1. Development and deployment of
a cross-platform
open-source software package:
the Infobiotics Workbench
Jonathan BlakesJonathan Blakes
26/10/201026/10/2010
Supervised by Professor Natalio KrasnogorSupervised by Professor Natalio Krasnogor

2. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 2
Outline
 Introduction to Infobiotics
 Organisation of software
 Supporting technologies
 Tour of the Infobiotics Dashboard UI
 Interface considerations
 Deployment on Windows, Mac and Linux
 Finishing touches and availability
 Conclusions

3. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 3
Infobiotics Workbench

4. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 4
Infobiotics Models (syntax)

5. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 5
Infobiotics Models (semantics)

6. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 6
Infobiotics Experiments
 Command line tools with a common parameter
file format:
 simulation (mcss)
 model checking (pmodelchecker)
 model structure and parameter optimisation
(poptimizer)
 Desktop applications (not cloud-based)
 Written in C++ for speed

7. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 7
Infobiotics Dashboard
 User friendly graphical user interface for
perform Infobiotics experiments
 setting, loading and saving of parameters
 running experiments and reporting progress
 plotting output
 Present options in a clear and understandable
manner, setting limits on parameter values
 Give feedback when things go wrong!
 Written in Python

8. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 8
Why Python?
 Dynamic language: rapid prototyping
 Large stdlib: tempfile, XML parsers, itertools

3rd
party Libraries:
 NumPy – n-dimensional arrays and ufuncs
 pytables – HDF5 (simulator output)
 PyQt – Qt GUI bindings (GPL), QScintilla text editor
 Matplotlib – 2D plotting
 Mayavi – 3D VTK-based visualisation (TVTK)
 Traits...

9. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 9
Traits = Reactive Programming

10. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 10
Simulation Parameters (file)

11. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 11
Simulation Parameters (GUI)

12. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 12
Model checker parameters (1)
MC2

13. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 13
Model checker parameters (2)

14. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 14
Simulator Results
 Simulation output – amounts of each species in
each compartment at each timepoint for each
run - quickly become very large (gigabytes), but
only some data is of use to the modeller.
 selecting important information
 scaling amounts (molecules) to biologist-friendly
units (e.g. nanomolar)
 calculating statistics across runs (and other
dimensions)
 plotting timeseries, exporting data, etc.

15. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 15
SimulatorResultsDialog

16. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 16
Selecting data (filtering)
 Filter compartments by name using wildcards
 Using set class difference method
 Custom ListWidget is a factory for filter LineEdit

17. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 17
Selecting data (sorting)
 By providing custom QListWidget with regular
expression and function map
 Sort species by name
 Sort compartments by name and/or positions

18. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 18
Selecting data (sampling)
 Reducing data size by
sampling reduces
memory requirements,
speeds up
calculations and
unclutters plots
 100 of 10,000 runs

Every 100th
recorded
timepoint

19. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 19
Transforming data (scaling)
 Converts time, substance quantities and
volumes from simulator data units into user-
friendly display units, using python-quantities
 For calculating concentrations, use compartment
volumes (at each timepoint) if recorded, otherwise use
one volume for all compartments at all timepoints

20. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 20
Exporting data
 Selected data can be exported in several
common formats for use with other tools:
 text (.csv)
 Excel (.xls)
 NumPy (.npz)

21. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 21
Plotting timeseries (old)

22. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 22
Plotting timeseries (improved)

23. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 23
Exporting figures
 Added ability to save figures resized to specific
screen dimensions (pixels), as surprisingly,
matplotlib only supports physical dimensions
(inches)

24. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 24
Model checker results

25. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 25
Visualising simulations (Mayavi)

26. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 26
Cross-platform issues
 A lot of communication in Workbench uses
temporary files – these behave differently on
Windows to Linux
 must close temp files before use, which can delete
them!
 Pseudo-terminal emulation library pexpect used
to gather progress information not for Windows
 winpexpect port not functioning at time of release
 fall back to 'working' progress indicator
not good for long experiments

27. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 27
Deploying Python apps
 A lot of dependencies inc. Python
 Python comes with most Linux distributions, but not
with Windows (unlike JVM) and Mac system Python is
crippled
 Therefore we needed to bundle Python interpreter and
all libraries for Windows/Mac
 Possible solution: 'freezing' Python applications,
creates a single executable (~100 megabytes!)
 Need a solid base to start from and add missing
libraries also python(x,y)
for Windows

28. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 28
Freezing Python applications
 Freezing works well for small scripts, not so well for
applications with many libraries
 uses static code analysis for determine libraries for
bundling – TraitsUI/Matplotlib use dynamic imports
 Freezers: cx_freeze, bbfreeze, PyInstaller,
 Wrap python setup.py py2exe/py2app with bash scripts
 copy missed files, unzip zipped Python classes
 patch Matplotlib
 fix Mac library paths using install_name_tool

29. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 29
Windows and Mac non-Python
 mcss, pmodelchecker and poptimizer need cross-
compiling for 32/64-bit Linux (chroot), Windows (32-
bit) and Mac (OSX Snow Leopard only)
 pmodelchecker requires PRISM and MC2 which are
both Java applications
 InstallJammer builds cross-platform installer:

30. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 30
Linux (Debian)
 Not trivial either – no authorative packaging
guide
 Make packages for mcss, ..., PRISM, MC2, libhdf5-
1.8
 Used python-support to install Dashboard for
system Python(s)
 (1) add apt repository to sources.list
 (2) sudo apt-get install infobiotics-workbench
 Automatic updates!
 Fedora/Suse packages made using Alien

31. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 31
Documentation (User Guide)

32. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 32
Documentation (User Guide)
 Produced using Sphinx:
 input is reStructuredText
 output is high-quality formatted HTML, PDF, …
 Used Enthought reST editor for writing

33. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 33
Documentation (API)
 HTML API
generated from
docstrings
using Endo
 Alternatives:
 Epydoc
 Doxygen

34. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 34
Code availability

35. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 35
Soliciting user feedback
 getsatisfaction.com Javascript added to Sphinx template

36. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 36
Conclusions
 Cross-platform application development in
Python is easy, deployment is hard
 Need to become an expert in knowing the
differences between platforms
 50 / 50 development vs. the rest
 Good to be part of a team :)

37. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 37
Publications

38. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 38
Acknowledgements
 Jamie Twycross (mcss, packaging)
 Fran Romero Campero (IML, pmodelchecker, docs)
 Claudio Lima (poptimizer, docs)
 Pawel (for turning me on to Python)
 Natalio Krasnogor

39. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 39
Questions?

40. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 40
Slides available on web

41. Jonathan Blakes - Development and deployment of a cross-platform open-source software package 41
Infobiotics