IPython Notebook Exploring How netCDF4 Variable fill_value=0 Works

gistfile1.txt

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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import print_function\n",
      "\n",
      "import netCDF4 as nc\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 56
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "foo = nc.Dataset('foo.nc', 'w', zlib=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 57
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "foo.createDimension('x', 10)\n",
      "x = foo.createVariable('x', 'float32', ('x',), fill_value=0, least_significant_digit=1, zlib=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 58
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "foo.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 59
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!ncdump -c foo.nc"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "netcdf foo {\r\n",
        "dimensions:\r\n",
        "\tx = 10 ;\r\n",
        "variables:\r\n",
        "\tfloat x(x) ;\r\n",
        "\t\tx:_FillValue = 0.f ;\r\n",
        "\t\tx:least_significant_digit = 1L ;\r\n",
        "data:\r\n",
        "\r\n",
        " x = _, _, _, _, _, _, _, _, _, _ ;\r\n",
        "}\r\n"
       ]
      }
     ],
     "prompt_number": 60
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bar = nc.Dataset('bar.nc', 'w', zlib=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bar.createDimension('x', 10)\n",
      "x = bar.createVariable('x', 'float32', ('x',), fill_value=0, least_significant_digit=1, zlib=True)\n",
      "z = np.ma.masked_equal(np.zeros(10), 0)\n",
      "x[:] = z\n",
      "z"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 67,
       "text": [
        "masked_array(data = [-- -- -- -- -- -- -- -- -- --],\n",
        "             mask = [ True  True  True  True  True  True  True  True  True  True],\n",
        "       fill_value = 0.0)\n"
       ]
      }
     ],
     "prompt_number": 67
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bar.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 68
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!ncdump -c bar.nc"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "netcdf bar {\r\n",
        "dimensions:\r\n",
        "\tx = 10 ;\r\n",
        "variables:\r\n",
        "\tfloat x(x) ;\r\n",
        "\t\tx:_FillValue = 0.f ;\r\n",
        "\t\tx:least_significant_digit = 1L ;\r\n",
        "data:\r\n",
        "\r\n",
        " x = _, _, _, _, _, _, _, _, _, _ ;\r\n",
        "}\r\n"
       ]
      }
     ],
     "prompt_number": 69
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "baz = nc.Dataset('baz.nc', 'w')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 70
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "baz.createDimension('x', 10)\n",
      "x = bar.createVariable('x', 'float32', ('x',), zlib=True)\n",
      "x[:] = np.zeros(10)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 71
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "baz.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 72
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!ncdump -c baz.nc"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "netcdf baz {\r\n",
        "dimensions:\r\n",
        "\tx = 10 ;\r\n",
        "variables:\r\n",
        "\tfloat x(x) ;\r\n",
        "data:\r\n",
        "\r\n",
        " x = 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ;\r\n",
        "}\r\n"
       ]
      }
     ],
     "prompt_number": 73
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}