{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import netCDF4 as nc\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import os\n",
    "import datetime as dt\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "saveloc='/ocean/aisabell/MEOPAR/extracted_files/'\n",
    "modver='201812'\n",
    "loc='S3'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# loop through years\n",
    "years=list()\n",
    "bloomtime1=list()\n",
    "for year in range(2015,2019):\n",
    "    fname=f'springTimeSeries_{str(year)}_{loc}_{modver}.pkl'\n",
    "    savepath=os.path.join(saveloc,fname)\n",
    "    bio_time,sno3,sdiat,sflag,scili,diat_alld,no3_alld,flag_alld,cili_alld,phyto_alld,intdiat,intphyto,spar,fracdiat,sphyto,percdiat,\\\n",
    "            u_wind,v_wind,twind,solar,wspeed,winddirec,riv_time,rivFlow=pickle.load(open(savepath,'rb'))\n",
    "    # put code that calculates bloom timing here\n",
    "    bt1=dt.datetime(year, 3,1)\n",
    "    years.append(year)\n",
    "    bloomtime1.append(bt1)\n",
    "years=np.array(years)\n",
    "bloomtime1=np.array(bloomtime1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2015, 2016, 2017, 2018])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[datetime.datetime(2015, 3, 1, 0, 0),\n",
       " datetime.datetime(2016, 3, 1, 0, 0),\n",
       " datetime.datetime(2017, 3, 1, 0, 0),\n",
       " datetime.datetime(2018, 3, 1, 0, 0)]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bloomtime1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "file_extension": ".py",
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