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Author SHA1 Message Date
Kasper D. Fischer
3be655017f updated paths to header image file 2024-06-10 12:15:28 +02:00
Kasper D. Fischer
228434397d add notebook collection from seismo-live.org on ObsPy 
activate LFS
 2024-06-10 11:47:40 +02:00
Kasper D. Fischer
dbcb4a3d8a initial import of PPSD exercise from seismo live web site 2024-06-03 12:17:07 +02:00
Kasper D. Fischer
d829006103 update README.md 2024-04-22 11:46:34 +02:00
Kasper D. Fischer
fc3b809875 Add data analysis code workspace configuration 
This commit adds a new file `dataanalaysis.code-workspace` which includes the necessary configuration for a data analysis project. The file specifies the root folder path and contains default settings.
 2024-04-22 11:35:38 +02:00
42 changed files with 36313 additions and 2 deletions
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*.png filter=lfs diff=lfs merge=lfs -text
*.mseed filter=lfs diff=lfs merge=lfs -text
*.sac filter=lfs diff=lfs merge=lfs -text

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div style='background-image: url(\"../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%\">Noise</div>\n",
" <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">Lab: Probabilistic Power Spectral Densities</div>\n",
" </div>\n",
" </div>\n",
"</div>\n",
"\n",
"\n",
"Seismo-Live: http://seismo-live.org\n",
"\n",
"##### Authors:\n",
"* Tobias Megies ([@megies](https://github.com/megies))\n",
"\n",
"---"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"plt.style.use(\"bmh\")\n",
"plt.rcParams['figure.figsize'] = 10, 6"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * read waveform data from file `data/GR.FUR..BHN.D.2015.361` (station `FUR`, [LMU geophysical observatory in Fürstenfeldbruck](https://www.geophysik.uni-muenchen.de/observatory/seismology))\n",
" * read corresponding station metadata from file `data/station_FUR.stationxml`\n",
" * print info on both waveforms and station metadata"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from obspy import read, read_inventory\n",
"\n",
"st = read(\"data/GR.FUR..BHN.D.2015.361\")\n",
"inv = read_inventory(\"data/station_FUR.stationxml\")\n",
"\n",
"print(st)\n",
"print(inv)\n",
"inv.plot(projection=\"ortho\");"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * compute probabilistic power spectral densities using `PPSD` class from obspy.signal, see http://docs.obspy.org/tutorial/code_snippets/probabilistic_power_spectral_density.html (but use the inventory you read from StationXML as metadata)\n",
" * plot the processed `PPSD` (`plot()` method attached to `PPSD` object)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from obspy.signal import PPSD\n",
"\n",
"tr = st[0]\n",
"ppsd = PPSD(stats=tr.stats, metadata=inv)\n",
"\n",
"ppsd.add(tr)\n",
"ppsd.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since longer term stacks would need too much waveform data and take way too long to compute, we prepared one year continuous data preprocessed for a single channel of station `FUR` to play with..\n",
"\n",
" * load long term pre-computed PPSD from file `PPSD_FUR_HHN.npz` using `PPSD`'s `load_npz()` staticmethod (i.e. it is called directly from the class, not an instance object of the class)\n",
" * plot the PPSD (default is full time-range, depending on how much data and spread is in the data, adjust `max_percentage` option of `plot()` option) (might take a couple of minutes..!)\n",
" * do a cumulative plot (which is good to judge non-exceedance percentage dB thresholds)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from obspy.signal import PPSD\n",
"\n",
"ppsd = PPSD.load_npz(\"data/PPSD_FUR_HHN.npz\", allow_pickle=True)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ppsd.plot(max_percentage=10)\n",
"ppsd.plot(cumulative=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * do different stacks of the data using the [`calculate_histogram()` (see docs!)](http://docs.obspy.org/packages/autogen/obspy.signal.spectral_estimation.PPSD.calculate_histogram.html) method of `PPSD` and visualize them\n",
" * compare differences in different frequency bands qualitatively (anthropogenic vs. \"natural\" noise)..\n",
" * nighttime stack, daytime stack\n",
" * advanced exercise: Use the `callback` option and use some crazy custom callback function in `calculate_histogram()`, e.g. stack together all data from birthdays in your family.. or all German holidays + Sundays in the time span.. or from dates of some bands' concerts on a tour.. etc."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ppsd.calculate_histogram(time_of_weekday=[(-1, 0, 2), (-1, 22, 24)])\n",
"ppsd.plot(max_percentage=10)\n",
"ppsd.calculate_histogram(time_of_weekday=[(-1, 8, 16)])\n",
"ppsd.plot(max_percentage=10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * do different stacks of the data using the [`calculate_histogram()` (see docs!)](http://docs.obspy.org/packages/autogen/obspy.signal.spectral_estimation.PPSD.calculate_histogram.html) method of `PPSD` and visualize them\n",
" * compare differences in different frequency bands qualitatively (anthropogenic vs. \"natural\" noise)..\n",
" * weekdays stack, weekend stack"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ppsd.calculate_histogram(time_of_weekday=[(1, 0, 24), (2, 0, 24), (3, 0, 24), (4, 0, 24), (5, 0, 24)])\n",
"ppsd.plot(max_percentage=10)\n",
"ppsd.calculate_histogram(time_of_weekday=[(6, 0, 24), (7, 0, 24)])\n",
"ppsd.plot(max_percentage=10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * do different stacks of the data using the [`calculate_histogram()` (see docs!)](http://docs.obspy.org/packages/autogen/obspy.signal.spectral_estimation.PPSD.calculate_histogram.html) method of `PPSD` and visualize them\n",
" * compare differences in different frequency bands qualitatively (anthropogenic vs. \"natural\" noise)..\n",
" * seasonal stacks (e.g. northern hemisphere autumn vs. spring/summer, ...)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ppsd.calculate_histogram(month=[10, 11, 12, 1])\n",
"ppsd.plot(max_percentage=10)\n",
"ppsd.calculate_histogram(month=[4, 5, 6, 7])\n",
"ppsd.plot(max_percentage=10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
" * do different stacks of the data using the [`calculate_histogram()` (see docs!)](http://docs.obspy.org/packages/autogen/obspy.signal.spectral_estimation.PPSD.calculate_histogram.html) method of `PPSD` and visualize them\n",
" * compare differences in different frequency bands qualitatively (anthropogenic vs. \"natural\" noise)..\n",
" * stacks by specific month\n",
" * maybe even combine several of above restrictions.. (e.g. only nighttime on weekends)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
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<?xml version='1.0' encoding='UTF-8'?>
<FDSNStationXML xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.fdsn.org/xml/station/1" schemaVersion="1.0" xsi:schemaLocation="http://www.fdsn.org/xml/station/1 http://www.fdsn.org/xml/station/fdsn-station-1.0.xsd">
<Source>Jane</Source>
<Sender>Jane</Sender>
<Module>JANE WEB SERVICE: fdsnws-station | Jane version: 0.0.0-gd6e1</Module>
<ModuleURI>http://jane/fdsnws/station/1/query?network=GR&amp;station=FUR&amp;starttime=2015-12-01&amp;endtime=2016-02-01&amp;level=response</ModuleURI>
<Created>2016-05-03T10:14:19+00:00</Created>
<Network startDate="2006-12-16T00:00:00.000000Z" code="GR">
<Description>GRSN</Description>
<SelectedNumberStations>1</SelectedNumberStations>
<TotalNumberStations>4</TotalNumberStations>
<Station startDate="2006-12-16T00:00:00.000000Z" code="FUR">
<Latitude plusError="0.0" minusError="0.0">48.162899</Latitude>
<Longitude plusError="0.0" minusError="0.0">11.2752</Longitude>
<Elevation plusError="0.0" minusError="0.0">565.0</Elevation>
<Site>
<Name>Fuerstenfeldbruck, Bavaria, GR-Net</Name>
</Site>
<CreationDate>2006-12-16T00:00:00.000</CreationDate>
<SelectedNumberChannels>12</SelectedNumberChannels>
<TotalNumberChannels>12</TotalNumberChannels>
<Channel locationCode="" code="HHN" startDate="2006-12-16T00:00:00.000">
<Latitude plusError="0.0" minusError="0.0">48.162899</Latitude>
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<Elevation plusError="0.0" minusError="0.0">565.0</Elevation>
<Depth plusError="0.0" minusError="0.0">0.0</Depth>
<Azimuth plusError="0.0" minusError="0.0">0.0</Azimuth>
<Dip plusError="0.0" minusError="0.0">0.0</Dip>
<Type>TRIGGERED</Type>
<Type>GEOPHYSICAL</Type>
<SampleRate plusError="0.0" minusError="0.0">100.0</SampleRate>
<ClockDrift plusError="0.0" minusError="0.0">0.02</ClockDrift>
<CalibrationUnits>
<Name>A</Name>
<Description>Amperes</Description>
</CalibrationUnits>
<Sensor>
<Type>Streckeisen STS-2/N seismometer</Type>
</Sensor>
<Response>
<InstrumentSensitivity>
<Value>9.4368E8</Value>
<Frequency>0.02</Frequency>
<InputUnits>
<Name>M/S</Name>
<Description>Velocity in Meters per Second</Description>
</InputUnits>
<OutputUnits>
<Name>COUNTS</Name>
<Description>Digital Counts</Description>
</OutputUnits>
</InstrumentSensitivity>
<Stage number="1">
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<Name>COUNTS</Name>
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<CfTransferFunctionType>DIGITAL</CfTransferFunctionType>
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<Decimation>
<InputSampleRate plusError="0.0" minusError="0.0">200.0</InputSampleRate>
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<Latitude plusError="0.0" minusError="0.0">48.162899</Latitude>
<Longitude plusError="0.0" minusError="0.0">11.2752</Longitude>
<Elevation plusError="0.0" minusError="0.0">565.0</Elevation>
<Depth plusError="0.0" minusError="0.0">0.0</Depth>
<Azimuth plusError="0.0" minusError="0.0">0.0</Azimuth>
<Dip plusError="0.0" minusError="0.0">0.0</Dip>
<Type>TRIGGERED</Type>
<Type>GEOPHYSICAL</Type>
<SampleRate plusError="0.0" minusError="0.0">20.0</SampleRate>
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<CalibrationUnits>
<Name>A</Name>
<Description>Amperes</Description>
</CalibrationUnits>
<Sensor>
<Type>Streckeisen STS-2/N seismometer</Type>
</Sensor>
<Response>
<InstrumentSensitivity>
<Value>9.4368E8</Value>
<Frequency>0.02</Frequency>
<InputUnits>
<Name>M/S</Name>
<Description>Velocity in Meters per Second</Description>
</InputUnits>
<OutputUnits>
<Name>COUNTS</Name>
<Description>Digital Counts</Description>
</OutputUnits>
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<InputUnits>
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<Description>Velocity in Meters per Second</Description>
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<div style='background-image: url(\"../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/Index</div>\n",
" </div>\n",
" </div>\n",
"</div>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![](images/obspy_logo_full_524x179px.png)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These notebooks are an introduction to ObsPy and will take about 2 days to fully complete. Some basic knowledge of scientific Python is assumed."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Timetable/Contents\n",
"\n",
"1. **[Introduction to File Formats and read/write in ObsPy](01_File_Formats.ipynb)** [45 Minutes] - *[[Solution]](01_File_Formats-with_solutions.ipynb)*\n",
"2. **[Handling Time](02_UTCDateTime.ipynb)** [35 Minutes] - *[[Solution]](02_UTCDateTime-with_solutions.ipynb)*\n",
"3. **[Handling Waveform Data: Stream & Trace Classes](03_waveform_data.ipynb)** [45 Minutes] - *[[Solution]](03_waveform_data-with_solutions.ipynb)*\n",
"4. **[Handling Station Metainformation](04_Station_metainformation.ipynb)** [15 Minutes] - *[[Solution]](04_Station_metainformation-with_solutions.ipynb)*\n",
"5. **[Handling Event Metainformation](05_Event_metadata.ipynb)** [25 Minutes] - *[[Solution]](05_Event_metadata-with_solutions.ipynb)*\n",
"6. **[Retrieving Data from Data Centers](06_FDSN.ipynb)** [30 Minutes] - *[[Solution]](06_FDSN-with_solutions.ipynb)*\n",
"7. **[Basic Downloading/Processing Exercise](07_Basic_Processing_Exercise.ipynb)** [60 - x Minutes] - *[[Solution]](07_Basic_Processing_Exercise-with_solutions.ipynb)*\n",
"8. **[Exercise: Event Detection and Magnitude Estimation in an Aftershock Series](08_Exercise__2008_MtCarmel_Earthquake_and_Aftershock_Series.ipynb)** [open end] - *[[Solution]](08_Exercise__2008_MtCarmel_Earthquake_and_Aftershock_Series-with_solutions.ipynb)*"
]
}
],
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{"cells":[{"cell_type":"markdown","metadata":{},"source":["<div style='background-image: url(\"../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)\">Handling Station Metadata</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":["![](images/obspy_logo_full_524x179px.png)"]},{"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":["- for station metadata, the de-facto standard of the future (replacing SEED/RESP) is [FDSN StationXML](http://www.fdsn.org/xml/station/)\n","- FDSN StationXML files can be read using **`read_inventory()`**"]},{"cell_type":"code","execution_count":null,"metadata":{},"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":{},"outputs":[],"source":["!head data/station_BFO.xml"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["print(inventory)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["network = inventory[0]\n","print(network)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["station = network[0]\n","print(station)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["channel = station[0]\n","print(channel)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["print(channel.response)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["from obspy import read\n","st = read(\"./data/waveform_PFO.mseed\")\n","print(st)"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["inv = read_inventory(\"./data/station_PFO.xml\", format=\"STATIONXML\")"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":["print(st[0].stats)"]},{"cell_type":"markdown","metadata":{},"source":["- 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":{},"outputs":[],"source":["st.plot()\n","st.remove_response(inventory=inv)\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":{},"outputs":[],"source":["st = read(\"./data/waveform_PFO.mseed\")\n","st.remove_response(inventory=inv, 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"]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"nbformat":4,"nbformat_minor":2}

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</Channel>
</Station>
</Network>
</FDSNStationXML>

467
ObsPy/data/station_PFO.xml Normal file
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@ -0,0 +1,467 @@
<?xml version="1.0" encoding="ISO-8859-1"?>
<FDSNStationXML xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.fdsn.org/xml/station/1" schemaVersion="1.0" xsi:schemaLocation="http://www.fdsn.org/xml/station/1 http://www.fdsn.org/xml/station/fdsn-station-1.0.xsd">
<Source>IRIS-DMC</Source>
<Sender>IRIS-DMC</Sender>
<Module>IRIS WEB SERVICE: fdsnws-station | version: 1.0.11</Module>
<ModuleURI>http://service.iris.edu/fdsnws/station/1/query?network=II&amp;level=response&amp;station=PFO&amp;starttime=2011-03-11T05%3A46%3A13.000000&amp;endtime=2011-03-11T05%3A46%3A33.000000&amp;channel=BHZ</ModuleURI>
<Created>2014-02-17T15:43:45</Created>
<Network code="II" startDate="1986-01-01T00:00:00" endDate="2020-12-12T23:59:59" restrictedStatus="open">
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<Elevation>1280.0</Elevation>
<Site>
<Name>Pinon Flat, California, USA</Name>
</Site>
<CreationDate>1986-10-24T00:00:00</CreationDate>
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<Comment>
<Value>S/N #119005</Value>
</Comment>
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<Elevation>1280.0</Elevation>
<Depth>5.3</Depth>
<Azimuth>0.0</Azimuth>
<Dip>-90.0</Dip>
<Type>CONTINUOUS</Type>
<Type>GEOPHYSICAL</Type>
<SampleRate>20.0</SampleRate>
<ClockDrift>2.5E-6</ClockDrift>
<CalibrationUnits>
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</CalibrationUnits>
<Sensor>
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</Sensor>
<Response>
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<Name>M/S</Name>
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</InputUnits>
<OutputUnits>
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<Description>Digital Counts</Description>
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</InstrumentSensitivity>
<Stage number="1">
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</InputUnits>
<OutputUnits>
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README.md
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# Seismological Data Analysis 2022
# Seismological Data Analysis 2024
Jupyter Notebooks for class "Seismological Data Analysis" (summer term 2022)
Jupyter Notebooks for class "Seismological Data Analysis" (summer term 2024)
## License
The content of this repository is licensed under Creative Commons Attribution 4.0 International (CC-BY 4.0) ***unless otherwise stated*** (see below)

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