{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# inter-run comparisons of N contained in phytoplankton\n",
    "    - S3\n",
    "    - Sentry Shoal\n",
    "    - Central Node\n",
    "    - JDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "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 re\n",
    "import dateutil as dutil\n",
    "from salishsea_tools import viz_tools, places\n",
    "import glob\n",
    "import pickle\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "import gsw\n",
    "mpl.rc('xtick', labelsize=14) \n",
    "mpl.rc('ytick', labelsize=16) \n",
    "mpl.rc('legend', fontsize=16) \n",
    "mpl.rc('axes', titlesize=16) \n",
    "mpl.rc('figure', titlesize=16) \n",
    "mpl.rc('axes', labelsize=16) \n",
    "mpl.rc('font', size=16) \n",
    "\n",
    "mpl.rcParams['font.size'] = 16\n",
    "mpl.rcParams['axes.titlesize'] = 16\n",
    "mpl.rcParams['legend.numpoints'] = 1\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plist=['Sentry Shoal','S3','Central node','Central SJDF']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "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",
    "    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,:,:]\n",
    "#stm=np.shape(tmask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_SentryShoal.nc\n",
      "/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_S3.nc\n",
      "/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_CentralNode.nc\n",
      "/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_CentralSJDF.nc\n"
     ]
    }
   ],
   "source": [
    "#saveloc='/data/eolson/MEOPAR/SS36runs/calcFiles/comparePhytoN/'\n",
    "baseloc='/data/eolson/MEOPAR/SS36runs/CedarRuns/'\n",
    "dirname1='spring16spun_Z6'\n",
    "dirname2='hindcast2016'\n",
    "dirnames=(dirname1,)\n",
    "#dirnames=('spring2015_NewSink','spring2015_slowPP','spring2015_KhT','spring2015_diatHS')\n",
    "varNameDict={'Sentry Shoal':'SentryShoal', 'S3':'S3', 'Central node':'CentralNode', 'Central SJDF':'CentralSJDF'}\n",
    "with open('/ocean/eolson/MEOPAR/analysis-elise/notebooks/bioTuning/spathsMaster.txt') as f:\n",
    "    spaths = dict(x.strip().split() for x in f)\n",
    "#spaths={'spring2015_NewSink':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_NewSink/',\n",
    "#    'spring2015_KhT':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_KhT/',\n",
    "#    'spring2015_uzoo':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_uzoo/',\n",
    "#    'spring2015_uzoo2':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_uzoo2/',\n",
    "#    'spring2015_slowPP':'/data/eolson/results/MEOPAR/SS36runs/OrcinusRuns/spring2015_slowPP/',\n",
    "#    'spring2015_lowMuNano':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_lowMuNano/',\n",
    "#    'spring2015_SMELTBFastSink':'/data/eolson/results/MEOPAR/SS36runs/OrcinusRuns/spring2015_SMELTBFastSink/',\n",
    "#    'spring2015_uzPref':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_uzPref/',\n",
    "#    'spring2015_hiNH':'/data/eolson/results/MEOPAR/SS36runs/CedarRuns/spring2015_hiNH/'}\n",
    "ff=dict()\n",
    "for idir in dirnames:\n",
    "    ff[idir]=dict()\n",
    "    for pl in plist:\n",
    "        print(spaths[idir]+'ts_'+idir+'_'+varNameDict[pl]+'.nc')\n",
    "        ff[idir][pl]=nc.Dataset(spaths[idir]+'ts_'+idir+'_'+varNameDict[pl]+'.nc')\n",
    "    #try:\n",
    "    #    pl='Total'\n",
    "    #    ff[idir][pl]=nc.Dataset(spaths[idir]+'ts_'+idir+'_'+varNameDict[pl]+'.nc')\n",
    "    #except:\n",
    "    #    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_CentralSJDF.nc'"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spaths[idir]+'ts_'+idir+'_'+varNameDict[pl]+'.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/data/eolson/MEOPAR/SS36runs/CedarRuns/spring16spun_Z6/ts_spring16spun_Z6_CentralSJDF.nc'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "spaths[idir]+'ts_'+idir+'_'+varNameDict[pl]+'.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1900-01-01 00:00:00\n"
     ]
    }
   ],
   "source": [
    "times=dict()\n",
    "for idir in dirnames:\n",
    "    f=ff[idir]['S3']\n",
    "    torig=dt.datetime.strptime(f.variables['time_centered'].time_origin,'%Y-%m-%d %H:%M:%S')\n",
    "    print(torig)\n",
    "    times[idir]=np.array([torig + dt.timedelta(seconds=ii) for ii in f.variables['time_centered'][:]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lcol={dirname1:{'votemper':'darkgreen','vosaline':'mediumblue'},\n",
    "     dirname2:{'diatoms':'c','flagellates':'blueviolet','ciliates':'orange'}}\n",
    "lsty={dirname1:'-',\n",
    "      dirname2:'-'}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tmins=list()\n",
    "tmaxs=list()\n",
    "for idir in dirnames:\n",
    "    tmins.append(times[idir][0])\n",
    "    tmaxs.append(times[idir][-1])\n",
    "xl=(np.min(np.array(tmins)),np.max(np.array(tmaxs)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "flist=['BritishColumbiaFerries_Tsawwassen-DukePoint_Turbidity-ChlorophyllandFluorescence_20150604T070624Z_20160307T160206Z-clean.csv',\n",
    "      'BritishColumbiaFerries_Tsawwassen-DukePoint_Turbidity-ChlorophyllandFluorescence_20160307T160215Z_20161019T064047Z-clean.csv',\n",
    "      'BritishColumbiaFerries_Tsawwassen-DukePoint_Turbidity-ChlorophyllandFluorescence_20161019T064056Z_20161115T220747Z-clean.csv']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/eolson/anaconda3/envs/python36/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2698: DtypeWarning: Columns (1,3,5) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  interactivity=interactivity, compiler=compiler, result=result)\n"
     ]
    }
   ],
   "source": [
    "dfs=list()\n",
    "for ii in range(0,len(flist)):\n",
    "    dfs.append(pd.read_csv('/ocean/eolson/MEOPAR/obs/ONC/turbidity/nearSurface/search3928586/'+flist[ii],\n",
    "        skiprows=102,header=None,usecols=[0,1,2,3,4,5,6,7,8,9,10],\n",
    "        names=('TimeUTC','CDOM','CDOMQC','Chlorophyll_ug','ChlQC','Turbidity_NTU','TurbQC','Lat','LatQC','Lon','LongQC')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df=pd.concat(dfs,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dts=[dt.datetime(int(r[0:4]),int(r[5:7]),int(r[8:10]),int(r[11:13]),int(r[14:16]),int(r[17:19])) for r in df['TimeUTC']]\n",
    "df=df.assign(dts=dts)\n",
    "df['Lat']=pd.to_numeric(df['Lat'],errors='coerce')\n",
    "df['Lon']=pd.to_numeric(df['Lon'],errors='coerce')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "llon=places.PLACES['S3']['lon lat'][0]-.01\n",
    "ulon=places.PLACES['S3']['lon lat'][0]+.01\n",
    "llat=places.PLACES['S3']['lon lat'][1]-.01\n",
    "ulat=places.PLACES['S3']['lon lat'][1]+.01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "iidfnd2=(df.Lon>llon)&(df.Lon<ulon)&(df.Lat>llat)&(df.Lat<ulat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f0efc2362b0>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABHQAAAECCAYAAACfT4DNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUTPUoSOEEEIIIYQQQghRM/4PolNWmLf3X+wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f0efc229f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "yearsFmt = mdates.DateFormatter('%b %d')\n",
    "fig,ax=plt.subplots(1,1,figsize=(16,1*(len(plist))))\n",
    "ax=(ax,)\n",
    "pl='S3'\n",
    "\n",
    "ii=0\n",
    "idir=dirname1\n",
    "f=ff[idir][pl]\n",
    "p01=ax[ii].plot(df.loc[iidfnd2,['dts']],[float(ik[0]) for ik in df.loc[iidfnd2,['Chlorophyll_ug']].values],'.',color='lightgreen',alpha=.5,\n",
    "               label='Ferry SA')\n",
    "p02=ax[ii].plot(times[idir],2.0*np.sum((f.variables['diatoms'][:,:3,0,0]+f.variables['flagellates'][:,:3,0,0]+f.variables['ciliates'][:,:3,0,0])*f.variables['e3t'][:,:3,0,0],1)/np.sum(f.variables['e3t'][:,:3,0,0],1),\n",
    "                          linestyle=lsty[idir],color='k',alpha=.6,label=idir+' '+'total chl')\n",
    "ax[ii].set_xlim(dt.datetime(2016,2,1),dt.datetime(2016,5,1))\n",
    "ax[ii].set_ylim(0,30)\n",
    "ax[ii].legend(bbox_to_anchor=(1,.5),fontsize=12)\n",
    "#p02=ax[ii].plot(times[idir],2.0*np.sum((f.variables['diatoms'][:,:3,0,0]+f.variables['flagellates'][:,:3,0,0]+f.variables['ciliates'][:,:3,0,0])*f.variables['e3t'][:,:3,0,0],1)/np.sum(f.variables['e3t'][:,:3,0,0],1),\n",
    "#                          linestyle=lsty[idir],color='k',alpha=.6,label=idir+' '+'total')"
   ]
  },
  {
   "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
}