video_parallel

gistfile1.txt

{
 "metadata": {
  "name": "video_parallel"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "from IPython import parallel\n\nrc = parallel.Client()\nview = rc.load_balanced_view()",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "%%px\n\nimport sys\nimport os\nfrom time import sleep\nfrom multiprocessing import Pool,cpu_count\n\n\nfrom pylab import *\nimport netCDF4\nimport datetime as dt\n\nimport numpy.ma as ma\nfrom datetime import date, datetime, timedelta",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "def perdelta(start, end, delta):\n    curr = start\n    while curr < end:\n        yield curr\n        curr += delta\n        \ndef plotWave(args):\n    start = args[\"date\"]\n    url = args[\"url\"]\n    box = args[\"box\"]\n    vname = args[\"vname\"]\n    pvar = args[\"pvar\"]\n    nc = netCDF4.Dataset(url)\n    lat = nc.variables['lat'][:]\n    lon = nc.variables['lon'][:]\n    lon = lon - 360.0 \n    time_var = nc.variables[str(pvar)]\n    dtime = netCDF4.num2date(time_var[:],time_var.units)\n    bi=(lon>=box[0])&(lon<=box[2])\n    bj=(lat>=box[1])&(lat<=box[3])\n    istart = netCDF4.date2index(start,time_var,select='nearest')\n    var = nc.variables[vname][istart,bj,bi]\n    hs = ma.masked_where(np.isnan(var),var)\n    figure(figsize=(12,12)) \n    plt.pcolormesh(lon[bi], lat[bj], hs, vmin=0, vmax=3)\n    title('Wave Height in the Gulf of Maine %s' % start.strftime('%Y-%m-%d-%H-%M'))\n    name = str(pvar)+'_0000'+start.strftime('%Y%m%d%H%M')+'.png'\n    print 'processed %' % start\n    plt.savefig(name)\n    \n\n\ndef gen_dates(past,url, box, vname, pvar):\n    #past = arg[0]\n    for result in perdelta(datetime.now() - timedelta(days=past), datetime.now(), timedelta(hours=1)):\n        yield {\"date\":result,\"url\":url, \"box\":box, \"vname\":vname, \"pvar\":pvar}",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "days=1\nurl='http://thredds.ucar.edu/thredds/dodsC/fmrc/NCEP/WW3/Coastal_US_East_Coast/NCEP-WW3-Coastal_US_East_Coast_best.ncd'\nbox = [-71.5,39.5,-63.,46.]\nvname = 'Significant_height_of_combined_wind_waves_and_swell'\npvar='time'",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "results = view.map(plotWave, list(gen_dates(days,url, box, vname, pvar)), ordered=False)\nresults",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "for r in results:\n    print r\n    sys.stdout.flush()",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "We can also see the stdout of each case, though in this case it isn't super interesting"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "results.display_outputs()",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "!jist -p Plot\\ video_parallel.ipynb",
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}