{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bias correction process\n",
    "\n",
    "This example shows how to call the bias-correction service based on the Kernel Density Distribution Mapping.\n",
    "We first connect to the WPS server and get some information on the service, identified by id `kddm_bc`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Bias correction method using Kernel Density Distribution Mapping (KDDM).\n"
     ]
    }
   ],
   "source": [
    "from owslib.wps import WebProcessingService\n",
    "url = 'https://pavics.ouranos.ca/twitcher/ows/proxy/flyingpigeon/wps'\n",
    "wps = WebProcessingService(url=url)\n",
    "proc = wps.describeprocess('kddm_bc')\n",
    "print(proc.abstract)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the next step, we'll create small synthetic files and run the process. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "\n",
    "obs_time_index = pd.date_range(start='2000-01-01', end='2000-12-31', freq='D')\n",
    "obs = xr.DataArray(np.arange(len(obs_time_index)), coords={'time': obs_time_index}, dims='time')\n",
    "ref = obs + 1\n",
    "\n",
    "fut_time_index = pd.date_range(start='2050-01-01', end='2050-12-31', freq='D')\n",
    "fut = xr.DataArray(np.arange(len(fut_time_index))+10, coords={'time': fut_time_index}, dims='time')\n",
    "\n",
    "fn = {'obs': '/tmp/obs.nc', \n",
    "      'ref': '/tmp/ref.nc',\n",
    "      'fut': '/tmp/fut.nc'}\n",
    "\n",
    "obs.to_netcdf(fn['obs'])\n",
    "ref.to_netcdf(fn['ref'])\n",
    "fut.to_netcdf(fn['fut'])\n",
    "\n",
    "resp = wps.execute('kddm_bc', inputs=[('obs', fn['obs']), ('ref', fn['ref']), ('fut', fn['fut'])])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ProcessAccepted\n"
     ]
    }
   ],
   "source": [
    "print(resp.status)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 0
}