Matplotlib (MPL) is python charting library, with function similar to Gnuplot and interface modelled on Matlab API. AsciiDoc is converter from ascii text files (with human readable markup) to html and other doc formats.
Let say we need include sin(x) plot below into asciidoc document.
We just include following MPL code snippet:
["mpl", "example-sin.png"] ------------------------------------------- figure(figsize=(4,2)) # PNG size, inches X = arange(0, 6, 0.1) # 0, 0.1, 0.2 ... 6.0 Y = sin(X) # vector op plot(X,Y) -------------------------------------------
On first line in square brackets there are two parameters. First - "mpl" is name of asciidoc filter. Second is file name of your choice to store generated chart
Asciidoc will send inline python code between "----" lines to stdin of mplw.py, and generate HTML file with <img …> tag for MPLW produced PNG file.
Now let say we have some data from two experiments and we need to plot it:
It can be made with this snippet:
["mpl", "example-data.png"]
-------------------------------------------
figure(figsize=(5,2.5))
title('Two Charts')
xlabel('Some text')
plot(c[0],c[1]) # x, y1
plot(c[0],c[2]) # x, y2
# columns below: x, y1, y2
___________________________________________
1.0, 2.0, 1.0
2.0, 4.0, 1.2
3.0, 4.5, 1.6
4.0, 5.0, 3.3
5.0, 5.2, 4.4
-------------------------------------------
Text after "__" is plot data in table form. The c[][] is matrix where c[0] is vector holding 1st column from above table, c[1] is second column and so on. You can store plot data in in external file if needed, see matplotlib manual.
To see what MatPlotLib is capable of go to matplotlib gallery.
