48 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
		
		
			
		
	
	
			48 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
|   | --- | ||
|  | title: Big Theta Notation | ||
|  | --- | ||
|  | ## Big Theta Notation
 | ||
|  | 
 | ||
|  | Big Omega tells us the lower bound of the runtime of a function, and Big O tells us the upper bound. Often times, they are different and we can't put a guarantee on the runtime - it will vary between the two bounds and the inputs. But what happens when they're the same? Then we can give a **theta** (Θ) bound - our function will run in that time, no matter what input we give it. In general, we always want to give a theta bound if possible because it is the most accurate and tightest bound. If we can't give a theta bound, the next best thing is the tightest O bound possible.  | ||
|  | 
 | ||
|  | 
 | ||
|  | Take, for example, a function that searches an array for the value 0: | ||
|  | ```python | ||
|  | def containsZero(arr): #assume normal array of length n with no edge cases | ||
|  |   for num x in arr: | ||
|  |     if x == 0: | ||
|  |        return true | ||
|  |   return false | ||
|  | ``` | ||
|  | 
 | ||
|  | 1. What's the best case? Well, if the array we give it has 0 as the first value, it will take constant time: Ω (1) | ||
|  | 2. What's the worst case? If the array doesn't contain 0, we will have iterated through the whole array: O(n) | ||
|  | 
 | ||
|  | We've given it an omega and O bound, so what about theta? We can't give it one! Depending on the array we give it, the runtime will be somewhere in between constant and linear.  | ||
|  | 
 | ||
|  | Let's change our code a bit. | ||
|  | ```python | ||
|  | def printNums(arr): #assume normal array of length n with no edge cases | ||
|  |   for num x in arr: | ||
|  |     print(x) | ||
|  | ``` | ||
|  | Can you think of a best case and worst case?? | ||
|  | I can't! No matter what array we give it, we have to iterate through every value in the array. So the function will take AT LEAST n time (Ω(n)), but we also know it won't take any longer than n time (O(n)). What does this mean? Our function will take **exactly** n time: Θ(n). | ||
|  | 
 | ||
|  | If the bounds are confusing, think about it like this. We have 2 numbers, x and y. We are given that x <= y and that y <= x. If x is less than or equal to y, and y is less than or equal to x, then x has to equal y! | ||
|  | 
 | ||
|  | If you're familiar with linked lists, test yourself and think about the runtimes for each of these functions! | ||
|  | 1. get | ||
|  | 2. remove | ||
|  | 3. add  | ||
|  | 
 | ||
|  | Things get even more interesting when you consider a doubly linked list! | ||
|  | <!-- The article goes here, in GitHub-flavored Markdown. Feel free to add YouTube videos, images, and CodePen/JSBin embeds  --> | ||
|  | 
 | ||
|  | #### More Information:
 | ||
|  | <!-- Please add any articles you think might be helpful to read before writing the article --> | ||
|  | https://www.khanacademy.org/computing/computer-science/algorithms/asymptotic-notation/a/big-big-theta-notation | ||
|  | https://stackoverflow.com/questions/10376740/what-exactly-does-big-%D3%A8-notation-represent | ||
|  | https://www.geeksforgeeks.org/analysis-of-algorithms-set-3asymptotic-notations/ | ||
|  | 
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