{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Infrared Sensor Data Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import warnings\n",
    "from osirisl1services.readlevel1 import open_level1_ir\n",
    "from osirisl1services.services import Level1Services\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import LogNorm\n",
    "from scipy.interpolate import interp1d\n",
    "\n",
    "FIG_SIZE = (15, 6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load the IR data for orbit 6432, scan 12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "channel = 1\n",
    "ir = open_level1_ir(orbit=6432, channel=channel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The data and added variables are returned as xarray Datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(ir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The corresponding pointing, position, tangent point, and sza info can be accessed through the 'l1' xarray accessor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(ir.l1.look_ecef)\n",
    "print(ir.l1.position_ecef)\n",
    "print(ir.l1.altitude)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the data vs pixel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "ir.data.plot(x='mjd', y='pixel', norm=LogNorm(), vmin=1e8, vmax=1e15, figsize=FIG_SIZE)\n",
    "plt.ylim(127, 20)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the data vs altitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "alts = np.arange(10000., 90000., 250.)\n",
    "ir_altitude = []\n",
    "for (data, alt) in zip(ir.data, ir.l1.altitude):\n",
    "    f = interp1d(alt, data, bounds_error=False)\n",
    "    ir_altitude.append(f(alts))\n",
    "ir_altitude = xr.DataArray(ir_altitude, coords=[ir.mjd, alts], dims=['mjd', 'altitude'])\n",
    "ir_altitude.plot(x='mjd', y='altitude', norm=LogNorm(), vmin=1e10, vmax=1e12, figsize=FIG_SIZE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot just night-time data vs altitude (be patient, calculating the sza's takes a minute)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ir_night = ir.where(ir.l1.sza > 90.)\n",
    "ir_night_altitudes = ir.l1.altitude.where(ir.l1.sza > 90.)\n",
    "\n",
    "alts = np.arange(50000., 90000., 250.)\n",
    "ir_altitude = []\n",
    "for (data, alt) in zip(ir_night.data, ir_night_altitudes):\n",
    "    f = interp1d(alt, data, bounds_error=False)\n",
    "    ir_altitude.append(f(alts))\n",
    "ir_altitude = xr.DataArray(ir_altitude, coords=[ir.mjd, alts], dims=['mjd', 'altitude'])\n",
    "ir_altitude.plot(x='mjd', y='altitude', norm=LogNorm(), vmin=1e10, vmax=1e12, figsize=FIG_SIZE)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}