{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import netCDF4 as nc\n",
    "import datetime as dt\n",
    "import subprocess\n",
    "import requests\n",
    "import matplotlib.pyplot as plt\n",
    "import cmocean\n",
    "import numpy as np\n",
    "import os\n",
    "import glob\n",
    "import dateutil as dutil\n",
    "from salishsea_tools import viz_tools\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "with nc.Dataset('/ocean/eolson/MEOPAR/NEMO-forcing/grid/mesh_mask201702_noLPE.nc') as fm:\n",
    "    tmask=np.copy(fm.variables['tmask'])\n",
    "    umask=np.copy(fm.variables['umask'])\n",
    "    vmask=np.copy(fm.variables['vmask'])\n",
    "    navlon=np.copy(fm.variables['nav_lon'])\n",
    "    navlat=np.copy(fm.variables['nav_lat'])\n",
    "    dept=np.copy(fm.variables['gdept_1d'])\n",
    "    e3t_0=np.copy(fm.variables['e3t_0'])\n",
    "    e3u_0=np.copy(fm.variables['e3u_0'])\n",
    "    e3v_0=np.copy(fm.variables['e3v_0'])\n",
    "    e1t=np.copy(fm.variables['e1t'])\n",
    "    e2t=np.copy(fm.variables['e2t'])\n",
    "    e1v=np.copy(fm.variables['e1v'])\n",
    "    e2u=np.copy(fm.variables['e2u'])\n",
    "    A=fm.variables['e1t'][0,:,:]*fm.variables['e2t'][0,:,:]*tmask[0,0,:,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "t0=dt.datetime(2014,12,1) # 1st start date of run\n",
    "#te=dt.datetime(2016,12,1)# last start date of runfnum=18\n",
    "stm=np.shape(tmask)\n",
    "SiN=2.0\n",
    "#nlen=36*2\n",
    "nlen=53\n",
    "dlist=[t0+dt.timedelta(days=ii*10) for ii in range(0,nlen)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#sdir0='/results/SalishSea/nowcast-green/'\n",
    "sdir1='/results/SalishSea/hindcast/'\n",
    "#sdir3='/data/eolson/MEOPAR/SS36runs/CedarRuns/spring2015_HCMZ/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tmaskC=np.copy(tmask)\n",
    "tmaskC[:,:,370:490,:12]=0\n",
    "tmaskC[:,:,887:,30:70]=0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/results/SalishSea/hindcast/01dec14/SalishSea_1h_20141201_20141201_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/11dec14/SalishSea_1h_20141211_20141211_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/21dec14/SalishSea_1h_20141221_20141221_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/31dec14/SalishSea_1h_20141231_20141231_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10jan15/SalishSea_1h_20150110_20150110_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20jan15/SalishSea_1h_20150120_20150120_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30jan15/SalishSea_1h_20150130_20150130_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09feb15/SalishSea_1h_20150209_20150209_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19feb15/SalishSea_1h_20150219_20150219_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/01mar15/SalishSea_1h_20150301_20150301_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/11mar15/SalishSea_1h_20150311_20150311_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/21mar15/SalishSea_1h_20150321_20150321_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/31mar15/SalishSea_1h_20150331_20150331_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10apr15/SalishSea_1h_20150410_20150410_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20apr15/SalishSea_1h_20150420_20150420_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30apr15/SalishSea_1h_20150430_20150430_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10may15/SalishSea_1h_20150510_20150510_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20may15/SalishSea_1h_20150520_20150520_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30may15/SalishSea_1h_20150530_20150530_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09jun15/SalishSea_1h_20150609_20150609_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19jun15/SalishSea_1h_20150619_20150619_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/29jun15/SalishSea_1h_20150629_20150629_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09jul15/SalishSea_1h_20150709_20150709_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19jul15/SalishSea_1h_20150719_20150719_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/29jul15/SalishSea_1h_20150729_20150729_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/08aug15/SalishSea_1h_20150808_20150808_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/18aug15/SalishSea_1h_20150818_20150818_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/28aug15/SalishSea_1h_20150828_20150828_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/07sep15/SalishSea_1h_20150907_20150907_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/17sep15/SalishSea_1h_20150917_20150917_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/27sep15/SalishSea_1h_20150927_20150927_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/07oct15/SalishSea_1h_20151007_20151007_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/17oct15/SalishSea_1h_20151017_20151017_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/27oct15/SalishSea_1h_20151027_20151027_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/06nov15/SalishSea_1h_20151106_20151106_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/16nov15/SalishSea_1h_20151116_20151116_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/26nov15/SalishSea_1h_20151126_20151126_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/06dec15/SalishSea_1h_20151206_20151206_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/16dec15/SalishSea_1h_20151216_20151216_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/26dec15/SalishSea_1h_20151226_20151226_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/05jan16/SalishSea_1h_20160105_20160105_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/15jan16/SalishSea_1h_20160115_20160115_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/25jan16/SalishSea_1h_20160125_20160125_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04feb16/SalishSea_1h_20160204_20160204_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/14feb16/SalishSea_1h_20160214_20160214_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/24feb16/SalishSea_1h_20160224_20160224_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/05mar16/SalishSea_1h_20160305_20160305_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/15mar16/SalishSea_1h_20160315_20160315_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/25mar16/SalishSea_1h_20160325_20160325_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04apr16/SalishSea_1h_20160404_20160404_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/14apr16/SalishSea_1h_20160414_20160414_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/24apr16/SalishSea_1h_20160424_20160424_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04may16/SalishSea_1h_20160504_20160504_ptrc_T.nc\n"
     ]
    }
   ],
   "source": [
    "tlist=dlist\n",
    "SiGlobalTot=dict()\n",
    "SiTot=dict()\n",
    "BSiTot=dict()\n",
    "DiatTot=dict()\n",
    "changeSiGlobalTot=dict()\n",
    "for idir in (sdir1,):\n",
    "    fformat1='%d%b%y/'\n",
    "    if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):\n",
    "        fformatT='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'\n",
    "        fformatP='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'\n",
    "    #elif idir==sdir0:\n",
    "    #    fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'\n",
    "    #    fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_grid_T.nc'\n",
    "    elif idir==sdir1:\n",
    "        fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'\n",
    "        fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_carp_T.nc'\n",
    "    sumSi=np.zeros((len(tlist),stm[1]))\n",
    "    sumBSi=np.zeros((len(tlist),stm[1]))\n",
    "    sumDiat=np.zeros((len(tlist),stm[1]))\n",
    "    ind=-1\n",
    "    for idt0 in tlist:\n",
    "        ind=ind+1\n",
    "        cdir=idt0.strftime(fformat1).lower()\n",
    "        iffT=idt0.strftime(fformatT)\n",
    "        iffP=idt0.strftime(fformatP)\n",
    "        if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):\n",
    "            sffT=idir+iffT\n",
    "            sffP=idir+iffP\n",
    "        elif idir.startswith('/results/'):\n",
    "            sffT=idir+cdir+iffT\n",
    "            sffP=idir+cdir+iffP\n",
    "        f=nc.Dataset(glob.glob(sffT)[0])\n",
    "        print(sffT)\n",
    "        fP=nc.Dataset(glob.glob(sffP)[0])\n",
    "        #if idir==sdir0:\n",
    "        #    e3t=np.expand_dims((1+fP.variables['sossheig'][0,:,:]/np.sum(e3t_0*tmask,1)),0)*e3t_0\n",
    "        if idir==sdir1:\n",
    "            e3t=fP.variables['e3t'][:2,:,:,:]\n",
    "        Vol=A*np.ones(np.shape(e3t))\n",
    "        sumSi[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['silicon'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumBSi[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['biogenic_silicon'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumDiat[ind,:]=SiN*1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['diatoms'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        f.close()\n",
    "        fP.close()\n",
    "    SiGlobalTot[idir]=sumSi+sumBSi+sumDiat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "siplot=SiGlobalTot[idir]-SiGlobalTot[idir][0,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f61ea81d9e8>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXUAAAEDCAYAAADKhpQUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJ0e4UXccx8kRbtQdx3FyxP8HhUaLIqtGw5IAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f61ea9d62e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cm1=cmocean.cm.balance\n",
    "#plt.pcolormesh([t0+dt.timedelta(10*ii) for ii in range(0,30)],dept[0,:],np.transpose(siplot[:30,:]),cmap=cm1,vmin=-1e9,vmax=1e9)\n",
    "plt.pcolormesh([t0+dt.timedelta(10*ii) for ii in range(0,nlen)],dept[0,:],np.transpose(siplot),cmap=cm1,vmin=-1e8,vmax=1e8)\n",
    "plt.ylim(400,0)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## repeat for N"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/results/SalishSea/hindcast/01dec14/SalishSea_1h_20141201_20141201_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/11dec14/SalishSea_1h_20141211_20141211_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/21dec14/SalishSea_1h_20141221_20141221_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/31dec14/SalishSea_1h_20141231_20141231_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10jan15/SalishSea_1h_20150110_20150110_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20jan15/SalishSea_1h_20150120_20150120_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30jan15/SalishSea_1h_20150130_20150130_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09feb15/SalishSea_1h_20150209_20150209_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19feb15/SalishSea_1h_20150219_20150219_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/01mar15/SalishSea_1h_20150301_20150301_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/11mar15/SalishSea_1h_20150311_20150311_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/21mar15/SalishSea_1h_20150321_20150321_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/31mar15/SalishSea_1h_20150331_20150331_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10apr15/SalishSea_1h_20150410_20150410_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20apr15/SalishSea_1h_20150420_20150420_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30apr15/SalishSea_1h_20150430_20150430_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/10may15/SalishSea_1h_20150510_20150510_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/20may15/SalishSea_1h_20150520_20150520_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/30may15/SalishSea_1h_20150530_20150530_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09jun15/SalishSea_1h_20150609_20150609_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19jun15/SalishSea_1h_20150619_20150619_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/29jun15/SalishSea_1h_20150629_20150629_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/09jul15/SalishSea_1h_20150709_20150709_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/19jul15/SalishSea_1h_20150719_20150719_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/29jul15/SalishSea_1h_20150729_20150729_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/08aug15/SalishSea_1h_20150808_20150808_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/18aug15/SalishSea_1h_20150818_20150818_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/28aug15/SalishSea_1h_20150828_20150828_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/07sep15/SalishSea_1h_20150907_20150907_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/17sep15/SalishSea_1h_20150917_20150917_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/27sep15/SalishSea_1h_20150927_20150927_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/07oct15/SalishSea_1h_20151007_20151007_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/17oct15/SalishSea_1h_20151017_20151017_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/27oct15/SalishSea_1h_20151027_20151027_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/06nov15/SalishSea_1h_20151106_20151106_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/16nov15/SalishSea_1h_20151116_20151116_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/26nov15/SalishSea_1h_20151126_20151126_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/06dec15/SalishSea_1h_20151206_20151206_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/16dec15/SalishSea_1h_20151216_20151216_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/26dec15/SalishSea_1h_20151226_20151226_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/05jan16/SalishSea_1h_20160105_20160105_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/15jan16/SalishSea_1h_20160115_20160115_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/25jan16/SalishSea_1h_20160125_20160125_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04feb16/SalishSea_1h_20160204_20160204_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/14feb16/SalishSea_1h_20160214_20160214_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/24feb16/SalishSea_1h_20160224_20160224_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/05mar16/SalishSea_1h_20160305_20160305_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/15mar16/SalishSea_1h_20160315_20160315_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/25mar16/SalishSea_1h_20160325_20160325_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04apr16/SalishSea_1h_20160404_20160404_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/14apr16/SalishSea_1h_20160414_20160414_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/24apr16/SalishSea_1h_20160424_20160424_ptrc_T.nc\n",
      "/results/SalishSea/hindcast/04may16/SalishSea_1h_20160504_20160504_ptrc_T.nc\n"
     ]
    }
   ],
   "source": [
    "tlist=dlist\n",
    "NGlobalTot=dict()\n",
    "VolTot=dict()\n",
    "NO3Tot=dict()\n",
    "NH4Tot=dict()\n",
    "PONTot=dict()\n",
    "DONTot=dict()\n",
    "DiatTot=dict()\n",
    "MyriTot=dict()\n",
    "NanoTot=dict()\n",
    "MiZoTot=dict()\n",
    "changeNGlobalTot=dict()\n",
    "for idir in (sdir1,):\n",
    "    fformat1='%d%b%y/'\n",
    "    if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):\n",
    "        fformatT='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'\n",
    "        fformatP='SalishSea_1h_*_ptrc_T_%Y%m%d-*.nc'\n",
    "    #elif idir==sdir0:\n",
    "    #    fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'\n",
    "    #    fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_grid_T.nc'\n",
    "    elif idir==sdir1:\n",
    "        fformatT='SalishSea_1h_%Y%m%d_%Y%m%d_ptrc_T.nc'\n",
    "        fformatP='SalishSea_1h_%Y%m%d_%Y%m%d_carp_T.nc'\n",
    "    sumNO3=np.zeros((len(tlist),stm[1]))\n",
    "    sumVol=np.zeros((len(tlist),stm[1]))\n",
    "    sumNH4=np.zeros((len(tlist),stm[1]))\n",
    "    sumPON=np.zeros((len(tlist),stm[1]))\n",
    "    sumDON=np.zeros((len(tlist),stm[1]))\n",
    "    sumDiat=np.zeros((len(tlist),stm[1]))\n",
    "    sumMyri=np.zeros((len(tlist),stm[1]))\n",
    "    sumNano=np.zeros((len(tlist),stm[1]))\n",
    "    sumMiZo=np.zeros((len(tlist),stm[1]))\n",
    "    ind=-1\n",
    "    for idt0 in tlist:\n",
    "        ind=ind+1\n",
    "        cdir=idt0.strftime(fformat1).lower()\n",
    "        iffT=idt0.strftime(fformatT)\n",
    "        iffP=idt0.strftime(fformatP)\n",
    "        if idir.startswith('/data/eolson/MEOPAR/SS36runs/CedarRuns/'):\n",
    "            sffT=idir+iffT\n",
    "            sffP=idir+iffP\n",
    "        elif idir.startswith('/results/'):\n",
    "            sffT=idir+cdir+iffT\n",
    "            sffP=idir+cdir+iffP\n",
    "        f=nc.Dataset(glob.glob(sffT)[0])\n",
    "        print(sffT)\n",
    "        fP=nc.Dataset(glob.glob(sffP)[0])\n",
    "        #if idir==sdir0:\n",
    "        #    e3t=np.expand_dims((1+fP.variables['sossheig'][0,:,:]/np.sum(e3t_0*tmask,1)),0)*e3t_0\n",
    "        if idir==sdir1:\n",
    "            e3t=fP.variables['e3t'][:2,:,:,:]\n",
    "        Vol=A*np.ones(np.shape(e3t))\n",
    "        sumVol[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumNO3[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['nitrate'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumNH4[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['ammonium'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumPON[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['particulate_organic_nitrogen'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumDON[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['dissolved_organic_nitrogen'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumDiat[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['diatoms'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumMyri[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['ciliates'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        sumMiZo[ind,:]=1e-3*np.sum(np.sum(tmaskC[0,:,:,:]*Vol[0,:,:,:]*f.variables['microzooplankton'][0,:,:,:],2),1) #mmol/m3*m3*10^-3=mol\n",
    "        f.close()\n",
    "        fP.close()\n",
    "    NGlobalTot[idir]=sumNO3+sumNH4+sumPON+sumDON+sumDiat+sumMyri+sumNano+sumMiZo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "Nplot=NGlobalTot[idir]-NGlobalTot[idir][0,:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f61d2b81438>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXUAAAEDCAYAAADKhpQUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJztvXucHVd15/v99emWuvV+2bIsyS+QDTIZJMdjTEImDobY\nFkxkMhOuPBnimThRyDVMcid3BnmYTJIh/lyHBHKT4eFRwBeRG1DEgIOGGBzbgQAT/JBBGMtPYcu2\nhCzZ7Ycelvp11vxR1ebo7FXddfqc02qdXt/Ppz5dvWrvvXZV7bNq16q915aZEQRBEHQGXSe7AkEQ\nBEHrCKMeBEHQQYRRD4Ig6CDCqAdBEHQQYdSDIAg6iDDqQRAEHUQY9SAIOhJJt0g6KOnBEmnPkvR1\nSd+T9ICkdZNRx3YQRj0Igk7lM8CVJdP+Z2Cbma0FNgCfaFel2k0Y9SAIOhIz+ybwQq1M0mskfU3S\n/ZK+Jel1o8mBefn+fOBHk1jVltJ9sisQBEEwiWwG3mtmj0t6E1mP/K3A7wN/J+n9wGzgbSevis0R\nRj0IgmmBpDnATwFfkDQqnpn/vQb4jJl9RNKbgb+U9AYzq56EqjZFGPUgCKYLXcBLZrbGOXYduf/d\nzL4jqRdYAhycxPq1hPCpB0EwLTCzQ8CTkn4JQBlvzA8/DVyey18P9ALPnZSKNknbjLqkKyU9Kmm3\npE3t0hMEQeAh6fPAd4ALJO2VdB3wy8B1kr4P7ALW58l/B/j1XP554N9YyRC24w2dzB8ef57bwgck\nXVRzrOV2Uu0IvSupAjwGvB3YC9wHXGNmD7VcWRAEwUlE0j8DjgCfNbM3OMfXAe8H1gFvAv7MzN7U\nLjvZrp76JcBuM3vCzAaBrfz4iRgEQdAxeEMn61hPZvDNzO4GFkhaRpvsZLs+lC4Hnqn5fy/ZE+pV\nJG0ENgLMnjXrJ1etWnVCAdXBgaRQGxlOZKpUUln3DL9WzofsI0OprK8nvSxHB4cS2YvHR9Ly9j+b\n1qcrrWNWnTR/MDXo6krbQM+SJYmstyfNu3TkSCIbeD79zb+cNnEAFvSlsqPHlMgqqYgjlrapPtL2\nd4w0XY/8Pt5cx0ocTn+K9JJWqKc79QT8aNFZiazIYTDSn/6ehocOP29mp/k5yrGwMsOGSw5sOWIj\nu4DjNaLNZra5AXWePVxeID/BTk6Ekzb6Jb8omwHWrllj/3DXnSccP/bc/iTPyMDxRFYdOJbIKn1z\nXJ1dPekv8MmhVLZkTvqr2rW/P5Hd+lj6Q739d29ydQenFgsu+NVE9vp/mdqRcxamBvPXj96fyB75\ns9QG3L/HeSIAl6xKLea9jzsdDVKj9JQdTWTnaXYie47BRLaKXrc+Z/Slep45lj4Azp6dPigWLU3z\nVj/2+UT27/7mRVf3yNb09/Ts3ruechM3wLBVWdM7v1Tabx974biZXdyszsmiXUZ9H7Cy5v8Vuaw0\nlZlOd8XBM+rDR192085YkPa0Xrt0USI77vTKV522IJFddOiVRPbFt37Q1b3sgb9NZIef3+mmDdrD\nzFl+5+7I2o2JbPFFqWG9+oJ5ieys+anBrO5IDab3UuabUBgZSrutI6Syw6R1nKn0IXNcqWHtMqeb\nX8CxIacH7qSrVtN0w87byOqH70hkF674SVf3A+PWboIIKip/DZqkyB72FMibol1G/T5glaRzySq5\nAfhXjRTg9ao9hkif8DaU/qjAd3foWNqzmeE8UFYsSp/qFx5K8970rw65uv/4pbcnsllDadpXXn7C\nzR80xsKz35nIji+8wE27/qq0XbzhtLQNXP1PXpvIqsNpW9t7T1rekGPcZjXwRctzFLxkqW7PheI5\n+YacEtP34LzMEcf146SrOi6U4bR/xO6bb0lkb/yA73V4eGa53nSjCNHjPADbxHbgfZK2krlXXjaz\n/ZKeo0k76dEWo25mw5LeB9xOdv9vMbNdjZTR1ZP6xW0kbYiuoe6Z4fbgq0NpCxtyevUzZ6Xum6Ej\nqQE+b0na4M5bMp+5fWkf7M9/4vuJrHLkZ9I6Dqe9/+NHU79i8GNmzT8vkR16czIIAYDFc1PL83+s\nTnvwZ85P28AL3/t2IqvMSXvv5liyYae3e/r8YY4cLWdYPPtfdXrvZZmrHl6wE580j3OUc5iVpB1y\nevVerbucjm/VeSA8tjs1O6f/+vW87mt/lcj/xy/9ZlroTV9ytDeGgC7nG8CEysqGTl4GLJG0F/g9\n8pcZM7sZuI1s5Mtu4BXg3+bHmraTHm3zqZvZbWQn07oyHQNuI47M6T0B7juwjaTNs9Ll9HacvHNn\np6/eXYPHYPDEB8q7tj7GGan3hqfmnJ7Ies/6hUR2/OFGvsl0Np4Bn3namxPZWctSg7cwtVcAnL0o\nNczLFqSy/fenMZ56nLdCr01Wna728YEuurpaP6S4Hs8AP2fpq8NK+lw3z0gTxs89b+eUr77vf7r5\n/9kF6besJydcmxNplfvFzK4Z57gB1xcca7mdnLJhArwRI1XvB1RkwB3cB8CI06N3yhw+lo5omOG4\niAYPpe6g1cv89+wfnJXKFy5dmMi6Rq5NZC8+tsUt81Rl4VlXJbKRuecksqM/kb4dzexLrcQ7Lkjf\nlhbM9Jv7gqH03r78+J5U9+7UwztjybJEVnVcesPDqQHprpQ36BXHsHoGuBkaGYtVNq133o5HhsUD\n/new//jT6UO8FS1fqGU99anGlDXqHmV76kV4xtrtVTkPD9d147hkqs4IndcvnpnIAM47I32gXHpu\naui/0H9mIpv/Qhq+orL4okRWfTF1+wAcfTGd31AdSc+7u8dxRTk/wBl96QfnGX1L0/J6/Y+Vh37q\njYls+aLUaP3iqvRhP+LYtreem+qePdP/TnPkkXsS2fBLzyeyY3v3JDJz2oXH4FB6X3tnlo8V1Yz3\nt+xH0UYeEmVr7vXUvV/sS/d/w80/93Vry1apYSoFQzhPdaasUXcNuDeEwGs1jvsECgy443v3hk56\nH1+9xuk9EH5xEeyszk3krzndewCkPcyLzkv97I/uvjyRDaxOjdbLR65wagl6MV07YPHLzkfj4+mb\nx8CBbyWyysp3JLIX5qcujN6V/kP4bRemMu9h+NbzUmN9dCA1rOfMS/N6D2GA555+LJGNHE3TDhxM\nDb1Hz7zU1+ZMh2DWJLhewO/lTxbDjk/d4/Cu+1x5I2/ijSBO7nVpJ1PWqDeFZ+jBH1fmpHXdNN4H\n2ZIPnqf7lpI6VWDRrLRRLe5LPxCfOS998HxzSWr81y5Oh7idNs83oi85Pv6DL6RO5xkvpt8NTtNl\niezpM1MDPn9Bqvt1y31Ddv6i9LxXLUp1n704db8cHUh/+Mf7DySyoZf8+EzDh9MH18iRw2m6o+lD\nuPsVZ57EzPTeeMP9GqGZPmXZXn5VBQ+Zks8eb/RLWQb7/Xsz+EJ6H1tBNvoleuonnbKjX8D3yZft\n/buTnDx/vleek27l0DNwdtoVXXP6S4nsnIVpj/6iY2mZ339t2nv/mfPS21n0MWjEmcL3xIvp+Tyy\nP023aI4zCacnfaCcOc/TLd6yInXpvOGM9LF3wRmLE9lLD6UTe7qdkVJH9/4wkQ085y9mc/xHzySy\nEccvfvyF9OOiKukDocuZkewMPae7Db8+r/fpyTx/cr8NsljptXSHL5asT9mH2eHd/vDsLucB2SrC\npz7JlPWV9y47h+P796T5PWM/kj6ZS4+eKXog1D88uipu2rl9qTvgjNlpg104K023bE6a7qzFjkvm\n+WHWvTY1mH3d3giftEEvmJn2OodGUkO2+jTnA3FBN+01C9LzuWh5aqzPWpy+OhzZm45z8O51EYNO\nb31g/9OJbPhQ+nAdGUjPe8gZtlE5nKbrmZ9ex4uvXMg9XzvxAfDMC92sXOTMt3fwDGt5A55yDn3s\nIa1nq/G+dyzrMQ7WDfG8+/ti7XnOd6tD/gfUZgn3yxSmkR95y/FiungG/XXpB8x2UNagTxaeQb90\nZVMhO0pT1qBPFvUGHSht0NuBZ9C9Xno7qDfogGvQ20kY9WlGWVeL1yRcl8xA2qsGONOZYr5wdjqT\n8cx5abrVp6U+3/OXpH5tLzgZwLze9Ae8qC/9ODhiaS/2Z89ODfOBI6mRON8JrXBGj9+jf+Wp9GPl\nMceF8sqeR9z89VRfcdwnB/xX/KGX02tZHUoNrjcrtHI0vd/DR9L77b3IdDU0pNHJX9KtUrpHXzBK\nxtPdjAn2xiAN+j8Rhg8XHGgB4X4JgiDoEKT4UHpKURTq1gvT6+H11JvBm5AEsGJhOjxvhjMCYem8\ndFTKP12W9spXnZ6OFZ8903+lHnDGYZ9+TjoefvaMtF+1yom1dsGylYls+Pn0w+SLD+xw6+PNAxjY\nvyeRHXs67b2XLq9gSOLQ4XK+ZW+q/+Ar6f0aeMkrLzUgBSNv8WyNNwW/xymz14ln4r0c9Tr9776C\nMTY9ju7Bki8ZPc7byCxnmGPRgLWR4zGksVE60qgHQRCMx8n72tRewqgHQTDtkDUWfvhUIox6EATT\nknC/TDJe6F0vxrq6HVmB79zztXt63PxVR+aU5zWTEWckBsAsZ8bl4MvpCJTFi1Pf+0+eleruPpbm\nPfKcPzV+0JmI0+MsInKBo7v/7nSRg5lLVySyIWc24OEH73XrI+c+DL2URuh75el0BEtlVjqOf+SV\ndAJZkX92+Hg60qXLc2J7eT0/++FyS8UVfPpx8fzac51xJPMsLXS2k3eBpT/9uQVGbo7nlHfOe0bB\nyKZ6FvU418cPj4Q1M011DDKfemcyZY16EARBuxCiJ3rqQRAEnUO4X4IgCDqEcL8EQRB0GJ059ahJ\noy5pD3CYLLT4sJldLGkR8NfAOcAe4N1m5s++Gats5ytSxVkQuuKsJ1o4+ajkl6mubmfCjiPzPqh6\nAcKKPtx68b29CJFeuhlOHPjjzofJ4YKJT96H0hFndScvto63AtCgM9HIi1h5dM9utz7dc9L76E0g\nOv5C+tF5lhcV0ZlQ1NVTvm9W6U3L7J2VflB148Y5c+j7up1gYOXWVgdgzox0ds6y42kB8x1LNc9Z\njKNrIE3o6QCY54RvnjWQui5mzyt3jt29qe5KQTiLRu5ZI7Sypy7pSuDP8iI/ZWY31R3/D8Av5/92\nA68HTjOzFzwb2mx9WvGw+jkzW1NTmU3AXWa2Crgr/z8IgmDKIGUjispsY5ejCvBx4CpgNXCNpNW1\naczsj3MbuQa4AfgHM3uhJkm9DW2KdryBrOfHywhuAa5ug44gCIIJM9pTL7ONwyXAbjN7wswGga1k\nNrCIa4DPN1H1cWnWqBtwp6T7JW3MZUvNbH++/yyQDnQOgiA4yXSp3DYOy4HaVVb25rIESbOAK4Ev\n1og9G9oUzX4ofYuZ7ZN0OnCHpBPiopqZSf4aWfkJbARYuSKduBIEQdAuGvSpL5FUG4lus5ltnoDa\nfw78rzrXS2JDzeybEyj7VZoy6ma2L/97UNKtZK8iByQtM7P9kpYBBwvybgY2A6xds2ZyVuANgiDI\n6Sq/8PfzY/i79wG1IUpX5DKPDdS5XgpsaFNGfcLuF0mzJc0d3Qd+HngQ2A5cmye7FvhyMxUMgiBo\nBy1yv9wHrJJ0rqQZZIZ7e30iSfOBn6XGHo5hQ5uimZ76UuBWZQsbdwOfM7OvSboP2CbpOuAp4N3N\nVjIIgqCVSObGem8UMxuW9D7gdjKPzi1mtkvSe/PjN+dJ3wX8nZnVjsl1bWizdZqwUTezJ4A3OvJ+\n4PJmKgVw3BmjPGNWuqxbz7x0FXp3nHkB3hhybwXzsmV648xV8V+I3KXvHNmwM358wBlnPuSMSa86\neQGGj6YL+nq6q854+MH+59LynMWb5QRg85aOA7CRdIy0d93cQFtOOnNWPK7M9e+hFzSq21kUvG9R\n2iarg2m9hwfS8mb3pul65/s/v5GhNO0CJ/hbl7Mm86xZad6+uWl95h1Py5uRrsUCQO+CcgPqvfs1\nw1mysXtuKmukXbQCUaoXXgozuw24rU52c93/nwE+UydzbWizxIzSIAimH2rIp35KEUY9CIJphyhe\nTvBUJ4x6EATTkuipB0EQdAhS9NSDIAg6B0F3yZWaTjXCqAdBMO0In3oQBEEnocbWiD2VCKMeBMG0\nxFkLvCOYskZ9cDidHDEI9M44cSJE95IzqQynizEULUxRJl3RRKNKbzohpVq3EET3rNkMOpOAvAU6\n3EU7nAlAI8fShSG658zn2N4fOmnTyUZlJ3B4C3zUnx/4k0ysOpLqGRqiMuvEGS1zX/96jj3zdKn6\nVPrS2TC9Zyxw03bPOnEBlTnn9TF82LluzsSXrp40XVdv2gb6Tkv1Fl3bwZdeOeH/3vlw/OUTF9k4\n/nKVuSvTxUG6jqeTnOb2pPemb76zQgfQMzv9WVd60wlEXc7CFJ6sMitdnKZr5sxEVh0YcOvTe8Yy\nJ/+Jv6W+FXBs71NJuuFX0slvrUDRU58a1Bt0oCmD3ghlDDpQ2qA3S6sNerN4euoNOlDaoDdCvUEH\nShv0dlBv0CE16IBr0Jul1Qa9WcoYdPANelsRVMZbAeMU5ZQy6kEQBK1AhPslCIKgcxCoEj31IAiC\njiGMehAEQacg+RE/O4Aw6kEQTDtE9NSDIAg6B0FXT2eOaQyjHgTB9EMqXLzmVCeMehAE0w8Vr0h2\nqhNGPQiCaYcQ6tCIXuOelaRbJB2U9GCNbJGkOyQ9nv9dWHPsBkm7JT0q6Yp2VTwIgmDC5D31Mtu4\nRUlX5vZut6RNzvHLJL0saWe+/ZeyeSdCmZ76Z4CPAZ+tkW0C7jKzm/KKbAI+IGk1sAG4EDgTuFPS\n+WbmB6kYgyEnDsnQsVQ2ty+dcjyj8EakX7t75swrVR8vHowXK8WbLt/IQtheQApzwhF4uPFlCnR3\nsyhNW/J1dMai0xOZV8cuZ6FwcxYUB3/R60pfmt8LPeCd94zFzkLNzvR0gJEj6aLHXn1I1zin6pxP\nV2+6CHf37DR0QM98P0xA9xynDTmLeI84sVYqTkwWb/p/9zwnho53zvgLiHfPTn83Xoyi3mVnpWqc\n0B5dM591dXcVtJdW0IqeuqQK8HHg7cBe4D5J283sobqk3zKzd04wb0OMe1Zm9k3ghTrxemBLvr8F\nuLpGvtXMBszsSWA3cEkzFQyCIGg5EurpLrWNwyXAbjN7wswGga1kdrAMzeQtZKKPqqVmtj/ffxZY\nmu8vB56pSbc3lyVI2ihph6Qd/f39E6xGEATBBMhHv5R0vywZtVX5trGmpLI276ckPSDpq5IubDBv\nQzT9odTMTFLD60KZ2WZgM8DaNWs6c12pIAimJFlAr9Lj1J83s4ubUPdd4CwzOyJpHfA3wKomyhuT\nifbUD0haBpD/PZjL9wEra9KtyGVBEARTh8Z66mMxrs0zs0NmdiTfvw3okbSkTN6JMFGjvh24Nt+/\nFvhyjXyDpJmSziV7Gt3bXBWDIAhaj7q6Sm3jcB+wStK5kmaQDRTZfoIe6QxJyvcvIbO7/WXyToRx\n3S+SPg9cRuZX2gv8HnATsE3SdcBTwLsBzGyXpG3AQ8AwcP1ERr4EQRC0Fckd1dMoZjYs6X3A7UAF\nuCW3g+/Nj98M/EvgNyUNA8eADWZmgJu32TqNa9TN7JqCQ5cXpL8RuLGZSgVBELQVqWUrkuUuldvq\nZDfX7H+MbFh4qbzNEjNKgyCYdmRRGjtzRmkY9SAIph8t7KlPNcKoB0EwPQmjHgRB0CFE6N0gCIJO\nQo3FZDqFmLJGvaL0KXpkIA0E1NuTjpjsLhhF6d3EZvxqIwPHE5k5wYqsYOiUGzSqJF6grop3fhX/\n/KwvDSblpfX0zBxekciqXkCvnuaut6fbvb7OdXSDmxXoHnGCU5Uts+q0gYoTOGx4Tho0rIjuOXNT\n3V5Ar1fSIGFe4C8vrxeUzQvIBf55e8HWPD0VJ2Betf9gIiu6N16AspYgIHrqQRAEnUEWTz186kEQ\nBJ1BjH4JgiDoLDp15aMw6kEQTD8kKPjedKoTRj0IgumHYvRLEARBZxGjX4IgCDoDxYfSIAiCziKM\nehAEQcegiP0SBEHQMUjujOdOIIx6EATTDwlinHoQBEHnUBQX6VRn3EeVpFskHZT0YI3s9yXtk7Qz\n39bVHLtB0m5Jj0q6ol0VD4IgmCijo1/KbCXKujK3d7slbXKO/7KkByT9QNI/SnpjzbE9uXynpB2t\nOLcyPfXPkK2v99k6+Z+a2Z/UCiStJlsR+0LgTOBOSedPZPHpnm4nMtyQSqXzIvkBWFdaDS+6YNkn\nuJfXRsqfqo1UnULT/F7EwC4nEqAbZbGgUbpRCJuYjOFd80YiJXrI8Xmac81LUxQJcPBYqse5j971\n9aI0evem0vdSmregnfYsWJwKvfp419eLlOhEVKyUjExZiDPGu9KT6vGuo3feRbHNvWvZKlox+kVS\nBfg48HZgL3CfpO1m9lBNsieBnzWzFyVdBWwG3lRz/OfM7PmmK5Mzbk/dzL4JvFCyvPXAVjMbMLMn\ngd3AJU3ULwiCoPUoH/1SZhubS4DdZvaEmQ0CW8ns4KuY2T+a2Yv5v3cDaezqFtLMl4L3568Ut0ha\nmMuWA8/UpNmbyxIkbZS0Q9KO/v7+JqoRBEHQIPnolzIbsGTUVuXbxpqSStu8nOuAr9b8b2Qejfvr\nyp0wE/1Q+kngQ3mFPgR8BPjVRgows81kryGsXbPGJliPIAiCCdDQOPXnzezipjVKP0dm1N9SI36L\nme2TdDpwh6RHcu/IhJlQT93MDpjZiJlVgb/gxy6WfcDKmqQrclkQBMHUQZkfv8w2DqVsnqR/AnwK\nWG9mr7omzGxf/vcgcCstcFdPyKhLWlbz77uA0ZEx24ENkmZKOhdYBdzbXBWDIAhay+jKRy0Y/XIf\nsErSuZJmkA0U2X6CLuks4EvAe8zssRr5bElzR/eBn+fHtnTCjOt+kfR54DIyv9Je4PeAyyStIXO/\n7AF+A8DMdknaBjwEDAPXT2TkSxAEQVsRLQkTYGbDkt4H3A5UgFtyO/je/PjNwH8BFgOfkAQwnLtz\nlgK35rJu4HNm9rVm6zSuUTezaxzxp8dIfyNwYzOVCoIgaCvqalmYADO7DbitTnZzzf6vAb/m5HsC\neGO9vFliRmkQBNOTCOgVBEHQKUQ89SAIgs5B6tjYL2HUgyCYdohYJCMIgqBziNC7QRAEHUQskjH5\n9PakVRsaTiPQ9aSBGxkeGnLL9KLQeZESVTJaXVGUvTJ6G8F7Teya2ZfKGmikbpRG73XUifDnpfOv\nbflIkGXrU/paeumKIlYOp+dYFnPamh+lMdXhRXgEqMxJIyhWB9JIkh5uu3Dq47WVRiIiuhEinXtr\nw/5vsazutrpIwv0SBEHQIcSH0iAIgk4ihjQGQRB0DFKMfgmCIOggwv0SBEHQOUhNLd84lQmjHgTB\n9EPF66Ke6oRRD4JgGhIfSoMgCDoGhVEPgiDoIER8KA2CIOgYJLriQ2kQBEGnoI79UDruWUlaKenr\nkh6StEvSb+XyRZLukPR4/ndhTZ4bJO2W9KikK9p5AkEQBI0yOvmoBQtPI+nK3NbtlrTJOS5Jf54f\nf0DSRWXzToQyj6ph4HfMbDVwKXC9pNXAJuAuM1sF3JX/T35sA3AhcCXZYqud6bwKguAUJZt8VGYb\ns5TMtn0cuApYDVyT28BargJW5dtG4JMN5G2YMgtP7wf25/uHJT0MLAfWA5flybYA3wA+kMu3mtkA\n8KSk3cAlwHcaqVilKw2/uGB2GoFu6MihtM4FkfzcSIJedMDqxKMDyol+Vx0aoqsnjTDp4kW/85J5\nUfYcmRcpsQg38p6nx+u9lLy2hZEAq2m0zNI4cbG96IBFva6y99a7luZE6pRzr7tmpG3Xywt+PUdK\nRkX0cKN3OtesIR+zFznUa/tOdElPT8/cBb6edn3MVMtGv1wC7M4XkUbSVjIb+FBNmvXAZ83MgLsl\nLZC0DDinRN6GacipJOkcYC1wD7A0N/gAzwJL8/3lwDM12fbmsvqyNkraIWlHf39/g9U+tSht0IMg\nmDTU1VVqA5aM2qp821hTTBl7V5SmlK1slNIfSiXNAb4I/LaZHZJ+3H80M5NkjSg2s83AZoC1a9Y0\nlDcIgqBZRqqlzc7zZnZxO+vSSkoZdUk9ZAb9r8zsS7n4gKRlZrY/f5U4mMv3AStrsq/IZUEQBFMC\nA0asJX3JMvauKE1PibwNU2b0i4BPAw+b2UdrDm0Hrs33rwW+XCPfIGmmpHPJPg7c22xFgyAIWoYZ\n1Wq11DYO9wGrJJ0raQbZIJHtdWm2A7+Sj4K5FHg5d12XydswZXrqPw28B/iBpJ257D8BNwHbJF0H\nPAW8G8DMdknaRubsHwauN7Pm1nMLgiBoIUZD7pficsyGJb0PuB2oALfkNvC9+fGbgduAdcBu4BXg\n346Vt9k6lRn98m38ARgAlxfkuRG4sYl6BUEQtA0zGGlmxNUJZdltZIa7VnZzzb4B15fN2ywxozQI\ngmmIUW1BT30qEkY9CIJphxkMNjCH41QijHoQBNMOw1rmfplqhFEPgmBa0ooPpVORMOpBEEw7zKDa\nmnHqU44w6kEQTEvC/RIEQdAhVM0YHAmjHgRB0DGET32SMefVqGyI1OIyS4ZY9cLIOsOfvNCdXQ0E\nZCy78orX9Nxwqq6O8uFFvbReGGLvvN0Qxo6ORkIBl8Wrtw05YW2LQq167cI7RydUrg15YW3Lhckt\nCr1rXg/SKbPS5O+hnnas2dnlhPh1wzn3zW657rHIZpRGTz0IgqAzMGtVQK8pRxj1IAimHQYxozQI\ngqCTiJ56EARBh5CNfokwAUEQBB1DjH4JgiDoELLQu2HUgyAIOobwqQdBEHQIrVr5aCoSRj0IgmmH\n0bnj1MssPL1S0tclPSRpl6TfyuW/L2mfpJ35tq4mzw2Sdkt6VNIV7TyBIAiCRskWyaiW2ppB0iJJ\nd0h6PP+70Enj2tj8WKGdLaJMT30Y+B0z+66kucD9ku7Ij/2pmf1JXQVXk62KfSFwJnCnpPNj8ekg\nCKYKk+h+2QTcZWY3SdqU//+BujSujTWzh/LjiZ0di3F76ma238y+m+8fBh4Glo+RZT2w1cwGzOxJ\nshW0Lynd2AU9AAATQElEQVRboSAIgrZj2YfSMluTrAe25PtbgKuTqjRuY8ekXESpHEnnAGuBe3LR\n+yU9IOmWmteK5cAzNdn2ehWUtFHSDkk7+vv7G654EATBRBn1qZc06ktGbVW+bWxA1VIz25/vPwss\nHSuxY2PBt7OFlP5QKmkO8EXgt83skKRPAh8ie5P5EPAR4FfLlmdmm4HNAGvXrEkeh17Uv6oXee8k\n4kUrnCy8/kPZ6IngR1D0IgGWjQbp4Ua2nFn+mrn5S9bHutO2UhSFsGzkyKoXDdJrA05kQu86FrVn\nL8JkV08a/tOPJlrSB+zk7ZrZ13Qk1LQ+Jctrsd7xMGC4vPvleTO7uOigpDuBM5xDHzxBp5lJKlRa\nb2NzccN2tpRRl9STK/srM/tSXsEDNcf/AvhK/u8+YGVN9hW5LAiCKUyrDfpUJvtQ2hqfupm9reiY\npAOSlpnZfknLgIMF6RIbm5ddZGcLKTP6RcCngYfN7KM18mU1yd4FPJjvbwc2SJop6VxgFXDveHqC\nIAgmk0nyqW8Hrs33rwW+XJ+gyMbmx4rsbCFleuo/DbwH+IGknbnsPwHXSFpD9lqwB/gNADPbJWkb\n8BDZV93rY+RLEARTiUkc/XITsE3SdcBTwLsBJJ0JfMrM1lFgY83sNuDDnp0di3GNupl9G98Fe9sY\neW4Ebhyv7CAIgpOBTdIiGWbWD1zuyH8ErMv3i2wsZvaeRnXGjNIgCKYlw525ml0Y9SAIph9GBPQK\ngiDoGFo5+mWqEUY9CIJpR9ZTP9m1aA9h1IMgmHY0OPnolCKMehAE0w+LnnoQBEHHEItkBEEQdBDZ\nh9KTXYv2EEY9CIJph2HRUw+CIOgkwqfeATQSmjbJWxC2dTLw610uFL4qfjobScv00nrpyiKndRXV\np+y98dJ5sqoTqraIsuFqvTZg3WlIXfWkoXOrA8fSdN1+Hc0J0+uFsHXbrhuOt1wbbzpKYxuiPLYr\ncqQZNLlS3ZRlWhn1IAiCUaKnHgRB0CFko19Odi3aQxj1IAimHWYw1KFd9TDqQRBMO6KnHgRB0EnE\njNIgCILOIXrqQRAEHUa1Q416mYWneyXdK+n7knZJ+oNcvkjSHZIez/8urMlzg6Tdkh6VdEU7TyAI\ngqBRLHe/lNmaYSw7WZduj6QfSNopaUej+WspM4NlAHirmb0RWANcKelSYBNwl5mtAu7K/0fSamAD\ncCFwJfAJSSdv5k4QBEEdBgwNl9uaxLWTBfycma0xs4snmB8oYdQt40j+b0++GbAe2JLLtwBX5/vr\nga1mNmBmTwK7gUvG0xMEQTBZjM4oLbM1SZGdbFv+UnPNJVUk7QQOAneY2T3AUjPbnyd5Flia7y8H\nnqnJvjeX1Ze5UdIOSTv6+/vLVCMIgqBlNOB+WTJqq/JtYwNqiuxkPQbcKen+uvLL5n+VUh9KzWwE\nWCNpAXCrpDfUHTdJDXmfzGwzsBlg7Zo1HTq4KAiCqYjR0IfS5+tcIicg6U7gDOfQB0/QObadfIuZ\n7ZN0OnCHpEfM7JsN5H+Vhka/mNlLkr5O5is/IGmZme2XtIysFw+wD1hZk21FLguCIJgatDCgl5m9\nreiYpCI7WV/GvvzvQUm3krmsv0mxnS2kzOiX0/IeOpL6gLcDjwDbgWvzZNcCX873twMbJM2UdC6w\nCrh3PD1BEASThQFDI+W2Jimyk68iabakuaP7wM8DD5bNX0+ZnvoyYEs+gqUL2GZmX5H0HWCbpOuA\np4B3A5jZLknbgIeAYeD63H3TNF6I1alGI3V0Q8uWDPFbNpxqYf6ucmFtvXQeZc+76PyaCb3biB6P\nstey6oQNrg4NJbKKo9sNDzyUhugFwAu9WzakbkmfQiMhbZtta6V0tCnEbqG+yQu9exOOnZR0JvAp\nM1tH5ie/VRJkNvlzZva1sfKPxbhG3cweANY68n7g8oI8NwI3jld2EATByWIyJh8V2Ukz+xGwLt9/\nAnhjI/nHImaUBkEw7YhFMoIgCDqMCOgVBEHQIWRDGnWyq9EWwqgHQTDtMIPB5kMATEnCqAdBMC3p\n1CiNYdSDIJh2mImRcL8EQRB0BrFIRhAEQSdh4X4JgiDoKGL0SxAEQYdgBsMx+iUIgqBzsOipB0EQ\ndAgGhE99cnGj9pWMFicnmt5UpJmok2WjJxbmLxkBsWz0vK7ucpEFi87Zu2c24kQ7LHlvvbyFaZu4\nlqWvmZOuy4nGCH47d6M0lrw3TUdZnOQIipNGGPUgCILOoSuMehAEQWcgg+40FH5HEEY9CILph0El\neupBEASdgYBKtTNj74ZRD4Jg2iGDSocGVC+z8HSvpHslfV/SLkl/kMt/X9I+STvzbV1Nnhsk7Zb0\nqKQr2nkCQRAEjWNUqtVSWzNIWiTpDkmP538XOmkuqLGjOyUdkvTb+bFCO1tEmZ76APBWMzsiqQf4\ntqSv5sf+1Mz+pK6Cq4ENwIXAmcCdks5v1eLTQRAEzSKjaYNdkk3AXWZ2k6RN+f8fqE1gZo8CawAk\nVYB9wK01SRI7Oxbj9tQt40j+b0++jfXesh7YamYDZvYksBu4pGyFgiAI2o3M6B4eKrU1yXpgS76/\nBbh6nPSXAz80s6cmqrDUTA5JFUk7gYPAHWZ2T37o/ZIekHRLzWvFcuCZmux7c1kQBMEUweiqjpTa\nmmSpme3P958Flo6TfgPw+TqZZ2cLKWXUzWzEzNYAK4BLJL0B+CRwHtlrw37gI2XKGkXSRkk7JO3o\n7+9vJGsQBEGTGLLhUhuwZNRW5dvG2pIk3SnpQWdbf4JGM2MML4ekGcAvAF+oETdsZxsa/WJmL0n6\nOnBlrY9H0l8AX8n/3QesrMm2IpfVl7UZ2Aywds2azvwMHQTB1MRA5Xvhz5vZxYVFmb2t6JikA5KW\nmdl+ScvIvB1FXAV818wO1JT96n6dnS2kzOiX0yQtyPf7gLcDj+QVHOVdwIP5/nZgg6SZks4FVgH3\njqcnCIJgshCGqsOltibZDlyb718LfHmMtNdQ53oZw84WUqanvgzYkn+V7QK2mdlXJP2lpDVkrxN7\ngN8AMLNdkrYBDwHDwPUx8iUIgqmFockxSzcB2yRdBzwFvBtA0pnAp8xsXf7/bLIO82/U5f+wZ2fH\nYlyjbmYPAGsd+XvGyHMjcON4ZQdBEJwUzGDk+CSosX6yES318h8B62r+PwosdtIV2tkiTqkZpapM\nPFRtYZlNhL+dLNwQtk2HF+5paTr/OpbV4d/bSQmJS1HY33QMc2VmX6kyPVnZ0MSFZZZcJblsON6m\nOeXD8Rp0qAPhlDLqQRAErcGgeX/5lCSMehAE0w8zsDDqQRAEnUO4X4IgCDqFKjYJH0pPBmHUgyCY\nfhjRUw+CIOgUDMPiQ2kQBEGnEEMagyAIOgjDYvRLEARBh2CTOFFrkgmjHgTBNKSKVQdOdiXaQhj1\nIAimJZ0aZzCMehAE0w6zGP0SBEHQQVj01IMgCDqKMOonn1MhTG47aCbksI1MTsPt6ikfWtZjqt3b\nsqF7/bC95cIIN3J9mrmPnTrKoynC/RIEQdBJGNXq4MmuRFsIox4EwbQjCxPQmW8wYdSDIJh+WOd+\nKC29JpqkiqTvSfpK/v8iSXdIejz/u7Am7Q2Sdkt6VNIV7ah4EARBM5iNlNqaQdIvSdolqSrp4jHS\nXZnby92SNtXIC+1sEY0sdPlbwMM1/28C7jKzVcBd+f9IWg1sAC4ErgQ+IWlqfQULgmCak7lfymxN\n8iDwi8A3ixLk9vHjwFXAauCa3I5CgZ0di1JGXdIK4B3Ap2rE64Et+f4W4Ooa+VYzGzCzJ4HdwCVl\n9ARBEEwGZkZ1ZLDU1qSeh83s0XGSXQLsNrMnzGwQ2EpmR6HYzhZS1qf+/wL/EZhbI1tqZvvz/WeB\npfn+cuDumnR7c9kJSNoIbMz/HZi/5LQHS9alHSwBng/d00b3ydYf594cZzdbieGhw7c/u/euJSWT\n90raUfP/ZjPb3GwdalgOPFPz/17gTfl+kZ0tZFyjLumdwEEzu1/SZV4aMzNJNl5ZdXk2A5tzHTvM\nrNDf1G5Opv7QfXKIc5+e5z6KmV3ZqrIk3Qmc4Rz6oJl9uVV6ytrZMj31nwZ+QdI6oBeYJ+n/Bw5I\nWmZm+yUtAw7m6fcBK2vyr8hlQRAEHYeZva3JIsaymUV2tpBxfepmdoOZrTCzc8g+gP69mf1rYDtw\nbZ7sWmD0ibQd2CBppqRzgVXAveOfVxAEwbTkPmCVpHMlzSCzs9vzY0V2tpBGRr/UcxPwdkmPA2/L\n/8fMdgHbgIeArwHX2/jjglrpn5oIJ1N/6J5++uPcpwmS3iVpL/Bm4G8l3Z7Lz5R0G4BlSzC9D7id\nbIThttyOQoGdHVOnWUOu8CAIgmAK00xPPQiCIJhihFEPgiDoJMys4Y3sS+3Xyfzmu4DfyuWLgDuA\nx/O/C3P54jz9EeBjBWVuBx4cQ+eNZGM5j9TpfzbfHgD+AfhWI/qBbwCPAjvz7fQC/T8JPAK8AvSP\nnjfw73P54fzYt9qg9wdkk7huqb/uwL8ADLinjef9A2AP2fjZWt3vzs/9CHCojbrrz/2x/Fy/l9fl\nu20699E2d7Tuuv974K+BJ4CXgSfbqLvV7X0GmV/7sfze/YsG7/utNfv9DZ57o7p3A39O7iauOT7a\n5i+eiP3q9G1imWAZcFG+Pze/SauBDwObcvkm4I/y/dnAW4D31t/o/PgvAp9jbKN+aa73SJ3+dXmj\nXg38HfD9RvTnP7JxGwfZCJ53ABcBX83r/Bjwb4CP5vp+E/h+G/ReCgj4e+B9Ndf9cWAH8CPgv7Xx\nvEev/f8im8o8N/8xPwz8Wa7z9Dbqrj/3/w84kN/zTwMvtuncR8/7KCe29wNkRv3DZO32r9uou9Xt\n/Q+AP8z3u4AlDd73Z8h+Ax8mM/CNnHujukX2W7uq5thcsin3d5e5jtNxm5D7xcz2m9l38/3DZD/u\n5RRMaTWzo2b2beB4fVmS5pD1fP5wHJ13Wz6zqk7/bWQ9h+XA+cDoEuGl9JchHx86z8z+Ntf7WeCK\n/Lz3kRn7LWQNbaANeu+2rEX/BfATedmHyX4YtwILgK/k2dpx3qPX/mPA1bnuYbIf3JXAFjM72Ebd\nJ5w7MEg2K3E52YiA3bm8ZfrzMkbP2+rau8gM3XqymdaXt1F3q9v7rwL/T56uambJ7M5x7vt3yXrj\n64FPkI2pbpduI/ut1U6N/xDwRwXlB7TApy7pHGAt2et/w1NayW7SR8hcF83qX8aPx3eW1Q+wRdJO\nSb8rSc7x5WSvoKPsBV5Let7X5frbqXc5gKR3kJ3vfyN7re3P07T7vJfn13w5Wft5DXCrpCsnQ3e+\n/ymy+Q+fIXNNvDeXt1K/S37uC8h6yUvNbC+ZC2ao3bpr9E+ovUtakO9+SNJ3JX1BkpdnrPv+apsn\nM+xfnQzdeRkXASvN7G/H0jXdacqo573sLwK/bWaHao/lT9kxx0tKWgO8xsxubVY/8AtABfjjsvpz\nftnMLgR+Jt/eUyJPH5nf79XzlvSvgYtz/e3SS65rLlnQn/9rIte9Sf0Vsmv+EFkMjiPANWQ96flt\n1j16z78EfM7MlpO5Rv5SUle7z72mvT1Ldt71TMa5N9Peu8l61v9oZhcB3wH+pKT60fs+2uZ7yNv7\nJOhGUheZm/N3yuaZrkzYqEvqIbvJf2VmX8rFB/LXp9HXqPGmtL4ZuFjSHuDbwPmSvqEsdvvOfPuv\n4+kn+0j3QbKPOosa0I+Z7cv/Hibzj17i6N9H1iBH9f4x8FDNeR8Gfo/sh7aoHXpzVgD7gb8hcwHc\nkF+7LuArki5u13nnnA28geya7yDrJR4gexV+jMwP2u5z/yKZQfndXP4jMj/ukhaf+wnUtbeHyd4Q\nDiiLYDo/r1NbdDv6J9re+8neiEfb7ReAixq572b2JUlvIzPSv2ZmA23WPTplfm5eh2/kbf5SYLvG\niFE+XZnQykf5K+OngYfN7KM1h0antN5EiSmtZvZJ4JN5mecAXzGzy/LDa8roJ/vS/j/IfLsbG9Ev\nqRtYYGbP5z+adwJ3WjYDdk1d2kOSLgX+T7If8Q25fC1Zg9tqZgeVBbhvh957gF8hc7X8wMwur0nz\nNPBlM9vRZv1/BNxnZh/N3S3XkN3z3yTz7/7UZJw7UCXzY3+GrDPwS8BzwAdaqb+OV9u7pAGy9rWd\n7IPh39Pi9laXryXt3cxM0v8ELsvrfDlZ56SR+74W+O9kvu53ksULb6fuXyEbBPAyWYTH0TTfAP5v\nM6uNnhjAhEe/vIXsdesBfjw0ax3ZB5S7yL7O3wksqsmzB3iB7LV1L7C6rsxzGHv0y4fzfFWyXsGo\n/sNk/swfkv3gnyurn6yHd39ezi6ykRyVAv0Xkw1hM7KPdKPn/b28PofJPlo91wa9D+bn98WC6/5t\nshED7TrvB8l6S/W6v0Q2PO8IWS+6Xbrrz/3hvMwn8nv+vTade22bM7K3kp1kI5y+xYlDGtupuyXt\nPZefTTZ65AGy3+pZDd73w8CLue7Defnt0v1Dso+0ctJ8gxj94m4RJiAIgqCDiBmlQRAEHUQY9SAI\ngg4ijHoQBEEHEUY9CIKggwijHgRB0EGEUQ+CIOggwqgHQRB0EP8boI5k8DLRKAsAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f61ea7df668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#plt.pcolormesh([t0+dt.timedelta(10*ii) for ii in range(0,30)],dept[0,:],np.transpose(siplot[:30,:]),cmap=cm1,vmin=-1e9,vmax=1e9)\n",
    "plt.pcolormesh([t0+dt.timedelta(10*ii) for ii in range(0,nlen)],dept[0,:],np.transpose(Nplot),cmap=cm1,vmin=-1e8,vmax=1e8)\n",
    "plt.ylim(400,0)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:python36]",
   "language": "python",
   "name": "conda-env-python36-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}