{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1575e2af",
   "metadata": {},
   "source": [
    "# Mesh2d refinement based on Gebco gridded samples with variable depth precision\n",
    "\n",
    "This is a brief introduction to the process of mesh refinement using gridded samples from Gebco global dataset. \n",
    "\n",
    "It is also an example of \n",
    "1. Generating a mesh of defined extension\n",
    "2. Saving the generated mesh to UGrid file\n",
    "3. Reading bathymetric data form a large NetDFC file\n",
    "4. Performing mesh refinement based on uniformly spaced gridded bathymetric data (fast), non-uniformly spaced bathymetric data (slow). "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7df2613e",
   "metadata": {},
   "source": [
    "Import necessary libraries, close all figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2839ee5f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import meshkernel\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.close(\"all\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b32722f0",
   "metadata": {},
   "source": [
    "# 1. Generating a mesh of defined extension"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04a588ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# general settings\n",
    "lon_min, lon_max = -1, -0.2\n",
    "lat_min, lat_max = 49.1, 49.6\n",
    "lon_res, lat_res = 0.1, 0.1\n",
    "figsize = (10, 4)\n",
    "crs = \"EPSG:4326\"\n",
    "\n",
    "\"\"\"\n",
    "Make a regular (potentially rotated) rectilinear grid. First generate a curvilinear grid than convert the curvilinear grid into unstructured grid. The steps are the following:\n",
    "- curvilinear_compute_uniform_on_extension, see the following notebook: https://github.com/Deltares/MeshKernelPy/blob/AddCurvilinearGridSupport/docs/examples/04_curvilineargrid_basics.ipynb\n",
    "- curvilinear_convert_to_mesh2d: https://github.com/Deltares/MeshKernelPy/blob/118cb4953c4e95d5b18ed283bb37f391134b2bb2/meshkernel/meshkernel.py#L1399 \n",
    "\"\"\"\n",
    "\n",
    "# Create an instance of MakeGridParameters and set the values\n",
    "make_grid_parameters = meshkernel.MakeGridParameters()\n",
    "make_grid_parameters.origin_x = lon_min\n",
    "make_grid_parameters.origin_y = lat_min\n",
    "make_grid_parameters.upper_right_x = lon_max\n",
    "make_grid_parameters.upper_right_y = lat_max\n",
    "make_grid_parameters.block_size_x = lon_res\n",
    "make_grid_parameters.block_size_y = lat_res\n",
    "\n",
    "\n",
    "mk2 = meshkernel.MeshKernel(projection=meshkernel.ProjectionType.SPHERICAL)\n",
    "mk2.curvilinear_compute_rectangular_grid_on_extension(make_grid_parameters)\n",
    "mk2.curvilinear_convert_to_mesh2d()  # convert to ugrid/mesh2d\n",
    "\n",
    "mesh2d = mk2.mesh2d_get()\n",
    "fig, ax = plt.subplots()\n",
    "mesh2d.plot_edges(ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44b5a9a3",
   "metadata": {},
   "source": [
    "# 2. Saving the generated mesh to UGrid file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ecb3baf",
   "metadata": {},
   "source": [
    "To save the generated mesh to a UGrid file, you can use the following code snippet. Please note that in order to execute the code below, the UGrid Python package needs to be installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8f7e2102",
   "metadata": {},
   "outputs": [],
   "source": [
    "ugrid_installed = False\n",
    "if ugrid_installed:\n",
    "    from ugrid import UGrid, UGridMesh2D\n",
    "\n",
    "    mesh2d_ugrid = UGrid.from_meshkernel_mesh2d_to_ugrid_mesh2d(\n",
    "        mesh2d=mesh2d, name=\"mesh2d\", is_spherical=True\n",
    "    )\n",
    "\n",
    "    attribute_dict = {\n",
    "        \"name\": \"Unknown projected\",\n",
    "        \"epsg\": np.array([4326], dtype=int),\n",
    "        \"grid_mapping_name\": \"Unknown projected\",\n",
    "        \"longitude_of_prime_meridian\": np.array([0.0], dtype=float),\n",
    "        \"semi_major_axis\": np.array([6378137.0], dtype=float),\n",
    "        \"semi_minor_axis\": np.array([6356752.314245], dtype=float),\n",
    "        \"inverse_flattening\": np.array([6356752.314245], dtype=float),\n",
    "        \"EPSG_code\": \"EPSG:4326\",\n",
    "        \"value\": \"value is equal to EPSG code\",\n",
    "    }\n",
    "\n",
    "    with UGrid(\"./gebco_mesh2d_net.nc\", \"w+\") as ug:\n",
    "        # 1. Define a new mesh2d\n",
    "        topology_id = ug.mesh2d_define(mesh2d_ugrid)\n",
    "        # 3. Put a new mesh2d\n",
    "        ug.mesh2d_put(topology_id, mesh2d_ugrid)\n",
    "        # 3. Add crs to file\n",
    "        ug.variable_int_with_attributes_define(\"wgs84\", attribute_dict)\n",
    "        # 4. Add conventions (global attributes)\n",
    "        conventions = {\n",
    "            \"institution\": \"Deltares\",\n",
    "            \"references\": \"Unknown\",\n",
    "            \"source\": \"Unknown Unknown. Model: Unknown\",\n",
    "            \"history\": \"Created on 2017-11-27T18:05:09+0100, Unknown\",\n",
    "            \"Conventions\": \"CF-1.6 UGRID-1.0/Deltares-0.8\",\n",
    "        }\n",
    "        ug.attribute_global_define(conventions)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24ae6fe1",
   "metadata": {},
   "source": [
    "# 3. Reading bathymetric data form a large NetDFC file"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99c45809",
   "metadata": {},
   "source": [
    "Bathymetric data can be read from a large dataset using the xarray package, which allows you to load only a selected portion of the data. When the longitude and latitude arrays are assumed not uniformly spaced, bilinear interpolation is slower"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f25b1525",
   "metadata": {},
   "outputs": [],
   "source": [
    "# select and plot bathy\n",
    "uniform_grid_spacing = False\n",
    "if not uniform_grid_spacing:\n",
    "    import xarray as xr\n",
    "\n",
    "    file_nc_bathy = r\"p:\\metocean-data\\open\\GEBCO\\2021\\GEBCO_2021.nc\"\n",
    "    data_bathy = xr.open_dataset(file_nc_bathy)\n",
    "    data_bathy_sel = data_bathy.sel(\n",
    "        lon=slice(lon_min - 1 / 4, lon_max + 1 / 4),\n",
    "        lat=slice(lat_min - 1 / 4, lat_max + 1 / 4),\n",
    "    )\n",
    "\n",
    "    lon_np = data_bathy_sel.lon.to_numpy().flatten().astype(\"float\")\n",
    "    lat_np = data_bathy_sel.lat.to_numpy().flatten().astype(\"float\")\n",
    "    values_np = data_bathy_sel.elevation.to_numpy().flatten().astype(\"float32\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6063f5a9",
   "metadata": {},
   "source": [
    "Otherwise, read from ascii, assuming uniform spacing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19cf9896",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_asc_file(file_path, dtype=np.float32):\n",
    "    \"\"\"Reads asc file and returns headers and data as numpy array\n",
    "    Args:\n",
    "            file_path (str): The file path\n",
    "    Returns:\n",
    "            header: The ascii header\n",
    "            data: The ascii data as a numpy array of doubles\n",
    "    \"\"\"\n",
    "\n",
    "    header = {}\n",
    "    data = []\n",
    "\n",
    "    with open(file_path, \"r\") as file:\n",
    "        # Read header information\n",
    "        for _ in range(6):\n",
    "            line = file.readline().strip().split()\n",
    "            header[line[0]] = float(line[1])\n",
    "\n",
    "        # Read data values\n",
    "        for line in file:\n",
    "            data_row = [float(value) for value in line.strip().split()]\n",
    "            data.insert(0, data_row)  # Insert row at the beginning\n",
    "\n",
    "        # Flatten the data\n",
    "        data = np.array(data).flatten().astype(dtype)\n",
    "\n",
    "    return header, data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "977b9d4d",
   "metadata": {},
   "source": [
    "# 4. Performing mesh refinement based on gridded data, depths as np.float32 or np.int16"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12487948",
   "metadata": {},
   "source": [
    "Read the depths in file as np.float32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "360b6ef8",
   "metadata": {},
   "outputs": [],
   "source": [
    "header, values_np = read_asc_file(\"./data_examples/gebco.asc\", dtype=np.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59f52827",
   "metadata": {},
   "source": [
    "Read the depths in file as np.int16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "56bd777a",
   "metadata": {},
   "outputs": [],
   "source": [
    "header, values_np = read_asc_file(\"./data_examples/gebco.asc\", dtype=np.int16)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d089097",
   "metadata": {},
   "source": [
    "Grid properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a2d80b66",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_x = int(header[\"ncols\"])\n",
    "num_y = int(header[\"nrows\"])\n",
    "x_origin = header[\"xllcenter\"]\n",
    "y_origin = header[\"yllcenter\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "856a428a",
   "metadata": {},
   "source": [
    "Gridded samples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "258e8353",
   "metadata": {},
   "outputs": [],
   "source": [
    "gridded_samples = meshkernel.GriddedSamples(\n",
    "    num_x=num_x,\n",
    "    num_y=num_y,\n",
    "    x_origin=x_origin,\n",
    "    y_origin=y_origin,\n",
    "    cell_size=0.0041666666666,\n",
    "    values=values_np,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34d296cc",
   "metadata": {},
   "source": [
    "Another option is to generate gridded samples from an array of x and y coordinates, not uniformly spaced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "de067008",
   "metadata": {},
   "outputs": [],
   "source": [
    "if not uniform_grid_spacing:\n",
    "    gridded_samples = meshkernel.GriddedSamples(\n",
    "        x_coordinates=lon_np,\n",
    "        y_coordinates=lat_np,\n",
    "        num_x=len(lon_np),\n",
    "        num_y=len(lat_np),\n",
    "        values=values_np,\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c662e624",
   "metadata": {},
   "source": [
    "Define the mesh refinement parameters "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b8c8825f",
   "metadata": {},
   "outputs": [],
   "source": [
    "mesh_refinement_parameters = meshkernel.MeshRefinementParameters(\n",
    "    refine_intersected=False,\n",
    "    use_mass_center_when_refining=False,\n",
    "    min_edge_size=500,\n",
    "    refinement_type=meshkernel.RefinementType.WAVE_COURANT,\n",
    "    connect_hanging_nodes=True,\n",
    "    account_for_samples_outside_face=False,\n",
    "    max_refinement_iterations=3,\n",
    "    smoothing_iterations=5,\n",
    "    max_courant_time=120.0,\n",
    "    directional_refinement=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b71101a",
   "metadata": {},
   "source": [
    "Perform the refinement (Bilinear interpolation will be used)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7ba9e478",
   "metadata": {},
   "outputs": [],
   "source": [
    "mk2.mesh2d_refine_based_on_gridded_samples(\n",
    "    gridded_samples=gridded_samples,\n",
    "    mesh_refinement_params=mesh_refinement_parameters,\n",
    "    use_nodal_refinement=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d798907",
   "metadata": {},
   "source": [
    "Plot the refined mesh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "63921e46",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 1600x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# zoomed in plot to focus on patchy coastlines\n",
    "fig1 = plt.figure(figsize=(16, 12))\n",
    "ax1 = fig1.add_subplot(111)\n",
    "\n",
    "mesh2d_grid2 = mk2.mesh2d_get()\n",
    "mesh2d_grid2.plot_edges(ax1, linewidth=1)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}