This document discusses why Python is useful for scientific research. It notes that Python is simple, dynamic and has many built-in libraries that can be used for tasks like network analysis, agent-based modeling, and complex systems modeling. Python also has a large community contributing libraries and support. Additionally, Python allows for reproducible science through documentation of code and data. The document provides examples of how Python has been used for projects involving modeling transportation systems, epidemics, social networks and more.

1. Why Python in
Scientific
Research?
Erika Fille Legara, Ph.D.
Program Director, M.S. in Data Science
Asian Institute of Management
@eflegara | eflegara.github.io

2. July 2017January 2012January 2006
~5.5 years
Master of Science in Data Science

3. Complex Systems
“In general usage, complexity
tends to be used to
characterize something with
many parts in intricate
arrangement.”
EF Legara • @eflegara • Asian Inst. of Management

4. Complicated vs.
Complex
EF Legara • @eflegara • Asian Inst. of Management

5. Complicated vs.
Complex
EF Legara • @eflegara • Asian Inst. of Management

6. Complex Systems in Nature
EF Legara • @eflegara • Asian Inst. of Management

7. Complex Systems in Society
EF Legara • @eflegara • Asian Inst. of Management

8. Complex Systems
• LARGE and DIVERSE
INTERACTING parts
• No centralised control
• SELF-ORGANISATION and
EMERGENCE
• EVOLUTION and ADAPTATION
EF Legara • @eflegara • Asian Inst. of Management

9. Why Study Complex Systems
1. Demographic change
2. Financial and economic stability
3. Social, economic and political inclusion
4. Public health (epidemics)
5. Balance of power and conflict
6. Corruption and crime
7. Collective social behavior
8. Institutional design
9. Sustainable use of resources
10. Reliability of critical infrastructures
Real-World Issues
EF Legara • @eflegara • Asian Inst. of Management

10. “I think the next
century will be
the century of
Complexity.”

11. Complexity Science
“The whole is more
than the sum of its
parts.”
EF Legara • @eflegara • Asian Inst. of Management

12. Game
Theory
Collective
Behavior
Networks
Evolution &
Adaptation
Pattern
Formation
Systems
Theory
Nonlinear
Dynamics
COMPLEX SYSTEMS
“The whole is more than the
sum of its parts.”
EF Legara • @eflegara • Asian Inst. of Management

13. Urban
Complexity
Projects
Bus Arrivals
Waiting time ½ x headway2 =
the area of each
triangle
time
headway
headway
EWT
SWT
AWT
An interactive visual, demand modelling, and decision-support tool.!

14. Bus Arrivals
Waiting time ½ x headway2 =
the area of each
triangle
time
headway
headway
EWT
SWT
AWT
An interactive visual, demand modelling, and decision-support tool.!An interactive visual, demand modelling, and decision-support tool.!
Bus Arrivals
Waiting time ½ x headway2 =
the area of each
triangle
time
headway
headway
EWT
SWT
AWT
Modeling and
Simulations of
the Rapid Transit
System
Reliability
Analysis of Bus
Arrivals
Lightless
intersection
control numerical
simulations
Land-Use &
Transport Modeling
Crowd Modeling
and Simulations
Characterizing
Public Transport
Commuters
Resilience of
Commuter
Encounter
Networks
Aging, Biology &
Computing:
Healthspan
Identification of
Regulators in a
Human Gene
Network
Urban Morphology
Dynamical Model of
Twitter Activity
Profiles
Diffusion &
Cascading Failures
on Multiplex
Networks
Urban
Complexity
Projects

15. OPEN-MINDED KA BA?
TARA, KAPE TAYO.

16. BLACK-BOX models
MECHANISM-BASED
models
START STEP DECISION
ACTION
ACTION
END
END
PREDICTIVE ANALYTICS
EF Legara • @eflegara • Asian Inst. of Management

17. Multilevel Marketing
or Pyramid Scams?
A mechanism-based model to
reconstruct network marketing
EF Legara • @eflegara • Asian Inst. of Management

18. Agent-Based Modeling + Network Science
Most real-world systems can only be modeled algorithmically.
“Social Network”
EF Legara • @eflegara • Asian Inst. of Management

19. Agent-based modeling
a class of computational models
for simulating the
actions and interactions of
autonomous agents
EF Legara • @eflegara • Asian Inst. of Management

20. Agent-based modeling
• Bottom-up approach
• Simulate actions and interactions of
autonomous agents in a synthetic
virtual “world”
• Best for “what-if” scenario modeling
Applications
• Epidemiology and Contagion
• Traffic
• Financial markets
** EF Legara (2014). Complexity in Public Policy: Tools and Applications (Complex Networks and Agent-Based Models: An Overview).
Managing Complexity from a Public Policy Perspective (A Lecture), Civil Service College, Singapore, 15-16 October 2014.
ABM in Public Policy**
Organisation for Economic Co-operation and
Development (OECD)
Global Science Forum

21. Agent-Based Modeling
EF Legara, KK Lee, GG Hung, and C Monterola, "Mechanism-based model of a mass rapid transit
system: A perspective," Int. J. Mod. Phys. Conf. Ser. 36, 1560011 (2015).
N Othman, EF Legara, V Selvam, and C Monterola, "A Data-Driven Agent-Based Model of
Congestion and Scaling Dynamics of Rapid Transit Systems," J of Computational Science (2015).
Integrated Public Transportation Visualization and
Simulation Platform of Singapore
Predicting the H1N1 Epidemic
The predicted spread of the H1N1 epidemics during 2009, representing the first successful real-time prediction of a
pandemic [13]. The project, relying on data describing the structure and the dynamics of the worldwide transportation
network, foresaw that H1N1 will peak out in October 2009, in contrast with the expected January-February peak of
influenza. This meant that the vaccines timed for November 2009 were too late, eventually having little impact on the
outcome of the epdemic. The success of this project shows the power of network science in facilitating advances in areas
of key importance for humanity.
Video courtesy of Alessandro Vespignani. Network Science by Albert-Laszlo Barabasi.
EF Legara • @eflegara • Asian Inst. of Management

22. SOCIETY BUSINESS NETWORK
EF Legara • @eflegara • Asian Inst. of Management

23. Network Science
• Short path length
• High clustering coefficient
Social Network
EF Legara • @eflegara • Asian Inst. of Management

24. 1
2
3
4
5
6 Can you connect
yourself to
Donald Trump?
Short path length
“It’s a small world!”
EF Legara • @eflegara • Asian Inst. of Management

25. High clustering coefficient
Our “friends” are
likely to also be
“friends” with each
other.
EF Legara • @eflegara • Asian Inst. of Management

26. EF Legara • @eflegara • Asian Inst. of Management
C++ C++

27. import networkx as nx
G = nx.watts_strogatz_graph(n, k, p, seed=None)
EF Legara • @eflegara • Asian Inst. of Management

28. NetworkX
The built-in
libraries!!
EF Legara • @eflegara • Asian Inst. of Management

30. EF Legara • @eflegara • Asian Inst. of Management

31. Aric Hagberg Dan Schult Pieter Swart
The
community!!
EF Legara • @eflegara • Asian Inst. of Management

32. Watts-Strogatz Social Network Model
Unilevel Business Network
Binary Level Business Network
EF Legara • @eflegara • Asian Inst. of Management
EF Legara, C Monterola, DE Juanico, M Litong-Palima, C. Saloma, "Earning potential in
multilevel marketing enterprises," Physica A 387, pp. 4889-4895 (2008).

33. Contrary to claims of unbridled growth.
analytic
actual
simulated
NumberofAgents
Level
https://tinyurl.com/erika-aim-mlm EF Legara, C Monterola, DE Juanico, M Litong-Palima, C. Saloma, "Earning potential in
multilevel marketing enterprises," Physica A 387, pp. 4889-4895 (2008).

34. The Unexpected Effectiveness
of Python in Science
by Jake VanderPlas
EF Legara • @eflegara • Asian Inst. of Management

35. Game
Theory
Collective
Behavior
Networks
Evolution &
Adaptation
Pattern
Formation
Systems
Theory
Nonlinear
Dynamics
COMPLEX SYSTEMS
“The whole is more than the sum
of its parts.”
EF Legara • @eflegara • Asian Inst. of Management

36. Graph-tool
PyPI Dependency Networkhttp://erikafille.ph
C++
Python

37. http://erikafille.ph

38. EF Legara • @eflegara • Asian Inst. of Management

40. GBM
DRF
SVM
Train the
ML models
Adult
Child
Senior Citizen
EF Legara and C Monterola,
"Inferring Passenger Types from
Commuter Eigentravel Matrices,"
Transportmetrica B: Transport
Dynamics, Feb 2017. Doi:
10.1080/21680566.2017.1291377
(“travel DNA”)

41. https://xkcd.com/353/
EF Legara • @eflegara • Asian Inst. of Management

42. EF Legara • @eflegara • Asian Inst. of Management

43. C++ python
EF Legara • @eflegara • Asian Inst. of Management

44. python
IEEE SCALE Challenge. First Prize Winner
Perfect for prototyping.
python
Scalable complex system modeling
for a sustainable city
EF Legara • @eflegara • Asian Inst. of Management

45. EF Legara • @eflegara • Asian Inst. of Management

46. Reproducible
Science
http://eflegara.github.io

47. Why python?
It’s simple and dynamic!
The built-in libraries!
The community!
The reproducibility!
And many more…
EF Legara • @eflegara • Asian Inst. of Management

48. Why Python in
Scientific
Research?
Erika Fille Legara, Ph.D.
Program Director, M.S. in Data Science
Asian Institute of Management
@eflegara | eflegara.github.io