Complex Systems Summer School 2013-Tutorials

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CSSS participants come from a wide range of disciplines. Participants are encouraged to share their knowledge by organizing their own tutorials.

Also, please post requests for tutorials here.

This is not a Tutorial! I Pablo_Galindo had nowhere else to post it! Its an article pointing out 15 mistakes that could sink your academic careers! http://chronicle.com/article/Self-Sabotage-in-the-Academic/138875/

Network Visualization Using Gephi

I will be showing people some basic features of using Gelphi to visualize networks this week. If there are other people who are also interested, we could turn it into a tutorial. -- Hua

This tutorial will be held on Wednesday (June 12th) at 1:30 (after lunch) at the main lecture hall. Stephan and I will show step by step network visualization and analysis in the tutorial. If you want to play with Gephi hands on during the tutorial, please download and install Gephi ahead of time. Link to Download Gephi. The example we will use can be downloaded from here.

• I'm in -- Mauricio
• Hua, thanks!. I'm in! Regina
• I will attend- Susanne

Bayesian Modeling

I'd love to attend tutorials on Bayesian Modeling. I will be happy if someone can give a series of tutorials on this topic. Ren

I would also be interested in this! -Brady same here! Ivana

• I'm in -- Mauricio

• I might be able to help with this, though likely in more of a discussion format, perhaps with some slides stolen from a colleague :) Nix

• Thanks Nix! Ren

• I'm in! Thanks. Regina

• Max and I will probably schedule this tutorial for next week (after my lecture). Nix

Dynamics in Networks

I am very interested in learning about network dynamics. Anyone else interested in having a tutorial on that? Regina

• I'm very experienced with hidden Markov models, which are a generalization of Markov chains. These are networks with a (potentially stochastic) dynamic. Maybe this would help! Nix

• Nix, that's great! Many thanks. I'm in for this one and the Bayesian-- Regina
• I'm in -- Mauricio

Cross impact balances and Markov chains

For anyone who could not make the tutorial, here is a copy of the slides, which provide another way of interpreting web pages explaining the CIB algorithm. Note that from the cross-impact balance analysis web site, you can download the free software to play with CIB analysis yourself. I am also happy to talk more one-on-one if needed! --Vanessas 02:24, 6 June 2013 (UTC)

As part of brainstorming for a possible project, three of us have decided to do a tutorial on cross-impact balances (CIB) (delivered by Vanessa) and Markov chains (delivered by Alastair and Matteo). We think these methods could be leveraged to research some interesting questions. All are invited to this tutorial regardless of their interest in contributing to a project using these methods. This tutorial will be Wed. June 5th at 4:00 PM in the large lecture hall. -- Vanessa
PS -- For those interested in examples of studies that have used CIB analysis, see this one on century-long socioeconomic scenarios or this abstract on a qualitative model regarding obesity development and prevention.

Genetic Algorithms and Multi-Objective Optimization

I have seen many people interested in implementing GAs to evolve networks, which is something I have done for some of my research. I also worked with Multi-Objective Optimization (MOO), which is perfectly possible with GAs and has been around for a while; but it has not become so mainstream. I propose to make a brief tutorial of classic Genetic Algorithm vs. Multi-Objective Genetic Algorithm. Enough people interested? If we are a few of us, we could just meet up and I'll tell you the basics! -- Luíño

I would be very interested! -- Molly

Me too --Mauricio_Cantor

Me too -- Elena

Me too! -- Matteo

Me too -- Cheryl

I'm in! Regina

Yes! Jim

• I will come, Susanne

We scheduled this tutorial for Tuesday at 3:00 pm, just before the time to work on projects. Hope that you find it interesting! -- Luíño

Material:

Some material from the presentation:

• Sildes, File:MOGA.pdf: These are from a larger, previously existing presentation; so you will find more stuff in there than I gave in the presentation. Feel free to come and ask about anything you want!
• Websites:
  • The infamous evolving car that takes away attention from the speaker.
  • Website to evolve pictures after successive selection.
  • This one uses a genotype that encodes for polygons and evolve the Mona Lisa. You can find a gallery with other pictures evolved and an applet in here. By the way, I used this polygon genetic algorithm for my project on EEG-based image reconstruction, so you never now when something turns out useful in really distant parts of science.
  • You can find plenty of resources similar to these by just googling!
• Some literature on the topic:
  • Nice, classic Science paper on genetic algorithms by Stefanie Forrest (external SFI).
  • Does nature use MOO? Some answers here and here.
• Code (in C++): I am not going to post it because I never made it thinking that someone but me could use... and my code is a relative mess. I will provide it to whoever requires it, specially if you are doing a CSSS project that would enjoy MOO. Just come talk to me! Most surely we would have to talk through some details about how it works, but I assure that it is very easy, it should be platform independent, and it should be trivial to make it work together with any arbitrary programming language that supports file I/O--i.e. any decent programming language... but please don't use something like this.

Nix's Bag O' Mathematical Tools

I'm planning on giving a number of tutorials to supplement Jim Crutchfield and I's lectures. The purpose of these should be to help you with your projects ( and encourage usage of our methods ;) ). I think it'd be cool for people to use this area to suggest topics to focus on. I started an empty bulleted list below. This will become more clear after we've given our lectures, but feel free to throw ideas out there when they come up. General topics might be: Information theory, time series analysis/modeling/prediction, symbolic dynamics (coarse-graining dynamical systems, i.e. what Liz Bradley discussed briefly), hidden Markov models, signal processing, bayesian inference, complexity measures, etc. Nix

• Intro to information theory. There seems to be some interest in this. I'd be happy to give a tutorial, but I should note that it will be covered (at a rapid pace) in Jim Crutchfield's lecture. Nix
• I really want to learn how to fit hidden Markov models to data. --David
• I'm very interested, Nix. Many thanks! Regina
• i'm in!! amara
• i'm in also! Ivana
• I'm in -- Mauricio

Okay, I'll try to cover info theory, hidden markof model inference, and bayesian inference next week. Some of this will be covered this week in Jim's lectures and my labs. Nix

Python

Downloads:

Python Python (get version 2.*, not 3.*)

IPython

You can find links to the key scientific packages for Python here

If you're new to coding, one good resource is Codecademy. Learn Python the Hard Way is exactly what it sounds like, and is also good. Finally, Google is your friend, and there's plenty of help online for pretty much anything Python-related.

To launch Python, just open a terminal / command line window and type python. If you've installed IPython, you can open an IPython command line with ipython.

To launch the IPython Notebook, run ipython notebook -- This will launch a notebook window in your browser. If you close it out, it's probably running at 127.0.0.1:8888 (but check the terminal window). Be sure to save your work, and when you're done shut down the server with command/control-C in the terminal.

If you've installed Matplotlib, you can embed plots in the notebook by launching it as ipython notebook --pylab inline

Notes from the CSSS tutorial are up online here. I've also put up a quick and dirty implementation of a very basic genetic algorithm in Python.