<?xml version='1.0' encoding='utf-8'?>
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:contributor>Jared R. Peacock</dc:contributor>
  <dc:creator>Lars Krieger</dc:creator>
  <dc:date>2014</dc:date>
  <dc:description>&lt;p id="sp0030"&gt;We present the software package&amp;nbsp;&lt;i&gt;MTpy&lt;/i&gt;&amp;nbsp;that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions,&amp;nbsp;&lt;i&gt;MTpy&lt;/i&gt;&amp;nbsp;provides wrappers and convenience scripts to call standard external data processing and modelling software.&lt;/p&gt;
&lt;p id="sp0035"&gt;In its current state, modules and functions of&amp;nbsp;&lt;i&gt;MTpy&lt;/i&gt;&amp;nbsp;work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce&amp;nbsp;&lt;i&gt;MTpy&lt;/i&gt;&amp;nbsp;as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools,&amp;nbsp;&lt;i&gt;MTpy&lt;/i&gt;&amp;nbsp;is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community.&lt;/p&gt;
&lt;p id="sp0040"&gt;In this paper, we introduce the structure and concept of&amp;nbsp;&lt;i&gt;MTpy &amp;nbsp;&lt;/i&gt;. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (&lt;span id="mmlsi0001" class="mathmlsrc"&gt;&lt;span class="formulatext stixSupport mathImg" title="Click to view the MathML source" data-mathurl="/science?_ob=MathURL&amp;amp;_method=retrieve&amp;amp;_eid=1-s2.0-S0098300414001794&amp;amp;_mathId=si0001.gif&amp;amp;_user=111111111&amp;amp;_pii=S0098300414001794&amp;amp;_rdoc=1&amp;amp;_issn=00983004&amp;amp;md5=c0f8e921697c4a6bafdc8188eaee938a"&gt;&lt;span&gt;E&lt;/span&gt;&lt;/span&gt;&lt;/span&gt;-) and magnetic flux density (&lt;span class="boldFont"&gt;B&lt;/span&gt;-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.&lt;/p&gt;</dc:description>
  <dc:format>application/pdf</dc:format>
  <dc:identifier>10.1016/j.cageo.2014.07.013</dc:identifier>
  <dc:language>en</dc:language>
  <dc:publisher>Elsevier</dc:publisher>
  <dc:title>MTpy: A Python toolbox for magnetotellurics</dc:title>
  <dc:type>article</dc:type>
</oai_dc:dc>