{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DFO Nutrient Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import sqlalchemy\n",
    "from sqlalchemy import (create_engine, Column, String, Integer, Float, MetaData, \n",
    "                        Table, type_coerce, ForeignKey, case)\n",
    "from sqlalchemy.orm import mapper, create_session, relationship, aliased, Session\n",
    "from sqlalchemy.ext.declarative import declarative_base\n",
    "from sqlalchemy import case\n",
    "import numpy as np\n",
    "from sqlalchemy.ext.automap import automap_base\n",
    "import matplotlib.pyplot as plt\n",
    "import sqlalchemy.types as types\n",
    "from sqlalchemy.sql import and_, or_, not_, func\n",
    "from sqlalchemy.sql import select\n",
    "import os\n",
    "from os.path import isfile\n",
    "import pandas as pd\n",
    "import netCDF4 as nc\n",
    "import datetime as dt\n",
    "from salishsea_tools import evaltools as et, viz_tools\n",
    "import datetime\n",
    "import glob\n",
    "import gsw\n",
    "import matplotlib.gridspec as gridspec\n",
    "import matplotlib as mpl\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "mpl.rc('xtick', labelsize=16)\n",
    "mpl.rc('ytick', labelsize=16)\n",
    "mpl.rc('legend', fontsize=12)\n",
    "mpl.rc('axes', titlesize=16)\n",
    "mpl.rc('axes', labelsize=16)\n",
    "mpl.rc('figure', titlesize=16)\n",
    "mpl.rc('font', size=16)\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Month</th>\n",
       "      <th>Day</th>\n",
       "      <th>Hour</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Pressure</th>\n",
       "      <th>Depth</th>\n",
       "      <th>Ammonium</th>\n",
       "      <th>Ammonium_units</th>\n",
       "      <th>Chlorophyll_Extracted</th>\n",
       "      <th>Chlorophyll_Extracted_units</th>\n",
       "      <th>N</th>\n",
       "      <th>Si</th>\n",
       "      <th>Silicate_units</th>\n",
       "      <th>AbsSal</th>\n",
       "      <th>T</th>\n",
       "      <th>T_units</th>\n",
       "      <th>Z</th>\n",
       "      <th>dtUTC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.068611</td>\n",
       "      <td>48.300833</td>\n",
       "      <td>-124.000333</td>\n",
       "      <td>1.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mg/m^3</td>\n",
       "      <td>15.31</td>\n",
       "      <td>32.14</td>\n",
       "      <td>umol/L</td>\n",
       "      <td>29.227507</td>\n",
       "      <td>9.7647</td>\n",
       "      <td>'deg_C_(ITS90)'</td>\n",
       "      <td>1.883998</td>\n",
       "      <td>2015-02-11 11:04:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.068611</td>\n",
       "      <td>48.300833</td>\n",
       "      <td>-124.000333</td>\n",
       "      <td>6.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>2.57</td>\n",
       "      <td>mg/m^3</td>\n",
       "      <td>17.13</td>\n",
       "      <td>33.90</td>\n",
       "      <td>umol/L</td>\n",
       "      <td>29.484341</td>\n",
       "      <td>9.6880</td>\n",
       "      <td>'deg_C_(ITS90)'</td>\n",
       "      <td>6.544340</td>\n",
       "      <td>2015-02-11 11:04:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.068611</td>\n",
       "      <td>48.300833</td>\n",
       "      <td>-124.000333</td>\n",
       "      <td>6.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mg/m^3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>umol/L</td>\n",
       "      <td>29.484839</td>\n",
       "      <td>9.6828</td>\n",
       "      <td>'deg_C_(ITS90)'</td>\n",
       "      <td>6.643495</td>\n",
       "      <td>2015-02-11 11:04:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.068611</td>\n",
       "      <td>48.300833</td>\n",
       "      <td>-124.000333</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mg/m^3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>umol/L</td>\n",
       "      <td>30.144549</td>\n",
       "      <td>9.3646</td>\n",
       "      <td>'deg_C_(ITS90)'</td>\n",
       "      <td>10.907117</td>\n",
       "      <td>2015-02-11 11:04:07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>11.068611</td>\n",
       "      <td>48.300833</td>\n",
       "      <td>-124.000333</td>\n",
       "      <td>11.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>mg/m^3</td>\n",
       "      <td>20.62</td>\n",
       "      <td>37.65</td>\n",
       "      <td>umol/L</td>\n",
       "      <td>30.157913</td>\n",
       "      <td>9.3586</td>\n",
       "      <td>'deg_C_(ITS90)'</td>\n",
       "      <td>10.907117</td>\n",
       "      <td>2015-02-11 11:04:07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Year  Month   Day       Hour        Lat         Lon  Pressure  Depth  \\\n",
       "0  2015.0    2.0  11.0  11.068611  48.300833 -124.000333       1.9    NaN   \n",
       "1  2015.0    2.0  11.0  11.068611  48.300833 -124.000333       6.6    NaN   \n",
       "2  2015.0    2.0  11.0  11.068611  48.300833 -124.000333       6.7    NaN   \n",
       "3  2015.0    2.0  11.0  11.068611  48.300833 -124.000333      11.0    NaN   \n",
       "4  2015.0    2.0  11.0  11.068611  48.300833 -124.000333      11.0    NaN   \n",
       "\n",
       "  Ammonium Ammonium_units  Chlorophyll_Extracted Chlorophyll_Extracted_units  \\\n",
       "0     None           None                    NaN                      mg/m^3   \n",
       "1     None           None                   2.57                      mg/m^3   \n",
       "2     None           None                    NaN                      mg/m^3   \n",
       "3     None           None                    NaN                      mg/m^3   \n",
       "4     None           None                    NaN                      mg/m^3   \n",
       "\n",
       "       N     Si Silicate_units     AbsSal       T          T_units          Z  \\\n",
       "0  15.31  32.14         umol/L  29.227507  9.7647  'deg_C_(ITS90)'   1.883998   \n",
       "1  17.13  33.90         umol/L  29.484341  9.6880  'deg_C_(ITS90)'   6.544340   \n",
       "2    NaN    NaN         umol/L  29.484839  9.6828  'deg_C_(ITS90)'   6.643495   \n",
       "3    NaN    NaN         umol/L  30.144549  9.3646  'deg_C_(ITS90)'  10.907117   \n",
       "4  20.62  37.65         umol/L  30.157913  9.3586  'deg_C_(ITS90)'  10.907117   \n",
       "\n",
       "                dtUTC  \n",
       "0 2015-02-11 11:04:07  \n",
       "1 2015-02-11 11:04:07  \n",
       "2 2015-02-11 11:04:07  \n",
       "3 2015-02-11 11:04:07  \n",
       "4 2015-02-11 11:04:07  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PATH= '/results2/SalishSea/hindcast/'\n",
    "start_date = datetime.datetime(2015,1,1)\n",
    "end_date = datetime.datetime(2018,1,1)\n",
    "flen=1\n",
    "namfmt='nowcast'\n",
    "#varmap={'N':'nitrate','Si':'silicon','Ammonium':'ammonium'}\n",
    "filemap={'nitrate':'ptrc_T','silicon':'ptrc_T','ammonium':'ptrc_T','diatoms':'ptrc_T','ciliates':'ptrc_T','flagellates':'ptrc_T','vosaline':'grid_T','votemper':'grid_T'}\n",
    "#gridmap={'nitrate':'tmask','silicon':'tmask','ammonium':'tmask'}\n",
    "fdict={'ptrc_T':1,'grid_T':1}\n",
    "\n",
    "df1=et.loadDFO()\n",
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data=et.matchData(df1,filemap, fdict, start_date, end_date, namfmt, PATH, flen)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize = (6,6))\n",
    "viz_tools.set_aspect(ax, coords = 'map')\n",
    "ax.plot(data['Lon'], data['Lat'], 'ro',label='data')\n",
    "ax.plot(data.loc[(data.Lon < -123.5) & (data.Lat < 48.6),['Lon']], \n",
    "        data.loc[(data.Lon < -123.5) & (data.Lat < 48.6),['Lat']], \n",
    "        'bo', label = 'Juan de Fuca')\n",
    "\n",
    "ax.plot(data.loc[data.Si>75,['Lon']],data.loc[data.Si>75,['Lat']],'*',color='y',label='high Si')\n",
    "grid = nc.Dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc')\n",
    "viz_tools.plot_coastline(ax, grid, coords = 'map')\n",
    "ax.set_ylim(48, 50.5)\n",
    "ax.legend()\n",
    "ax.set_xlim(-125.7, -122.5);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2015"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 2015\n",
    "data2015=data.loc[(data.dtUTC>=dt.datetime(2015,1,1))&(data.dtUTC<dt.datetime(2016,1,1))]\n",
    "idata=data2015\n",
    "yy='2015'\n",
    "fig = plt.figure(figsize = (12,4))\n",
    "gs1 = gridspec.GridSpec(2,3,left=.08,right=.93,hspace=.8,wspace=.7,bottom=.08,top=.9,height_ratios=[5.8,.5],width_ratios=[4,4,3])\n",
    "ax1 = fig.add_subplot(gs1[0,0])\n",
    "ax2 = fig.add_subplot(gs1[0,1])\n",
    "ax3 = fig.add_subplot(gs1[0,2])\n",
    "axb = fig.add_subplot(gs1[1, :])\n",
    "\n",
    "ps=et.varvarPlot(ax1,idata,'N','mod_nitrate','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "#ax1.legend(handles=ps)\n",
    "ax1.set_xlabel('Observed')\n",
    "ax1.set_ylabel('Modelled')\n",
    "ax1.set_title(yy+' NO$_3$ ($\\mu$M)')\n",
    "ax1.set_xlim((0,45))\n",
    "ax1.set_ylim((0,45))\n",
    "ntick=np.arange(0,56,15)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax1.set_xticks(ntick)\n",
    "ax1.set_xticklabels(ntickl)\n",
    "ax1.set_yticks(ntick)\n",
    "ax1.set_yticklabels(ntickl)\n",
    "\n",
    "ps=et.varvarPlot(ax2,idata,'Si','mod_silicon','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "ax2.legend(handles=ps,bbox_to_anchor=[.65,.45])\n",
    "ax2.set_xlabel('Observed')\n",
    "ax2.set_ylabel('Modelled')\n",
    "ax2.set_title(yy+' dSi ($\\mu$M)')\n",
    "ax2.set_xlim((0,80))\n",
    "ax2.set_ylim((0,80))\n",
    "ntick=np.arange(0,81,20)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax2.set_xticks(ntick)\n",
    "ax2.set_xticklabels(ntickl)\n",
    "ax2.set_yticks(ntick)\n",
    "ax2.set_yticklabels(ntickl)\n",
    "\n",
    "viz_tools.set_aspect(ax3, coords = 'map')\n",
    "datanut=idata.loc[(idata.N>=0)|(idata.Si>=0)]\n",
    "ax3.plot(datanut['Lon'], datanut['Lat'], '.',color='darkorange',label='data',markersize=6)\n",
    "grid = nc.Dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc')\n",
    "viz_tools.plot_coastline(ax3, grid, coords = 'map')\n",
    "ax3.set_ylim(48, 50.7)\n",
    "#ax3.legend()\n",
    "ax3.set_xlim(-125.8, -122.4);\n",
    "ax3.axis('off')\n",
    "test=ax3.get_position()\n",
    "ax3.set_position(mpl.transforms.Bbox(points=[[.7,.2],[.97,.99]]))\n",
    "\n",
    "axb.plot(datanut.dtUTC,np.ones(np.shape(datanut.dtUTC)),'.',color='darkorange',markersize=6)\n",
    "axb.set_yticks(());\n",
    "yearsFmt = mdates.DateFormatter('%d %b %Y')\n",
    "axb.xaxis.set_major_formatter(yearsFmt)\n",
    "axb.xaxis.set_ticks([dt.datetime(int(yy),1,1), dt.datetime(int(yy),4,1),dt.datetime(int(yy),7,1),dt.datetime(int(yy),10,1),dt.datetime(int(yy)+1,1,1)])\n",
    "#axb.autofmt_xdate(bottom=0.2, rotation=15, ha='right')\n",
    "#axb.set_title('Sampling Dates')\n",
    "#plt.setp(plt.xticks()[1], rotation=10, ha='right')\n",
    "axb.set_title('Sample Dates')\n",
    "#fig.savefig('/home/eolson/pyCode/notebooks/figs/EvalDFO2015.png',dpi=200,transparent=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 2016\n",
    "data2016=data.loc[(data.dtUTC>=dt.datetime(2016,1,1))&(data.dtUTC<dt.datetime(2017,1,1))]\n",
    "idata=data2016\n",
    "yy='2016'\n",
    "fig = plt.figure(figsize = (12,4))\n",
    "gs1 = gridspec.GridSpec(2,3,left=.08,right=.93,hspace=.8,wspace=.7,bottom=.08,top=.9,height_ratios=[5.8,.5],width_ratios=[4,4,3])\n",
    "ax1 = fig.add_subplot(gs1[0,0])\n",
    "ax2 = fig.add_subplot(gs1[0,1])\n",
    "ax3 = fig.add_subplot(gs1[0,2])\n",
    "axb = fig.add_subplot(gs1[1, :])\n",
    "\n",
    "ps=et.varvarPlot(ax1,idata,'N','mod_nitrate','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "#ax1.legend(handles=ps)\n",
    "ax1.set_xlabel('Observed')\n",
    "ax1.set_ylabel('Modelled')\n",
    "ax1.set_title(yy+' NO$_3$ ($\\mu$M)')\n",
    "ax1.set_xlim((0,45))\n",
    "ax1.set_ylim((0,45))\n",
    "ntick=np.arange(0,56,15)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax1.set_xticks(ntick)\n",
    "ax1.set_xticklabels(ntickl)\n",
    "ax1.set_yticks(ntick)\n",
    "ax1.set_yticklabels(ntickl)\n",
    "\n",
    "ps=et.varvarPlot(ax2,idata,'Si','mod_silicon','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "#ax2.legend(handles=ps,bbox_to_anchor=[.65,.4])\n",
    "ax2.set_xlabel('Observed')\n",
    "ax2.set_ylabel('Modelled')\n",
    "ax2.set_title(yy+' dSi ($\\mu$M)')\n",
    "ax2.set_xlim((0,80))\n",
    "ax2.set_ylim((0,80))\n",
    "ntick=np.arange(0,81,20)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax2.set_xticks(ntick)\n",
    "ax2.set_xticklabels(ntickl)\n",
    "ax2.set_yticks(ntick)\n",
    "ax2.set_yticklabels(ntickl)\n",
    "\n",
    "viz_tools.set_aspect(ax3, coords = 'map')\n",
    "datanut=idata.loc[(idata.N>=0)|(idata.Si>=0)]\n",
    "ax3.plot(datanut['Lon'], datanut['Lat'], '.',color='darkorange',label='data',markersize=6)\n",
    "grid = nc.Dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc')\n",
    "viz_tools.plot_coastline(ax3, grid, coords = 'map')\n",
    "ax3.set_ylim(48, 50.7)\n",
    "#ax3.legend()\n",
    "ax3.set_xlim(-125.8, -122.4);\n",
    "ax3.axis('off')\n",
    "test=ax3.get_position()\n",
    "ax3.set_position(mpl.transforms.Bbox(points=[[.7,.2],[.97,.99]]))\n",
    "\n",
    "axb.plot(datanut.dtUTC,np.ones(np.shape(datanut.dtUTC)),'.',color='darkorange',markersize=6)\n",
    "axb.set_yticks(());\n",
    "yearsFmt = mdates.DateFormatter('%d %b %Y')\n",
    "axb.xaxis.set_major_formatter(yearsFmt)\n",
    "axb.xaxis.set_ticks([dt.datetime(int(yy),1,1), dt.datetime(int(yy),4,1),dt.datetime(int(yy),7,1),dt.datetime(int(yy),10,1),dt.datetime(int(yy)+1,1,1)])\n",
    "#axb.autofmt_xdate(bottom=0.2, rotation=15, ha='right')\n",
    "#axb.set_title('Sampling Dates')\n",
    "#plt.setp(plt.xticks()[1], rotation=10, ha='right')\n",
    "axb.set_title('Sample Dates')\n",
    "#fig.savefig('/home/eolson/pyCode/notebooks/figs/EvalDFO2016.png',dpi=200,transparent=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2017"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# 2017\n",
    "data2016=data.loc[(data.dtUTC>=dt.datetime(2016,1,1))&(data.dtUTC<dt.datetime(2017,1,1))]\n",
    "idata=data2016\n",
    "yy='2017'\n",
    "fig = plt.figure(figsize = (12,4))\n",
    "gs1 = gridspec.GridSpec(2,3,left=.08,right=.93,hspace=.8,wspace=.7,bottom=.08,top=.9,height_ratios=[5.8,.5],width_ratios=[4,4,3])\n",
    "ax1 = fig.add_subplot(gs1[0,0])\n",
    "ax2 = fig.add_subplot(gs1[0,1])\n",
    "ax3 = fig.add_subplot(gs1[0,2])\n",
    "axb = fig.add_subplot(gs1[1, :])\n",
    "\n",
    "ps=et.varvarPlot(ax1,idata,'N','mod_nitrate','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "#ax1.legend(handles=ps)\n",
    "ax1.set_xlabel('Observed')\n",
    "ax1.set_ylabel('Modelled')\n",
    "ax1.set_title(yy+' NO$_3$ ($\\mu$M)')\n",
    "ax1.set_xlim((0,45))\n",
    "ax1.set_ylim((0,45))\n",
    "ntick=np.arange(0,56,15)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax1.set_xticks(ntick)\n",
    "ax1.set_xticklabels(ntickl)\n",
    "ax1.set_yticks(ntick)\n",
    "ax1.set_yticklabels(ntickl)\n",
    "\n",
    "ps=et.varvarPlot(ax2,idata,'Si','mod_silicon','Z',(15,22),'z','m',('mediumseagreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.3)\n",
    "#ax2.legend(handles=ps,bbox_to_anchor=[.65,.4])\n",
    "ax2.set_xlabel('Observed')\n",
    "ax2.set_ylabel('Modelled')\n",
    "ax2.set_title(yy+' dSi ($\\mu$M)')\n",
    "ax2.set_xlim((0,80))\n",
    "ax2.set_ylim((0,80))\n",
    "ntick=np.arange(0,81,20)\n",
    "ntickl=[str(i) for i in ntick]\n",
    "ax2.set_xticks(ntick)\n",
    "ax2.set_xticklabels(ntickl)\n",
    "ax2.set_yticks(ntick)\n",
    "ax2.set_yticklabels(ntickl)\n",
    "\n",
    "viz_tools.set_aspect(ax3, coords = 'map')\n",
    "datanut=idata.loc[(idata.N>=0)|(idata.Si>=0)]\n",
    "ax3.plot(datanut['Lon'], datanut['Lat'], '.',color='darkorange',label='data',markersize=6)\n",
    "grid = nc.Dataset('/data/vdo/MEOPAR/NEMO-forcing/grid/bathymetry_201702.nc')\n",
    "viz_tools.plot_coastline(ax3, grid, coords = 'map')\n",
    "ax3.set_ylim(48, 50.7)\n",
    "#ax3.legend()\n",
    "ax3.set_xlim(-125.8, -122.4);\n",
    "ax3.axis('off')\n",
    "test=ax3.get_position()\n",
    "ax3.set_position(mpl.transforms.Bbox(points=[[.7,.2],[.97,.99]]))\n",
    "\n",
    "axb.plot(datanut.dtUTC,np.ones(np.shape(datanut.dtUTC)),'.',color='darkorange',markersize=6)\n",
    "axb.set_yticks(());\n",
    "yearsFmt = mdates.DateFormatter('%d %b %Y')\n",
    "axb.xaxis.set_major_formatter(yearsFmt)\n",
    "axb.xaxis.set_ticks([dt.datetime(int(yy),1,1), dt.datetime(int(yy),4,1),dt.datetime(int(yy),7,1),dt.datetime(int(yy),10,1),dt.datetime(int(yy)+1,1,1)])\n",
    "#axb.autofmt_xdate(bottom=0.2, rotation=15, ha='right')\n",
    "#axb.set_title('Sampling Dates')\n",
    "#plt.setp(plt.xticks()[1], rotation=10, ha='right')\n",
    "axb.set_title('Sample Dates')\n",
    "#fig.savefig('/home/eolson/pyCode/notebooks/figs/EvalDFO2016.png',dpi=200,transparent=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Chl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data['l10_obsChl']=np.log10(data['Chlorophyll_Extracted']+0.01)\n",
    "data['l10_modChl']=np.log10(2*(data['mod_diatoms']+data['mod_ciliates']+data['mod_flagellates'])+0.01)\n",
    "data['mod_Chl']=2*(data['mod_diatoms']+data['mod_ciliates']+data['mod_flagellates'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fig = plt.figure(figsize = (12,4.5))\n",
    "gs1 = gridspec.GridSpec(1,3,left=.1,right=.96,wspace=.5,bottom=.15,top=.85,width_ratios=[4,4,1])\n",
    "ax1 = fig.add_subplot(gs1[0])\n",
    "ax2 = fig.add_subplot(gs1[1])\n",
    "chtick=np.arange(-2,2.1,1)\n",
    "chtickl=[str(i) for i in chtick]\n",
    "\n",
    "data2015=data.loc[(data.dtUTC>=dt.datetime(2015,1,1))&(data.dtUTC<dt.datetime(2016,1,1))]\n",
    "idata=data2015\n",
    "yy='2015'\n",
    "ax1.plot(chtick,chtick,'k-')\n",
    "ps=et.varvarPlot(ax1,idata,'l10_obsChl','l10_modChl','Z',(5,10,15,20,25),'z','m',('crimson','darkorange','lime','forestgreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.5)\n",
    "#ax1.legend(handles=ps)\n",
    "ax1.set_xlabel('Observed')\n",
    "ax1.set_ylabel('Modelled')\n",
    "ax1.set_title(yy+'\\nlog10[Chl ($\\mu$g/L)+0.01]')\n",
    "ax1.set_xticks(chtick)\n",
    "ax1.set_xticklabels(chtickl)\n",
    "ax1.set_yticks(chtick)\n",
    "ax1.set_yticklabels(chtickl)\n",
    "ax1.set_xlim(-2,1.8)\n",
    "ax1.set_ylim(-2,1.8)\n",
    "\n",
    "\n",
    "data2016=data.loc[(data.dtUTC>=dt.datetime(2016,1,1))&(data.dtUTC<dt.datetime(2017,1,1))]\n",
    "idata=data2016\n",
    "yy='2016'\n",
    "ax2.plot(chtick,chtick,'k-')\n",
    "ax2.plot(np.arange(-.6,1.6,.1),np.arange(-.6,1.6,.1),'k-')\n",
    "ps=et.varvarPlot(ax2,idata,'l10_obsChl','l10_modChl','Z',(5,10,15,20,25),'z','m',('crimson','darkorange','lime','forestgreen','darkturquoise','navy'))\n",
    "for el in ps:\n",
    "    el.set_alpha(.5)\n",
    "ax2.legend(handles=ps,bbox_to_anchor=[1.08,.8])\n",
    "ax2.set_xlabel('Observed')\n",
    "ax2.set_ylabel('Modelled')\n",
    "ax2.set_title(yy+'\\nlog10[Chl ($\\mu$g/L)+0.01]')\n",
    "ax2.set_xticks(chtick)\n",
    "ax2.set_xticklabels(chtickl)\n",
    "ax2.set_yticks(chtick)\n",
    "ax2.set_yticklabels(chtickl)\n",
    "ax2.set_xlim(-2,1.8)\n",
    "ax2.set_ylim(-2,1.8)\n",
    "\n",
    "#fig.savefig('/home/eolson/pyCode/notebooks/figs/EvalDFOChl.png',dpi=200,transparent=True)"
   ]
  },
  {
   "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": []
  }
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