C1. Python Basics

15 min

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