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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Basic test of the wflow BMI interface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import wflow.wflow_bmi as bmi\n",
    "import logging\n",
    "\n",
    "reload(bmi)\n",
    "%pylab inline \n",
    "import datetime\n",
    "from IPython.html.widgets import interact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Startup two models:\n",
    "\n",
    "+ The wflow_sbm model calculates the runoff from each cell (the LA land-atmosphere model)\n",
    "+ the wflow_routing model that uses a kinimatic wave for routing the flow (the RT routing model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# This is the LAnd Atmophere (LA) model\n",
    "LA_model = bmi.wflowbmi_csdms()\n",
    "LA_model.initialize('../../examples/wflow_rhine_sbm/wflow_sbm.ini',loglevel=logging.ERROR)\n",
    "\n",
    "# This is the routing (RT) model\n",
    "RT_model = bmi.wflowbmi_csdms()\n",
    "RT_model.initialize('../../examples/wflow_rhine_sbm/wflow_routing.ini',loglevel=logging.ERROR)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Now we can investigate some model parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(LA_model.get_value(\"timestepsecs\"))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "imshow(LA_model.get_value(\"Altitude\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "imshow(LA_model.get_value(\"Slope\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "imshow(LA_model.get_value(\"FirstZoneDepth\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a =LA_model.get_value(\"TopoId\")\n",
    "a[a==-2147483648] = 0\n",
    "imshow(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "imshow(LA_model.get_value(\"River\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Start and end times"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "t_end = RT_model.get_end_time()\n",
    "t_start = RT_model.get_start_time()\n",
    "t = RT_model.get_current_time()\n",
    "\n",
    "(t_end  - t_start)/(86400)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Now start the models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "t_end = RT_model.get_end_time()\n",
    "t = RT_model.get_start_time()\n",
    "\n",
    "res = []\n",
    "resq = []\n",
    "\n",
    "# Loop in time and put output of SBM in seperate routing module - 1way link\n",
    "while t < t_end:\n",
    "    LA_model.update()\n",
    "    # Now set the output from the LA model (specific Q) as input to the RT model\n",
    "    thevar = LA_model.get_value(\"InwaterMM\")\n",
    "    RT_model.set_value(\"IW\",thevar) # The IW is set in the wflow_routing.ini var as a forcing\n",
    "    RT_model.update()\n",
    "    resq.append(RT_model.get_value(\"SurfaceRunoff\"))\n",
    "    res.append(thevar)\n",
    "    t = RT_model.get_current_time()\n",
    "    \n",
    "    print datetime.datetime.fromtimestamp(t)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "LA_model.finalize()\n",
    "RT_model.finalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Define function to view the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def browse_res(digits):\n",
    "    n = len(digits)\n",
    "    def view_image(i):\n",
    "        plt.imshow(log(digits[i]+1))\n",
    "        plt.title('Step: %d' % i)\n",
    "        plt.colorbar()\n",
    "        plt.show()\n",
    "    interact(view_image, i=(0,n-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "browse_res(res)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    " browse_res(resq)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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