YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Bulletin of the American Meteorological Society
    • View Item
    •   YE&T Library
    • AMS
    • Bulletin of the American Meteorological Society
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    MetPy: A Meteorological Python Library for Data Analysis and Visualization

    Source: Bulletin of the American Meteorological Society:;2022:;volume( 103 ):;issue: 010::page E2273
    Author:
    Ryan M. May
    ,
    Kevin H. Goebbert
    ,
    Jonathan E. Thielen
    ,
    John R. Leeman
    ,
    M. Drew Camron
    ,
    Zachary Bruick
    ,
    Eric C. Bruning
    ,
    Russell P. Manser
    ,
    Sean C. Arms
    ,
    Patrick T. Marsh
    DOI: 10.1175/BAMS-D-21-0125.1
    Publisher: American Meteorological Society
    Abstract: MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew
    • Download: (3.177Mb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      MetPy: A Meteorological Python Library for Data Analysis and Visualization

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4290319
    Collections
    • Bulletin of the American Meteorological Society

    Show full item record

    contributor authorRyan M. May
    contributor authorKevin H. Goebbert
    contributor authorJonathan E. Thielen
    contributor authorJohn R. Leeman
    contributor authorM. Drew Camron
    contributor authorZachary Bruick
    contributor authorEric C. Bruning
    contributor authorRussell P. Manser
    contributor authorSean C. Arms
    contributor authorPatrick T. Marsh
    date accessioned2023-04-12T18:50:01Z
    date available2023-04-12T18:50:01Z
    date copyright2022/10/26
    date issued2022
    identifier otherBAMS-D-21-0125.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290319
    description abstractMetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skew
    publisherAmerican Meteorological Society
    titleMetPy: A Meteorological Python Library for Data Analysis and Visualization
    typeJournal Paper
    journal volume103
    journal issue10
    journal titleBulletin of the American Meteorological Society
    identifier doi10.1175/BAMS-D-21-0125.1
    journal fristpageE2273
    journal lastpageE2284
    pageE2273–E2284
    treeBulletin of the American Meteorological Society:;2022:;volume( 103 ):;issue: 010
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian