{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Topography with RocketPy"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Along this jupyter notebook we will show how RocketPy interacts with\n",
    "Earth Topography. We mainly will use data provided by the NASADEM Merged DEM Global 1 arc second nc.\n",
    "\n",
    "NASADEM is a digital elevation model based on the Shuttle Radar Topography Mission (SRTM), \n",
    "a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA),\n",
    "as well as participation from the German and Italian space agencies. \n",
    "You can read more about NASADEM at: https://cmr.earthdata.nasa.gov/search/concepts/C1546314436-LPDAAC_ECS.html\n",
    "\n",
    "This is a first step forward stopping consider Earth as a constant plane\n",
    "better results when we are flying next to mountains or valleys"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialization"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First of all, we import the Environment Class, which allows to set topographic profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rocketpy import Environment"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, let's set an Environment consider a fictional launch at Switzerland.\n",
    "First we need to set the basic information about our Environment object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "env = Environment(latitude=46.90479, longitude=8.07575, datum=\"WGS84\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Obs.: Notice that the `datum` argument is used only for the converting from geodesic \n",
    "(i.e. lat/lon) to UTM coordinate system."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set topography"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we finally set our topography"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Region covered by the Topographical file: \n",
      "Latitude from 46.000000° to 47.000000°\n",
      "Longitude from 8.000000° to 9.000000°\n"
     ]
    }
   ],
   "source": [
    "env.set_topographic_profile(\n",
    "    type=\"NASADEM_HGT\",\n",
    "    file=\"../../../data/sites/switzerland/NASADEM_NC_n46e008.nc\",\n",
    "    dictionary=\"netCDF4\",\n",
    "    crs=None,\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find the launch site elevation"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once we defined the topographic profile, we can find the launch site elevation\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "elevation = env.get_elevation_from_topographic_profile(env.latitude, env.longitude)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally set the elevation to the Environment object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "env.set_elevation(elevation)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize information"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can see the elevation that we've set, as well as other important attributes \n",
    "of our Environment object. We do that by running the `.info()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Gravity Details\n",
      "\n",
      "Acceleration of Gravity at Lauch Site: 9.803093916992397 m/s²\n",
      "\n",
      "\n",
      "Launch Site Details\n",
      "\n",
      "Launch Site Latitude: 46.90479°\n",
      "Launch Site Longitude: 8.07575°\n",
      "Reference Datum: WGS84\n",
      "Launch Site UTM coordinates: 886538.30 E    5207102.17 N\n",
      "Launch Site UTM zone: 31T\n",
      "Launch Site Surface Elevation: 1565.0 m\n",
      "\n",
      "\n",
      "Atmospheric Model Details\n",
      "\n",
      "Atmospheric Model Type: standard_atmosphere\n",
      "standard_atmosphere Maximum Height: 80.000 km\n",
      "\n",
      "\n",
      "Surface Atmospheric Conditions\n",
      "\n",
      "Surface Wind Speed: 0.00 m/s\n",
      "Surface Wind Direction: 0.00°\n",
      "Surface Wind Heading: 0.00°\n",
      "Surface Pressure: 838.88 hPa\n",
      "Surface Temperature: 278.00 K\n",
      "Surface Air Density: 1.051 kg/m³\n",
      "Surface Speed of Sound: 333.87 m/s\n",
      "\n",
      "\n",
      "Atmospheric Model Plots\n",
      "\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 648x324 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "env.info()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate Earth Radius at latitude"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to, we can calculate the Earth radius based on the launch site\n",
    "latitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Earth radius at latitude 46.904790°:  6366.78 km\n"
     ]
    }
   ],
   "source": [
    "e_radius = env.calculate_earth_radius(env.latitude)\n",
    "\n",
    "print(\n",
    "    \"The Earth radius at latitude {:.6f}°:  {:.2f} km\".format(\n",
    "        env.latitude, e_radius / 1000\n",
    "    )\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.10.5"
  },
  "vscode": {
   "interpreter": {
    "hash": "e5b7a8cae4f67c92cb11d9e20ddffc69e636d67ed689401b5441ad3ba95f0999"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}