-19, 81)\n",
    "pperp = np.linspace(0, 1.3e-19, 41)\n",
    "\n",
    "# Run AFSI which creates a fusion alpha distribution\n",
    "a5.afsi.thermal(\n",
    "    \"DT_He4n\", nmc=1000, r=r, z=z,\n",
    "    ppar1=ppar, pperp1=pperp, ppar2=ppar, pperp2=pperp\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result is stored in the HDF5 file in a similar run group (found in ``a5.data``) as the ASCOT5 simulations are, and the group works in a similar manner.\n",
    "The group contains information on the magnetic field and plasma inputs that were used and provides methods to access the product distributions.\n",
    "However, now the distributions are called ``prod1`` and ``prod2`` instead of ``5d``, but they act exactly as a ``5d`` distribution would."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:16.024904Z",
     "iopub.status.busy": "2025-04-14T13:13:16.024699Z",
     "iopub.status.idle": "2025-04-14T13:13:16.709714Z",
     "shell.execute_reply": "2025-04-14T13:13:16.709071Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "alphadist = a5.data.active.getdist(\"prod1\")\n",
    "alphadist.integrate(time=np.s_[:], charge=np.s_[:]) # Distribution must be 5D\n",
    "\n",
    "rzdist  = alphadist.integrate(copy=True, phi=np.s_[:], ppar=np.s_[:], pperp=np.s_[:])\n",
    "momdist = alphadist.integrate(copy=True, phi=np.s_[:], r=np.s_[:], z=np.s_[:])\n",
    "\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "\n",
    "rzdist.plot(axes=ax1)\n",
    "momdist.plot(axes=ax2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The momentum space can either be $(p_\\parallel,p_\\perp)$ or $(E_\\mathrm{kin},\\xi=p_\\parallel/p)$.\n",
    "While the spatial grid must be the same for both products, the momentum grid can be different as long as the basis is the same.\n",
    "Here's the thermal fusion calculation redone using energy-pitch basis and computing alfas and neutrons using separate grids."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:16.711694Z",
     "iopub.status.busy": "2025-04-14T13:13:16.711339Z",
     "iopub.status.idle": "2025-04-14T13:13:17.814800Z",
     "shell.execute_reply": "2025-04-14T13:13:17.814166Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFSI5\n",
      "Tag 37c8483\n",
      "Branch docs\n",
      "\n",
      "Note: Output file /home/runner/work/ascot5/ascot5/doc/tutorials/ascot.h5 is already present.\n",
      "\n",
      "The qid of this run is 1483293914\n",
      "\n",
      "Done\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a5.afsi.thermal(\n",
    "    \"DT_He4n\", nmc=1000, r=r, z=z,\n",
    "    ekin1=np.linspace(1.5e6, 5.5e6, 20),\n",
    "    pitch1=np.linspace(-1, 1, 20),\n",
    "    ekin2=np.linspace(12.1e6, 16.1e6, 30),\n",
    "    pitch2=np.linspace(-1, 1, 30),\n",
    "    )\n",
    "\n",
    "alphadist = a5.data.active.getdist(\"prod1\")\n",
    "alphadist.integrate(time=np.s_[:], charge=np.s_[:], phi=np.s_[:], r=np.s_[:], z=np.s_[:])\n",
    "neutrondist = a5.data.active.getdist(\"prod2\")\n",
    "neutrondist.integrate(time=np.s_[:], charge=np.s_[:], phi=np.s_[:], r=np.s_[:], z=np.s_[:])\n",
    "\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "\n",
    "alphadist.plot(axes=ax1)\n",
    "neutrondist.plot(axes=ax2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For thermal reactants, one can use toroidal coordinates $(\\rho,\\theta,\\phi)$ as spatial grid, in which case the product distributions are also in toroidal coordinates.\n",
    "Using toroidal coordinates is especially useful for generating markers for stellarator simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:17.816691Z",
     "iopub.status.busy": "2025-04-14T13:13:17.816336Z",
     "iopub.status.idle": "2025-04-14T13:13:18.408780Z",
     "shell.execute_reply": "2025-04-14T13:13:18.408156Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFSI5\n",
      "Tag 37c8483\n",
      "Branch docs\n",
      "\n",
      "Note: Output file /home/runner/work/ascot5/ascot5/doc/tutorials/ascot.h5 is already present.\n",
      "\n",
      "The qid of this run is 0835726560\n",
      "\n",
      "Done\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a5.afsi.thermal(\n",
    "    \"DT_He4n\", nmc=1000,\n",
    "    rho=np.linspace(0, 1, 50),\n",
    "    theta=np.linspace(0, 360, 10),\n",
    "    )\n",
    "\n",
    "alphadist = a5.data.active.getdist(\"prod1\")\n",
    "alphadist.integrate(time=np.s_[:], charge=np.s_[:], phi=np.s_[:])\n",
    "\n",
    "rzdist  = alphadist.integrate(copy=True, ppar=np.s_[:], pperp=np.s_[:])\n",
    "momdist = alphadist.integrate(copy=True, rho=np.s_[:], theta=np.s_[:])\n",
    "\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "\n",
    "rzdist.plot(axes=ax1)\n",
    "momdist.plot(axes=ax2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we run the beam-thermal fusion between the deuterium beam (whose distribution was calculated earlier) and thermal deuterium.\n",
    "This time we use ``beamthermal`` function and provide the beam 5D function as an input.\n",
    "Note that this time we can't specify a cylindrical grid for the outputs, as the same grid is used as in the beam distribution.\n",
    "\n",
    "The results is again stored as a new run from which the data is read as usual.\n",
    "Take a note how the product distribution is strongly anisotropic; the product velocities consists of both the kinetic energy released in the reaction and the (beam) velocity that the reactants had."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:18.410863Z",
     "iopub.status.busy": "2025-04-14T13:13:18.410399Z",
     "iopub.status.idle": "2025-04-14T13:13:46.438953Z",
     "shell.execute_reply": "2025-04-14T13:13:46.438281Z"
    },
    "nbsphinx-thumbnail": {
     "tooltip": "This tooltip message was defined in cell metadata"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFSI5\n",
      "Tag 37c8483\n",
      "Branch docs\n",
      "\n",
      "Note: Output file /home/runner/work/ascot5/ascot5/doc/tutorials/ascot.h5 is already present.\n",
      "\n",
      "The qid of this run is 0465468306\n",
      "\n",
      "Done\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "beamdist = a5.data.BEAMSD.getdist(\"5d\")\n",
    "a5.afsi.beamthermal(\"DD_Tp\", beamdist, swap=True)\n",
    "\n",
    "alphadist = a5.data.active.getdist(\"prod1\", exi=True, ekin_edges=20, pitch_edges=10)\n",
    "rzdist  = alphadist.integrate(copy=True, phi=np.s_[:], ekin=np.s_[:], pitch=np.s_[:])\n",
    "exidist = alphadist.integrate(copy=True, phi=np.s_[:], r=np.s_[:], z=np.s_[:])\n",
    "\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "\n",
    "rzdist.plot(axes=ax1)\n",
    "exidist.plot(axes=ax2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we demonstrate the beam-beam fusion.\n",
    "Providing the ``beambeam`` function with just a single distribution calculates the fusion product for the beam interacting with itself.\n",
    "The other beam would be provided with ``beam2`` argument (which must have the same abscissae as the first beam distribution)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-04-14T13:13:46.440931Z",
     "iopub.status.busy": "2025-04-14T13:13:46.440518Z",
     "iopub.status.idle": "2025-04-14T13:14:14.667806Z",
     "shell.execute_reply": "2025-04-14T13:14:14.667209Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AFSI5\n",
      "Tag 37c8483\n",
      "Branch docs\n",
      "\n",
      "Note: Output file /home/runner/work/ascot5/ascot5/doc/tutorials/ascot.h5 is already present.\n",
      "\n",
      "The qid of this run is 0230518065\n",
      "\n",
      "Done\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a5 = Ascot(\"ascot.h5\")\n",
    "beamdist = a5.data.BEAMSD.getdist(\"5d\")\n",
    "a5.afsi.beambeam(\"DD_Tp\", beamdist)\n",
    "\n",
    "alphadist = a5.data.active.getdist(\"prod1\", exi=True, ekin_edges=20, pitch_edges=10)\n",
    "alphadist.integrate(time=np.s_[:], charge=np.s_[:]) # Distribution must be 5D\n",
    "\n",
    "rzdist  = alphadist.integrate(copy=True, phi=np.s_[:], ekin=np.s_[:], pitch=np.s_[:])\n",
    "exidist = alphadist.integrate(copy=True, phi=np.s_[:], r=np.s_[:], z=np.s_[:])\n",
    "\n",
    "fig = plt.figure(figsize=(10,5))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "\n",
    "rzdist.plot(axes=ax1)\n",
    "exidist.plot(axes=ax2)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.17"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}