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  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Reading CTD data with CoTeDe"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Author: Guilherme Castel\u00e3o"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Description ToDo"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "\n",
      "from cotede.qc import fProfileQC"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let's first download an example file with some CTD data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!wget https://raw.githubusercontent.com/castelao/seabird/master/tests/test_data/dPIRX003.cnv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "--2015-03-31 15:47:26--  https://raw.githubusercontent.com/castelao/seabird/master/tests/test_data/dPIRX003.cnv\r\n",
        "Resolving raw.githubusercontent.com... "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "199.27.74.133\r\n",
        "Connecting to raw.githubusercontent.com|199.27.74.133|:443... "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "connected.\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "HTTP request sent, awaiting response... "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "200 OK\r\n",
        "Length: 47291 (46K) [text/plain]\r\n",
        "Saving to: 'dPIRX003.cnv'\r\n",
        "\r\n",
        "\r",
        "dPIRX003.cnv       0%[                      ]       0  --.-KB/s             "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "dPIRX003.cnv     100%[=====================>]  46.18K   261KB/s   in 0.2s   \r\n",
        "\r\n",
        "2015-03-31 15:47:27 (261 KB/s) - 'dPIRX003.cnv' saved [47291/47291]\r\n",
        "\r\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Loading and processing the data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc = fProfileQC('dPIRX003.cnv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using rules from: cnv.yaml\n",
        "evaluating:  temperature temperature\n",
        "evaluating: "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " temperature2 temperature\n",
        "evaluating: "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " salinity salinity\n",
        "evaluating: "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " salinity2 salinity\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The file dPIRX003.cnv was parsed with the default rules cnv.yaml by PySeabird. \n",
      "Than, the temperature and salinity data, from the primary and secondary sensors were evaluated by the default Quality Control rules."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Checking the attributes (header) of the CTD input file"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc.attributes"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "{'bad_flag': '-9.990e-29',\n",
        " 'datetime': datetime.datetime(2008, 4, 2, 18, 52, 30),\n",
        " 'file_type': 'ascii',\n",
        " 'filename': 'dPIRX003.cnv',\n",
        " 'latitude': 12.674333333333333,\n",
        " 'longitude': -38.00183333333333,\n",
        " 'md5': '4b941b902a3aea7d99e1cf4c78c51877',\n",
        " 'nquan': '11',\n",
        " 'nvalues': '349',\n",
        " 'seasave': 'Win32 V 5.37d',\n",
        " 'start_time': 'Apr 02 2008 18:52:30'}"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Printing the datetime of the profile"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print pqc.attributes['datetime']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "2008-04-02 18:52:30\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Checking the available variables"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc.keys()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "['timeS',\n",
        " 'pressure',\n",
        " 'temperature',\n",
        " 'temperature2',\n",
        " 'conductivity',\n",
        " 'conductivity2',\n",
        " 'potemperature',\n",
        " 'potemperature2',\n",
        " 'salinity',\n",
        " 'salinity2',\n",
        " 'flag']"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Accessing one specific variable"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The first 20 records of temperature"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc['temperature'][:20]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "masked_array(data = [15.8635 15.4798 15.3983 15.293 15.1721 15.0904 15.0685 15.0887 15.0373\n",
        " 15.0092 14.9356 14.8848 14.7707 14.7372 14.7144 14.7371 14.738 14.7466\n",
        " 14.7556 --],\n",
        "             mask = [False False False False False False False False False False False False\n",
        " False False False False False False False  True],\n",
        "       fill_value = -9.99e-29)"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The Q.C. flags are stored at pqc.flags and is a dictionary, being one item per variable evaluated. For example, to see the flags for the secondary salinity instrument, just do"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc.flags['salinity2'].keys()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "['global_range',\n",
        " 'gradient_depthconditional',\n",
        " 'gradient',\n",
        " 'digit_roll_over',\n",
        " 'tukey53H_norm',\n",
        " 'woa_comparison',\n",
        " 'spike',\n",
        " 'spike_depthconditional']"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To check the gradient test flag for the first 20ths records:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pqc.flags['salinity2']['gradient'][:20]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "array([0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 9], dtype=int8)"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from matplotlib import pyplot as plt\n",
      "\n",
      "plt.plot(pqc['temperature'], pqc['pressure'],'b')\n",
      "plt.plot(pqc['temperature2'], pqc['pressure'],'g')\n",
      "plt.gca().invert_yaxis()\n",
      "plt.xlabel('temperature')\n",
      "plt.ylabel('pressure')\n",
      "plt.title(pqc.attributes['filename'])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "<matplotlib.text.Text at 0x11403d810>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Sqy/JuG8+NarUiDqSizMvDs65/Rr71Vp6P3872ckTGXXt/7wwlBNeHJxz+5SbC5e8cBPd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\nNIt5e9Nw3w8MHjx473ZaWhp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       "text": [
        "<matplotlib.figure.Figure at 0x113c13690>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}