Lazy NetCDF save bug

lazy_netcdf_save_bug

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  "signature": "sha256:1ccaf1d6efde449dc4d273823364434c19bdd068d41587570ffde0a5be796216"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import iris"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "cube = iris.cube.Cube(np.ma.array(np.arange(4), mask=[False, True, True, False], fill_value=-1))\n",
      "cube.add_dim_coord(iris.coords.DimCoord(np.arange(4), long_name='bla'), 0)\n",
      "print cube"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "unknown / (unknown)                 (bla: 4)\n",
        "     Dimension coordinates:\n",
        "          bla                           x\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "iris.save(cube, 'tmp.nc', unlimited_dimensions=[])\n",
      "ncube = iris.load_cube('tmp.nc')\n",
      "print ncube.lazy_data().fill_value"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "-1\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "iris.save(ncube, 'tmp2.nc', unlimited_dimensions=[])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "ncdump -h 'tmp2.nc'"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "netcdf tmp2 {\n",
        "dimensions:\n",
        "\tbla = 4 ;\n",
        "variables:\n",
        "\tint64 unknown(bla) ;\n",
        "\t\tunknown:units = \"1\" ;\n",
        "\tint64 bla(bla) ;\n",
        "\t\tbla:units = \"1\" ;\n",
        "\t\tbla:long_name = \"bla\" ;\n",
        "\n",
        "// global attributes:\n",
        "\t\t:Conventions = \"CF-1.5\" ;\n",
        "}\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ncube2 = iris.load_cube('tmp2.nc')\n",
      "ncube2.data.fill_value"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "-9223372036854775806"
       ]
      }
     ],
     "prompt_number": 13
    }
   ],
   "metadata": {}
  }
 ]
}