This document introduces AvoPlot, a graphical frontend for matplotlib that aims to make data visualization easier for scientists. AvoPlot allows graphical import of common data formats, basic data processing, and a drag-and-drop replacement for matplotlib's plotting interface. Plugins can be created to add new data types and processing tools. The document provides background on issues with existing tools, outlines AvoPlot's design and goals, and demonstrates its scripting interface and use of plugins through an example FTIR plugin. It concludes by inviting more developers to contribute to the open source project.

1. Life after matplotlib:
Harder, better, faster, stronger
Kayla Iacovino
http://code.google.com/p/avoplot

2. A brief history of me.

3. A brief history of me.

4. A brief history of me.

5. It all started with a bang...

6. ...and a rather chilly garage

7. Data Problems
+
Existing Python tools
● Aims
● Design
● Current state
● Future
=

8. Science in a nutshell.
Data
Import
Processing
Visualisation

9. What is the problem?
● Need general tools that can be
specialised for the task at hand.
● Specialisations should be easily
reusable.

10. Python solves all?
Data
Import
Processing
Visualisation
● xlrd
● NumPy
● csv
● Pandas
● SciPy
● NumPy
● matplotlib

11. What is the real problem?
● Scientists are not (usually)
programmers.
● Scientists are usually in a hurry.
● Scientists are stupid (outside of
their field).
● Scripting is a frustrating way to
achieve visualisation tasks.

12. AvoPlot: Aims
● Graphical frontend to matplotlib.
● Graphical import of common data
formats (txt, csv, xls etc.).
● Basic data processing capabilities.

13. ● Drag and drop replacement for
matplotlib's pyplot interface.
● Easily customisable.
● Framework for scientists to create
GUIs for their processing tools.
AvoPlot: Aims 2

14. GUI interface for easy
data visualisation
Plugins mean AvoPlot is
versatile – and extensible!
Powered by Python with a
powerful scripting interface
Anatomy of AvoPlot

15. “Open-source software is written by a
bunch of hippies living in a commune in
Palo Alto. With their beards down to their
socks and sandals, living on nothing but
organic avocados. Look at me, I am so
moral.”
- Talfan Barnie, 2010 (somewhere in Ethiopia)
But what has this got to do with
avocados?

17. import matplotlib.pyplot as plt
import numpy
xdata = numpy.linspace(0, 7, 500)
ydata = numpy.cos(xdata)
plt.plot(xdata, ydata, 'r-')
plt.show() import avoplot.pyplot as plt
import numpy
xdata = numpy.linspace(0, 7, 500)
ydata = numpy.cos(xdata)
plt.plot(xdata, ydata, 'r-')
plt.show()
Scripting interface

18. Plugins
● Python module or Python package
● Allow import of new data types, and
provision of new manipulation or
processing tools.
● Distributed with distutils.
● Highly integrated with the GUI.

20. FTIR Plugin
#define new data series type for FTIR data
class FTIRSpectrumData(series.XYDataSeries):
def __init__(self, *args, **kwargs):
super(FTIRSpectrumData, self).__init__(*args, **kwargs)
self.add_control_panel(BackgroundCalcCtrl(self))
@staticmethod
def get_supported_subplot_type():
return FTIRSpectrumSubplot
class FTIRPlugin(plugins.AvoPlotPluginSimple):
def __init__(self):
super(FTIRPlugin, self).__init__("FTIR Plugin", FTIRSpectrumData)
self.set_menu_entry(['FTIR', 'New Spectrum'], "Plot an FTIR spectrum")

21. AvoPlot: the future
X Y
0.3 0.296
0.4 0.389
0.5 0.479
0.6 0.565
0.7 0.644
0.8 0.767
0.9 0.783
1.0 0.841
1.1 0.891
1.2 0.932

22. Overview/Conclusions
● It works (sort of).
● It's useful (at least we think so).
● More developers are needed!

23. Questions
http://code.google.com/p/avoplot