C1. Python Basics

C1.1. Prerequisite

1. Download and install Anaconda 3  before class.

   • Anaconda 3 is a Python distribution which will be the compiler for our Python codes;
   • We are going to use it to create virtual environment to ensure everybody in this class is on the same page;
   • The version does not matter if we use virtual environment. I installed Anaconda3-2022.10-Windows-x86_64.exe for my Windows machine.
   • For Windows PCs, you can set up a virtual environment following these steps:
     • Open anaconda prompt, or alternatively, you can add anaconda to system path (the Windows environment variable).

       D:\Programs\anaconda3
       D:\Programs\anaconda3\Scripts
       D:\Programs\anaconda3\Library\bin

       After doing this, you can call python.exe and pip.exe in your command prompt (cmd.exe)
     • Create a virtual environment python 3.10 under the name “main”:
       • conda create -n main python=3.10
       • Type y to confirm downloading the packages and wait.
     • Activate it
       • conda activate main
     • Now, if you run command pip install, the packages will be installed for this virtual environment
       • pip install matplotlib pandas numba control dearpygui
     • Open file explorer.exe at current directory
       • explorer.exe .
     • Create a file named my_dearpygui_demo.py and paste the following codes and save

       import dearpygui.dearpygui as dpg
       import dearpygui.demo as demo
       dpg.create_context()
       dpg.create_viewport(title='Custom Title', width=600, height=600)
       demo.show_demo()
       dpg.setup_dearpygui()
       dpg.show_viewport()
       dpg.start_dearpygui()
       dpg.destroy_context()

     • Run python codes
       • python my_dearpygui_demo.py
       • Have fun!
     • You can check existing virtual environment by typing: conda env list
   • Jupyter notebook/lab
     • Open cmd.exe and type jupyter lab. It will fire up jupyter lab in your default browser.
     • I often use jupyter lab to do derivation verification and here is an example (you need to pip install sympy):

       from sympy import *
       from IPython.display import display, Latex
        
       # display result without need of print (matlab like)
       from IPython.core.interactiveshell import InteractiveShell; InteractiveShell.ast_node_interactivity = "all"
        
       # use mathjax
       init_printing(use_latex='mathjax')
        
       # Define symbols
       t, p, a, b, c, d, e = symbols('t, p, a, b, c, d, e')
       L_σ = Symbol(r'L_\sigma')
       M_σ = Symbol(r'M_\sigma')
       i_alpha = Function(r'i_{\alpha}')(t)
       i_beta  = Function(r'i_{\beta}')(t)
       i_abs = Matrix(2, 1, [i_alpha, i_beta])
       Theta = Function(r'\varTheta')(t)
       Omega = Theta.diff(t)
        
       # Display stuff
       display(i_abs)
       display(Theta, Omega)
       a=100
       a
       100+a
        
       # Rotation Matrix
       P = Matrix(2,2,     [ cos(Theta), sin(Theta), \
                            -sin(Theta), cos(Theta)] )
       P_inv = P.T
       # Full Park transformation (power invariant)
       T = sqrt(2/3)*Matrix(3,3,
                            [ cos(Theta),  cos(Theta-2*pi/3),  cos(Theta-4*pi/3), 
                             -sin(Theta), -sin(Theta-2*pi/3), -sin(Theta-4*pi/3),
                               1/sqrt(2),          1/sqrt(2),          1/sqrt(2)] )
       T_inv = T.T
       # Verify inverse equals transpose
       display(simplify(T*T_inv))
       display(simplify(T_inv*T))
        
       # Matrix
       Labcσs = Matrix(3,3, [L_σ, M_σ, M_σ, \
                             M_σ, L_σ, M_σ, \
                             M_σ, M_σ, L_σ] )
       display(Labcσs)
       Ldqnσs = T * Labcσs * T_inv
       display(simplify(Ldqnσs))
        
       # LaTeX
       latex(simplify(Ldqnσs))

     • ctrl+enter to execute and stay at current block.
     • shift+enter to execute and move to next block.

2. Download and install Visual Studio Code  before class. VS code is a popular editor for programmers.

   • You need to install extension for Python
   • We can then take advantage of its super-cool jupyter notebook compatibility.
     • Option 1: to activate a regular jupyter notebook, press ctrl+shift+p, type create: new jupyter notebook.
     • Option 2: use the magic command #%% in your regular .py file.
       • ctrl+enter to execute and stay at current block.
       • shift+enter to execute and move to next block.
   • Alternative editor I very like is sublime text 4 

C1.2. Outline

1. Numerical simulation essentials
   • Euler method (ode1)
   • Runge Kutta method (ode4)
   • Learn concept of a variable step size solver
   • Solve for some example systems
2. Numba accelerated simulation
3. Separation between simulation framework and motor dynamics

C1.3. My Python Tutorials

Donwload jupyter notebook .ipynb file here. .

C1.?. Learn Python in one video by Derek Banas (N4mEzFDjqtA)

(need access to Youtube)

C1.?. Quiz