Beginning of Chapter 4 of the MB Cookbook... using MB System for multibeam sonar data

mbcookbook2.ipynb

{
 "metadata": {
  "name": "mbcookbook2"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "4.4.1 Ancillary Files"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cd loihi"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/schwehr/Desktop/mbcookbook/loihi\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cd MBARI1998EM300"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/schwehr/Desktop/mbcookbook/loihi/MBARI1998EM300\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls -lh"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "total 285024\r\n",
        "-rw-r--r--  1 schwehr  5000   139B Nov 25  2002 README\r\n",
        "-rw-r--r--  1 schwehr  5000   234B Nov 25  2002 datalist.mb-1\r\n",
        "-rw-r--r--  1 schwehr  5000    30M Nov 25  2002 mbari_1998_53_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   8.9M Nov 25  2002 mbari_1998_54_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   5.9M Nov 25  2002 mbari_1998_55_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   3.6M Nov 25  2002 mbari_1998_56_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000    44M Nov 25  2002 mbari_1998_57_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   7.5M Nov 25  2002 mbari_1998_58_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   7.0M Nov 25  2002 mbari_1998_59_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000   5.7M Nov 25  2002 mbari_1998_60_msn.mb57\r\n",
        "-rw-r--r--  1 schwehr  5000    26M Nov 25  2002 mbari_1998_61_msn.mb57\r\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mbdatalist -I datalist.mb-1 -N"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "README                      mbari_1998_55_msn.mb57      mbari_1998_57_msn.mb57.fnv  mbari_1998_60_msn.mb57\r\n",
        "datalist.mb-1               mbari_1998_55_msn.mb57.fbt  mbari_1998_57_msn.mb57.inf  mbari_1998_60_msn.mb57.fbt\r\n",
        "mbari_1998_53_msn.mb57      mbari_1998_55_msn.mb57.fnv  mbari_1998_58_msn.mb57      mbari_1998_60_msn.mb57.fnv\r\n",
        "mbari_1998_53_msn.mb57.fbt  mbari_1998_55_msn.mb57.inf  mbari_1998_58_msn.mb57.fbt  mbari_1998_60_msn.mb57.inf\r\n",
        "mbari_1998_53_msn.mb57.fnv  mbari_1998_56_msn.mb57      mbari_1998_58_msn.mb57.fnv  mbari_1998_61_msn.mb57\r\n",
        "mbari_1998_53_msn.mb57.inf  mbari_1998_56_msn.mb57.fbt  mbari_1998_58_msn.mb57.inf  mbari_1998_61_msn.mb57.fbt\r\n",
        "mbari_1998_54_msn.mb57      mbari_1998_56_msn.mb57.fnv  mbari_1998_59_msn.mb57      mbari_1998_61_msn.mb57.fnv\r\n",
        "mbari_1998_54_msn.mb57.fbt  mbari_1998_56_msn.mb57.inf  mbari_1998_59_msn.mb57.fbt  mbari_1998_61_msn.mb57.inf\r\n",
        "mbari_1998_54_msn.mb57.fnv  mbari_1998_57_msn.mb57      mbari_1998_59_msn.mb57.fnv\r\n",
        "mbari_1998_54_msn.mb57.inf  mbari_1998_57_msn.mb57.fbt  mbari_1998_59_msn.mb57.inf\r\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "4.4.4 Surveying your Survey - Revisited"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mbm_plot -I datalist.mb-1 -N\n",
      "!./datalist.mb-1.cmd 2>&1 | tail -5\n",
      "!convert datalist.mb-1.{ps,png}\n",
      "imshow(imread('datalist.mb-1.png'), cmap=get_cmap('gray'))\n",
      "!open datalist.mb-1.ps"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r\n",
        "Plot generation shellscript <datalist.mb-1.cmd> created.\r\n",
        "\r\n",
        "Instructions:\r\n",
        "  Execute <datalist.mb-1.cmd> to generate Postscript plot <datalist.mb-1.ps>.\r\n",
        "  Executing <datalist.mb-1.cmd> also invokes ghostview to view the plot on the screen.\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Resetting GMT fonts...\r\n",
        "Running ghostview in background...\r\n",
        "[1] 92707\r\n",
        "All done!\r\n",
        "ghostview: Command not found.\r\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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JCXv37oVSqRRcq27SdOgMvYeHB/7880+N9UlJSVpfv3z5cixfvrzhlRGiJyZx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\n2EMAAAAASUVORK5CYII=\n"
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mbm_plot -F-1 -I datalist.mb-1 -N -R-155.33/-155.14/18.7/19.15\n",
      "!./datalist.mb-1.cmd 2>&1 | tail -5\n",
      "!convert datalist.mb-1.{ps,png}\n",
      "imshow(imread('datalist.mb-1.png'), cmap=get_cmap('gray'))\n",
      "# !open datalist.mb-1.ps"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r\n",
        "Plot generation shellscript <datalist.mb-1.cmd> created.\r\n",
        "\r\n",
        "Instructions:\r\n",
        "  Execute <datalist.mb-1.cmd> to generate Postscript plot <datalist.mb-1.ps>.\r\n",
        "  Executing <datalist.mb-1.cmd> also invokes ghostview to view the plot on the screen.\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Resetting GMT fonts...\r\n",
        "Running ghostview in background...\r\n",
        "[1] 93389\r\n",
        "All done!\r\n",
        "ghostview: Command not found.\r\n"
       ]
      },
      {
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "<matplotlib.image.AxesImage at 0x109454850>"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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9RmOmxZ07d2LOnDmQSCQQiUT45z//CalUiuDgYCQkJEAoFMoSuInFYgQHB0Ms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\nRK5CYII=\n"
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mbm_plot -I datalist.mb-1 -C -G1\n",
      "!./datalist.mb-1.cmd 2>&1 | tail -5\n",
      "!convert datalist.mb-1.{ps,png}\n",
      "imshow(imread('datalist.mb-1.png')) # , cmap=get_cmap('gray'))\n",
      "# !open datalist.mb-1.ps"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r\n",
        "Plot generation shellscript <datalist.mb-1.cmd> created.\r\n",
        "\r\n",
        "Instructions:\r\n",
        "  Execute <datalist.mb-1.cmd> to generate Postscript plot <datalist.mb-1.ps>.\r\n",
        "  Executing <datalist.mb-1.cmd> also invokes ghostview to view the plot on the screen.\r\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Resetting GMT fonts...\r\n",
        "Running ghostview in background...\r\n",
        "[1] 93483\r\n",
        "All done!\r\n",
        "ghostview: Command not found.\r\n"
       ]
      },
      {
       "output_type": "display_data",
       "png": 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vry+HDx8mOTkZf39/Jk2aZLz9KTLC0Vx+m/lTmufGMXoDIGGwVNNv6BYcyliz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\nBoCq9gL8d5/9e0YJ8gAAAABJRU5ErkJggg==\n"
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cd .."
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "/Users/schwehr/Desktop/mbcookbook/loihi"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!mbinfo -I MBARI1998EM300/datalist.mb-1 | grep -A 40 'Data Totals'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Data Totals:\r\n",
        "Number of Records:                        9917\r\n",
        "Bathymetry Data (135 beams):\r\n",
        "  Number of Beams:          1338795\r\n",
        "  Number of Good Beams:     1207888     90.22%\r\n",
        "  Number of Zero Beams:       79143      5.91%\r\n",
        "  Number of Flagged Beams:    51764      3.87%\r\n",
        "Amplitude Data (135 beams):\r\n",
        "  Number of Beams:          1338795\r\n",
        "  Number of Good Beams:     1207888     90.22%\r\n",
        "  Number of Zero Beams:       79143      5.91%\r\n",
        "  Number of Flagged Beams:    51764      3.87%\r\n",
        "Sidescan Data (1024 pixels):\r\n",
        "  Number of Pixels:        10155008\r\n",
        "  Number of Good Pixels:   10153984     99.99%\r\n",
        "  Number of Zero Pixels:          0      0.00%\r\n",
        "  Number of Flagged Pixels:    1024      0.01%\r\n",
        "\r\n",
        "Navigation Totals:\r\n",
        "Total Time:            15.4770 hours\r\n",
        "Total Track Length:   286.9084 km\r\n",
        "Average Speed:         18.5377 km/hr (10.0204 knots)\r\n",
        "\r\n",
        "Start of Data:\r\n",
        "Time:  03 02 1998 20:06:01.740000  JD61 (1998-03-02T20:06:01.740000)\r\n",
        "Lon:  -154.798805300     Lat:    19.473399550     Depth:  1000.6700 meters\r\n",
        "Speed:  0.0000 km/hr ( 0.0000 knots)  Heading: 243.2100 degrees\r\n",
        "Sonar Depth:    6.0700 m  Sonar Altitude:  994.6000 m\r\n",
        "\r\n",
        "End of Data:\r\n",
        "Time:  03 03 1998 11:34:38.985000  JD62 (1998-03-03T11:34:38.985000)\r\n",
        "Lon:  -154.793818600     Lat:    19.445800850     Depth:  1502.0900 meters\r\n",
        "Speed: 18.0000 km/hr ( 9.7297 knots)  Heading:  59.4300 degrees\r\n",
        "Sonar Depth:    5.0100 m  Sonar Altitude: 1497.0800 m\r\n",
        "\r\n",
        "Limits:\r\n",
        "Minimum Longitude:    -155.341233539   Maximum Longitude:    -154.778216873\r\n",
        "Minimum Latitude:       18.661225521   Maximum Latitude:       19.487286286\r\n",
        "Minimum Sonar Depth:     3.8700   Maximum Sonar Depth:     7.4600\r\n",
        "Minimum Altitude:      700.2800   Maximum Altitude:     4867.2000\r\n",
        "Minimum Depth:         331.8400   Maximum Depth:        4919.0700\r\n"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "4.5 Determin Roll and Pitch Bias"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}