{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook sets up forcing for two storm surge simulations: one during a neap tide and one during a spring tide. The idea is to examine the influence of the tidal dissipation on surge amplitude. The surge from Feb 1-8, 2006 will be used in both simulations. However, I will run over different times in order to capture the spring/neap variability.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Steps:\n",
    "1. Look up spring/neap cycle in dec 2006\n",
    "2. Split feb2006 forcing into days (Feb 1-8)\n",
    "3. Copy into time periods of for spring and neap. \n",
    "\n",
    "Ideally each simulation is 7 days long."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import netCDF4 as nc\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import datetime\n",
    "from dateutil import tz\n",
    "import os\n",
    "import glob\n",
    "\n",
    "from salishsea_tools.nowcast import figures\n",
    "from salishsea_tools import nc_tools\n",
    "\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Spring/Neap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def dateParserMeasured2(s):\n",
    "    \"\"\"\n",
    "    converts string in %d-%b-%Y %H:%M:%S format Pacific time to a datetime object UTC time.\n",
    "    \"\"\"\n",
    "    PST=tz.tzoffset(\"PST\",-28800)\n",
    "    #convert the string to a datetime object\n",
    "    unaware = datetime.datetime.strptime(s, \"%d-%b-%Y %H:%M:%S \")\n",
    "    #add in the local time zone (Canada/Pacific)\n",
    "    aware = unaware.replace(tzinfo=PST)\n",
    "    #convert to UTC\n",
    "    return aware.astimezone(tz.tzutc())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fname = '/data/nsoontie/MEOPAR/storm-surge/Revisions/tides/analysis/PointAtkinson_t_tide_compare8_31-Dec-2005_02-Jan-2007_snr2_filter.csv'\n",
    "\n",
    "ttide = pd.read_csv(fname,skiprows=3,parse_dates=[0],date_parser=dateParserMeasured2)\n",
    "ttide = ttide.rename(columns={'Time_Local ': 'time', ' pred_8 ': 'pred_8', ' pred_all ': 'pred_all'})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(732646.0, 732676.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5IAAAEACAYAAADBQElzAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8PGQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa385748ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "to=datetime.datetime(2006,12,1)\n",
    "tf=datetime.datetime(2006,12,31)\n",
    "\n",
    "fig,ax=plt.subplots(1,1,figsize=(15,4))\n",
    "plt.plot(ttide.time, ttide.pred_all)\n",
    "\n",
    "ax.set_xlim([to,tf])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Spring surge**\n",
    "* December 1-7, 2006\n",
    "\n",
    "**Neap surge**\n",
    "* December 12-18, 2006\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Divide forcing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, load the feb 2006 forcing file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[u'time_counter', u'nav_lat', u'nav_lon', u'sossheig', u'vobtcrtx', u'vobtcrty', u'nbidta', u'nbjdta', u'nbrdta']\n"
     ]
    }
   ],
   "source": [
    "fname = '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/ssh_y2006m02.nc'\n",
    "res = nc.Dataset(fname)\n",
    "\n",
    "nc_tools.show_variables(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ssh = res.variables['sossheig']\n",
    "time =res.variables['time_counter']\n",
    "\n",
    "\n",
    "#fboundary parameters\n",
    "startj = 384\n",
    "endj = 471\n",
    "lengthj = endj-startj\n",
    "r = 1\n",
    "\n",
    "#load bathy\n",
    "fB = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc','r')\n",
    "lat = fB.variables['nav_lat'][:]\n",
    "lon = fB.variables['nav_lon'][:]\n",
    "fB.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def prepare_netcdf(ssh_file, count, ssh):\n",
    "    # dataset attributes\n",
    "    nc_tools.init_dataset_attrs(\n",
    "    ssh_file, \n",
    "    title='Juan de Fuca SSH hourly values', \n",
    "    notebook_name='', \n",
    "    nc_filepath='/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring' + filename,\n",
    "    comment='SSH for Tofino - testing spring/neap effect')\n",
    "\n",
    "    \n",
    "    #dimensions\n",
    "    ssh_file.createDimension('xbT', lengthj*r)\n",
    "    ssh_file.createDimension('yb', 1)\n",
    "    ssh_file.createDimension('time_counter', None)\n",
    "    # variables\n",
    "    # time_counter\n",
    "    time_counter = ssh_file.createVariable('time_counter', 'float32', ('time_counter'))\n",
    "    time_counter.long_name = 'Time axis'\n",
    "    time_counter.axis = 'T'\n",
    "    time_counter.units = 'hour since 00:00:00 '\n",
    "    # nav_lat and nav_lon\n",
    "    nav_lat = ssh_file.createVariable('nav_lat','float32',('yb','xbT'))\n",
    "    nav_lat.long_name = 'Latitude'\n",
    "    nav_lat.units = 'degrees_north'\n",
    "    nav_lon = ssh_file.createVariable('nav_lon','float32',('yb','xbT'))\n",
    "    nav_lon.long_name = 'Longitude'\n",
    "    nav_lon.units = 'degrees_east'\n",
    "    # ssh\n",
    "    sossheig = ssh_file.createVariable('sossheig', 'float32', \n",
    "                               ('time_counter','yb','xbT'), zlib=True)\n",
    "    sossheig.units = 'm'\n",
    "    sossheig.long_name = 'Sea surface height'   \n",
    "    sossheig.coordinates = 'nav_lon nav_lat time_counter'\n",
    "    sossheig.grid = 'SalishSea2'\n",
    "    # vobtcrtx, vobtcrty\n",
    "    vobtcrtx = ssh_file.createVariable('vobtcrtx', 'float32',\n",
    "                                   ('time_counter','yb','xbT'), zlib=True)\n",
    "    vobtcrtx.units = 'm/s'\n",
    "    vobtcrtx.long_name = 'Barotropic U Velocity- ZEROD'   \n",
    "    vobtcrtx.grid = 'SalishSea2'\n",
    "    vobtcrty = ssh_file.createVariable('vobtcrty', 'float32',\n",
    "                                   ('time_counter','yb','xbT'), zlib=True)\n",
    "    vobtcrty.units = 'm/s'\n",
    "    vobtcrty.long_name = 'Barotropic V Velocity- ZEROD'   \n",
    "    vobtcrty.grid = 'SalishSea2'\n",
    "    # nbidta, ndjdta, ndrdta\n",
    "    nbidta = ssh_file.createVariable('nbidta', 'int32' , ('yb','xbT'), zlib=True)\n",
    "    nbidta.long_name = 'i grid position'\n",
    "    nbidta.units = 1\n",
    "    nbjdta = ssh_file.createVariable('nbjdta', 'int32' , ('yb','xbT'), zlib=True)\n",
    "    nbjdta.long_name = 'j grid position'\n",
    "    nbjdta.units = 1\n",
    "    nbrdta = ssh_file.createVariable('nbrdta', 'int32' , ('yb','xbT'), zlib=True)\n",
    "    nbrdta.long_name = 'position from boundary'\n",
    "    nbrdta.units = 1\n",
    "    \n",
    "    for ir in range(0,r):\n",
    "        nav_lat[0,ir*lengthj:(ir+1)*lengthj] = lat[startj:endj,ir]\n",
    "        nav_lon[0,ir*lengthj:(ir+1)*lengthj] = lon[startj:endj,ir]\n",
    "        nbidta[0,ir*lengthj:(ir+1)*lengthj] = ir\n",
    "        nbjdta[0,ir*lengthj:(ir+1)*lengthj] = range(startj,endj)\n",
    "        nbrdta[0,ir*lengthj:(ir+1)*lengthj] = ir\n",
    "        \n",
    "    for ib in range(0,lengthj*r):\n",
    "        sossheig[0:count,0,ib] = ssh[0:count]\n",
    "        time_counter[0:count] = range(1,count+1)\n",
    "        vobtcrtx[0:count,0,ib] = 0*np.ones(count)\n",
    "        vobtcrty[0:count,0,ib] = 0*np.ones(count)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Loop through Feb 1-10. Create the spring files Dec 1-10, 2006."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[[ 0.67745298  0.67745298  0.67745298 ...,  0.67745298  0.67745298\n",
      "    0.67745298]]\n",
      "\n",
      " [[ 0.81208497  0.81208497  0.81208497 ...,  0.81208497  0.81208497\n",
      "    0.81208497]]\n",
      "\n",
      " [[ 0.86075902  0.86075902  0.86075902 ...,  0.86075902  0.86075902\n",
      "    0.86075902]]\n",
      "\n",
      " ..., \n",
      " [[ 0.27557901  0.27557901  0.27557901 ...,  0.27557901  0.27557901\n",
      "    0.27557901]]\n",
      "\n",
      " [[ 0.33987099  0.33987099  0.33987099 ...,  0.33987099  0.33987099\n",
      "    0.33987099]]\n",
      "\n",
      " [[ 0.37389499  0.37389499  0.37389499 ...,  0.37389499  0.37389499\n",
      "    0.37389499]]]\n",
      "2006-12-01 00:00:00\n",
      "[  1.   2.   3.   4.   5.   6.   7.   8.   9.  10.  11.  12.  13.  14.  15.\n",
      "  16.  17.  18.  19.  20.  21.  22.  23.  24.]\n",
      "ssh_y2006m12d01.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:02] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.36940199  0.36940199  0.36940199 ...,  0.36940199  0.36940199\n",
      "    0.36940199]]\n",
      "\n",
      " [[ 0.35389999  0.35389999  0.35389999 ...,  0.35389999  0.35389999\n",
      "    0.35389999]]\n",
      "\n",
      " [[ 0.377929    0.377929    0.377929   ...,  0.377929    0.377929    0.377929  ]]\n",
      "\n",
      " ..., \n",
      " [[ 0.21154     0.21154     0.21154    ...,  0.21154     0.21154     0.21154   ]]\n",
      "\n",
      " [[ 0.199637    0.199637    0.199637   ...,  0.199637    0.199637    0.199637  ]]\n",
      "\n",
      " [[ 0.224934    0.224934    0.224934   ...,  0.224934    0.224934    0.224934  ]]]\n",
      "2006-12-02 00:00:00\n",
      "[ 25.  26.  27.  28.  29.  30.  31.  32.  33.  34.  35.  36.  37.  38.  39.\n",
      "  40.  41.  42.  43.  44.  45.  46.  47.  48.]\n",
      "ssh_y2006m12d02.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:02] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.218465    0.218465    0.218465   ...,  0.218465    0.218465    0.218465  ]]\n",
      "\n",
      " [[ 0.20141     0.20141     0.20141    ...,  0.20141     0.20141     0.20141   ]]\n",
      "\n",
      " [[ 0.222629    0.222629    0.222629   ...,  0.222629    0.222629    0.222629  ]]\n",
      "\n",
      " ..., \n",
      " [[ 0.213973    0.213973    0.213973   ...,  0.213973    0.213973    0.213973  ]]\n",
      "\n",
      " [[ 0.216717    0.216717    0.216717   ...,  0.216717    0.216717    0.216717  ]]\n",
      "\n",
      " [[ 0.25186399  0.25186399  0.25186399 ...,  0.25186399  0.25186399\n",
      "    0.25186399]]]\n",
      "2006-12-03 00:00:00\n",
      "[ 49.  50.  51.  52.  53.  54.  55.  56.  57.  58.  59.  60.  61.  62.  63.\n",
      "  64.  65.  66.  67.  68.  69.  70.  71.  72.]\n",
      "ssh_y2006m12d03.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:02] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.31834301  0.31834301  0.31834301 ...,  0.31834301  0.31834301\n",
      "    0.31834301]]\n",
      "\n",
      " [[ 0.41075501  0.41075501  0.41075501 ...,  0.41075501  0.41075501\n",
      "    0.41075501]]\n",
      "\n",
      " [[ 0.47863901  0.47863901  0.47863901 ...,  0.47863901  0.47863901\n",
      "    0.47863901]]\n",
      "\n",
      " ..., \n",
      " [[ 0.497152    0.497152    0.497152   ...,  0.497152    0.497152    0.497152  ]]\n",
      "\n",
      " [[ 0.408452    0.408452    0.408452   ...,  0.408452    0.408452    0.408452  ]]\n",
      "\n",
      " [[ 0.330928    0.330928    0.330928   ...,  0.330928    0.330928    0.330928  ]]]\n",
      "2006-12-04 00:00:00\n",
      "[ 73.  74.  75.  76.  77.  78.  79.  80.  81.  82.  83.  84.  85.  86.  87.\n",
      "  88.  89.  90.  91.  92.  93.  94.  95.  96.]\n",
      "ssh_y2006m12d04.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:02] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.247356    0.247356    0.247356   ...,  0.247356    0.247356    0.247356  ]]\n",
      "\n",
      " [[ 0.20305499  0.20305499  0.20305499 ...,  0.20305499  0.20305499\n",
      "    0.20305499]]\n",
      "\n",
      " [[ 0.178451    0.178451    0.178451   ...,  0.178451    0.178451    0.178451  ]]\n",
      "\n",
      " ..., \n",
      " [[ 0.001747    0.001747    0.001747   ...,  0.001747    0.001747    0.001747  ]]\n",
      "\n",
      " [[-0.0046     -0.0046     -0.0046     ..., -0.0046     -0.0046     -0.0046    ]]\n",
      "\n",
      " [[-0.030398   -0.030398   -0.030398   ..., -0.030398   -0.030398   -0.030398  ]]]\n",
      "2006-12-05 00:00:00\n",
      "[  97.   98.   99.  100.  101.  102.  103.  104.  105.  106.  107.  108.\n",
      "  109.  110.  111.  112.  113.  114.  115.  116.  117.  118.  119.  120.]\n",
      "ssh_y2006m12d05.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[-0.015177 -0.015177 -0.015177 ..., -0.015177 -0.015177 -0.015177]]\n",
      "\n",
      " [[ 0.004114  0.004114  0.004114 ...,  0.004114  0.004114  0.004114]]\n",
      "\n",
      " [[ 0.026801  0.026801  0.026801 ...,  0.026801  0.026801  0.026801]]\n",
      "\n",
      " ..., \n",
      " [[ 0.111174  0.111174  0.111174 ...,  0.111174  0.111174  0.111174]]\n",
      "\n",
      " [[ 0.122326  0.122326  0.122326 ...,  0.122326  0.122326  0.122326]]\n",
      "\n",
      " [[ 0.096723  0.096723  0.096723 ...,  0.096723  0.096723  0.096723]]]\n",
      "2006-12-06 00:00:00\n",
      "[ 121.  122.  123.  124.  125.  126.  127.  128.  129.  130.  131.  132.\n",
      "  133.  134.  135.  136.  137.  138.  139.  140.  141.  142.  143.  144.]\n",
      "ssh_y2006m12d06.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.082286    0.082286    0.082286   ...,  0.082286    0.082286    0.082286  ]]\n",
      "\n",
      " [[ 0.081318    0.081318    0.081318   ...,  0.081318    0.081318    0.081318  ]]\n",
      "\n",
      " [[ 0.101295    0.101295    0.101295   ...,  0.101295    0.101295    0.101295  ]]\n",
      "\n",
      " ..., \n",
      " [[ 0.14754     0.14754     0.14754    ...,  0.14754     0.14754     0.14754   ]]\n",
      "\n",
      " [[ 0.17461801  0.17461801  0.17461801 ...,  0.17461801  0.17461801\n",
      "    0.17461801]]\n",
      "\n",
      " [[ 0.144858    0.144858    0.144858   ...,  0.144858    0.144858    0.144858  ]]]\n",
      "2006-12-07 00:00:00\n",
      "[ 145.  146.  147.  148.  149.  150.  151.  152.  153.  154.  155.  156.\n",
      "  157.  158.  159.  160.  161.  162.  163.  164.  165.  166.  167.  168.]\n",
      "ssh_y2006m12d07.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[ 0.143169  0.143169  0.143169 ...,  0.143169  0.143169  0.143169]]\n",
      "\n",
      " [[ 0.117628  0.117628  0.117628 ...,  0.117628  0.117628  0.117628]]\n",
      "\n",
      " [[ 0.146513  0.146513  0.146513 ...,  0.146513  0.146513  0.146513]]\n",
      "\n",
      " ..., \n",
      " [[-0.06797  -0.06797  -0.06797  ..., -0.06797  -0.06797  -0.06797 ]]\n",
      "\n",
      " [[-0.08533  -0.08533  -0.08533  ..., -0.08533  -0.08533  -0.08533 ]]\n",
      "\n",
      " [[-0.099235 -0.099235 -0.099235 ..., -0.099235 -0.099235 -0.099235]]]\n",
      "2006-12-08 00:00:00\n",
      "[ 169.  170.  171.  172.  173.  174.  175.  176.  177.  178.  179.  180.\n",
      "  181.  182.  183.  184.  185.  186.  187.  188.  189.  190.  191.  192.]\n",
      "ssh_y2006m12d08.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[-0.099829 -0.099829 -0.099829 ..., -0.099829 -0.099829 -0.099829]]\n",
      "\n",
      " [[-0.085324 -0.085324 -0.085324 ..., -0.085324 -0.085324 -0.085324]]\n",
      "\n",
      " [[-0.109058 -0.109058 -0.109058 ..., -0.109058 -0.109058 -0.109058]]\n",
      "\n",
      " ..., \n",
      " [[-0.10731  -0.10731  -0.10731  ..., -0.10731  -0.10731  -0.10731 ]]\n",
      "\n",
      " [[-0.097291 -0.097291 -0.097291 ..., -0.097291 -0.097291 -0.097291]]\n",
      "\n",
      " [[-0.090911 -0.090911 -0.090911 ..., -0.090911 -0.090911 -0.090911]]]\n",
      "2006-12-09 00:00:00\n",
      "[ 193.  194.  195.  196.  197.  198.  199.  200.  201.  202.  203.  204.\n",
      "  205.  206.  207.  208.  209.  210.  211.  212.  213.  214.  215.  216.]\n",
      "ssh_y2006m12d09.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n",
      "[[[-0.086759 -0.086759 -0.086759 ..., -0.086759 -0.086759 -0.086759]]\n",
      "\n",
      " [[-0.069909 -0.069909 -0.069909 ..., -0.069909 -0.069909 -0.069909]]\n",
      "\n",
      " [[-0.04106  -0.04106  -0.04106  ..., -0.04106  -0.04106  -0.04106 ]]\n",
      "\n",
      " ..., \n",
      " [[ 0.013694  0.013694  0.013694 ...,  0.013694  0.013694  0.013694]]\n",
      "\n",
      " [[ 0.038598  0.038598  0.038598 ...,  0.038598  0.038598  0.038598]]\n",
      "\n",
      " [[ 0.017858  0.017858  0.017858 ...,  0.017858  0.017858  0.017858]]]\n",
      "2006-12-10 00:00:00\n",
      "[ 217.  218.  219.  220.  221.  222.  223.  224.  225.  226.  227.  228.\n",
      "  229.  230.  231.  232.  233.  234.  235.  236.  237.  238.  239.  240.]\n",
      "ssh_y2006m12d10.nc\n",
      "file format: NETCDF4\n",
      "Conventions: CF-1.6\n",
      "title: Juan de Fuca SSH hourly values\n",
      "institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n",
      "source: REQUIRED\n",
      "references: REQUIRED\n",
      "history: [2015-05-20 11:11:03] Created netCDF4 zlib=True dataset.\n",
      "comment: SSH for Tofino - testing spring/neap effect\n"
     ]
    }
   ],
   "source": [
    "start_day = datetime.datetime(2006,12,1)\n",
    "for d in np.arange(1,11):\n",
    "    day = start_day + datetime.timedelta(days = d-1)\n",
    "    \n",
    "    #grab subset of ssh data \n",
    "    ssh_sub = ssh[24*(d-1):24*d,:,:]\n",
    "    print ssh_sub\n",
    "    \n",
    "    #print day and time counters for sanity check\n",
    "    print day\n",
    "    print time[24*(d-1):24*d]\n",
    "    \n",
    "    # construct file name\n",
    "    filename = day.strftime('ssh_y%Ym%md%d.nc')\n",
    "    ssh_file = nc.Dataset(filename, 'w', zlib=True)\n",
    "    print filename\n",
    "    #construct netcdf\n",
    "    prepare_netcdf(ssh_file,24,ssh_sub)\n",
    "    \n",
    "    ssh_file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copy these files into forcing directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "srcdir='.'\n",
    "dstdir='/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/'\n",
    "\n",
    "import shutil\n",
    "\n",
    "for basename in os.listdir(srcdir):\n",
    "    if basename.endswith('.nc'):\n",
    "        pathname = os.path.join(srcdir, basename)\n",
    "        if os.path.isfile(pathname):\n",
    "            shutil.copy2(pathname, dstdir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copy files into neap period Dec 11-21, 2011"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2006-12-03 00:00:00 2006-12-11 00:00:00\n",
      "ssh_y2006m12d03.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d11.nc\n",
      "2006-12-04 00:00:00 2006-12-12 00:00:00\n",
      "ssh_y2006m12d04.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d12.nc\n",
      "2006-12-05 00:00:00 2006-12-13 00:00:00\n",
      "ssh_y2006m12d05.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d13.nc\n",
      "2006-12-06 00:00:00 2006-12-14 00:00:00\n",
      "ssh_y2006m12d06.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d14.nc\n",
      "2006-12-07 00:00:00 2006-12-15 00:00:00\n",
      "ssh_y2006m12d07.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d15.nc\n",
      "2006-12-08 00:00:00 2006-12-16 00:00:00\n",
      "ssh_y2006m12d08.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d16.nc\n",
      "2006-12-09 00:00:00 2006-12-17 00:00:00\n",
      "ssh_y2006m12d09.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d17.nc\n",
      "2006-12-10 00:00:00 2006-12-18 00:00:00\n",
      "ssh_y2006m12d10.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d18.nc\n",
      "2006-12-11 00:00:00 2006-12-19 00:00:00\n",
      "ssh_y2006m12d11.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d19.nc\n",
      "2006-12-12 00:00:00 2006-12-20 00:00:00\n",
      "ssh_y2006m12d12.nc /data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d20.nc\n"
     ]
    }
   ],
   "source": [
    "spring=datetime.datetime(2006,12,1)\n",
    "neap = datetime.datetime(2006,12,11)\n",
    "for d in np.arange(1,11):\n",
    "    ds = spring +datetime.timedelta(days=d-1)\n",
    "    dn= neap +datetime.timedelta(days=d-1)\n",
    "    print ds,dn\n",
    "    old = ds.strftime('ssh_y%Ym%md%d.nc')\n",
    "    new = dn.strftime('/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y%Ym%md%d.nc')\n",
    "    print old, new\n",
    "    shutil.copy2(old,new)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d03.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d04.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d05.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d06.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d07.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d08.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d09.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d10.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d11.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d12.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/ssh_y2006m12d7.nc']\n"
     ]
    }
   ],
   "source": [
    "springs = glob.glob('/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/spring/*.nc')\n",
    "springs.sort(key=os.path.basename)\n",
    "print springs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d11.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d12.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d13.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d14.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d15.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d16.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d17.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d18.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d19.nc', '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/ssh_y2006m12d20.nc']\n"
     ]
    }
   ],
   "source": [
    "neaps = glob.glob('/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/neap/*.nc')\n",
    "neaps.sort(key=os.path.basename)\n",
    "print neaps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "s_ssh=np.array([])\n",
    "n_ssh =np.array([])\n",
    "\n",
    "for s,n in zip(springs,neaps):\n",
    "    fs=nc.Dataset(s)\n",
    "    s1=fs.variables['sossheig'][:,0,1]\n",
    "    s_ssh=np.append(s_ssh,s1)\n",
    "    \n",
    "    fn=nc.Dataset(n)\n",
    "    n1=fn.variables['sossheig'][:,0,1]\n",
    "    n_ssh=np.append(n_ssh,n1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f96c9198a50>]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEACAYAAAC6d6FnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnAAYYyxKcQJgjLEoxQmAMcai1P8DL1szMncs8JgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f96c95a3310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1)\n",
    "\n",
    "ax.plot(s_ssh)\n",
    "ax.plot(n_ssh)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like a match.\n",
    "\n",
    "* I will neglect Port Hardy forcing because it isn't a very strong component. \n",
    "* I will also neglect wind forcing/river. I'm only interested in surge propogation modulated but the tides."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}