{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from netCDF4 import Dataset, num2date\n",
    "import numpy as np\n",
    "import datetime\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "url = 'http://opendap.deltares.nl/thredds/dodsC/opendap/rijkswaterstaat/jarkus/profiles/transect.nc'\n",
    "url = '/Users/heijer/surfdrive/Documents/work/Deltares/Projects/transect_r20171010.nc'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "with Dataset(url) as ds:\n",
    "    aidx = np.ma.masked_inside(ds.variables['id'][:], *(13001248, 13001425)).mask\n",
    "    time_topo = ds.variables['time_topo'][:,aidx]\n",
    "    time_bathy = ds.variables['time_bathy'][:,aidx]\n",
    "    time = np.array([y.year for y in num2date(ds.variables['time'][:], ds.variables['time'].units)])\n",
    "    x = np.ones(time.shape) * np.nan\n",
    "    err = np.ones((2, len(time))) * np.nan\n",
    "    for i,(tt, tb) in enumerate(zip(time_topo, time_bathy)):\n",
    "        try:\n",
    "            t1 = (num2date(tt.mean(), ds.variables['time'].units)- datetime.datetime(time[i], 1, 1)).days\n",
    "            t2 = (num2date(tb.mean(), ds.variables['time'].units)- datetime.datetime(time[i], 1, 1)).days\n",
    "            x[i] = np.array([t1, t2]).mean()\n",
    "            err[0,i] = np.abs(x[i] - t1)\n",
    "            err[1,i] = np.abs(x[i] - t2)\n",
    "        except:\n",
    "            pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1, figsize=(6,10))\n",
    "ax.errorbar(x, time, xerr=err, fmt='o')\n",
    "ax.set_xlim(-1, 366)\n",
    "ax.axvline(x[-1], color='r')\n",
    "ax.set_ylabel('year')\n",
    "ax.set_xlabel('day in year')\n",
    "fig.savefig('jarkus_dates.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[datetime.datetime(1965, 7, 1, 0, 0) datetime.datetime(1966, 7, 1, 0, 0)\n",
      " datetime.datetime(1967, 7, 1, 0, 0) datetime.datetime(1968, 7, 1, 0, 0)\n",
      " datetime.datetime(1969, 7, 1, 0, 0) datetime.datetime(1970, 7, 1, 0, 0)\n",
      " datetime.datetime(1971, 7, 1, 0, 0) datetime.datetime(1972, 7, 1, 0, 0)\n",
      " datetime.datetime(1973, 7, 1, 0, 0) datetime.datetime(1974, 7, 1, 0, 0)\n",
      " datetime.datetime(1975, 7, 1, 0, 0) datetime.datetime(1976, 7, 1, 0, 0)\n",
      " datetime.datetime(1977, 7, 1, 0, 0) datetime.datetime(1978, 7, 1, 0, 0)\n",
      " datetime.datetime(1979, 7, 1, 0, 0) datetime.datetime(1980, 7, 1, 0, 0)\n",
      " datetime.datetime(1981, 7, 1, 0, 0) datetime.datetime(1982, 7, 1, 0, 0)\n",
      " datetime.datetime(1983, 7, 1, 0, 0) datetime.datetime(1984, 7, 1, 0, 0)\n",
      " datetime.datetime(1985, 7, 1, 0, 0) datetime.datetime(1986, 7, 1, 0, 0)\n",
      " datetime.datetime(1987, 7, 1, 0, 0) datetime.datetime(1988, 7, 1, 0, 0)\n",
      " datetime.datetime(1989, 7, 1, 0, 0) datetime.datetime(1990, 7, 1, 0, 0)\n",
      " datetime.datetime(1991, 7, 1, 0, 0) datetime.datetime(1992, 7, 1, 0, 0)\n",
      " datetime.datetime(1993, 7, 1, 0, 0) datetime.datetime(1994, 7, 1, 0, 0)\n",
      " datetime.datetime(1995, 7, 1, 0, 0) datetime.datetime(1996, 7, 1, 0, 0)\n",
      " datetime.datetime(1997, 7, 1, 0, 0) datetime.datetime(1998, 7, 1, 0, 0)\n",
      " datetime.datetime(1999, 7, 1, 0, 0) datetime.datetime(2000, 7, 1, 0, 0)\n",
      " datetime.datetime(2001, 7, 1, 0, 0) datetime.datetime(2002, 7, 1, 0, 0)\n",
      " datetime.datetime(2003, 7, 1, 0, 0) datetime.datetime(2004, 7, 1, 0, 0)\n",
      " datetime.datetime(2005, 7, 1, 0, 0) datetime.datetime(2006, 7, 1, 0, 0)\n",
      " datetime.datetime(2007, 7, 1, 0, 0) datetime.datetime(2008, 7, 1, 0, 0)\n",
      " datetime.datetime(2009, 7, 1, 0, 0) datetime.datetime(2010, 7, 1, 0, 0)\n",
      " datetime.datetime(2011, 7, 1, 0, 0) datetime.datetime(2012, 7, 1, 0, 0)\n",
      " datetime.datetime(2013, 7, 1, 0, 0) datetime.datetime(2014, 7, 1, 0, 0)\n",
      " datetime.datetime(2015, 7, 1, 0, 0) datetime.datetime(2016, 7, 1, 0, 0)\n",
      " datetime.datetime(2017, 7, 1, 0, 0)]\n"
     ]
    }
   ],
   "source": [
    "with Dataset(url) as ds:\n",
    "    time = ds.variables['time']\n",
    "    print(num2date(time[:], time.units))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2016-07-01 00:00:00\n"
     ]
    }
   ],
   "source": [
    "url_df = '/Users/heijer/surfdrive/Documents/work/Deltares/Projects/DF.nc'\n",
    "with Dataset(url_df) as ds:\n",
    "    aidx = np.ma.masked_inside(ds.variables['id'][:], *(13001248, 13001425)).mask\n",
    "    print(num2date(ds.variables['time'][-1], ds.variables['time'].units))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907]),)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nonzero(aidx)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[13001248 13001268 13001288 13001308 13001322 13001335 13001355 13001375\n",
      " 13001395 13001411 13001425]\n"
     ]
    }
   ],
   "source": [
    "url_df = '/Users/heijer/surfdrive/Documents/work/Deltares/Projects/transect_r20171010_kop_van_schouwen.nc'\n",
    "with Dataset(url_df) as ds:\n",
    "    aidx = np.ma.masked_inside(ds.variables['id'][:], *(13001248, 13001425)).mask\n",
    "    print(ds.variables['id'][:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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