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{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["<div style='background-image: url(\"../share/images/header.svg\") ; padding: 0px ; background-size: cover ; border-radius: 5px ; height: 250px'>\n", " <div style=\"float: right ; margin: 50px ; padding: 20px ; background: rgba(255 , 255 , 255 , 0.7) ; width: 50% ; height: 150px\">\n", " <div style=\"position: relative ; top: 50% ; transform: translatey(-50%)\">\n", " <div style=\"font-size: xx-large ; font-weight: 900 ; color: rgba(0 , 0 , 0 , 0.8) ; line-height: 100%\">ObsPy Tutorial</div>\n", " <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Introduction to File Formats and read/write in ObsPy</div>\n", " </div>\n", " </div>\n", "</div>"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Seismo-Live: http://seismo-live.org\n", "\n", "##### Authors:\n", "* Lion Krischer ([@krischer](https://github.com/krischer))\n", "* Tobias Megies ([@megies](https://github.com/megies))\n", "---"]}, {"cell_type": "markdown", "metadata": {}, "source": [""]}, {"cell_type": "markdown", "metadata": {}, "source": ["This is oftentimes not taught, but fairly important to understand, at least at a basic level. This also teaches you how to work with these in ObsPy."]}, {"cell_type": "markdown", "metadata": {}, "source": ["**This notebook aims to give a quick introductions to ObsPy's core functions and classes. Everything here will be repeated in more detail in later notebooks.**"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["%matplotlib inline\n", "import matplotlib.pyplot as plt\n", "plt.style.use('ggplot')\n", "plt.rcParams['figure.figsize'] = 12, 8"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## SEED Identifiers\n", "\n", "According to the [SEED standard](www.fdsn.org/seed_manual/SEEDManual_V2.4.pdf), which is fairly well adopted, the following nomenclature is used to identify seismic receivers:\n", "\n", "* **Network code**: Identifies the network/owner of the data. Assigned by the FDSN and thus unique.\n", "* **Station code**: The station within a network. *NOT UNIQUE IN PRACTICE!* Always use together with a network code!\n", "* **Location ID**: Identifies different data streams within one station. Commonly used to logically separate multiple instruments at a single station.\n", "* **Channel codes**: Three character code: 1) Band and approximate sampling rate, 2) The type of instrument, 3) The orientation\n", "\n", "This results in full ids of the form **NET.STA.LOC.CHAN**, e.g. **IV.PRMA..HHE**.\n", "\n", "\n", "---\n", "\n", "\n", "In seismology we generally distinguish between three separate types of data:\n", "\n", "1. **Waveform Data** - The actual waveforms as time series.\n", "2. **Station Data** - Information about the stations' operators, geographical locations, and the instrument's responses.\n", "3. **Event Data** - Information about earthquakes.\n", "\n", "Some formats have elements of two or more of these."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Waveform Data\n", "\n", "\n", "\n", "There are a myriad of waveform data formats but in Europe and the USA two formats dominate: **MiniSEED** and **SAC**\n", "\n", "\n", "### MiniSEED\n", "\n", "* This is what you get from datacenters and also what they store, thus the original data\n", "* Can store integers and single/double precision floats\n", "* Integer data (e.g. counts from a digitizer) are heavily compressed: a factor of 3-5 depending on the data\n", "* Can deal with gaps and overlaps\n", "* Multiple components per file\n", "* Contains only the really necessary parameters and some information for the data providers"]}, {"cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": ["import obspy\n", "\n", "# ObsPy automatically detects the file format.\n", "st = obspy.read(\"data/example.mseed\")\n", "print(st)\n", "\n", "# Fileformat specific informatio
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