examples/03_init_single_element_model.ipynb

{
 "cells": [
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Copyright 2020 Marco Dal Molin et al.\n",
    "\n",
    "This file is part of SuperflexPy.\n",
    "\n",
    "SuperflexPy is free software: you can redistribute it and/or modify\n",
    "it under the terms of the GNU Lesser General Public License as published by\n",
    "the Free Software Foundation, either version 3 of the License, or\n",
    "(at your option) any later version.\n",
    "\n",
    "SuperflexPy is distributed in the hope that it will be useful,\n",
    "but WITHOUT ANY WARRANTY; without even the implied warranty of\n",
    "MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n",
    "GNU Lesser General Public License for more details.\n",
    "\n",
    "You should have received a copy of the GNU Lesser General Public License\n",
    "along with SuperflexPy. If not, see <https://www.gnu.org/licenses/>.\n",
    "\n",
    "This file is part of the SuperflexPy modelling framework. For details about it,\n",
    "visit the page https://superflexpy.readthedocs.io\n",
    "\n",
    "CODED BY: Marco Dal Molin\n",
    "DESIGNED BY: Marco Dal Molin, Fabrizio Fenicia, Dmitri Kavetski"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# SuperflexPy example 03: Initialize a single element model\n",
    "\n",
    "Author: Marco Dal Molin\n",
    "\n",
    "Collaborators: Fabrizio Fenicia, Dmitri Kavetski"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What's in this example\n",
    "\n",
    "This example will cover the following aspects:\n",
    "- [Initialize a single element model](https://superflexpy.readthedocs.io/en/latest/demo.html#single-element-configuration)\n",
    "\n",
    "By clicking on the items you will be redirected to the documentation page (when available) that explains the arguments in a more detailed way. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## What's not in this example\n",
    "\n",
    "The following aspects are already covered in other examples:\n",
    "\n",
    "- [Run the model](./01_run_simple_model.ipynb)\n",
    "- [Change states and parameters](./01_run_simple_model.ipynb)\n",
    "\n",
    "For this reason we will put only the code need, without further explanations. You can check the other examples by clicking on the items above."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Do you want to use this example as a script?\n",
    "\n",
    "Examples of SuperflexPy are created and distributed using Jupyter notebooks because they enable to conjugate runnable code with text explanations. We have decided to not provide the content of the notebooks as script because this would mean duplicating the same content in multiple places, bringing to maintainability problems.\n",
    "\n",
    "If the user wants to download the content of this notebook as a python script, it is possible following the steps:\n",
    "1. If not already done, open this notebook using [Binder](https://mybinder.org/v2/gh/dalmo1991/superflexPy/master?filepath=examples%2F03_init_single_element_model.ipynb)\n",
    "2. Go on File -> Download as -> Python (.py)\n",
    "3. Select the saving path\n",
    "\n",
    "The result is a Python script that contains all the markdown text as comment and the code contained inside the cells."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP 1: Initialize the single element model\n",
    "\n",
    "A single element model is composed by just one element. Its initialization requires the definition of:\n",
    "\n",
    "- parameters (if present)\n",
    "- states (if present)\n",
    "- numerical approximator (if present)\n",
    "- identifier\n",
    "\n",
    "For this example we will use the `PowerReservoir` implemented as part of the `hbv` model."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 01. Import an initialize the numerical routines\n",
    "\n",
    "The differential equations of the reservoir require a numerical approximator and a root finder. Before initializing the reservoir, these need to be imported and initialized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from superflexpy.implementation.root_finders.pegasus import PegasusPython\n",
    "from superflexpy.implementation.numerical_approximators.implicit_euler import ImplicitEulerPython\n",
    "\n",
    "root_finder = PegasusPython()\n",
    "numeric_approximator = ImplicitEulerPython(root_finder=root_finder)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 02. Initialize the reservoir\n",
    "\n",
    "Now the reservoir can be imported and initialized. The names of parameters and states are specified in the documentation of the class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from superflexpy.implementation.elements.hbv import PowerReservoir\n",
    "\n",
    "pr = PowerReservoir(\n",
    "    parameters={'k': 0.1, 'alpha': 1.0},\n",
    "    states={'S0': 10.0},\n",
    "    approximation=numeric_approximator,\n",
    "    id='PR'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## STEP 2: Run the model\n",
    "\n",
    "Now that the reservoir has been initialized, it can be run. This can be done running the code in the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x864 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams.update({'font.size': 20})\n",
    "\n",
    "# Fix the seed\n",
    "SEED = 2\n",
    "rng = np.random.RandomState(seed=SEED)\n",
    "\n",
    "# Generate the input\n",
    "P = np.zeros(100)\n",
    "P[:10] = rng.randint(10, size=10)\n",
    "P[25:30] = rng.randint(20, size=5)\n",
    "P[40:60] = rng.randint(5, size=20)\n",
    "P[80:83] = rng.randint(30, 50, size=3)\n",
    "\n",
    "# Assign the input\n",
    "pr.set_input([P])\n",
    "\n",
    "# Set the timestep\n",
    "pr.set_timestep(1.0)\n",
    "\n",
    "# Run the model\n",
    "output = pr.get_output()\n",
    "\n",
    "# Plot\n",
    "fig, ax = plt.subplots(2, 1, figsize=(20, 12), sharex=True)\n",
    "ax[0].bar(x=np.arange(len(P)), height=P, color='royalblue')\n",
    "ax[0].set_ylabel('Precipitation [mm/day]')\n",
    "ax[0].grid(True)\n",
    "ax[1].plot(np.arange(len(P)), output[0], lw=2, label='Total outflow')\n",
    "ax[1].set_xlabel('Time [days]')\n",
    "ax[1].set_ylabel('Streamflow [mm/day]')\n",
    "ax[1].legend()\n",
    "ax[1].grid(True)\n",
    "pass"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "just_sfpy_RC",
   "language": "python",
   "name": "just_sfpy_rc"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}