Hi, welcome to my personal blog. Hope you could find useful python tricks. Feel free to exchange your valuable ideas with me. I am looking forward to your insightful opinion.
First look at the following code: import time # create Font object text_font = pygame . font . SysFont( 'arial' , 50 ) # create a list that stores two pos that going to compare to each other pos_to_compare_list = [] # create a list that stores all the pos that matched pos_matched = [] # set backgroud color to white while True : for event in pygame . event . get(): if event . type == QUIT: pygame . quit() sys . exit() elif event . type == MOUSEBUTTONDOWN: (x,y) = pygame . mouse . get_pos() pos = check_click(x,y, square_pos) if pos: text_surface = text_font . render(board[pos[ 0 ]][pos[ 1 ]], True , WHITE) if len (pos_to_compare_list) < 2 : if pos not in pos_to_compare_list: pos_to_compare_list . append(pos) ...
The “Big-Oh” Notation If f(n) and g(n) are two functions that map positive integers to positive real numbers. We could say that f(n) is O(g(n)) if there is a real constant c > 0 and an integer constant n 0 > 1 that: f(n) ≤ cg(n), for n > n 0 The f(n) is O(g(n)) is usually read as “ f(n) is big-Oh of g(n) ”. The following graph illustrates the “ Big-Oh ” notation. Example 1.1 Justify the function f(n) = 5n + 3 is O(n) Answer: By the definition of “ Big-Oh ” notation, there must exist a constant c > 0 such that: f(n) ≤ cg(n) or 5n + 3 ≤ cn for all n > n 0 5n + 3 ≤ (5 + 3)n = 8n and n 0 = 1 , so 5n + 3 is O(n) Example 1.2 Justify 5n 2 + 2nlogn + 3n + 6 is O(n 2 ) ( logn ≤ n for n ≥ 1 , base 2 ) Answer: 5n 2 + 2nlogn + 3n + 6 ≤ (5 + 2 + 3 + 6)n 2 = 16n 2 for c = 16 , when n ≥ n 0 = 1 Example 1.3 Justify 2logn + 2 is O(...
Introduction This is the first course of the "Data Structure and Algorithms in Python" series. Before we go deeper on this topic, I would like to introduce the most important math tool that we are gonna use through out this topic " Aysmpotic Analysis ". What is asymptotic analysis? In mathematics, asymptotic analysis, also known as asymptotics, is a method of describing limiting behaviors. For instance, if we are insterested in the properties of function f(n) as n becomes very large. If f(n) = n 2 + 4n + 3 , as n goes to infinity ( ∞ ), the term 4n and constant 3 becomes insignificant compared to n 2 . And we can say that “ f(n) is asymptotically equivalent to n 2 , as n → ∞ ” . This is often written as f(n)~n 2 , which read as “ f(n) is asymptotic to n 2 ” .
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