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| Titel |
MTpy - Python Tools for Magnetotelluric Data Processing and Analysis |
| VerfasserIn |
Lars Krieger, Jared Peacock, Stephan Thiel, Kent Inverarity, Alison Kirkby, Kate Robertson, Paul Soeffky, Yohannes Didana |
| Konferenz |
EGU General Assembly 2014
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250090597
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| Publikation (Nr.) |
 EGU/EGU2014-4852.pdf |
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| Zusammenfassung |
| We present the Python package MTpy, which provides functions for the processing, analysis,
and handling of magnetotelluric (MT) data sets.
MT is a relatively immature and not widely applied geophysical method in
comparison to other geophysical techniques such as seismology. As a result, the data
processing within the academic MT community is not thoroughly standardised and
is often based on a loose collection of software, adapted to the respective local
specifications. We have developed MTpy to overcome problems that arise from
missing standards, and to provide a simplification of the general handling of MT
data.
MTpy is written in Python, and the open-source code is freely available from a
GitHub repository. The setup follows the modular approach of successful geoscience
software packages such as GMT or Obspy. It contains sub-packages and modules
for the various tasks within the standard work-flow of MT data processing and
interpretation. In order to allow the inclusion of already existing and well established
software, MTpy does not only provide pure Python classes and functions, but also
wrapping command-line scripts to run standalone tools, e.g. modelling and inversion
codes.
Our aim is to provide a flexible framework, which is open for future dynamic extensions.
MTpy has the potential to promote the standardisation of processing procedures and at same
time be a versatile supplement for existing algorithms.
Here, we introduce the concept and structure of MTpy, and we illustrate the workflow of
MT data processing, interpretation, and visualisation utilising MTpy on example data sets
collected over different regions of Australia and the USA. |
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