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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Overview\n",
"\n",
"This a notebook that inspects the results of a WarpX simulation.\n",
"\n",
"# Instructions\n",
"\n",
"Execute the cells below one by one, by selecting them with your mouse and typing `Shift + Enter`"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# Import statements\n",
"import sys\n",
"from tqdm import tqdm\n",
"import yt, glob\n",
"yt.funcs.mylog.setLevel(50)\n",
"from IPython.display import clear_output\n",
"import numpy as np\n",
"from ipywidgets import interact, RadioButtons, IntSlider\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib\n",
"\n",
"# Find iterations\n",
"file_list = glob.glob('plt?????')\n",
"iterations = [ int(file_name[3:]) for file_name in file_list ]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Functions to plot the fields"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"def plot_field( iteration, field, slicing_direction='y', plotter='matplotlib' ):\n",
" ds = yt.load( './plt%05d/' %iteration )\n",
" all_data_level_0 = ds.covering_grid(level=0, \n",
" left_edge=ds.domain_left_edge, dims=ds.domain_dimensions)\n",
" \n",
" if plotter == 'yt':\n",
" sl = yt.SlicePlot(ds, slicing_direction, field)\n",
" sl.set_log( field, False)\n",
" sl.annotate_grids()\n",
" # Show the new plot\n",
" clear_output()\n",
" sl.show()\n",
"\n",
" elif plotter == 'matplotlib':\n",
"\n",
" left_edge = ds.domain_left_edge.convert_to_mks()*1.e6\n",
" right_edge = ds.domain_right_edge.convert_to_mks()*1.e6\n",
" \n",
" if slicing_direction == 'x':\n",
" n = int( ds.domain_dimensions[0]//2 )\n",
" data2d = all_data_level_0[field][n, :, :]\n",
" extent = [ left_edge[2], right_edge[2], left_edge[1], right_edge[1] ]\n",
" elif slicing_direction == 'y':\n",
" n = int( ds.domain_dimensions[1]//2 )\n",
" data2d = all_data_level_0[field][:, n, :]\n",
" extent = [ left_edge[2], right_edge[2], left_edge[0], right_edge[0] ]\n",
" elif slicing_direction == 'z':\n",
" n = int( ds.domain_dimensions[2]//2 )\n",
" data2d = all_data_level_0[field][:, :, n]\n",
" extent = [ left_edge[1], right_edge[1], left_edge[0], right_edge[0] ]\n",
" plt.clf()\n",
" plt.title(\"%s at iteration %d\" %(field, iteration) )\n",
" plt.imshow( data2d, interpolation='nearest', cmap='viridis',\n",
" origin='lower', extent=extent, aspect='auto' )\n",
" plt.colorbar()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Interactive viewer"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"interact(plot_field, \n",
" iteration = IntSlider(min=min(iterations), max=max(iterations), step=iterations[1]-iterations[0]),\n",
" field = RadioButtons( options=['jx', 'jy', 'jz', 'Ex', 'Ey', 'Ez'], value='jz'),\n",
" slicing_direction = RadioButtons( options=[ 'x', 'y', 'z'], value='y'),\n",
" plotter = RadioButtons( options=['matplotlib', 'yt'] ) )"
]
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [default]",
"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": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
|
