GitHub - EnricoBorriello/CAS522_Dynamical_Systems_didactic_material: This folder contains didactic material for the students of 'CAS 522 Dynamical Systems' (Instructor: Enrico Borriello - ASU, Fall B 2021). Come back at the end of each Module, for a sample solution to the coding problems.

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This folder contains didactic material for the students of 'CAS 522 Dynamical Systems' (Instructor: Enrico Borriello - ASU, Fall B 2021). Come back at the end of each Module, for a sample solution to the coding problems.

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Name		Name	Last commit message	Last commit date
Latest commit History 96 Commits
figures		figures
Module 2 - Random Networks.ipynb		Module 2 - Random Networks.ipynb
Module 3 - Systems of ODEs with SciPy.ipynb		Module 3 - Systems of ODEs with SciPy.ipynb
Module 4 - Difference Equations & Iteration.ipynb		Module 4 - Difference Equations & Iteration.ipynb
Module 5 - Linear Systems of Equations & Absorbing Markov Chains.ipynb		Module 5 - Linear Systems of Equations & Absorbing Markov Chains.ipynb
Module 7 Pt 1 - Continuous Systems w_ 1 indep. variable.ipynb		Module 7 Pt 1 - Continuous Systems w_ 1 indep. variable.ipynb
Module 7 Pt 2 - Continuous Systems w: multiple indep, variables.ipynb		Module 7 Pt 2 - Continuous Systems w: multiple indep, variables.ipynb
Module 7 Pt 3 - Finite_State Systems.ipynb		Module 7 Pt 3 - Finite_State Systems.ipynb
README.dm		README.dm
diffusion.mp4		diffusion.mp4

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Instructor: Enrico Borriello, PhD (School of Complex Adaprive systems, ASU) 
Class: CAS 522 Dynamical Systems (Fall B 2023)

This folder contains didactic material for the students of 'CAS 522 Dynamical Systems'.
Come back at the end of each module, for sample solutions to the coding problems.

Module 2 | Random Networks
Required Packages: Numpy, Random, PyVis 
Goals: In this module you will learn how to generate and visualize random networks. You will also learn how to extract information from an adjacency matrix, and calculate the clustering coefficient of a random network.

Module 3 | Systems of ODEs with ScyPy
Required Packages: NumPy, SciPy, Matplotlib
Goals: In this module you will learn how to use ScyPy to numerically solve systems of normal and ordinary differential equations.

Module 4 | Difference Equations & Iteration
Required Packages: Matplotlib
Goals: In this module you will learn how to generate time series iteratively, and how to visualize them using Matplotlib.

Module 5 | Linear Systems of Equations and Absorbing Markov Chains
Required Packages: Numpy, PyVis, SymPy
Goals: Solve linear systems of equations symbolically, and use this technique to solve absorbing Markov Chains.