Matplotlib:from brain surgery to rocket scienceJohn D. Hunter, Ph.D.Perry Greenfield, Ph.D.

http://matplotlib.sourceforge.net

brain surgery…

dongle

pbrain

loc3djr

http://pbrain.sourceforge.net

The three stages of python• Matlab hell• Python purgatory• The path to

enlightenment

3D python fantastic, but 2D?PyX, ChartDirector, biggles, DISLIN, gnuplot, chaco, xplt, gplt, pyngl, ppgplot, tkinter canvas, gtk-extras, pychart, gist, piddle, graphite….

• Multiple plotting idioms

• Cross platform

• Publication quality

• Permissive license

• Extensible (by me!)

• Easy plots should be easy (OO not always best)

• But app embedding should be supported (OO sometimes best)

• GUI agnosticism

• The curse of python

# matplotlib 0.1~/python/matplot_gtk12> lsREADME matplotlib.py subplot_demo.pydata simple_plot.py view_data.pymatplot.py stock_demo.py vline_demo.py

# matplotlib 0.73

53 python modules

17 files of extension code

44,000 lines of code

130 examples

• 2-5 active developers at any time; 25 contributors

•Co-developed with NASA STScI and JPL

• 1200-1500 downloads/month

• approx 10 messages per/day on mailing list

Copy the great architecturesE Tufte

backends

The matplotlib APIfrom matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvasfrom matplotlib.figure import Figure

fig = Figure()canvas = FigureCanvas(fig)ax = fig.add_subplot(111)ax.plot([1,2,3]) aax.set_title('hi mom')ax.grid(True)ax.set_xlabel('time')ax.set_ylabel('volts')fig.savefig('test')

pylab interface

• Plotting should just work

• Easy plots should be easy

• GUI / interactive complexity should be managed

• ipython to the rescue

IPython 0.6.12_cvs -- An enhanced Interactive Python.? -> Introduction to IPython's features.%magic -> Information about IPython's 'magic' % functions.help -> Python's own help system.object? -> Details about 'object'. ?object also works, ?? prints more.

Welcome to pylab, a matplotlib-based Python environment help(matplotlib) -> generic matplotlib information help(pylab) -> matlab-compatible commands from matplotlib help(plotting) -> plotting commands

In [1]: plot([1,2,3])

# Numericfrom Numeric import array, wherefrom MLab import stdfrom Numeric import convolvefrom FFT import fft

# numarrayfrom numarray import array, wherefrom numarray.linear_algebra.mlab import stdfrom numarray.convolve import convolvefrom numarray.fft import fft

# matplotlib.numerixfrom matplotlib.numerix import array, wherefrom matplotlib.numerix.mlab import, mean, std

# choose numeric or numarray from the shellC:> python myscript.py --numarray

# or in an rc file settingnumerix : ‘numarray’

The numerix module

font manager

• Cross platform font finding: win32, linux, OS X

• Configurable families: the font engine will pick the best font to match your requirements

• W3C compliant

font.family : sans-seriffont.style : normalfont.variant : normalfont.weight : mediumfont.stretch : normalfont.size : mediumfont.serif : New Century Schoolbook, Century Schoolbook L, Utopia, ITC Bookman, Bookman, Bitstream Vera Serif, Nimbus Roman No9 L, Times New Roman, Times, Palatino, Charter, seriffont.sans-serif : Lucida Grande, Verdana, Geneva, Lucida,

tex = r'$\cal{R}\prod_{i=\alpha_{i+1}}^\infty a_I … \rm{sin}(2 \pi f x_i)$'text(1, 1.6, tex, fontsize=30)

mathtext demo

bar demo

stacked bar

pie demo

scatter demo

histogram demo

log demo

polar demo

layer image

subplot demo

axes demo

legend demo

text alignment

mathtext demo2

cylindrical equidistant, mercator, lambert conformal conic, lambert azimuthal equal area, albers equal area conic and stereographic.

basemaptoolkit

stock demo

finance demo

MRI with eeg

EEG demo

VTK demo

Did I talk about?

• Event handling

• set/set Introspection

• RC configuration

• Embedding

• Dynamic/animated plots

• Math text

• Contouring

• Toolkits / basemap

• Font management

…from astronomy to zoology?• Basic 3D• Different colorspaces (CMYK)• Arbitrary clipping paths, gradient/pattern fills• Unicode support & better TeX support• Domain specific toolkits• SWF, PDF, Aqua, …• Direction fields, arrows, etc

MATPLOTLIB CREDITS (in order of appearance…)

• Jeremy O'Donoghue wrote the wx backend• Andrew Straw provided much of the log scaling architecture, the fill command, PIL support for

imshow, and provided many examples• Charles Twardy provided the impetus code for the legend class and has made countless bug

reports and suggestions for improvement.• Gary Ruben made many enhancements to errorbar to support x and y errorbar plots, and added a

number of new marker types to plot.• John Gill wrote the table class and examples• David Moore wrote the paint backend• Todd Miller contributed the TkAgg backend and the numerix module, which allows matplotlib to

work with either numeric or numarray. He also ported image support to the postscript backend, with much pain and suffering.

• Paul Barrett overhauled font management to provide an improved, free-standing, platform independent font manager with a WC3 compliant font finder and cache mechanism and ported truetype and mathtext to PS

• Perry Greenfield overhauled and modernized the goals and priorities page, implemented an improved colormap framework, and has provided many suggestions and a lot of insight to the overall design and organization of matplotlib.

• Jared Wahlstrand wrote the SVG backend

MATPLOTLIB CREDITS (continued)

• Steve Chaplin is the GTK maintainer and wrote the Cairo and GTKCairo backends• Jim Benson provided the patch to handle vertical mathttext• Gregory Lielens provided the FltkAgg backend and several patches for the frontend, including

contributions to toolbar2, and support for log ticking with alternate bases and major and minor log ticking

• Darren Dale did the work to do mathtext exponential labeling for log plots.• Paul Mcguire provided the pyparsing module on which mathtext relies, and made a number of

optimizations to the matplotlib mathtext grammar.• Fernando Perez has provided numerous bug reports and patches for cleaning up backend

imports and expanding pylab functionality, and provided matplotlib support in the pylab mode for ipython. He also provided the matshow command.

• Andrew Dalke of Dalke Scientific Software contributed the strftime formatting code to handle years earlier than 1900

• Jochen Voss maintained the PS backend and has contributed several bugfixes.• Nadia Dencheva of STScI provided the contouring and contour labeling code• Baptiste Carvello provided the key ideas in a patch for proper shared axes support that underlies

ganged plots and multiscale plots• Sigve Tjoraand Ted Drain and colleagues at the JPL collaborated on the QtAgg backend• Eric Firing added the contourf function and general contour refactoring

pie demo