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   "metadata": {},
   "source": [
    "<div style=\"background-image:url(images/meschede-seismic-waves.png); padding: 10px 30px 20px 30px; background-size:cover; background-opacity:50%; border-radius:5px\">\n",
    "<p style=\"float:right; margin-top:20px; padding: 20px 20px 0px 20px; background:rgba(255,255,255,0.6); border-radius:10px;\">\n",
    "<img width=\"400px\" src=images/obspy_logo_full_524x179px.png?raw=true>\n",
    "</p>\n",
    "\n",
    "<h1 style=\"color:#999\">ObsPy Workshop</h1>\n",
    "<h5 style=\"color:#FFF\">Münster, July 7th & 8th</h5>\n",
    "\n",
    "<h3 style=\"color:#EEE\">Data Acquisition and Processing with ObsPy</h3>\n",
    "\n",
    "<h2 style=\"color:#FFF\">Handling Station Metadata</h2>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from __future__ import print_function\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "plt.rcParams['figure.figsize'] = 12, 8"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- for station metadata, the de-facto standard of the future (replacing SEED/RESP) is [FDSN StationXML](https://www.fdsn.org/xml/station/)\n",
    "- FDSN StationXML files can be read using **`read_inventory()`**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from obspy import read_inventory\n",
    "# real-world StationXML files often deviate from the official schema definition\n",
    "# therefore file-format autodiscovery sometimes fails and we have to force the file format\n",
    "inventory = read_inventory(\"./data/station_PFO.xml\", format=\"STATIONXML\")\n",
    "print(type(inventory))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- the nested ObsPy Inventory class structure (Inventory/Station/Channel/Response/...) is closely modelled after FDSN StationXML\n",
    "<img src=\"images/Inventory.svg\" width=90%>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "!head data/station_BFO.xml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(inventory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "network = inventory[0]\n",
    "print(network)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "station = network[0]\n",
    "print(station)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "channel = station[0]\n",
    "print(channel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(channel.response)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- for metadata read from StationXML the response information can be attached to the waveform data using the convenience method **`Stream.attach_response()`**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from obspy import read\n",
    "st = read(\"./data/waveform_PFO.mseed\")\n",
    "print(st)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "inv = read_inventory(\"./data/station_PFO.xml\", format=\"STATIONXML\")\n",
    "st.attach_response(inv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "print(st[0].stats)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- once attached to the waveform data, the instrument response can be deconvolved from the waveform data using the convenience method **`Stream.remove_response()`**\n",
    "- evalresp is used internally to calculate the instrument response"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "st.plot()\n",
    "st.remove_response()\n",
    "st.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- several options can be used to specify details of the deconvolution (water level, frequency domain prefiltering), output units (velocity/displacement/acceleration), demeaning, tapering and to specify if any response stages should be omitted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "st = read(\"./data/waveform_PFO.mseed\")\n",
    "st.attach_response(inv)\n",
    "st.remove_response(water_level=60, pre_filt=(0.01, 0.02, 8, 10), output=\"DISP\")\n",
    "st.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- station metadata not present in StationXML yet but in Dataless SEED or RESP files can be used for instrument correction using the `.simulate()` method of Stream/Trace in a similar fashion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Acknowledgements\n",
    "\n",
    "Background picture at the very top is from Matthias Meschede."
   ]
  }
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