{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import geoviews as gv\n",
    "import geoviews.feature as gf\n",
    "import cartopy.crs as ccrs\n",
    "\n",
    "gv.extension('matplotlib')\n",
    "\n",
    "gv.output(fig='svg', size=200)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sample_data(shape=(73, 145)):\n",
    "    \"\"\"Returns ``lons``, ``lats`` and ``data`` of some fake data.\"\"\"\n",
    "    nlats, nlons = shape\n",
    "    ys = np.linspace(-np.pi / 2, np.pi / 2, nlats)\n",
    "    xs = np.linspace(0, 2 * np.pi, nlons)\n",
    "    lons, lats = np.meshgrid(xs, ys)\n",
    "    wave = 0.75 * (np.sin(2 * lats) ** 8) * np.cos(4 * lons)\n",
    "    mean = 0.5 * np.cos(2 * lats) * ((np.sin(2 * lats)) ** 2 + 2)\n",
    "\n",
    "    lats = np.rad2deg(ys)\n",
    "    lons = np.rad2deg(xs)\n",
    "    data = wave + mean\n",
    "\n",
    "    return lons, lats, data\n",
    "\n",
    "lons, lats, data = sample_data()\n",
    "\n",
    "# Make sure we declare the central longitude\n",
    "contours = gv.FilledContours((lons, lats, data), crs=ccrs.PlateCarree(central_longitude=180))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "contours.opts(colorbar=True, levels=8, color_levels=10, cmap='nipy_spectral', projection=ccrs.Mollweide()) * gf.coastline"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "name": "python",
   "pygments_lexer": "ipython3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}