Motivation

As a scientist you need to produce plots.

The question is how to plot?

plot and compare subsets of large data sets

You usually face large data sets, which you want to process in different manner to extract and plot a single aspect of this data set.

But you may also want to compare a single aspect of different data sets, or on the contrary different aspects of a single data set.

plot fast and interactively

And you may want to do in a fast and interactive manner.

be sure what you plot

But the most important for a scientist is to control what you do and be sure of what you plot.

clear and transparent way to plot

Plots are the key value of your work. You want to spend time on the quality of the content and form. Not on the technical aspect of how to plot what.

reuse, improve, and combine your plots

After spending time on designing the content and the form of a single plot you want to be able to use it for various data sets without loosing consistence between versions of the plot.

keep track of your plots over long periods

Finally, when you come back on some former work, you don't want to rethink about the technique, you want to start from the same point as before from another point of view.

These are the basic features of myplotlib and much more.

The power of myplotlib

myplotlib allows you to design a plot, that consist of a single file. It can then plotted alone or combined with any other plot.

This plot contains it own data processing method and can be used for any compatible raw data you provide.

A plot can be called interactively from a python interpreter, or from the command line.

The same plot can be drawn on screen or directly in a file making sure that what you see is what you get.

Producing files of the same aspect of large number of data sets is possible thanks to the scripting mode.

Because a plot is in a unique file, any changes will be spread, allowing fast and consistent corrections.

myplotlib can:

• interactive mode
• script mode
• consistent corrections
• versatile dataset
• full user control on IOs and data processing making it fast and safe