/Untitled21.ipynb

## Untitled21.ipynb
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "yt : [INFO     ] 2016-02-16 17:49:35,976 Parameters: current_time              = 0.00600002000283\n",
      "yt : [INFO     ] 2016-02-16 17:49:35,976 Parameters: domain_dimensions         = [32 32 32]\n",
      "yt : [INFO     ] 2016-02-16 17:49:35,977 Parameters: domain_left_edge          = [ 0.  0.  0.]\n",
      "yt : [INFO     ] 2016-02-16 17:49:35,978 Parameters: domain_right_edge         = [ 1.  1.  1.]\n",
      "yt : [INFO     ] 2016-02-16 17:49:35,979 Parameters: cosmological_simulation   = 0.0\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import yt\n",
    "\n",
    "ds = yt.load('IsolatedGalaxy/galaxy0030/galaxy0030')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Parsing Hierarchy : 100%|██████████| 173/173 [00:00<00:00, 13106.02it/s]\n",
      "yt : [INFO     ] 2016-02-16 17:49:36,035 Gathering a field list (this may take a moment.)\n",
      "/Users/goldbaum/Documents/numpy/numpy/ma/core.py:3113: FutureWarning: Currently, slicing will try to return a view of the data, but will return a copy of the mask. In the future, it will try to return both as views.\n",
      "  FutureWarning\n"
     ]
    },
    {
     "data": {
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\"><br>"
      ],
      "text/plain": [
       "<yt.visualization.profile_plotter.ProfilePlot at 0x10aa42d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = yt.ProfilePlot(ds.all_data(), 'density', 'temperature')\n",
    "\n",
    "plot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# get reference to matplotlib axes object\n",
    "ax = plot.axes['gas', 'temperature']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "labels = ax.xaxis.get_ticklabels() + ax.yaxis.get_ticklabels()\n",
    "labels += [ax.title, ax.xaxis.label, ax.yaxis.label,\n",
    "           ax.xaxis.get_offset_text(), ax.yaxis.get_offset_text()]\n",
    "for label in labels:\n",
    "    label.set_fontsize(22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img style=\"max-width:100%%;max-height:100%%;\" 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\"><br>"
      ],
      "text/plain": [
       "<yt.visualization.profile_plotter.ProfilePlot at 0x10aa42d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}