OpenMC/docs/source/pythonapi/examples/post-processing.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebook demonstrates some basic post-processing tasks that can be performed with the Python API, such as plotting a 2D mesh tally and plotting neutron source sites from an eigenvalue calculation. The problem we will use is a simple reflected pin-cell."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"from IPython.display import Image\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import openmc"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generate Input Files"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"First we need to define materials that will be used in the problem. Before defining a material, we must create nuclides that are used in the material."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Instantiate some Nuclides\n",
"h1 = openmc.Nuclide('H-1')\n",
"b10 = openmc.Nuclide('B-10')\n",
"o16 = openmc.Nuclide('O-16')\n",
"u235 = openmc.Nuclide('U-235')\n",
"u238 = openmc.Nuclide('U-238')\n",
"zr90 = openmc.Nuclide('Zr-90')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With the nuclides we defined, we will now create three materials for the fuel, water, and cladding of the fuel pin."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# 1.6 enriched fuel\n",
"fuel = openmc.Material(name='1.6% Fuel')\n",
"fuel.set_density('g/cm3', 10.31341)\n",
"fuel.add_nuclide(u235, 3.7503e-4)\n",
"fuel.add_nuclide(u238, 2.2625e-2)\n",
"fuel.add_nuclide(o16, 4.6007e-2)\n",
"\n",
"# borated water\n",
"water = openmc.Material(name='Borated Water')\n",
"water.set_density('g/cm3', 0.740582)\n",
"water.add_nuclide(h1, 4.9457e-2)\n",
"water.add_nuclide(o16, 2.4732e-2)\n",
"water.add_nuclide(b10, 8.0042e-6)\n",
"\n",
"# zircaloy\n",
"zircaloy = openmc.Material(name='Zircaloy')\n",
"zircaloy.set_density('g/cm3', 6.55)\n",
"zircaloy.add_nuclide(zr90, 7.2758e-3)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With our three materials, we can now create a materials file object that can be exported to an actual XML file."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Instantiate a MaterialsFile, add Materials\n",
"materials_file = openmc.MaterialsFile()\n",
"materials_file.add_material(fuel)\n",
"materials_file.add_material(water)\n",
"materials_file.add_material(zircaloy)\n",
"materials_file.default_xs = '71c'\n",
"\n",
"# Export to \"materials.xml\"\n",
"materials_file.export_to_xml()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's move on to the geometry. Our problem will have three regions for the fuel, the clad, and the surrounding coolant. The first step is to create the bounding surfaces -- in this case two cylinders and six reflective planes."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Create cylinders for the fuel and clad\n",
"fuel_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.39218)\n",
"clad_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.45720)\n",
"\n",
"# Create boundary planes to surround the geometry\n",
"# Use both reflective and vacuum boundaries to make life interesting\n",
"min_x = openmc.XPlane(x0=-0.63, boundary_type='reflective')\n",
"max_x = openmc.XPlane(x0=+0.63, boundary_type='reflective')\n",
"min_y = openmc.YPlane(y0=-0.63, boundary_type='reflective')\n",
"max_y = openmc.YPlane(y0=+0.63, boundary_type='reflective')\n",
"min_z = openmc.ZPlane(z0=-0.63, boundary_type='reflective')\n",
"max_z = openmc.ZPlane(z0=+0.63, boundary_type='reflective')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With the surfaces defined, we can now create cells that are defined by intersections of half-spaces created by the surfaces."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Create a Universe to encapsulate a fuel pin\n",
"pin_cell_universe = openmc.Universe(name='1.6% Fuel Pin')\n",
"\n",
"# Create fuel Cell\n",
"fuel_cell = openmc.Cell(name='1.6% Fuel')\n",
"fuel_cell.fill = fuel\n",
"fuel_cell.region = -fuel_outer_radius\n",
"pin_cell_universe.add_cell(fuel_cell)\n",
"\n",
"# Create a clad Cell\n",
"clad_cell = openmc.Cell(name='1.6% Clad')\n",
"clad_cell.fill = zircaloy\n",
"clad_cell.region = +fuel_outer_radius & -clad_outer_radius\n",
"pin_cell_universe.add_cell(clad_cell)\n",
"\n",
"# Create a moderator Cell\n",
"moderator_cell = openmc.Cell(name='1.6% Moderator')\n",
"moderator_cell.fill = water\n",
"moderator_cell.region = +clad_outer_radius\n",
"pin_cell_universe.add_cell(moderator_cell)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"OpenMC requires that there is a \"root\" universe. Let us create a root cell that is filled by the pin cell universe and then assign it to the root universe."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Create root Cell\n",
"root_cell = openmc.Cell(name='root cell')\n",
"root_cell.fill = pin_cell_universe\n",
"\n",
"# Add boundary planes\n",
"root_cell.region = +min_x & -max_x & +min_y & -max_y & +min_z & -max_z\n",
"\n",
"# Create root Universe\n",
"root_universe = openmc.Universe(universe_id=0, name='root universe')\n",
"root_universe.add_cell(root_cell)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We now must create a geometry that is assigned a root universe, put the geometry into a geometry file, and export it to XML."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Create Geometry and set root Universe\n",
"geometry = openmc.Geometry()\n",
"geometry.root_universe = root_universe"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Instantiate a GeometryFile\n",
"geometry_file = openmc.GeometryFile()\n",
"geometry_file.geometry = geometry\n",
"\n",
"# Export to \"geometry.xml\"\n",
"geometry_file.export_to_xml()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With the geometry and materials finished, we now just need to define simulation parameters. In this case, we will use 10 inactive batches and 90 active batches each with 5000 particles."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# OpenMC simulation parameters\n",
"batches = 100\n",
"inactive = 10\n",
"particles = 5000\n",
"\n",
"# Instantiate a SettingsFile\n",
"settings_file = openmc.SettingsFile()\n",
"settings_file.batches = batches\n",
"settings_file.inactive = inactive\n",
"settings_file.particles = particles\n",
"\n",
"# Create an initial uniform spatial source distribution over fissionable zones\n",
"bounds = [-0.63, -0.63, -0.63, 0.63, 0.63, 0.63]\n",
"uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)\n",
"settings_file.source = openmc.source.Source(space=uniform_dist)\n",
"\n",
"# Export to \"settings.xml\"\n",
"settings_file.export_to_xml()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us also create a plot file that we can use to verify that our pin cell geometry was created successfully."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Instantiate a Plot\n",
"plot = openmc.Plot(plot_id=1)\n",
"plot.filename = 'materials-xy'\n",
"plot.origin = [0, 0, 0]\n",
"plot.width = [1.26, 1.26]\n",
"plot.pixels = [250, 250]\n",
"plot.color = 'mat'\n",
"\n",
"# Instantiate a PlotsFile, add Plot, and export to \"plots.xml\"\n",
"plot_file = openmc.PlotsFile()\n",
"plot_file.add_plot(plot)\n",
"plot_file.export_to_xml()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With the plots.xml file, we can now generate and view the plot. OpenMC outputs plots in .ppm format, which can be converted into a compressed format like .png with the convert utility."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Run openmc in plotting mode\n",
"executor = openmc.Executor()\n",
"executor.plot_geometry(output=False)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAPoAAAD6AgMAAAD1grKuAAAABGdBTUEAALGPC/xhBQAAAAFzUkdC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\nVDExOjMyOjU1LTA0OjAwoL4U5gAAAABJRU5ErkJggg==\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Convert OpenMC's funky ppm to png\n",
"!convert materials-xy.ppm materials-xy.png\n",
"\n",
"# Display the materials plot inline\n",
"Image(filename='materials-xy.png')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As we can see from the plot, we have a nice pin cell with fuel, cladding, and water! Before we run our simulation, we need to tell the code what we want to tally. The following code shows how to create a 2D mesh tally."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Instantiate an empty TalliesFile\n",
"tallies_file = openmc.TalliesFile()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Create mesh which will be used for tally\n",
"mesh = openmc.Mesh()\n",
"mesh.dimension = [100, 100]\n",
"mesh.lower_left = [-0.63, -0.63]\n",
"mesh.upper_right = [0.63, 0.63]\n",
"tallies_file.add_mesh(mesh)\n",
"\n",
"# Create mesh filter for tally\n",
"mesh_filter = openmc.Filter(type='mesh', bins=[1])\n",
"mesh_filter.mesh = mesh\n",
"\n",
"# Create mesh tally to score flux and fission rate\n",
"tally = openmc.Tally(name='flux')\n",
"tally.filters = [mesh_filter]\n",
"tally.scores = ['flux', 'fission']\n",
"tallies_file.add_tally(tally)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Export to \"tallies.xml\"\n",
"tallies_file.export_to_xml()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we a have a complete set of inputs, so we can go ahead and run our simulation."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
" .d88888b. 888b d888 .d8888b.\n",
" d88P\" \"Y88b 8888b d8888 d88P Y88b\n",
" 888 888 88888b.d88888 888 888\n",
" 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n",
" 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n",
" 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n",
" Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n",
" \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n",
"__________________888______________________________________________________\n",
" 888\n",
" 888\n",
"\n",
" Copyright: 2011-2015 Massachusetts Institute of Technology\n",
" License: http://mit-crpg.github.io/openmc/license.html\n",
" Version: 0.7.1\n",
" Git SHA1: eeb5091ca3a34cc85df73a3318cae2b6c7097413\n",
" Date/Time: 2016-04-13 11:32:56\n",
" MPI Processes: 1\n",
"\n",
" ===========================================================================\n",
" ========================> INITIALIZATION <=========================\n",
" ===========================================================================\n",
"\n",
" Reading settings XML file...\n",
" Reading cross sections XML file...\n",
" Reading geometry XML file...\n",
" Reading materials XML file...\n",
" Reading tallies XML file...\n",
" Building neighboring cells lists for each surface...\n",
" Loading ACE cross section table: 92235.71c\n",
" Loading ACE cross section table: 92238.71c\n",
" Loading ACE cross section table: 8016.71c\n",
" Loading ACE cross section table: 1001.71c\n",
" Loading ACE cross section table: 5010.71c\n",
" Loading ACE cross section table: 40090.71c\n",
" Maximum neutron transport energy: 20.0000 MeV for 92235.71c\n",
" Initializing source particles...\n",
"\n",
" ===========================================================================\n",
" ====================> K EIGENVALUE SIMULATION <====================\n",
" ===========================================================================\n",
"\n",
" Bat./Gen. k Average k \n",
" ========= ======== ==================== \n",
" 1/1 1.04359 \n",
" 2/1 1.04244 \n",
" 3/1 1.03020 \n",
" 4/1 1.03630 \n",
" 5/1 1.06478 \n",
" 6/1 1.05450 \n",
" 7/1 1.02369 \n",
" 8/1 1.03614 \n",
" 9/1 1.05193 \n",
" 10/1 1.02886 \n",
" 11/1 1.05011 \n",
" 12/1 1.04597 1.04804 +/- 0.00207\n",
" 13/1 1.07035 1.05548 +/- 0.00753\n",
" 14/1 1.06150 1.05698 +/- 0.00554\n",
" 15/1 1.07094 1.05977 +/- 0.00512\n",
" 16/1 1.05131 1.05836 +/- 0.00441\n",
" 17/1 1.04733 1.05679 +/- 0.00405\n",
" 18/1 1.08130 1.05985 +/- 0.00465\n",
" 19/1 1.02559 1.05605 +/- 0.00560\n",
" 20/1 1.03399 1.05384 +/- 0.00547\n",
" 21/1 1.04617 1.05314 +/- 0.00500\n",
" 22/1 1.06981 1.05453 +/- 0.00477\n",
" 23/1 1.05270 1.05439 +/- 0.00439\n",
" 24/1 1.02487 1.05228 +/- 0.00458\n",
" 25/1 1.05905 1.05273 +/- 0.00429\n",
" 26/1 1.07658 1.05422 +/- 0.00428\n",
" 27/1 1.03455 1.05307 +/- 0.00418\n",
" 28/1 1.00971 1.05066 +/- 0.00462\n",
" 29/1 1.06111 1.05121 +/- 0.00440\n",
" 30/1 1.01777 1.04954 +/- 0.00450\n",
" 31/1 1.04718 1.04942 +/- 0.00428\n",
" 32/1 1.03340 1.04870 +/- 0.00415\n",
" 33/1 1.04570 1.04857 +/- 0.00397\n",
" 34/1 1.02728 1.04768 +/- 0.00390\n",
" 35/1 1.02852 1.04691 +/- 0.00382\n",
" 36/1 1.03242 1.04636 +/- 0.00371\n",
" 37/1 1.01479 1.04519 +/- 0.00376\n",
" 38/1 1.06045 1.04573 +/- 0.00366\n",
" 39/1 1.03810 1.04547 +/- 0.00354\n",
" 40/1 1.05281 1.04571 +/- 0.00343\n",
" 41/1 1.03941 1.04551 +/- 0.00332\n",
" 42/1 1.04049 1.04535 +/- 0.00322\n",
" 43/1 1.04586 1.04537 +/- 0.00312\n",
" 44/1 1.05437 1.04563 +/- 0.00304\n",
" 45/1 1.03445 1.04531 +/- 0.00297\n",
" 46/1 1.05104 1.04547 +/- 0.00289\n",
" 47/1 1.00773 1.04445 +/- 0.00299\n",
" 48/1 1.06879 1.04509 +/- 0.00298\n",
" 49/1 1.06625 1.04564 +/- 0.00295\n",
" 50/1 1.02641 1.04515 +/- 0.00292\n",
" 51/1 1.05701 1.04544 +/- 0.00286\n",
" 52/1 1.02868 1.04504 +/- 0.00282\n",
" 53/1 1.04592 1.04506 +/- 0.00275\n",
" 54/1 1.05757 1.04535 +/- 0.00271\n",
" 55/1 1.02329 1.04486 +/- 0.00269\n",
" 56/1 1.04116 1.04478 +/- 0.00263\n",
" 57/1 1.01990 1.04425 +/- 0.00263\n",
" 58/1 1.06202 1.04462 +/- 0.00260\n",
" 59/1 1.03550 1.04443 +/- 0.00255\n",
" 60/1 1.01383 1.04382 +/- 0.00258\n",
" 61/1 1.04111 1.04377 +/- 0.00253\n",
" 62/1 1.02061 1.04332 +/- 0.00252\n",
" 63/1 1.00456 1.04259 +/- 0.00257\n",
" 64/1 1.02277 1.04222 +/- 0.00255\n",
" 65/1 1.04544 1.04228 +/- 0.00251\n",
" 66/1 1.04487 1.04233 +/- 0.00246\n",
" 67/1 1.02699 1.04206 +/- 0.00243\n",
" 68/1 1.06160 1.04240 +/- 0.00241\n",
" 69/1 1.02989 1.04218 +/- 0.00238\n",
" 70/1 1.03107 1.04200 +/- 0.00235\n",
" 71/1 1.06571 1.04239 +/- 0.00234\n",
" 72/1 1.03444 1.04226 +/- 0.00231\n",
" 73/1 1.05059 1.04239 +/- 0.00228\n",
" 74/1 1.03352 1.04225 +/- 0.00224\n",
" 75/1 1.03707 1.04217 +/- 0.00221\n",
" 76/1 1.02994 1.04199 +/- 0.00219\n",
" 77/1 1.05416 1.04217 +/- 0.00216\n",
" 78/1 1.03794 1.04211 +/- 0.00213\n",
" 79/1 1.04652 1.04217 +/- 0.00210\n",
" 80/1 1.05715 1.04239 +/- 0.00208\n",
" 81/1 1.08146 1.04294 +/- 0.00212\n",
" 82/1 1.02159 1.04264 +/- 0.00211\n",
" 83/1 1.01968 1.04233 +/- 0.00211\n",
" 84/1 1.05577 1.04251 +/- 0.00209\n",
" 85/1 1.07808 1.04298 +/- 0.00211\n",
" 86/1 1.03943 1.04293 +/- 0.00209\n",
" 87/1 1.03431 1.04282 +/- 0.00206\n",
" 88/1 1.02414 1.04258 +/- 0.00205\n",
" 89/1 1.02316 1.04234 +/- 0.00204\n",
" 90/1 1.03342 1.04223 +/- 0.00202\n",
" 91/1 1.02781 1.04205 +/- 0.00200\n",
" 92/1 1.01293 1.04169 +/- 0.00201\n",
" 93/1 1.04347 1.04171 +/- 0.00198\n",
" 94/1 1.05357 1.04186 +/- 0.00196\n",
" 95/1 1.04740 1.04192 +/- 0.00194\n",
" 96/1 1.05215 1.04204 +/- 0.00192\n",
" 97/1 1.06667 1.04232 +/- 0.00192\n",
" 98/1 1.04926 1.04240 +/- 0.00190\n",
" 99/1 1.05386 1.04253 +/- 0.00188\n",
" 100/1 1.05088 1.04262 +/- 0.00186\n",
" Creating state point statepoint.100.h5...\n",
"\n",
" ===========================================================================\n",
" ======================> SIMULATION FINISHED <======================\n",
" ===========================================================================\n",
"\n",
"\n",
" =======================> TIMING STATISTICS <=======================\n",
"\n",
" Total time for initialization = 3.8100E-01 seconds\n",
" Reading cross sections = 8.6000E-02 seconds\n",
" Total time in simulation = 2.4400E+02 seconds\n",
" Time in transport only = 2.4395E+02 seconds\n",
" Time in inactive batches = 8.3260E+00 seconds\n",
" Time in active batches = 2.3567E+02 seconds\n",
" Time synchronizing fission bank = 1.6000E-02 seconds\n",
" Sampling source sites = 6.0000E-03 seconds\n",
" SEND/RECV source sites = 7.0000E-03 seconds\n",
" Time accumulating tallies = 1.9000E-02 seconds\n",
" Total time for finalization = 1.7400E-01 seconds\n",
" Total time elapsed = 2.4458E+02 seconds\n",
" Calculation Rate (inactive) = 6005.28 neutrons/second\n",
" Calculation Rate (active) = 1909.46 neutrons/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.04214 +/- 0.00161\n",
" k-effective (Track-length) = 1.04262 +/- 0.00186\n",
" k-effective (Absorption) = 1.04338 +/- 0.00158\n",
" Combined k-effective = 1.04278 +/- 0.00122\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n"
]
},
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Run OpenMC!\n",
"executor.run_simulation()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Tally Data Processing"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our simulation ran successfully and created a statepoint file with all the tally data in it. We begin our analysis here loading the statepoint file and 'reading' the results. By default, data from the statepoint file is only read into memory when it is requested. This helps keep the memory use to a minimum even when a statepoint file may be huge."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [],
"source": [
"# Load the statepoint file\n",
"sp = openmc.StatePoint('statepoint.100.h5')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next we need to get the tally, which can be done with the ``StatePoint.get_tally(...)`` method."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tally\n",
"\tID =\t10000\n",
"\tName =\t\n",
"\tFilters =\t\n",
" \t\tmesh\t[10000]\n",
"\tNuclides =\ttotal \n",
"\tScores =\t[u'flux', u'fission']\n",
"\tEstimator =\ttracklength\n",
"\n"
]
}
],
"source": [
"tally = sp.get_tally(scores=['flux'])\n",
"print(tally)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The statepoint file actually stores the sum and sum-of-squares for each tally bin from which the mean and variance can be calculated as described [here](http://mit-crpg.github.io/openmc/methods/tallies.html#variance). The sum and sum-of-squares can be accessed using the ``sum`` and ``sum_sq`` properties:"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([[[ 0.40945685, 0. ]],\n",
"\n",
" [[ 0.40939021, 0. ]],\n",
"\n",
" [[ 0.410625 , 0. ]],\n",
"\n",
" ..., \n",
" [[ 0.41130501, 0. ]],\n",
"\n",
" [[ 0.41228849, 0. ]],\n",
"\n",
" [[ 0.41420317, 0. ]]])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tally.sum"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"However, the mean and standard deviation of the mean are usually what you are more interested in. The Tally class also has properties ``mean`` and ``std_dev`` which automatically calculate these statistics on-the-fly."
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(10000, 1, 2)\n"
]
},
{
"data": {
"text/plain": [
"(array([[[ 0.00454952, 0. ]],\n",
" \n",
" [[ 0.00454878, 0. ]],\n",
" \n",
" [[ 0.0045625 , 0. ]],\n",
" \n",
" ..., \n",
" [[ 0.00457006, 0. ]],\n",
" \n",
" [[ 0.00458098, 0. ]],\n",
" \n",
" [[ 0.00460226, 0. ]]]),\n",
" array([[[ 1.64748193e-05, 0.00000000e+00]],\n",
" \n",
" [[ 1.70922989e-05, 0.00000000e+00]],\n",
" \n",
" [[ 1.67622385e-05, 0.00000000e+00]],\n",
" \n",
" ..., \n",
" [[ 1.69274948e-05, 0.00000000e+00]],\n",
" \n",
" [[ 1.57842763e-05, 0.00000000e+00]],\n",
" \n",
" [[ 2.06590062e-05, 0.00000000e+00]]]))"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print(tally.mean.shape)\n",
"(tally.mean, tally.std_dev)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The tally data has three dimensions: one for filter combinations, one for nuclides, and one for scores. We see that there are 10000 filter combinations (corresponding to the 100 x 100 mesh bins), a single nuclide (since none was specified), and two scores. If we only want to look at a single score, we can use the ``get_slice(...)`` method as follows."
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Tally\n",
"\tID =\t10001\n",
"\tName =\t\n",
"\tFilters =\t\n",
" \t\tmesh\t[10000]\n",
"\tNuclides =\ttotal \n",
"\tScores =\t[u'flux']\n",
"\tEstimator =\ttracklength\n",
"\n"
]
}
],
"source": [
"flux = tally.get_slice(scores=['flux'])\n",
"fission = tally.get_slice(scores=['fission'])\n",
"print(flux)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"To get the bins into a form that we can plot, we can simply change the shape of the array since it is a numpy array."
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"flux.std_dev.shape = (100, 100)\n",
"flux.mean.shape = (100, 100)\n",
"fission.std_dev.shape = (100, 100)\n",
"fission.mean.shape = (100, 100)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f34aaaf5a10>"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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dHYwxnwF+tv9cfcZSuEhS5aY53cGpqRLyYEtZLtFQm9jTLhqLe0EU5dVUATOh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\nRK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f34ab420910>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = plt.subplot(121)\n",
"fig.imshow(flux.mean)\n",
"fig2 = plt.subplot(122)\n",
"fig2.imshow(fission.mean)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's say we want to look at the distribution of relative errors of our tally bins for flux. First we create a new variable called ``relative_error`` and set it to the ratio of the standard deviation and the mean, being careful not to divide by zero in case some bins were never scored to."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7f34ab3eb410>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Determine relative error\n",
"relative_error = np.zeros_like(flux.std_dev)\n",
"nonzero = flux.mean > 0\n",
"relative_error[nonzero] = flux.std_dev[nonzero] / flux.mean[nonzero]\n",
"\n",
"# distribution of relative errors\n",
"ret = plt.hist(relative_error[nonzero], bins=50)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Source Sites"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Source sites can be accessed from the ``source`` property. As shown below, the source sites are represented as a numpy array with a structured datatype."
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ (1.0, [-0.1382758052991497, -0.3512177196880901, -0.33148352853135243], [0.4185689312254184, 0.515870835450486, -0.7474472094699589], 0.12980877137486158, 0),\n",
" (1.0, [-0.1382758052991497, -0.3512177196880901, -0.33148352853135243], [-0.7887279871402189, -0.41474066458733805, -0.4537602268152112], 0.9055673129689725, 0),\n",
" (1.0, [-0.037141545763691594, 0.3164763430804079, -0.13705878399440294], [0.3855911650385466, 0.7867859791128493, -0.48196190359368796], 0.996776361155944, 0),\n",
" ...,\n",
" (1.0, [0.10735654583359178, -0.007276312264885898, -0.05173760352485271], [0.5349120379020222, -0.015907381482490993, 0.8447579931091957], 0.8409377635712494, 0),\n",
" (1.0, [-0.048566216245400286, 0.29160532148505824, 0.31942717397594755], [0.6200960701401188, -0.409911862042636, 0.6689193741801173], 3.8787384499997857, 0),\n",
" (1.0, [0.07888442268099938, -0.14443885526015943, 0.3095767587545024], [0.373899151360205, 0.18819594431853104, 0.9081749342247754], 4.776147593645684, 0)], \n",
" dtype=[('wgt', '<f8'), ('xyz', '<f8', (3,)), ('uvw', '<f8', (3,)), ('E', '<f8'), ('delayed_group', '<i4')])"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sp.source"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we want, say, only the energies from the source sites, we can simply index the source array with the name of the field:"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([ 0.12980877, 0.90556731, 0.99677636, ..., 0.84093776,\n",
" 3.87873845, 4.77614759])"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sp.source['E']"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now, we can look at things like the energy distribution of source sites. Note that we don't directly use the ``matplotlib.pyplot.hist`` method since our binning is logarithmic."
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1.0\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x7f34aa95d7d0>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<matplotlib.figure.Figure at 0x7f34aaa2fcd0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Create log-spaced energy bins from 1 keV to 100 MeV\n",
"energy_bins = np.logspace(-3,1)\n",
"\n",
"# Calculate pdf for source energies\n",
"probability, bin_edges = np.histogram(sp.source['E'], energy_bins, density=True)\n",
"\n",
"# Make sure integrating the PDF gives us unity\n",
"print(sum(probability*np.diff(energy_bins)))\n",
"\n",
"# Plot source energy PDF\n",
"plt.semilogx(energy_bins[:-1], probability*np.diff(energy_bins), linestyle='steps')\n",
"plt.xlabel('Energy (MeV)')\n",
"plt.ylabel('Probability/MeV')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's also look at the spatial distribution of the sites. To make the plot a little more interesting, we can also include the direction of the particle emitted from the source and color each source by the logarithm of its energy."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"(-0.5, 0.5)"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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f4IwNxcCDBBQ9PrtKeqEFpeeTVHnX4DRG0sP2ME0UU8VWZNcO5OZtQhnsQ1et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\nbZVKpTqB/D+F7yW5gV7LfQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f34aa99aa90>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.quiver(sp.source['xyz'][:,0], sp.source['xyz'][:,1],\n",
" sp.source['uvw'][:,0], sp.source['uvw'][:,1],\n",
" np.log(sp.source['E']), cmap='jet', scale=20.0)\n",
"plt.colorbar()\n",
"plt.xlim((-0.5,0.5))\n",
"plt.ylim((-0.5,0.5))"
]
}
],
"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": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 0
}