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Showing posts from January, 2017

Scientific writing: high quality scalable vector graphics

I recently found a new way to prepare publication-ready high quality vector graphic using Google Drive.
Here is the result:

Here are steps you can follow:

Prepare a Google sheets within Google Drive;Insert chart from the menu;Define whatever color or label you like;Use development tool within Google Chrome to find the SVG tag in the html script;Open your text editor and paste the SVG html tag into it;Make up the SVG header, remember to define the SVG version.Save the text file as a SVG file.You may want to convert the SVG file to a Postscript (PS) file so you can convert it to any 600dpi raster figure. The essential idea behind this is that Google Chart API uses SVG and we are basically calling Google Chart API to produce chart without actually writing any script! The above figure is Copy right protected

High Performance Computing: Download and prepare data in a batch mode

Over the time, I need to manipulate a lot of data on a Linux cluster. Some of these manipulations actually read/write data, whereas some are essentially file system operations, such as downloading the files.
Here I present a list of similar operations suitable for HPC using pbs job approach whenever possible.
I do not attempt to include all possible methods but only the ones that I find useful and easy to prepare in seconds.
The most efficient way to download MODIS alike data using HPC.
wget -r --no-parent -R "index.html*" --retr-symlinks -A "*.nc" ftp-url
wget -r --no-parent -R "index.html*" -A "MOD17A2.A2000*.hdf" -A "MOD17A2.A2000*.xml" http-url
wget -r --no-parent -R "index.html*" -A "MOD17*.hdf" -A "MOD17*.xml" http-url
You can basically setup filter for file type, year and granule id.
A live example:
#PBS -l…