R Class for Wildfire Scientists

Mazama Science has just finished creating class materials on using R for the AirFire team at the USFS Pacific Wildland Fire Sciences Lab in Seattle, Washington. This team of scientists works on monitoring and modeling wildfire emissions, smoke and air quality. The AirFire team has granted permission to release these class materials to the public in the interest of encouraging scientists in other agencies to experiment with R for their daily work. A detailed syllabus follows.   read more …

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Population Databrowser

At Mazama Science we produce web based tools for interrogating important datasets. We are proud to announce the release of a new Population databrowser that allows users to review international population trends. We have done our best to make this release Open, Transparent and Reproducible by providing source code and data that enable readers to retrace our steps from raw data to final graphic.   read more …

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Using R — Working with Geospatial Data (and ggplot2)

This is a follow-up blog-post to an earlier introductory post by Steven Brey: Using R: Working with Geospatial Data. In this post, we’ll learn how to plot geospatial data in ggplot2. Why might we want to do this? Well, it’s really about your personal taste. Some people are willing to forfeit the fine-grained control of base graphics in exchange for the elegance of a ggplot. The choice is entirely yours.   read more …

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Getting your Mac ready for netCDF

If you are working with weather or climate data or big 3-4D model datasets you will undoubtedly encounter netCDF. Unidata’s Network Common Data Format has been the workhorse data format for atmospheric and oceanographic modelers since the early 1990′s. With more and more scientists using Macs to get their work done, it is important to get them ready with the the necessary tools of the trade.  This post walks you through the steps for setting up a Mac to work with netCDF.   read more …

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Installing FFTW3 and the ‘fftw’ R package

If you have to compile code that uses Fourier Transforms you may wish to use the FFTW library which the authors describe thusly:

Our benchmarks, performed on on a variety of platforms, show that FFTW’s performance is typically superior to that of other publicly available FFT software, and is even competitive with vendor-tuned codes. In contrast to vendor-tuned codes, however, FFTW’s performance is portable: the same program will perform well on most architectures without modification. Hence the name, “FFTW,” which stands for the somewhat whimsical title of “Fastest Fourier Transform in the West.”

This post has some tips on compiling this code and the associated R package ‘fftw’.   read more …

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