{
 "metadata": {
  "name": "Stars"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "tau = 2.0 * pi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import ephem\n",
      "from ephem.stars import stars"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(stars)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "starlist = stars.values()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for star in starlist:\n",
      "    star.compute('2012/1/10')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "degree = tau / 360.0\n",
      "hour = tau / 24.0\n",
      "\n",
      "ra_list = [star.ra / hour for star in starlist]\n",
      "dec_list = [star.dec / degree for star in starlist]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list)\n",
      "gca().invert_xaxis()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list)\n",
      "axis([7.5, 3.5, -20, 20])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "orion_axes = [7.5, 3.5, -20, 20]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print starlist[0].name\n",
      "print starlist[0].mag\n",
      "print starlist[0]._spect"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "[star.mag for star in starlist[:5]]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mag_array = np.array([ star.mag for star in starlist ])\n",
      "mag_array[:5]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "size_array = (5 - mag_array) ** 1.5 * 4\n",
      "size_array[:5]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list, size_array)\n",
      "axis(orion_axes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "spectral_list = [star._spect for star in starlist]\n",
      "spectral_list[:10]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from spectral_classification import build_color_chart\n",
      "color_chart = build_color_chart('starcolors.txt')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "color_list = [color_chart[spectral_class + '(V)']\n",
      "              for spectral_class in spectral_list]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list, size_array, color_list)\n",
      "axis(orion_axes)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def pretty_hours(h, pos=None):\n",
      "    if h % 1.0 == 0.0:\n",
      "        return '{:.0g}h'.format(h)\n",
      "    else:\n",
      "        return '{:.2g}h'.format(h)\n",
      "\n",
      "def pretty_degrees(d, pos=None):\n",
      "    return u'{}\u00b0'.format(d)\n",
      "\n",
      "print pretty_hours(3.5)\n",
      "print pretty_hours(5.0)\n",
      "print pretty_degrees(125)\n",
      "print pretty_degrees(360)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from matplotlib.ticker import FuncFormatter\n",
      "\n",
      "hours_formatter = FuncFormatter(pretty_hours)\n",
      "degrees_formatter = FuncFormatter(pretty_degrees)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list, size_array, color_list)\n",
      "axis(orion_axes)\n",
      "gca().xaxis.set_major_formatter(hours_formatter)\n",
      "gca().yaxis.set_major_formatter(degrees_formatter)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "scatter(ra_list, dec_list, size_array, color_list)\n",
      "axis(orion_axes)\n",
      "gca().xaxis.set_major_formatter(hours_formatter)\n",
      "gca().yaxis.set_major_formatter(degrees_formatter)\n",
      "gca().xaxis.grid(True)\n",
      "gca().yaxis.grid(True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}