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PyNGL Home PageUsing PyNGL: a document on how to use PyNGL, a Python interface for the analysis and visualization of data.
http://pyngl.ucar.edu/
Using PyNGL: a document on how to use PyNGL, a Python interface for the analysis and visualization of data.
http://pyngl.ucar.edu/
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PyNGL Home Page | pyngl.ucar.edu Reviews
https://pyngl.ucar.edu
Using PyNGL: a document on how to use PyNGL, a Python interface for the analysis and visualization of data.
pyngl.ucar.edu
PyNGL/PyNIO User Forum (pyngl-talk)
http://www.pyngl.ucar.edu/User_forum
The email list pyngl-talk@ucar.edu. Was created for PyNGL and PyNIO users to exchange information, ask questions, and report bugs. It is also for the developers to share information about new releases, features, bug fixes, and other related information. You must be subscribed. To this email list in order to post to it. All of the pyngl-talk emails and their responses are archived for your convenience:. Posting a bug report. Import Ngl print Ngl. version import Nio print Nio. version. Finally, please incl...
PyNGL: list of resources
http://www.pyngl.ucar.edu/Resources
This page provides links to detailed information on PyNGL resources. For an introductory description of PyNGL resources, see the PyNGL resources overview. Ct (coordinate array table). Ngl (PyNGL special resources). Skt (skew-T special resources). PyNGL and PyNIO are products of the Computational and Information Systems Laboratory. At the National Center for Atmospheric Research. With support from NSF.
PyNGL color table gallery
http://www.pyngl.ucar.edu/Graphics/color_table_gallery.shtml
PyNGL color table gallery. For a discussion and examples on color maps (tables) in PyNGL, see the explanation of PyNGL color maps. Large Colormaps (more than 50 colors). Small Colormaps (less than 50 colors). PyNGL and PyNIO are products of the Computational and Information Systems Laboratory. At the National Center for Atmospheric Research. With support from NSF.
PyNGL - Gallery
http://www.pyngl.ucar.edu/Examples/gallery.shtml
Below is a gallery of all images produced by PyNGL examples. Click on the smaller image for a larger one. The image title link takes you to the source example that created the image; that source has details on the example. Contouring on non-rectangular grids. Meteograms, direct overlays. Multiple plots on a page. Wind barbs/station model data. PyNGL and PyNIO are products of the Computational and Information Systems Laboratory. At the National Center for Atmospheric Research. With support from NSF.
The Nio module for reading and writing supported data formats
http://www.pyngl.ucar.edu/Nio.shtml
Is a Python package that allows read and/or write access to a variety of data formats using an interface modeled on netCDF. Is composed of a C library called libnio. Along with a Python module based on and with an interface similar to the Scientific.IO.NetCDF. Module written by Konrad Hinsen. The C library contains the same data I/O code used in NCL. A scripting language developed for analysis and visualization of geo-scientific data. Currently supported formats include:. NetCDF 4 non-classic format.
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EarthPy - Visualization
http://earthpy.org/category/visualization.html
Published: Sa 14 Februar 2015. Make matplotlib plots look nicer. We going to work with climate indeces (AO, NAO, PNA indices):. Wget http:/ www.cpc.ncep.noaa.gov/products/precip/CWlink/daily ao index/monthly.ao.index.b50.current.ascii! Wget http:/ www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/norm.nao.monthly.b5001.current.ascii! Wget http:/ www.cpc.ncep.noaa.gov/products/precip/CWlink/pna/norm.pna.monthly.b5001.current.ascii. Create pandas data frame (. And now we just import. Statistical plots ¶.
EarthPy - Nikolay Koldunov
http://earthpy.org/author/nikolay-koldunov.html
Published: Di 28 März 2023. EarthPy is a collection of IPython notebooks. With examples of Earth Science related Python code. It can be tutorials, descriptions of the modules, small scripts, or just tricks, that you think might be useful for others. Contributions are very welcome. To add your code to EarthPy, just send .ipynb file to koldunovn@gmail.com. Calculations with arrays bigger than your memory (dask arrays). Published: So 07 Juni 2015. Process numpy arrays in parallel. To do this. However I ...
Yellowstone | Computational Information Systems Laboratory
https://www2.cisl.ucar.edu/resources/yellowstone
Skip to main content. Data Analysis and Visualization. Computational Information Systems Laboratory. Access and user environment. Yellowstone User Environment Survey Results. Data transfers and sharing. Managing allocations and charges. User accounts and access. CISL User Support - Horizontal Block. Submit a help ticket. Walk-in: ML 1B Suite 55. Yellowstone is NCAR's 1.5-petaflops high-performance IBM iDataPlex cluster, which features 72,576 Intel Sandy Bridge processors and 144.6 TB of memory. Introduct...
CISL’s Data Support Section to collaborate on “Big Data” project | Computational Information Systems Laboratory
http://www2.cisl.ucar.edu/features/cisl’s-data-support-section-collaborate-“big-data”-project
Skip to main content. Data Analysis and Visualization. Computational Information Systems Laboratory. CISL’s Data Support Section to collaborate on Big Data project. The project is titled A Service to Match Satellite and. Marine Observations to Support Platform Inter-comparisons, Cross-calibration, Validation, and Quality Control. Its goal is to address the problem of matching large volumes of marine observations made by Earth-orbiting satellites to those from instruments on ocean-based observing plat...
NCL Application Examples: Models
http://ncl.ucar.edu/Applications/list_models.shtml
Ct (coordinate array table). Gsn (gsn high-level interfaces). High Resolution Map Database. Using NCL on Yellowstone. Earth System Modeling Framework. Data files for some examples. Example pages containing: tips. The following pages contain NCL scripts and graphics that you can download and use.
Advanced visualization support | Computational Information Systems Laboratory
https://www2.cisl.ucar.edu/docs/vis_support
Skip to main content. Data Analysis and Visualization. Computational Information Systems Laboratory. Managing allocations and charges. User accounts and access. Data transfers and sharing. Submit a help ticket. Walk-in: ML 1B Suite 55. And numerous other journals. To request assistance, use this Special Request Form. Indicate clearly that the request is for "Advanced Visualization Support" and describe how the proposed visualization project meets the following criteria. The deliverable(s) will help demon...
Computational & Information Systems Laboratory
http://dailyb.cisl.ucar.edu/calendar-node-field-date-of-event/day/2015-08-10
Skip to main content. Data Analysis and Visualization. Computational and Information Systems Laboratory. Monday, August 10 2015. CU-Boulder hosting Aug. 17-21 XSEDE Performance Tuning summer school. To 08/17/2015 - 16:15. Consider the impact of file size when using HPSS. 1st and 3rd Wednesday. Institute for Mathematics Applied to Geosciences. CISL High performance computing Advisory Panel.
Computational & Information Systems Laboratory
http://dailyb.cisl.ucar.edu/calendar-node-field-date-of-event/day/2015-08-14
Skip to main content. Data Analysis and Visualization. Computational and Information Systems Laboratory. Friday, August 14 2015. CU-Boulder hosting Aug. 17-21 XSEDE Performance Tuning summer school. To 08/17/2015 - 16:15. Fortran training planned for Aug. 24-27. 1st and 3rd Wednesday. Institute for Mathematics Applied to Geosciences. CISL High performance computing Advisory Panel.
Computational & Information Systems Laboratory
http://dailyb.cisl.ucar.edu/calendar-node-field-date-of-event/day/2015-08-07
Skip to main content. Data Analysis and Visualization. Computational and Information Systems Laboratory. Friday, August 7 2015. CU-Boulder hosting Aug. 17-21 XSEDE Performance Tuning summer school. To 08/17/2015 - 16:15. Seminar topics: RDA, command files, ensemble forecasting. 1st and 3rd Wednesday. Institute for Mathematics Applied to Geosciences. CISL High performance computing Advisory Panel.
Computational & Information Systems Laboratory
http://dailyb.cisl.ucar.edu/calendar-node-field-date-of-event/day/2015-08-03
Skip to main content. Data Analysis and Visualization. Computational and Information Systems Laboratory. Monday, August 3 2015. CU-Boulder hosting Aug. 17-21 XSEDE Performance Tuning summer school. To 08/17/2015 - 16:15. 1st and 3rd Wednesday. Institute for Mathematics Applied to Geosciences. CISL High performance computing Advisory Panel.
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