sncosmo-introduction

{
 "metadata": {
  "name": "Introduction"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import sncosmo\n",
      "%pylab inline\n",
      "from matplotlib import pyplot as plt"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 52
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Models: Initializing"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model = sncosmo.get_model('salt2')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 53
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print model"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Model class: SALT2Model\n",
        "Model name: salt2\n",
        "Model version: 2.0\n",
        "Model phases: [-20, .., 50] days (71 points)\n",
        "Model dispersion: [2000, .., 9200] Angstroms (721 points) \n",
        "Reference phase: -0.58148 days\n",
        "Cosmology: WMAP9(H0=69.3, Om0=0.286, Ode0=0.713)\n",
        "Current Parameters:\n",
        "    fscale = 1.0\n",
        "    m = None [bessellb, ab]\n",
        "    mabs = None [bessellb, ab]\n",
        "    t0 = 0.0\n",
        "    z = None\n",
        "    c = 0.0\n",
        "    x1 = 0.0\n"
       ]
      }
     ],
     "prompt_number": 54
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Models: Accessing Spectral flux"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux(0., 4000.)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 55,
       "text": [
        "0.45198690190000013"
       ]
      }
     ],
     "prompt_number": 55
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux(0., [3000., 4000.])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 56,
       "text": [
        "array([ 0.14458496,  0.4519869 ])"
       ]
      }
     ],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux([0., 1.], [3000., 4000.])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 57,
       "text": [
        "array([[ 0.14458496,  0.4519869 ],\n",
        "       [ 0.13127263,  0.43813728]])"
       ]
      }
     ],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux(0.).shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 58,
       "text": [
        "(721,)"
       ]
      }
     ],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux(disp=4000.).shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 59,
       "text": [
        "(71, 1)"
       ]
      }
     ],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux().shape"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 60,
       "text": [
        "(71, 721)"
       ]
      }
     ],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(model.disp(), model.flux(-10.))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 61,
       "text": [
        "[<matplotlib.lines.Line2D at 0x3e09310>]"
       ]
      },
      {
       "output_type": "display_data",
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      }
     ],
     "prompt_number": 61
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Models: Setting parameters"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.parnames"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 62,
       "text": [
        "['fscale', 'm', 'mabs', 't0', 'z', 'c', 'x1']"
       ]
      }
     ],
     "prompt_number": 62
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.params"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 63,
       "text": [
        "OrderedDict([('fscale', 1.0), ('m', None), ('mabs', None), ('t0', 0.0), ('z', None), ('c', 0.0), ('x1', 0.0)])"
       ]
      }
     ],
     "prompt_number": 63
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.set(z=0.5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 64
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.params['z']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 65,
       "text": [
        "0.5"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.set(z=0.5, mabs=-19.5, x1=0.5, c=0.2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.set(**{'z': 0.5, 'mabs':-19.5, 'x1': 0.5, 'c':0.2})  # same thing as above"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print model"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Model class: SALT2Model\n",
        "Model name: salt2\n",
        "Model version: 2.0\n",
        "Model phases: [-20, .., 50] days (71 points)\n",
        "Model dispersion: [2000, .., 9200] Angstroms (721 points) \n",
        "Reference phase: -0.58148 days\n",
        "Cosmology: WMAP9(H0=69.3, Om0=0.286, Ode0=0.713)\n",
        "Current Parameters:\n",
        "    fscale = 1.20342088139e-17\n",
        "    m = 22.7925124979 [bessellb, ab]\n",
        "    mabs = -19.5 [bessellb, ab]\n",
        "    t0 = 0.0\n",
        "    z = 0.5 [dist. mod. = 42.2925, lum. dist. = 2874.1 Mpc]\n",
        "    c = 0.2\n",
        "    x1 = 0.5\n"
       ]
      }
     ],
     "prompt_number": 68
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.flux(0., [3000., 4000.])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 69,
       "text": [
        "array([  2.12553806e-30,   1.41092723e-19])"
       ]
      }
     ],
     "prompt_number": 69
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Bandpasses"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "band = sncosmo.Bandpass([4000., 4200., 4400., 4600., 4800., 5000.], \n",
      "                        [0., 1., 1., 1., 1., 0.], name='tophatg')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 70
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print band"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<Bandpass 'tophatg' at 0x3e0d110>\n"
       ]
      }
     ],
     "prompt_number": 71
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(band.disp, band.trans)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 72,
       "text": [
        "[<matplotlib.lines.Line2D at 0x406c710>]"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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TejLsac0CcBu379t7Muyff57WLAB3cXub1pNhzykcAG7j9jat58Ke1iwAt3LzVo7nwp7W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\n"
      }
     ],
     "prompt_number": 72
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "band = sncosmo.get_bandpass('sdssr')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 73
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(band.disp, band.trans)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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ZMwYYNAgI0tT4xfXz2Zi9zWZDREQEwsLCkJaWVucxzzzzDMLCwhATE4M9e/Y0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\nAyx7IiId+H/PfhkErUVN6QAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 74
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Magnitude Systems"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "magsys = sncosmo.ABMagSystem()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 75
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "magsys = sncosmo.get_magsystem('ab')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 76
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Model Synthetic Photometry"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.bandmag(band, magsys, [0., 10., 20.])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 77,
       "text": [
        "array([ 22.45817988,  22.78314817,  23.45016425])"
       ]
      }
     ],
     "prompt_number": 77
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.bandmag('sdssr', 'ab', [0., 10., 20.])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 78,
       "text": [
        "array([ 22.45817988,  22.78314817,  23.45016425])"
       ]
      }
     ],
     "prompt_number": 78
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.bandflux('sdssr', [0., 10., 20.]) # physical flux in photons/s/cm^2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 79,
       "text": [
        "array([ 0.00051287,  0.00038021,  0.00020569])"
       ]
      }
     ],
     "prompt_number": 79
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "model.bandflux('sdssr', [0., 10., 20.], zp=25., zpsys='ab') # flux scaled to desired zp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 80,
       "text": [
        "array([ 10.39269175,   7.70443389,   4.16806324])"
       ]
      }
     ],
     "prompt_number": 80
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 80
    }
   ],
   "metadata": {}
  }
 ]
}