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MTpy: A Python toolbox for magnetotellurics
We present the software package MTpy 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...
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Published in: | Computers & geosciences 2014-11, Vol.72, p.167-175 |
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creator | Krieger, Lars Peacock, Jared R. |
description | We present the software package MTpy 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, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software.
In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy 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, MTpy 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.
In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) 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. |
doi_str_mv | 10.1016/j.cageo.2014.07.013 |
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In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy 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, MTpy 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.
In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) 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.</description><identifier>ISSN: 0098-3004</identifier><identifier>EISSN: 1873-7803</identifier><identifier>DOI: 10.1016/j.cageo.2014.07.013</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Computer programs ; Data processing ; Magnetotellurics ; Mathematical analysis ; Mathematical models ; Modules ; Open source ; Python toolbox ; Software</subject><ispartof>Computers & geosciences, 2014-11, Vol.72, p.167-175</ispartof><rights>2014 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a425t-a27b81585be8651cacd7588034283d24a236626bd5dc4331f13b11fbe9854d7c3</citedby><cites>FETCH-LOGICAL-a425t-a27b81585be8651cacd7588034283d24a236626bd5dc4331f13b11fbe9854d7c3</cites><orcidid>0000-0002-1832-8245</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Krieger, Lars</creatorcontrib><creatorcontrib>Peacock, Jared R.</creatorcontrib><title>MTpy: A Python toolbox for magnetotellurics</title><title>Computers & geosciences</title><description>We present the software package MTpy 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, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software.
In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy 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, MTpy 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.
In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) 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.</description><subject>Computer programs</subject><subject>Data processing</subject><subject>Magnetotellurics</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Modules</subject><subject>Open source</subject><subject>Python toolbox</subject><subject>Software</subject><issn>0098-3004</issn><issn>1873-7803</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNp9kMtOwzAQRS0EEqXwBWyyREIJM34kLhKLquIlFcGirC3HcYqrNC52iujf41LWrGZzz9WdQ8glQoGA5c2qMHppfUEBeQFVAciOyAhlxfJKAjsmI4CJzBkAPyVnMa4AgFIpRuT6ZbHZ3WbT7G03fPg-G7zvav-dtT5ka73s7eAH23Xb4Ew8Jyet7qK9-Ltj8v5wv5g95fPXx-fZdJ5rTsWQa1rVEoUUtZWlQKNNUwmZZnAqWUO5pqwsaVk3ojGcMWyR1YhtbSdS8KYybEyuDr2b4D-3Ng5q7aJJK3Rv_TYqTK0cmWSTFGWHqAk-xmBbtQlurcNOIai9GrVSv2rUXo2CSiU1ibo7UDZ98eVsUNE42xvbuGDNoBrv_uV_AJwva6I</recordid><startdate>201411</startdate><enddate>201411</enddate><creator>Krieger, Lars</creator><creator>Peacock, Jared R.</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-1832-8245</orcidid></search><sort><creationdate>201411</creationdate><title>MTpy: A Python toolbox for magnetotellurics</title><author>Krieger, Lars ; Peacock, Jared R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a425t-a27b81585be8651cacd7588034283d24a236626bd5dc4331f13b11fbe9854d7c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Computer programs</topic><topic>Data processing</topic><topic>Magnetotellurics</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Modules</topic><topic>Open source</topic><topic>Python toolbox</topic><topic>Software</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Krieger, Lars</creatorcontrib><creatorcontrib>Peacock, Jared R.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers & geosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Krieger, Lars</au><au>Peacock, Jared R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MTpy: A Python toolbox for magnetotellurics</atitle><jtitle>Computers & geosciences</jtitle><date>2014-11</date><risdate>2014</risdate><volume>72</volume><spage>167</spage><epage>175</epage><pages>167-175</pages><issn>0098-3004</issn><eissn>1873-7803</eissn><abstract>We present the software package MTpy 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, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software.
In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy 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, MTpy 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.
In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) 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.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.cageo.2014.07.013</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1832-8245</orcidid></addata></record> |
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subjects | Computer programs Data processing Magnetotellurics Mathematical analysis Mathematical models Modules Open source Python toolbox Software |
title | MTpy: A Python toolbox for magnetotellurics |
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