92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 11:00 AM
PyFerret: The Next Generation of Ferret
Room 346/347 (New Orleans Convention Center )
Karl Smith, JISAO/Univ. of Washington, Seattle, WA; and A. C. Manke, S. Hankin, C. Doutriaux, and D. N. Williams

PyFerret: The Next Generation of Ferret

Ferret is a widely used and recognized program for interactive access, analysis, and visualization of data. With its mathematician approach to analysis, “intelligent” on-demand access of data, simplicity in generating fully-documented graphics, and special emphasis for working with geophysical data, Ferret has been a standard program for the oceanographic community for over 20 years. Ferret has also become an integral tool in the Ferret-THREDDS Data Server (F-TDS), an OPeNDAP server that uses Ferret for server-side creation of virtual variables built from existing netCDF data. F-TDS, in turn, is used by the Live Access Server (LAS), a web server designed to provide flexible access to geo-referenced scientific data.

As Ferret has evolved over the many years, we have come to recognize the need take advantage of the wealth of other software freely available to the scientific community. We also recognize the need to make Ferret's capabilities more easily accessed by other software. To this end, we have developed the PyFerret Python package. For traditional Ferret users, this package can be used transparently as the next version of Ferret. However, Ferret users can now make use of numerous Python computational packages, such as those provided by SciPy, from within the Ferret environment. Also, Python users can now directly use Ferret's data access, analysis, and visualization capabilities. This talk will discuss these connections between Ferret and Python and the enhancements to Ferret resulting from leveraging Python software packages.

We will also discuss the progress of an effort to merge PyFerret with the Climate Data Analysis Tools (CDAT) program from PCMDI. This project seeks to bring together the strengths of both systems: the power of being able to program in Python and the highly developed climate visualization and analysis products from CDAT; with the fluid, insight-driven analysis style and ability to generate quick custom visualizations that characterize Ferret usage.

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