Introduction to High-Performance Scientific Computing

Re:Introduction to High-Performance Scientific Computing by leephillips on Tuesday January 24, 2017 @09:35AM (#13471573)

Gnuplot can handle data files with millions of points, that some users have reported to cause Matplotlib to crash. It's actually easy to make the plots look good. It can be controlled through a socket interface from any programming language, and seemlessly integrates with LaTeX.

We're about to start rolling out chapters from my book, which covers the latest version:

https://alogus.com/publishing/gnuplot5/

EDITed to reflect comment below.

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Re:Introduction to High-Performance Scientific Computing by metaobject on Tuesday January 24, 2017 @10:40AM (#13472187)

Hmmm, I've never had mpl crash and we routinely plot data sets with 10s of millions of points. We do a mixture of 2D scatter plots. 1D/2D histograms, and a few 3D plots. What type of plots are you generating? What type of data?

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Re:Introduction to High-Performance Scientific Computing by leephillips on Tuesday January 24, 2017 @10:46AM (#13472240)

I never had the problem myself, but have seen a handful of user reports in mailing lists and SO. Perhaps recent releases are better performing. I used to use mpl regularly and found it very capable, but never liked the API.

I've edited my comment to make it more accurate.

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Re:Introduction to High-Performance Scientific Computing by n00b101 on Tuesday January 24, 2017 @06:02PM (#13476615)

> we routinely plot data sets with 10s of millions of points

What is the performance like on that?

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