Response to Scott's email

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 "metadata": {
  "name": "Response to swolk email"
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     "language": "python",
     "metadata": {},
     "outputs": [
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       "stream": "stdout",
       "text": "Auto-detected table type: fits\nAuto-detected table type: fits"
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
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       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
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      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: ipac\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: ipac\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 3.5"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 3.5"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 3\nCase 3.5"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1\nCase 1\nCase 1\nCase 3.5\nCase 3.5\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nCase 1"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\nAuto-detected table type: fits"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "\n"
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# How many stars were considered in the analysis? We threw out any star that didn't have at least 50 detections in at least one band.\nminimum",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 2,
       "text": "<Table name='None' rows=14728 fields=156>"
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# How many stars would be considered variables if we ignored quality cuts? Only a subset (less than half!) of these stars are considered variables.\nmaxvars",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 3,
       "text": "<Table name='None' rows=3141 fields=156>"
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# What are the faintest magnitudes seen among the stars considered in our analysis?\n\nprint minimum.j_max.max()\nprint minimum.h_max.max()\nprint minimum.k_max.max()",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "20.848110199\n20.2637691498\n19.4341564178\n"
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# What are the largest errorbars in that whole dataset?\n\nprint minimum.j_rms.max()\nprint minimum.h_rms.max()\nprint minimum.k_rms.max()",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "1.30606272299\n1.3895023629\n0.935794026545\n"
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
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   "metadata": {}
  }
 ]
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