{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# A comprehensive example\n",
    "This jupyter notebook is a complete example of how to use Watlab. It will guide you through the different steps of a classic Watlab usage: the mesh creation with GMSH, the model description with one of the modules of Watlab, and the visualisation with the visualisation tools of Watlab.\n",
    "\n",
    "Now make sure you have installed Watlab correctly, and dig in with us!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## All you need is GMSH!\n",
    "GMSH is a mesh generator. It comes with a GUI, but also with a nice Python-API.\n",
    "The very first step is to import GMSH and initialise the process. Then, we'll be able to construct the mesh point by point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import the module\n",
    "import gmsh\n",
    "import sys\n",
    "\n",
    "# Initialise gmsh and create a model\n",
    "gmsh.initialize()\n",
    "gmsh.model.add(\"damBreak\")"
   ]
  },
  {
   "attachments": {
    "mesh.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up the geometry of the domain\n",
    "\n",
    "The domain of this first example will look like the picture displayed here under: a rectangle with two separated zones. The left one will be filled with water and called \"Filled area\", and the right one will be empty and called \"Empty area\".\n",
    "\n",
    "![../pics/tuto1_mesh.png](attachment:mesh.png)\n",
    "\n",
    "The domain is made of several physical objects that must be created sequentially. They are part of the **geometry** of the model.\n",
    "\n",
    "#### 1. Six points correspond to the nodes of the domain (one at each corner, two in the middle to create the separation line).\n",
    "\n",
    "The points are just coordinates. To each point, one must specify a mesh-size characteristic. Optionnally, one can give it a number (otherwise, it is set automatically). We recommend to attribute the number manually to control it easily."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#characteristic size of cells\n",
    "lc = 0.01\n",
    "\n",
    "# create points \n",
    "gmsh.model.geo.addPoint(0, 0, 0, lc, 1)\n",
    "gmsh.model.geo.addPoint(0.5, 0, 0, lc, 2)\n",
    "gmsh.model.geo.addPoint(1, 0, 0, lc, 3)\n",
    "gmsh.model.geo.addPoint(0, 0.4, 0, lc, 4)\n",
    "gmsh.model.geo.addPoint(0.5, 0.4, 0, lc, 5)\n",
    "gmsh.model.geo.addPoint(1,0.4, 0, lc, 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Seven edges join thoses points: six for the contour, one for the separation\n",
    "The edges join two points to each other. They also receive each an identifier number. The syntax is extremely simple: `addLine(point_i, point_j, line_identifier)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gmsh.model.geo.addLine(1, 2, 1)\n",
    "gmsh.model.geo.addLine(2, 3, 2)\n",
    "gmsh.model.geo.addLine(1, 4, 3)\n",
    "gmsh.model.geo.addLine(2, 5, 4)\n",
    "gmsh.model.geo.addLine(3, 6, 5)\n",
    "gmsh.model.geo.addLine(4, 5, 6)\n",
    "gmsh.model.geo.addLine(5, 6, 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3. Two curve loops delimit the zones\n",
    "The curves are concatenation of lines. The orientation is very important here, as the line is defined as coming **from** `point_i` and going **to** `point_j`. Each curve receives an identifier.\n",
    "\n",
    "The syntax, again, is simple: `addCurveLoop(list_of_lines_identifiers, indentifier)`.\n",
    "\n",
    "Warning: every curve loop **must** be created in counter-clockwise direction. Otherwise, the cells will not be properly oriented."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gmsh.model.geo.addCurveLoop([1, 4, -6, -3], 1)\n",
    "gmsh.model.geo.addCurveLoop([2, 5, -7, -4], 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 4. Two plane surface represent the zones\n",
    "Finally, the plane surfaces are build on (one or more) curves, with the syntax `addPlaneSurface(list_of_curveLoops_identifiers, identifier)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gmsh.model.geo.addPlaneSurface([1], 1)\n",
    "gmsh.model.geo.addPlaneSurface([2], 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up the model\n",
    "Now, that the **geometry** is set up, one can build the **model** on it, and give names to objects that we will manipulate later with Watlab. Those objects are named \"Physical Groups\" and represent the boundaries, or the areas. The basic syntax is: `addPhysicalGroup(dimension, list_of_suited_identifiers, name=\"a nice name\")`\n",
    "\n",
    "The groups may be of two types:\n",
    "1. Boundaries are Physical Groups of dimension one, and build on line identifiers. They are created as `addPhysicalGroup(1, list_of_lines_identifiers, name=\"a nice boundary name\")`\n",
    "2. Areas are Physical Groups of dimension two, and build on plane surfaces identifiers. They are created as `addPhysicalGroup(2, list_of_plane_surfaces_identifiers, name=\"a nice zone name\")`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# first synchronize the information with gmsh.model !\n",
    "gmsh.model.geo.synchronize()\n",
    "\n",
    "# Dimension 1 groups (boundaries) build on lines identifiers.\n",
    "gmsh.model.addPhysicalGroup(1, [1,2],name=\"Boundaries down\")\n",
    "gmsh.model.addPhysicalGroup(1, [5],name=\"Boundaries right\")\n",
    "gmsh.model.addPhysicalGroup(1, [6,7],name=\"Boundaries up\") \n",
    "gmsh.model.addPhysicalGroup(1, [3],name=\"Boundaries left\")\n",
    "\n",
    "gmsh.model.addPhysicalGroup(1, [4],name=\"Center line\")\n",
    "\n",
    "# Dimension 2 groups (areas) build on plane surfaces identifiers.\n",
    "gmsh.model.addPhysicalGroup(2, [1],name=\"Filled area\")\n",
    "gmsh.model.addPhysicalGroup(2, [2],name=\"Empty area\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let the magic play!\n",
    "Now you can generate the mesh and save it with the following commands."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We generate and optimize the mesh\n",
    "gmsh.model.mesh.generate(2)\n",
    "gmsh.model.mesh.optimize('Laplace2D')\n",
    "\n",
    "# Here we save the mesh as a .msh file\n",
    "gmsh.write(\"damBreakMesh.msh\")\n",
    "if '-nopopup' not in sys.argv:\n",
    "    gmsh.fltk.run()\n",
    "\n",
    "# And we finalize gmsh.\n",
    "gmsh.finalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Watlab helps you master the model\n",
    "Now that the geometry of your domain is done, you can focus on solving your hydraulic problem. For this, you need a solver (hopefully, Watlab provides you one!). You also need to tell Watlab what mesh represents the domain, and what conditions are set to the cells and the boundaries.\n",
    "\n",
    "First, import Watlab, import the mesh, and create a Watlab model!\n",
    "\n",
    "The example here is hydrodynamics, so the solver is hydroflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import watlab\n",
    "\n",
    "# The mesh is created from the .msh file saved above\n",
    "mesh = watlab.Mesh(\"damBreakMesh.msh\")\n",
    "\n",
    "# Impose a meshchecking if needed (defaul = False)\n",
    "mesh.meshchecking = True\n",
    "\n",
    "# The model builds on that mesh\n",
    "model = watlab.HydroflowModel(mesh)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model can be give several properties (see the documentation for a complete set of properties)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Your model requires some general parameters such as the simulation time.\n",
    "model.name = \"Simple Dam Break\"\n",
    "model.ending_time = 5 \n",
    "model.Cfl_number = 0.95"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But the most interresting functions concern the initial conditions and boundary conditions (check also the doc for a comprehensive list). The conditions are associated with an area from the mesh or a boundary. Just call them by their nice name, and Watlab will find them :-). The syntax is usually: `set_certain_condition(list_of_areas_names, list_of_values)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We specify the friction coefficient to both zones to 0.01\n",
    "model.set_friction_coefficient(\"Filled area\",0.01)\n",
    "model.set_friction_coefficient(\"Empty area\",0.01)\n",
    "\n",
    "# But the initial water height must be different in the filled area than in the empty one.\n",
    "model.set_initial_water_height(\"Filled area\", 0.15)\n",
    "model.set_initial_water_height(\"Empty area\", 0.015)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, all boundaries are walls, except the center line between the filled and empty areas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.set_wall_boundaries([\"Boundaries down\",\"Boundaries up\",\"Boundaries left\",\"Boundaries right\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can specify output parameters and generate the data files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here we choose how many \"pictures\" of the flow we want\n",
    "model.set_picture_times(n_pic = 51)\n",
    "\n",
    "# And here we set the names of the io folders (by default, they are named... input and output. How imaginative!)\n",
    "model.export.input_folder_name = \"InputExample01\"\n",
    "model.export.output_folder_name = \"OutputExample01\"\n",
    "\n",
    "# Finally, we generate the datafiles needed by the solver.\n",
    "model.export_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data files are stored in the input folder. They are super important for the solver: without them, no simulation will be run.\n",
    "Speaking of running a simulation, you just need to run the model (the solver can sometimes be parallelized)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "meshchecker.exe exists\n",
      "Launching the meshchecker executable ...\n",
      "hydroflow.exe exists\n",
      "Launching the executable ...\n",
      "Boundary condition of type 4234 not defined!"
     ]
    }
   ],
   "source": [
    "model.solve(isParallel=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualise the outputs thanks to Watlab\n",
    "Nothing seems to happen? It's normal. Output files have been outputed in the dedicated folder. Watlab comes with basic visualisation functions to saves you from writing your own plotters.\n",
    "\n",
    "You need to first create a plotter, then just reference the files of the picture you want to print."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create a plotter based on the watlab's mesh\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plotter = watlab.Plotter(mesh)\n",
    "\n",
    "# And plot\n",
    "myPic = \"OutputExample01\\\\pic_0_60.txt\"\n",
    "plotter.plot(myPic,'h')\n",
    "plt.title(\"Results for time : 0.6 [s]\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.6 ('signal')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.7"
  },
  "vscode": {
   "interpreter": {
    "hash": "c4832a0222a2f8fcb65f55b27509e315d14874a0e8cdc3391325014f12302299"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}