{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "04e0612f-4319-4261-ad7e-61fd03e8dc67",
   "metadata": {},
   "source": [
    "# Plot track density"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ab3d052-d18b-4452-8582-638cd69860b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import huracanpy\n",
    "\n",
    "import cartopy.crs as ccrs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "261ee449-f5e8-442b-994c-73d608829204",
   "metadata": {},
   "source": [
    "## Basic routine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5c041bf-cf40-44d6-97ba-6cce60e42e9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load data (example : ibtracs)\n",
    "tracks = huracanpy.load(source=\"ibtracs\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "026ef63e-9ece-4d2b-99f9-1c578c94cf7f",
   "metadata": {},
   "source": [
    "To plot the track density, you need two functions. The first one, `huracanpy.diags.track_density.simple_global_histogram` computes the track density, which is stored in a 2D xarray. The second one `huracanpy.plot.density.plot_density` will plot the track density. Because the track density is a xarray object, you can also use built-in xarray functions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3edeabba-475a-4b9b-a937-bd196cb2b40a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compute track density\n",
    "D = huracanpy.calc.density(tracks.lon, tracks.lat)\n",
    "D  # D, the track density, is a map stored in xarray"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c65a7fe-8672-4903-bbbc-b39aafb45243",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting using huracanpy function\n",
    "huracanpy.plot.density(D)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e11e8de-5bb0-4997-9743-fcc3fe40a372",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plotting using xarray's plot function\n",
    "D.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7d322fe-9d22-4147-a403-26373e2e7336",
   "metadata": {},
   "source": [
    "## Customization"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3c035e4-69b2-40cc-a03a-8a25ea12c082",
   "metadata": {},
   "source": [
    "### Density computation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d565d25-8c48-4321-a36b-fea62ece433b",
   "metadata": {},
   "source": [
    "For the track density computation, there are two things that can be customized : \n",
    "* `bin_size` : The size of the boxes over which the track density is computed, in degrees.\n",
    "* `N_seasons` is a normalization factor. It is useful to make the number make sense, such as \"number of TC point per year in a `bin_size x bin_size` box\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1271d02c-59b9-414e-b229-8844408ecce0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting a smaller bin_size\n",
    "D = huracanpy.calc.density(tracks.lon, tracks.lat, bin_size=1)\n",
    "D.plot()\n",
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abb6c39b-100a-4f95-be9b-868c56564df5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting a larger bin_size\n",
    "D = huracanpy.calc.density(tracks.lon, tracks.lat, bin_size=10)\n",
    "D.plot()\n",
    "D"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50aec700-e567-4c9e-9fbd-c967a7244222",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Normalizing\n",
    "## Computing the number of season in the dataset\n",
    "import numpy as np\n",
    "\n",
    "N = len(np.unique(tracks.season.values))\n",
    "print(N)\n",
    "## Track density with normalization.\n",
    "D = huracanpy.calc.density(tracks.lon, tracks.lat, n_seasons=N)\n",
    "# In this case, now the number in D in number of TC points in each 5x5 box.\n",
    "D.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a200209-83ec-45a7-864e-8da1444cacfa",
   "metadata": {},
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "64adaac9-dc53-4d56-8791-37a6cc9fcc4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# With huracanpy's function\n",
    "## The function is based on matplotlib's contourf, so you can use its options\n",
    "huracanpy.plot.density(D, contourf_kws=dict(cmap=\"tab20c_r\", levels=20))\n",
    "## Changing the projection with subplot_kws\n",
    "huracanpy.plot.density(D, subplot_kws=dict(projection=ccrs.Mollweide(180)))\n",
    "## Changing the figure's properties\n",
    "huracanpy.plot.density(D, fig_kws=dict(figsize=(15, 5)))"
   ]
  }
 ],
 "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}